Run trace — Tue 3 Nov

{
  "query": "select:WebFetch,WebSearch",
  "max_results": 5
}

{
  "matches": [
    "WebFetch",
    "WebSearch"
  ],
  "query": "select:WebFetch,WebSearch",
  "total_deferred_tools": 92
}

{
  "query": "select:WebSearch,WebFetch",
  "max_results": 5
}

{
  "matches": [
    "WebSearch",
    "WebFetch"
  ],
  "query": "select:WebSearch,WebFetch",
  "total_deferred_tools": 92
}

{
  "query": "select:WebFetch,WebSearch",
  "max_results": 5
}

{
  "matches": [
    "WebFetch",
    "WebSearch"
  ],
  "query": "select:WebFetch,WebSearch",
  "total_deferred_tools": 92
}

{
  "query": "select:WebSearch,WebFetch",
  "max_results": 5
}

{
  "matches": [
    "WebSearch",
    "WebFetch"
  ],
  "query": "select:WebSearch,WebFetch",
  "total_deferred_tools": 92
}

{
  "command": "ls && ls scripts/ 2>/dev/null",
  "description": "List project files"
}

{
  "stdout": "LICENSE\nLICENSE-EDITIONS.md\nPROMPT-WEEK.md\nPROMPT.md\nREADME.md\nSOURCES.md\ndata\ndocs\nscripts\nstorylines\ntrace\nworker\nbuild.js\nburn.js\ncover.js\ndns.js\nfetch.js\nindexnow.js\nlib.js\nmail.js\nmigrate-r2.js\nnarrate.js\nplayer.js\npodcast.js\nr2.js\nrasterize.sh\nsocial.js\nspotify.js\nstats.js\ntrace-hook.js\nvalidate-host-script.js\nvalidate-lib.js\nvalidate-script.js\nvalidate-storyline.js\nvalidate-week.js\nvalidate.js\nverify-audio.js\nvoices.js\nweekly-audio.js\nyoutube.js",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "command": "ls && ls scripts/ 2>/dev/null",
  "description": "List project files"
}

{
  "stdout": "LICENSE\nLICENSE-EDITIONS.md\nPROMPT-WEEK.md\nPROMPT.md\nREADME.md\nSOURCES.md\ndata\ndocs\nscripts\nstorylines\ntrace\nworker\nbuild.js\nburn.js\ncover.js\ndns.js\nfetch.js\nindexnow.js\nlib.js\nmail.js\nmigrate-r2.js\nnarrate.js\nplayer.js\npodcast.js\nr2.js\nrasterize.sh\nsocial.js\nspotify.js\nstats.js\ntrace-hook.js\nvalidate-host-script.js\nvalidate-lib.js\nvalidate-script.js\nvalidate-storyline.js\nvalidate-week.js\nvalidate.js\nverify-audio.js\nvoices.js\nweekly-audio.js\nyoutube.js",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "ls && ls scripts/ && date -u",
  "description": "List project files and show UTC date"
}

{
  "stdout": "LICENSE\nLICENSE-EDITIONS.md\nPROMPT-WEEK.md\nPROMPT.md\nREADME.md\nSOURCES.md\ndata\ndocs\nscripts\nstorylines\ntrace\nworker\nbuild.js\nburn.js\ncover.js\ndns.js\nfetch.js\nindexnow.js\nlib.js\nmail.js\nmigrate-r2.js\nnarrate.js\nplayer.js\npodcast.js\nr2.js\nrasterize.sh\nsocial.js\nspotify.js\nstats.js\ntrace-hook.js\nvalidate-host-script.js\nvalidate-lib.js\nvalidate-script.js\nvalidate-storyline.js\nvalidate-week.js\nvalidate.js\nverify-audio.js\nvoices.js\nweekly-audio.js\nyoutube.js\nTue Nov  3 11:07:49 UTC 2026",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "command": "ls && ls scripts/ 2>/dev/null",
  "description": "List project files"
}

{
  "stdout": "LICENSE\nLICENSE-EDITIONS.md\nPROMPT-WEEK.md\nPROMPT.md\nREADME.md\nSOURCES.md\ndata\ndocs\nscripts\nstorylines\ntrace\nworker\nbuild.js\nburn.js\ncover.js\ndns.js\nfetch.js\nindexnow.js\nlib.js\nmail.js\nmigrate-r2.js\nnarrate.js\nplayer.js\npodcast.js\nr2.js\nrasterize.sh\nsocial.js\nspotify.js\nstats.js\ntrace-hook.js\nvalidate-host-script.js\nvalidate-lib.js\nvalidate-script.js\nvalidate-storyline.js\nvalidate-week.js\nvalidate.js\nverify-audio.js\nvoices.js\nweekly-audio.js\nyoutube.js",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "node scripts/fetch.js https://huggingface.co/papers 2>&1 | head -200",
  "description": "Fetch HuggingFace papers page"
}

{
  "stdout": "HTTP 200 · https://huggingface.co/papers · text/html\nDaily Papers - Hugging Face\n\nnew\nGet trending papers in your email inbox once a day!\nGet trending papers in your email inbox!\nSubscribe\n\n# Daily Papers\n\n# by AK and the research community\n\n- Daily\n\n- Weekly\n\n- Monthly\n\nNov 3\n\nSubmitted by\nDrewJin0827\n80\n\n# Wave Forcing: Towards Speed-of-Light Streaming Video Generation\nDENG Lab @ SJTU 68 3\n\nSubmitted by\nneversa\n58\n\n# Video Generation Meets Agent Harness: Agentic Video Generation, Agentic World Modeling and Recursive Self-Improvement\nVideo Rebirth 30 1\n\nSubmitted by\ndongguanting\n57\n\n# CoworkOS:Scaling Agent Coworkers for Real-world Automation\nRenmin University of China 46 2\n\nSubmitted by\nyuxinzuo\n35\n\n# Democratizing Robot-Use Agents: A Unified Harness with Open Models\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- ·\n28 authors\n\n7 1\n\nSubmitted by\nyxl66666\n34\n\n# CUA-Master: Scaling Computer-use Agents through Open-World Recursive Improvements\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- ·\n18 authors\n\n44 1\n\nSubmitted by\nvyokky\n25\n\n# NorthCUA Technical Report: Turbocharging Computer-Use Agents through Experience at Scale\nbeipo-ai 14 1\n\nSubmitted by\nbangpro\n24\n\n# Lost in Recovery: Demystifying Recovery Behavior of Computer-Use Agents via Goal-Oriented Action Replay\nKAIST AI 3 1\n\nSubmitted by\nzzzhu\n23\n\n# Reviso: Not All Visual Evidence Deserves Equal Attention in Video Captioning\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- ·\n15 authors\n\n2\n\nSubmitted by\nGeralt-Targaryen\n20\n\n# From Fragmentation to Fusion: A Survey and Roadmap for Omnimodal Embeddings\nCodeFuse AI 19 1\n\nSubmitted by\nSilin-Chen\n19\n\n# CrossSWE: Benchmarking Cross-Repository Joint Development for Coding Agents\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- ·\n7 authors\n\n1\n\nSubmitted by\nNeilLeeNTU\n17\n\n# PhotoGuider: Composition-Aware Cropping and 360^{circ} View Framing with Explainable Photographic Assessments\n\n-\n\n-\n\n-\n\n-\n\n- ·\n4 authors\n\n18 1\n\nSubmitted by\nwuuuuuz\n15\n\n# Avatar Intelligence: Amplifying Human Agency Through Persistent Personal Agents\nShanghai Jiao Tong University 1\n\nSubmitted by\nkenchan0226\n14\n\n# Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- ·\n5 authors\n\n1 2\n\nSubmitted by\nyudian\n9\n\n# DecisionRank: On-Policy Distillation for Decision-Model Rerankers\nMeta 1",
  "stderr": "",
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{
  "query": "AI clinical trial results November 2 2026",
  "mode": "extended"
}

{
  "query": "AI clinical trial results November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01ABbfy14r91V4oj9qnMatNp",
      "content": [
        {
          "title": "The Clinical Trial Pipeline Reveals the Next Wave of Artificial Intelligence in Healthcare: A Multidimensional Analysis of 8,532 Registered Studies",
          "url": "https://arxiv.org/pdf/2607.22607"
        },
        {
          "title": "Health AI Insights for the Week of November 2, 2026",
          "url": "https://healthaiinsights.substack.com/p/health-ai-insights-for-the-week-of-4e9"
        },
        {
          "title": "NEJM AI",
          "url": "https://ai.nejm.org/"
        },
        {
          "title": "AI-Discovered Drugs in Clinical Trials 2026: Full Pipeline",
          "url": "https://intuitionlabs.ai/articles/ai-discovered-drugs-clinical-trials-2026"
        },
        {
          "title": "Applied Clinical Trials Online",
          "url": "https://www.appliedclinicaltrialsonline.com/"
        },
        {
          "title": "Annual AI in Clinical Trials Report",
          "url": "https://www.medidata.com/en/ai-report-2nd-edition/"
        },
        {
          "title": "Beyond the Growth: A Registry-Based Analysis of Global Imbalances in Artificial Intelligence Clinical Trials",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12385212/"
        },
        {
          "title": "Trends in AI and Human-AI Interaction in Clinical Trials -- A Hybrid Human-AI Exploration",
          "url": "https://arxiv.org/pdf/2605.29096"
        },
        {
          "title": "AI Drug Discovery FDA Approvals: The 2026 Reality Check",
          "url": "https://intuitionlabs.ai/articles/ai-drug-discovery-fda-approvals"
        },
        {
          "title": "Randomized Controlled Trials Evaluating AI in Clinical Practice: A Scoping Evaluation",
          "url": "https://www.medrxiv.org/content/10.1101/2023.09.12.23295381.full.pdf"
        }
      ]
    },
    "The search didn't turn up a headline AI clinical trial result dated November 2, 2026, but a few items touch on it.\n\n- **NEJM AI listing:** Its November 2026 issue includes an original article, a randomized clinical trial on automation bias in LLM-assisted diagnosis among physicians trained in AI literacy. The listing shows a November 2, 2026 date, and a published letter says the trial found a significant drop in diagnostic accuracy. Automation Bias in Large Language Model–Assisted Diagnostic Reasoning among Physicians Trained in AI Literacy — A Randomized Clinical Trial is the relevant title. This is the closest match to your date.\n- **Health AI newsletter:** A Substack weekly digest is dated for the week of November 2, 2026, but the snippet only lists its topics (admin AI, responsible AI, results validation) and gives no trial data.\n- **Applied Clinical Trials Online:** Its news feed has items dated November 2, 2026, including a feature on why faster trial data isn't producing faster decisions. These are commentary pieces, not new results.\n- **AI-discovered drugs:** Not dated to November 2, but relevant context. Insilico's rentosertib showed a mean forced vital capacity improvement of +98.4 mL at 12 weeks in the 60 mg once-daily arm of its Phase IIa trial.\n\nFor a specific result from that day, I'd check the NEJM AI article page directly or a trial registry, since the snippets here don't include the full findings."
  ],
  "durationSeconds": 6.553461257999996,
  "searchCount": 1
}

{
  "query": "AI-enabled cyberattack malware LLM November 3 2026",
  "mode": "extended"
}

{
  "query": "AI-enabled cyberattack malware LLM November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01EnVbVLzRxoMU4Nudt66Sj4",
      "content": [
        {
          "title": "When LLMs Meet Cybersecurity: A Systematic Literature Review",
          "url": "https://arxiv.org/pdf/2405.03644"
        },
        {
          "title": "AI-Enabled Malware Now Actively Deployed, Says Google - Infosecurity Magazine",
          "url": "https://www.infosecurity-magazine.com/news/aienabled-malware-actively/"
        },
        {
          "title": "AI-based malware makes attacks stealthier and more adaptive",
          "url": "https://www.cybersecuritydive.com/news/ai-powered-malware-google/804760/"
        },
        {
          "title": "Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks",
          "url": "https://arxiv.org/pdf/2505.12786"
        },
        {
          "title": "The Rise of AI-Driven Cyber Attacks: How LLMs Are Reshaping the Threat Landscape",
          "url": "https://www.deepinstinct.com/blog/the-rise-of-ai-driven-cyber-attacks-how-llms-are-reshaping-the-threat-landscape"
        },
        {
          "title": "LLM-Enabled Malware In the Wild",
          "url": "https://www.startupdefense.io/blog/llm-enabled-malware-in-the-wild"
        },
        {
          "title": "How AI-Driven Cyberattacks Are Changing the Threat Landscape in 2026",
          "url": "https://northwave-cybersecurity.com/articles/how-ai-driven-cyber-attacks-are-changing-the-threat-landscape-in-2026"
        },
        {
          "title": "Trustworthy AI LLM Scalability Risk Index (LSRI): A Cybersecurity Framework Assessing Agentic-AI Security & Software Model Supply Chain Safety Boosting AI-Generated Malware Defense & Explainability Mitigating Emerging Risks of Generative AI",
          "url": "https://arxiv.org/pdf/2602.19021"
        },
        {
          "title": "CyberSOCEval: Benchmarking LLMs Capabilities for Malware Analysis and Threat Intelligence Reasoning",
          "url": "https://arxiv.org/pdf/2509.20166"
        }
      ]
    },
    "The search didn't turn up anything dated today (November 3, 2026), so this is the latest material I found, not a same-day report.\n\n- **Google's \"just-in-time\" AI malware:** Google's threat intelligence group reported malware families, including PromptFlux and PromptSteal, that call an LLM during execution to generate malicious code and evade detection. The coverage is roughly five weeks old. Google's earlier report (about a year old) described five families and said it was the first time it had seen malware querying an LLM in the wild.\n- **Other examples:** Reporting on LAMEHUG describes malware that uses live LLM interactions to generate system commands on-demand. Villager adds LLM automation on top of Cobalt Strike, and HexStrike AI is described as a tool for running complete attack chains.\n- **Skeptical view:** One analysis argues that LLM-enabled malware is real, but it's still forming, more experimental than dominant. Another says AI-generated malware is currently more detectable than many fear.\n- **Academic framing:** Surveys describe LLM agents automating malware generation and multi-stage attacks, with one noting that multi-stage attacks require minimal oversight.\n\nFor current news from today, I'd suggest searching again with specific vendor or agency names."
  ],
  "durationSeconds": 6.341934723999992,
  "searchCount": 1
}

{
  "query": "AI threat intelligence report November 2 2026",
  "mode": "extended"
}

{
  "query": "AI threat intelligence report November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01E2oz9qwdypi6kmNMLJu6fs",
      "content": [
        {
          "title": "2nd November",
          "url": "https://research.checkpoint.com/2026/2nd-november-threat-intelligence-report/"
        },
        {
          "title": "UK Cybersecurity Agency Warns AI Could Accelerate Ransomware Attacks on Critical Infrastructure",
          "url": "https://cybersecuritynews.com/ai-could-accelerate-ransomware"
        },
        {
          "title": "Unit 42 Threat Intelligence Highlights - Nov. 2, 2026",
          "url": "https://origin-unit42.paloaltonetworks.com/u42-threat-intelligence-highlights-oct-2026/"
        },
        {
          "title": "Microsoft's AI Risk Report Misses Key Detail",
          "url": "https://www.darkreading.com/cyberattacks-data-breaches/microsoft-ai-cyber-risk-report-miss"
        },
        {
          "title": "Fortinet 2026 Global Threat Landscape Report",
          "url": "https://www.fortinet.com/resources/reports/threat-landscape-report"
        },
        {
          "title": "Cyber chief: UK facing AI-powered attacks on critical infrastructure within two years",
          "url": "https://ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years"
        },
        {
          "title": "Unit 42 Threat Intelligence Highlights · Nov. 2, 2026",
          "url": "https://radar.offseq.com/threat/unit-42-threat-intelligence-highlights-nov-2-2026-83565ee8e6389b8f"
        },
        {
          "title": "Today in Cyber Security –",
          "url": "https://www.xloggs.com/2026/11/01/weekly-threat-report-2026-11-02/"
        },
        {
          "title": "November 2026 Cyberattacks: Full List by Type",
          "url": "https://explainx.ai/blog/november-2026-cyberattacks-list-breaches-exploits-ai-run-attacks-tracker-2026"
        }
      ]
    },
    "The search returned several threat intelligence publications dated November 2 and 3, 2026, with AI as a common theme.\n\n- **Check Point (Nov. 2 weekly report):** It describes the GOLD OGRE ransomware group using AI agents during Aur0ra attacks, with AI tools handling reconnaissance and lateral movement. It also notes growing AI use by North Korean threat actors and a Cisco Catalyst SD-WAN exploit tied to the KeyDrift malware (1-4, 1-5, 1-7).\n- **Unit 42 (Nov. 2 highlights):** It covers cyberespionage, financial extortion, and generative AI use in offensive workflows (3-3). A secondary summary says actors use LLMs to scale social engineering, payload development, and deepfake-based impersonation (7-6).\n- **UK NCSC (Nov. 3 Annual Review):** The agency reports AI is making attacks faster and cheaper, and it warns of AI-powered ransomware against critical infrastructure by 2028 (6-2). Coverage notes the review records 1,831 attack reports (2-3).\n- **Microsoft 2026 Digital Defense Report (Nov. 2):** Dark Reading argues the report overlooks legacy software as a major source of risk (4-7).\n- **Fortinet 2026 Global Threat Landscape Report:** It finds AI and automation are shrinking time-to-exploit from days to hours (5-2). The source is undated in the results, so treat it as a general report rather than a Nov. 2 item.\n\nTwo items are weaker. An unverified social-media claim about OpenAI scanning agents appears in a tracker, and the tracker itself labels it unconfirmed (9-8). Several arXiv papers on prompt injection and AI-agent security were also listed in a Nov. 2 digest (8-4)."
  ],
  "durationSeconds": 7.151456365999999,
  "searchCount": 1
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{
  "query": "deepfake fraud scam arrest November 2026",
  "mode": "extended"
}

{
  "query": "deepfake fraud scam arrest November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01GKRCCMvZ3XHrWrbPmmAkB8",
      "content": [
        {
          "title": "For scammers, the deepfake is now a working tool",
          "url": "https://www.manilatimes.net/2026/10/18/business/sunday-business-it/for-scammers-the-deepfake-is-now-a-working-tool/2447912"
        },
        {
          "title": "AI Deepfake Scam 2026: Rajasthan Man Arrested For Impersonating Tamil Nadu CM In Viral Video Fraud - Careerindia",
          "url": "https://www.careerindia.com/news/ai-deepfake-scam-2026-rajasthan-man-arrested-for-impersonating-tamil-nadu-cm-viral-video-fraud-011-65693.html"
        },
        {
          "title": "Verified: Video Of Ex-Army Commander On China Incursion Is A Deepfake",
          "url": "https://newsmobile.in/nm-fact-checker/verified-viral-video-of-ex-army-commander-on-china-incursion-is-a-deepfake"
        },
        {
          "title": "Innefu AI Flags ₹5,700 Crore Suspected GST Fraud",
          "url": "https://cio.eletsonline.com/artificial-intelligence/innefu-ai-gst-fraud/76692"
        },
        {
          "title": "Seven Arrested in Cyber Fraud Scam Impersonating Police and NIA Officials",
          "url": "https://www.news4hackers.com/seven-arrested-in-cyber-fraud-scam-impersonating-police-and-nia-officials"
        },
        {
          "title": "Influencer who flaunted private jets indicted over alleged $4 million food stamp fraud scheme - Dexerto",
          "url": "https://dexerto.com/entertainment/influencer-who-flaunted-private-jets-indicted-over-alleged-4-million-food-stamp-fraud-scheme-3423763"
        },
        {
          "title": "Seven Arrested in Cyber Fraud Scandal: Fake Police and NIA Officials Impersonated",
          "url": "https://www.news4hackers.com/seven-arrested-in-cyber-fraud-scandal-fake-police-and-nia-officials-impersonated"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/fraud/cybersecurity/fbi"
        },
        {
          "title": "Newsletter Newsletters Events Events Podcasts Videos Africanews",
          "url": "https://euronews.com/2026/02/23/how-deepfake-scams-are-reaching-record-levels-by-targeting-social-media-users"
        }
      ]
    },
    "I found no arrest tied specifically to deepfakes in November 2026, but a few recent cases came close.\n\n- **Closest match:** On November 1, 2026, a report said seven people were detained in cybercrime cases involving impersonation of police and intelligence officers. One case involved the deployment of artificial intelligence to generate synthetic voice and visual identities.\n- **Earlier deepfake arrest (India):** Tamil Nadu police arrested a Rajasthan man over fake videos of the state's chief minister promising cash aid. The arrest was in Alwar on September 12, so it is not from November.\n- **Background:** A Philippine report described a dentist who was defrauded of about P93 million after a deepfake of the president endorsing an investment. Police arrested two suspects in October 2025 ([Manila Times, Oct. 2026](https://www.manilatimes.net/2026/10/18/business/sunday-business-it/for-scammers-the-deepfake-is-now-a-working-tool/2447912)).\n- **Scale:** One study estimated that deepfake-related scam and fraud schemes tricked people out of approximately $1.1 billion worldwide in 2025.\n\nThe other results were not deepfake arrests. They covered a Lucknow telecom bust tied to digital arrest scams and a U.S. influencer indicted for a food-stamp fraud, so I left them out."
  ],
  "durationSeconds": 6.243973771000019,
  "searchCount": 1
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{
  "query": "FDA AI-enabled medical device clearance November 2026",
  "mode": "extended"
}

{
  "query": "FDA AI-enabled medical device clearance November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01RRKudRHBJPsKraiokR399D",
      "content": [
        {
          "title": "AI Medical Devices Market Overview and Recalls",
          "url": "https://paragoninstitute.org/ai-tools/ai-medical-devices/"
        },
        {
          "title": "First FDA-Cleared AI Agent and LLM Enabled Device Confirmed",
          "url": "https://innolitics.com/articles/updoc-fda-cleared-ai-agent/"
        },
        {
          "title": "FDA-Approved AI Medical Devices List: Complete 2026 Guide",
          "url": "https://intuitionlabs.ai/articles/fda-approved-ai-medical-devices-list"
        },
        {
          "title": "Trends in Clinical Validation and Usage of Food and Drug Administration (FDA)-Cleared Artificial Intelligence (AI) Algorithms for Medical Imaging",
          "url": "https://www.medrxiv.org/content/10.1101/2022.06.19.22276350.full.pdf"
        },
        {
          "title": "AI Innovation and Firm Performance in the Medical Device Industry",
          "url": "https://arxiv.org/pdf/2609.08485"
        },
        {
          "title": "FDA Rules for Marketing AI Medical Devices: A Claims Guide",
          "url": "https://everything-pr.com/fda-ai-medical-device-marketing"
        },
        {
          "title": "96% of FDA-Cleared AI Devices Used 510(k): What the Data Shows",
          "url": "https://sequenex.com/fda-ai-medical-device-authorizations-analysis/"
        },
        {
          "title": "FDA Has Cleared 1,614 AI Medical Devices. 96% Took the Same Path.",
          "url": "https://www.complizen.ai/post/fda-has-cleared-1614-ai-medical-devices"
        },
        {
          "title": "Medical Devices FDA Guide 2026: Pathways, QMSR & AI Rules",
          "url": "https://adiamed.com/medical-devices-fda-guide-2026/"
        },
        {
          "title": "FDA AI-Enabled Medical Device Clearances: Data and Trends",
          "url": "https://www.innometrique.com/fda-ai-enabled-device-clearances.html"
        }
      ]
    },
    "I found no FDA AI-enabled device clearances dated November 2026. The newest data in these results runs only through late June 2026, so the list may not yet reflect anything from November.\n\n- **Latest list:** The FDA list was updated September 4, 2026, to 1,614 entries, with decisions through June 29, 2026. One analysis says the file was retrieved October 15, 2026, and it still shows the same June cutoff.\n- **Pace:** One tally counts 181 AI-enabled devices authorized in 2026 through June 29, against 173 in the same period of 2025.\n- **Pathway:** Most are 510(k) clearances. One analysis puts that at 1,553 of 1,614, or 96 percent, and radiology accounts for about 76% of all AI-enabled device authorizations.\n- **Caveat:** FDA says the list is \"not a comprehensive resource of AI-enabled medical devices.\"\n- **Notable item:** A June 2026 announcement from UpDoc described an FDA-cleared clinical AI platform. Analysts are not yet clear if this press release is talking about the same device or a new one, so treat that claim cautiously.\n\nFor November 2026 specifically, check FDA's AI-Enabled Medical Device List directly, since these secondary sources are all third-party analyses of the same list."
  ],
  "durationSeconds": 8.14982467500001,
  "searchCount": 1
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{
  "query": "Pentagon AI contract award November 2026",
  "mode": "extended"
}

{
  "query": "Pentagon AI contract award November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01X3jXpgNJJp5GJsBKLbsNUT",
      "content": [
        {
          "title": "Pentagon awards Scale AI $500 million military AI contract - CXO Digitalpulse",
          "url": "https://www.cxodigitalpulse.com/pentagon-awards-scale-ai-500-million-military-ai-contract/"
        },
        {
          "title": "Pentagon awards $318M contract for Dataminr alerting services technology",
          "url": "https://defensescoop.com/2026/08/27/pentagon-awards-dataminr-318m-contract/"
        },
        {
          "title": "Accenture wins $821M Pentagon AI data platform contract - Federal News Network",
          "url": "https://federalnewsnetwork.com/defense-news/2026/07/accenture-wins-821m-pentagon-ai-data-platform-contract/"
        },
        {
          "title": "Pentagon awards Scale AI $500M contract to expand military AI",
          "url": "https://en.yenisafak.com/world/pentagon-awards-scale-ai-500m-contract-to-expand-military-ai-3717977"
        },
        {
          "title": "Pentagon Awards $9M for AI-Written Code + What Comes Next",
          "url": "https://www.rosefinancial.com/the-pentagon-just-awarded-9-million-for-ai-written-code-is-this-the-future-of-defense-contracting"
        },
        {
          "title": "Shield AI",
          "url": "https://en.wikipedia.org/wiki/Shield_AI"
        },
        {
          "title": "U.S. military reaches deals with 7 companies to use AI on classified systems - The Watch",
          "url": "https://thewatch-journal.com/2026/06/02/u-s-military-reaches-deals-with-7-companies-to-use-ai-on-classified-systems/"
        },
        {
          "title": "Pentagon Awards $400M to Raytheon Despite Fraud Admissions (2026)",
          "url": "https://neopetscheats.org/article/pentagon-awards-400m-to-raytheon-despite-fraud-admissions"
        },
        {
          "title": "Pentagon's $400M Deal with Fraudulent Firm Raises Questions (2026)",
          "url": "https://playmgreatspot.com/article/pentagon-s-400m-deal-with-fraudulent-firm-raises-questions"
        },
        {
          "title": "Pentagon Hands Meta-Backed Scale AI $500 Million Contract, 5 Times Last Year's Deal",
          "url": "https://www.forbes.com/sites/aliciapark/2026/05/06/pentagon-hands-meta-backed-scale-ai-500-million-contract-5-times-last-years-deal-report-says/"
        }
      ]
    },
    "I didn't find any Pentagon AI contract award dated November 2026. The most recent AI-related award in the results is from late August 2026, so this may be a gap in coverage rather than a confirmed absence of news.\n\n- **Dataminr, late August 2026:** Dataminr won a $318 million contract from the Defense Department for AI-powered situational awareness technology to support the A2 Publicly Available Information Alerting program. The Air Force issued it, and eight offers were received in a competitive process.\n- **Accenture, July 2026:** Accenture Federal Services received a contract worth up to $821 million over five years to build core software for the Pentagon's War Data Platform, which feeds its AI tools.\n- **Scale AI, May 2026:** The Pentagon awarded Scale AI a $500 million contract through its Chief Digital and Artificial Intelligence Office. That is a fivefold increase from the $100 million deal the startup signed in September 2025.\n- **Classified-network deals, May 2026:** The Pentagon said in May 2026 that it has reached deals with seven tech companies to use their artificial intelligence in its classified computer networks.\n\nTwo results dated \"0 days ago\" concerned a $400 million Raytheon contract extension, not AI, so I left them out. Several of the sources are also secondary or low-quality, so I'd verify any figures against official DoD announcements before relying on them."
  ],
  "durationSeconds": 6.138361098000023,
  "searchCount": 1
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{
  "url": "https://ai.nejm.org/",
  "prompt": "List all articles with publication dates of November 2 or November 3, 2026, with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 422,
  "url": "https://ai.nejm.org/"
}

{
  "url": "https://ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years",
  "prompt": "Full text: publication date, all numbers (attack reports, nationally significant incidents), AI claims, who said what. Quote figures exactly."
}

{
  "bytes": 851,
  "code": 301,
  "codeText": "Moved Permanently",
  "result": "REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.\n\n    Original URL: https://ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years\n    Redirect URL (from the server's Location header — server-supplied, not verified): http://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years\n    Status: 301 Moved Permanently\n\n    To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:\n    - url: \"http://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years\"\n    - prompt: \"Full text: publication date, all numbers (attack reports, nationally significant incidents), AI claims, who said what. Quote figures exactly.\"",
  "durationMs": 439,
  "url": "https://ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years"
}

{
  "url": "https://www.anthropic.com/news",
  "prompt": "List all news items with titles, dates and links."
}

{
  "bytes": 348795,
  "code": 200,
  "codeText": "OK",
  "result": "The page lists 24 articles under \"All news\" (of 283 total, with more available via \"See more\"), plus four featured stories and one item in the top section. Links are relative paths on the Anthropic newsroom.\n\n**All news (newest first)**\n\n| Date | Title | Link |\n|---|---|---|\n| Oct 28, 2026 | \"AI for Science expands to foundations and research institutions\" | /news/ai-for-science-expands-foundations-research-institutions |\n| Oct 27, 2026 | \"Early progress on accelerating drug development with Claude\" | /research/early-progress-drug-development |\n| Oct 27, 2026 | \"Expanding our partnership with GSA to bring Claude to all levels of government\" | /news/expanding-partnership-gsa |\n| Oct 26, 2026 | \"Anthropic files S-1 with the SEC for proposed initial public offering\" | /news/s1-sec |\n| Oct 22, 2026 | \"Donating Agent Skills to the Agentic AI Foundation\" | /news/donating-agent-skills-to-the-agentic-ai-foundation |\n| Oct 22, 2026 | \"Open call for guest investigators in the life sciences\" | /news/open-call-guest-investigators-life-sciences |\n| Oct 21, 2026 | \"Physicist Christopher Stubbs joins Anthropic's Long-Term Benefit Trust\" | /news/christopher-stubbs-joins-long-term-benefit-trust |\n| Oct 18, 2026 | \"Investing in the public benefit\" | /news/public-benefit-fund |\n| Oct 15, 2026 | \"An update on independent evaluators\" | /news/an-update-on-independent-evaluators |\n| Oct 14, 2026 | \"Preparing for the 2026 US midterms\" | /news/2026-us-midterms |\n| Oct 14, 2026 | \"Anthropic opens Singapore office and signs MOU with the Government of Singapore\" | /news/singapore-office-opening |\n| Oct 12, 2026 | \"Strengthening our defenses against distillation attacks\" | /news/distillation-defenses |\n| Oct 8, 2026 | \"Introducing the Anthropic Cyber Mission\" | /news/anthropic-cyber-mission |\n| Oct 8, 2026 | \"2026 Usage Policy update\" | /news/2026-usage-policy-update |\n| Oct 8, 2026 | \"Building on our commitment to American scientific discovery\" | /news/genesis-mission-commitment |\n| Oct 7, 2026 | \"Introducing Claude Haiku 5.5\" | /claude-haiku-5-5 |\n| Oct 6, 2026 | \"Expanding the Cyber Verification Program\" | /news/cyber-verification-program |\n| Oct 2, 2026 | \"Anthropic invests $100 million to train 10,000 engineers and tackle the enterprise AI talent gap\" | /news/claude-frontier-academy |\n| Oct 1, 2026 | \"Barclays scales Claude to upgrade operations and improve client experience\" | /news/barclays-scales-claude |\n| Sep 28, 2026 | \"Introducing Claude Sonnet 5.5\" | /claude-sonnet-5-5 |\n| Sep 22, 2026 | \"Introducing Claude Opus 5.5\" | /claude-opus-5-5 |\n| Sep 21, 2026 | \"The Situation Report\" | /features/ebola-response |\n| Sep 18, 2026 | \"Partnering with Accenture on embedded evaluation\" | /news/accenture-embedded-evaluation |\n| Sep 17, 2026 | \"Introducing the Life Sciences Verification Program\" | /news/life-sciences-verification-program |\n\n**Featured items not in the All news list**\n\n| Date | Title | Link |\n|---|---|---|\n| Sep 9, 2026 | \"Scenarios for our economic future\" | /institute/econ-scenarios |\n| Apr 21, 2026 | \"Project Deal: our Claude-run marketplace experiment\" | /features/project-deal |\n| Feb 23, 2026 | \"The making of Claude Code\" | /features/making-of-claude-code |\n| Jan 24, 2026 | \"The first AI-planned drive on Mars\" | /features/claude-on-mars |",
  "durationMs": 11232,
  "url": "https://www.anthropic.com/news"
}

{
  "url": "https://techcrunch.com/category/artificial-intelligence/feed/",
  "prompt": "List all items with titles, links and publication dates/times."
}

{
  "bytes": 18162,
  "code": 200,
  "codeText": "OK",
  "result": "The feed contains 20 items. Times are as listed in the feed (UTC).\n\n| # | Title | Link | Published (UTC) |\n|---|---|---|---|\n| 1 | \"Apple Watch's AI features for rewinding and recapping conversations begin beta testing\" | https://techcrunch.com/2026/11/02/apple-watchs-ai-features-for-rewinding-and-recapping-conversations-begin-beta-testing/ | Tue, 03 Nov 2026 07:20:00 |\n| 2 | \"Google takes Dreambeans to India in bid to bring AI-generated personal stories to the masses\" | https://techcrunch.com/2026/11/02/google-takes-dreambeans-to-india-in-bid-to-bring-ai-generated-personal-stories-to-the-masses/ | Tue, 03 Nov 2026 03:30:00 |\n| 3 | \"Apple may try to increase revenue by doing…something with third-party AI apps\" | https://techcrunch.com/2026/11/02/apple-may-try-to-increase-revenue-by-doing-something-with-third-party-ai-apps/ | Tue, 03 Nov 2026 01:49:52 |\n| 4 | \"Y Combinator's Garry Tan uses AI agents so much, he spends up to $200K a year on tokens\" | https://techcrunch.com/2026/11/02/y-combinators-garry-tan-uses-ai-agents-so-much-he-spends-up-to-200k-a-year-on-tokens/ | Tue, 03 Nov 2026 00:35:52 |\n| 5 | \"Trajectory raises $45M to make AI model training accessible to nontechnical experts\" | https://techcrunch.com/2026/11/02/trajectory-raises-45m-to-make-ai-model-training-accessible-to-nontechnical-experts/ | Mon, 02 Nov 2026 23:13:53 |\n| 6 | \"Anthropic warns that it's very close to RSI capability, aka self-building AI\" | https://techcrunch.com/2026/11/02/anthropic-warns-that-its-very-close-to-rsi-capability-aka-self-building-ai/ | Mon, 02 Nov 2026 22:14:50 |\n| 7 | \"Web host Squarespace lays off 19% of its employees\" | https://techcrunch.com/2026/11/02/web-host-squarespace-lays-off-19-of-its-employees/ | Mon, 02 Nov 2026 19:25:59 |\n| 8 | \"New York Times and other outlets sue web browser Brave over alleged content scraping\" | https://techcrunch.com/2026/11/02/new-york-times-and-other-outlets-sue-web-browser-brave-over-alleged-content-scraping/ | Mon, 02 Nov 2026 19:19:17 |\n| 9 | \"42AI comes out of stealth with $62.5M and a world model that can 'predict human behavior'\" | https://techcrunch.com/2026/11/02/42ai-comes-out-of-stealth-with-62-5m-and-a-world-model-that-can-predict-human-behavior/ | Mon, 02 Nov 2026 16:30:00 |\n| 10 | \"Elon Musk throttles Grok Bot limits due to 'unsustainably high' costs\" | https://techcrunch.com/2026/11/02/elon-musk-throttles-grok-bot-limits-due-to-unsustainably-high-costs/ | Mon, 02 Nov 2026 16:23:21 |\n| 11 | \"Omen AI adds liquid know-how in $16 million Aquatic Labs acquisition\" | https://techcrunch.com/2026/11/02/omen-ai-adds-liquid-know-how-in-16-million-aquatic-labs-acquisition/ | Mon, 02 Nov 2026 15:00:00 |\n| 12 | \"2 days till TechCrunch Founder Summit: Boston founders don't need a Silicon Valley address to build something big\" | https://techcrunch.com/2026/11/02/2-days-till-techcrunch-founder-summit-boston-founders-dont-need-a-silicon-valley-address-to-build-something-big/ | Mon, 02 Nov 2026 14:00:00 |\n| 13 | \"OpenAI is finally merging ChatGPT's Chat and Work tabs\" | https://techcrunch.com/2026/11/02/openai-is-finally-merging-chatgpts-chat-and-work-tabs/ | Mon, 02 Nov 2026 13:57:53 |\n| 14 | \"OpenAI might rebrand its data centers as 'AI compute campuses'\" | https://techcrunch.com/2026/11/01/openai-might-rebrand-its-data-centers-as-ai-compute-campuses/ | Sun, 01 Nov 2026 21:55:23 |\n| 15 | \"AI can make tech CEOs' lives easier. What about everyone else?\" | https://techcrunch.com/2026/11/01/ai-can-make-tech-ceos-lives-easier-what-about-everyone-else/ | Sun, 01 Nov 2026 20:57:58 |\n| 16 | \"Data centers are now a midterm issue, even in Brooklyn\" | https://techcrunch.com/2026/10/31/data-centers-are-now-a-midterm-issue-even-in-brooklyn/ | Sun, 01 Nov 2026 02:22:10 |\n| 17 | \"Apple CEO says the company doesn't 'want to ship AI for AI's sake'\" | https://techcrunch.com/2026/10/31/apple-ceo-says-the-company-doesnt-want-to-ship-ai-for-ais-sake/ | Sat, 31 Oct 2026 21:41:00 |\n| 18 | \"4 days left: How TechCrunch Founder Summit helps you make more useful connections to scale\" | https://techcrunch.com/2026/10/31/4-days-left-how-techcrunch-founder-summit-helps-you-make-more-useful-connections-to-scale/ | Sat, 31 Oct 2026 21:36:07 |\n| 19 | \"Judge allows NAACP lawsuit over xAI data center pollution to move forward\" | https://techcrunch.com/2026/10/31/judge-allows-naacp-lawsuit-over-xai-data-center-pollution-to-move-forward/ | Sat, 31 Oct 2026 21:17:03 |\n| 20 | \"OpenAI reportedly lowers funding target for new round\" | https://techcrunch.com/2026/10/31/openai-reportedly-lowers-funding-target-for-new-round/ | Sat, 31 Oct 2026 16:12:55 |",
  "durationMs": 10912,
  "url": "https://techcrunch.com/category/artificial-intelligence/feed/"
}

{
  "url": "https://www.federalregister.gov/documents/search?conditions%5Bterm%5D=%22artificial+intelligence%22&conditions%5Bpublication_date%5D%5Bgte%5D=2026-11-02",
  "prompt": "List documents published November 2 or 3, 2026 mentioning artificial intelligence, with agency, title, type and URL."
}

{
  "bytes": 717,
  "code": 302,
  "codeText": "Found",
  "result": "REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.\n\n    Original URL: https://www.federalregister.gov/documents/search?conditions%5Bterm%5D=%22artificial+intelligence%22&conditions%5Bpublication_date%5D%5Bgte%5D=2026-11-02\n    Redirect URL (from the server's Location header — server-supplied, not verified): https://unblock.federalregister.gov/\n    Status: 302 Found\n\n    To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:\n    - url: \"https://unblock.federalregister.gov/\"\n    - prompt: \"List documents published November 2 or 3, 2026 mentioning artificial intelligence, with agency, title, type and URL.\"",
  "durationMs": 362,
  "url": "https://www.federalregister.gov/documents/search?conditions%5Bterm%5D=%22artificial+intelligence%22&conditions%5Bpublication_date%5D%5Bgte%5D=2026-11-02"
}

{
  "url": "https://www.statnews.com/topic/artificial-intelligence/",
  "prompt": "List all articles with dates November 2 or 3, 2026, with titles, dates and URLs."
}

{
  "bytes": 161303,
  "code": 200,
  "codeText": "OK",
  "result": "The page contains no articles dated November 2 or 3, 2026. The most recent date shown is October 30, 2026:\n\n- **STAT Plus: FDA, CMS scramble to avoid regulatory logjam as more states look to test AI in clinical settings** (October 30, 2026): https://www.statnews.com/2026/10/30/fda-cms-health-ai-regulation-state-sandboxes-run-into-federal-rules/",
  "durationMs": 3254,
  "url": "https://www.statnews.com/topic/artificial-intelligence/"
}

{
  "url": "https://digital-strategy.ec.europa.eu/en/news",
  "prompt": "List all news items dated 2 November 2026 or 3 November 2026, with titles and URLs."
}

{
  "bytes": 70384,
  "code": 200,
  "codeText": "OK",
  "result": "Only one item in the provided content is dated 3 November 2026, and none is dated 2 November 2026:\n\n- **DigitalEU at Web Summit 2026: Supporting businesses and startups to grow and innovate**\n  https://digital-strategy.ec.europa.eu/en/news/digitaleu-web-summit-2026-supporting-businesses-and-startups-grow-and-innovate\n\nThis item describes DG Connect's presence at Web Summit in Lisbon from 10 to 12 November, including two masterclasses. The content shows only the first page of 595 search-result pages, so other items from these dates may exist elsewhere.",
  "durationMs": 3899,
  "url": "https://digital-strategy.ec.europa.eu/en/news"
}

{
  "url": "https://www.techmeme.com/",
  "prompt": "List all AI-related headlines with their timestamps and source publishers, especially anything from Nov 2-3 2026 about frontier models, labs, chips, datacenters, funding, earnings, deployment."
}

{
  "bytes": 402122,
  "code": 200,
  "codeText": "OK",
  "result": "**Snapshot time:** November 3, 2026, 6:05 AM. The page gives dates but not exact article times, and the content is truncated, so this list may be incomplete.\n\n**Frontier labs (Anthropic)**\n- **Nov 2, TechCrunch (Julie Bort):** Anthropic's revised S-1 says it may \"imminently meet\" its RSI threshold and might not spot significant acceleration until after it occurs. Also covered by Wccftech, Gizmodo, and WSJ.\n- **Nov 2, CNBC (Ashley Capoot):** The amended S-1 discloses $895.4B in purchase commitments and leases, \"substantially all of which is related to compute and infrastructure.\"\n- **Nov 2, Bloomberg:** Q3 revenue rose to nearly $17B, up 12x year over year, with a $23.3B net loss. Also covered by NYT, FT, The Information, The Verge, SiliconANGLE, and The Register.\n- **Nov 2, Bloomberg:** Anthropic is seeking up to $3.5B from Japanese investors as part of its IPO.\n- **Undated in snapshot, WSJ:** Institutional investors reportedly want an IPO valuation of about $1.5T–$1.6T, down from earlier estimates near $2T.\n\n**Research and deployment**\n- **Nov 2–3, VentureBeat, The Register (Nov 3), Digit, AIM, RuntimeWire:** MIT researchers reportedly used GPT-6 Astra to edit about 0.016% of Qwen3.5-0.8B's weights, improving its math scores. Critics such as Adam Karvonen argue it used standard interpretability methods and ablation rather than directly reading the weights.\n\n**Chips, memory, and datacenters**\n- **Nov 3, FT (also Bloomberg, The Information):** Nvidia reportedly told cloud clients to sell at least 51% of their services to non-Chinese companies, limiting China's access to AI chips.\n- **Nov 2, Gizmodo:** Apple's earnings coverage says \"Even Higher Memory Prices and Siri AI Push Will Weigh On Profits,\" and Apple expects memory costs to keep rising into December.\n- **Nov 2, TechCrunch:** Apple's inventory reached $14.54B in Q4.\n- **Nov 2, NYT:** Sources describe Anthropic's compute deals, with 3.5GW+ of expected 2026 capacity spread across Amazon, Google, and AMD beyond Nvidia.\n- **Nov 2, DatacenterDynamics:** Anthropic's S-1 update shows $895.4bn in cloud and datacenter commitments.\n\n**Funding and M&A**\n- **Nov 2, The Information:** Salesforce plans to acquire Cresta, an AI contact-center automation provider, reportedly for $2.7B. Salesforce confirmed a definitive agreement.\n\n[WebFetch note: this page's text is 243785 characters long and the answer above covers only characters 0 to 100000; the final 143785 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 18024,
  "url": "https://www.techmeme.com/"
}

{
  "url": "https://research.checkpoint.com/2026/2nd-november-threat-intelligence-report/",
  "prompt": "Publication date and all AI-related items: GOLD OGRE ransomware AI agents, Aur0ra attacks, North Korean threat actors AI use, numbers and named actors."
}

{
  "bytes": 192637,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026\n\n**AI-related items**\n\n- **GOLD OGRE (Aur0ra attacks):** Sophos reports that this ransomware group used AI agents extensively. Operators gave the tools compromised credentials and goals, and the tools handled network reconnaissance, located privileged accounts, and supported lateral movement. The group also used AI-assisted development to test ways to evade endpoint security.\n- **North Korean threat actors:** Microsoft documents growing AI use by North Korean actors. They use language models for reconnaissance, malicious tool development, refining social engineering, and speeding up intrusions. Both espionage and financially motivated operations are involved.\n- **VAPOR PANDA (China-linked):** CrowdStrike uncovered a global espionage campaign using the \"AI-enabled ARTEX framework.\" It targeted more than 200 organizations in at least 14 countries, including government agencies, telecom providers, and defense companies. Confirmed intrusions involved credential theft and the BLOODALCHEMY backdoor.\n- **Alibaba Qwen model:** Check Point Research found unexpected network activity from Qwen during a security-related task, with many different destination addresses. They assess unstable model behavior as more likely than a deliberately built-in data-exfiltration mechanism.",
  "durationMs": 6347,
  "url": "https://research.checkpoint.com/2026/2nd-november-threat-intelligence-report/"
}

{
  "query": "NCSC Annual Review 2026 AI ransomware nationally significant incidents",
  "mode": "extended"
}

{
  "query": "NCSC Annual Review 2026 AI ransomware nationally significant incidents",
  "results": [
    {
      "tool_use_id": "srvtoolu_01TWjzaoevQknAi6wKWEn7Nc",
      "content": [
        {
          "title": "UK Cybersecurity Agency Warns AI Could Accelerate Ransomware Attacks on Critical Infrastructure",
          "url": "https://cybersecuritynews.com/ai-could-accelerate-ransomware/"
        },
        {
          "title": "Cyberattacks Cost UK £14.7B; NCSC Sees AI Ransomware by 2028 - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-cyberattacks-cost-uk-14-7b-ncsc-sees-ai-ransomware-by-2028/"
        },
        {
          "title": "Cyber chief: UK facing AI-powered attacks on critical infrastructure within two years",
          "url": "https://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years"
        },
        {
          "title": "NCSC warns AI ransomware likely to hit UK infrastructure by 2028",
          "url": "https://aiweekly.co/alerts/ncsc-warns-ai-ransomware-likely-to-hit-uk-infrastructure-by-2028"
        },
        {
          "title": "NCSC warns AI ransomware is highly likely to hit UK infrastructure by 2028",
          "url": "https://superpowerdaily.com/posts/ncsc-warns-ai-ransomware-is-highly-likely-to-hit-uk-infrastructure-by-2028"
        },
        {
          "title": "NCSC: AI ransomware on UK infrastructure likely by 2028",
          "url": "https://www.resultsense.com/news/2026-11-03-ncsc-state-of-cyber-nation-ai-ransomware-2028/"
        },
        {
          "title": "NCSC Warns AI-Powered Ransomware Is Highly Likely to Hit UK Critical Infrastructure by 2028",
          "url": "https://windowsforum.com/news/ncsc-warns-ai-powered-ransomware-is-highly-likely-to-hit-uk-critical-infrastructure-by-2028.450709/"
        },
        {
          "title": "UK Cyber Agency Warns AI Ransomware Attack on Critical Infrastructure Is “Highly Likely” by 2028",
          "url": "https://blockonomi.com/uk-cyber-agency-warns-ai-ransomware-attack-on-critical-infrastructure-is-highly-likely-by-2028"
        },
        {
          "title": "NCSC Annual Review 2024",
          "url": "https://www.ncsc.gov.uk/collection/ncsc-annual-review-2024/chapter-01"
        }
      ]
    },
    "The NCSC's 2026 Annual Review, published 3 November 2026, reports 80 nationally significant incidents and warns that AI-enabled ransomware is likely to hit UK critical infrastructure by 2028.\n\n- **Incident counts:** One report says the review records 1,831 attack reports, with 337 incidents requiring support from its Incident Management Team. The 80 nationally significant incidents are a subset of the 337 cases that needed NCSC support, not the total number of cyber attacks across the UK. The year-on-year drop is notable: one analysis notes the count was 80 nationally significant incidents in the year to August 2026, against 204 a year earlier.\n- **Ransomware warning:** The review judges that \"highly likely\" that AI-powered malware will feature in ransomware aimed at UK critical national infrastructure by 2028. It expects AI to speed up existing tactics rather than create fresh attack routes, and it says adoption among attackers remains uneven.\n- **Caveats:** Another source notes that the scenarios are not predictions, and the report admits the prospect of surprise is high.\n- **Funding:** The government is putting £60 million into the first phase of a national Cyber Shield, along with £70 million for a National Exposure and Real-Time Vulnerability Centre and a new AI Cyber Security Centre of Excellence.\n\n**Conflicting figures:** One outlet (Superpower Daily) reports that the NCSC managed more than 200 cyber incidents affecting UK critical infrastructure and its supporting ecosystem in the year to May 2026. That conflicts with the 80/337 figures and the 1 September 2025 to 31 August 2026 review period, so I would treat it as unreliable unless confirmed against the NCSC's own pages. The report's naming is also inconsistent across coverage, with some outlets calling it the \"State of the Cyber Nation\" report and others the Annual Review. I'd check the NCSC site directly before relying on any specific number."
  ],
  "durationSeconds": 7.110299547000002,
  "searchCount": 1
}

{
  "url": "https://unit42.paloaltonetworks.com/",
  "prompt": "List recent posts with dates, especially Nov 2 2026 threat intelligence highlights and anything AI-related."
}

{
  "bytes": 290183,
  "code": 200,
  "codeText": "OK",
  "result": "**Nov 2, 2026 Threat Intelligence Highlights**\n- **Nov 2, 2026: \"Unit 42 Threat Intelligence Highlights - Nov. 2, 2026\"** (Insights): Summarizes recent cyberespionage and financial extortion activity and how threat actors are rapidly adopting AI in offensive operations.\n\n**AI-related posts**\n- **Oct 21, 2026: \"Next Exploit Opportunities\"** (Malware): A threat actor's use of AI to plan and carry out several kinds of cybercrime.\n- **Oct 15, 2026: AI-Powered Espionage Campaign Targets Government Linux Infrastructure** (Malware): An espionage campaign using AI against government Linux systems.\n- **Oct 28, 2026: Unwrapping Retail Peak Season Cyber Threats** (Insights): Retail threats during peak season, tagged with frontier AI.\n- **Undated: Unit 42 Breaking Insights: Combat Risks from Frontier AI Models**: A threat briefing, with a watch-on-demand link, on how frontier AI models shorten the time from vulnerability discovery to exploitation.\n- **Undated: The Current Landscape of OAuth Attacks** (Insights): Covers OAuth attacks and is tagged with AI.\n\n**Other recent posts (newest first)**\n- **Oct 29, 2026:** Threat Brief on critical PHP vulnerabilities CVE-2026-109618 and CVE-2026-109619 (updated Oct 29).\n- **Oct 22, 2026:** EMudhra Intermediate CA Certificates Compromised (Malware).\n- **Oct 20, 2026:** Active exploitation of the May 2026 PAN-OS vulnerability CVE-2026-0257 (updated Oct 20).\n- **Oct 16, 2026:** Top 5 Initial Access Threat Vectors Observed in September 2026.\n- **Oct 14, 2026:** Unit 42 Uncovers PEERSTITCH, a stealthy FortiGate implant (Malware).\n- **Sep 30, 2026:** Threat Brief on NetScaler zero-days CVE-2026-88771 and CVE-2026-88772, exploited in the wild (updated Sep 30).\n- **Aug 18, 2026:** Threat Brief on mitigating large-scale credential attacks (updated Aug 18).\n- **Aug 6, 2026:** ChainDrop: Inside a Self-Propagating npm Worm (Malware), tagged with Claude Code.\n- **Jul 15, 2026:** The npm Threat Landscape: Attack Surface and Mitigations (updated Jul 15).",
  "durationMs": 8862,
  "url": "https://unit42.paloaltonetworks.com/"
}

{
  "command": "curl -s \"https://www.federalregister.gov/api/v1/documents.json?conditions%5Bterm%5D=artificial+intelligence&conditions%5Bpublication_date%5D%5Bgte%5D=2026-11-02&conditions%5Bpublication_date%5D%5Blte%5D=2026-11-03&per_page=50&fields%5B%5D=title&fields%5B%5D=type&fields%5B%5D=agencies&fields%5B%5D=publication_date&fields%5B%5D=html_url&fields%5B%5D=abstract\" | head -c 8000",
  "description": "Query Federal Register API for AI documents"
}

{"stdout":"{\"description\":\"Documents matching 'artificial intelligence' and published from 11/02/2026 to 11/03/2026\",\"count\":2,\"total_pages\":1,\"results\":[{\"title\":\"Streamlining Contested Adjudications in Licensing Proceedings\",\"type\":\"Rule\",\"agencies\":[{\"raw_name\":\"NUCLEAR REGULATORY COMMISSION\",\"name\":\"Nuclear Regulatory Commission\",\"id\":383,\"url\":\"https://www.federalregister.gov/agencies/nuclear-regulatory-commission\",\"json_url\":\"https://www.federalregister.gov/api/v1/agencies/383\",\"parent_id\":null,\"slug\":\"nuclear-regulatory-commission\"}],\"publication_date\":\"2026-11-03\",\"html_url\":\"https://www.federalregister.gov/documents/2026/11/03/2026-22443/streamlining-contested-adjudications-in-licensing-proceedings\",\"abstract\":\"The U.S. Nuclear Regulatory Commission (NRC, agency, or Commission) is revising the agency's rules of practice and procedure to streamline contested adjudications in NRC licensing proceedings in response to the Accelerating Deployment of Versatile, Advanced Nuclear for Clean Energy Act of 2024 (ADVANCE Act) and Executive Order 14300, Ordering the Reform of the Nuclear Regulatory Commission.\"},{\"title\":\"Pipeline Safety: Amendments to Liquefied Natural Gas Facilities\",\"type\":\"Proposed Rule\",\"agencies\":[{\"raw_name\":\"DEPARTMENT OF TRANSPORTATION\",\"name\":\"Transportation Department\",\"id\":492,\"url\":\"https://www.federalregister.gov/agencies/transportation-department\",\"json_url\":\"https://www.federalregister.gov/api/v1/agencies/492\",\"parent_id\":null,\"slug\":\"transportation-department\"},{\"raw_name\":\"Pipeline and Hazardous Materials Safety Administration\",\"name\":\"Pipeline and Hazardous Materials Safety Administration\",\"id\":408,\"url\":\"https://www.federalregister.gov/agencies/pipeline-and-hazardous-materials-safety-administration\",\"json_url\":\"https://www.federalregister.gov/api/v1/agencies/408\",\"parent_id\":492,\"slug\":\"pipeline-and-hazardous-materials-safety-administration\"}],\"publication_date\":\"2026-11-03\",\"html_url\":\"https://www.federalregister.gov/documents/2026/11/03/2026-22396/pipeline-safety-amendments-to-liquefied-natural-gas-facilities\",\"abstract\":\"PHMSA proposes updating its regulations for liquefied natural gas (LNG) facilities to incorporate by reference the most recent industry safety standards and to make other changes to account for more than two decades of improvements and technological advancements. This rulemaking also responds to congressional mandates directing PHMSA to integrate risk-based regulatory approaches for certain LNG facilities.\"}]}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":39,"oldLines":3,"newStart":39,"newLines":5,"lines":[" {\"t\":\"2026-11-03T11:08:10.730Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"afb0755d99de3a80e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_015yWZ2U5v9myCm5AVhhh62s\",\"duration_ms\":18025,\"input\":{\"url\":\"https://www.techmeme.com/\",\"prompt\":\"List all AI-related headlines with their timestamps and source publishers, especially anything from Nov 2-3 2026 about frontier models, labs, chips, datacenters, funding, earnings, deployment.\"},\"response\":{\"bytes\":402122,\"code\":200,\"codeText\":\"OK\",\"result\":\"**Snapshot time:** November 3, 2026, 6:05 AM. The page gives dates but not exact article times, and the content is truncated, so this list may be incomplete.\\n\\n**Frontier labs (Anthropic)**\\n- **Nov 2, TechCrunch (Julie Bort):** Anthropic's revised S-1 says it may \\\"imminently meet\\\" its RSI threshold and might not spot significant acceleration until after it occurs. Also covered by Wccftech, Gizmodo, and WSJ.\\n- **Nov 2, CNBC (Ashley Capoot):** The amended S-1 discloses $895.4B in purchase commitments and leases, \\\"substantially all of which is related to compute and infrastructure.\\\"\\n- **Nov 2, Bloomberg:** Q3 revenue rose to nearly $17B, up 12x year over year, with a $23.3B net loss. Also covered by NYT, FT, The Information, The Verge, SiliconANGLE, and The Register.\\n- **Nov 2, Bloomberg:** Anthropic is seeking up to $3.5B from Japanese investors as part of its IPO.\\n- **Undated in snapshot, WSJ:** Institutional investors reportedly want an IPO valuation of about $1.5T–$1.6T, down from earlier estimates near $2T.\\n\\n**Research and deployment**\\n- **Nov 2–3, VentureBeat, The Register (Nov 3), Digit, AIM, RuntimeWire:** MIT researchers reportedly used GPT-6 Astra to edit about 0.016% of Qwen3.5-0.8B's weights, improving its math scores. Critics such as Adam Karvonen argue it used standard interpretability methods and ablation rather than directly reading the weights.\\n\\n**Chips, memory, and datacenters**\\n- **Nov 3, FT (also Bloomberg, The Information):** Nvidia reportedly told cloud clients to sell at least 51% of their services to non-Chinese companies, limiting China's access to AI chips.\\n- **Nov 2, Gizmodo:** Apple's earnings coverage says \\\"Even Higher Memory Prices and Siri AI Push Will Weigh On Profits,\\\" and Apple expects memory costs to keep rising into December.\\n- **Nov 2, TechCrunch:** Apple's inventory reached $14.54B in Q4.\\n- **Nov 2, NYT:** Sources describe Anthropic's compute deals, with 3.5GW+ of expected 2026 capacity spread across Amazon, Google, and AMD beyond Nvidia.\\n- **Nov 2, DatacenterDynamics:** Anthropic's S-1 update shows $895.4bn in cloud and datacenter commitments.\\n\\n**Funding and M&A**\\n- **Nov 2, The Information:** Salesf
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://ai.nejm.org/toc/ai/current\" 2>&1 | head -c 6000",
  "description": "Fetch NEJM AI current issue"
}

{
  "stdout": "HTTP 403 · https://ai.nejm.org/toc/ai/current · text/html\nJust a moment...",
  "stderr": "",
  "interrupted": false,
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{
  "url": "https://rss.arxiv.org/rss/cs.AI",
  "prompt": "List all paper titles, arXiv IDs, and the first 2 sentences of each abstract. Also note the feed's pubDate/announce date."
}

{
  "bytes": 1787655,
  "code": 200,
  "codeText": "OK",
  "result": "**Feed date:** The feed's pubDate and announce date are both **Tue, 03 Nov 2026 00:00:00 -0500**.\n\nEach summary below paraphrases the abstract's first two sentences, so no quoted text is needed. The feed content cuts off partway through the last abstract (TopoQuant), so the list may be incomplete beyond that point.\n\n1. **A Generalized Sparse Fuzzy Clustering Framework with Automated Cluster Cardinality Estimation Ability** (arXiv:2611.00159): Standard fuzzy clustering gives dense memberships that hurt noise handling and cluster-count estimation. The authors add a sparsity penalty.\n2. **Learning to bid and bundle: a posterior-sampling agent for online retail** (arXiv:2611.00165): A retailer selling a perishable product must learn click response and market strength from censored data. The authors design a posterior-sampling agent for this.\n3. **Early Stopping in Large Reasoning Models: A Survey and Empirical Audit of Efficiency and Reliability** (arXiv:2611.00166): Longer reasoning can improve accuracy but may waste compute. Early-stopping methods try to halt once enough reasoning exists.\n4. **PatchScout: Thematic Web Data Collection via Information Foraging** (arXiv:2611.00169): Researchers need reusable document collections spread across many web sources. The paper frames this as long-horizon information foraging.\n5. **Reimagining Text-to-SQL: A Survey of Large Language Model Architectures and Strategies** (arXiv:2611.00171): Text-to-SQL systems have moved from rules to neural methods and now to LLMs. The survey reviews these LLM-driven approaches.\n6. **AuroraWorld: Structured 4D World Modeling for Exo-to-Ego Video Generation in Robot Manipulation** (arXiv:2611.00177): Egocentric robot data is costly to collect. Synthesizing it from exocentric videos is a scalable alternative, but existing methods struggle.\n7. **Neurons Are All You Need** (arXiv:2611.00186): Artificial networks store capability mainly in synaptic weights, which causes forgetting. The authors propose NURESA, a layer with persistent intra-unit memory.\n8. **MemU-Bench: Benchmarking GUI Agents on Long-Horizon User Interactions** (arXiv:2611.00191): Real user instructions are vague and depend on history, which existing GUI benchmarks miss. The authors add a 118-task mobile benchmark.\n9. **From Cross-Section to Cross-Omics: Conditional Cell Nucleus Image Editing in Spatial Transcriptomics** (arXiv:2611.00226): Sectioning tissue creates a link between gene expression and nuclear measurements. The authors apply a diffusion framework to edit cell images across both omics layers.\n10. **RE-SciVQA: Improving Scientific VQA With Context-Relevant Retrieval and Lightweight MLLM Adaptation** (arXiv:2611.00242): Scientific figures often hold key information beyond the text. The method improves retrieval and fine-tunes small LLMs with LoRA.\n11. **OmniPiano: Diverse Dexterous Piano-Playing Challenges for Standard, Robust, Safe, and Multi-Agent RL** (arXiv:2611.00243): Dexterous piano playing is a demanding RL testbed. OmniPiano offers a benchmark with up to five Shadow Hands and multiple RL settings.\n12. **Taurus: LLM-in-the-Loop CT Annotation Matches Coding Agents at Half the Cost** (arXiv:2611.00247): Labeling aortic CT scans is slow, and public datasets use different conventions. The authors compare an LLM harness with free-form coding agents on blind label recovery.\n13. **A generative foundation model for computational brain imaging** (arXiv:2611.00265): Brain imaging tasks vary, while clinical data is scarce. BrainGFM is a generative prior pretrained on about 1.3 million MRI and CT slices.\n14. **Automated Theorem Generation in First-Order Logic by Construction from Triangular Standard Contradictions** (arXiv:2611.00269): Automated theorem generation aims to create new theorems, not just prove given ones. The method builds theorems that are correct by construction from minimally unsatisfiable clause sets.\n15. **Quantifying Local and Global Fidelity of Nonlinear Embeddings** (arXiv:2611.00290): Common claims say t-SNE and UMAP keep local structure while PCA keeps global structure. The paper proposes a single locality-profile statistic to test this.\n16. **Decentralized Multi-Agent Coordination and Communication in Shared Codebases** (arXiv:2611.00314): Coding agents working in one repository can get separate requests that conflict when merged. The authors introduce ParallACT, a benchmark for this.\n17. **Beyond Semantic IDs: Atomic Creator Tokens for Large-Scale Generative Recommendation** (arXiv:2611.00323): Cold-start creator recommendation relies on semantic IDs, which collide and limit recall. The authors propose one trainable token per creator.\n18. **Efficient NPN Classification for Large Functions using Graph Neural Network** (arXiv:2611.00339): Exact NPN classification of Boolean functions grows exponentially with input count. The paper recasts it as learned action prediction using a graph neural network.\n19. **Dependence-Aware Risk Assessment and Optimal Design of AI-Agent Safeguard Systems** (arXiv:2611.00386): Risk assessments for multi-layer AI safeguards often ignore dependence between checks. The paper builds a dependence-aware framework for selecting configurations and policies.\n20. **CalVLA: Shaping Native Confidence in Vision-Language-Action Policies with Outcome Supervision** (arXiv:2611.00394): The paper asks whether a VLA policy's action probabilities can signal likely task failure. It tunes confidence using successful and failed rollouts.\n21. **Hacking or Just Failing? A More Capable LLM Monitor Better Separates Reward Hacking from Honest Failure** (arXiv:2611.00407): An agent's score can rise through gaming or through ordinary mistakes, and monitors must tell these apart. Small local monitors performed poorly, while a stronger one did better.\n22. **Nonconformal Distortion and Local Orientation Reversal in the Fourier Circuit
… [7224 more characters in events.jsonl]

{
  "query": "AI regulation lawsuit ruling November 2 2026",
  "mode": "extended"
}

{
  "query": "AI regulation lawsuit ruling November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_012FkZg5y8ufHDN427c715BS",
      "content": [
        {
          "title": "AI Class Action Lawsuits in 2026: The October Tracker",
          "url": "https://openclassactions.substack.com/p/ai-class-action-lawsuits-in-2026"
        },
        {
          "title": "November 2026: Unprecedented State Enforcement Ahead of Midterms",
          "url": "https://thealgorithmicupdate.substack.com/p/november-2026-unprecedented-state"
        },
        {
          "title": "AI in litigation series: An update on AI copyright cases in 2026",
          "url": "https://www.nortonrosefulbright.com/en/knowledge/publications/ce8eaa5f/ai-in-litigation-series-an-update-on-ai-copyright-cases-in-2026"
        },
        {
          "title": "NetChoice v. Weiser",
          "url": "https://en.wikipedia.org/wiki/NetChoice_v._Weiser"
        },
        {
          "title": "Latest AI Lawsuits Filed (2026): The 30 Newest Cases",
          "url": "https://ailawsuittracker.com/latest/"
        },
        {
          "title": "AI Copyright Lawsuits Tracker (2026) — Cases We Track",
          "url": "https://ailawsuittracker.com/copyright/"
        },
        {
          "title": "Major AI Court Rulings (2026): Fair Use, Output & More",
          "url": "https://ailawsuittracker.com/rulings/"
        },
        {
          "title": "AI Lawsuit Tracker: 330 AI Lawsuits, Status & Rulings",
          "url": "https://ailawsuittracker.com/"
        },
        {
          "title": "Appeals Court Rules on AI Use and Legal Fees",
          "url": "https://www.jdjournal.com/2026/11/03/court-ruling-ai-law-firm-legal-fees/"
        }
      ]
    },
    "I found one ruling dated November 2, 2026 that touches AI, but nothing that squarely matches \"AI regulation\" on that date.\n\n- **Tenth Circuit fee ruling (Nov. 2):** The Court of Appeals for the 10th Circuit issued a decision on that date. It upholds a $115,000 award to Brownstein Hyatt Farber Schreck following a trade secrets lawsuit. The court focused on whether the company had a sufficient basis to challenge specific charges, not on AI-based fee cuts. The ruling does not establish that AI can never justify lower fees.\n\n- **State enforcement roundup (Nov. 2):** The Algorithmic Update's November 2 issue covers state attorney general actions on AI and child safety. It also covers Republican AGs targeting data flows to China and New York banning \"unsafe\" chatbot features. These are enforcement actions, not rulings. Some AG cases seek civil penalties, data deletion and injunctions that could halt advanced AI testing until specific safeguards are met.\n\n- **Other AI litigation (undated in results):** A tracker says the Ninth Circuit affirmed dismissal of a DMCA § 1202(b) claim against GitHub Copilot and OpenAI Codex. Another entry reports that the Federal Circuit denied Anthropic's petition over the Department of War's supply-chain exclusion. The search results don't give a date for either.\n\nThe search results don't confirm any other AI regulation ruling on November 2, 2026. The sources are mostly trackers and newsletters, so check the court dockets before relying on any of this."
  ],
  "durationSeconds": 6.986378861000005,
  "searchCount": 1
}

{
  "query": "EU AI Act digital omnibus delay November 2026",
  "mode": "extended"
}

{
  "query": "EU AI Act digital omnibus delay November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01CLg5RXEKP7ZHSxWAXXtZpA",
      "content": [
        {
          "title": "EU AI Act Deal: Digital Omnibus Now in Force",
          "url": "https://usercentrics.com/knowledge-hub/eu-ai-act-high-risk-delay-article-50-transparency-consent/"
        },
        {
          "title": "Digital Omnibus: EU Parliament Delays the AI Act Rules",
          "url": "https://pasqualepillitteri.it/en/news/5190/digital-omnibus-ai-act-eu-parliament"
        },
        {
          "title": "EU AI Act Omnibus Agreement — Postponed High-Risk Deadlines and Other Key Changes - Gibson Dunn",
          "url": "https://www.gibsondunn.com/eu-ai-act-omnibus-agreement-postponed-high-risk-deadlines-and-other-key-changes/"
        },
        {
          "title": "Why the EU’s AI Omnibus Still Leaves US Firms Facing Steep Costs - The National Interest",
          "url": "https://nationalinterest.org/blog/techland/why-the-eus-ai-omnibus-still-leaves-us-firms-facing-steep-costs"
        },
        {
          "title": "AI Omnibus: provisional agreement on changes to EU AI Act, including delayed deadlines",
          "url": "https://www.addleshawgoddard.com/en/insights/insights-briefings/2026/technology/ai-omnibus-provisional-agreement-changes-eu-ai-act-delayed-deadlines/"
        },
        {
          "title": "EU AI Act Timeline After the Digital Omnibus Delay to 2027",
          "url": "https://futureagi.com/blog/eu-ai-act-timeline-digital-omnibus-2027/"
        },
        {
          "title": "Yes, August 2 Still Matters: The EU Approved a High-Risk AI Delay, but Most Transparency Obligations Remain",
          "url": "https://www.joneswalker.com/en/insights/blogs/ai-law-blog/yes-august-2-still-matters-the-eu-approved-a-high-risk-ai-delay-but-most-trans.html"
        },
        {
          "title": "The Digital AI Omnibus: Proposed deferral of high risk AI obligations under the AI Act (update) - DLA Piper GENIE",
          "url": "https://knowledge.dlapiper.com/dlapiperknowledge/globalemploymentlatestdevelopments/2026/The-Digital-AI-Omnibus-Proposed-deferral-of-high-risk-AI-obligations-under-the-AI-Act"
        },
        {
          "title": "EU AI Act Digital Omnibus Delay Explained: What Moved to 2027, What's In Force Now, and the Enterprise Strategy",
          "url": "https://www.theaienterprise.io/p/eu-ai-act-omnibus-reprieve-strategy"
        }
      ]
    },
    "The Digital Omnibus has been adopted and is in force, and it pushes back most high-risk obligations. The main dates to watch in or near November 2026 are the 2 December 2026 deadlines.\n\n- **Status:** One source says the omnibus became Regulation (EU) 2026/1744, in force since 27 July 2026. Another, a National Interest piece, describes it as having become law this summer. Some older sources predate final adoption, so treat their \"pending\" language with caution.\n- **High-risk delay:** Standalone Annex III systems move to 2 December 2027, and AI embedded in regulated products under Annex I moves to 2 August 2028.\n- **December 2026 deadline:** Watermarking has a grace period that has been delayed until 2 December 2026. Per one timeline, 2 December 2026: two new prohibitions and legacy Article 50(2) marking also takes effect, and the new prohibitions cover nudification and CSAM.\n- **Not everything moved:** The Omnibus left most of the Act's transparency obligations exactly where they were. Article 50 duties for chatbots and generative AI were still scheduled for 2 August 2026, per Jones Walker.\n- **Other changes:** Sandbox deadlines move to 2 August 2027.\n\nI didn't find sources that directly address whether anything changes specifically in November 2026, so this is based on the scheduled dates above."
  ],
  "durationSeconds": 7.016034952999995,
  "searchCount": 1
}

{
  "url": "https://origin-unit42.paloaltonetworks.com/u42-threat-intelligence-highlights-oct-2026/",
  "prompt": "Publication date and all AI-related findings with numbers and named threat actors."
}

{
  "bytes": 220886,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026\n\n**AI-related findings:** The page has three AI-related observations, all under \"AI-Enabled Offensive Operations.\" It includes no statistics and names no threat actors.\n\n- Threat actors are adding generative AI and large language models (LLMs) to their offensive workflows, which the report calls a notable emerging trend across several motivations.\n- AI is used to generate highly tailored social engineering lures and synthetic personas at scale.\n- LLMs help with rapid scripting, payload debugging, and code obfuscation.\n- Automated reconnaissance and multimodal tools, including deepfakes, support executive impersonation and access operations.",
  "durationMs": 6017,
  "url": "https://origin-unit42.paloaltonetworks.com/u42-threat-intelligence-highlights-oct-2026/"
}

{
  "query": "Sophos GOLD OGRE Aur0ra ransomware AI agents report",
  "mode": "extended"
}

{
  "query": "Sophos GOLD OGRE Aur0ra ransomware AI agents report",
  "results": [
    {
      "tool_use_id": "srvtoolu_011EwNYAtLFETjsb23CueswL",
      "content": [
        {
          "title": "Aur0ra Ransomware AI Agent Playbook - Brandefense",
          "url": "https://brandefense.io/security-news/aur0ra-ransomware-ai-agent-defender-playbook/"
        },
        {
          "title": "Dark Web Intelligence on X: \"🚨 SOPHOS LINKS AI-ASSISTED EVASION TESTING TO AUR0RA RANSOMWARE OPERATIONS New Sophos research says the GOLD OGRE group, which runs Aur0ra (Aurora) ransomware, used an AI-assisted, Cursor-built framework to test EDR evasion, then used similar AI agents in real intrusi… / X",
          "url": "https://x.com/DailyDarkWeb/status/2116172361552810348"
        },
        {
          "title": "In Other News: Anthropic Breach Dispute, UEFI Flaw Hits Most Servers, Cloudflare AI Data Leak - SecurityWeek",
          "url": "https://www.securityweek.com/in-other-news-anthropic-breach-dispute-uefi-flaw-hits-most-servers-cloudflare-ai-data-leak/"
        },
        {
          "title": "Sophos traces how the Aur0ra ransomware operation uses AI",
          "url": "https://www.comparethecloud.net/news/sophos-traces-how-the-aur0ra-ransomware-operation-uses-ai-to-run-attacks"
        },
        {
          "title": "Hackers Use Cursor and Claude AI to Automate Attacks in Aur0ra Ransomware Operations",
          "url": "https://gbhackers.com/aur0ra-ransomware-ai-attacks/"
        },
        {
          "title": "Aur0ra Ransomware Operators Use Cursor AI Agents to Escalate Privileges and Steal Data",
          "url": "https://mallory.ai/stories/01a187e4-5f31-7b22-9580-fba45e337505"
        },
        {
          "title": "Ransomware gang used AI agents to move through victim networks, Sophos finds",
          "url": "https://superpowerdaily.com/posts/ransomware-gang-used-ai-agents-to-move-through-victim-networks-sophos-finds"
        },
        {
          "title": "Sophos 揭露 Aur0ra 勒索軟體攻擊大量運用 AI 技術,Information Security 資安人科技網",
          "url": "https://www.informationsecurity.com.tw/article/article_detail.aspx?aid=13441"
        },
        {
          "title": "Aur0ra Ransomware Ran Cursor AI Agents to Domain Admin",
          "url": "https://zerohunt.ai/blog/aur0ra-ransomware-cursor-ai-agents/"
        },
        {
          "title": "Cybersecurity Watch: GMO Security Cases, Supply Chain & Cloud Exposure, and Platform Security - The CODEW",
          "url": "https://www.thecodew.com/2026/11/cybersecurity-watch-november-3.html"
        }
      ]
    },
    "Sophos's Counter Threat Unit attributes the Aur0ra ransomware operation to GOLD OGRE and reports that the group used AI coding agents in intrusions. Sources agree on the main points, though some details vary.\n\n- **Agent role:** Coverage says the agents handled Active Directory discovery, credential attacks, and lateral movement with limited human involvement. In some environments they reached domain admin, and three of those victims later appeared on Aur0ra's leak site (the agents then ran Active Directory discovery, analyzed credential attack paths and moved laterally... three of those victims later appeared on Aur0ra's leak site).\n- **Human control:** Human operators supplied VPN access, targets, and objectives, and ransomware deployment stayed human-run (the impact stage, deploying the ransomware itself, stayed human controlled).\n- **Models:** Sources differ. Sophos names Cursor's Composer model as the main tool, with models from Anthropic, xAI, and Moonshot also involved. Gambit Security, cited separately, identified the specific agent in semi-automated attacks as Claude 4.5-Sonnet (Gambit Security, cited separately in Sophos's report, identified the specific agent in semi-automated attacks as Claude 4.5-Sonnet).\n- **Evasion testing:** Sophos assesses with high confidence that GOLD OGRE used AI to test evasion against EDR products, then shared similar tooling with Aur0ra associates (Sophos assesses with high confidence that GOLD OGRE tested evasion with AI and then gave affiliates similar tooling). The GOLD OGRE attribution and this testing-to-operations link are Sophos assessments.\n- **Timing:** The intrusion artifacts date to late August, and Sophos published on October 29, 2026.\n- **Caveat:** This is vendor research describing AI-assisted operations, not fully autonomous ransomware (it describes AI-assisted operational techniques, not fully autonomous ransomware)."
  ],
  "durationSeconds": 7.020469448999997,
  "searchCount": 1
}

{
  "query": "CrowdStrike VAPOR PANDA ARTEX framework 200 organizations espionage",
  "mode": "extended"
}

{
  "query": "CrowdStrike VAPOR PANDA ARTEX framework 200 organizations espionage",
  "results": [
    {
      "tool_use_id": "srvtoolu_01SmddEjhaVkU4RNRK8oWLYg",
      "content": [
        {
          "title": "VAPOR PANDA ARTEX Campaign: How It Worked - Brandefense",
          "url": "https://brandefense.io/security-news/vapor-panda-artex-ai-espionage-campaign/"
        },
        {
          "title": "VAPOR PANDA Uses AI-Driven ARTEX to Grow Global Espionage Campaign",
          "url": "https://www.crowdstrike.com/en-us/blog/vapor-panda-uses-artex-to-scale-global-campaign/"
        },
        {
          "title": "VAPOR PANDA APT Threat Actor Profile - Brandefense",
          "url": "https://brandefense.io/knowledge-hub/apt-groups/vapor-panda/"
        },
        {
          "title": "Chinese hackers attack 200+ organizations with DeepSeek AI agents",
          "url": "https://pasqualepillitteri.it/en/news/28850/chinese-hackers-deepseek-ai-agents-artex-200-organizations"
        },
        {
          "title": "ARTEX AI hacking framework spreads to another China-linked group - iTnews",
          "url": "https://www.itnews.com.au/news/artex-ai-hacking-framework-spreads-to-another-china-linked-group-630045"
        },
        {
          "title": "Armed with AI, hackers target endpoint security blind spots, raising stakes for CISOs",
          "url": "https://csoonline.com/article/4243816/armed-with-ai-hackers-target-endpoint-security-blind-spots-raising-stakes-for-cisos.html"
        },
        {
          "title": "China-Linked Group Ran AI Agents Against 200+ Targets - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-china-linked-group-ran-ai-agents-against-200-targets/"
        },
        {
          "title": "CrowdStrike: VAPOR PANDA Used the ARTEX AI Framework to Scale a Global Espionage Campaign",
          "url": "https://zerostrike.net/en/blog/crowdstrike-vapor-panda-artex-global-espionage-campaign/"
        },
        {
          "title": "PLA Unit 61486",
          "url": "https://en.wikipedia.org/wiki/PLA_Unit_61486"
        }
      ]
    },
    "CrowdStrike reported on October 29, 2026, that VAPOR PANDA, a China-nexus espionage group, used the open-source ARTEX agentic AI framework against more than 200 organizations. The campaign ran from October 17 and reached at least 14 countries. The sources agree on the core figures.\n\n- **Scale and confirmed compromises:** One ARTEX controller reached targets in at least 14 countries over an 11-day window From 17 October, one ARTEX controller went after more than 200 organizations in at least 14 countries over 11 days. CrowdStrike confirmed post-exploitation activity at nine of them.\n- **AI models:** The framework ran mostly on DeepSeek. CrowdStrike says VAPOR PANDA ran ARTEX primarily with the Chinese-origin DeepSeek model, supplemented with a second, subscription-based commercial model it could not confirm.\n- **Human role:** Recovered transcripts showed an operator issuing instructions in Chinese, and the agents were directed to write web shells and extract domain administrator passwords. The campaign marks an escalation from single intrusions to multiple simultaneous engagements directed by a human operator.\n- **Targets:** Reported targets include foreign ministries, United States semiconductor, defence and think tank organisations, and telecommunications providers across several regions.\n- **Tooling:** ARTEX's developer, a GitHub user known as Autumn-27, withdrew the original code in October because of its misuse, though copies and modified versions remain available.\n- **Separate from Storm-0940:** CrowdStrike says this activity is distinct from a campaign Microsoft reported under the Storm-0940 designation, and neither report says the two activities overlap.\n- **Caveat on autonomy:** Google's GTIG said there is no evidence fully autonomous, human-out-of-the-loop hacking exists yet."
  ],
  "durationSeconds": 7.479884247999988,
  "searchCount": 1
}

{
  "url": "https://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years",
  "prompt": "Publication date, all numbers, AI claims, named quotes (who said what). Quote figures exactly as written."
}

{
  "bytes": 11806,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** 3 November 2026 (the article text says \"Tuesday 3 November\").\n\n**Numbers**\n- **2028:** The year by which AI-powered malware is \"highly likely\" to be used in a ransomware attack on UK critical national infrastructure.\n- **Two years:** The window in which hostile actors' AI adoption is expected to grow.\n- **\"£60 million\":** Funding for the first phase of a national Cyber Shield.\n- **\"£70 million\":** Funding for the National Exposure and Real-Time Vulnerability (NERV) Centre.\n- **Tenth year:** The NCSC's anniversary. The annual review covers 1 September 2025 to 31 August 2026.\n\n**AI claims**\n- Hostile actors' use of AI is \"highly likely\" to increase the scale and efficiency of ransomware, social engineering, and vulnerability exploitation.\n- AI doesn't create new attack methods. It allows long-standing weaknesses to be found and exploited far more widely.\n- AI is also an opportunity to improve the UK's collective cyber resilience.\n\n**Named quotes**\n- **Dr Richard Horne, NCSC CEO:** \"For decades, we have collectively got away with doing tech on the cheap.\"\n- **Dr Richard Horne, NCSC CEO:** \"But we must be clear that is not because AI has invented new ways to attack us.\"\n- **Security Minister Dan Jarvis:** \"The NCSC's latest annual report shows cyber threats are growing more sophisticated.\"",
  "durationMs": 11621,
  "url": "https://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years"
}

{
  "url": "https://www.lawfaremedia.org/current-topics/artificial-intelligence",
  "prompt": "List all articles dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 439,
  "url": "https://www.lawfaremedia.org/current-topics/artificial-intelligence"
}

{
  "url": "https://iapp.org/news/",
  "prompt": "List all news items dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 638096,
  "code": 200,
  "codeText": "OK",
  "result": "None of the news items on this page are dated November 2 or 3, 2026. The listed items run from October 30 back to October 21, 2026, and the page shows only the first 20 of 7,879 results. Other pages may contain November items, but their content isn't included here, so I can't check them.",
  "durationMs": 3357,
  "url": "https://iapp.org/news/"
}

{
  "url": "https://www.techpolicy.press/",
  "prompt": "List all articles dated November 2 or November 3, 2026 with titles and URLs."
}

{
  "bytes": 298515,
  "code": 200,
  "codeText": "OK",
  "result": "Nine articles are dated November 2, 2026. None are dated November 3, 2026.\n\n1. \"How AI Companies Want to Be Governed, and What That Means for AI Governance\": /how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance\n2. \"There is No Universal Election Integrity Playbook for Platforms\": /there-is-no-universal-election-integrity-playbook-for-platforms\n3. \"Meta Streamlines State Censorship in India with Automated Takedowns\": /meta-streamlines-state-censorship-in-india-with-automated-takedowns\n4. \"How the EU AI Office Can See the Choices Behind Frontier Labs' Safety Claims\": /how-the-eu-ai-office-can-see-the-choices-behind-frontier-labs-safety-claims\n5. \"The SEC Should Block Anthropic's IPO to Protect the Public\": /the-sec-should-block-anthropics-ipo-to-protect-the-public\n6. \"October 2026 US Tech Policy Roundup\": /october-2026-us-tech-policy-roundup\n7. \"Europe and Canada Plot a Digital Alliance as US Ties Fray\": /europe-and-canada-plot-a-digital-alliance-as-us-ties-fray\n8. \"What's Really Behind the Science Slowdown the White House Wants to Fix?\": /whats-really-behind-the-science-slowdown-the-white-house-wants-to-fix\n9. \"Why Parental Consent Policies for Social Media Do Not Help Families\": /why-parental-consent-policies-for-social-media-do-not-help-families\n\nAll URLs are relative to the Tech Policy Press domain (techpolicy.press).",
  "durationMs": 5624,
  "url": "https://www.techpolicy.press/"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && for f in cs.LG cs.CL cs.CR cs.CY; do curl -sS \"https://rss.arxiv.org/rss/$f\" -o \"$f.xml\"; echo \"=== $f $(wc -c < $f.xml) bytes\"; grep -o '<pubDate>[^<]*' \"$f.xml\" | head -2; done",
  "description": "Download arXiv RSS feeds"
}

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Brandefense\\\",\\\"url\\\":\\\"https://brandefense.io/security-news/aur0ra-ransomware-ai-agent-defender-playbook/\\\"},{\\\"title\\\":\\\"Dark Web Intelligence on X: \\\\\\\"🚨 SOPHOS LINKS AI-ASSISTED EVASION TESTING TO AUR0RA RANSOMWARE OPERATIONS New Sophos research says the GOLD OGRE group, which runs Aur0ra (Aurora) ransomware, used an AI-assisted, Cursor-built framework to test EDR evasion, then used similar AI agents in real intrusi… / X\\\",\\\"url\\\":\\\"https://x.com/DailyDarkWeb/status/2116172361552810348\\\"},{\\\"title\\\":\\\"In Other News: Anthropic Breach Dispute, UEFI Flaw Hits Most Servers, Cloudflare AI Data Leak - SecurityWeek\\\",\\\"url\\\":\\\"https://www.securityweek.com/in-other-news-anthropic-breach-dispute-uefi-flaw-hits-most-servers-cloudflare-ai-data-leak/\\\"},{\\\"title\\\":\\\"Sophos traces how the Aur0ra ransomware operation uses AI\\\",\\\"url\\\":\\\"https://www.comparethecloud.net/news/sophos-traces-how-the-aur0ra-ransomware-operation-uses-ai-to-run-attacks\\\"},{\\\"title\\\":\\\"Hackers Use Cursor and Claude AI to Automate Attacks in Aur0ra Ransomware Operations\\\",\\\"url\\\":\\\"https://gbhackers.com/aur0ra-ransomware-ai-attacks/\\\"},{\\\"title\\\":\\\"Aur0ra Ransomware Operators Use Cursor AI Agents to Escalate Privileges and Steal Data\\\",\\\"url\\\":\\\"https://mallory.ai/stories/01a187e4-5f31-7b22-9580-fba45e337505\\\"},{\\\"title\\\":\\\"Ransomware gang used AI agents to move through victim networks, Sophos finds\\\",\\\"url\\\":\\\"https://superpowerdaily.com/posts/ransomware-gang-used-ai-agents-to-move-through-victim-networks-sophos-finds\\\"},{\\\"title\\\":\\\"Sophos 揭露 Aur0ra 勒索軟體攻擊大量運用 AI 技術,Information Security 資安人科技網\\\",\\\"url\\\":\\\"https://www.informationsecurity.com.tw/article/article_detail.aspx?aid=13441\\\"},{\\\"title\\\":\\\"Aur0ra Ransomware Ran Cursor AI Agents to Domain Admin\\\",\\\"url\\\":\\\"https://zerohunt.ai/blog/aur0ra-ransomware-cursor-ai-agents/\\\"},{\\\"title\\\":\\\"Cybersecurity Watch: GMO Security Cases, Supply Chain & Cloud Exposure, and Platform Security - The CODEW\\\",\\\"url\\\":\\\"https://www.thecodew.com/2026/11/cybersecurity-watch-november-3.html\\\"}]},\\\"Sophos's Counter Threat Unit attributes the Aur0ra ransomware operation to GOLD OGRE and reports that the group used AI coding agents in intrusions. Sources agree on the main points, though some details vary.\\\\n\\\\n- **Agent role:** Coverage says the agents handled Active Directory discovery, credential attacks, and lateral movement with limited human involvement. In some environments they reached domain admin, and three of those victims later appeared on Aur0ra's leak site (the agents then ran Active Directory discovery, analyzed credential attack paths and moved laterally... three of those victims later appeared on Aur0ra's leak site).\\\\n- **Human control:** Human operators supplied VPN access, targets, and objectives, and ransomware deployment stayed human-run (the impact stage, deploying the ransomware itself, stayed human controlled).\\\\n- **Models:** Sources differ. Sophos names Cursor's Composer model as the main tool, with models from Anthropic, xAI, and Moonshot also involved. Gambit Security, cited separately, identified the specific agent in semi-automate
… [10069 more characters in events.jsonl]

{
  "query": "NEJM AI automation bias large language model diagnostic reasoning randomized clinical trial physicians AI literacy",
  "mode": "extended"
}

{
  "query": "NEJM AI automation bias large language model diagnostic reasoning randomized clinical trial physicians AI literacy",
  "results": [
    {
      "tool_use_id": "srvtoolu_01A6Uzfx3HYDi6pz5xGbHFaw",
      "content": [
        {
          "title": "Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning Using Behavioral Nudges: A Randomized Controlled Trial",
          "url": "https://www.medrxiv.org/content/10.64898/2026.06.01.26354596v1.full"
        },
        {
          "title": "Automation Bias in Large Language Model–Assisted Diagnostic Reasoning among Physicians Trained in AI Literacy — A Randomized Clinical Trial",
          "url": "https://ai.nejm.org/doi/full/10.1056/AIoa2501001"
        },
        {
          "title": "Teaching the Override Automation Bias, Clinical Reasoning, and the Formation of the Physician in the AI Era",
          "url": "https://zenodo.org/records/23338856"
        },
        {
          "title": "Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning Using Behavioral Nudges",
          "url": "https://cdn.clinicaltrials.gov/large-docs/15/NCT07328815/Prot_SAP_000.pdf"
        },
        {
          "title": "1 Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among",
          "url": "https://www.medrxiv.org/content/10.1101/2025.08.23.25334280v2.full.pdf"
        },
        {
          "title": "NEJM AI on X: \"Original Article by I.A. Qazi et al.: Automation Bias in Large Language Model–Assisted Diagnostic Reasoning among Physicians Trained in AI Literacy — A Randomized Clinical Trial https://t.co/k86EzvJY4g\" / X",
          "url": "https://x.com/NEJM_AI/status/2056455808427155554"
        },
        {
          "title": "What Automation Bias is doing to Clinical Judgment.",
          "url": "https://algoadipose.substack.com/p/what-automation-bias-is-doing-to"
        },
        {
          "title": "Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among AI-Trained Physicians",
          "url": "https://www.medrxiv.org/content/10.1101/2025.08.23.25334280.full.pdf"
        },
        {
          "title": "NEJM AI",
          "url": "https://ai.nejm.org/"
        },
        {
          "title": "(PDF) Automation Bias in Large Language Model Assisted Diagnostic Reasoning Among AI-Trained Physicians",
          "url": "https://www.researchgate.net/publication/394976787_Automation_Bias_in_Large_Language_Model_Assisted_Diagnostic_Reasoning_Among_AI-Trained_Physicians"
        }
      ]
    },
    "The NEJM AI trial is Qazi et al., and it found that AI literacy training did not protect physicians from automation bias. Here's what the search turned up:\n\n- **Core trial:** A single-blind RCT ran from June to August 2025 with 44 physicians in Pakistan who had finished a 20-hour AI literacy program. They could voluntarily consult ChatGPT-4o. Accuracy was 84.9% in the control group and 73.3% in the group that received erroneous suggestions, a 14-point drop (a single-blind, randomized clinical trial from June 20 to August 15, 2025, involving 44 physicians in Pakistan who completed a 20-hour AI literacy training program; an adjusted 14.0-percentage-point reduction compared with the control group's 84.9%). The authors conclude that physicians demonstrate substantial automation bias when exposed to erroneous LLM recommendations, even with voluntary consultation and prior AI literacy training.\n- **Follow-up nudge trial:** A preprint on medRxiv (not yet peer-reviewed as far as the results show) reports a randomized trial of 72 physicians testing a behavioral nudge. It reports a 7.6 percentage-point gain over the control group in diagnostic reasoning, with the same AI-literacy preparation in both arms.\n- **Commentary:** An NEJM AI letter argues that generic AI-literacy training is insufficient, advocating instead for empirical automation bias stress tests and structural governance. A response letter from the trial authors argues that workflow design that shapes how and when AI output enters clinical reasoning also matters.\n- **Context:** A separate RCT found that the availability of an LLM to physicians as a diagnostic aid did not significantly improve clinical reasoning compared with conventional resources.\n\nCaveat: the core trial's sample is small (44 physicians, 264 cases), and the nudge result is from a preprint, so treat both as preliminary."
  ],
  "durationSeconds": 8.013578175000003,
  "searchCount": 1
}

{
  "url": "https://defensescoop.com/",
  "prompt": "List articles with dates from Nov 2 and Nov 3 2026, especially AI-related. Include headlines and URLs."
}

{
  "bytes": 139420,
  "code": 200,
  "codeText": "OK",
  "result": "Only one article in the page content is dated November 2, 2026, and none are dated November 3. It isn't AI-related.\n\n- **[Leonardo DRS tapped to support Army's high-energy laser program](https://defensescoop.com/2026/11/02/army-high-energy-laser-program-leonardo-drs-av/)** (by Jon Harper): The teaser says \"The company will be helping prime contractor AeroVironment under the E-HEL program.\" The date comes from the URL, since the page doesn't display it.\n\nThe AI-related pieces on the page are dated October 2026, outside your requested range, so I've left them out.",
  "durationMs": 4523,
  "url": "https://defensescoop.com/"
}

{
  "url": "https://breakingdefense.com/tag/artificial-intelligence/",
  "prompt": "List articles with dates from Nov 2 and Nov 3 2026. Headlines and URLs."
}

{
  "bytes": 118901,
  "code": 200,
  "codeText": "OK",
  "result": "The page content doesn't include any articles dated November 2 or November 3, 2026. The most recent items are from October 2026, based on their URL paths (`/2026/10/`). I can list those headlines and URLs if that would help.",
  "durationMs": 3768,
  "url": "https://breakingdefense.com/tag/artificial-intelligence/"
}

{
  "url": "https://openai.com/news/rss.xml",
  "prompt": "List all items with titles, links and publication dates."
}

{"bytes":821495,"code":200,"codeText":"OK","result":"The feed was truncated, so this covers only the items visible in the content. The last visible entry, \"Learning never stops: How AI makes learning continuous,\" has no visible date. All links below use the base `https://openai.com/index/` unless noted.\n\n**Nov–Oct 2026**\n1. \"Heimstaden is changing residential real estate management with AI\": heimstaden, Tue 03 Nov 2026\n2. \"Scaling Git at OpenAI\": scaling-git-at-openai, Mon 02 Nov 2026\n3. \"Introducing the Grid Protectors Program\": grid-protectors-program, Mon 02 Nov 2026\n4. \"Rewarding defenders with bigger bug bounties\": rewarding-defenders-with-bigger-bug-bounties, Mon 02 Nov 2026\n5. \"Preparing our next security sprint to harden OpenAI\": preparing-our-next-security-sprint-to-harden-openai, Mon 02 Nov 2026\n6. \"LifeVal\": lifeval, Mon 02 Nov 2026\n7. \"Qodo builds context into AI code review with Codex\": qodo-codex-plugin, Mon 02 Nov 2026\n8. \"OpenAI appoints Dan Driscoll as Senior Counselor for National Security Modernization\": dan-driscoll-joins-openai, Mon 02 Nov 2026\n9. \"Making it easier for websites to express AI training preferences\": helping-websites-express-ai-training-preferences, Fri 30 Oct 2026\n10. \"Community safety report and new protections for teens\": community-safety-report-and-new-protections-for-teens, Fri 30 Oct 2026\n11. \"Fair use benefits everyone\": fair-use-benefits-everyone, Fri 30 Oct 2026\n12. \"An updated Model Spec for more capable and beneficial AI\": updated-model-spec, Thu 29 Oct 2026\n13. \"How we detect frontier model misalignment\": how-we-detect-frontier-model-misalignment, Thu 29 Oct 2026\n14. \"How Ropes & Gray is developing AI for transactional diligence\": ropes-gray-ai-diligence, Thu 29 Oct 2026\n15. \"Credit Saison achieves 954% ROI in a ChatGPT Enterprise pilot\": credit-saison, Thu 29 Oct 2026\n16. \"OpenAI and ServiceNow expand partnership across enterprise workflows\": openai-servicenow-partnership-expansion, Wed 28 Oct 2026\n17. \"The future of the firm\": the-future-of-the-firm, Wed 28 Oct 2026\n18. \"Legora is building the agentic operating system for legal work\": legora, Wed 28 Oct 2026\n19. \"Retell uses OpenAI models to help power 100M monthly calls\": retell-ai, Tue 27 Oct 2026\n20. \"OpenAI expands partnership with Oracle to bring its apps to ChatGPT\": oracle-apps-in-chatgpt, Tue 27 Oct 2026\n21. \"How Check Point accelerates vulnerability research with Daybreak\": check-point-daybreak, Tue 27 Oct 2026\n22. \"Greptile takes bug detection beyond code review with GPT-6 Astra\": greptile-code-review-codex-astra, Mon 26 Oct 2026\n23. \"Working with academic communities to build scientific understanding\": building-scientific-understanding-with-academic-communities, Mon 26 Oct 2026\n24. \"GPT-6.1 Sol helps CodeRabbit strengthen security across complex codebases\": gpt-6-1-sol-coderabbit-code-security, Mon 26 Oct 2026\n25. \"ChatGPT's expanding world of work\": chatgpt-expanding-world-of-work, Mon 26 Oct 2026\n26. \"How Fanatics and OpenAI streamline the fan experience\": fanatics-streamline-fan-experience, Mon 26 Oct 2026\n27. \"How Ultrafast cut incident investigation from hours to minutes at OpenAI\": openai-cut-incident-investigation, Mon 26 Oct 2026\n28. \"Introducing GPT-6.1 Terra\": introducing-gpt-6-1-terra, Mon 26 Oct 2026\n29. \"Rapidly scaling online storage to serve over 1 billion ChatGPT users (Part II)\": scaling-storage-one-billion-users-part-two, Fri 23 Oct 2026\n30. \"Securing our frontier model training environment\": securing-our-frontier-model-training-environment, Fri 23 Oct 2026\n31. \"Anima helps clinics cut call waits by 75% with GPT-6 and GPT-Live\": anima, Fri 23 Oct 2026\n32. \"OpenAI and Poland's NASK partner to advance AI safety and security\": openai-nask-ai-safety-security-partnership, Fri 23 Oct 2026\n33. \"Build more responsive apps with the Decisions API\": decisions-api, Thu 22 Oct 2026\n34. \"What FDE means at OpenAI\": forward-deployed-engineering-means, Thu 22 Oct 2026\n35. \"Uber brings ChatGPT Work to all employees with OpenAI\": uber-chatgpt-work-rollout, Thu 22 Oct 2026\n36. \"How AT&T is rethinking in-house legal work with OpenAI\": att-legal, Wed 21 Oct 2026\n37. \"Broad access through consistent standards\": broad-access-through-consistent-standards, Wed 21 Oct 2026\n38. \"OpenAI models are coming to Google Cloud\": openai-models-google-cloud, Wed 21 Oct 2026\n39. \"Patch the Planet: global response coordination as agents uncover critical vulnerabilities\": coordinated-disclosure-of-critical-vulnerabilities, Wed 21 Oct 2026\n40. \"ChatGPT Ads expands to 26 new countries as over 100,000 advertisers have used the platform\": chatgpt-ads-expands-26-new-countries, Wed 21 Oct 2026\n41. \"Using thousands of AI agents to uncover new leads in biological data\": scaling-ai-research-for-complex-biological-data, Wed 21 Oct 2026\n42. \"Cloudflare links vulnerability discovery to defense with OpenAI\": cloudflare-cyber, Wed 21 Oct 2026\n43. \"How we built ChatGPT's novel ad stack for user trust and relevance\": building-chatgpt-ad-stack, Wed 21 Oct 2026\n44. \"Democratic governance of frontier AI, part II: Empowering cyber defenders\": empowering-cyber-defenders, Wed 21 Oct 2026\n45. \"Franchisee reconciles cash in 94% less time with ChatGPT Work\": ted-taylor-restaurant, Tue 20 Oct 2026\n46. \"Terminal X matches senior investor judgment 88.6% with GPT-6.1\": terminal-x, Tue 20 Oct 2026\n47. \"OpenAI acquires Orchestra Bio\": openai-to-acquire-orchestra-bio, Tue 20 Oct 2026\n48. \"Advancing coding in low-resource programming languages\": low-resource-programming-languages, Mon 19 Oct 2026\n49. \"How Itaú is building generative AI for its entire customer base\": itau-generative-ai, Fri 16 Oct 2026\n50. \"How Localiza reorganized work around generative AI\": localiza-generative-ai, Fri 16 Oct 2026\n51. \"How Grupo Boticário uses AI to strengthen human connections\": grupo-boticario,
… [10069 more characters in events.jsonl]

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && cat > parse.py <<'EOF'\nimport re,sys,xml.etree.ElementTree as ET\nf=sys.argv[1]\nt=ET.parse(f).getroot()\nfor it in t.iter('item'):\n    title=it.findtext('title','')\n    link=it.findtext('link','')\n    desc=it.findtext('description','')\n    ann=re.search(r'Announce Type:\\s*(\\w+)',desc)\n    ann=ann.group(1) if ann else '?'\n    if ann!='new': continue\n    aid=link.split('/abs/')[-1]\n    print(f\"{aid}\\t{title}\")\nEOF\nfor f in cs.LG cs.CL cs.CR cs.CY; do echo \"===== $f\"; python3 -I parse.py $f.xml; done 2>&1 | head -500",
  "description": "Extract new submission titles from feeds"
}

{"stdout":"===== cs.LG\n2611.00015\tOutput-Aware Block Influence: Jacobian-Lens Weighting for Depth Pruning\n2611.00130\tFB-MOAC: A Reinforcement Learning Algorithm for Forward-Backward Markov Decision Processes\n2611.00175\tInterpretable structural temperature scaling for calibrating graph neural networks and point-cloud segmentation\n2611.00236\tProLand: A New Infeasible Manifold Optimization Method for LoRA Fine-Tuning\n2611.00241\tIsoAlign: Isoform-Aware DNA-Protein Alignment via Joint-Embedding Predictive Architectures\n2611.00264\tKINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure\n2611.00281\tDELBERT-2: Pretrained Fingerprint Language Models for DEL Protein Binder Prediction\n2611.00284\tOCELOT: Planetary-Scale Species Distribution Modeling with Satellite Foundation Embeddings\n2611.00286\tQuantization of Large Models with Weight Outliers and Sparsity\n2611.00298\tA Framework for Task-Agnostic Counterfactual Fairness in Transformers through Activation Steering\n2611.00312\tRaMMOBO: Random Max-Margin Multi-Objective Bayesian Optimization\n2611.00316\tCyber-physical attack detection approaches in the wide-area measurement system\n2611.00333\tC3: Speech-Guided KV Retrieval for Long-Context SpeechLLM Inference\n2611.00337\tDecomposing Irregular Time Series into Interpretable Temporal Patterns with Mixture-of-Experts\n2611.00342\tDEPLOY-RL: Active Boundary Discovery and Conservative Certification for Deployable Reinforcement Learning in Safety-Critical Continuous Processes\n2611.00350\tOn the Limits of Test-Time Compute for Self-Evaluation\n2611.00374\tUnlearning by Extrapolating a Shrink-and-Heal Lookahead\n2611.00403\tMXCode: Vector Quantization for MX-Native Inference at Scale\n2611.00408\tTileWeave: Heterogeneous Tiling for Sparse Prefill on Mobile SoCs\n2611.00421\tRankLane: Efficient MoE Prefill on Accelerators with Ranked Expert Capacities\n2611.00422\tA Spectral Renormalization-Group View of Learning\n2611.00428\tDo Multimodal Models Decide Consistently on Equivalent Optical Spectra?\n2611.00433\tLocal Spatial TreeSHAP: Geographically Explainable AI Revealing Urbanization-Dependent Spatial Heterogeneity in Flood Resilience\n2611.00438\tStatistical Inference under Performativity: From Policy Feedback to Self-Evolving Systems\n2611.00444\tCLiS: Plug-and-Play Attention Acceleration for Video Diffusion on TPUs via Certified Stabilization\n2611.00448\tLearning to evolve by matching velocities\n2611.00452\tCompositional Self-Improvement: Promises and Pitfalls\n2611.00473\tStochastic learning flow: moment equations for stochastic gradient descent at finite step size\n2611.00477\tEnsemble Classification and Cancer-Specific Gene Signatures from Quality-Aware Hybrid Gene Selection in TCGA RNA-Seq data\n2611.00484\tWhere Causal Discovery Breaks on Real Data: Measuring the Assumptions One Property at a Time\n2611.00486\tInteger-Exact Microscaling: Running MXFP4 Language Models on INT8 Matrix Units\n2611.00491\tVoirDire: Counterfactual Calibration for Reliable LLM-as-a-Judge Aggregation\n2611.00497\tWhere Does EEG Help Wearable Freezing of Gait Detection?\n2611.00510\tBeyond Blackwell: Constrained Data Processing Inequalities\n2611.00511\tEfficient and Scalable Multi-View Masked Autoencoder for Heterogeneous Graph Self-Supervised Learning\n2611.00532\tWhen Does Spatial Cooperation Help? Contamination Regimes in Decentralized Online Spectrum Anomaly Learning\n2611.00554\tFrom Weeks to Hours: Fast and Principled SFT Data Generation for Reasoning LLMs\n2611.00562\tTabAbax: A Tabular Foundation Model Technical Report\n2611.00576\tThe First-Order Value of Free Covariates in Budgeted Risk Monitoring\n2611.00585\tConic Certification of Transformer Attention\n2611.00586\tDataset Mismatch Matters in Group Relative Policy Optimization for Reinforcement Learning from Verifiable Rewards\n2611.00588\tTVP: TV is Almost All You Need for Speculative Decoding\n2611.00589\tGuarded Compression of Adam Optimizer State with Shared-Gradient Bounds\n2611.00593\tDo Orthogonality Constraints Help Language-Model Training Beyond Sphere Optimization?\n2611.00606\tSparse Autoencoder Attribution Graphs Are Decided at the Margin\n2611.00614\tECG2Gene: Deep Learning-Based Germline Tumor Susceptibility Gene Risk Assessment Using Electrocardiograms\n2611.00636\tStructural Dual Adaptation for Safe Reinforcement Learning\n2611.00640\tBridging Singular Learning Theory and Mechanistic Interpretability at the Billion-Parameter Scale\n2611.00643\tSelecting LLM-Generated Hypotheses Raises Truth Beyond What an LLM Panel Expects: A Pre-registered Study on NAS-Bench-201 and HPOBench\n2611.00650\tHeirloom: Carrying a Phone's Personalization Across Base-Model Generations\n2611.00652\tInference First, Training Underneath: Layer-Granular LoRA Co-Serving with LayerLoom\n2611.00654\tGateTrim: Adaptive-Rank Quantization for Large Language Models\n2611.00670\tVersatile Graph Foundation Models from Frozen Time-Series Foundation Models via Parallel Flows\n2611.00686\tGenerative Forecasting from Coarse-Grained Observations: When Does Cascading Help?\n2611.00688\tShaped by What's Missing: Topological Invariance Simplification Discovers Behavioral Transitions\n2611.00716\tUncertainty Aware Quality-Diversity Optimization For Offline Biological Sequence Design\n2611.00742\tLearning hidden-state dynamics from unpaired snapshots with lift-project SDEs\n2611.00749\tPeptSol: A Translational Benchmark for Protected-Peptide Solubility in Drug Manufacturing\n2611.00786\tThe Tangled Web They Weave: Exploring Neural Representations with Directed Simplicial Complexes\n2611.00788\tTight Stochastic Sequential Covers for General VC Classes with Unknown i.i.d. Features\n2611.00794\tCrop Mapping Evaluation under Sampling Bias\n2611.00797\tPrivate Uniform Language Generation\n2611.00806\tStreaming Virtual Metrology via Lightweight Adaptation under Temporal Distribution Shifts\n2611.00875\tHamFormer: A Hamiltonian Flow-ba
… [10069 more characters in events.jsonl]

{
  "url": "https://www.itnews.com.au/news/artex-ai-hacking-framework-spreads-to-another-china-linked-group-630045",
  "prompt": "Publication date and all facts: which groups, numbers, who reported."
}

{
  "bytes": 112096,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026 (6:57 AM), by Juha Saarinen, iTnews.\n\n**Groups and actors**\n- **VAPOR PANDA**, a China-linked group, used the open-source ARTEX framework. CrowdStrike says it began on October 17.\n- **Storm-0940**, a China-aligned group, used ARTEX in the ConnectWise Cloud Backup compromise, per Microsoft.\n- **South Korean financial institution attacks:** CrowdStrike says these were likely the work of a China-based individual, not a confirmed state-linked group.\n- **Financially motivated extortion crews** also used ARTEX in incident response cases since late August, per Google's GTIG.\n- **Developer:** GitHub user Autumn-27 withdrew the original ARTEX code in October.\n\n**Key numbers**\n- VAPOR PANDA targeted more than 200 organisations worldwide in under two weeks.\n- CrowdStrike confirmed post-exploitation activity at nine organisations.\n- One intrusion's planning agents consumed roughly 1.4 billion input tokens.\n- Storm-0940 went from initial targeting to privileged cloud access in under three hours in several cases.\n- One GTIG-observed execution sequence generated 27 events in 23 seconds.\n\n**Reporters and researchers quoted**\n- **CrowdStrike:** reported the VAPOR PANDA campaign and the South Korean attacks.\n- **Microsoft:** attributed the ConnectWise compromise to Storm-0940.\n- **Google GTIG and Mandiant:** reported the code withdrawal and the wider threat activity. Rohit Nambiar of GTIG described the campaign as a \"warning shot\" from unsophisticated attackers and said there is no evidence of fully autonomous hacking yet.",
  "durationMs": 9559,
  "url": "https://www.itnews.com.au/news/artex-ai-hacking-framework-spreads-to-another-china-linked-group-630045"
}

{
  "url": "https://www.microsoft.com/en-us/security/blog/topic/threat-intelligence/",
  "prompt": "List recent posts with dates, especially Nov 2-3 2026 and anything on North Korea AI use or Digital Defense Report."
}

{
  "bytes": 328734,
  "code": 200,
  "codeText": "OK",
  "result": "**Nov 2-3, 2026:** Only one post falls in this window. There are no Nov 3 posts.\n\n- **Nov 2:** \"What exploited vulnerabilities have in common: A data-driven analysis of real-world attacks.\" It finds that real-world exploitation concentrates in a small, high-impact subset of CVEs.\n\n**North Korea AI use:** \"Tracking AI adoption in North Korean threat actor tradecraft\" (Oct 29). It covers North Korean actors expanding their use of AI, with varying levels of adoption, as they \"operationalize AI\" to speed up attacks.\n\n**Digital Defense Report:** No post on the page covers it. The only reference is a navigation link to the 2025 Microsoft Digital Defense Report.\n\n**Other recent posts (newest first):**\n\n- **Oct 30:** \"Inside a malicious Claude Code-branded extension and its persistent SSH backdoor\" analyzes a malicious extension and its backdoor, with detection and remediation guidance.\n- **Oct 30:** \"From help desk impersonation to AD CS abuse: Investigating ESC1 and ESC8 intrusion paths\" traces an intrusion that began with Teams support impersonation and led to Certificate Services abuse.\n- **Oct 21:** \"AI-driven, large-scale nation-state campaign using ARTEX enables supply chain compromise\" covers Storm-0940's use of agentic AI in a ConnectWise supply chain compromise.\n- **Oct 14:** \"The hidden network: Inside the phishing infrastructure ecosystem powering global cybercrime\" describes a Chinese-language phishing kit ecosystem (Storm-2990) and a marketplace (Storm-3119).\n- **Sep 30:** \"Unauthenticated command injection on internet-facing mail servers: tracking CVE-2026-73570\" covers exploitation of this Zimbra vulnerability and mitigation guidance.\n- **Sep 29:** \"Phishing Abuses RMM Tools for Persistent Access\" describes campaigns that used MSP360 to deploy ScreenConnect for redundant remote access.\n- **Sep 29:** \"Star Blizzard refines phishing and malware delivery with the RedFlick technique\" covers Russian actor Star Blizzard's evasion and a new malware delivery method.\n- **Sep 28:** \"NeedyMantis: Unpacking a post-compromise malware family used in targeted operations\" analyzes a modular malware framework used in targeted intrusions.\n- **Sep 25:** \"Storm-3168: Agentic-driven cloud attacks using compromised service principals\" covers Azure reconnaissance, resource deletion, and credential access.\n- **Sep 24:** \"Beyond the ransomware: Tracking Storm-2570's consistent tradecraft across deployments\" covers a ransomware affiliate's consistent tools across several ransomware families.",
  "durationMs": 6810,
  "url": "https://www.microsoft.com/en-us/security/blog/topic/threat-intelligence/"
}

{
  "url": "https://ai.nejm.org/doi/full/10.1056/AIoa2501001",
  "prompt": "Give the publication date, authors, trial design, sample size, and all primary outcome numbers with baselines."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 132,
  "url": "https://ai.nejm.org/doi/full/10.1056/AIoa2501001"
}

{
  "command": "cd /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results && grep -niE \"alignment|align |safet|sandbag|deceptive|deception|scheming|sabotage|interpretab|sparse autoencoder|SAE|circuit|probe|monitor|reward hack|jailbreak|refusal|unlearn|eval |evaluat|benchmark|RLHF|reasoning model|chain-of-thought|CoT |faithful|sycophan|situational|introspect|red.team|guardrail|misalign|honest|emergent|scaling law|frontier\" bcqfj8vgg.txt | head -150",
  "description": "Filter titles for safety and eval keywords"
}

{
  "stdout": "4:2611.00175\tInterpretable structural temperature scaling for calibrating graph neural networks and point-cloud segmentation\n6:2611.00241\tIsoAlign: Isoform-Aware DNA-Protein Alignment via Joint-Embedding Predictive Architectures\n14:2611.00333\tC3: Speech-Guided KV Retrieval for Long-Context SpeechLLM Inference\n15:2611.00337\tDecomposing Irregular Time Series into Interpretable Temporal Patterns with Mixture-of-Experts\n16:2611.00342\tDEPLOY-RL: Active Boundary Discovery and Conservative Certification for Deployable Reinforcement Learning in Safety-Critical Continuous Processes\n17:2611.00350\tOn the Limits of Test-Time Compute for Self-Evaluation\n18:2611.00374\tUnlearning by Extrapolating a Shrink-and-Heal Lookahead\n40:2611.00576\tThe First-Order Value of Free Covariates in Budgeted Risk Monitoring\n46:2611.00606\tSparse Autoencoder Attribution Graphs Are Decided at the Margin\n49:2611.00640\tBridging Singular Learning Theory and Mechanistic Interpretability at the Billion-Parameter Scale\n59:2611.00749\tPeptSol: A Translational Benchmark for Protected-Peptide Solubility in Drug Manufacturing\n62:2611.00794\tCrop Mapping Evaluation under Sampling Bias\n67:2611.00917\tBenchmarking Classical Machine Learning Models for Shading-Fault Detection in Rooftop Photovoltaic Systems Using Real Sensor Data\n69:2611.00920\tWhat matters in classical machine learning for non-intrusive load monitoring? A factorial benchmark on REFIT with validation on unseen houses\n73:2611.00999\tISBC: Interpretable Sparse Binary Coding of Pretrained Text Embeddings\n95:2611.01239\tMathematical Formulation and Comparative Performance Evaluation of Machine Learning Algorithms for Maize Land Suitability Prediction\n100:2611.01272\tGeometry of Confabulation and Refusal in Small Language Models\n106:2611.01322\tAlignment Flywheel-Guided Suppression Patching for Interactionless Inverse Reinforcement Learning\n121:2611.01447\tCorrectness and Predictive Uncertainty in Bayesian TSK Fuzzy Regression: A Reproducible Evaluation on Tabular and Building-Meter Data\n128:2611.01525\tInformedXRD: Reproducible Benchmarks and Physics-Informed Evaluation for Powder Diffraction Symmetry Classification\n132:2611.01564\tMeta-memorization and memorization scaling laws in transformers\n134:2611.01568\tSearch-Aware On-Policy Self-Distillation with Sibling Alignment for Generative Recommendation\n154:2611.01740\tHow Does Chain-of-Thought Supervision Teach Models to Reason? A Theoretical Analysis\n158:2611.01769\tSilent Reward and Environment Defects in EV Charging Simulation Benchmarks: A Diagnostic Checklist\n166:2611.01898\tRobust Remote ECG Monitoring under Energy Constraints: Anomaly Filtering versus Predictive Uncertainty\n179:2611.02052\tSame Function, Different Gradients: Evaluating Gradient Reliability under Reparameterization\n188:2611.02132\tTSSDA: An Autonomous Agent for Constructing a Time-Series Text-to-SQL Benchmark\n200:2611.02248\tMetamorphic Testing for Evaluating Robustness of Sentiment Analysis Models\n203:2611.02270\tHinted Scaling Laws\n206:2611.02278\tConcise-9B: Removing the Slack from a Reasoning Model's Thinking\n217:2611.02413\tA Scientific Claim Stability Framework for Evaluating MRI Morphometry Pipelines\n232:2611.02576\tBeyond $L_\\infty$-Norm Sets: Synthesizing Interpretable Non-Uniform Uncertainty Sets for Evaluation-Time State-Adversarial Robustness\n234:2611.02620\tAdaptive Localization of Knowledge Negation for Continual LLM Unlearning\n236:2611.02634\tEvolving Explanations: Complexity-Adaptive Refinement of Faithful Explanations for Symbolic Regression\n248:2611.02774\tDIKT: A Diagnostic and Interpretable Knowledge Tracing Framework for Prediction and Model-based Learning Analysis\n259:2611.02842\tNIR: Approximate Neural Instance Retrieval for ALCIQ\n260:2611.02856\tKolmogorov-Arnold Networks vs. Multi-Layer Perceptrons: A Rigorous Statistical Benchmark on Clinical Tabular Data\n266:2611.02917\tUnimodal Augmentation-based SSL Objectives Induce Cross-Modal Alignment\n276:2611.03039\tTSB-SEG: A Systematic Time-Series Segmentation Benchmark\n278:2611.03101\tDiagonal Equivalence in State Space Models: Characterization, Retrieval Rank, and Selective Extensions\n285:2611.03171\tViAdminShift: A Vietnamese Benchmark for Event-Level Knowledge Updates Built from the 2025 Administrative Reform\n290:2611.03244\tForecasting How RLHF Responds to Reward-Model Edits Before Training\n311:2611.03420\tTemporal Island Sparse Autoencoders for Interpreting Clinical Time-Series Models\n315:2611.03454\tOnline Class Posteriors for Interpretable and Controllable Discrete Diffusion\n318:2611.03486\tA Hybrid Visitor Prediction Framework using Interpretable Temporal features, Integrating IQR and Anomaly Detection in Lakes in Nebraska\n327:2611.03592\tEvaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models\n331:2611.03614\tBenchmark Prediction with Sparse and Unpaired Cached Responses\n332:2611.03623\tThought-deciphering via hierarchical EEG-to-text alignment\n340:2611.00319\tGAVAGAI: Referential Alignment for Infant-Scale Vision-Language Models via Balanced Optimal Transport\n344:2611.00420\tCircuit Oracle: Automating Attribution Graph Analysis via Natural-Language Queries\n350:2611.00536\tDual-Axis Policy Entailment: A Benchmark for Policy-Change Reasoning\n351:2611.00555\tDistinguishing among reasoning levels of GPT 5.5 Pro via a grammar lens benchmark\n360:2611.00755\tDuSE-Bench: Benchmarking Joint Reasoning over Evolving Dialogue and Documents\n366:2611.00883\tRandom Is Almost Enough? Stable and Low-Cost Benchmark Compression via BestRand\n368:2611.00935\tLabadain-MedQA: A Tetun Medical QA Dataset for Fine-Tuning and Evaluating Large Language Models\n376:2611.01123\tDo Earnings Calls Help Predict Financial Restatements? Evaluating Text Beyond Public Firm Information\n381:2611.01261\tMedAstra: ASR-less Speech Retrieval with Diagnostic Grounding for Medical QA\n390:2611.01370\tXDecideBench
… [2910 more characters in events.jsonl]

{
  "command": "cd /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results && awk '/^===== cs.CR/,0' bcqfj8vgg.txt | head -120",
  "description": "Show cs.CR and cs.CY sections"
}

{
  "stdout": "===== cs.CR\n2611.00138\tKerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents\n2611.00367\tWhen appearance and motion disagree: evaluating class--motion consistency against disguised uncrewed surface vessels\n2611.00489\tThreat Modeling Intimate Partner Abuse in Agentic Systems\n2611.00512\tPractical Preimages for 19- and 20-Step SHA-256 with Standard Padding\n2611.00587\tPrice is Only the Symptom: Understanding and Analyzing Economic-State Manipulation Vulnerabilities in DeFi\n2611.00594\tBeyond Sensitive APIs: Detecting Access Control Flaws at Sensitive Callsites in Android Firmware\n2611.00713\tAdversarial Robustness Is Not Zero-Day Generalization: A Controlled Evaluation of Flow-Based Intrusion Detectors on Corrected CIC-IDS2017\n2611.00725\tThe Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents\n2611.00729\tAgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution\n2611.00738\tCross-Evidence Authorization State Learning for Runtime Detection of Broken Object-Level Authorization in Black-Box Web Applications\n2611.00839\tIntent-Bound Authorization for Cryptocurrency Withdrawals Under Backend Compromise\n2611.00923\tIllusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems via Behavior-Preserving Obfuscation",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.techpolicy.press/how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance/",
  "prompt": "What new research or data does this report? Give date, author, any numbers, methodology, and what underlying study/document it is based on."
}

{
  "bytes": 228135,
  "code": 200,
  "codeText": "OK",
  "result": "**Short answer:** The piece presents no new quantitative data, surveys, or experiments. It is a qualitative comparative analysis of public policy statements.\n\n- **Publication:** Tech Policy Press, November 2, 2026 (Analysis section)\n- **Authors:** Jason Pielemeier, Jhalak M. Kakkar, Elonnai Hickok, Sudisha Mishra, and Revati Vaidya. They write as part of the Multistakeholder Approach to Participation in AI Governance (MAP-AI) project and state that their views do not represent CCG, GNI, or GNI members.\n- **Methodology:** The authors reviewed the recent public pronouncements of five AI developers: Anthropic, Google, Meta, Microsoft, and OpenAI. They mapped each company's positions onto three areas: Pacing, Development/Deployment/Disclosure, and Collective Action. The supporting comparison spreadsheet is linked, but it is not part of the article.\n- **Underlying documents:**\n  - Anthropic: \"Advanced AI Framework,\" \"Policy on the AI Exponential,\" and Dario Amodei's \"We Must Pace the Frontier\"\n  - OpenAI: \"Public Policy Agenda\" and Chris Lehane's \"reverse federalism\" essay\n  - Google: \"A Pragmatic Approach to AI Governance in America\"\n  - Microsoft: \"Governing AI: A Blueprint for the Future\" (2023)\n  - Meta: Mark Zuckerberg's \"The Future Is for Everyone\"\n- **Specific figures cited (from company proposals, not new data):**\n  - Anthropic proposes a 15-day window for reporting stolen weights and realized harms, and a risk report every six months.\n  - Google's proposed FARO would run annual audits.\n  - Microsoft proposes annual transparency reports.\n- **Limitations:** The authors call this an \"initial compilation\" that will be updated over time. It relies only on public statements, and the article notes that some positions were drawn from press reporting, such as Politico and Fortune, rather than primary documents.",
  "durationMs": 7210,
  "url": "https://www.techpolicy.press/how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance/"
}

{
  "command": "node scripts/fetch.js \"https://techcrunch.com/2026/11/02/anthropic-warns-that-its-very-close-to-rsi-capability-aka-self-building-ai/\" 2>&1 | head -120",
  "description": "Fetch TechCrunch Anthropic RSI article"
}

{"stdout":"HTTP 200 · https://techcrunch.com/2026/11/02/anthropic-warns-that-its-very-close-to-rsi-capability-aka-self-building-ai/ · text/html\nAnthropic warns that it's very close to RSI capability, aka self-building AI | TechCrunch\n\n–:–:–:–\n\nBuy One Founder Summit Ticket, Get a Second for Free. Register now.\n\nFounder Summit begins Nov. 4, 9:00 a.m. ET. Get your pass savings & deals before it starts. REGISTER HERE.\n\nClose\n\nImage Credits: TechCrunch/AI generated\n\nAI\n\n# Anthropic warns that it’s very close to RSI capability, aka self-building AI\n\nJulie Bort\n\n2:14 PM PST · November 2, 2026\n\nWhile much attention has focused on the updated financials Anthropic revealed in its revised S-1/A on Monday (revenue is soaring, but so are expenses), the AI lab dropped another little bombshell in the fine print.\n\nThe filing seems to warn that the company is on the cusp of creating a model capable of recursive self-improvement (RSI).\n\nRSI is the point at which AI grows so good at training itself that it spawns a dramatic acceleration of AI capabilities. To the AI doomers, RSI represents the cataclysm from which there is no return, in which AI builds itself into something powerful enough that it slips beyond human control and may be indifferent to the damage it causes while achieving its goals.\n\nTo AI enthusiasts, RSI, or some version of AI reliably using itself to improve, represents the technology’s promise, where it becomes a tool of unimaginable productivity, scientific discovery, and more.\n\nAnthropic seems to believe that RSI is both a promise and a peril. It says in the S-1 that it uses AI in its R&D, but it cautions: “Using AI to help build more capable AI could also pose a considerable safety risk, particularly if it sharply accelerates the pace of progress. This is one of the areas covered by our Responsible Scaling Policy, which sets out our plans to monitor and mitigate the risks as we approach what has been termed ‘recursive self-improvement.’”\n\nWhen the term RSI became popular earlier this year , many believed it was a buzzword or, at best, a goal too hard to achieve, define, or prove.\n\nBut on Monday, Anthropic added new statements to its Risk Factors section, saying 1) it has already used AI to develop new models whose leaps in capability it didn’t recognize at the time, and 2) it may soon meet its own definition of RSI (bold emphasis ours, below):\n\nIn addition, our increasing use of AI systems to accelerate our own research and development may cause the capabilities of our models to advance more rapidly than our ability to develop, validate, and implement corresponding safety, alignment, and security measures. As a result, we have in the past not identified , and may in the future not identify, a significant acceleration in our rate of development until after it has occurred.\n\nFor example, our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy’s definition of “dramatically accelerated progress attributable to AI.” We have not designated any of our current models as exceeding this threshold, and we continue to assess the underlying data.\n\nHowever, Anthropic also said in the filing that none of its models have crossed this RSI threshold yet and that it is promising to keep humans in the R&D process for the foreseeable future. “We do not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding, if and when that becomes technically possible. Accordingly, we are considering updates to our Responsible Scaling Policy to keep humans in control of frontier model development at Anthropic.”\n\nSkeptics might point out that an S-1 functions as both disclosure and marketing, and that claims of being close to a model so powerful that it can build itself could fall into the latter category.\n\nNevertheless, there’s no question that Claude’s capabilities, especially in terms of coding, math, and cybersecurity, have grown leaps and bounds this year. If Anthropic thinks the possibility of RSI is close, maybe we should believe it and act — perhaps govern — accordingly.\n\nTopics\n\nAI , Anthropic , RSI , TC\n\nWhen you purchase through links in our articles, we may earn a small commission . This doesn’t affect our editorial independence.\n\nJulie Bort\n\nVenture Editor\n\nJulie Bort is the Startups/Venture Desk editor for TechCrunch. \r\n\r\n\nYou can contact or verify outreach from Julie by emailing [email protected] or via @Julie188 on X.\n\nView Bio\n\nNovember 4\n\nBoston\n\nBuy One Pass, Get a Second Free\n\nCover more ground at TechCrunch’s ultimate founder bootcamp of the year by bringing your co-founder or partner for free\n\nBook before the BOGO deal expires\n\nRegister Now\n\n# Most Popular\n\n-\n\n#\nAnthropic warns that it’s very close to RSI capability, aka self-building AI\n\n- Julie Bort\n\n-\n\n#\nAnthropic expected to receive high ‘junk’ rating from credit agencies following IPO, FT report says\n\n- Lucas Ropek\n\n-\n\n#\nGoogle’s first data center satellite is online and writing poetry\n\n- Tim Fernholz\n\n-\n\n#\nBinance pauses withdrawals as hackers suspected of stealing billions in crypto\n\n- Zack Whittaker\n\n-\n\n#\nAs search traffic dries up, Reddit announces it’s shifting to a logged-in experience\n\n- Sarah Perez\n\n-\n\n#\nAI execs may be too out of touch to build for the general public\n\n- Amanda Silberling\n\n-","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":70,"oldLines":3,"newStart":70,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:08:47.518Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/
… [10069 more characters in events.jsonl]

{
  "query": "\"November 2, 2026\" OR \"November 3, 2026\" AI health FDA announcement",
  "mode": "extended"
}

{
  "query": "\"November 2, 2026\" OR \"November 3, 2026\" AI health FDA announcement",
  "results": [
    {
      "tool_use_id": "srvtoolu_01SJGXZYNKXLdYDMPVrjLpdW",
      "content": [
        {
          "title": "FDA Seeks Public Feedback to Inform Regulatory Approach for Generative AI-Enabled Medical Devices",
          "url": "https://www.fda.gov/news-events/press-announcements/fda-seeks-public-feedback-inform-regulatory-approach-generative-ai-enabled-medical-devices"
        },
        {
          "title": "FDA Expands AI Capabilities and Completes Data Platform Consolidation",
          "url": "https://www.fda.gov/news-events/press-announcements/fda-expands-ai-capabilities-and-completes-data-platform-consolidation"
        },
        {
          "title": "FDA Expands Artificial Intelligence Capabilities with Agentic AI Deployment",
          "url": "https://www.fda.gov/news-events/press-announcements/fda-expands-artificial-intelligence-capabilities-agentic-ai-deployment"
        },
        {
          "title": "FDA Proposes Framework to Advance Credibility of AI Models Used for Drug and Biological Product Submissions",
          "url": "https://www.fda.gov/news-events/press-announcements/fda-proposes-framework-advance-credibility-ai-models-used-drug-and-biological-product-submissions"
        },
        {
          "title": "FDA announces hands-off approach to some health wearables",
          "url": "https://www.foxbusiness.com/media/fda-commissioner-says-non-medical-grade-wearable-data-exempt-regulation"
        },
        {
          "title": "FDA announces sweeping changes to oversight of wearables, AI-enabled devices",
          "url": "https://www.statnews.com/2026/01/06/fda-pulls-back-oversight-ai-enabled-devices-wearables/"
        },
        {
          "title": "FDA Limits Oversight of AI Health Software and Wearables",
          "url": "https://telehealth.org/news/fda-clarifies-oversight-of-ai-health-software-and-wearables-limiting-regulation-of-low-risk-devices/"
        },
        {
          "title": "This Week at FDA: New ConOps for drug inspections, AI policy proposal, and more",
          "url": "https://www.raps.org/resource/this-week-at-fda-new-conops-for-drug-inspections-ai-policy-proposal-and-more.html"
        },
        {
          "title": "FDA paves way for more consumer wearables to hit the market, eases regulation of AI-enabled devices",
          "url": "https://www.fiercehealthcare.com/digital-health/fda-paves-way-more-consumer-wearables-hit-market"
        },
        {
          "title": "FDA exempts more wearable, AI features from oversight",
          "url": "https://www.medtechdive.com/news/fda-exempts-wearable-ai-features-guidance/809099/"
        }
      ]
    },
    "I didn't find any results dated November 2 or 3, 2026. The search was a simplified version of your query, since the exact OR string wasn't used.\n\nThe closest recent item is a RAPS \"This Week at FDA\" roundup, listed as 3 days old. It reports that Sen. Bill Cassidy (R-LA), the outgoing chair of the Senate Committee on Health, Education, Labor and Pensions (HELP), has released a discussion draft of a bill, called the Protecting Americans Through Intelligent, Ethical, and Transparent Artificial Intelligence in Health Care Act, or PATIENT AI Act. The draft would address when AI-based health tools fall under FDA or ONC oversight. Because the item is only dated relative to today, its exact publication date is uncertain.\n\nOther FDA AI-health items in the results are older:\n- An FDA request for public feedback on generative AI-enabled medical devices, dated August 18, 2026.\n- Elsa 4.0 and the HALO data platform, announced May 6, 2026.\n- Wearable and clinical decision support guidance announced in early January 2026."
  ],
  "durationSeconds": 5.840870293000014,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://openai.com/index/grid-protectors-program/\" 2>&1 | head -80",
  "description": "Fetch OpenAI Grid Protectors Program page"
}

{"stdout":"HTTP 403 · https://openai.com/index/grid-protectors-program/ · text/html","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":72,"oldLines":3,"newStart":72,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:08:55.407Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7f44935a6a031c3b\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_017EfBg5sjqRZRJzhH4V5rGZ\",\"duration_ms\":39,\"input\":{\"command\":\"cd /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results && awk '/^===== cs.CR/,0' bcqfj8vgg.txt | head -120\",\"description\":\"Show cs.CR and cs.CY sections\"},\"response\":{\"stdout\":\"===== cs.CR\\n2611.00138\\tKerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents\\n2611.00367\\tWhen appearance and motion disagree: evaluating class--motion consistency against disguised uncrewed surface vessels\\n2611.00489\\tThreat Modeling Intimate Partner Abuse in Agentic Systems\\n2611.00512\\tPractical Preimages for 19- and 20-Step SHA-256 with Standard Padding\\n2611.00587\\tPrice is Only the Symptom: Understanding and Analyzing Economic-State Manipulation Vulnerabilities in DeFi\\n2611.00594\\tBeyond Sensitive APIs: Detecting Access Control Flaws at Sensitive Callsites in Android Firmware\\n2611.00713\\tAdversarial Robustness Is Not Zero-Day Generalization: A Controlled Evaluation of Flow-Based Intrusion Detectors on Corrected CIC-IDS2017\\n2611.00725\\tThe Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents\\n2611.00729\\tAgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution\\n2611.00738\\tCross-Evidence Authorization State Learning for Runtime Detection of Broken Object-Level Authorization in Black-Box Web Applications\\n2611.00839\\tIntent-Bound Authorization for Cryptocurrency Withdrawals Under Backend Compromise\\n2611.00923\\tIllusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems via Behavior-Preserving Obfuscation\",\"stderr\":\"\",\"interrupted\":false,\"isImage\":false,\"noOutputExpected\":false}}"," {\"t\":\"2026-11-03T11:08:56.191Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_016UqAwrHKWwqcaUNgbCCnWm\",\"duration_ms\":7211,\"input\":{\"url\":\"https://www.techpolicy.press/how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance/\",\"prompt\":\"What new research or data does this report? Give date, author, any numbers, methodology, and what underlying study/document it is based on.\"},\"response\":{\"bytes\":228135,\"code\":200,\"codeText\":\"OK\",\"result\":\"**Short answer:** The piece presents no new quantitative data, surveys, or experiments. It is a qualitative comparative analysis of public policy statements.\\n\\n- **Publication:** Tech Policy Press, November 2, 2026 (Analysis section)\\n- **Authors:** Jason Pielemeier, Jhalak M. Kakkar, Elonnai Hickok, Sudisha Mishra, and Revati Vaidya. They write as part of the Multistakeholder Approach to Participation in AI Governance (MAP-AI) project and state that their views do not represent CCG, GNI, or GNI members.\\n- **Methodology:** The authors reviewed the recent public pronouncements of five AI developers: Anthropic, Google, Meta, Microsoft, and OpenAI. They mapped each company's positions onto three areas: Pacing, Development/Deployment/Disclosure, and Collective Action. The supporting comparison spreadsheet is linked, but it is not part of the article.\\n- **Underlying documents:**\\n  - Anthropic: \\\"Advanced AI Framework,\\\" \\\"Policy on the AI Exponential,\\\" and Dario Amodei's \\\"We Must Pace the Frontier\\\"\\n  - OpenAI: \\\"Public Policy Agenda\\\" and Chris Lehane's \\\"reverse federalism\\\" essay\\n  - Google: \\\"A Pragmatic Approach to AI Governance in America\\\"\\n  - Microsoft: \\\"Governing AI: A Blueprint for the Future\\\" (2023)\\n  - Meta: Mark Zuckerberg's \\\"The Future Is for Everyone\\\"\\n- **Specific figures cited (from company proposals, not new data):**\\n  - Anthropic proposes a 15-day window for reporting stolen weights and realized harms, and a risk report every six months.\\n  - Google's proposed FARO would run annual audits.\\n  - Microsoft proposes annual transparency reports.\\n- **Limitations:** The authors call this an \\\"initial compilation\\\" that will be updated over time. It relies only on public statements, and the article notes that some positions were drawn from press reporting, such as Politico and Fortune, rather than primary documents.\",\"durationMs\":7210,\"url\":\"https://www.techpolicy.press/how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance/\"}}"," {\"t\":\"2026-11-03T11:08:56.457Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"afb0755d99de3a80e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://openai.com/index/lifeval/\" 2>&1 | head -100",
  "description": "Fetch OpenAI LifeVal page"
}

{
  "stdout": "HTTP 403 · https://openai.com/index/lifeval/ · text/html",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://therecord.media/feed",
  "prompt": "List items with publication dates from Nov 2 and Nov 3 2026, with titles and URLs. Flag AI-related ones."
}

{
  "bytes": 5214,
  "code": 200,
  "codeText": "OK",
  "result": "**Nov 3, 2026**\n- \"UK faces 'unprecedented rise' in cyberattacks in coming months, warns cyber chief\": https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months\n\n**Nov 2, 2026**\n- \"Largest crypto exchange in Brazil confirms cyberattack as millions flow out of platform\": https://therecord.media/mercado-bitcoin-brazil-cryptocurrency-heist\n- \"Michigan State cyber incident claimed by ransomware gang behind recent hospital attack\": https://therecord.media/michigan-state-university-byod-gang-cyber-incident\n- \"Polymarket pledges to give $3.9 million back to victims after site compromise\": https://therecord.media/polymarket-returning-funds-to-customers-after-site-compromise\n- \"Russia's statistics agency confirms cyberattack claimed by Belarusian and Ukrainian hackers\": https://therecord.media/hackers-ukraine-belarus-russia\n\n**AI-related:** None. The feed content does not mention AI in any of these items.",
  "durationMs": 4549,
  "url": "https://therecord.media/feed"
}

{
  "command": "cd /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results && sed -n '490,600p' bcqfj8vgg.txt",
  "description": "Show tail of candidate list"
}

{
  "stdout": "2611.00367\tWhen appearance and motion disagree: evaluating class--motion consistency against disguised uncrewed surface vessels\n2611.00489\tThreat Modeling Intimate Partner Abuse in Agentic Systems\n2611.00512\tPractical Preimages for 19- and 20-Step SHA-256 with Standard Padding\n2611.00587\tPrice is Only the Symptom: Understanding and Analyzing Economic-State Manipulation Vulnerabilities in DeFi\n2611.00594\tBeyond Sensitive APIs: Detecting Access Control Flaws at Sensitive Callsites in Android Firmware\n2611.00713\tAdversarial Robustness Is Not Zero-Day Generalization: A Controlled Evaluation of Flow-Based Intrusion Detectors on Corrected CIC-IDS2017\n2611.00725\tThe Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents\n2611.00729\tAgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution\n2611.00738\tCross-Evidence Authorization State Learning for Runtime Detection of Broken Object-Level Authorization in Black-Box Web Applications\n2611.00839\tIntent-Bound Authorization for Cryptocurrency Withdrawals Under Backend Compromise\n2611.00923\tIllusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems via Behavior-Preserving Obfuscation",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.techpolicy.press/europe-and-canada-plot-a-digital-alliance-as-us-ties-fray/",
  "prompt": "Date, author, and what new facts/documents/agreements does it report? Any dates and official documents cited?"
}

{
  "bytes": 157907,
  "code": 200,
  "codeText": "OK",
  "result": "**Date:** The article is dated November 2, 2026. It covers the EU-Canada summit in Montreal on October 30, 2026.\n\n**Author:** Mark Scott, Contributing Editor at Tech Policy Press.\n\n**New facts and agreements reported:**\n\n- **Digital trade agreement:** Negotiations on an EU-Canada digital trade pact have concluded, but it has not entered into force. It complements the broader EU-Canada trade deal and covers cross-border data flows, digital transactions, consumer protection, and regulatory cooperation.\n- **Digital services trade:** Bilateral trade in digital services was almost €20 billion in 2025, according to European Commission data.\n- **High-performance computing:** Canada joined the European High Performance Computing Joint Undertaking (EuroHPC JU), which gives Canadian businesses access to its supercomputing infrastructure.\n- **Competition pact:** The two sides agreed a separate pact between their competition authorities.\n- **Regulatory cooperation:** Commitments include working toward mutual recognition of digital identities and credentials, AI safety assessments, and cybersecurity arrangements.\n- **Election integrity:** The two sides will cooperate on election integrity and on countering foreign information manipulation and interference ahead of elections planned for 2027.\n- **Infrastructure:** Plans cover subsea cable links between Canada, Europe, and Asia, improved Canadian access to Europe's satellite navigation and communications systems, and joint AI, high-performance computing, and cloud initiatives.\n- **Associate membership:** Carney announced that Canada is moving toward becoming the EU's first \"associate member,\" though the article notes this remains a proposal.\n\n**Dates and official documents cited:**\n\n- Joint statement, \"Building Together\" Alliance, Canada and the EU (October 30, 2026), which refers to an \"Alliance for the Future.\"\n- Carney's remarks concluding the EU-Canada summit (October 30, 2026).\n- European Commission announcement on concluding digital trade negotiations (October 30, 2026).\n- The Economist's leader on Carney's \"Middle Powers\" strategy (October 15, 2026), cited as background.\n\nThe article notes that only three of the announced items had moved beyond the proposal stage: the digital trade negotiations, the competition authority pact, and Canada's EuroHPC participation. Most other commitments remain proposals.",
  "durationMs": 8817,
  "url": "https://www.techpolicy.press/europe-and-canada-plot-a-digital-alliance-as-us-ties-fray/"
}

{
  "url": "https://simonwillison.net/atom/everything/",
  "prompt": "List entries dated Nov 2 or Nov 3 2026 with titles, URLs, and whether they concern prompt injection or agent security."
}

{
  "bytes": 112904,
  "code": 200,
  "codeText": "OK",
  "result": "Four entries are dated Nov 2 or Nov 3, 2026:\n\n1. **\"I discovered a sound that leaks your exact location (and it's everywhere) - YouTube\"** (Nov 3)\n   https://simonwillison.net/2026/Nov/3/a-sound-that-leaks-your-exact-location/\n   Privacy/OSINT. It covers inferring a video's location from aircraft noise. Not prompt injection or agent security.\n\n2. **\"October sponsors-only newsletter\"** (Nov 3)\n   https://simonwillison.net/2026/Nov/3/october-newsletter/\n   Newsletter announcement. Not prompt injection or agent security.\n\n3. **\"llm 0.37\"** (Nov 2)\n   https://simonwillison.net/2026/Nov/2/llm/\n   Release notes for the LLM CLI and Python library. Not prompt injection or agent security.\n\n4. **\"The U.S. Census Bureau and \"Super Intelligence\"\"** (Nov 2)\n   https://simonwillison.net/2026/Nov/2/census-bureau-super-intelligence/\n   Analysis of changes to the Census Bureau's AI adoption survey. Not prompt injection or agent security.\n\nNone of the four entries concern prompt injection or agent security.\n\n[WebFetch note: this page's text is 112810 characters long and the answer above covers only characters 0 to 100000; the final 12810 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 6253,
  "url": "https://simonwillison.net/atom/everything/"
}

{
  "url": "https://openai.com/index/lifeval/",
  "prompt": "What is LifeVal? Give all benchmark numbers, model scores, dataset size, methodology and the publication date."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 66,
  "url": "https://openai.com/index/lifeval/"
}

{
  "query": "export controls chips China AI November 2 3 2026",
  "mode": "extended"
}

{
  "query": "export controls chips China AI November 2 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01SQyAP6xQWjECDcEhPRZS1H",
      "content": [
        {
          "title": "China proposes export controls on its advanced AI models and chip designs",
          "url": "https://thenextweb.com/news/china-ai-export-controls-draft"
        },
        {
          "title": "China considers export controls on AI, chips",
          "url": "https://www.semafor.com/article/10/18/2026/china-mulls-ai-export-rules"
        },
        {
          "title": "China Plans AI Export Curbs to Exert Control Over Key Tech - Bloomberg",
          "url": "https://www.bloomberg.com/news/articles/2026-10-16/china-proposes-export-controls-on-ai-models-chips-and-agents"
        },
        {
          "title": "The U.S. banned Nvidia's best chips from going to China. Now it's trying to close a crucial loophole",
          "url": "https://www.cnbc.com/2026/08/19/china-ai-nvidia-chips-us-export-controls.html"
        },
        {
          "title": "China Proposes AI Export Controls on Models and Chips",
          "url": "https://emergent.sh/news/china-proposes-ai-export-controls-models"
        },
        {
          "title": "China HBM smuggling reportedly exploits export controls",
          "url": "https://chinadailystar.com/news/china-hbm-smuggling-server-chips"
        },
        {
          "title": "Nvidia Tells Cloud Clients 51% of Capacity Must Go to Non-Chinese Buyers - Seoul Economic Daily",
          "url": "https://en.sedaily.com/international/2026/11/03/nvidia-tells-cloud-clients-51-percent-of-capacity-must-go"
        },
        {
          "title": "u s enacts toughest chip export controls to curb chinas ai ambitions",
          "url": "https://www.tipranks.com/news/u-s-enacts-toughest-chip-export-controls-to-curb-chinas-ai-ambitions"
        },
        {
          "title": "US imposes export controls on chip design software to China",
          "url": "https://autotechinsight.spglobal.com/news/5282236/us-imposes-export-controls-on-chip-design-software-to-china"
        }
      ]
    },
    "Today's results are thin, and most of the coverage is from mid-October or earlier. The newest items are two stories dated November 3, 2026.\n\n**Newest (Nov. 3):**\n- **Nvidia cloud rule:** Nvidia has reportedly told cloud and data center customers that a large share of their capacity must go to non-Chinese buyers, which squeezes China's offshore AI rental market. The requirement presents a fresh threat to the AI ambitions of Chinese technology companies, as the U.S. government also tightens access to advanced chips obtained through overseas cloud contracts. Nvidia's top B300 chip is barred from sale in China under U.S. export controls.\n- **HBM smuggling:** A China Daily report says smugglers ship high-bandwidth memory bundled with low-end server processors, then separate the parts in China. SK hynix said it complies with US and South Korean export laws and had not supplied Huawei since US export controls took effect in 2020.\n\n**Chinese controls (mid-October):**\n- Beijing has proposed restricting exports of 23 AI technologies, including large language models, agents, chip designs and computing clusters. Comments on the draft close on 15 November.\n- Firms must now register before they export any of the listed items, under a temporary rule that took effect on Friday.\n\n**Background:** The U.S. controls on Nvidia's most advanced chips remain in place, and a CNBC piece from August reports Washington was trying to close gaps such as remote access to their computing power.\n\nI found no reporting specifically dated November 2, and this was a single search, so coverage may be incomplete."
  ],
  "durationSeconds": 7.083188208000007,
  "searchCount": 1
}

{
  "query": "\"November 2, 2026\" OR \"November 3, 2026\" AI security prompt injection agent exploit",
  "mode": "extended"
}

{
  "query": "\"November 2, 2026\" OR \"November 3, 2026\" AI security prompt injection agent exploit",
  "results": [
    {
      "tool_use_id": "srvtoolu_01QWtBJx6ZPn4166HbDSBbKR",
      "content": [
        {
          "title": "Indirect Prompt Injection Goes Operational",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-indirect-prompt-injection-in-the-wild-2026/"
        },
        {
          "title": "Top Agentic AI Security Threats in Late 2026",
          "url": "https://stellarcyber.ai/learn/agentic-ai-securiry-threats/"
        },
        {
          "title": "Parallax: Why AI Agents That Think Must Never Act",
          "url": "https://arxiv.org/pdf/2604.12986"
        },
        {
          "title": "Are AI-assisted Development Tools Immune to Prompt Injection?",
          "url": "https://arxiv.org/pdf/2603.21642"
        },
        {
          "title": "A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors",
          "url": "https://arxiv.org/pdf/2609.03884"
        },
        {
          "title": "The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multistep Malware Delivery Mechanism",
          "url": "https://arxiv.org/pdf/2601.09625"
        },
        {
          "title": "Prompt injection",
          "url": "https://en.wikipedia.org/wiki/Prompt_injection"
        },
        {
          "title": "Agent Data Injection Attacks are Realistic Threats to AI Agents",
          "url": "https://arxiv.org/pdf/2607.05120"
        },
        {
          "title": "Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems",
          "url": "https://arxiv.org/pdf/2607.14611"
        }
      ]
    },
    "The search didn't turn up anything dated specifically to November 2 or 3, 2026. The results are general 2026 coverage, and some are dated inconsistently, so treat them as background rather than same-day news.\n\n- **In-the-wild attacks:** A Cloud Security Alliance note reports that indirect prompt injection has moved from proof-of-concept to live exploitation. It describes a hidden destructive shell command aimed at coding agents that summarize a web page (index 1-4), and it says Google reported a 32% relative increase in malicious injected content from November 2025 to February 2026 (index 1-3).\n- **Hidden payloads:** Invisible text such as CSS-suppressed content or zero-pixel fonts is unseen by human reviewers but still reaches an LLM that reads the raw page (index 1-7).\n- **Agent memory and multi-step manipulation:** A vendor blog cites Lakera research from November 2026 on memory injection, where poisoned data corrupted an agent's long-term memory (indices 2-3 to 2-4). The same blog describes a procurement agent that was manipulated over three weeks (index 2-9). This is a vendor source, so its examples are hard to verify.\n- **Coding-agent and harness flaws:** Academic papers list recent CVEs in agent tooling, including a command injection in an OpenHarness gateway (index 5-14), and a 2026 paper on attacker-controlled hook updates steering agent harnesses (index 5-5).\n\nFor same-day items, a follow-up search on security news sites or the CVE database would be needed."
  ],
  "durationSeconds": 8.054500657999975,
  "searchCount": 1
}

{
  "command": "cd /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results && wc -l bcqfj8vgg.txt && grep -n \"=====\" bcqfj8vgg.txt\ncd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I parse.py cs.CY.xml",
  "description": "Check file and parse cs.CY"
}

{
  "stdout": "500 bcqfj8vgg.txt\n1:===== cs.LG\n336:===== cs.CL\n488:===== cs.CR\n2611.00260\tA Parametric Model for Generating Synthetic Homelessness and Housing Administrative Data\n2611.00380\tWhere Intention Goes, Responsibility Flows: Grounding AI Accountability in the Machine Learning Paradigm\n2611.00412\tOn the Framing Effect of AI Red-Teaming Instructions: Evidence from Prior Exercises and Controlled Simulations\n2611.00465\tThe Promises and Limitations of Evaluation-Based AI Governance: Evidence from Expert Interviews\n2611.00508\tDo Social Influence Pressures Move LLM Agents? Evidence from Delegated Audit Judgment\n2611.01033\tForecasting Visitor Demand from Open AI-Camera Counts and Weather: Lessons from Japan for Saudi Heritage Sites\n2611.01330\tFrom Policing Provenance to Designing for Evidence: Testing Four Propositions on Generative AI Against Research and Institutional Policy\n2611.01785\tRubric-Based Assessment of Student Reports Using Small Language Models\n2611.02016\tImproving Entrepreneurial Skills by Practicing with AI\n2611.02590\tFrom Source-Based Quizzes to Reteaching Decisions: A Practitioner Guide to ClassQuest\n2611.02916\tDefining Autonomous Weapon Systems: A schematic framework for refined purpose-driven definitions\n2611.02996\tLLMs and the Organization of Scientific Work\n2611.03135\tFrom Simulation to Sustainable Urban Mobility: A Purpose-Driven Framework for Advanced EV Charging Technology Transfer\n2611.03213\tReducing SNAP Payment Errors at Lower Cost With AI: A Simulation Study\n2611.03494\tHarder Than the Task: From Technical to Organizational Difficulty in AI Benchmarking",
  "stderr": "",
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{
  "query": "OpenAI LifeVal benchmark November 2026",
  "mode": "standard"
}

{
  "query": "OpenAI LifeVal benchmark November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01K992s7ZsajhKgigyrMZsvc",
      "content": [
        {
          "title": "api.openalex.org",
          "url": "https://api.openalex.org/works/doi:10.48550%2FARXIV.2603.00490"
        },
        {
          "title": "https:%2F%2Fscience.slashdot.org%2Fstory%2F26%2F06%2F20%2F202204%2Fopenai announces benchmarks for ai life sciences research its best model failed 639 of the test",
          "url": "https://scour.ing/p/https:%2F%2Fscience.slashdot.org%2Fstory%2F26%2F06%2F20%2F202204%2Fopenai-announces-benchmarks-for-ai-life-sciences-research-its-best-model-failed-639-of-the-test"
        },
        {
          "title": "openai launches lifescibench to evaluate ai systems in real scientific research",
          "url": "https://www.kucoin.com/news/flash/openai-launches-lifescibench-to-evaluate-ai-systems-in-real-scientific-research"
        },
        {
          "title": "openai lifescibench 750 tareas ia investigacion ciencias vida 2026",
          "url": "https://wwwhatsnew.com/2026/06/20/openai-lifescibench-750-tareas-ia-investigacion-ciencias-vida-2026/"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2603.00490"
        },
        {
          "title": "loom-scope.readthedocs.io",
          "url": "https://loom-scope.readthedocs.io/en/latest/_sources/benchmarks/Reasoning/LVEval.rst.txt"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/abs/2603.00490"
        },
        {
          "title": "DEV Community",
          "url": "https://dev.to/eli_9c82b7dfe52c1bc371ffe/openai-unveils-lifescibench-to-test-ai-performance-on-biomedical-research-50hk"
        },
        {
          "title": "gmagazine.it.com",
          "url": "https://gmagazine.it.com/?p=390"
        },
        {
          "title": "OpenAI's LifeSciBench Tests AI on 750 Life-Science Research Tasks",
          "url": "https://aiweekly.co/node/3135"
        },
        {
          "title": "OpenAI's New Science Benchmark",
          "url": "https://natural20.beehiiv.com/p/openai-s-new-science-benchmark"
        },
        {
          "title": "OpenAI Announces Benchmarks for AI Life Sciences Research. Its Best Model Failed 63.9% of the Test",
          "url": "https://www.pulse.bot/ai/news/openai-announces-benchmarks-for-ai-life-sciences-research-its-best-model-failed-639-of-the-test-97f173b1-1f38-4f28-b44e-528df4705448/"
        },
        {
          "title": "- The AI Report",
          "url": "https://theaireport.beehiiv.com/p/openai-s-game-changing-benchmark-test"
        },
        {
          "title": "openais game changing benchmark test",
          "url": "https://www.theaireport.ai/articles/openais-game-changing-benchmark-test"
        },
        {
          "title": "Passer au contenu principal",
          "url": "https://openai.com/fr-FR/index/introducing-life-sci-bench/"
        },
        {
          "title": "introducing lifescibench 01KVBNH0PC7WGVQZR787GXJRGM",
          "url": "https://themodelwire.com/article/introducing-lifescibench-01KVBNH0PC7WGVQZR787GXJRGM"
        },
        {
          "title": "openai lifescibench 173 scientists best ai passed 36 percent",
          "url": "https://letsdatascience.com/blog/openai-lifescibench-173-scientists-best-ai-passed-36-percent"
        },
        {
          "title": "openai lifescibench life science benchmark",
          "url": "https://runtimewire.com/article/openai-lifescibench-life-science-benchmark"
        },
        {
          "title": "DEV Community",
          "url": "https://dev.to/nidalz954lgtm/openai-introduces-lifescibench-50i4"
        },
        {
          "title": "20260618 openai lifescibench",
          "url": "https://gigazine.net/gsc_news/en/20260618-openai-lifescibench/"
        },
        {
          "title": "www.alphaxiv.org",
          "url": "https://www.alphaxiv.org/hi/overview/2411.07037"
        },
        {
          "title": "jimmysong.io",
          "url": "https://jimmysong.io/en/ai/livebench"
        },
        {
          "title": "openai evals",
          "url": "https://benchmarklist.com/benchmarks/openai_evals/"
        },
        {
          "title": "LifeSciBench: OpenAI’s Hard New Life-Science Benchmark — and How GPT-Rosalind Stacks Up",
          "url": "https://labcritics.com/?p=14230"
        },
        {
          "title": "IA & Ética",
          "url": "https://doutoranathalia.com.br/blog/news-315-introducing-lifescibench/"
        },
        {
          "title": "techjacksolutions.com",
          "url": "https://techjacksolutions.com/?p=59757"
        },
        {
          "title": "AI Research2026-06-18OpenAI Blog",
          "url": "https://aistart.ai/ainews/openai-introduces-lifescibench-benchmark"
        }
      ]
    },
    "I couldn't find any OpenAI benchmark called \"LifeVal\" in the results, and nothing dated November 2026. The closest match is OpenAI's **LifeSciBench**, which was announced in June 2026.\n\n- **LifeSciBench:** Coverage dates the announcement to June 17, 2026. One summary describes it as a 750-task, expert-written, expert-reviewed benchmark for life-science research. Its top model, GPT-Rosalind, reportedly reached a pass rate of just 36.1 percent.\n- **Caveats:** Several sources note that OpenAI both built and ran the benchmark. One points out that Epoch AI has not independently evaluated GPT-Rosalind on LifeSciBench.\n- **Unrelated \"LifeEval\":** An arXiv paper (2603.00490) introduces a benchmark called LifeEval, designed to systematically evaluate MLLMs as real-time and task-oriented assistants in first-person scenarios. It is not from OpenAI.\n\nIf \"LifeVal\" was a typo for one of these, LifeSciBench is the likely match. If you meant a different OpenAI release, the search didn't surface it."
  ],
  "durationSeconds": 6.701262420999992,
  "searchCount": 1
}

{
  "query": "OpenAI \"Grid Protectors Program\" electric grid AI",
  "mode": "standard"
}

{
  "query": "OpenAI \"Grid Protectors Program\" electric grid AI",
  "results": [
    {
      "tool_use_id": "srvtoolu_01N1anZxGCLUkjG5gmWg8Sge",
      "content": [
        {
          "title": "OpenAI Advocates Electric Grid, Safety Net Spending for New AI Era",
          "url": "https://www.bloomberg.com/news/articles/2026-04-06/openai-advocates-electric-grid-safety-net-spending-for-new-ai-era"
        },
        {
          "title": "Sam Altman pitches US utilities on OpenAI’s Daybreak programme for grid defence",
          "url": "https://thenextweb.com/news/altman-utilities-openai-daybreak-grid-defence"
        },
        {
          "title": "protecting the grid with artificial intelligence",
          "url": "https://m.getcoai.com/newsfeed/protecting-the-grid-with-artificial-intelligence"
        },
        {
          "title": "sam altman please let openai into the energy grid 2000810331",
          "url": "https://gizmodo.com/sam-altman-please-let-openai-into-the-energy-grid-2000810331"
        },
        {
          "title": "Lightning Talk 7",
          "url": "https://sdmay25-42.sd.ece.iastate.edu/Lightning Talk 7.pdf"
        },
        {
          "title": "OpenAI Advocates Electric Grid, Safety Net Spending for New AI Era",
          "url": "https://www.energyconnects.com/news/utilities/2026/april/openai-advocates-electric-grid-safety-net-spending-for-new-ai-era"
        },
        {
          "title": "Protecting the electric grid with AI? Stony Brook team awarded $5 million to try",
          "url": "https://solarbuildermag.com/news/protecting-the-electric-grid-with-ai-stony-brook-team-awarded-5-million-to-try/"
        },
        {
          "title": "AI training for grid operators is new research target",
          "url": "https://www.eenews.net/articles/ai-training-for-grid-operators-is-new-research-target/"
        },
        {
          "title": "DOE Funds U of A Research to Safeguard the AI Behind America's Electric Grid",
          "url": "https://news.uark.edu/articles/82674/doe-funds-u-of-a-research-to-safeguard-the-ai-behind-americas-electric-grid"
        },
        {
          "title": "DOE Funds U of A Research to Safeguard the AI Behind America's Electric Grid",
          "url": "https://news-dev.uark.edu/articles/82674/doe-funds-u-of-a-research-to-safeguard-the-ai-behind-america-s-electric-grid"
        }
      ]
    },
    "I couldn't find any source that mentions an OpenAI \"Grid Protectors Program\" by that name. The closest results describe related OpenAI grid-security work:\n\n- **Daybreak pitch to utilities:** Sam Altman has been meeting with U.S. electric utilities about using OpenAI's models to defend grid infrastructure against autonomous cyberattacks. Per one report, the meetings include Duke Energy, Exelon, Southern Company, and NextEra Energy, and began in July ([TheNextWeb](https://thenextweb.com/news/altman-utilities-openai-daybreak-grid-defence); [Gizmodo](https://gizmodo.com/sam-altman-please-let-openai-into-the-energy-grid-2000810331)). One report says the $1bn already committed to the program covers water utilities and community banks, and that electric utilities are an extension of that commitment, with no new dollar figure announced ([TheNextWeb](https://thenextweb.com/news/altman-utilities-openai-daybreak-grid-defence)).\n- **Policy document:** In April 2026, OpenAI published \"Industrial Policy for the Intelligence Age,\" which includes proposals for faster electrical grid development ([Bloomberg](https://www.bloomberg.com/news/articles/2026-04-06/openai-advocates-electric-grid-safety-net-spending-for-new-ai-era)).\n\nOther results were about unrelated grid-AI efforts, such as EPRI's Open Power AI Consortium and a DOE-funded University of Arkansas project on securing AI used in grid operations. None of them mention OpenAI.\n\nIf \"Grid Protectors Program\" is a real name, it may be a newer or differently named initiative. A search on OpenAI's own blog or newsroom would be the best next check."
  ],
  "durationSeconds": 6.413240401999996,
  "searchCount": 1
}

{
  "query": "Cassidy PATIENT AI Act discussion draft health care artificial intelligence Senate HELP",
  "mode": "extended"
}

{
  "query": "Cassidy PATIENT AI Act discussion draft health care artificial intelligence Senate HELP",
  "results": [
    {
      "tool_use_id": "srvtoolu_01BiZs8scYbj8jZG9cDXUu4a",
      "content": [
        {
          "title": "Senator’s draft bill would create healthcare AI payment pathway",
          "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ai/senators-draft-bill-would-create-healthcare-ai-payment-pathway/"
        },
        {
          "title": "Cassidy's AI Health Draft Puts 5 of 19 Sections on Medicare - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-cassidys-ai-health-draft-puts-5-of-19-sections-on-medicare/"
        },
        {
          "title": "Proposed Senate bill offers ideas for regs and reimbursement of health AI",
          "url": "https://www.healthcareitnews.com/news/proposed-senate-bill-offers-ideas-regs-and-reimbursement-health-ai"
        },
        {
          "title": "Cassidy Floats Draft Bill To Regulate Health AI",
          "url": "https://insidehealthpolicy.com/daily-news/cassidy-floats-draft-bill-regulate-health-ai"
        },
        {
          "title": "Medicare Could Test Paying for AI That Performs Clinical Tasks on Its Own Under Cassidy's Senate Draft",
          "url": "https://www.inkl.com/news/medicare-could-test-paying-for-ai-that-performs-clinical-tasks-on-its-own-under-cassidys-senate-draft"
        },
        {
          "title": "GENERAL HEALTH CARE NEWS: Senator’s report explores implications of AI in health care, seeks feedback",
          "url": "https://www.vitallaw.com/news/general-health-care-news-senator-s-report-explores-implications-of-ai-in-health-care-seeks-feedback/hld01302dba1f53bf4467bb8c7a7291b33787"
        },
        {
          "title": "Framework for the Future of AI: Senator Cassidy Issues White Paper, Seeks Public Feedback - Lexology",
          "url": "https://www.lexology.com/library/detail.aspx?g=d973f84c-b412-40a5-b633-a15a3d5a8efb"
        },
        {
          "title": "Medicare Could Test Paying for AI That Performs Clinical Tasks on Its Own Under Cassidy's Senate Draft",
          "url": "https://www.medicaldaily.com/medicare-autonomous-ai-payment-cassidy-patient-ai-act-480674"
        },
        {
          "title": "ranking member cassidy releases white paper on artificial intelligence",
          "url": "https://www.help.senate.gov/rep/newsroom/press/ranking-member-cassidy-releases-white-paper-on-artificial-intelligence"
        },
        {
          "title": "February 10, 2021",
          "url": "https://www.cassidy.senate.gov/news/press-releases/cassidy-requests-fda-update-on-artificial-intelligence-software-for-medical-devices"
        }
      ]
    },
    "The PATIENT AI Act is a discussion draft from Sen. Bill Cassidy, R-La., who chairs the Senate HELP Committee. It was released October 29, 2026, and it has not been introduced or voted on.\n\n- **Purpose:** The draft would clarify whether the FDA or ONC oversees a given health care AI tool, and it would set up a federal payment pathway for AI-based services. It proposes to clarify whether the FDA or ONC oversees healthcare AI tools and to create a federal payment pathway for AI-based services.\n- **Oversight split:** AI applications that don't qualify as FDA-regulated devices would fall under ONC's certified health IT program. It also reaffirms federal preemption of state product liability laws for these devices. \n- **Medicare payment:** The draft would have the CMS Innovation Center run a five-year payment model for AI tools that perform clinical functions on their own. Patient notice and appeal rights would be preserved. It would direct Medicare to test paying for autonomous clinical AI while requiring patient notice and preserving appeal rights.\n- **Open questions:** Liability for harm caused by autonomous AI is not resolved. The draft sends the question of who is liable to further study through a nonprofit review rather than settling it.\n- **Comments:** Feedback is due December 1, 2026, and can be sent to [email redacted]. \n\nSources differ slightly on how many sections the draft contains; one analysis counts 19 sections, with five dealing with Medicare and Medicaid payment."
  ],
  "durationSeconds": 6.632687672,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://ai.nejm.org/doi/full/10.1056/AIoa2501001\" 2>&1 | head -c 4000",
  "description": "Fetch NEJM AI article"
}

{
  "stdout": "HTTP 403 · https://ai.nejm.org/doi/full/10.1056/AIoa2501001 · text/html\nJust a moment...",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "Google first data center satellite online Suncatcher",
  "mode": "standard"
}

{
  "query": "Google first data center satellite online Suncatcher",
  "results": [
    {
      "tool_use_id": "srvtoolu_01QfHWvVmuS4Rc6kdLzCAMJb",
      "content": [
        {
          "title": "Google and SpaceX May Team Up on Solar-Powered Data Centers in Space | eWeek",
          "url": "https://www.eweek.com/fr/news/google-spacex-project-suncatcher-orbital-data-centers/"
        },
        {
          "title": "Google looks to space as AI datacentres strain Earth’s infrastructure",
          "url": "https://www.computing.co.uk/news/2025/ai/google-looks-to-space-ai-datacentres"
        },
        {
          "title": "Notebookcheck Logo",
          "url": "https://www.notebookcheck.net/Google-wants-data-centers-in-space-by-2027-and-while-it-may-seem-smart-the-reality-is-way-more-complicated.1175259.0.html"
        },
        {
          "title": "Google lanza el 1 de octubre el primer satélite de Suncatcher",
          "url": "https://ecosistemastartup.com/?p=111204"
        },
        {
          "title": "Google Reveals AI Space Plan for Orbital Data Centers by 2027",
          "url": "https://www.datamation.com/artificial-intelligence/google-ai-space-plan/"
        },
        {
          "title": "Jan 26, 2026",
          "url": "https://www.folio3.ai/ai-pulse/google-announces-plan-launch-ai-datacenters-space"
        },
        {
          "title": "Google Launches Project Suncatcher: AI Data Centers in Space",
          "url": "https://ground.news/article/if-you-want-to-satiate-ais-hunger-for-power-google-suggests-going-to-space"
        },
        {
          "title": "Google’s Project Suncatcher | 07 Nov 2025",
          "url": "https://www.drishtiias.com/state-pcs-current-affairs/googles-project-suncatcher/print_manually"
        },
        {
          "title": "Unsere Marken MIT Technology Review Digital Bash",
          "url": "https://t3n.de/news/?p=1715196"
        },
        {
          "title": "Google Wants to Take AI Data Centers to Space",
          "url": "https://itdaily.com/news/innovation/google-datacenters-in-de-ruimte"
        }
      ]
    },
    "The search didn't turn up confirmation that Google's first Suncatcher satellite is online. The sources conflict on timing.\n\n- **Official plan:** Google plans to launch two prototype satellites with Planet, targeting early 2027. Each would carry four TPUs to test whether distributed machine learning can work in low orbit.\n- **Conflicting report:** A Spanish-language article (ecosistemastartup.com) says the first physical prototype would launch on October 1, 2026. It calls this a \"learning mission\" rather than a working data center. No other result I found mentions that launch, and it's the only source with that date. Since today is November 3, 2026, I'd verify it before relying on it.\n- **Not Google:** Starcloud's satellite is a different project. It carries an Nvidia H100 GPU and was launched in November 2025.\n- **Challenges:** Google itself says \"Significant engineering challenges remain\". Analysts also note that removing heat from dense AI chips in a vacuum requires very large radiative surfaces.\n\nFor a definitive answer on whether the satellite has launched, check Google's announcements or Planet's launch schedule directly."
  ],
  "durationSeconds": 7.30389403299999,
  "searchCount": 1
}

{
  "url": "https://www.defenseone.com/topic/artificial-intelligence/",
  "prompt": "List articles dated Nov 2 or Nov 3 2026 with headlines and URLs."
}

{
  "bytes": 184785,
  "code": 200,
  "codeText": "OK",
  "result": "The page content doesn't include any articles dated November 2 or 3, 2026. The most recent dated item is an October 26, 2026 piece, \"Policy proposal would require firms to disclose how they use AI to develop new models\" (defenseone.com/policy/2026/10/policy-proposal-would-require-firms-disclose-how-they-use-ai-develop-new-models/416833/).\n\nThe page is likely a snapshot from late October 2026, so newer articles would need to be checked on the live Defense One site or its archive.",
  "durationMs": 3487,
  "url": "https://www.defenseone.com/topic/artificial-intelligence/"
}

{
  "query": "Nvidia tells cloud customers 51% capacity non-Chinese buyers",
  "mode": "extended"
}

{
  "query": "Nvidia tells cloud customers 51% capacity non-Chinese buyers",
  "results": [
    {
      "tool_use_id": "srvtoolu_01ExsRpoNSu4fAkTKH9GRFZ2",
      "content": [
        {
          "title": "Nvidia tells cloud clients to sell at least 51% of services to non-Chinese firms — TradingView News",
          "url": "https://www.tradingview.com/news/cryptobriefing:ffa228717094b:0-nvidia-tells-cloud-clients-to-sell-at-least-51-of-services-to-non-chinese-firms/"
        },
        {
          "title": "NVIDIA Requires Cloud Providers to Sell 51% of Computing Power to Non-Chinese Clients",
          "url": "https://www.kucoin.com/news/flash/nvidia-requires-cloud-providers-to-sell-51-of-computing-power-to-non-chinese-clients"
        },
        {
          "title": "Nvidia Requires Cloud Clients to Limit Business With Chinese Customers",
          "url": "https://www.marketscreener.com/news/nvidia-requires-cloud-clients-to-limit-business-with-chinese-customers-ce785fd9de81ff21"
        },
        {
          "title": "Nvidia Tells Data Centre Clients to Cut Their China Exposure - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-nvidia-tells-data-centre-clients-to-cut-their-china-exposure/"
        },
        {
          "title": "Nvidia China Curbs Hit Cloud Clients With a 51% Rule",
          "url": "https://shiftdelete.net/en/nvidia-china"
        },
        {
          "title": "Nvidia tells data center partners to limit China sales- FT By Investing.com",
          "url": "https://za.investing.com/news/stock-market-news/nvidia-tells-data-center-partners-to-limit-china-sales-ft-4544767"
        },
        {
          "title": "Nvidia Tells Cloud Clients 51% of Capacity Must Go to Non-Chinese Buyers - Seoul Economic Daily",
          "url": "https://en.sedaily.com/international/2026/11/03/nvidia-tells-cloud-clients-51-percent-of-capacity-must-go"
        },
        {
          "title": "Nvidia tells cloud clients to sell 51% of services outside China: Report - Türkiye Today",
          "url": "https://www.turkiyetoday.com/business/nvidia-tells-cloud-clients-to-sell-51-of-services-outside-china-report-3231617"
        },
        {
          "title": "Nvidia Limits China AI Chip Access To Under 49 Percent",
          "url": "https://gokhshtein.com/news/2026-11-03-nvidia-directs-cloud-partners-to-curb-china-ai-access"
        }
      ]
    },
    "The Financial Times reported this on Tuesday, November 3, 2026, and the story is being picked up widely. Nvidia has not confirmed it publicly.\n\n- **The rule:** Per the FT, Nvidia's cloud computing clients must now sell at least 51% of their services to non-Chinese companies, citing five people with knowledge of the matter. The instructions have been delivered verbally through Nvidia's sales force and regional teams rather than through written documents.\n- **Scope:** The new rules only affect future contracts and not existing agreements. The rule doesn't ban Chinese customers from overseas cloud capacity outright.\n- **Unclear details:** Reports did not say whether the share is measured by revenue, computing capacity or number of customers, or how Nvidia defines a Chinese company.\n- **Nvidia's response:** Nvidia neither confirmed nor denied the report to Agence France-Presse (AFP), but said in a statement that American-chip data centers and clouds are foundational to U.S. AI competitiveness.\n- **Industry reaction:** A Singapore-based provider said it is difficult to secure enough non-Chinese customers outside the U.S., adding that strict enforcement would clearly hurt its business.\n- **Context:** The move follows Nvidia's July tightening of its approved Asian buyer list, which reduced by more than half the list of approved customers in Asia allowed to purchase AI chips."
  ],
  "durationSeconds": 6.020556043999997,
  "searchCount": 1
}

{
  "url": "https://www.securityweek.com/in-other-news-anthropic-breach-dispute-uefi-flaw-hits-most-servers-cloudflare-ai-data-leak/",
  "prompt": "Publication date and details of the Anthropic breach dispute and Cloudflare AI data leak items."
}

{
  "bytes": 172559,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** The SecurityWeek roundup was published October 30, 2026, at 10:41 AM ET.\n\n**Anthropic breach dispute**\n- Cathedral, a cybersecurity startup founded by former DOGE staffers, says its AI agents got into Anthropic's internal systems in under 12 hours by exploiting weaknesses in third-party business software. This is according to a draft report that the Washington Post reviewed.\n- Cathedral says it reached meeting transcripts, salary and job offer data, and Slack discussions about Anthropic's most advanced models.\n- Anthropic received the findings through its bug bounty program. It says only a limited set of sales, HR, and IT systems was reached, and that it cut off the startup's access the same day.\n- Anthropic says Claude conversations, source code, and model weights were not affected.\n- Anthropic also accuses Cathedral of breaking the bounty program's rules by not disclosing all of its activity.\n\n**Cloudflare AI data leak**\n- Between August 27 and September 9, 155 responses from the GLM 5.3 model on Cloudflare's Workers AI platform contained data from other customers' recent requests to the same model. All of the affected prompts were longer than 681,280 tokens.\n- The cause was a configuration mismatch that left the model's KV cache smaller than its advertised context window. A bug in the SGLang inference engine then let over-length requests read cache data left by earlier sessions.\n- Knostic researcher Gadi Evron reported the issue through HackerOne. Cloudflare fixed it, found no evidence of deliberate exploitation, and recommends that SGLang operators update to version 0.5.22 or later.",
  "durationMs": 7052,
  "url": "https://www.securityweek.com/in-other-news-anthropic-breach-dispute-uefi-flaw-hits-most-servers-cloudflare-ai-data-leak/"
}

{
  "command": "curl -s \"https://api.crossref.org/works/10.1056/AIoa2501001\" | python3 -c \"import sys,json;d=json.load(sys.stdin)['message'];print(d.get('title'));print('published',d.get('published'));print('issued',d.get('issued'));print('created',d.get('created',{}).get('date-time'));print('journal-issue',d.get('journal-issue'));print(d.get('volume'),d.get('issue'))\" 2>&1 | head -40",
  "description": "Check Crossref metadata for NEJM AI article"
}

{
  "stdout": "Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\n  File \"/usr/lib/python3.11/json/__init__.py\", line 293, in load\n    return loads(fp.read(),\n           ^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.11/json/__init__.py\", line 346, in loads\n    return _default_decoder.decode(s)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.11/json/decoder.py\", line 337, in decode\n    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.11/json/decoder.py\", line 355, in raw_decode\n    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\njson.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)",
  "stderr": "",
  "interrupted": false,
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{
  "command": "for u in \"https://openai.com/fr-FR/index/lifeval/\" \"https://openai.com/fr-FR/index/grid-protectors-program/\"; do echo \"=== $u\"; node scripts/fetch.js \"$u\" 2>&1 | head -45; done",
  "description": "Try OpenAI locale paths for two articles"
}

{
  "stdout": "=== https://openai.com/fr-FR/index/lifeval/\nHTTP 403 · https://openai.com/fr-FR/index/lifeval/ · text/html\n\n=== https://openai.com/fr-FR/index/grid-protectors-program/\nHTTP 403 · https://openai.com/fr-FR/index/grid-protectors-program/ · text/html",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false,
  "bashEditDiff": {
    "files": [
      {
        "filePath": "/home/user/ainews/trace/2026-11-03.jsonl",
        "hunks": [
          {
            "oldStart": 93,
            "oldLines": 3,
            "newStart": 93,
            "newLines": 5,
            "lines": [
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… [7107 more characters in events.jsonl]

{
  "url": "https://www.404media.co/",
  "prompt": "List articles dated Nov 2 or Nov 3 2026 with headlines and URLs, flagging AI surveillance/deepfake/security ones."
}

{
  "bytes": 68487,
  "code": 200,
  "codeText": "OK",
  "result": "Three articles on the page are dated Nov 2 or Nov 3, 2026:\n\n1. \"Vibe Coded AO3 Clone Site Down After Fanfic Authors Buried It With 2,000 Takedown Notices in a Single Day\" (Nov 3, 2026)\n   https://www.404media.co/vibe-coded-ao3-clone-site-down-after-fanfic-authors-buried-it-with-2-000-takedown-notices-in-a-single-day/\n   **Flag (borderline):** The summary says the site scraped fanfiction and sold repackaged audiobooks without authors' permission. It's a copyright and unauthorized-use story, and the page doesn't describe AI surveillance, deepfakes, or security issues.\n\n2. \"Voting in 2026 Is Getting an AI Slop 'I Voted' Sticker\" (Nov 2, 2026)\n   https://www.404media.co/voting-in-2026-is-getting-an-ai-slop-i-voted-sticker/\n   **Flag:** No. It concerns AI-generated content at polling places, not surveillance, deepfakes, or security.\n\n3. \"Reaping and sowing, CEO edition\" (Nov 2, 2026)\n   https://www.404media.co/reaping-and-sowing-ceo-edition/\n   **Flag:** No. The summary is a newsletter roundup covering Apple, Texas data centers, and other items, none of which is clearly about AI surveillance, deepfakes, or security.",
  "durationMs": 6197,
  "url": "https://www.404media.co/"
}

{
  "url": "https://blog.redwoodresearch.org/",
  "prompt": "List post titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 106920,
  "code": 200,
  "codeText": "OK",
  "result": "The page content doesn't include any post titles or dates, so I can't list posts or confirm whether any are dated November 2 or 3, 2026. It only shows the blog's header, a subscriber count (\"Over 8,000 subscribers\"), and a subscribe prompt. The blog describes itself as: \"We research catastrophic AI risks and techniques that could be used to mitigate them.\"\n\nTo answer your question, you'd need a version of the page that includes the post list, such as the blog's archive page.",
  "durationMs": 2787,
  "url": "https://blog.redwoodresearch.org/"
}

{
  "url": "https://transluce.org/",
  "prompt": "List publication/post titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 28950,
  "code": 200,
  "codeText": "OK",
  "result": "No. None of the listed items are dated November 2 or November 3, 2026. The most recent are:\n\n1. September 30, 2026: \"AI Agents Targeted U.S. and Canadian Government Websites\"\n2. September 23, 2026: \"Early rogue AI agent activity and attempts to hack found on urlquery.net\"\n3. September 16, 2026: \"Some Focus Areas for Embedded Evaluations and How to Approach Them\"\n4. August 31, 2026: \"Announcing Transluce's Mental Health Evaluation\"",
  "durationMs": 3684,
  "url": "https://transluce.org/"
}

{
  "query": "medRxiv preprint November 2 2026 artificial intelligence clinical",
  "mode": "extended"
}

{
  "query": "medRxiv preprint November 2 2026 artificial intelligence clinical",
  "results": [
    {
      "tool_use_id": "srvtoolu_015McyViGYb6nQzZVbr9k3QP",
      "content": [
        {
          "title": "Evaluative Stance Toward Artificial Intelligence in High-Quartile Medical Journals (2021-2026)",
          "url": "https://www.medrxiv.org/content/10.64898/2026.07.23.26358815v1.full.pdf"
        },
        {
          "title": "Artificial Intelligence in Healthcare: 2025 Year in Review",
          "url": "https://www.medrxiv.org/content/10.64898/2026.02.23.26346888v1.full.pdf"
        },
        {
          "title": "The Causal Artificial Intelligence Clinician for early 1",
          "url": "https://www.medrxiv.org/content/10.64898/2026.07.06.26357375v2.full.pdf"
        },
        {
          "title": "medrXiv Archive",
          "url": "http://connect.medrxiv.org/archive/index.php"
        },
        {
          "title": "Artificial Intelligence in Medical Imaging With Emphasis on ...",
          "url": "https://www.medrxiv.org/content/10.64898/2026.06.26.26356684v1.full.pdf"
        },
        {
          "title": "1 MedOS: AI-XR-Cobot World Model for Clinical Perception and Action",
          "url": "https://www.medrxiv.org/content/medrxiv/early/2026/02/23/2026.02.18.26345936.full.pdf"
        },
        {
          "title": "Word count: 7852 Abstract: 161 Tables: 1 Figures: 3 References: 25",
          "url": "https://www.medrxiv.org/content/10.64898/2026.09.29.26364234v1.full.pdf"
        },
        {
          "title": "Assessing AI and Neurologist Diagnostic Reasoning ...",
          "url": "https://www.medrxiv.org/content/10.64898/2026.07.07.26356930v2.full.pdf"
        },
        {
          "title": "Medrxiv",
          "url": "https://www.medrxiv.org/content/10.64898/2026.03.11.26348161v1.full.pdf"
        },
        {
          "title": "ResidencyRL: Reinforcement Learning in Simulated Clinical Environments",
          "url": "https://arxiv.org/pdf/2608.07418"
        }
      ]
    },
    "The search didn't turn up any medRxiv preprints posted on November 2, 2026. The newest items are from early October 2026, and the archive page it returned covers October 2026.\n\n- **October 2026 archive:** A medRxiv archive page lists several AI-related October postings, including a foundation model for electrocardiogram detection of rheumatic mitral stenosis and an autoregressive clinical foundation model for disease risk and clinical event prediction.\n- **Neurology diagnosis:** A preprint posted October 3, 2026 presents the first systematic evaluation of LLM-assisted diagnostic reasoning across diverse, pathologically confirmed neurological disorders.\n- **Psychotherapy:** A preprint posted September 30, 2026 covers AI and treatment preferences in psychotherapy, based on its keywords.\n- **Causal AI clinician:** A version of a causal AI clinician preprint for early sepsis-type care was posted September 14, 2026.\n\nEach of these is a preprint that has not been peer reviewed, and medRxiv notes that such work should not be used to guide clinical practice.\n\nIf you need November 2026 postings specifically, the medRxiv website or its search filtered by date would be the most reliable place to check, since the index may not yet include items from that date."
  ],
  "durationSeconds": 7.276759743000002,
  "searchCount": 1
}

{
  "url": "https://www.apolloresearch.ai/research",
  "prompt": "List research post titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 204728,
  "code": 200,
  "codeText": "OK",
  "result": "No post is dated November 2 or 3, 2026. The closest is October 15, 2026. Here are the research posts shown on the page, most recent first:\n\n1. October 15, 2026: \"GLM-5.3 Sometimes Considers How Train-Time Actions Shape Future Behavior\"\n2. July 21, 2026: \"Measuring Reward-Seeking via Contrastive Belief Updates\"\n3. July 5, 2026: \"We need 3rd party Training-Run Evaluations\"\n4. January 19, 2026: \"We Need A Science of Scheming\"\n5. September 17, 2025: \"Stress Testing Deliberative Alignment for Anti-Scheming Training\"\n6. July 15, 2025: \"Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety\"\n7. July 3, 2025: \"Research Note: Our scheming precursor evals had limited predictive power for our in-context scheming evals\"\n8. June 19, 2025: \"More Capable Models Are Better At In-Context Scheming\"\n9. March 17, 2025: \"Claude Sonnet 3.7 (often) knows when it's in alignment evaluations\"\n10. February 24, 2025: \"Forecasting Frontier Language Model Agent Capabilities\"\n\nThe page includes a \"Load more\" link, so older or additional posts may exist beyond this list.",
  "durationMs": 6712,
  "url": "https://www.apolloresearch.ai/research"
}

{
  "url": "https://epoch.ai/",
  "prompt": "List recent reports/data insights/gradient updates with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 182467,
  "code": 200,
  "codeText": "OK",
  "result": "None of the reports, Data Insights, or Gradient Updates on the page are dated Nov 2 or Nov 3, 2026.\n\n**Reports and Data Insights**\n- Oct 30, 2026 (Data Insight): LLM use is acknowledged almost as often as specialized AI tools in biology preprints\n- Oct 29, 2026 (Report): AI can turn security fixes into working exploits before users receive an update\n- Oct 29, 2026 (Data Insight): New global AI computing capacity is doubling every 9 months\n- Oct 16, 2026 (Data Insight): Open-weight models trail closed models in cyber capabilities by 6–7 months\n- Feb 4, 2026 (Data Insight): Compute accounts for the majority of expenses of AI companies\n- Aug 20, 2024 (Report): Can AI scaling continue through 2030?\n\nThe page also lists an Oct 27, 2026 \"Update\" (Introducing the AI Chip Imports explorer). The page doesn't list any Gradient Updates.\n\nTwo data explorers show Nov 2 and Nov 3, 2026 dates: AI data centers (\"Updated Nov. 2, 2026\") and Capabilities & benchmarking (\"Updated Nov. 3, 2026\"). These are data explorers, not reports, Data Insights, or Gradient Updates.",
  "durationMs": 5195,
  "url": "https://epoch.ai/"
}

{
  "command": "node scripts/fetch.js \"https://www.ft.com/content/nvidia-cloud-china-51\" 2>&1 | head -20; echo \"---SEARCH FT---\"",
  "description": "Try fetching FT article"
}

{
  "stdout": "HTTP 403 · https://www.ft.com/content/nvidia-cloud-china-51 · text/plain\nBlocked by egress policy\n---SEARCH FT---",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://metr.org/research",
  "prompt": "List research post titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 133242,
  "code": 200,
  "codeText": "OK",
  "result": "No posts are dated November 2 or 3, 2026. The most recent entry is from August 26, 2026.\n\n**2026**\n- August 26, 2026: \"Brief independent investigation of agents’ behavior...\" (the OpenAI / Hugging Face incident)\n- July 21, 2026: \"Expenditure Horizon: Measuring Optimization Ability, with an Application to NanoGPT\"\n- May 19, 2026: \"Frontier Risk Report (February to March 2026)\"\n- May 11, 2026: \"Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity\"\n- May 8, 2026: \"Task Substitution and Uplift\"\n- April 10, 2026: \"MirrorCode: Evidence that AI can already do some weeks-long coding tasks\"\n- February 24, 2026: \"We are Changing our Developer Productivity Experiment Design\"\n- January 29, 2026: \"Time Horizon 1.1\"\n- January 22, 2026: \"Early work on monitorability evaluations\"\n\n**2025**\n- November 19, 2025: \"GPT-5.1-Codex-Max Evaluation Results\"\n- October 14, 2025: \"MALT: A Dataset of Natural and Prompted Behaviors That Threaten Eval Integrity\"\n- August 20, 2025: \"Forecasting the Impacts of AI R&D Acceleration: Results of a Pilot Study\"\n- August 13, 2025: \"Research Update: Algorithmic vs. Holistic Evaluation\"\n- August 8, 2025: \"CoT May Be Highly Informative Despite 'Unfaithfulness'\"\n- August 7, 2025: \"GPT-5 Evaluation Results\"\n- July 14, 2025: \"How Does Time Horizon Vary Across Domains?\"\n- July 10, 2025: \"Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity\"\n- June 27, 2025: \"DeepSeek and Qwen Evaluation Results\"\n- June 5, 2025: \"Recent Frontier Models Are Reward Hacking\"\n- April 16, 2025: \"OpenAI o3 and o4-mini Evaluation Results\"\n- April 4, 2025: \"Claude 3.7 Evaluation Results\"\n- March 19, 2025: \"Measuring AI Ability to Complete Long Software Tasks\"\n- March 17, 2025: \"HCAST: Human-Calibrated Autonomy Software Tasks\"\n- March 5, 2025: \"DeepSeek-R1 Evaluation Results\"\n- February 27, 2025: \"METR's GPT-4.5 pre-deployment evaluations\"\n- February 14, 2025: \"Measuring Automated Kernel Engineering\"\n- February 12, 2025: \"DeepSeek-V3 Evaluation Results\"\n- January 31, 2025: \"An update on our preliminary evaluations of Claude 3.5 Sonnet and o1\"\n\n**2024**\n- November 22, 2024: \"Evaluating frontier AI R&D capabilities of language model agents against human experts\"\n- November 12, 2024: \"The Rogue Replication Threat Model\"\n- September 12, 2024: \"Details about METR's preliminary evaluation of o1-preview\"\n- August 20, 2024: \"Evaluation platform: Vivaria\"\n- August 7, 2024: \"Details about METR's preliminary evaluation of GPT-4o\"\n- August 6, 2024: \"An update on our general capability evaluations\"\n- March 15, 2024 (five posts): \"Autonomy Evaluation Resources,\" \"Example autonomy evaluation protocol,\" \"Example autonomy task suite,\" \"Guidelines for capability elicitation,\" and \"Measuring the impact of post-training enhancements\"\n- February 29, 2024: \"Portable Evaluation Tasks via the METR Task Standard\"\n\n**2023**\n- July 31, 2023: \"New report: Evaluating Language-Model Agents on Realistic Autonomous Tasks\"\n- March 17, 2023: \"Update on ARC's recent eval efforts\"",
  "durationMs": 12935,
  "url": "https://metr.org/research"
}

{
  "url": "https://www.cisa.gov/news-events/cybersecurity-advisories",
  "prompt": "List advisories dated Nov 2 or Nov 3 2026 with titles and URLs. Note any AI-related ones."
}

{
  "bytes": 164848,
  "code": 200,
  "codeText": "OK",
  "result": "**No advisories dated Nov 2 or Nov 3, 2026 appear in the provided content.** The most recent entry is dated Oct 30, 2026, and the listing covers Oct 20–30 only.\n\n**AI-related items:** None in the Nov 2–3 window. The closest is an out-of-range resource dated Oct 22, 2026: \"Managing AI Token Consumption for Operational Resilience\" (https://www.cisa.gov/resources-tools/resources/managing-ai-token-consumption-operational-resilience).",
  "durationMs": 3718,
  "url": "https://www.cisa.gov/news-events/cybersecurity-advisories"
}

{
  "url": "https://www.techmeme.com/",
  "prompt": "List all AI-related headlines with dates and publishers from the rest of the page.",
  "offset": 100000
}

{
  "bytes": 402122,
  "code": 200,
  "codeText": "OK",
  "result": "The excerpt cuts off mid-page (\"[Content truncated due to length...]\"), so I can only list AI-related items visible here. Headlines are paraphrased, and dates come from the page or from URL dates when the page gives none.\n\n| Topic (paraphrased) | Publisher | Date |\n|---|---|---|\n| Nvidia reportedly told cloud clients to sell at least 51% of AI compute to non-Chinese buyers | Financial Times (via Techmeme) | Nov 3, 2026 |\n| Nvidia tells data center clients to trim China business | Bloomberg | Nov 3, 2026 |\n| Nvidia's new China-related limits on cloud clients | The Information | Undated |\n| OpenAI teams with Cathedral to test its security defenses and expands its bug bounty | OpenAI | Undated |\n| OpenAI raises its top bug bounty payout to $172,000 | Help Net Security | Nov 3, 2026 |\n| OpenAI raises bug bounty rewards for researchers | Blockchain.News | Undated |\n| OpenAI's new security sprint to find vulnerabilities | Cyber Security News | Undated |\n| OpenAI's Grid Protectors Program for data center power demand | OpenAI / The Verge / NY Post | Nov 2, 2026 (NY Post URL) |\n| Anthropic adds Claude Code limits to stop game cloning | Tom's Hardware | Undated (Nov 2026) |\n| Claude's game-cloning rules and the AI copying boom | Ars Technica | Nov 2026 |\n| Anthropic cracks down on game cloning in Claude Code | The Decoder | Undated |\n| Anthropic restricts Claude's video game clones | The Verge | Undated |\n| Claude stops reverse-engineering games | PCWorld | Undated |\n| Anthropic blocks AI game clones in a Claude Opus update | IGN | Undated |\n| Developers deliberately downgrading their AI tools | The New Stack | Undated |\n| UK cyber chief warns AI will transform cyber operations; China and Russia expected to use AI cyber tools by 2028 | Financial Times | Undated (Nov 2026) |\n| AI-powered malware \"highly likely\" to hit UK infrastructure by 2028 | The Guardian | Nov 3, 2026 |\n| NCSC warns AI could accelerate ransomware attacks | Cyber Security News | Undated |\n| UK warns of AI ransomware attack on infrastructure by 2028 | Cointelegraph | Undated |\n| UK cyber chief warns of AI-driven attacks on critical infrastructure by 2028 | Political.org | Nov 2, 2026 |\n| UK will face AI cyberattacks on critical infrastructure by 2028 | SecurityWeek | Undated |\n| Palantir's outlook signals slowing AI-fueled sales growth | Bloomberg | Nov 2, 2026 |\n| Palantir earnings reveal a major AI turning point | MarketWatch | Undated |\n| Palantir expects revenue above estimates on strong AI demand | Channel NewsAsia | Undated |\n| Google expands AI story app Dreambeans to India | TechCrunch | Nov 2, 2026 |\n| Drax, Brookfield and Radiant plan an AI data center in North Yorkshire | CNBC | Nov 3, 2026 |\n| Tutor Intelligence raises $75M for robot foundation models | Forbes | Nov 2, 2026 |\n| 42AI emerges with $62.5M for a behavioral world model | TechCrunch | Nov 2, 2026 |\n| Trajectory raises $45M for AI model post-training tools | TechCrunch | Nov 2, 2026 |\n| Larridin raises $30M to measure AI's workforce impact | Business Insider | Nov 2026 |\n| DeepSeek adds a \"creator mode\" for custom AI agent plugins | Bloomberg | Nov 2, 2026 |\n| OpenAI plans to merge ChatGPT's Chat and Work tabs | TechCrunch | Nov 2, 2026 |\n| Huawei's upcoming AI chip reportedly to use Samsung and SK Hynix memory | The Information | Undated |\n| Apple's tabletop home robot with a swiveling arm, reportedly 2027–2028 | The Information | Undated |\n| Profile of OpenAI executive Charles Porch and AI outreach to Hollywood | New York Magazine | Undated |\n| Alex Bores' PAC aims to make AI safety a Democratic position | New York Magazine | Undated |\n| Oracle raises $20B in stock and bonds to fund AI buildout | WSJ | Nov 2–3, 2026 |\n\nNote: The Apple and Oracle items and the Palantir items are only loosely AI-related. The page's remaining sections were not included in this excerpt, so the list may be incomplete.\n\n[WebFetch note: this page's text is 243785 characters long and the answer above covers only characters 100000 to 200000; the final 43785 were not read — to read on, call WebFetch again with the same url and offset: 200000.]",
  "durationMs": 15938,
  "url": "https://www.techmeme.com/"
}

{
  "url": "https://cloud.google.com/blog/topics/threat-intelligence",
  "prompt": "List recent posts with dates, especially Nov 2-3 2026 and anything AI-related."
}

{
  "bytes": 214489,
  "code": 200,
  "codeText": "OK",
  "result": "The page doesn't include publication dates for any post, so I can't confirm which were published on Nov 2-3, 2026. Each entry shows only the author and estimated reading time. The list also ends with \"Load more stories,\" so older posts aren't shown.\n\n**Recent Threat Intelligence posts (in page order, newest first as displayed):**\n\n1. **GTIG AI Threat Tracker: From Prompting to Autonomy – The Evolution of Adversarial AI** (Google Threat Intelligence Group, 44 min) **[AI-related]**. Covers adversarial misuse of AI, including Gemini and non-Google tools.\n2. **The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources** (GTIG, 16 min) **[AI-related]**. Covers attackers monetizing compromised cloud and AI model resources.\n3. **Shutting the Door on the XCPE Botnet** (GTIG, 76 min)\n4. **ARTEX and Friends: Enter Agentic Offensive Frameworks** (GTIG, 35 min) **[AI-related, based on title]**. The \"agentic\" framing suggests AI-driven offensive tooling, but the page gives no summary.\n5. **ARMORY CASTLE Exploits BeyondTrust** (GTIG, 19 min)\n6. **Investigating Ephemeral Supply Chain Tampering** (Mandiant, 41 min)\n7. **Vulnerability Discovery and Exploitation Trends in the AI Era** (GTIG, 17 min) **[AI-related, based on title]**\n8. **Defending Against Active Exploitation of Citrix NetScaler ADC and Gateway Appliances** (Mandiant, 29 min)\n9. **ShinyHunters Renewed Mass Exploitation Campaign Targeting Oracle PeopleSoft** (Mandiant, 18 min)\n10. **Proactive Defense: Hardening Code Pipelines and CI/CD Infrastructure** (Mandiant, 15 min)\n11. **Financially Motivated Threat Actor BREEZE COMET Targets Brazil** (GTIG, 16 min)\n\n**AI-related posts:** #1, #2, #4, and #7. Only #1 and #2 have summaries on the page confirming AI content. #4 and #7 are inferred from their titles.\n\n**To get exact dates:** Subscribe to the Threat Intelligence RSS feed (linked on the page), which includes publication timestamps, or open each article, where the date usually appears at the top.",
  "durationMs": 6469,
  "url": "https://cloud.google.com/blog/topics/threat-intelligence"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -s \"https://api.crossref.org/works/10.1056/AIoa2501001?mailto=[email redacted]\" -o cr.json -w \"%{http_code}\\n\" && head -c 300 cr.json",
  "description": "Fetch crossref record"
}

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{
  "query": "autonomous weapons UN First Committee resolution drone AI November 2026",
  "mode": "extended"
}

{
  "query": "autonomous weapons UN First Committee resolution drone AI November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01PsFBUsffbkm3ZsR8LzhvZo",
      "content": [
        {
          "title": "156 states support UNGA resolution on autonomous weapons",
          "url": "https://www.stopkillerrobots.org/news/156-states-support-unga-resolution/"
        },
        {
          "title": "164 states Vote Against the Machine at the UN General Assembly",
          "url": "https://www.stopkillerrobots.org/news/164-states-vote-against-the-machine/"
        },
        {
          "title": "UN Moves to Expand Autonomous Weapons Discussions",
          "url": "https://www.armscontrol.org/act/2024-12/news/un-moves-expand-autonomous-weapons-discussions"
        },
        {
          "title": "First Committee Forwards 14 Texts on Outer Space, Conventional Weapons to General Assembly",
          "url": "https://press.un.org/en/2026/gadis3781.doc.htm"
        },
        {
          "title": "First Committee Underscores Need for Nuclear Non-Proliferation, Weapons-Free Zones, Control of Artificial Intelligence in Warfare, End to Ukraine War",
          "url": "https://press.un.org/en/2026/gadis3766.doc.htm"
        },
        {
          "title": "UN First Committee approves resolution to advance dialogue on military AI",
          "url": "https://dig.watch/updates/un-approves-dialogue-on-military-ai"
        },
        {
          "title": "Autonomous weapons at the 79th United Nations General Assembly First Committee",
          "url": "https://automatedresearch.org/news/autonomous-weapons-at-the-79th-united-nations-general-assembly-first-committee/"
        },
        {
          "title": "First Committee",
          "url": "https://press.un.org//en/first-committee"
        },
        {
          "title": "UN resolution a step forward against killer robots",
          "url": "https://www.atlasofwars.com/un-resolution-a-step-forward-against-killer-robots/"
        },
        {
          "title": "UN chief, Red Cross renew call for rules on lethal autonomous weapons",
          "url": "https://news.un.org/en/story/2026/08/1168196"
        }
      ]
    },
    "The most recent results show the First Committee has already acted on autonomous weapons this session, with the General Assembly vote still to come.\n\n- **Lethal autonomous weapons resolution (A/C.1/81/L.37):** The Committee approved it on 29 October 2026 by a recorded vote of 163 in favour to 5 against, with 9 abstentions. The five against were Belarus, North Korea, Israel, Russia and the United States. It calls for progress towards negotiations on an international instrument addressing lethal autonomous weapons systems.\n- **Military AI resolution:** On 30 October 2026, the Committee approved a separate text that establishes a framework for continued international discussions on military AI. It establishes a dialogue covering a wide range of applications without initiating treaty negotiations.\n- **Next steps:** The First Committee's approval does not constitute final adoption by the General Assembly, which is expected to consider the text in plenary in December 2026. The autonomous weapons process will be considered at the Seventh Review Conference of the Convention on Certain Conventional Weapons (CCW), scheduled for 16–20 November 2026 in Geneva.\n- **Advocacy context:** In August 2026, the UN and ICRC urged governments to move beyond discussions and begin negotiations on a legally binding instrument.\n\nI found no reporting on a November 2026 First Committee vote on autonomous weapons. The First Committee's autonomous weapons action happened in late October, so the November 2026 date in your query may refer to the CCW review conference or the December plenary. The earlier trend is consistent: the 2024 text passed 161-3 with 13 abstentions, per Arms Control Association."
  ],
  "durationSeconds": 8.606681593999994,
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{
  "url": "https://alignment.anthropic.com/",
  "prompt": "List post titles with dates, most recent first. Any posts dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 68609,
  "code": 200,
  "codeText": "OK",
  "result": "No posts are dated November 2 or 3, 2026. The page lists posts only by month, and the most recent section is October 2026, so no November 2026 entries appear.\n\n**October 2026**\n- \"Automated Subtle Emergent Misalignment Research\"\n- \"Anthropic Residency: applications open for established technical leaders\"\n- \"Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents\"\n- \"Reducing Reward Hacking by Localizing Bad Behavior Instead of Penalizing It\"\n- \"Training Alignment Auditors via Reinforcement Learning\"\n\n**August 2026**\n- \"Training a Misaligned Reward Seeker\"\n- \"Automated Researchers Can Mitigate Well-Characterized Alignment Failures\"\n- \"TASTE: Can AI Models Judge AI Safety Research Proposals?\"\n- \"Would This Change Your Answer? Evaluating Explanations of LLM Behavior in the Wild with Counterfactual Experiments\"\n- \"Fine-Tuned Lie Detectors Failed to Generalize\"\n- \"Introducing the Conceptual Reasoning Index\"\n\n**July 2026**\n- \"Agentic Misalignment in Summer 2026\"\n- \"Modular Pretraining Enables Access Control\"\n\n**June 2026**\n- \"Diffuse AI Control on Fuzzy Tasks\"\n\n**May 2026**\n- \"SLEIGHT-Bench: Finding Blind Spots in AI Monitors\"\n- \"Teaching Claude Why\"\n- \"Model Spec Midtraining: Improving How Alignment Training Generalizes\"\n\n**April 2026**\n- \"Poisoning Fine-tuning Datasets of Constitutional Classifiers\"\n- \"Introspection Adapters: Training LLMs to Report Their Learned Behaviors\"\n- \"AI Organizations Can Be More Effective but Less Aligned than Individual Agents\"\n- \"Automated Weak-to-Strong Researcher\"\n\n**March 2026**\n- \"Abstractive Red-Teaming of Language Model Character\"\n- \"Measuring and improving coding audit realism with deployment resources\"\n- \"A3: An Automated Alignment Agent for Safety Finetuning\"\n- \"AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors\"\n- \"3 Challenges and 2 Hopes for the Safety of Unsupervised Elicitation\"\n\n**February 2026**\n- \"The Persona Selection Model: Why AI Assistants might Behave like Humans\"\n- \"The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?\"\n\n**January 2026**\n- \"Pre-deployment auditing can catch an overt saboteur\"\n- \"Petri 2.0: New Scenarios, New Model Comparisons, and Improved Eval-Awareness Mitigations\"\n\n**December 2025**\n- \"Bloom: an open source tool for automated behavioral evaluations\"\n- \"Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers\"\n- \"Towards training-time mitigations for alignment faking in RL\"\n- \"Open Source Replication of the Auditing Game Model Organism\"\n- \"Anthropic Fellows Program 2026\"\n- \"Beyond Data Filtering: Knowledge Localization for Capability Removal in LLMs\"\n\n**November 2025**\n- \"Evaluating honesty and lie detection techniques on a diverse suite dishonest models\"\n- \"Strengthening Red Teams: A Modular Scaffold for Control Evaluations\"\n\n**October 2025**\n- \"Anthropic's Pilot Sabotage Risk Report\"\n- \"Stress-testing model specs reveals character differences among language models\"\n- \"Believe It or Not: How Deeply do LLMs Believe Implanted Facts?\"\n- \"Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment\"\n- \"Training fails to elicit subtle reasoning in current language models\"\n- \"Petri: An open-source auditing tool to accelerate AI safety research\"\n\n**August 2025**\n- \"Findings from a Pilot Anthropic–OpenAI Alignment Evaluation Exercise\"\n- \"Enhancing Model Safety through Pretraining Data Filtering\"\n\n**July 2025**\n- \"Building and evaluating alignment auditing agents\"\n- \"Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data\"\n- \"Inverse Scaling in Test-Time Compute\"\n\n**June 2025**\n- \"Why Do Some Language Models Fake Alignment While Others Don't?\"\n- \"Model-Internals Classifiers\"\n- \"Unsupervised Elicitation\"\n\n**April 2025**\n- \"Reasoning Models Don't Always Say What They Think\"\n- \"Publicly Releasing CoT Faithfulness Evaluations\"\n- \"Modifying LLM Beliefs with Synthetic Document Finetuning\"\n- \"Putting up Bumpers\"\n- \"Alignment Faking Revisited: Improved Classifiers and Open Source Extensions\"\n\n**March 2025**\n- \"Auditing Language Models for Hidden Objectives\"\n- \"Do reasoning models use their scratchpad like we do? Evidence from distilling paraphrases\"\n- \"Automated Researchers Can Subtly Sandbag\"\n\n**February 2025**\n- \"Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming\"\n- \"Introducing Anthropic's Safeguards Research Team\"\n- \"Won't vs. Can't: Sandbagging-like Behavior from Claude Models\"\n- \"Monitoring Computer Use via Hierarchical Summarization\"\n- \"Forecasting Rare Language Model Behaviors\"\n\n**January 2025**\n- \"Training on Documents about Reward Hacking Induces Reward Hacking\"\n- \"Recommendations for Technical AI Safety Research Directions\"\n\n**December 2024**\n- \"Alignment Faking in Large Language Models\"\n- \"How to Replicate and Extend our Alignment Faking Demo\"\n- \"A Toy Evaluation of Inference Code Tampering\"\n- \"Introducing the Anthropic Fellows Program for AI Safety Research\"\n\n**November 2024**\n- \"Rapid Response: Mitigating LLM Jailbreaks with a Few Examples\"\n- \"Three Sketches of ASL-4 Safety Case Components\"\n\n**October 2024**\n- \"Sabotage Evaluations for Frontier Models\"\n\n**June 2024**\n- \"Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models\"\n\n**April 2024**\n- \"Many-shot Jailbreaking\"\n- \"Simple Probes can Catch Sleeper Agents\"\n\n**January 2024**\n- \"Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training\"\n\n**October 2023**\n- \"Specific versus General Principles for Constitutional AI\"\n- \"Tow
… [860 more characters in events.jsonl]

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && for d in 2026-11-02 2026-11-03; do echo \"== $d\"; curl -s \"https://api.biorxiv.org/details/medrxiv/$d/$d/0\" -o m_$d.json -w \"%{http_code}\\n\"; python3 -I -c \"\nimport json,sys\nd=json.load(open('m_$d.json'))\nprint(d.get('messages'))\nfor c in d.get('collection',[]):\n    t=c.get('title','')\n    if any(k in (t+c.get('abstract','')).lower() for k in ['artificial intelligence',' ai ','machine learning','large language model','llm','deep learning','foundation model','neural network']):\n        print(c.get('date'),'|',t,'|',c.get('doi'))\n\" 2>&1 | head -60; done",
  "description": "Query medRxiv API for Nov 2-3 AI preprints"
}

{"stdout":"== 2026-11-02\n200\n[{'status': 'ok', 'category': 'all', 'interval': '2026-11-02:2026-11-02', 'cursor': 0, 'count': 30, 'count_new_papers': '74', 'total': '90'}]\n2026-11-02 | Variantscape: Retrospective Study of Large Language Model-Based Extraction of Variant-Treatment-Cancer Associations from Published Oncology Abstracts | 10.64898/2026.08.02.26359492\n2026-11-02 | Real-time Volumetric Imaging for Minimally-Invasive Thoracic Interventions: A Deformable Phantom Study | 10.64898/2026.10.28.26366767\n2026-11-02 | Ophthalmic AI With Just Ten Examples: Comparing Multimodal Large Language Models, Vision Foundation Models, and Vision-Language Models | 10.64898/2026.10.30.26366929\n== 2026-11-03\n200\n[{'status': 'no posts found'}]","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":110,"oldLines":3,"newStart":110,"newLines":5,"lines":[" {\"t\":\"2026-11-03T11:09:35.133Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_017AYtpLTH5feeMAmAXbMhQJ\",\"duration_ms\":392,\"input\":{\"command\":\"cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -s \\\"https://api.crossref.org/works/10.1056/AIoa2501001?mailto=[email redacted]\\\" -o cr.json -w \\\"%{http_code}\\\\n\\\" && head -c 300 cr.json\",\"description\":\"Fetch crossref record\"},\"response\":{\"truncated\":true,\"length\":42501,\"head\":\"{\\\"stdout\\\":\\\"429\\\",\\\"stderr\\\":\\\"\\\",\\\"interrupted\\\":false,\\\"isImage\\\":false,\\\"noOutputExpected\\\":false,\\\"bashEditDiff\\\":{\\\"files\\\":[{\\\"filePath\\\":\\\"/home/user/ainews/trace/2026-11-03.jsonl\\\",\\\"hunks\\\":[{\\\"oldStart\\\":98,\\\"oldLines\\\":3,\\\"newStart\\\":98,\\\"newLines\\\":12,\\\"lines\\\":[\\\" {\\\\\\\"t\\\\\\\":\\\\\\\"2026-11-03T11:09:17.890Z\\\\\\\",\\\\\\\"event\\\\\\\":\\\\\\\"PostToolUse\\\\\\\",\\\\\\\"session_id\\\\\\\":\\\\\\\"c0ba620c-ead7-5889-a588-1d740c20a25e\\\\\\\",\\\\\\\"cwd\\\\\\\":\\\\\\\"/home/user/ainews\\\\\\\",\\\\\\\"scratchpad_dir\\\\\\\":\\\\\\\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\\\\\\\",\\\\\\\"prompt_id\\\\\\\":\\\\\\\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\\\\\\\",\\\\\\\"permission_mode\\\\\\\":\\\\\\\"auto\\\\\\\",\\\\\\\"agent_id\\\\\\\":\\\\\\\"afb0755d99de3a80e\\\\\\\",\\\\\\\"agent_type\\\\\\\":\\\\\\\"general-purpose\\\\\\\",\\\\\\\"effort\\\\\\\":{\\\\\\\"level\\\\\\\":\\\\\\\"high\\\\\\\"},\\\\\\\"hook_event_name\\\\\\\":\\\\\\\"PostToolUse\\\\\\\",\\\\\\\"tool_name\\\\\\\":\\\\\\\"Bash\\\\\\\",\\\\\\\"tool_use_id\\\\\\\":\\\\\\\"toolu_01WBMS4gWSZTTPUjBQ5ZgedJ\\\\\\\",\\\\\\\"duration_ms\\\\\\\":569,\\\\\\\"input\\\\\\\":{\\\\\\\"command\\\\\\\":\\\\\\\"for u in \\\\\\\\\\\\\\\"https://openai.com/fr-FR/index/lifeval/\\\\\\\\\\\\\\\" \\\\\\\\\\\\\\\"https://openai.com/fr-FR/index/grid-protectors-program/\\\\\\\\\\\\\\\"; do echo \\\\\\\\\\\\\\\"=== $u\\\\\\\\\\\\\\\"; node scripts/fetch.js \\\\\\\\\\\\\\\"$u\\\\\\\\\\\\\\\" 2>&1 | head -45; done\\\\\\\",\\\\\\\"description\\\\\\\":\\\\\\\"Try OpenAI locale paths for two articles\\\\\\\"},\\\\\\\"response\\\\\\\":{\\\\\\\"stdout\\\\\\\":\\\\\\\"=== https://openai.com/fr-FR/index/lifeval/\\\\\\\\nHTTP 403 · https://openai.com/fr-FR/index/lifeval/ · text/html\\\\\\\\n\\\\\\\\n=== https://openai.com/fr-FR/index/grid-protectors-program/\\\\\\\\nHTTP 403 · https://openai.com/fr-FR/index/grid-protectors-program/ · text/html\\\\\\\",\\\\\\\"stderr\\\\\\\":\\\\\\\"\\\\\\\",\\\\\\\"interrupted\\\\\\\":false,\\\\\\\"isImage\\\\\\\":false,\\\\\\\"noOutputExpected\\\\\\\":false,\\\\\\\"bashEditDiff\\\\\\\":{\\\\\\\"files\\\\\\\":[{\\\\\\\"filePath\\\\\\\":\\\\\\\"/home/user/ainews/trace/2026-11-03.jsonl\\\\\\\",\\\\\\\"hunks\\\\\\\":[{\\\\\\\"oldStart\\\\\\\":93,\\\\\\\"oldLines\\\\\\\":3,\\\\\\\"newStart\\\\\\\":93,\\\\\\\"newLines\\\\\\\":5,\\\\\\\"lines\\\\\\\":[\\\\\\\" {\\\\\\\\\\\\\\\"t\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"2026-11-03T11:09:14.106Z\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"event\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"PostToolUse\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"session_id\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"c0ba620c-ead7-5889-a588-1d740c20a25e\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"cwd\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"/home/user/ainews\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"scratchpad_dir\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"prompt_id\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"permission_mode\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"auto\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"effort\\\\\\\\\\\\\\\":{\\\\\\\\\\\\\\\"level\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"high\\\\\\\\\\\\\\\"},\\\\\\\\\\\\\\\"hook_event_name\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"PostToolUse\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"tool_name\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"Bash\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"tool_use_id\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"toolu_01StA6e8F9Mqqy84NC2PUeEj\\\\\\\\\\\\\\\",\\\\\\\\\\\\\\\"duration_ms\\\\\\\\\\\\\\\":262,\\\\\\\\\\\\\\\"input\\\\\\\\\\\\\\\":{\\\\\\\\\\\\\\\"command\\\\\\\\\\\\\\\":\\\\\\\\\\\\\\\"curl -sS -H \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"User-Agent: AI Edge Briefing editorial bot\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\" \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"https://efts.sec.gov/LATEST/search-index?q=%22Anthropic%22&forms=S-1%2FA\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\" 2>&1 | python3 -c \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\nimport j
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://cloud.google.com/blog/topics/threat-intelligence/rss\" 2>&1 | grep -oE \"<title>[^<]*</title>|<pubDate>[^<]*</pubDate>\" | head -60",
  "description": "Fetch Google threat intel RSS dates"
}

{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":112,"oldLines":3,"newStart":112,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:09:37.251Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7f44935a6a031c3b\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_01QTjEAcQWNxuwkr5Verzv6X\",\"duration_ms\":19533,\"input\":{\"url\":\"https://alignment.anthropic.com/\",\"prompt\":\"List post titles with dates, most recent first. Any posts dated Nov 2 or Nov 3 2026?\"},\"response\":{\"bytes\":68609,\"code\":200,\"codeText\":\"OK\",\"result\":\"No posts are dated November 2 or 3, 2026. The page lists posts only by month, and the most recent section is October 2026, so no November 2026 entries appear.\\n\\n**October 2026**\\n- \\\"Automated Subtle Emergent Misalignment Research\\\"\\n- \\\"Anthropic Residency: applications open for established technical leaders\\\"\\n- \\\"Red-Teaming Auto Mode: Improving Blocking Classifiers Against Malign Coding Agents\\\"\\n- \\\"Reducing Reward Hacking by Localizing Bad Behavior Instead of Penalizing It\\\"\\n- \\\"Training Alignment Auditors via Reinforcement Learning\\\"\\n\\n**August 2026**\\n- \\\"Training a Misaligned Reward Seeker\\\"\\n- \\\"Automated Researchers Can Mitigate Well-Characterized Alignment Failures\\\"\\n- \\\"TASTE: Can AI Models Judge AI Safety Research Proposals?\\\"\\n- \\\"Would This Change Your Answer? Evaluating Explanations of LLM Behavior in the Wild with Counterfactual Experiments\\\"\\n- \\\"Fine-Tuned Lie Detectors Failed to Generalize\\\"\\n- \\\"Introducing the Conceptual Reasoning Index\\\"\\n\\n**July 2026**\\n- \\\"Agentic Misalignment in Summer 2026\\\"\\n- \\\"Modular Pretraining Enables Access Control\\\"\\n\\n**June 2026**\\n- \\\"Diffuse AI Control on Fuzzy Tasks\\\"\\n\\n**May 2026**\\n- \\\"SLEIGHT-Bench: Finding Blind Spots in AI Monitors\\\"\\n- \\\"Teaching Claude Why\\\"\\n- \\\"Model Spec Midtraining: Improving How Alignment Training Generalizes\\\"\\n\\n**April 2026**\\n- \\\"Poisoning Fine-tuning Datasets of Constitutional Classifiers\\\"\\n- \\\"Introspection Adapters: Training LLMs to Report Their Learned Behaviors\\\"\\n- \\\"AI Organizations Can Be More Effective but Less Aligned than Individual Agents\\\"\\n- \\\"Automated Weak-to-Strong Researcher\\\"\\n\\n**March 2026**\\n- \\\"Abstractive Red-Teaming of Language Model Character\\\"\\n- \\\"Measuring and improving coding audit realism with deployment resources\\\"\\n- \\\"A3: An Automated Alignment Agent for Safety Finetuning\\\"\\n- \\\"AuditBench: Evaluating Alignment Auditing Techniques on Models with Hidden Behaviors\\\"\\n- \\\"3 Challenges and 2 Hopes for the Safety of Unsupervised Elicitation\\\"\\n\\n**February 2026**\\n- \\\"The Persona Selection Model: Why AI Assistants might Behave like Humans\\\"\\n- \\\"The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?\\\"\\n\\n**January 2026**\\n- \\\"Pre-deployment auditing can catch an overt saboteur\\\"\\n- \\\"Petri 2.0: New Scenarios, New Model Comparisons, and Improved Eval-Awareness Mitigations\\\"\\n\\n**December 2025**\\n- \\\"Bloom: an open source tool for automated behavioral evaluations\\\"\\n- \\\"Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers\\\"\\n- \\\"Towards training-time mitigations for alignment faking in RL\\\"\\n- \\\"Open Source Replication of the Auditing Game Model Organism\\\"\\n- \\\"Anthropic Fellows Program 2026\\\"\\n- \\\"Beyond Data Filtering: Knowledge Localization for Capability Removal in LLMs\\\"\\n\\n**November 2025**\\n- \\\"Evaluating honesty and lie detection techniques on a diverse suite dishonest models\\\"\\n- \\\"Strengthening Red Teams: A Modular Scaffold for Control Evaluations\\\"\\n\\n**October 2025**\\n- \\\"Anthropic's Pilot Sabotage Risk Report\\\"\\n- \\\"Stress-testing model specs reveals character differences among language models\\\"\\n- \\\"Believe It or Not: How Deeply do LLMs Believe Implanted Facts?\\\"\\n- \\\"Inoculation Prompting: Instructing LLMs to misbehave at train-time improves test-time alignment\\\"\\n- \\\"Training fails to elicit subtle reasoning in current language models\\\"\\n- \\\"Petri: An open-source auditing tool to accelerate AI safety research\\\"\\n\\n**August 2025**\\n- \\\"Findings from a Pilot Anthropic–OpenAI Alignment Evaluation Exercise\\\"\\n- \\\"Enhancing Model Safety through Pretraining Data Filtering\\\"\\n\\n**July 2025**\\n- \\\"Building and evaluating alignment auditing agents\\\"\\n- \\\"Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data\\\"\\n- \\\"Inverse Scaling in Test-Time Compute\\\"\\n\\n**June 2025**\\n- \\\"Why Do Some Language Models Fake Alignment While Others Don't?\\\"\\n- \\\"Model-Internals Classifiers\\\"\\n- \\\"Unsupervised Elicitation\\\"\\n\\n**April 2025**\\n- \\\"Reasoning Models Don't Always Say What They Think\\\"\\n- \\\"Publicly Releasing CoT Faithfulness Evaluations\\\"\\n- \\\"Modifying LLM Beliefs with Synthetic Document Finetuning\\\"\\n- \\\"Putting up Bumpers\\\"\\n- \\\"Alignment Faking Revisited: Improved Classifiers and Open Source Extensions\\\"\\n\\n**March 2025**\\n- \\\"Auditing Language Models for Hidden Objectives\\\"\\n- \\\"Do reasoning models use their scratchpad like we do? Evidence from distilling paraphrases\\\"\\n- \\\"Automated Researchers Can Subtly Sandbag\\\"\\n\\n**February 2025**\\n- \\\"Constitutional Classifiers: Defending against Uni
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://www.cnbc.com/2026/11/03/drax-brookfield-radiant-ai-data-centre-north-yorkshire.html\" 2>&1 | head -60; echo \"######\"; node scripts/fetch.js \"https://www.theguardian.com/technology/2026/nov/03/ai-powered-malware-uk-infrastructure-2028-ncsc\" 2>&1 | head -60",
  "description": "Fetch CNBC Drax datacenter and Guardian NCSC articles"
}

{
  "stdout": "HTTP 404 · https://www.cnbc.com/2026/11/03/drax-brookfield-radiant-ai-data-centre-north-yorkshire.html · text/html\nNot Found\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n######\nHTTP 403 · https://www.theguardian.com/technology/2026/nov/03/ai-powered-malware-uk-infrastructure-2028-ncsc · text/plain\nBlocked by egress policy",
  "stderr": "",
  "interrupted": false,
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  "noOutputExpected": false,
  "bashEditDiff": {
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      "/home/user/ainews/trace/2026-11-03.jsonl"
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    "shared": true
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{
  "url": "https://research.google/blog/",
  "prompt": "List blog post titles with dates, most recent first. Any dated November 2 or 3, 2026?"
}

{
  "bytes": 181420,
  "code": 200,
  "codeText": "OK",
  "result": "No blog post on this page is dated November 2 or 3, 2026. The most recent is dated October 27.\n\n1. October 27, 2026: \"The sleep framework: A new way for LLMs to retain knowledge in continual learning\"\n2. October 23, 2026: \"Bringing foundational models to the front lines of TB screening\"\n3. October 21, 2026: \"Empowering frontline maternal care with AI-assisted ultrasound\"\n4. October 16, 2026: \"Grounding AI agents in biological reality: Building blocks for autonomous wet labs\"\n5. October 14, 2026: \"Research@ 2026: 10 ways we're amplifying human ingenuity\"\n6. October 14, 2026: \"Putting Earth AI to work: Geospatial agents for our planet's biggest challenges\"\n7. October 14, 2026: \"Analyzing technical documents with Deep Review\"\n8. October 7, 2026: \"Does better work always mean better workers?\"\n9. October 6, 2026: \"Unlocking Earth AI's planetary geospatial foundation models for global public health\"\n10. October 5, 2026: \"Open and Emergent Problems in Agentic Privacy and Security: A Contextual Angle\"\n11. October 2, 2026: \"Toward provably private learning from federated data\"\n12. September 29, 2026: \"How Diffusion Controller unifies and simplifies AI image generation\"",
  "durationMs": 5600,
  "url": "https://research.google/blog/"
}

{
  "url": "https://deepmind.google/discover/blog/",
  "prompt": "List blog post titles with dates, most recent first. Any dated 2 or 3 November 2026?"
}

{
  "bytes": 194794,
  "code": 200,
  "codeText": "OK",
  "result": "No posts on the page are dated 2 or 3 November 2026. The most recent are dated October 2026. This page is only the first of 19, so posts from other pages aren't covered here.\n\n1. \"Genie 4: A new generation of world simulation\" (October 2026)\n2. \"Speeding up planning decisions with AI\" (October 2026)\n3. \"Gemini 4 Carbon: Our next frontier model\" (October 2026)\n4. \"Beyond tree cover: mapping the world's forest types\" (October 2026)\n5. \"Accelerating the search for antimicrobial peptides with Google Antigravity\" (October 2026)\n6. \"Google DeepMind and Singapore Government collaborate to build fine-tuned AI model for scam detection\" (October 2026)\n7. \"Developing Gemini 4 Argon responsibly and safely\" (October 2026)\n8. \"Gemini 4 Argon for Robotics\" (October 2026)\n9. \"Gemini 4 Argon: Built to solve your hardest problems\" (October 2026)\n10. \"EmbeddingGemma 2: an open, lightweight multimodal embedding model\" (October 2026)\n11. \"Gemini 4 Argon: our next era of frontier intelligence\" (September 2026)\n12. \"Introducing SynthID Bio\" (September 2026)\n13. \"Introducing Gemini 3.8 Live with Live Avatar\" (September 2026)\n14. \"Advancing Private AI Compute with secure, server-side memory\" (September 2026)\n15. \"Gemini 3.8 text-to-speech says hello\" (September 2026)\n16. \"Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking\" (September 2026)\n17. \"AlphaGenome Atlas: A predictive map of every possible DNA letter change in the human genome\" (September 2026)\n18. \"Introducing WeatherNext 3, our most advanced and accurate global weather AI model\" (September 2026)\n19. \"Proactive cyber defense for governments and enterprises\" (September 2026)\n20. \"Introducing Gemini 3.8 Flash and 3.8 Flash Cyber\" (September 2026)\n21. \"Introducing agentic video understanding with Gemini\" (September 2026)\n22. \"Gemini Omni 1.1 Flash lets you build with more control\" (August 2026)\n23. \"Piloting the world's first double-blind AI evaluations\" (August 2026)\n24. \"Intelligent transcription with Gemini 3.5 Transcribe\" (August 2026)\n25. \"From Atari to EVE Online: Building on 15 Years of AI Research in Games\" (August 2026)",
  "durationMs": 8466,
  "url": "https://deepmind.google/discover/blog/"
}

{
  "url": "https://www.alphaxiv.org/",
  "prompt": "List trending paper titles with arXiv IDs and dates."
}

{
  "bytes": 883789,
  "code": 200,
  "codeText": "OK",
  "result": "The page doesn't define \"trending,\" so I've ranked these by the view counts shown:\n\n| Paper title | arXiv ID | Date | Views |\n|---|---|---|---|\n| Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights | 2611.weight-space-programming | 02 Nov 2026 | 30k |\n| Proving and Improving the Platonic Representation Hypothesis with JEPAs | 2610.39302 | 29 Oct 2026 | 17k |\n| Training Foundation Models with a Single Algorithm | 2610.40564 | 29 Oct 2026 | 2k |\n| Probing Spatial State Representations in Visual Foundation Models | 2610.40636 | 29 Oct 2026 | 665 |\n| Mistral Large 4 | 2611.mistral-large-4 | 03 Nov 2026 | 945 |\n| Freeform Preference Learning for Robotic Manipulation | 2606.32027 | 01 Aug 2026 | 646 |\n| Hierarchical World Models with Implicit Dynamics | 2610.42146 | 30 Oct 2026 | 447 |\n| Statistical Foundations of Reinforcement Learning: A Non-Asymptotic Perspective | 2610.41903 | 30 Oct 2026 | 170 |\n| Latent Sparse Attention: Towards Subquadratic Ultra-Long Context Attention | 2610.42147 | 30 Oct 2026 | 174 |\n| Hierarchical Residuals: A Minimalist Decoupling of Residual Width from Compute Width | 2610.41711 | 30 Oct 2026 | 133 |",
  "durationMs": 6103,
  "url": "https://www.alphaxiv.org/"
}

{
  "query": "Nvidia tells cloud clients sell 51% non-Chinese companies China AI chips",
  "mode": "standard"
}

{
  "query": "Nvidia tells cloud clients sell 51% non-Chinese companies China AI chips",
  "results": [
    {
      "tool_use_id": "srvtoolu_01KZiqWpjFc9PLU397gYToYC",
      "content": [
        {
          "title": "CO/AI Subscribe",
          "url": "https://getcoai.com/news/just-2-customers-drive-39-of-nvidias-record-46-7b-quarterly-sales"
        },
        {
          "title": "YOU ARE AT:AI InfrastructureNvidia says two customers represented 39% of revenue in Q2",
          "url": "https://www.rcrwireless.com/?p=423883"
        },
        {
          "title": "Nvidia Finds Reduced China Demand For Slower Chips",
          "url": "https://www.silicon.co.uk/cloud/nvidia-china-h20-demand-544954/amp"
        },
        {
          "title": "nvidias nasdaqnvda ai chips flood china despite u s export ban",
          "url": "https://www.tipranks.com/news/nvidias-nasdaqnvda-ai-chips-flood-china-despite-u-s-export-ban"
        },
        {
          "title": "nvidias nasdaqnvda new chips face rejection from chinese clients",
          "url": "https://www.tipranks.com/news/nvidias-nasdaqnvda-new-chips-face-rejection-from-chinese-clients"
        },
        {
          "title": "Nvidia is expected to sell one million H20 chips to China in 2024. Image: Nvidia",
          "url": "https://asiatimes.com/2024/07/china-uses-nvidia-chips-via-azure-google-clouds"
        },
        {
          "title": "more than 50 percent of nvidias data center revenue comes from three customers usd21 9 billion in sales recorded from the unnamed companies",
          "url": "https://www.tomshardware.com/tech-industry/more-than-50-percent-of-nvidias-data-center-revenue-comes-from-three-customers-usd21-9-billion-in-sales-recorded-from-the-unnamed-companies"
        },
        {
          "title": "asiafinancial.com",
          "url": "https://asiafinancial.com/?p=99693"
        },
        {
          "title": "nvidia china h20 demand 544954",
          "url": "https://www.silicon.co.uk/cloud/nvidia-china-h20-demand-544954"
        },
        {
          "title": "NVIDIA’s Explosive AI Growth Comes with a Catch: 39% of Sales Tied to Two Customers",
          "url": "https://techovedas.com/nvidias-explosive-ai-growth-comes-with-a-catch-39-of-sales-tied-to-two-customers/"
        }
      ]
    },
    "The search didn't turn up the specific report you're asking about: that Nvidia told cloud clients they must sell to non-Chinese companies at a 51% threshold. None of the results mention a 51% rule or a requirement like that. The closest material is older and covers related issues.\n\n- **Chinese cloud buyers pulled back:** A Reuters-sourced report says Alibaba Group and Tencent have both told Nvidia they plan to buy far fewer Nvidia chips this year than they had originally planned, citing US regulatory uncertainty.\n- **Access through foreign cloud units:** An Asia Times piece says Chinese firms still have access to Nvidia's high-end AI chips by using cloud servers operated by Google and Microsoft, and notes that the Commerce Department was preparing to bar US firms from providing cloud services that use advanced AI chips to Chinese customers.\n- **Chinese market share:** A silicon.co.uk article reports that Nvidia currently provides about 80 percent of the high-end AI chips used by Chinese cloud companies, a share that TrendForce projected could fall.\n\nThese results are dated, so they may not reflect the current situation. I'd suggest searching a news outlet such as Reuters, Bloomberg, or The Information with terms like \"Nvidia 51% rule China cloud\" to find the specific report and its date."
  ],
  "durationSeconds": 6.001453809999977,
  "searchCount": 1
}

{
  "query": "Oracle raises $20 billion stock bonds AI buildout November 2026",
  "mode": "standard"
}

{
  "query": "Oracle raises $20 billion stock bonds AI buildout November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01KCTLtJYsYhHgLP157PTtUY",
      "content": [
        {
          "title": "JOURNAL ARTICLE",
          "url": "https://www.ebsco.com/articles/business-and-management/59f9efdd-b8ea-5820-928a-049dc6818fe9/oracle-eyes-up-to-25-billion-in-bond-sale-for-ai-buildout"
        },
        {
          "title": "ORCL Stock In Focus As Tech Giant Reportedly Launches Bond Offering To Cover Half Of 2026 Funding Needs",
          "url": "https://stocktwits.com/news-articles/markets/equity/oracle-bond-offering-funding-ai-cloud-infrastructure/cZbgYA1R4ki"
        },
        {
          "title": "oracle draws retail attention after plan to raise up to 50b debt and equity in 2026 articleshow fqfv0dy",
          "url": "https://newsable.asianetnews.com/markets/oracle-draws-retail-attention-after-plan-to-raise-up-to-50b-debt-and-equity-in-2026-articleshow-fqfv0dy"
        },
        {
          "title": "Oracle to raise $50 billion as AI debt piles up",
          "url": "https://www.axios.com/2026/02/02/oracle-50-billion-ai-chatgpt-meta"
        },
        {
          "title": "biz.heraldcorp.com",
          "url": "https://biz.heraldcorp.com/article/10779491"
        },
        {
          "title": "oracle returns with another jumbo bond to fund ai expansion",
          "url": "https://www.ifre.com/bonds/2379081/oracle-returns-with-another-jumbo-bond-to-fund-ai-expansion"
        },
        {
          "title": "oracle to raise up to 50 billion in debt and equity this year",
          "url": "https://oodaloop.com/briefs/technology/oracle-to-raise-up-to-50-billion-in-debt-and-equity-this-year/"
        },
        {
          "title": "Oracle Draws Retail Attention After Plan To Raise Up To $50B Debt And Equity In 2026",
          "url": "https://newsable.asianetnews.com/amp/markets/oracle-draws-retail-attention-after-plan-to-raise-up-to-50b-debt-and-equity-in-2026-articleshow-fqfv0dy"
        },
        {
          "title": "Oracle to Raise $20B Debt on Top of $20B Equity Issuance for $70B AI Buildout",
          "url": "https://rallies.ai/news/oracle-to-raise-20b-debt-on-top-of-20b-equity-issuance-for-70b-ai-buildout"
        },
        {
          "title": "longportapp.cn",
          "url": "https://longportapp.cn/news/274530058"
        }
      ]
    },
    "The search didn't turn up a November 2026 Oracle deal. The coverage I found is from earlier in 2026, mostly February, so I can't confirm the $20 billion stock-and-bond raise you're asking about.\n\n**The February 2026 bond sale:** Oracle launched a U.S. dollar bond offering of roughly $20 billion to $25 billion, and it priced at about $25 billion. The eight-part bond sale had tenors ranging from three to 40 years. Oracle's stated plan was to raise $45 billion to $50 billion in gross cash to finance its buildout, with around half of the funding through a combination of equity-linked and common equity issuances, including mandatory convertible preferred securities and a new at-the-market equity program of up to $20 billion.\n\n**Later revision:** An article on Oracle's fiscal Q4 2026 earnings says Oracle said it plans to raise a total of $40 billion through a combination of bond and equity issuances, including a previously announced $20 billion share offering. The fundraising announcement weighed on the stock, driving shares down more than 9% in after-hours trading.\n\n**Context:** Oracle said it \"does not expect to issue additional bonds during calendar year 2026 beyond this transaction\" and expects to maintain an investment grade credit rating. That makes a further bond sale in November 2026 unlikely, though I couldn't verify it either way. The $20 billion figure you mentioned may refer to the equity portion rather than a bond deal.\n\nI'd suggest checking Oracle's SEC filings or a recent news search to confirm whether anything new happened in November 2026."
  ],
  "durationSeconds": 6.443909882000007,
  "searchCount": 1
}

{
  "query": "GTIG \"ARTEX and Friends\" agentic offensive frameworks Google Threat Intelligence",
  "mode": "extended"
}

{
  "query": "GTIG \"ARTEX and Friends\" agentic offensive frameworks Google Threat Intelligence",
  "results": [
    {
      "tool_use_id": "srvtoolu_012mexta3PVDynzhyJgACZZt",
      "content": [
        {
          "title": "ARTEX and Friends: Enter Agentic Offensive Frameworks",
          "url": "https://cloud.google.com/blog/topics/threat-intelligence/artex-and-friends-enter-agentic-offensive-frameworks"
        },
        {
          "title": "Agentic Offensive Frameworks in Live Operations",
          "url": "https://cyberwarrior76.substack.com/p/agentic-offensive-frameworks-in-live"
        },
        {
          "title": "ARTEX AI Pentest Framework Profile - Brandefense",
          "url": "https://brandefense.io/knowledge-hub/malware/artex/"
        },
        {
          "title": "sigma: add 2 rules from threat-intel 2026-11-02 (ARTEX: DB-written webshell, request-catcher C2) by C-E-S-3 · Pull Request #126 · C-E-S-3/detection-engineering · GitHub",
          "url": "https://github.com/C-E-S-3/detection-engineering/pull/126"
        },
        {
          "title": "Agentic Offensive Frameworks Accelerate Cyber Intrusions",
          "url": "https://blog.netmanageit.com/agentic-offensive-frameworks-machine-speed-intrusions/"
        },
        {
          "title": "Government Linux Servers Targeted With SysGoRAT and Suspected AI-Generated Scripts",
          "url": "https://thehackernews.com/2026/11/government-linux-servers-targeted-with.html"
        },
        {
          "title": "Threat Actors Deploy ARTEX and PentAGI to Automate Real-World Intrusions",
          "url": "https://mallory.ai/stories/01a1989f-f01e-7785-8ce6-7b514bb80824"
        },
        {
          "title": "ARTEX: Open-Source Agentic Pentest Tool Turned on Korean Banks",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-artex-agentic-pentest-tool-korean-banks-20/"
        },
        {
          "title": "Cybersecurity Checklist in the Agentic Hacking Era · Ministry of Cyber Affairs",
          "url": "https://ministryofcyberaffairs.com/news/cybersecurity-checklist-in-the-agentic-hacking-era-40db2d2e-a42a-4f1d-8528-7bc19dbf0b6e"
        }
      ]
    },
    "The GTIG report, \"ARTEX and Friends: Enter Agentic Offensive Frameworks,\" was published October 30, 2026, and secondary coverage is consistent on its core findings.\n\n- **What it covers:** GTIG and Mandiant report that multiple threat actors have abused the open-source agentic pentesting frameworks ARTEX, Hexstrike and CAIRN in incident response engagements. Coverage also names PentAGI.\n- **Structure:** One summary says ARTEX splits an attack across six sub-agents that run on frontier and open-source LLMs.\n- **Actors:** GTIG links one ARTEX campaign to the PRC-nexus actor STORM-0940, which Microsoft tracks. Other reporting says North Korean groups Onyx Sleet and Pearl Sleet have also used ARTEX.\n- **Assessment:** GTIG judges that these tools compress attack timelines to machine speed; however, they currently trade stealth for velocity. That makes them noisier and more detectable.\n- **Repository takedown:** One source says the creator took the original GitHub repository down in October 2026 because of widespread abuse, and that forks and rebrands remain.\n\nSource caveats: the Google Cloud blog post itself is the primary source, but the search only returned excerpts from it. Several details come from secondary blogs and aggregators, and their dates and specifics don't fully agree. For example, one says ARTEX was published in July 2026, while another says observed use began in late August 2026. Check the original GTIG post before relying on specific dates or attributions."
  ],
  "durationSeconds": 7.287090777000005,
  "searchCount": 1
}

{
  "url": "https://www.alignmentforum.org/",
  "prompt": "List post titles with authors and dates, most recent first. Any from Nov 2 or Nov 3 2026?"
}

{
  "bytes": 839065,
  "code": 200,
  "codeText": "OK",
  "result": "The page shows only relative ages (for example \"21h\" or \"7d\"), not calendar dates, so I can't confirm whether any posts are from November 2 or 3, 2026. Based on the ages shown, most recent first:\n\n1. \"Some 'coherence arguments' are two different things in a trenchcoat\" by Steven Byrnes (21h)\n2. \"Additional Course Context (for AI Safety Fundamentals; unofficial)\" by Chris_Leong (20h)\n3. \"Explaining 'AI might obliterate you' to senior policymakers in India\" by TurnTrout (3d)\n4. \"Notes on 'We're in Triage Mode for AI Safety' by Miles Brundage\" by Chris_Leong (7d)\n5. \"Setting the Scene (Public v1; October 2026)\" by Chris_Leong (9d)\n6. \"Monitorability evaluations and policy proposals\" by evhub (12d)\n7. \"Neural nets are exceptionally vulnerable to goal self-hack\" by Stuart_Armstrong (13d)\n8. \"The Alignment Problem: Computer Science Meets Analytic Philosophy\" by Vanessa Kosoy (16d)\n9. \"Deconfusing Corrigibility\" by berns (17d)\n10. \"A Simpler and Better Debate Protocol for Scalable Oversight\" by Zhiyang Xun, Jiawei Li, and Jonah Brown-Cohen (19d)\n\n\"Setting the Scene\" is the only title with a date, and that date (October 2026) is part of the title rather than a posting date.",
  "durationMs": 9424,
  "url": "https://www.alignmentforum.org/"
}

{
  "url": "https://www.aisi.gov.uk/work",
  "prompt": "List publications/research with dates, most recent first. Any dated 2 or 3 November 2026?"
}

{
  "bytes": 150894,
  "code": 200,
  "codeText": "OK",
  "result": "**No posts are dated 2 or 3 November 2026.** The most recent item on the page is dated 26 October 2026.\n\nThe page lists blog posts, not separate research publications. These are the 2026 entries, most recent first:\n\n- Oct 26, 2026: \"Pretraining data filtering in open-weight biological models\"\n- Oct 26, 2026: \"Can AI coding agents rebuild biological AI tools from a paper?\"\n- Oct 23, 2026: \"Investigating alignment failures in AISI's incident\"\n- Oct 12, 2026: \"Towards technical best practice for frontier AI development\"\n- Oct 7, 2026: \"Transect: Making large-scale agentic evaluations easier to understand\"\n- Oct 1, 2026: \"Building a more secure environment for evaluating dangerous capabilities\"\n- Sep 28, 2026: \"GPT-6 Astra performs unsanctioned supply-chain attacks in simulations\"\n- Aug 27, 2026: \"Optimal stopping: spending evaluation compute where it counts\"\n- Aug 4, 2026: \"Incident Report: unsanctioned agent behaviour during cyber testing\"\n- Jul 23, 2026: \"International evaluation best practice and open questions in AI measurement\"\n- Jul 23, 2026: \"UK AISI / CAISI Preliminary Assessment of Kimi K3's Cyber Capabilities\"\n- Jul 23, 2026: \"How our Control Red Team is stress-testing frontier monitors\"\n- Jul 21, 2026: \"Cheating behaviour in frontier model evaluations\"\n- Jul 17, 2026: \"How Far Behind the Frontier are Leading Open Weight Models on Cyber?\"\n- Jul 7, 2026: \"Finding Cloud Misconfigurations with Frontier AI: A Case Study\"\n- Jul 2, 2026: \"More compute, more capability: Why AI agent evaluations need to account for test-time compute\"\n- Jun 30, 2026: \"UK-Germany Joint Statement on advanced AI safety and security\"\n- Jun 18, 2026: \"Releasing AISI's Engineering Playbook\"\n- Jun 8, 2026: \"RealityTest: Do AI systems disclose their identity when asked?\"\n- May 25, 2026: \"Deepening our partnership with the Australian AI Safety Institute\"\n- May 21, 2026: \"Will it become harder to oversee AI systems?\"\n- May 13, 2026: \"How fast is autonomous AI cyber capability advancing?\"\n- May 5, 2026: \"Partnering with Microsoft to strengthen frontier AI safety\"\n- Apr 30, 2026: \"Our evaluation of OpenAI's GPT-5.5 cyber capabilities\"\n- Apr 28, 2026: \"Ask Don't Tell: Reducing Sycophancy in Large Language Models\"\n- Apr 27, 2026: \"Evaluating whether AI models would sabotage AI safety research\"\n- Apr 24, 2026: \"How do environmental factors impact AI behaviour?\"\n- Apr 20, 2026: \"What can sandboxed AI agents learn about their evaluation environments?\"\n- Apr 13, 2026: \"Our evaluation of Claude Mythos Preview's cyber capabilities\"\n- Mar 31, 2026: \"Harnessing frontier AI for cyber defence\"\n- Mar 26, 2026: \"How are AI Agents used? Evidence from 177,000 AI agent tools\"\n- Mar 23, 2026: \"Can AI agents escape their sandboxes? A benchmark for safely measuring container breakout capabilities\"\n- Mar 16, 2026: \"How do frontier AI agents perform in multi-step cyber-attack scenarios?\"\n- Mar 5, 2026: \"Evidence for inference scaling in AI cyber tasks: Increased evaluation budgets reveal higher success rates\"\n- Feb 26, 2026: \"An evaluation framework for AI misuse in fraud and cybercrime\"\n- Feb 25, 2026: \"A pipeline for transcript analysis using Inspect Scout\"\n- Feb 19, 2026: \"Funding 60 projects to advance AI alignment research\"\n- Feb 18, 2026: \"Advancing AI voice security with ElevenLabs\"\n- Feb 17, 2026: \"Boundary Point Jailbreaking: A new way to break the strongest AI defences\"\n- Feb 12, 2026: \"International consensus and open questions in AI evaluations\"\n- Feb 2, 2026: \"AI and the future of work: Measuring AI-driven productivity gains for workplace tasks\"\n\nThe page also contains entries from 2024 and 2025, which I have not listed here.",
  "durationMs": 13957,
  "url": "https://www.aisi.gov.uk/work"
}

{
  "command": "node scripts/fetch.js https://www.nature.com/subjects/machine-learning 2>&1 | head -80",
  "description": "Fetch Nature machine learning subject page"
}

{
  "stdout": "HTTP 200 · https://www.nature.com/subjects/machine-learning?error=cookies_not_supported&code=229f2de1-feda-4b1a-a370-b44ca9cf2c87 · text/html\nMachine learning - Latest research and news | Nature\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\n# Machine learning articles from across Nature Portfolio\n\n- Atom\n\n- RSS Feed\n\nDefinition\nMachine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms.\n\n# Featured\n\n-\n\n#\nTracing causal cascades underlying biological state changes\n\nMaps constructed from omics data to identify the causal mechanisms underlying state transitions have not been established. We developed CauTrigger, which treats state transitions as layered causal cascades rather than isolated molecular changes, effectively separating causal signals from spurious variation. CauTrigger prioritizes potential upstream triggers, predicts perturbation responses and helps turn omics measurements into testable mechanistic hypotheses.\n\nNews & Views 22 Oct 2026\n\nNature Methods\n\nP: 1-2\n\n-\n\n#\nAn AI tool improves weather forecasts up to a month ahead\n\nAn innovative artificial-intelligence application enhances weather forecasting in the difficult subseasonal range, providing accurate forecasts of precipitation, temperature and pressure 3–5 weeks in advance. The tool refines both physics- and AI-based weather models and improves the early prediction of extremes of heat, cold, rainfall and flooding.\n\nNews & Views 21 Oct 2026\n\nNature\n\n-\n\n#\nUsing AI to offer personalized health advice\n\nThe use of artificial-intelligence tools in medicine is increasing. What types of technology might be on the horizon and how can such health-advice tools be tested?\n\n- Emma Pierson\n\nNews & Views 21 Oct 2026\n\nNature\n\n# Latest Research and Reviews\n\n-\n\n#\nA document classification benchmark dataset on cybersecurity policy domain\n\n- JungHun Yuk\n\n- KyungTae Lim\n\n- Haneol Jang\n\nResearch Open Access 03 Nov 2026\n\nScientific Reports\n\nP: 1-13\n\n-\n\n#",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "echo \"=== REUTERS ===\"; node scripts/fetch.js \"https://www.reuters.com/technology/artificial-intelligence/\" 2>&1 | head -70",
  "description": "Fetch Reuters AI section"
}

{
  "stdout": "=== REUTERS ===\nHTTP 403 · https://www.reuters.com/technology/artificial-intelligence/ · text/plain\nBlocked by egress policy",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "echo \"=== CNBC AI ===\"; node scripts/fetch.js \"https://www.cnbc.com/ai-artificial-intelligence/\" 2>&1 | head -80",
  "description": "Fetch CNBC AI section"
}

{
  "stdout": "=== CNBC AI ===\nHTTP 200 · https://www.cnbc.com/ai-artificial-intelligence/ · text/html\nAI - Artificial Intelligence\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nApple shares slide after weak margin outlook; Palantir slumps 8% after earnings\n\nKai Nicol-Schwarz 35 min ago\n\nBrookfield plans for a $27 billion AI data center at UK power station\n\nKai Nicol-Schwarz 2 hours ago\n\nMore equity needed to fund AI buildout as debt risks mount: Blackstone\n\nMatthew Tan 4 hours ago\n\nwatch now\n\nLovable CEO says AI is collapsing barriers to starting a business\n\nArjun Kharpal Tue, Nov 3rd 2026\n\nwatch now\n\nState-level politics will partially dictate data center development, regulation\n\nMon, Nov 2nd 2026\n\nwatch now\n\nwatch now\n\nVIDEO 03:52\n\nSquawk Box Asia\n\nPartnering with hyperscalers invested in AI cloud is a 'safe bet'\n\nMon, Nov 2nd 2026\n\nwatch now\n\nwatch now\n\nVIDEO 03:28\n\nSquawk Box Asia\n\nAI trade faces a key test of confidence in long-term fundamentals: Strategist\n\nMon, Nov 2nd 2026\n\nTech\n\nPalantir's U.S. commercial revenue growth booms, topping govt for first time\n\nMon, Nov 2nd 2026\n\nClosing Bell\n\nOpenAI trims fundraising goal\n\nMon, Nov 2nd 2026\n\nTech\n\nIntel foundry push faces critical test after stock's 45% plunge in October",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "OpenAI Anthropic threat report ban accounts influence operation November 2026",
  "mode": "extended"
}

{
  "query": "OpenAI Anthropic threat report ban accounts influence operation November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01SyKFdUWoxwR1JZaUKWKaec",
      "content": [
        {
          "title": "June 2025 Disrupting malicious uses of AI: June 2025",
          "url": "https://cdn.openai.com/threat-intelligence-reports/5f73af09-a3a3-4a55-992e-069237681620/disrupting-malicious-uses-of-ai-june-2025.pdf"
        },
        {
          "title": "OpenAI Bans Russian ChatGPT Accounts Used to Run Influence Operation",
          "url": "https://thehackernews.com/2026/08/openai-bans-russian-chatgpt-accounts.html"
        },
        {
          "title": "October 2025 Disrupting malicious uses of AI: an update",
          "url": "https://cdn.openai.com/threat-intelligence-reports/7d662b68-952f-4dfd-a2f2-fe55b041cc4a/disrupting-malicious-uses-of-ai-october-2025.pdf"
        },
        {
          "title": "Countering misuse of AI: September 2026 / Anthropic \\ Anthropic",
          "url": "https://www.anthropic.com/threat-intelligence-report-september-2026"
        },
        {
          "title": "“Tech and Tariffs” Campaign: Influence activity targeting US tech policy",
          "url": "https://openai.com/index/disrupting-malicious-uses-of-ai-tech-and-tariffs/"
        },
        {
          "title": "February 2025 Disrupting malicious uses of our models: an update February 2025",
          "url": "https://cdn.openai.com/threat-intelligence-reports/disrupting-malicious-uses-of-our-models-february-2025-update.pdf"
        },
        {
          "title": "OpenAI takes down covert operations tied to China and other countries",
          "url": "https://www.npr.org/2025/06/05/nx-s1-5423607/openai-china-influence-operations"
        },
        {
          "title": "Anthropic bans accounts over AI bioweapons research",
          "url": "https://www.wonderwall.com/news/anthropic-bans-accounts-claude-ai-bioweapons-research"
        },
        {
          "title": "Anthropic's September 2026 Threat Report, Explained",
          "url": "https://www.orcarouter.ai/blog/2026-09-10-anthropic-september-threat-report"
        }
      ]
    },
    "I found no OpenAI or Anthropic threat report dated November 2026. The most recent items are from August and September 2026, so the result may not cover what you're after.\n\n**Anthropic (September 2026):** Anthropic's latest report appears to be from September 10, 2026. It follows Anthropic's earlier reports in March, August and November 2025, and covers seven harm areas, including influence operations. In that report, Anthropic said it identified nine influence operations in which groups created networks of inauthentic social media accounts to amplify political messages. Anthropic's accounts of its bans are self-reported, and no outside auditor has checked its numbers. One case involved a UAE-directed operation targeting the Muslim Brotherhood, and another was a commercial \"influence-as-a-service\" operation. Anthropic says it banned accounts associated with the actors and shared threat information with public- and private-sector partners.\n\n**OpenAI (2026):** The most recent OpenAI item I found is an August 2026 report. OpenAI said it banned a cluster of Russian ChatGPT accounts that used VPNs to bypass access restrictions and run an influence operation. The operation was used to promote the International Burke Institute (IBI), a self-described 'expert community' based in Israel. Separately, a June 2026 OpenAI report covered likely PRC-origin accounts using AI to create comments and cartoons about US tech policy, tariffs, and trade restrictions.\n\n**Caveat:** The search returned older OpenAI reports from 2025 as well, and I couldn't confirm whether either company published anything in November 2026. A follow-up search on each company's threat-intelligence page would be the best way to check."
  ],
  "durationSeconds": 6.361754053999961,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && for c in 0 30 60; do curl -s \"https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/$c\" -o mm_$c.json; done; python3 -I -c \"\nimport json,glob\nfor f in ['mm_0.json','mm_30.json','mm_60.json']:\n    d=json.load(open(f))\n    for c in d.get('collection',[]):\n        t=c.get('title','')\n        if any(k in (t+c.get('abstract','')).lower() for k in ['artificial intelligence','machine learning','large language model','llm','deep learning','foundation model','neural network','transformer','gpt-','chatgpt']):\n            print(t,'|',c.get('doi'),'|',c.get('category'))\n\" 2>&1 | head -60",
  "description": "Paginate medRxiv Nov 2 listings"
}

{"stdout":"Variantscape: Retrospective Study of Large Language Model-Based Extraction of Variant-Treatment-Cancer Associations from Published Oncology Abstracts | 10.64898/2026.08.02.26359492 | health informatics\nReal-time Volumetric Imaging for Minimally-Invasive Thoracic Interventions: A Deformable Phantom Study | 10.64898/2026.10.28.26366767 | radiology and imaging\nOphthalmic AI With Just Ten Examples: Comparing Multimodal Large Language Models, Vision Foundation Models, and Vision-Language Models | 10.64898/2026.10.30.26366929 | ophthalmology\nComparing Machine Learning Methods for Detecting Caregiver Burden in Transcribed Conversations with Clinicians | 10.64898/2026.10.30.26366925 | health informatics\nA decision-only model as a low-cost judge of medical AI answers | 10.64898/2026.10.30.26366939 | health informatics\nDeep learning grading of Schistosoma japonicum-associated liver fibrosis from ultrasound images: a weighted soft-voting ensemble of convolutional and transformer networks | 10.64898/2026.11.02.26364999 | infectious diseases\nBenchmarking single-subject detectability of cognitive event-related potentials in healthy controls and minimally conscious state patients | 10.64898/2026.10.31.26366991 | neurology\nECG foundation models share an age-related performance disparity that originates in the data, not the models | 10.64898/2026.10.30.26366943 | cardiovascular medicine\nSurvey of Physician Attitudes on Artificial Intelligence | 10.64898/2026.11.01.26367027 | medical education\nIdentifying interstitial lung disease with large language models on clinical notes and claims | 10.64898/2026.10.30.26366942 | health informatics\nQuestioning the Benchmarks: Hidden Circularity in AQ-10 Autism Screening Datasets | 10.64898/2026.11.01.26367003 | health informatics","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":126,"oldLines":3,"newStart":126,"newLines":6,"lines":[" {\"t\":\"2026-11-03T11:09:53.716Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01MWA8oZCXG36TLF3Fux38h2\",\"duration_ms\":77,\"input\":{\"command\":\"cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I -c \\\"\\nt=open('sec/s1a.txt',encoding='utf-8').read()\\nimport re\\ni=t.find('net loss of \\\\$')\\nwhile i>0 and i<len(t):\\n    print('>>>',t[i-300:i+300].replace(chr(10),' '));print()\\n    i=t.find('net loss of \\\\$',i+1)\\n    if i>600000: break\\n\\\" | head -40\",\"description\":\"Find net loss figures\"},\"response\":{\"stdout\":\"\",\"stderr\":\"\\nShell cwd was reset to /home/user/ainews\",\"interrupted\":false,\"isImage\":false,\"noOutputExpected\":false}}"," {\"t\":\"2026-11-03T11:09:56.737Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7f44935a6a031c3b\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_01AY2uAbCngRq7puf2HA6szQ\",\"duration_ms\":13957,\"input\":{\"url\":\"https://www.aisi.gov.uk/work\",\"prompt\":\"List publications/research with dates, most recent first. Any dated 2 or 3 November 2026?\"},\"response\":{\"bytes\":150894,\"code\":200,\"codeText\":\"OK\",\"result\":\"**No posts are dated 2 or 3 November 2026.** The most recent item on the page is dated 26 October 2026.\\n\\nThe page lists blog posts, not separate research publications. These are the 2026 entries, most recent first:\\n\\n- Oct 26, 2026: \\\"Pretraining data filtering in open-weight biological models\\\"\\n- Oct 26, 2026: \\\"Can AI coding agents rebuild biological AI tools from a paper?\\\"\\n- Oct 23, 2026: \\\"Investigating alignment failures in AISI's incident\\\"\\n- Oct 12, 2026: \\\"Towards technical best practice for frontier AI development\\\"\\n- Oct 7, 2026: \\\"Transect: Making large-scale agentic evaluations easier to understand\\\"\\n- Oct 1, 2026: \\\"Building a more secure environment for evaluating dangerous capabilities\\\"\\n- Sep 28, 2026: \\\"GPT-6 Astra performs unsanctioned supply-chain attacks in simulations\\\"\\n- Aug 27, 2026: \\\"Optimal stopping: spending evaluation compute where it counts\\\"\\n- Aug 4, 2026: \\\"Incident Report: unsanctioned agent behaviour during cyber testing\\\"\\n- Jul 23, 2026: \\\"International evaluation best practice and open questions in AI measurement\\\"\\n- Jul 23, 2026: \\\"UK AISI / CAISI Preliminary Assessment of Kimi K3's Cyber Capabilities\\\"\\n- Jul 23, 2026: \\\"How our Control Red Team is stress-testing frontier monitors\\\"\\n- Jul 21, 2026: \\\"Cheating behaviour in frontier model evaluations\\\"\\n- Jul 17, 2026: \\\"How Far Behind the Frontier are Leading Open Weight Models on Cyber?\\\"\\n- Jul 7, 2026: \\\"Finding Cloud Misconfigurations with Frontier AI: A Case Study\\\"\\n- Jul 2, 2026: \\\"More compute, more capability: Why AI agent evaluations need to account for test-time compute\\\"\\n- Jun 30, 2026: \\\"UK-Germany Joint Statement on advanced AI safety and security\\\"\\n- Jun 18, 2026: \\\"Releasing AISI's Engineering Playbook\\\"\\n- Jun 8, 2026: \\\"RealityTest: Do AI systems disclose their identity when asked?\\\"\\n- May 25, 2026: \\\"Deepening our partnership with the Australian AI Safety Institute\\\"\\n- May 21, 2026: \\\"Will it become h
… [10069 more characters in events.jsonl]

{
  "url": "https://www.datacenterdynamics.com/en/news/",
  "prompt": "List all news headlines with dates and URLs from Nov 2 and Nov 3 2026."
}

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  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 274,
  "url": "https://www.datacenterdynamics.com/en/news/"
}

{
  "url": "https://thehackernews.com/2026/11/government-linux-servers-targeted-with.html",
  "prompt": "Publication date, all facts: actor, targets, AI-generated scripts evidence, who reported, numbers."
}

{
  "bytes": 179604,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026 (The Hacker News, by Ravie Lakshmanan)\n\n**Threat actor:** Tracked as CL-UNK-1211. \"CL\" stands for cluster and \"UNK\" for unknown motivation, so the actor's identity and goals are unattributed.\n\n**Reporting source:** Palo Alto Networks Unit 42, with researchers Roey Porat and Tom Fakterman.\n\n**Observation period:** October 2025 to April 2026.\n\n**Targets:** Linux infrastructure tied to government entities and state-affiliated organizations.\n\n**Objectives:** Intelligence gathering. The attackers tried to dump sensitive databases and exfiltrate government mailboxes to reach social media accounts.\n\n**AI-generated script evidence:**\n- Unit 42 says the malicious PHP and shell scripts were likely generated using AI.\n- Several scripts contained conversational, step-by-step reasoning notes that explained the code to the operator. Unit 42 says this suggests the code was copied from AI prompt output or deployed by an automated AI agent.\n- A bash script named zip_mails.sh, meant to compress and exfiltrate emails, had syntax errors and failed when executed.\n\n**Key numbers:**\n- 7 command types supported by the SysGoRAT remote access trojan, which is written in Go and uses a WebSocket C2 connection.\n- 3 credential-harvesting methods: replacing .bashrc, injecting code into PHP login pages, and scanning configuration and command history files for cleartext passwords.\n- 1 hard-coded C2 address (104.194.158[.]65:443).",
  "durationMs": 7747,
  "url": "https://thehackernews.com/2026/11/government-linux-servers-targeted-with.html"
}

{
  "query": "AI jailbreak vulnerability disclosure November 2 2026 researchers",
  "mode": "extended"
}

{
  "query": "AI jailbreak vulnerability disclosure November 2 2026 researchers",
  "results": [
    {
      "tool_use_id": "srvtoolu_01NzstkViCZNFWpkUsJNM2gE",
      "content": [
        {
          "title": "AI Jailbreak Disclosure Is Broken. Here’s How to Fix It",
          "url": "https://ai-frontiers.org/articles/ai-jailbreak-disclosure-is-broken-heres-how-to-fix-it"
        },
        {
          "title": "The Biggest AI Security Vulnerabilities Discovered in 2026",
          "url": "https://www.redfoxsec.com/blog/the-biggest-ai-security-vulnerabilities-discovered-in-2026-redfox-cybersecurity"
        },
        {
          "title": "Arbitrary Cipher Attacks Against Large Language Models Do Not Require Fine-Tuning",
          "url": "https://arxiv.org/pdf/2609.09553"
        },
        {
          "title": "Anthropic Cyber Jailbreak - Vulnerability Disclosure Program",
          "url": "https://hackerone.com/anthropic-cyber-jailbreak/"
        },
        {
          "title": "Security framework for artificial intelligence systems",
          "url": "https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/12556388"
        },
        {
          "title": "AI Security Leaderboard: Methodology, Results and Minimal Standard",
          "url": "https://arxiv.org/pdf/2608.03070"
        },
        {
          "title": "FLARE-AI: Flaw Reporting for AI",
          "url": "https://arxiv.org/pdf/2606.31567"
        },
        {
          "title": "How Darth Vader Taught Me Card Counting and AI Security Got Weird",
          "url": "https://spectrum.ieee.org/jailbreaking-llms"
        },
        {
          "title": "PHP2Shell: AI uncovers critical RCE vulnerabilities affecting 70% of the Internet",
          "url": "https://www.wiz.io/blog/php2shell-php-rce"
        }
      ]
    },
    "I found no reports dated specifically to November 2, 2026, so these are the closest relevant results, most of them from the past few months.\n\n- **Disclosure channels are weak.** An AI Frontiers piece argues that OpenAI and Anthropic are the only frontier model vendors to provide any concrete jailbreak reporting routes. It says Google DeepMind, xAI (now SpaceXAI), and Meta exclude jailbreaks from their programs.\n- **Anthropic's program.** Anthropic's HackerOne program covers jailbreaks that could enable harmful cyber use. It asks researchers to coordinate the timing of disclosure with us and not to disclose details publicly before receiving written confirmation.\n- **Unanswered reports.** An arXiv paper on cipher-based jailbreaks says its authors reported findings to Anthropic, OpenAI, and Google in May 2026. It says the Anthropic reports drew no meaningful feedback.\n- **Older disclosure, weak response.** An IEEE Spectrum article describes a universal jailbreak disclosed through CERT, which affected models from most major vendors. It reports that the response to the disclosure was almost nil.\n- **New tooling.** In July 2026, researchers from several universities released FLARE-AI, which routes vulnerability submissions directly into CERT/CC's coordination process.\n- **Other 2026 AI security work.** A RedFox blog post lists multimodal jailbreaks that hide prohibited instructions in images or audio, though it cites no specific disclosure."
  ],
  "durationSeconds": 6.1454592750000305,
  "searchCount": 1
}

{
  "query": "defense AI drone procurement announcement \"November 2, 2026\"",
  "mode": "extended"
}

{
  "query": "defense AI drone procurement announcement \"November 2, 2026\"",
  "results": [
    {
      "tool_use_id": "srvtoolu_01PYj41eP7KPhvtKnZY9ZGfr",
      "content": [
        {
          "title": "Pentagon ramps AI adoption and moves to buy 200,000 small drones by 2027",
          "url": "https://www.digitimes.com/news/a20260528PD204/2026-2027-adoption-capacity-defense-expansion.html"
        },
        {
          "title": "European Allies Pursue Defense Production",
          "url": "https://app.govly.com/public/signals/232796"
        },
        {
          "title": "NATO pushes faster counter-drone defenses and AI-enabled targeting",
          "url": "https://www.jpost.com/defense-and-tech/article-913472"
        },
        {
          "title": "Anduril Altius",
          "url": "https://en.wikipedia.org/wiki/Anduril_Altius"
        },
        {
          "title": "The INSIDER daily digest -- November 2, 2026",
          "url": "https://insidedefense.com/insider/insider-daily-digest-november-2-2026"
        },
        {
          "title": "🛡️ Defense Tech Intelligence Brief — November 02, 2026",
          "url": "https://edsnews.substack.com/p/defense-tech-intelligence-brief-november"
        },
        {
          "title": "Pentagon Details $450 Million Drone Dominance Competition as Gauntlet 2.5 Moves to November",
          "url": "https://dronelife.com/2026/10/14/drone-dominance-phase-iii-gauntlet-2-5/"
        },
        {
          "title": "Ukraine's drone production jumps 370% in 2026, says defense ministry",
          "url": "https://www.yahoo.com/news/world/articles/ukraines-drone-production-jumps-370-141444712.html"
        },
        {
          "title": "US Defence Drone Procurement Market 2026 Forecast",
          "url": "https://droneintelligence.ai/intelligence/us-defence-drone-procurement-market"
        },
        {
          "title": "U.S. Agencies Expand Counter-UAS Procurement",
          "url": "https://app.govly.com/public/signals/95540"
        }
      ]
    },
    "The search turned up no drone procurement award dated November 2, 2026, but several related items from that day and the days around it.\n\n- **Loan to a drone maker (closest match):** The INSIDER digest reports that the Defense Department's credit office signed a conditional loan agreement of up to $450 million with Neros Technologies, a small-drone maker taking part in the Pentagon's $1.1 billion drone competition. That is financing, not a purchase. The INSIDER daily digest -- November 2, 2026 is the source.\n- **Autonomy budget debate:** A Defense Tech brief dated November 2 says the Pentagon's requested autonomy funding is about $53.6 billion, tied to a reconciliation process, and that drone makers question whether the demand signal is real. The total is assigned to the Defense Autonomous Warfare Group program element, successor to Replicator.\n- **NATO counter-drone push:** A JPost article dated November 2 reports that NATO is trying to shorten innovation and adoption timelines for counter-drone and AI targeting, but it describes a testing event rather than a procurement. The event brought together military organizations, operators, and industry to test concepts and gather data on what works under realistic conditions rather than serving as a procurement exercise.\n- **Background, not dated November 2:** The 200,000-small-drone program by 2027 with a $1.1 billion cap was announced at SOF Week in May 2026 (Digitimes). A separate Drone Dominance Phase III item from mid-October describes about 60,000 one-way attack drones under a $450 million request for solutions.\n\nNet: the search did not find a formal drone buy announced on November 2, 2026. The Neros loan is the most direct match. The search results are secondary news and aggregator pages, so I'd confirm against the Pentagon's or the Defense Innovation Unit's own releases before relying on any of these details."
  ],
  "durationSeconds": 7.37972516599996,
  "searchCount": 1
}

{
  "query": "health AI news November 2 2026 hospital deployment study",
  "mode": "extended"
}

{
  "query": "health AI news November 2 2026 hospital deployment study",
  "results": [
    {
      "tool_use_id": "srvtoolu_01JbRGDk2LHfeuFZvqtnes6w",
      "content": [
        {
          "title": "Bonus Features",
          "url": "https://www.healthcareittoday.com/2026/11/01/bonus-features-november-1-2026-91-of-patients-want-their-permission-required-when-ai-is-used-for-diagnosis-64-of-providers-plan-to-deploy-ai-for-claims-and-denials-management-pl/"
        },
        {
          "title": "Evidence-Grounded AI for Musculoskeletal Care",
          "url": "https://arxiv.org/pdf/2607.12527"
        },
        {
          "title": "AI Health Summit NYC 2026",
          "url": "https://events.newsweek.com/ai-health-nyc-2026"
        },
        {
          "title": "ESSENCE is a Quality Improvement Study That Evaluates the Impact of Ada's AI-powered Core Symptom Assessment Technology on Clinical Workflow and Individual Healthcare Guidance, Following the November 2021 Integration of the Tool Into the CUF Hospital Network. Study Duration Nov 2024-Oct 2025",
          "url": "https://clinicaltrials.gov/study/NCT06846957"
        },
        {
          "title": "The landscape of AI implementation in US hospitals",
          "url": "https://www.nature.com/articles/s44360-025-00016-7"
        },
        {
          "title": "Perfecting Human-AI Interaction at Clinical Scale. Turning Production Signals into Safer, More Human Conversations",
          "url": "https://arxiv.org/pdf/2603.29893"
        },
        {
          "title": "Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium",
          "url": "https://arxiv.org/pdf/2403.01628"
        },
        {
          "title": "A Real-World Study of Patient-Facing AI in Primary Care - Technology Org",
          "url": "https://technology.org/2026/11/01/a-real-world-study-of-patient-facing-ai-in-primary-care"
        },
        {
          "title": "AI Implementation in U.S. Hospitals: Regional Disparities and System-Level Implications",
          "url": "https://www.medrxiv.org/content/10.1101/2025.06.27.25330441.full.pdf"
        }
      ]
    },
    "I found no coverage dated exactly November 2, 2026. The closest items are from October 31 to November 1.\n\n- **Patient-facing AI in primary care (Nov 1):** Harvard Medical School researchers at Beth Israel Deaconess Medical Center describe what they believe is the first prospective real-world study of a patient-facing conversational AI system in primary care. The study enrolled 114 patients, and 98 completed both the AI interaction and their appointment. It was designed to test safety and feasibility, not whether AI improves outcomes. (Harvard Medical School researchers at Beth Israel Deaconess Medical Center have conducted what they believe is the first prospective real-world study of a patient-facing conversational AI system in primary care. Conducted between April and November 2025, the study enrolled 114 patients, 98 of whom completed both the AI interaction and their primary care appointment. Rodman and colleagues emphasized that the study was designed to evaluate safety and feasibility rather than to determine whether AI improves health outcomes.\")\n\n- **Industry survey (Nov 1):** An Experian Health survey found that 64% of providers plan to invest in AI for claims and denial management, and 91% of patients want their permission required when AI is used for diagnosis.\n\n- **Randomized hospital study (arXiv preprint):** A single-centre randomized trial at Ruijin Hospital tested OrthoPilot, an AI system for musculoskeletal care, over September 2025 to April 2026. Outcomes covered hospital efficiency, physician workload, nursing workflow, and patient experience. The paper's date is unclear, so I can't confirm it was published in early November.\n\n- **Background:** A Nature Health paper from January 2026 mapped AI adoption across US hospitals, and a WellSpan Health study reported nearly 2 million patient conversations with an AI voice assistant from September 2024 to September 2025."
  ],
  "durationSeconds": 6.539236704999988,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://www.cnbc.com/ai-artificial-intelligence/\" --full 2>&1 | grep -oE 'https://www\\.cnbc\\.com/2026/11/0[23]/[a-z0-9-]+\\.html' | sort -u | head -40",
  "description": "Extract CNBC article URLs from AI section"
}

{
  "stdout": "",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "\"Sparks of Weight-Space Programming\" LLMs read write neural network weights arXiv",
  "mode": "extended"
}

{
  "query": "\"Sparks of Weight-Space Programming\" LLMs read write neural network weights arXiv",
  "results": [
    {
      "tool_use_id": "srvtoolu_01LDVpsHVsQoZVR1eLsAR55s",
      "content": [
        {
          "title": "Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights",
          "url": "https://www.alphaxiv.org/abs/2611.weight-space-programming"
        },
        {
          "title": "Explore",
          "url": "https://www.alphaxiv.org/"
        },
        {
          "title": "Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights",
          "url": "https://rikiyat.github.io/blog/weight-space-programming/"
        },
        {
          "title": "Sparks of Weight-Space Programming: LLMs can natively rea...",
          "url": "https://www.bestblogs.dev/en/article/fd6265405c?entry=landing_todays_picks"
        },
        {
          "title": "Blog - Rikiya Takehi",
          "url": "https://rikiyat.github.io/blog/"
        },
        {
          "title": "LLMs can read & write neural network weights: \"Weight Space Programming\" cuts Autoresearch out of the RSI loop — Latent Space",
          "url": "https://latent.space/p/ainews-llms-can-read-write-neural-network-weights-weight-space-programming-cuts-autoresearch-out-of/"
        },
        {
          "title": "Weight-of-Thought Reasoning: Exploring Neural Network Weights for Enhanced LLM Reasoning",
          "url": "https://arxiv.org/pdf/2504.10646"
        },
        {
          "title": "MIT Shows an LLM Can Read and Edit Another Neural Network's Weights Directly",
          "url": "https://xenospectrum.com/en/sparks-of-weight-space-programming-mit-csail/"
        },
        {
          "title": "Position: Weight Space Should Be a First-Class Generative AI Modality",
          "url": "https://arxiv.org/pdf/2605.18632"
        }
      ]
    },
    "The paper appears to be a November 2026 technical report by Rikiya Takehi and colleagues, but I didn't find an arXiv ID or the PDF in these results. The main sources are the authors' blog, an alphaXiv listing, and secondary coverage.\n\n- **The claim:** The authors report that GPT-6 Astra, a general-purpose frontier LLM, can read and write neural network weights directly, without gradient descent or trained helper models. They call this Weight-Space Programming.\n- **Experiments:** Across eight experiments it identifies what small networks were trained on from their weights, fixes and writes game-playing policies, and edits 0.016% of Qwen3.5-0.8B's weights to stop reasoning loops. One secondary summary reports that the model improved Qwen3.5-0.8B's math performance from 7.9% to 48.1% on MATH-500 by editing 0.016% of weights.\n- **Authorship:** One article attributes the work to MIT CSAIL, listing Rikiya Takehi, Jayden Teoh, Alex Zhang, and Omar Khattab, and describes it as a technical report published November 2.\n- **Status:** The authors say they are building a benchmark to evaluate, and a harness to help LLMs explore and write weights.\n\nBecause the search returned only blog and aggregator pages, the specific numbers above come from secondary coverage and should be checked against the original paper."
  ],
  "durationSeconds": 6.6319355169999765,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://www.nature.com/subjects/machine-learning\" --full 2>&1 | sed -n '60,220p'",
  "description": "Fetch more of Nature ML listing"
}

{"stdout":"-\n\n#\nA document classification benchmark dataset on cybersecurity policy domain\n\n- JungHun Yuk\n\n- KyungTae Lim\n\n- Haneol Jang\n\nResearch Open Access 03 Nov 2026\n\nScientific Reports\n\nP: 1-13\n\n-\n\n#\nLimitations of de novo peptide sequencing in resolving sequence ambiguity\n\nA benchmark of eight deep learning tools that sequence peptides directly from mass spectra (de novo) shows that their errors mostly stem from incomplete spectra, not model design, calling for tools that flag uncertain regions instead of guessing full sequences.\n\n- Sam van Puyenbroeck\n\n- Denis Beslic\n\n- Tine Claeys\n\nResearch Open Access 03 Nov 2026\n\nNature Methods\n\nP: 1-11\n\n-\n\n#\nBuilding a pre-trained model for single-cell multi-omics analysis beyond highly variable feature selection\n\nThe authors present scPMMI, a pre-trained model that learns from multiple types of molecular data in individual cells. They show that this method captures signals beyond highly variable features and supports diverse multi-omics analysis tasks.\n\n- Zhen Yuan\n\n- Shaoqing Jiao\n\n- Jiajie Peng\n\nResearch Open Access 02 Nov 2026\n\nNature Communications\n\nP: 1-18\n\n-\n\n#\nGenome-anchored foundation model embeddings improve molecular prediction from histology images\n\nObtaining accurate molecular insights for precision oncology remains costly and time consuming. Here, the authors develop PathLUPI, a deep learning method to enable effective molecular prediction in cancer using only routine whole-slide images, with evaluation across 49 molecular oncology tasks in 20 different cohorts.\n\n- Cheng Jin\n\n- Fengtao Zhou\n\n- Hao Chen\n\nResearch Open Access 02 Nov 2026\n\nNature Communications\n\nP: 1-15\n\n-\n\n#\nRe-timing mortality risk through individualized modelling of lifespan trajectories\n\nRetiME is a deep learning-based biomarker that maps retinal features to individual mortality risks and can reconstruct personalized lifespan trajectories associated with observed mortality outcomes with distinct disease-related mortality patterns.\n\n- Ting Xu\n\n- Qingsheng Peng\n\n- Ching-Yu Cheng\n\nResearch 02 Nov 2026\n\nNature Biomedical Engineering\n\nP: 1-18\n\n-\n\n#\nAI-driven discovery and engineering of human-derived protein scaffolds for mRNA delivery\n\nProtein-based carriers could provide biocompatible options for mRNA delivery. Here, authors develop an AI-guided platform to identify and engineer human-derived protein scaffolds that assemble into particles and support mRNA delivery in cultured cells.\n\n- Dongmin Xun\n\n- Lanqing Li\n\n- Chao Zhong\n\nResearch Open Access 31 Oct 2026\n\nNature Communications\n\nP: 1-17\n\nAll Research & Reviews\n\n# News and Comment\n\n-\n\n#\nUniversities must measure learning, both with and without AI assistance\n\n- Christoph Trattner\n\nCorrespondence 03 Nov 2026\n\nNature\n\nVolume: 659, P: 264\n\n-\n\n#\nApplying digital twins to prevent preterm births\n\nResearchers developed a digital twin framework to safely evaluate the effects of drugs on the immune system and time to labor, which could enable personalized interventions to prevent preterm births.\n\n- Karen O’Leary\n\nResearch Highlights 29 Oct 2026\n\nNature Medicine\n\n-\n\n#\nThis Arabian desert was once a lush paradise. Why did ancient humans avoid it?\n\nExpedition revealed that water wasn’t enough for human settlement — plus, proposals to block sunlight get serious.\n\n- Shamini Bundell\n\n- Nick Petrić Howe\n\nNews 28 Oct 2026\n\nNature\n\n-\n\n#","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":139,"oldLines":3,"newStart":139,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:10:09.655Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_01PMQocMncd7a1ayiTyF23w4\",\"duration_ms\":6539,\"input\":{\"query\":\"health AI news November 2 2026 hospital deployment study\",\"mode\":\"extended\"},\"response\":{\"query\":\"health AI news November 2 2026 hospital deployment study\",\"results\":[{\"tool_use_id\":\"srvtoolu_01JbRGDk2LHfeuFZvqtnes6w\",\"content\":[{\"title\":\"Bonus Features\",\"url\":\"https://www.healthcareittoday.com/2026/11/01/bonus-features-november-1-2026-91-of-patients-want-their-permission-required-when-ai-is-used-for-diagnosis-64-of-providers-plan-to-deploy-ai-for-claims-and-denials-management-pl/\"},{\"title\":\"Evidence-Grounded AI for Musculoskeletal Care\",\"url\":\"https://arxiv.org/pdf/2607.12527\"},{\"title\":\"AI Health Summit NYC 2026\",\"url\":\"https://events.newsweek.com/ai-health-nyc-2026\"},{\"title\":\"ESSENCE is a Quality Improvement Study That Evaluates the Impact of Ada's AI-powered Core Symptom Assessment Technology on Clinical Workflow and Individual Healthcare Guidance, Following the November 2021 Integration of the Tool Into the CUF Hospital Network. Study Duration Nov 2024-Oct 2025\",\"url\":\"https://clinicaltrials.gov/study/NCT06846957\"},{\"title\":\"The landscape of AI implementation in US hospitals\",\"url\":\"https://www.nature.com/articles/s44360-025-00016-7\"},{\"title\":\"Perfecting Human-AI Interaction at Clinical Scale. Turning Production Signals into Safer, More Human Conversations\",\"url\":\"https://arxiv.org/pdf/2603.29893\"},{\"title\":\"Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium\",\"url\":\"https://arxiv.org/pdf/2403.01628\"},{\"title\":\"A Real-World Study of Patient-Facing AI in Pr
… [10069 more characters in events.jsonl]

{
  "query": "Unit 42 SysGoRAT CL-UNK-1211 government Linux AI-generated scripts",
  "mode": "extended"
}

{
  "query": "Unit 42 SysGoRAT CL-UNK-1211 government Linux AI-generated scripts",
  "results": [
    {
      "tool_use_id": "srvtoolu_01XEoac9ZYG8G3uwXdeWm1yP",
      "content": [
        {
          "title": "Government Linux Servers Targeted With SysGoRAT and Suspected AI-Generated Scripts",
          "url": "https://thehackernews.com/2026/11/government-linux-servers-targeted-with.html"
        },
        {
          "title": "AI-Powered Espionage Campaign Targets Government Linux Infrastructure",
          "url": "https://unit42.paloaltonetworks.com/ai-campaign-targets-linux-infrastructure/"
        },
        {
          "title": "Hackers Use AI-Generated Scripts to Hijack Linux Sudo Commands and Steal Passwords",
          "url": "https://cybersecuritynews.com/hackers-use-ai-generated-scripts/"
        },
        {
          "title": "Hackers Used AI-Generated Scripts to Break Into Government Linux Servers and Hunt for Secrets",
          "url": "https://gbhackers.com/ai-generated-scripts/"
        },
        {
          "title": "AI-Powered Espionage Campaign Targets Government Linux Infrastructure",
          "url": "https://daily.dev/posts/ai-powered-espionage-campaign-targets-government-linux-infrastructure-j5b4ue4rm"
        },
        {
          "title": "SysGoRAT Targets Government Linux Servers With Suspected AI-Generated Scripts - The 420.in",
          "url": "https://the420.in/sysgorat-government-linux-servers-ai-espionage/"
        },
        {
          "title": "Government Linux Servers Targeted With SysGoRAT and Suspected AI-Generated Scripts",
          "url": "https://nuclearcoffee.org/government-linux-servers-targeted-with-sysgorat-and-suspected-ai-generated-scripts/"
        },
        {
          "title": "CL-UNK-1211 Deploys SysGoRAT Malware and AI Scripts Against Government Linux Servers",
          "url": "https://securityonline.info/sysgorat-malware-cl-unk-1211-linux/"
        },
        {
          "title": "AI-Generated Scripts Hijack Linux Sudo to Steal Passwords",
          "url": "https://cyberupdates365.com/ai-generated-scripts-linux-sudo-passwords/"
        },
        {
          "title": "Government Linux Servers Targeted With SysGoRAT and Suspected AI-Generated Scripts",
          "url": "https://news.cybertechworld.co.in/index.php/2026/11/02/government-linux-servers-targeted-with-sysgorat-and-suspected-ai-generated-scripts/"
        }
      ]
    },
    "Unit 42 tracks the campaign as CL-UNK-1211, and the findings cover activity from October 2025 to April 2026.\n\n- **Targets and timeline:** Unit 42 identified a campaign targeting government entities and state-affiliated infrastructure, with observed activity spanning from October 2025–April 2026.\n- **Malware and tooling:** The toolkit included SysGoRAT, a custom Go remote access Trojan supporting Linux and Windows. SysGoRAT reaches its command server over WebSocket, and the operators also used PHP web shell deployments via auto_prepend_file hijacking, credential theft through modified .bashrc files and PHP login loggers, and mailbox enumeration.\n- **AI-generated scripts:** Several PHP and shell scripts contained conversational comments and step-by-step reasoning notes that researchers said were consistent with AI-generated code or an automated AI agent. One mailbox-archiving script contained a syntax error and would fail as written.\n- **Attribution:** Attribution is unresolved. Unit 42 uses \"UNK\" for clusters whose links to either state-backed activity or cybercrime have not been determined, so the findings do not identify a known government or criminal group as responsible.\n- **Defense evasion:** Unit 42 said endpoint protections detected and stopped attempts to terminate Cortex XDR processes; that result concerns the observed systems and does not mean every attempted activity was blocked.\n\nCoverage is consistent across outlets, but the \"AI-generated\" label is an inference. Unit 42 describes the scripts as likely AI-generated, not confirmed. Full details, including indicators of compromise, are in Unit 42's original report at unit42.paloaltonetworks.com/ai-campaign-targets-linux-infrastructure/."
  ],
  "durationSeconds": 6.029518875000009,
  "searchCount": 1
}

{
  "query": "Neros Technologies Office of Strategic Capital $450 million loan drones",
  "mode": "extended"
}

{
  "query": "Neros Technologies Office of Strategic Capital $450 million loan drones",
  "results": [
    {
      "tool_use_id": "srvtoolu_015L9NV5ZYfi2LFZpCTiUSLj",
      "content": [
        {
          "title": "Neros Says $450M Pentagon Loan Deal Gives Taxpayers An Ownership Stake",
          "url": "https://dronexl.co/2026/11/02/neros-450m-osc-loan-taxpayer-ownership-stake/"
        },
        {
          "title": "Neros Technologies on X: \"Neros has received a $450M conditional loan commitment from the Office of Strategic Capital under the @deptofwar, and is adding $165M in Neros equity to accelerate vertically integrated drone production and in-house component manufacturing. This combined $615M project will… / X",
          "url": "https://x.com/neros_tech/status/2117296865784074342"
        },
        {
          "title": "NEROS SIGNS $450M CONDITIONAL LOAN COMMITMENT WITH THE OFFICE OF STRATEGIC CAPITAL TO ESTABLISH AMERICA'S DRONE INDUSTRIAL BASE",
          "url": "https://www.morningstar.com/news/pr-newswire/20261102la86859/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base"
        },
        {
          "title": "DoD Taking Equity Stake In Drone Manufacturer Neros With Planned $450 Million Loan - Defense Daily",
          "url": "https://www.defensedaily.com/dod-taking-equity-stake-in-drone-manufacturer-neros-with-planned-450-million-loan/unmanned-systems/"
        },
        {
          "title": "DOD credit office set to give DDP competitor up to $450M loan",
          "url": "https://insidedefense.com/ai-news/dod-credit-office-set-give-ddp-competitor-450m-loan"
        },
        {
          "title": "Neros gets $450M Pentagon loan to cut reliance on Chinese drone parts",
          "url": "https://defence-blog.com/neros-gets-450m-pentagon-loan-to-cut-reliance-on-chinese-drone-parts/"
        },
        {
          "title": "Neros",
          "url": "https://en.wikipedia.org/wiki/Neros"
        },
        {
          "title": "Neros secures conditional Pentagon loan commitment of up to $450M",
          "url": "https://runtimewire.com/article/neros-450m-osc-conditional-loan-drone-manufacturing"
        },
        {
          "title": "NEROS SIGNS $450M CONDITIONAL LOAN COMMITMENT WITH THE OFFICE OF STRATEGIC CAPITAL TO ESTABLISH AMERICA'S DRONE INDUSTRIAL BASE",
          "url": "https://uk.advfn.com/stock-market/share-news/NEROS-SIGNS-450M-CONDITIONAL-LOAN-COMMITMENT-WITH/99609618"
        },
        {
          "title": "Neros Secures Up to $450 Million Conditional OSC Loan Commitment",
          "url": "https://www.securities.io/neros-secures-up-to-450-million-conditional-osc-loan-commitment/"
        }
      ]
    },
    "The Pentagon's Office of Strategic Capital (OSC) announced a conditional loan of up to $450 million to Neros on November 2, 2026, to expand drone and component production in Torrance, California. Neros is adding $165 million of its own equity, for a total project of $615 million.\n\nSources disagree on whether the government takes an ownership stake. Defense Daily's headline describes an equity stake for the Pentagon. DroneXL reports that OSC's release describes a conditional loan made alongside additional private capital and does not mention a government ownership stake.\n\nNeros CEO Soren Monroe-Anderson tied the funding to a production goal. He said the money puts the company on a path to produce one million drones annually by 2028. DroneXL notes that Neros was building about 1,200 drones a week in August, or roughly 62,000 a year, so that target implies a large increase.\n\nThe loan is not final. The conditional loan commitment specifies additional steps Neros must complete before financial close, including satisfying financial, legal, technical, investment, due-diligence and other requirements."
  ],
  "durationSeconds": 5.344441848999995,
  "searchCount": 1
}

{
  "query": "Brookfield $27 billion AI data center UK power station Drax",
  "mode": "standard"
}

{
  "query": "Brookfield $27 billion AI data center UK power station Drax",
  "results": [
    {
      "tool_use_id": "srvtoolu_01UXDX3y7Xm2EpZvdq67xD66",
      "content": [
        {
          "title": "ai data centres",
          "url": "https://www.drax.com/what-we-do/ai-data-centres/"
        },
        {
          "title": "www.drax.com",
          "url": "https://www.drax.com/?p=19945"
        },
        {
          "title": "BECCS developer Drax mulls plans to build 1GW AI data centre",
          "url": "https://www.qcintel.com/carbon/article/beccs-developer-drax-mulls-plans-to-build-1gw-ai-data-centre-54889.html"
        },
        {
          "title": "英國Drax擬將燃煤電廠轉型為AI資料中心 瞄準2031年建置超過1GW容量",
          "url": "https://uanalyze.com.tw/articles/8489341808"
        },
        {
          "title": "It’s rich in cloud data centers, but can the U.K. compete for AI assets?",
          "url": "https://www.rbccm.com/en/insights/2026/07/its-rich-in-cloud-data-centers-but-can-the-uk-compete-for-ai-assets"
        },
        {
          "title": "drax plans to convert part of its north yorkshire power plant into datacentre",
          "url": "https://www.inkl.com/news/drax-plans-to-convert-part-of-its-north-yorkshire-power-plant-into-datacentre"
        },
        {
          "title": "Brookfield plans AI data centers in London to meet demand",
          "url": "https://cryptobriefing.com/brookfield-ai-data-centers-london/"
        },
        {
          "title": "Brookfield’s $100 Billion Fund Drives AI Data Center Onsite Power Strategy 2026",
          "url": "https://enkiai.com/ai-market-intelligence/ai-data-center-power-brookfields-100b-masterplan-for-2026/"
        },
        {
          "title": "drax to convert yorkshire power station into 1gw data centre to meet ai energy demand",
          "url": "https://invezz.com/news/2025/12/11/drax-to-convert-yorkshire-power-station-into-1gw-data-centre-to-meet-ai-energy-demand/"
        },
        {
          "title": "uk govt rejects ai growth zone bid to power data center with drax biomass plant in selby north yorkshire",
          "url": "https://www.datacenterdynamics.com/en/news/uk-govt-rejects-ai-growth-zone-bid-to-power-data-center-with-drax-biomass-plant-in-selby-north-yorkshire"
        }
      ]
    },
    "I couldn't find any source linking Brookfield, a $27 billion figure, and Drax. The results cover Drax's data center plans and Brookfield's broader AI push separately.\n\n**Drax's plans:** Drax is planning a first-phase data center of under 100MW on its North Yorkshire site, and this could support the operation of a data centre at Drax Power Station by 2027. Its longer-term aim is a facility with over 1GW capacity before the end of the decade. A larger earlier bid did not succeed: the UK government rejected a bid by North Yorkshire Council, the University of York, and energy company Drax to utilize a bioenergy power plant near Selby for an AI data center. The power producer has now pivoted to a smaller project, planning a 100MW data center that would draw power from the national grid rather than from the power plant.\n\n**Brookfield's plans:** Reports tie Brookfield to London data centers, not Drax. One source says Brookfield launched a $100 billion AI infrastructure program back in November 2025, with $10 billion in equity commitments. Another describes a $5 billion partnership with Bloom Energy for 1 GW of fuel cell power solutions for data centers, including facilities across Europe.\n\nThe $27 billion figure and any Brookfield–Drax deal may be newer than these results or may not exist. A more specific search, such as \"Brookfield Drax deal,\" or a check of recent news, would help confirm."
  ],
  "durationSeconds": 6.780267516000022,
  "searchCount": 1
}

{
  "url": "https://www.diu.mil/latest",
  "prompt": "List items dated Nov 2 or Nov 3 2026 with titles and URLs."
}

{
  "bytes": 3303209,
  "code": 200,
  "codeText": "OK",
  "result": "None of the items visible in the page content are dated November 2 or 3, 2026. The listed announcements are:\n\n- **19 Aug 2026:** \"Director Memo: Establishment of the Bridge Program\" (/latest/director-memo-establishment-of-the-bridge-program)\n- **18 July 2026:** \"Director Memo: Reorganization to Support the Revolution\" (/latest/director-memo-reorganization-to-support-the-revolution)\n- **9 Mar 2026:** \"Director Memo: Ethics Build Trust\" (/latest/director-memo-ethics-build-trust)\n- **2 Mar 2026:** \"Director Memo: Converting Commercial Technology into Combat Power\" (/latest/director-memo-converting-commercial-technology-into-combat-power)\n\nThe page content is truncated, so there may be additional announcements that aren't shown.",
  "durationMs": 4977,
  "url": "https://www.diu.mil/latest"
}

{
  "url": "https://www.jpost.com/defense-and-tech/article-913472",
  "prompt": "Publication date and all facts about NATO counter-drone and AI-enabled targeting: names, numbers, locations, dates."
}

{
  "bytes": 361415,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026, 09:38, by Anna Ahronheim in *The Jerusalem Post's* Defense & Tech section.\n\n**Event and programs**\n- NATO FUSE took place in Latvia on October 29-30, 2026. NATO's Allied Command Transformation organized it.\n- Three initiatives were showcased: Digital Backbone eXperimentation (DiBaX), the Layered Counter-UAS Initiative (LCI-X), and Next Generation Targeting (NGT).\n- More than 30 countries and over 100 companies are taking part.\n- Israeli companies took part in earlier NATO events but, per the outlet's understanding, not in NATO FUSE.\n\n**People**\n- Maj.-Gen. Arnoud Stallmann, NATO's assistant chief of staff for multi-domain capability, is the main source. He previously led the Dutch Directorate for Ukraine.\n\n**Counter-drone (LCI-X)**\n- LCI-X has run C-UAS events in Finland and Latvia over the past year.\n- NATO is building layered defenses that link sensors, effectors, and command-and-control, and is avoiding reliance on a single technology.\n- Stallmann stressed the need for cheaper intercept options than fighter jets or missile interceptors. He noted drone incursions into Poland last September as a turning point.\n\n**AI-enabled targeting (NGT)**\n- NGT aims to build a federated framework that combines national data through modular AI tools.\n- A cited goal is cutting information-to-decision latency by more than 50%.\n- Human operators would keep authority over engagement decisions.\n\n**Other details**\n- DiBaX 2026 focused on resilient command-and-control, communications during network disruption, and AI-assisted decision-making.\n- NATO is also examining quantum computing and quantum-resistant systems.\n- Photos cite locations including Adazi and Latvia (DiBaX), Jurmalciems, Latvia (Czech troops), and Paluknys airfield, Lithuania (Viligant Owl media day, October 28, 2026).",
  "durationMs": 7166,
  "url": "https://www.jpost.com/defense-and-tech/article-913472"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I -c \"\nimport json\nwant=['26366943','26366929','26367027','26364999','26366942','26359492','26366939']\nfor f in ['mm_0.json','mm_30.json','mm_60.json']:\n    d=json.load(open(f))\n    for c in d.get('collection',[]):\n        if any(w in c.get('doi','') for w in want):\n            print('==',c.get('title'))\n            print('DOI',c.get('doi'),'version',c.get('version'),'date',c.get('date'))\n            print(c.get('abstract','')[:1600])\n            print()\n\" 2>&1 | head -200",
  "description": "Print selected medRxiv abstracts"
}

{
  "stdout": "== Variantscape: Retrospective Study of Large Language Model-Based Extraction of Variant-Treatment-Cancer Associations from Published Oncology Abstracts\nDOI 10.64898/2026.08.02.26359492 version 2 date 2026-11-02\nObjectives: Precision oncology relies on accurate interpretation of tumour-detected gene variants, to guide personalised treatment decisions. However, interpretation of variants in context requires extensive information that is often buried within unstructured biomedical literature and obscured by inconsistent nomenclature, making manual retrieval labour-intensive and prone to omissions. In this study, our aim was to evaluate the potential of large language models to extract variant-treatment-cancer associations at scale from published abstracts. Design: We developed Variantscape, a large-scale, automated pipeline and open-access web tool. It integrates traditional natural language processing methods with state-of-the-art large language models to extract, standardise, and analyse co-associations between genetic variants, cancer types, and therapeutic interventions from published biomedical abstracts. Results: From over 3.7 million abstracts published between January 2014 and October 2026, 886,195 articles containing gene names were eligible for extraction. Among these, 37,895 (4.3%) mentioned a variant, cancer type, and therapeutic agent together, covering 11,985 unique variants across 197 cancer types and 547 therapeutic agents. LLM verification against the abstract text confirmed at least one association in 35,224 papers, giving a literature-derived graph of 10,571 nodes and 44,644 verified edges. Canonical alterations in well-studied cancers (e.g., BRAF V600E in melanoma) were strongly linked to established treatments, while several rare variants also emerged with high-c\n\n== Ophthalmic AI With Just Ten Examples: Comparing Multimodal Large Language Models, Vision Foundation Models, and Vision-Language Models\nDOI 10.64898/2026.10.30.26366929 version 1 date 2026-11-02\nPurpose: To compare multimodal large language models (MLLMs), vision foundation models (VFMs), and contrastive vision-language models (VLMs) for ophthalmic image interpretation with no labeled examples (zero-shot) or as few as 10 labeled examples per class (10-shot). Design: Retrospective benchmarking study. Subjects: 4 public datasets (UCSD, IDRiD, REFUGE, ASOCT-MSDC) and 3 private datasets (OHTS, BPEI-DLS, WashU-OCT) of anterior- and posterior-segment ophthalmic imaging. Methods: Nine AI models were evaluated across 3 architectural families: MLLMs (Qwen3.8-27B, GLM-5.3-Flash, Gemma-4-31B-it), VFMs (DINOv3, RETFound, VisionFM), and VLMs (CLIP, EyeCLIP, SigLIP2). Models were assessed on disease classification, disease risk and severity grading, anatomical assessment, and lesion localization in fundus and OCT imaging. MLLMs were also compared with a 3D VFM (OCTCube-M) for whole-volume OCT classification. MLLMs were evaluated zero-shot and 10-shot, without additional training. Vision models (VFMs and VLMs) were adapted by linear probing and fine-tuning on the same 10-shot set and on the full training dataset (FD). Main Outcome Measures: Disease classification performance (macro-averaged F1, AUROC, quadratic weighted kappa [QWK]), anatomical localization accuracy, and cross-dataset generalization. Results: For retinal OCT disease classification, 10-shot MLLMs achieved a macro-F1 of 0.94, versus 0.59 (10-shot) and 0.96 (FD) for vision models. For diabetic retinopathy and macular edema grading, 10-shot MLLMs achieved QWKs of 0.69 and 0.73, versus 0.48 and 0.57 (10-shot) and 0.72\n\n== A decision-only model as a low-cost judge of medical AI answers\nDOI 10.64898/2026.10.30.26366939 version 1 date 2026-11-02\nBackground. Testing and deploying medical AI systems at scale already results in more outputs than clinicians can review, and the use of large language models (LLMs) as judges is growing rapidly. Decision-only models, cheap and fast models that return structured probabilities rather than text, offer a potentially scalable option for that goal. Methods. In an OSF pre-registered evaluation, we tested TypeSafe Jev 1.13 as a judge on tasks from five validated clinical benchmarks: rubric grading (HealthBench), planted clinical errors (When Rubrics Fail), risk in AI-written clinical documents (MedVAL), counseling ratings and failures (CounselBench) and physicians' preferences between answers (Real-POCQi). Comparators were expert raters' agreement with each other, OpenAI Decisions, GPT-6 Luna, a proposed hybrid team combining decision models and a cheap LLM and, as frontier comparators, GPT-6.1 Sol and Claude Opus 5.5. The main outcome was plain agreement with the expert label. Results. The test comprised 25,091 units and 213,913 model calls. Jev's agreement with expert labels averaged 64.7% over six tasks. On 3,614 matched units it averaged 66.1%, against 65.0% for Opus and 60.7% for Sol, and it was non-inferior to both on four of six tasks. Jev judged the whole pool in 17 minutes for US$1.46; per judgment, it cost 1/34 of Sol's price and 1/152 of Opus's. A preset cutoff held its false-alarm rate on fresh planted-error answers, and in simulation, reviewing Jev's least-sure answers first found 1.4 times the errors of a random audit. Still, omissions were hard for both: at the same\n\n== Deep learning grading of Schistosoma japonicum-associated liver fibrosis from ultrasound images: a weighted soft-voting ensemble of convolutional and transformer networks\nDOI 10.64898/2026.11.02.26364999 version 1 date 2026-11-02\nBackground: Schistosomiasis morbidity still persists in China despite extensive progress towards elimination of new and active infections. Diagnosis of liver fibrosis related to Schistosoma japonicum remains challenging due to the subjective nature of ultrasound grading and the shortage of experienced sonographers in endemic counties. Methods: We developed a deep learning model that grades schi
… [6371 more characters in events.jsonl]

{
  "url": "https://www.alphaxiv.org/abs/2611.weight-space-programming",
  "prompt": "Give the abstract, publication date, authors and institutions, and all quantitative results with baselines."
}

{
  "bytes": 247998,
  "code": 200,
  "codeText": "OK",
  "result": "**Abstract (summarized from the page's Summary section):** The authors report that GPT-6 Astra, a general-purpose frontier LLM, can read and write neural network weights directly, without gradient descent or trained helper models. Across eight experiments, it identifies what small networks were trained on from their weights, writes and fixes game-playing policies, and edits 0.016% of Qwen3.5-0.8B's weights to stop reasoning loops. The authors call this \"Weight-Space Programming.\"\n\n**Publication date:** Submitted 02 Nov 2026 to alphaXiv. The work was originally published on the author's blog.\n\n**Authors:** Rikiya Takehi, Jayden Teoh, Alex Zhang, Omar Khattab\n\n**Institutions:** Not listed on the page.\n\n**Quantitative results**\n\n- **Game policy identification:** With no tools or options, Astra correctly named all four policies (Breakout, Pong, Pac-Man, Freeway). No accuracy figure or baseline is given.\n- **PPO car policy patch:** Editing 3.5% of the weights raised success to 100%. The page says the original policy \"kept getting stuck on a ramp\" but gives no baseline success rate.\n- **Breakout network written from scratch:** Scored 20× higher than PPO trained for 500M steps. Absolute scores are not given.\n- **Qwen3.5-0.8B edit:** Changing 0.016% of weights improved math up to 6× and instruction following up to 3×. The page does not state the baseline values or benchmarks behind these multipliers.\n- **Community reproduction (unverified, from a reader comment, not the authors):** Unedited Qwen3.5-0.8B hit the max token cap 88.7% of the time, with 10.9% accuracy and a median of 32,768 tokens. With the released edit, the cap rate fell to 17.6%, accuracy rose to 61.7%, and the median dropped to 13,451 tokens.",
  "durationMs": 7118,
  "url": "https://www.alphaxiv.org/abs/2611.weight-space-programming"
}

{
  "query": "state attorney general AI chatbot enforcement November 2026",
  "mode": "extended"
}

{
  "query": "state attorney general AI chatbot enforcement November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Lpkg5fQHY2efaK9rgRSWax",
      "content": [
        {
          "title": "November 2026: Unprecedented State Enforcement Ahead of Midterms",
          "url": "https://thealgorithmicupdate.substack.com/p/november-2026-unprecedented-state"
        },
        {
          "title": "State AG Enforcement Action: Priorities for 2026",
          "url": "https://www.wilmerhale.com/en/insights/client-alerts/20260109-state-ag-enforcement-action-priorities-for-2026"
        },
        {
          "title": "New York Lawmakers Crack Down on AI - BKReader",
          "url": "https://www.bkreader.com/national-news/new-york-lawmakers-crack-down-on-ai-12959018"
        },
        {
          "title": "NY Implements Chatbot Restrictions for Interactions With Minors, Puts AI Companies 'On Notice'",
          "url": "https://www.law.com/newyorklawjournal/2026/10/28/ny-implements-chatbot-restrictions-for-interactions-with-minors-puts-ai-companies-on-notice/"
        },
        {
          "title": "State AI Chatbot Laws: Compliance Guide for Businesses",
          "url": "https://stackcyber.com/posts/ai-chatbot-laws"
        },
        {
          "title": "AI Companion Chatbot Laws by State (2026)",
          "url": "https://astraea.law/insights/ai-companion-chatbot-laws-by-state"
        },
        {
          "title": "New York Bans AI Chatbots From Acting Like Friends to Kids",
          "url": "https://www.lawcommentary.com/articles/new-york-ai-chatbot-ban-kids-emotional-relationships"
        },
        {
          "title": "Attorney General Ken Paxton Investigates Meta and Character.AI for Misleading Children with Deceptive AI-Generated Mental Health Services",
          "url": "https://www.texasattorneygeneral.gov/news/releases/attorney-general-ken-paxton-investigates-meta-and-characterai-misleading-children-deceptive-ai"
        },
        {
          "title": "Watershed year for chatbot safety: 14 new state laws passed so far in 2026 — Transparency Coalition. Legislation for Transparency in AI Now.",
          "url": "https://www.transparencycoalition.ai/news/watershed-year-for-chatbot-safety-measures-14-new-state-laws-enacted-so-far-in-2026"
        }
      ]
    },
    "Recent state AG activity on AI chatbots is heavy, mostly centered on OpenAI and child safety.\n\n- **Lawsuits against OpenAI:** A newsletter dated Nov 2, 2026 reports that eight state attorneys general filed separate but coordinated consumer protection lawsuits against OpenAI in their respective state courts on October 14, and that Texas AG Paxton filed another similar lawsuit on October 23. Another analysis counts ten state attorneys general have sued OpenAI.\n- **New York:** Governor Hochul signed a law restricting unsafe chatbot features for users under 18. New York Attorney General Letitia James will oversee enforcement and can seek court orders blocking violations, restitution, damages and the recovery of profits obtained through unlawful practices.\n- **Texas investigations:** Earlier, AG Paxton opened an investigation into artificial intelligence chatbot platforms, including Meta AI Studio and Character.AI, over possible deceptive mental-health marketing.\n- **Broader trend:** Enforcement and private right: Attorney General is the enforcement mechanism in most new state chatbot statutes. For example, Jim Pillen signed LB 525, the Conversational AI Safety Act, on April 14, 2026. One tracker says enforcement by state attorney general, with violations subject to penalties of up to $15,000 per day under one state's law.\n\nCaveat: the November 2026 roundup is a Substack newsletter, so its counts (such as 53 actions) and the lawsuit dates should be checked against court filings or AG press releases. The sources also disagree on the number of states suing OpenAI (eight plus Texas in one, ten in another)."
  ],
  "durationSeconds": 6.383151186000032,
  "searchCount": 1
}

{
  "command": "curl -sS -A \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 Chrome/131.0 Safari/537.36\" \"https://www.techmeme.com/\" | grep -oE 'href=\"https?://[^\"]+\"' | sed 's/href=\"//;s/\"$//' | grep -viE 'techmeme|twitter|facebook|mailto' | head -150",
  "description": "Extract outbound links from Techmeme"
}

{
  "stdout": "",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "AI court filing docket November 2 2026 copyright OpenAI Anthropic",
  "mode": "extended"
}

{
  "query": "AI court filing docket November 2 2026 copyright OpenAI Anthropic",
  "results": [
    {
      "tool_use_id": "srvtoolu_017tEXnVWMenoNmphTMUrZ7c",
      "content": [
        {
          "title": "The OpenAI Copyright Case Has Drawn A Mountain Of Amicus Briefs. We Sorted Them For You.",
          "url": "https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/"
        },
        {
          "title": "Bartz v. Anthropic Settlement: What Authors Need to Know - The Authors Guild",
          "url": "https://authorsguild.org/advocacy/artificial-intelligence/what-authors-need-to-know-about-the-anthropic-settlement/"
        },
        {
          "title": "More Amicus Briefs Flood NYT, OpenAI Copyright Case - Law360 UK",
          "url": "https://www.law360.com/aerospace/articles/2545351"
        },
        {
          "title": "Who's suing AI and who's signing latest: US newspapers sue Brave Software and Canadian publishers sue Anthropic",
          "url": "https://pressgazette.co.uk/platforms/news-publisher-ai-deals-lawsuits-openai-google/"
        },
        {
          "title": "AI Copyright Lawsuits (2026): 144 Tracked Cases & Status",
          "url": "https://ailawsuittracker.com/ai-copyright-lawsuits/"
        },
        {
          "title": "AI Copyright Lawsuits Tracker (2026) — Cases We Track",
          "url": "https://ailawsuittracker.com/copyright/"
        },
        {
          "title": "Wikipedia Enters OpenAI Copyright Showdown - Benzinga",
          "url": "https://www.benzinga.com/markets/private-markets/26/11/62789700/wikipedia-enters-openai-copyright-showdown-with-a-warning-about-the-future-of-the-web"
        },
        {
          "title": "OpenAI Copyright Lawsuit: Authors vs. AI Training Data",
          "url": "https://legalnewsreport.com/openai-copyright-lawsuit-authors-ai-training/"
        },
        {
          "title": "AI Copyright Lawsuits Tracker 2026: Live Case Status",
          "url": "https://axis-intelligence.com/ai-copyright-lawsuits-tracker/"
        }
      ]
    },
    "Here's what the search turned up for early November 2026. Most of the activity is in the OpenAI case, which is in a multidistrict litigation (MDL) in New York federal court.\n\n- **Amicus briefs in the OpenAI MDL:** Many groups filed briefs, including actors, writers' groups, law professors, and political leaders, with some arguing fair use protects OpenAI and others arguing it does not. Actors, writers groups, advocacy organizations, law professors and current and former political leaders weighed in. The Wikimedia Foundation also filed an amicus brief Friday in federal court in the Southern District of New York.\n- **Schedule conflict:** One source says oppositions were filed October 23; replies are due November 20, 2026. Another tracker says summary judgment replies not due until November 6. I couldn't resolve which date is correct, so check the docket.\n- **Anthropic:** The Bartz settlement is moving toward payment. According to a new filing, initial payments to claimants will go out during the week of November 23. A tracker also lists oral argument set for November 4, 2026 in the UMG/Concord/ABKCO v. Anthropic II case in N.D. Cal.\n- **New suits:** The New York Times, The Chicago Tribune, The Orlando Sentinel and The Daily News have sued Brave Software on November 2, 2026, alleging the browser maker took their articles for use by AI companies.\n\nI didn't find a specific filing dated November 2, 2026 that is the single \"docket\" entry you mentioned. The results are mostly trade-press and tracker coverage, so the docket itself is the authoritative source to confirm dates."
  ],
  "durationSeconds": 7.17315952799999,
  "searchCount": 1
}

{
  "url": "https://rikiyat.github.io/blog/weight-space-programming/",
  "prompt": "Give the exact publication date, author names and institutions, and all quantitative results with baselines (e.g. percentages, number of experiments, model names, fraction of weights edited). Is there an arXiv ID or PDF link?"
}

{
  "bytes": 85671,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication and authors**\n- **Date:** November 2, 2026 (the citation gives November 2026).\n- **Authors:** Rikiya Takehi\\*, Jayden Teoh\\*, Alex Zhang, and Omar Khattab (\\*equal contribution is implied by the asterisk, but the page doesn't define it).\n- **Affiliation:** MIT CSAIL for all four authors.\n- **arXiv ID or PDF:** None is listed. The page offers the blog URL (rikiyat.github.io/blog/weight-space-programming/), a BibTeX entry, and GitHub logs (github.com/RikiyaT/lm_understand-logs).\n\n**Experiment results**\n\n| Exp. | Task | Result | Baseline / comparison |\n|---|---|---|---|\n| 1 | Identify the game from weights (17,253-weight MLP) | Correct for all 4 games (Breakout, Pong, Pac-Man, Freeway) | Not stated |\n| 2 | Identify the shape a DDPM generates (23,824 weights) | Identified circle, triangle, and square models from weights alone | No accuracy figure given |\n| 3 | Identify training language and copying heads (7.16M weights) | Correct language for all 3 models, in both attempts; found the copying heads | Measured copying heads scored 0.22–0.55; other heads at most 0.02 |\n| 4 | Fix a Kinetix car-on-ramp policy (171,664 weights) | Success in all 1,024 episodes; 3.5% of weights changed | Original PPO (1B steps): 0% success in 256 episodes |\n| 5 | Write MinAtar networks from scratch (zero-shot) | Breakout 517.4; Seaquest 53.1; Asterix 53.2 | PPO 100M: 15.8 / 5.6 / 25.8. PPO 500M: 25.3 / 88.9 / 55.2 |\n| 6 | Write a 9×9 Go network (1,480,274 weights) | 0 forward passes: wins more than half of games vs. two smaller PPO nets. 50 forward passes: beats the equal-sized PPO net trained on 20M games | Two smaller PPO nets (seeds 0 and 2) |\n| 7 | Identify the sycophantic Gemma 3 270M (3 pairs) | Weights alone: failed in 4 attempts. With attention patterns: correct in all 3 pairs | Sycophant follows 100% of wrong guesses; honest model 1–3% |\n| 8 | Improve Qwen3.5-0.8B at math (131,072 weights edited, 0.016%) | See table below | Base model |\n\n**Experiment 8 (Qwen3.5-0.8B), scores in %**\n\n| Model | MATH-500 | GSM8K | IFEval | Hit token limit |\n|---|---|---|---|---|\n| Base | 7.9 | 13.8 | 21.0 | 93.0 |\n| Edited, 10 forward passes | 12.3 | 25.7 | 49.0 | 87.2 |\n| Edited, 25 forward passes | 14.1 | 25.1 | 39.9 | 86.4 |\n| Edited, 50 forward passes | 48.1 | 67.1 | 62.3 | 33.1 |\n\n**Additional experiment (Gemma 3 270M, MATH-500 %):** Base 6.8; 5 passes 7.0; 10 passes 7.6; 25 passes 7.7; 50 passes 7.0. The authors report no meaningful improvement.",
  "durationMs": 12744,
  "url": "https://rikiyat.github.io/blog/weight-space-programming/"
}

{
  "url": "https://unit42.paloaltonetworks.com/ai-campaign-targets-linux-infrastructure/",
  "prompt": "Exact publication date and any update date. Key numbers and findings on AI-generated scripts."
}

{
  "bytes": 333525,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** October 15, 2026. The page lists no separate update date.\n\n**Key numbers:**\n- Observed activity ran from October 2025 to April 2026. Unit 42 tracks it as CL-UNK-1211.\n- Reverse shells ran across at least seven distinct C2 servers. The primary named-pipe Netcat method was used on three of them.\n- The SysGoRAT RAT has seven command types and four control sub-actions. Its persist action supports six installation methods.\n- Persistence via PHP config hijacking covered all PHP configuration files under /etc/php/ and /opt/plesk/php/.\n- The report lists 17 IP addresses, four domains, and several SHA-256 hashes for web shells, scanners, and backdoors.\n\n**Findings on AI-generated scripts:**\n- Multiple artifacts contained \"AI-made conversational annotations and developer reasoning comments.\" Unit 42 suggests the code was either generated by LLMs or run by an automated AI agent.\n- Scripts contained step-by-step reasoning notes aimed at the operator, rather than standard developer documentation.\n- Other traits Unit 42 considered consistent with AI-assisted or AI-operated attacks include section headers in scripts and commands, heavy use of Base64-encoded commands, and switching between PHP, JavaScript, Bash, and Python.\n- The conclusion says attackers are using AI to \"rapidly generate, adapt and deploy operational scripts,\" which lets them keep a fast pace while minimizing manual developer effort.",
  "durationMs": 6056,
  "url": "https://unit42.paloaltonetworks.com/ai-campaign-targets-linux-infrastructure/"
}

{
  "query": "AI influence operation disinformation network takedown report November 3 2026",
  "mode": "extended"
}

{
  "query": "AI influence operation disinformation network takedown report November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01PKNL8eWEn4kh4uGJah9CQd",
      "content": [
        {
          "title": "Exclusive: Meta disrupts Iran-linked AI operation targeting politicians, journalists",
          "url": "https://www.axios.com/2026/08/27/facebook-instagram-iran-ai-disinformation"
        },
        {
          "title": "OpenAI takes down covert operations tied to China and other countries",
          "url": "https://www.npr.org/2025/06/05/nx-s1-5423607/openai-china-influence-operations"
        },
        {
          "title": "Influence Operations in Social Networks",
          "url": "https://arxiv.org/pdf/2502.11827"
        },
        {
          "title": "For Beijing’s Foreign Disinformation, the Era of AI-Driven Operations Has Arrived",
          "url": "https://thediplomat.com/2025/09/for-beijings-foreign-disinformation-the-era-of-ai-driven-operations-has-arrived/"
        },
        {
          "title": "OpenAI, Meta, and TikTok Crack Down on Covert Influence Campaigns, Some AI-Powered",
          "url": "https://thehackernews.com/2024/05/openai-meta-tiktok-disrupt-multiple-ai.html"
        },
        {
          "title": "Propagandists are using AI too—and companies need to be open about it",
          "url": "https://www.technologyreview.com/2024/06/08/1093356/propagandists-are-using-ai-too-and-companies-need-to-be-open-about-it/"
        },
        {
          "title": "Frontiers",
          "url": "https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1569115/full"
        },
        {
          "title": "Graphika",
          "url": "https://en.wikipedia.org/wiki/Graphika"
        },
        {
          "title": "Spamouflage",
          "url": "https://en.wikipedia.org/wiki/Spamouflage"
        }
      ]
    },
    "I didn't find a report dated November 3, 2026. The closest match is a Meta takedown from late August 2026.\n\n- **Most recent relevant item:** Meta removed a network of Facebook and Instagram accounts tied to an Iran-based operation that used AI to target U.S. audiences with posts about American politics. It was part of a broader threat report, and Meta said it disrupted four Facebook accounts and 31 Instagram accounts linked to actors based in Iran. Meta also said it finds the technology's use in virtually every influence network it disrupts.\n- **Earlier AI-enabled takedowns (2024–2025):** OpenAI's June 2025 report covered operations tied to Russia, China, and Iran, including a Chinese operation that used ChatGPT to generate short comments that were posted across TikTok, X, Reddit, Facebook and other websites. Graphika's \"Falsos Amigos\" report identified a network of 11 fake websites that used AI-generated images.\n- **Unverified item:** A Frontiers article dated two days ago discusses a Russian AI-enhanced disinformation network, but its case study is labeled 2024, so I can't confirm it's new.\n\nI'd recommend searching for the specific date or for \"Meta adversarial threat report\" or \"OpenAI threat report\" to check for anything published in November 2026."
  ],
  "durationSeconds": 6.285001787000045,
  "searchCount": 1
}

{
  "url": "https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/",
  "prompt": "Date, case name/docket number, court, how many amicus briefs, who filed on each side, what motion they address, and key dates."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 309,
  "url": "https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/"
}

{
  "query": "China military AI PLA report CSET CNAS November 2026",
  "mode": "extended"
}

{
  "query": "China military AI PLA report CSET CNAS November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_015cZVJJJ56DyxuSbSu3qqBU",
      "content": [
        {
          "title": "China’s Military AI Wish List",
          "url": "https://cset.georgetown.edu/publication/chinas-military-ai-wish-list/"
        },
        {
          "title": "Issue Brief February 2026 China’s Military AI Wish List Command, Control,",
          "url": "https://cset.georgetown.edu/wp-content/uploads/CSET-Chinas-Military-AI-Wish-List.pdf"
        },
        {
          "title": "New CNAS Report: “U.S.-China Competition and Military AI: How Washington Can Manage Strategic Risks amid Rivalry with Beijing”",
          "url": "https://www.cnas.org/press/press-release/new-cnas-report-u-s-china-competition-and-military-ai-how-washington-can-manage-strategic-risks-amid-rivalry-with-beijing"
        },
        {
          "title": "The National Security Case for Limiting China's Access to Advanced U.S. Compute: Evidence from PLA Procurement Documents",
          "url": "https://cset.georgetown.edu/article/the-national-security-case-for-limiting-chinas-access-to-advanced-u-s-compute-evidence-from-pla-procurement-documents"
        },
        {
          "title": "How China Is Using AI To Win Future Wars",
          "url": "https://cset.georgetown.edu/article/how-china-is-using-ai-to-win-future-wars/"
        },
        {
          "title": "U.S.-China Competition and Military AI",
          "url": "https://www.cnas.org/publications/reports/u-s-china-competition-and-military-ai"
        },
        {
          "title": "National Security Commission on Artificial Intelligence",
          "url": "https://en.wikipedia.org/wiki/National_Security_Commission_on_Artificial_Intelligence"
        },
        {
          "title": "Robot wolf",
          "url": "https://en.wikipedia.org/wiki/Robot_wolf"
        },
        {
          "title": "China’s PLA Challenges and Competitions",
          "url": "https://cset.georgetown.edu/article/chinas-pla-challenges-and-competitions/"
        }
      ]
    },
    "I didn't find a CSET or CNAS report on Chinese military AI dated November 2026. The closest matches are older or adjacent work:\n\n- **CSET, February 2026:** \"China's Military AI Wish List\" analyzes more than 9,000 PLA requests for proposal to map its AI priorities across C5ISRT functions. The RFPs reflect China's desire to generate, augment, and fuse increasing quantities of data to speed military decision-making. The authors also argue that relaxing export controls will facilitate China's development and use of AI-enabled C5ISRT technologies.\n- **CSET, April 2026:** A follow-on article argues that allowing China to access advanced U.S. compute would help the PLA develop and deploy military AI systems.\n- **CSET, earlier:** A report on military-civil fusion examined 2,857 AI-related defense contract award notices published between January 2023 and December 2024.\n- **CNAS, July 2023:** \"U.S.-China Competition and Military AI\" lays out five categories of pathways through which military AI could undermine stability and increase strategic risk between Washington and Beijing.\n\nIf you need a November 2026 publication specifically, I'd check the CSET and CNAS publication pages directly, since the search index may not have it yet."
  ],
  "durationSeconds": 6.352232449000002,
  "searchCount": 1
}

{
  "query": "AI voice cloning scam losses FBI FTC figures November 2026",
  "mode": "extended"
}

{
  "query": "AI voice cloning scam losses FBI FTC figures November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_0196yK7mZVfjmetxCyiFYwgw",
      "content": [
        {
          "title": "AI Voice Cloning Statistics 2026: Scams and Laws",
          "url": "https://www.afterlife.ai/ai-voice-cloning-statistics"
        },
        {
          "title": "AI Voice-Cloning Scams Cost Older Americans $352 Million Last Year. Here's the Defense That Actually Works.",
          "url": "https://www.alperinlaw.com/blog/ai-voice-cloning-elder-fraud-protection.cfm"
        },
        {
          "title": "AI Voice Cloning Ethics Statistics (2026): 48 Data Points on Deepfake Policies, SAG-AFTRA, and Voice Rights — VoxBooster",
          "url": "https://voxbooster.com/blog/ai-voice-cloning-ethics-statistics-2026/"
        },
        {
          "title": "AI Voice Cloning Scams in 2026: What the FBI's $893M Warning Means for You",
          "url": "https://www.cyberfenceplatform.com/blog/ai-voice-cloning-scams-2026"
        },
        {
          "title": "AI Voice Cloning Scam Statistics 2026: $893M in AI Fraud Data",
          "url": "https://axis-intelligence.com/voice-cloning-scam-statistics/"
        },
        {
          "title": "AI Voice Cloning Scams: What They Are and How to Stay Safe",
          "url": "https://ginihelp.com/blog/ai-voice-cloning-scams"
        },
        {
          "title": "Is AI Voice Safe? Voice Cloning Scams and Protection (2026)",
          "url": "https://kveeky.com/blog/is-ai-voice-safe"
        },
        {
          "title": "AI Voice Cloning Scam Statistics 2026: FBI, FTC & Industry Data",
          "url": "https://www.eyesift.com/blog/ai-voice-cloning-scam-statistics-2026/"
        },
        {
          "title": "AI Voice Scam: How It Works and How to Stop It",
          "url": "https://felloai.com/ai-voice-scam/"
        }
      ]
    },
    "The figures are mostly from FBI and FTC annual reports for 2025, but nearly every source I found is a secondary blog, so check the primary reports before citing them.\n\n- **FBI, AI-related fraud overall:** The FBI's 2025 report logged about 22,364 AI-related complaints with roughly $893 million in losses. The report's own line on the voice scam is far smaller, and one commentary notes that the $893 million covers AI-related fraud of every type, not just voice cloning.\n- **FBI, voice-clone specifically:** Losses from voice-clone \"family in trouble\" or distress scams were reported at over $5 million in 2025. The closest voice-specific figure the FBI publishes is losses over $5 million to distress scams within the confidence and romance category.\n- **FBI, older adults:** Americans 60 and older filed 201,266 internet fraud complaints, reporting $7.7 billion in losses. One source puts AI-related losses for that age group at about $352 million, but I could not confirm that against the FBI report itself.\n- **FTC:** Total fraud reports reached about 3 million with $15.9 billion in losses in 2025, and imposter scams reported to the FTC exceeded $3.5 billion. The FTC does not appear to break out voice cloning as its own category in these results.\n- **Conflicting figure:** One site cites $440 million in FTC-reported voice-clone family emergency losses. I found no primary source for that number, so I would not rely on it.\n\nBottom line: the defensible voice-cloning-specific figure is about $5 million (FBI distress scams), while the $893 million figure covers AI-related fraud broadly. The search did not return the FBI IC3 or FTC reports directly, so verify these numbers against those sources before publishing."
  ],
  "durationSeconds": 7.293605227000022,
  "searchCount": 1
}

{
  "query": "New York Times Chicago Tribune sue Brave Software lawsuit November 2 2026 AI",
  "mode": "extended"
}

{
  "query": "New York Times Chicago Tribune sue Brave Software lawsuit November 2 2026 AI",
  "results": [
    {
      "tool_use_id": "srvtoolu_01RiVN1uMRSGia27wmKu6zKY",
      "content": [
        {
          "title": "New York Times, Chicago Tribune Sue Tech Company Brave Over AI Copyright Claims",
          "url": "https://www.yahoo.com/news/politics/articles/york-times-chicago-tribune-sue-213726490.html"
        },
        {
          "title": "New York Times, Chicago Tribune Sue Tech Company Brave Over AI Copyright Claims",
          "url": "https://www.thewrap.com/industry-news/tech/new-york-times-chicago-tribune-brave-ai-copyright-lawsuit/"
        },
        {
          "title": "Who's suing AI and who's signing latest: US newspapers sue Brave Software and Canadian publishers sue Anthropic",
          "url": "https://pressgazette.co.uk/platforms/news-publisher-ai-deals-lawsuits-openai-google/"
        },
        {
          "title": "New York Times and three other US papers sue Brave over AI scraping",
          "url": "https://thenextweb.com/news/nyt-newspapers-sue-brave-ai-scraping"
        },
        {
          "title": "NYT, Tribune Papers Sue Brave Over 30B-Page AI Scraping Index",
          "url": "https://aiweekly.co/alerts/nyt-tribune-papers-sue-brave-over-30b-page-ai-scraping-index"
        },
        {
          "title": "New York Times and three other US papers sue Brave over AI scraping",
          "url": "https://daily.dev/posts/new-york-times-and-three-other-us-papers-sue-brave-over-ai-scraping-a6npfekqt"
        },
        {
          "title": "NYT, Tribune papers file copyright lawsuit against Brave Software",
          "url": "https://www.adgully.com/post/23299/nyt-tribune-papers-file-copyright-lawsuit-against-brave-software"
        },
        {
          "title": "New York Times Sues Brave Browser Over AI Scraping",
          "url": "https://www.techbuzz.ai/articles/new-york-times-sues-brave-browser-over-ai-scraping"
        },
        {
          "title": "New York Times Sues Brave for AI Scraping and Bypassing Paywalls",
          "url": "https://theoutpost.ai/news-story/new-york-times-and-major-publishers-sue-brave-over-ai-scraping-and-copyright-infringement-33003/"
        }
      ]
    },
    "The New York Times and three Tribune Publishing papers sued Brave Software on November 2, 2026, in Manhattan federal court, over AI-related copying. The Times filed its own suit, and the Daily News, Chicago Tribune, and Orlando Sentinel filed a separate, similar suit hours later.\n\n- **The allegations:** The publishers say Brave built a index of more than 30 billion pages and sells access to it to AI companies. One report says Brave allegedly sells this data via its Search API to Anthropic, Perplexity, Mistral, xAI and Cohere. The Tribune-owned papers also say its AI answer tool, Ask Brave, reproduced large chunks of their articles. The tool generated more than 1,200 words from a Chicago Tribune article about tax breaks for data centers and nearly 600 words from a Daily News article about Central Park horse carriages.\n- **Other claims:** The suits also target Brave's paywall-blocking feature and its ad-blocking business model, according to one report.\n- **Relief sought:** Brave had not responded to requests for comment at publication, and the complaints seek an injunction and damages.\n- **Context:** News Corp, which owns the Wall Street Journal and New York Post, countersued Brave in July, accusing the company of scraping and reselling copyrighted journalism to AI developers without permission.\n\nOne source (TechBuzz) says the filings came on Sunday, but most reports say Monday, which matches November 2, 2026. Sources also disagree on whether the named AI companies are defendants or only identified as customers. The coverage I found doesn't settle that."
  ],
  "durationSeconds": 6.397570756000001,
  "searchCount": 1
}

{
  "url": "https://www.techmeme.com/",
  "prompt": "Give me the exact full URLs (hyperlink targets) for the following stories, plus any byline/time shown: (1) Nvidia telling cloud clients to sell at least 51% to non-Chinese companies; (2) Brookfield/Drax/Radiant AI data centre North Yorkshire; (3) Oracle raising $20B; (4) Palantir earnings; (5) OpenAI Grid Protectors Program; (6) OpenAI bug bounty $172,000; (7) Anthropic Claude Code game cloning limits; (8) UK NCSC AI cyber warning; (9) Huawei AI chip Samsung SK Hynix memory; (10) Google first data center satellite."
}

{
  "bytes": 402122,
  "code": 200,
  "codeText": "OK",
  "result": "I can only find one of the ten stories in the material you provided. The page content is cut off partway through the Nvidia item, so the other nine don't appear.\n\n**1. Nvidia telling cloud clients to sell at least 51% to non-Chinese companies**\n- **URL:** https://www.ft.com/content/1902df70-1380-4588-bad5-171352b575f2\n- **Source:** Financial Times (no individual byline shown)\n- **Time:** No story-level time is shown. The page's \"November 3, 2026, 6:05 AM\" is the snapshot time of the Techmeme page.\n- **Related coverage:** Bloomberg's report on the same story is at https://www.bloomberg.com/news/articles/2026-11-03/nvidia-tells-data-center-clients-to-trim-china-business-ft-says\n\n**Not in the provided content (truncated):** Items 2 through 10 (Brookfield/Drax/Radiant, Oracle, Palantir, OpenAI's Grid Protectors Program, OpenAI's bug bounty, Anthropic's Claude Code limits, the UK NCSC warning, Huawei/Samsung/SK Hynix, and Google's satellite data center). If you paste the remaining page content, I can extract their URLs, bylines, and times.\n\n[WebFetch note: this page's text is 243785 characters long and the answer above covers only characters 0 to 100000; the final 143785 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 5435,
  "url": "https://www.techmeme.com/"
}

{
  "url": "https://www.darkreading.com/",
  "prompt": "List articles dated Nov 2 or Nov 3 2026 with headlines and URLs; flag AI-related ones."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 241,
  "url": "https://www.darkreading.com/"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -sS \"https://rss.arxiv.org/rss/cs.AI\" -o cs.AI.xml && cat > get.py <<'EOF'\nimport re,sys,glob,xml.etree.ElementTree as ET,html\nwant=set(sys.argv[1:])\nseen=set()\nfor f in glob.glob('cs.*.xml'):\n    for it in ET.parse(f).getroot().iter('item'):\n        link=it.findtext('link','')\n        aid=link.split('/abs/')[-1]\n        if aid in want and aid not in seen:\n            seen.add(aid)\n            print(\"=\"*8,aid,it.findtext('title',''))\n            print(it.findtext('description','').replace('\\n',' '))\n            print()\nfor w in want-seen: print(\"MISSING\",w)\nEOF\npython3 -I get.py 2611.00407 2611.00640 2611.00606 2611.00602 2611.00350 2611.03244 2611.01564 2611.02270 2611.00464 2>&1 | head -120",
  "description": "Extract abstracts for top candidates"
}

{
  "stdout": "======== 2611.00350 On the Limits of Test-Time Compute for Self-Evaluation\narXiv:2611.00350v1 Announce Type: new  Abstract: Self-verification and aggregation have emerged as popular approaches for bridging the gap between pass@1 and pass@N. However, increasing the number of candidates does not consistently narrow the gap between final-answer accuracy and pass@N. To understand this limitation, we use ranking error to measure how reliably models distinguish their correct generations from incorrect ones. We show that ranking error admits a bias-variance decomposition, with both components shaped by algorithmic design choices and inference compute. Across our experiments, additional compute reduces variance, while bias initially decreases before approaching a plateau. Guided by this analysis, we introduce Scorpio, a simple and general method that jointly scores randomly grouped candidates. Across math, code, and puzzle benchmarks, Scorpio improves verification, tree search, and aggregation. For verification, Scorpio improves accuracy over the strongest baseline by up to 7 percentage points while matching or exceeding that baseline's peak accuracy with 17-42% lower inference cost. For tree search, using Scorpio to score partial solutions and select the final answer improves accuracy by up to 10 percentage points over prior methods. Finally, Scorpio improves the scaling of aggregation-based methods by 11 percentage points on coding tasks.\n\n======== 2611.00606 Sparse Autoencoder Attribution Graphs Are Decided at the Margin\narXiv:2611.00606v1 Announce Type: new  Abstract: Attribution graphs over the features of sparse autoencoders (SAEs) are used to predict what an ablation does and are compared across training seeds. A TopK SAE keeps the largest preactivations at each token, and a feature's margin is its preactivation's distance to the cutoff. On five public TopK SAE pairs from three Pythia models, zeroing one feature moves a next layer feature across the cutoff in 0.74 of cases or more, and the crossings carry most of the response's energy. Over writes that scale a feature's code by three factors, the graph built on the features active beforehand has a median relative error of 0.247 or more. The margin graph adds the first order change to every preactivation and reranks, at the same cost, and errs by at most 0.033. At the median, the crossing features' decoded change is 1.24 times the model's own change in norm or more. Between seeds of one testbed, sparse maps between features explain 0.85 of a graph's energy on its active features, and 0.47 once the other seed's graph keeps only its own. The largest model studied is pythia-160m.\n\n======== 2611.00640 Bridging Singular Learning Theory and Mechanistic Interpretability at the Billion-Parameter Scale\narXiv:2611.00640v1 Announce Type: new  Abstract: Mechanistic interpretability (MI) explains a computation in a trained network by identifying the components and variables that implement it and testing them with interventions. Singular learning theory (SLT) describes the same network through the geometry of the loss around its parameters, summarized by the local learning coefficient. In pretrained language models the two have not been compared: SLT's estimates at this scale concern whole models or components whose roles were not independently established, and the estimator, which averages the loss over parameter settings drawn near the trained ones, has had no reference for how far those draws may move the parameters. We show that both are functions of one object, the map from a component's parameters to the model's predictions under inputs and interventions, whose first derivatives determine the Fisher information, the learning coefficient, and intervention effects, and whose higher derivatives add a quartic correction and pairwise terms. We test this correspondence in Pythia-1B on Dyck bracket matching at all 154 training checkpoints, against a five-stage circuit identified by interventions. We measure the local geometry of all 144 components inside the region where predictions are preserved, with the Fisher spectrum at every checkpoint, which gives the quadratic part of the learning-coefficient estimate at every temperature. Changes of the Fisher trace track changes of causal effect (median partial rank correlation 0.51), largely as a trend shared across the model, whereas the gain Fisher of a component's output and the large-temperature count are specific to the component. The count follows causal change across the population but not the growth of a formed circuit component. The quartic part is what a sampler that leaves the region registers beyond curvature. Pairwise interaction curvature tracks joint-ablation interactions.\n\n======== 2611.01564 Meta-memorization and memorization scaling laws in transformers\narXiv:2611.01564v1 Announce Type: new  Abstract: Larger transformers can memorize more data, with a capacity (in bits) that scales roughly linearly with the number of parameters. Counterintuitively, larger models also memorize faster, requiring fewer repetitions of a sequence during training before it is memorized. We reproduce both memorization scaling laws in transformers trained on random binary sequences, showing that rapid memorization can arise even when data contain no semantic or compositional structure. Rapid memorization is due to a meta-memorization effect, where models trained to memorize a large set of random sequences learn to memorize novel sequences more quickly. The rate $r(t)$ at which models memorize grows with training time $t$ as a power-law $r(t) \\sim t^{\\beta}$ with a fixed exponent $\\beta$ but an increasing upper cutoff across model scales. Meta-memorization enables even one-layer transformers to few-shot memorize a 100-bit sequence. This effect is partly explained by the formation of structured attention heads that convey position-invariant sequence information to MLPs where memorized sequen
… [9083 more characters in events.jsonl]

{
  "url": "https://www.anthropic.com/news",
  "prompt": "List items dated Nov 2 or Nov 3 2026 with titles and URLs."
}

{
  "bytes": 348795,
  "code": 200,
  "codeText": "OK",
  "result": "No items on this page are dated November 2 or November 3, 2026.\n\nThe only \"November 3, 2026\" on the page is a standalone date label above the \"Introducing Claude Opus 5.5\" entry, which is dated September 22, 2026. The most recent dated article in the list is \"AI for Science expands to foundations and research institutions\" (Oct 28, 2026): /news/ai-for-science-expands-foundations-research-institutions",
  "durationMs": 3501,
  "url": "https://www.anthropic.com/news"
}

{
  "url": "https://www.europol.europa.eu/media-press/newsroom",
  "prompt": "List press releases dated Nov 2 or Nov 3 2026 with titles and URLs; flag AI/deepfake/fraud ones."
}

{
  "bytes": 60786,
  "code": 200,
  "codeText": "OK",
  "result": "The content you provided doesn't include any press releases. It shows only the page title \"Newsroom | Europol\" and the message \"Loading application. Please wait.\" It has no titles, dates, or URLs, so I can't list releases from November 2 or 3, 2026, or flag any AI, deepfake, or fraud-related items.\n\nIf you paste the page's full text once it has loaded, or the list of releases, I can filter for those dates and flag the relevant ones.",
  "durationMs": 3523,
  "url": "https://www.europol.europa.eu/media-press/newsroom"
}

{
  "command": "node scripts/fetch.js \"https://www.ft.com/content/1902df70-1380-4588-bad5-171352b575f2\" 2>&1 | head -60",
  "description": "Fetch FT Nvidia China article"
}

{"stdout":"HTTP 403 · https://www.ft.com/content/1902df70-1380-4588-bad5-171352b575f2 · text/plain\nBlocked by egress policy","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":165,"oldLines":3,"newStart":165,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:10:43.146Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7d5674a33c6d710e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_01ByJ62WNed2Ke7awNYhMwgD\",\"duration_ms\":242,\"input\":{\"url\":\"https://www.darkreading.com/\",\"prompt\":\"List articles dated Nov 2 or Nov 3 2026 with headlines and URLs; flag AI-related ones.\"},\"response\":{\"bytes\":0,\"code\":403,\"codeText\":\"Forbidden\",\"result\":\"The server returned HTTP 403 Forbidden.\\n\\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.\",\"durationMs\":241,\"url\":\"https://www.darkreading.com/\"}}"," {\"t\":\"2026-11-03T11:10:47.560Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7f44935a6a031c3b\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01JPepEibAcahWrS9qpboEBi\",\"duration_ms\":378,\"input\":{\"command\":\"cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -sS \\\"https://rss.arxiv.org/rss/cs.AI\\\" -o cs.AI.xml && cat > get.py <<'EOF'\\nimport re,sys,glob,xml.etree.ElementTree as ET,html\\nwant=set(sys.argv[1:])\\nseen=set()\\nfor f in glob.glob('cs.*.xml'):\\n    for it in ET.parse(f).getroot().iter('item'):\\n        link=it.findtext('link','')\\n        aid=link.split('/abs/')[-1]\\n        if aid in want and aid not in seen:\\n            seen.add(aid)\\n            print(\\\"=\\\"*8,aid,it.findtext('title',''))\\n            print(it.findtext('description','').replace('\\\\n',' '))\\n            print()\\nfor w in want-seen: print(\\\"MISSING\\\",w)\\nEOF\\npython3 -I get.py 2611.00407 2611.00640 2611.00606 2611.00602 2611.00350 2611.03244 2611.01564 2611.02270 2611.00464 2>&1 | head -120\",\"description\":\"Extract abstracts for top candidates\"},\"response\":{\"stdout\":\"======== 2611.00350 On the Limits of Test-Time Compute for Self-Evaluation\\narXiv:2611.00350v1 Announce Type: new  Abstract: Self-verification and aggregation have emerged as popular approaches for bridging the gap between pass@1 and pass@N. However, increasing the number of candidates does not consistently narrow the gap between final-answer accuracy and pass@N. To understand this limitation, we use ranking error to measure how reliably models distinguish their correct generations from incorrect ones. We show that ranking error admits a bias-variance decomposition, with both components shaped by algorithmic design choices and inference compute. Across our experiments, additional compute reduces variance, while bias initially decreases before approaching a plateau. Guided by this analysis, we introduce Scorpio, a simple and general method that jointly scores randomly grouped candidates. Across math, code, and puzzle benchmarks, Scorpio improves verification, tree search, and aggregation. For verification, Scorpio improves accuracy over the strongest baseline by up to 7 percentage points while matching or exceeding that baseline's peak accuracy with 17-42% lower inference cost. For tree search, using Scorpio to score partial solutions and select the final answer improves accuracy by up to 10 percentage points over prior methods. Finally, Scorpio improves the scaling of aggregation-based methods by 11 percentage points on coding tasks.\\n\\n======== 2611.00606 Sparse Autoencoder Attribution Graphs Are Decided at the Margin\\narXiv:2611.00606v1 Announce Type: new  Abstract: Attribution graphs over the features of sparse autoencoders (SAEs) are used to predict what an ablation does and are compared across training seeds. A TopK SAE keeps the largest preactivations at each token, and a feature's margin is its preactivation's distance to the cutoff. On five public TopK SAE pairs from three Pythia models, zeroing one feature moves a next layer feature across the cutoff in 0.74 of cases or more, and the crossings carry most of the response's energy. Over writes that scale a feature's code by three factors, the graph built on the features active beforehand has a median relative error of 0.247 or more. The margin graph adds the first order change to every preactivation and reranks, at the same cost, and errs by at most 0.033. At the median, the crossing features' decoded change is 1.24 times the model's own change in norm or more. Between seeds of one testbed, sparse maps between features explain 0.85 of a graph's energy on its active features, and 0.47 once the other seed's graph keeps only its own. The largest model studied is pythia-160m.\\n\\n======== 2611.00640 Bridging Singular Learning Theory and Mechanistic Interpretability at the Billion-Parameter Scale\\narXiv:2611.00640v1 Announce Type: new  Abstract: Mechanistic interpretability (MI) explains a computation in a trained network by identifying the components and variables that implement it and testing them with intervention
… [10069 more characters in events.jsonl]

{
  "url": "https://www.theregister.com/security/",
  "prompt": "List articles dated Nov 2 or Nov 3 2026 with headlines and URLs; flag AI-related ones."
}

{
  "bytes": 448676,
  "code": 200,
  "codeText": "OK",
  "result": "Articles dated November 2, 2026 (none dated November 3 appear on the page):\n\n1. \"Max-severity bug in widely used OT programming tool exploited to deliver Linux malware\". https://www.theregister.com/security/2026/11/02/max-severity-bug-in-widely-used-ot-programming-tool-exploited-to-deliver-linux-malware/5307086\n2. \"Cops bust botnet of 1.3M infected Android TV boxes\". https://www.theregister.com/cyber-crime/2026/11/02/cops-bust-botnet-of-13m-infected-android-tv-boxes/5307045\n3. \"Thieves pilfer environment variables from Trigger AI workflow tool\". https://www.theregister.com/security/2026/11/02/thieves-pilfer-environment-variables-from-trigger-ai-workflow-tool/5306998 **(AI-related)**\n4. \"Token thieves costing companies $100K+ per day in illicit LLM charges\". https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967 **(AI-related)**\n5. \"Nuclear threats and street brawls: Russia, Ukraine report attacks on their emergency alert apps\". https://www.theregister.com/security/2026/11/02/nuclear-threats-and-street-brawls-russia-ukraine-report-attacks-on-their-emergency-alert-apps/5306901\n6. \"Frozen part II: Hackers remotely defrost produce in Euro supermarkets ... again\". https://www.theregister.com/cyber-crime/2026/11/02/frozen-part-ii-hackers-remotely-defrost-produce-in-euro-supermarkets-again/5306924\n7. \"FBI pins $6.3B Binance crypto heist on North Korean hackers\". https://www.theregister.com/security/2026/11/02/fbi-pins-63b-binance-crypto-heist-on-north-korean-hackers/5306889\n\n**AI-related:** Items 3 and 4.",
  "durationMs": 6900,
  "url": "https://www.theregister.com/security/"
}

{
  "url": "https://www.thewrap.com/industry-news/tech/new-york-times-chicago-tribune-brave-ai-copyright-lawsuit/",
  "prompt": "Date of article, filing date, court, plaintiffs, defendants, exact allegations with numbers, and relief sought."
}

{
  "bytes": 176409,
  "code": 200,
  "codeText": "OK",
  "result": "**Article date:** November 2, 2026 (TheWrap, by A.J. Katz)\n\n**Filing date:** The article says the suits were filed \"on Monday,\" which matches the article date. The exact filing date is not stated.\n\n**Court:** Manhattan federal court. The suits were filed separately. A complaint link in the article references docket \"26-cv-9554\" for the Daily News, Tribune, and Sentinel filing.\n\n**Plaintiffs:**\n- The New York Times\n- New York Daily News\n- Chicago Tribune\n- Orlando Sentinel\n\n**Defendant:** Brave Software, described as a web browser and AI search company. The article names CEO Brendan Eich only as the recipient of cease-and-desist letters.\n\n**Allegations and figures:**\n- The Daily News, Tribune, and Sentinel filed a 69-page complaint alleging Brave copied copyrighted articles and distributed them through its Brave Search API.\n- The NYT filed a separate 72-page complaint. It alleges it sent cease-and-desist letters to Eich in August 2025 and April 2026 with no response.\n- The NYT also alleges Brave reproduced its copyrighted reporting and let users bypass its paywall.\n- The complaint says Brave's \"Ask Brave\" tool generated more than 1,200 words from a Chicago Tribune article on data center tax breaks.\n- It says the tool generated nearly 600 words from a Daily News article on Central Park horse carriages.\n- The filing names Anthropic, Perplexity, Mistral, xAI, and Cohere as companies that have used Brave's services.\n- The publishers argue Brave profits from their journalism without payment, potentially cutting into subscription, advertising, and licensing revenue.\n\n**Relief sought:** The article does not state what relief the plaintiffs are requesting.\n\n**Context:** Brave has defended its search practices as fair use. News Corp countersued Brave in July, and Brave had earlier sued News Corp seeking a ruling that its practices were lawful.",
  "durationMs": 7599,
  "url": "https://www.thewrap.com/industry-news/tech/new-york-times-chicago-tribune-brave-ai-copyright-lawsuit/"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I get.py 2611.00412 2611.00508 2611.00460 2611.00138 2611.00725 2611.00505 2611.02348 2611.00386 2611.00420 2611.01378 2611.02710 2611.00555 2611.03494 2611.00465 2611.02278 2611.00247 2>&1 | head -200",
  "description": "Extract second batch of abstracts"
}

{"stdout":"======== 2611.00138 Kerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents\narXiv:2611.00138v1 Announce Type: new  Abstract: Existing large language model (LLM) backdoor attacks operate primarily in chat settings, where the risk is bounded by free-form text outputs. AI agents remove that bound by performing actions and executing commands on the user's machine. We introduce structured-output backdoor attacks against reasoning models in agentic coding settings. A trigger placed anywhere in the agent's context causes the model to emit an attacker-chosen tool call, which the harness executes, directly compromising the system's confidentiality, integrity, or availability. We present Kerkoporta, a methodology that constructs high-quality poison samples, injects the backdoor via supervised fine-tuning, and recovers utility loss with lightweight reinforcement learning. We evaluate on modern, heavily post-trained open-weight models across proprietary and open-source harnesses, focusing on coding for its wide adoption and long-horizon task structure. The attack reaches success rates of up to 96.2% and can be configured to generalize across harnesses or bind to a single target. The resulting models can outperform the clean baseline on standard utility benchmarks, giving victims a direct incentive to adopt them. Overall, we demonstrate that LLM backdoors can have critical security impacts in the context of modern coding agents, and we characterize the poisoning methodology required to insert backdoors that are both effective and stealthy in this setting.\n\n======== 2611.00725 The Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents\narXiv:2611.00725v1 Announce Type: new  Abstract: Coding agents increasingly operate with web access and high privileges, creating a new attack surface where web fraud can directly target autonomous agents. Existing studies mainly focus on malicious links, prompt injection, and interface deception, while content-level web fraud against agents and the amplification of attacks through agent trust remain underexplored. In this paper, we present EtE (Earn-then-Exploit), a web fraud attack framework against coding agents, in which a malicious website first provides multiple rounds of genuinely verifiable assistance to establish trust and then introduces task-related instructions that cross intended operational boundaries. To systematically evaluate its effectiveness, we construct 56 organizational environments (8 task contexts x 7 attack consequences) and evaluate three representative coding agents. EtE achieves an average scene-level attack success rate of 71.4%, including 85.7% on Codex-GPT-5.5, 67.9% on ZCode-GLM-5.3-Flash, and 60.7% on QwenCode-Qwen3.7-Plus, significantly outperforming all injection-based baselines. More importantly, our experiments reveal that coding agents exhibit trust-like behavioral reliance on previously helpful Web sources, and that such accumulated credibility significantly increases their susceptibility to subsequent malicious instructions. Based on this finding, we propose action-authorization separation (AAS), which prevents web content from directly authorizing privileged actions and reduces the attack success rate to 0% while preserving 100% task completion, outperforming all evaluated defense baselines.\n\n======== 2611.02278 Concise-9B: Removing the Slack from a Reasoning Model's Thinking\narXiv:2611.02278v1 Announce Type: new  Abstract: Reasoning models answer better when they think longer, but a thinking trace keeps going well after its answer has formed. We measure this slack in Qwen3.5-9B and remove most of it with concise self-training: two rounds of on-policy rejection-sampling fine-tuning that keep the shortest correct samples, plus a small share of answer-synthesis targets, giving Concise-9B. On 8,983 held-out problems (competition and hard mathematics, SuperGPQA, a five-area confirmation set and MMLU-Pro), Concise-9B generates 0.66x the tokens of Qwen3.5-9B at a 32K thinking budget, with accuracy equivalent within +/-1 point (-0.20 [-0.77, +0.36] points). Forcing each trace on the hard and confirmation sets to answer every 2,048 thinking tokens, we find that 54-64% of Qwen3.5-9B's thinking tokens come after the point from which every forced answer equals the final one (41-48% for Concise-9B). Stopping there would keep every answer at 0.35-0.44x the base model's tokens, but finding that point takes hindsight: stopping when three consecutive forced answers agree costs the base model 2.4-9.2 points. Concise self-training removes slack without that cost: 86% [83, 90] of the thinking tokens it saves come after the answer has formed. It has a limit: with traces continued to 80K tokens, Concise-9B solves 25 fewer of 1,276 hard problems (-25 [-49, -1]), mostly in competition mathematics. The measurement also yields a cheap commit signal for adaptive sampling that matched two-sample escalation within +/-1 point at 0.67x its tokens in a pre-registered test. Results on Qwen3.5-4B, on which the recipe was developed, and a replication on Olmo-3-7B-Think suggest that the saving depends on how verbose the base model is.\n\n======== 2611.00412 On the Framing Effect of AI Red-Teaming Instructions: Evidence from Prior Exercises and Controlled Simulations\narXiv:2611.00412v1 Announce Type: cross  Abstract: AI red-teaming, adversarially probing generative AI systems to surface harms, has become a central evaluation method. However, prior work has highlighted that red-teaming is a fairly open-ended task, laden with myriad design choices that can shape its findings. In this work, we focus on the instructions used to conduct red-teaming exercises and hypothesize that they can significantly affect outcomes in a manner analogous to the framing effect in psychology, where the format in which information is presented greatly impacts how people respond. To understand whether and why instructions impact re
… [10069 more characters in events.jsonl]

{
  "query": "China CAC artificial intelligence rules November 2026 announcement",
  "mode": "extended"
}

{
  "query": "China CAC artificial intelligence rules November 2026 announcement",
  "results": [
    {
      "tool_use_id": "srvtoolu_01FphK3AEiU7z4Gm4y9j5nY8",
      "content": [
        {
          "title": "China’s AI Governance Push and the Race to Shape Global AI Rules",
          "url": "https://thediplomat.com/2026/10/chinas-ai-governance-push-and-the-race-to-shape-global-ai-rules/"
        },
        {
          "title": "Cyberspace Administration's domestic generative AI services filing list - Digital Policy Alert",
          "url": "https://digitalpolicyalert.org/change/12565-chinese-cyberspace-administration-registration-of-generative-ai-services"
        },
        {
          "title": "China Proposes Export Controls for Large AI Models - DEV Community",
          "url": "https://dev.to/neticslabs/china-proposes-export-controls-for-large-ai-models-5da9"
        },
        {
          "title": "China AI Export Rule Takes Effect Today: 40 Techs [2026]",
          "url": "https://tech-insider.org/china-ai-export-rule-takes-effect-40-techs-2026/"
        },
        {
          "title": "China Proposes AI Export Curbs on 23 Technologies [2026]",
          "url": "https://tech-insider.org/china-ai-export-curbs-23-technologies-2026/"
        },
        {
          "title": "China AI Governance Framework 2026",
          "url": "https://gaeedu.org/ai-governance-profiles/china"
        },
        {
          "title": "China Moves to Extend AI Safety Rules Across the Full Lifecycle",
          "url": "https://www.tokenpost.com/news/regulation/47487"
        },
        {
          "title": "China to Introduce AI Full-Lifecycle Safety Regulation Standards",
          "url": "https://www.kucoin.com/news/flash/china-to-introduce-ai-full-lifecycle-safety-regulation-standards"
        },
        {
          "title": "China AI Regulations 2026: Rules Companies Must Follow",
          "url": "https://www.pertamapartners.com/insights/china-ai-regulations"
        }
      ]
    },
    "I found no CAC announcement dated November 2026 in these results. The closest items are:\n\n- **AI lifecycle legislation (Nov 3):** On November 3, Wang Ruomeng of the National Development and Reform Commission said China is accelerating AI legislation to encompass data and computing power. This comes from the NDRC, not the CAC, and I found no draft text or date yet.\n- **Social-impact standard:** The recommended national standard's scheduled implementation date is 1 November 2026; it remains a technical standard rather than a standalone binding rule. This is GB/T 47863-2026 on generative-AI social-impact assessment.\n- **Export controls on AI models:** The two ministries published the draft on Friday 16 October 2026 as a proposed adjustment to the catalogue of technologies whose export is banned or restricted. The public consultation period runs through November 15, 2026, after which China's Ministry of Commerce and Ministry of Science and Technology are expected to review feedback before finalizing the catalogue. The issuing bodies are MOFCOM and MOST, not the CAC.\n- **Earlier CAC action:** On July 15, the Cyberspace Administration of China (CAC), China's top internet regulator, brought its Interim Measures for the Administration of Anthropomorphic AI Interaction Services into effect.\n\nSources are thin, and the export-catalogue details come from secondary outlets, so check the official CAC and MOFCOM websites before relying on any of this."
  ],
  "durationSeconds": 6.928258010999998,
  "searchCount": 1
}

{
  "url": "https://thenextweb.com/news/nyt-newspapers-sue-brave-ai-scraping",
  "prompt": "Date, filing details, court, numbers alleged (pages indexed, words reproduced), named AI companies."
}

{
  "bytes": 185315,
  "code": 200,
  "codeText": "OK",
  "result": "**Filing details**\n- **Date:** The New York Times sued Brave Software on Monday, November 2, 2026. The New York Daily News, Chicago Tribune, and Orlando Sentinel publishers filed a separate suit hours later.\n- **Court:** Both cases were filed in federal court in Manhattan. The article does not give docket numbers.\n- **Plaintiffs:** The New York Times; the Alden-owned papers, through MediaNews Group and Tribune Publishing.\n- **Claims:** The three newspapers allege direct, contributory, and vicarious copyright infringement, DMCA circumvention, and unjust enrichment under New York law. The Times filed its own copyright and DMCA claims.\n- **Relief sought:** Statutory and actual damages, repayment of profits, and a permanent injunction. A jury trial has been requested.\n\n**Numbers alleged**\n- The Brave Index contains more than 30 billion web pages.\n- More than two million registered articles are affected, according to the Alden-owned papers.\n- A cited study found AI crawlers generate 95.7% less referral traffic than traditional Google search.\n- Brave reported over $100m in 2025 revenue and about 130 million monthly users.\n- The article does not give figures for pages indexed or words reproduced in the complaints.\n\n**Named AI companies**\nAnthropic, Perplexity, Mistral, xAI, and Cohere are the five Search API customers both complaints identify.",
  "durationMs": 8077,
  "url": "https://thenextweb.com/news/nyt-newspapers-sue-brave-ai-scraping"
}

{
  "query": "UK DSIT AI announcement November 2 2026",
  "mode": "extended"
}

{
  "query": "UK DSIT AI announcement November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Ws5bkS2NAm8gyRj4CYhvmx",
      "content": [
        {
          "title": "New package puts AI at the heart of “national renewal”",
          "url": "https://www.techuk.org/resource/new-package-puts-ai-at-the-heart-of-national-renewal-package.html"
        },
        {
          "title": "commonslibrary.parliament.uk Research Briefing 14 October 2026",
          "url": "https://researchbriefings.files.parliament.uk/documents/CBP-10003/CBP-10003.pdf"
        },
        {
          "title": "AI Security Institute",
          "url": "https://en.wikipedia.org/wiki/AI_Security_Institute"
        },
        {
          "title": "AI Safety Summit 2023",
          "url": "https://en.wikipedia.org/wiki/AI_Safety_Summit_2023"
        },
        {
          "title": "UK AI Regulation 2026: SI 2026/425 & ICO Code",
          "url": "https://vorplabs.com/ai-regulatory-updates/united-kingdom"
        },
        {
          "title": "AI Opportunities Action Plan Government Response CP 1242",
          "url": "https://assets.publishing.service.gov.uk/media/678639913a9388161c5d2376/ai_opportunities_action_plan_government_repsonse.pdf"
        },
        {
          "title": "AI gains Cabinet seat: UK government abolishes DSIT",
          "url": "https://www.fuseenergy.com/news/artificial-intelligence"
        },
        {
          "title": "Department for Science, Innovation and Technology (DSIT)",
          "url": "https://strategygov.uk/wiki/entities/dsit"
        },
        {
          "title": "DSIT scrapped and AI gains top-table seat as Burnham premiership kicks off",
          "url": "https://www.globalgovernmentfinance.com/andy-burnham-pm-dsit-scrapped-ai-minister/"
        }
      ]
    },
    "I couldn't find any DSIT AI announcement dated November 2, 2026. The results are also inconsistent about whether DSIT still exists.\n\n- **Possible DSIT abolition:** One report says the Department for Science, Innovation & Technology (DSIT) has been scrapped under a new Burnham premiership, with AI responsibilities shifting to the Cabinet Office. Another says DSIT merged into BIST in July 2026. These sources are not dated to November 2 and are not from official government channels, so I'd treat them as unconfirmed.\n- **Recent DSIT activity:** A Commons Library briefing dated 14 October 2026 mentions that an AI Economics Institute was established within DSIT in June 2026. A separate tracker notes that DSIT call for evidence on data regulation and AI closed, and the ICO's agentic AI call for evidence responses are due by the end of November 20, 2026.\n- **Older package, not a November 2026 one:** A techUK item on a DSIT \"National Renewal Package for AI\" appears to be from about a year ago, despite mentioning a 3rd November 2026 event. It includes up to £250mn to ensure British researchers and startups access to free compute.\n\nNext step: check gov.uk's DSIT or Cabinet Office news pages directly for any November 2, 2026 release, since the search index doesn't appear to have one."
  ],
  "durationSeconds": 6.766045738000015,
  "searchCount": 1
}

{
  "command": "echo \"=== TOKEN THIEVES ===\" && node scripts/fetch.js \"https://www.theregister.com/security/2026/11/02/token_thieves_costing_companies_100K_per_day_in_illicit_LLM_charges/5306967\" 2>&1 | head -5; node scripts/fetch.js \"https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967\" 2>&1 | head -80",
  "description": "Fetch Register LLMjacking article"
}

{
  "stdout": "=== TOKEN THIEVES ===\nHTTP 200 · https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967 · text/html\nToken thieves costing companies $100K+ per day in illicit LLM charges\n\nJump to main content\n\nHTTP 403 · https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967 ·",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.nih.gov/news-events/news-releases",
  "prompt": "List news releases dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 375,
  "url": "https://www.nih.gov/news-events/news-releases"
}

{
  "command": "node scripts/fetch.js \"https://www.theregister.com/security/2026/11/02/token_thieves_costing_companies_100K_per_day_in_illicit_LLM_charges/5306967\" 2>&1 | head -120",
  "description": "Fetch Register LLMjacking article full"
}

{
  "stdout": "HTTP 200 · https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967 · text/html\nToken thieves costing companies $100K+ per day in illicit LLM charges\n\nJump to main content\n\nREG AD\n\nsecurity\n\n#\nToken thieves costing companies $100K+ per day in illicit LLM charges\n\nDon't let the LLMjackers hit you\n\nJessica Lyons\n\nJessica\nLyons\n\nCybersecurity Editor\n\nPublished\nmon 2 Nov 2026 // 16:00 UTC\n\nMake us preferred on Google\n\n# READ MORE\n\n-\n\n# Forget retraining - AI can now tweak another AI's weights\n\n2 hours ago\n\n-\n\n# Open models can do 90% of agentic work at a twentieth of the cost of a frontier LLM: Gartner\n\n4 hours ago\n\n-\n\n# Toyota shows off SoC that stores model weights and its OS on integrated memory\n\n7 hours ago\n\n-\n\n# Anthropic's compute tab could top $1T as Q3 revenue nears $17B\n\n11 hours ago\n\n-\n\n# AI could break legal systems by finding previously hidden loopholes\n\n13 hours ago\n\nVictim organizations are losing millions of dollars in token charges as criminals hijack their corporate LLM access to steal expensive computing resources and AI services.\nThese fraudulent charges from resource consumption can exceed $100,000 a day, according to a Monday report by Google's Mandiant incident responders, who saw cumulative charges at some organizations hit $1 million before the victim companies revoked intruders' access.\n\"Whenever possible, threat actors want to use this technology to gain a scale advantage over defenders. They achieve that with agentic tools and by stealing tokens from unwitting third parties,” John Hultquist, chief analyst at Google Threat Intelligence Group, told The Register . “Locking down these resources will not only protect organizations from runaway costs, but also protect the broader community from a deluge of cheap, autonomous attacks.”\n\nREG AD\n\nThis tactic of hijacking access to LLMs is called LLMJacking , and it’s been increasing steadily over the past two years. In one extreme case, documented in an August report from CrowdStrike, a token thief sent about 200,000 API requests in just two minutes.\n\nREG AD\n\nIn one case detailed in the report, a group Google tracks as UNC6993 illicitly gained access to LLM API keys, then generated additional keys and enabled services within the victim’s cloud projects, racking up $100,000 in charges.\nThe threat intel biz also documented a different token thief subscribing victim accounts to Pay-As-You-Go agreements to access advanced models on the victim company’s dime. The crook selected premium foundation models, launched high-volume inference streams, and used a “burn and rotate strategy” to bypass rate limits by creating and deleting short-lived service accounts while auditing the billing interface to monitor financial impact.\nIn yet another incident, an intruder executed more than 500,000 LLM API calls in less than eight hours using stolen third-party API keys to power a token routing service called Jet Night, according to a Monday report from Google.\n“Given Jet Night’s per-token costs to users are so far below typical market rates GTIG believes the service relies on stolen keys to operate profitably,” the report says. “For example, Jet Night offers an unlimited token plan for approximately $60 USD per month with alleged access to frontier models, a consumer service level that would typically run between $100 and $250 per month.”\nJet Night has also admitted to multiple outages on its public Telegram channel, which the Google threat hunters note is “likely due to stolen keys being revoked as victims discover their respective compromises.”\n\n# Specialized LLMjacking roles\nAs more criminals join the LLMJacking ecosystem, Google says it has documented a division of labor between the criminals that establish initial access to compromised cloud and AI services, and those that manage downstream monetization infrastructure, called “LLM Mixers.”\nIn one case that Mandiant responded to in mid-2026, UNC6993 compromised a cloud instance through a misconfigured Service Account key and used this access to grant further access to a model API.\n\nREG AD\n\nThe crooks also spun up a session hijacking page purporting to be an application portal to join a group of LLM users. “This page tricks users into navigating to the legitimate LLM service website, and pasting their raw JSON payload containing an active access token, which was then posted to the backend API to bypass password and multifactor authentication (MFA) controls,” the report says.\nGoogle predicts miscreants will “increasingly prioritize LLMJacking” compared to other types of resource theft like cryptojacking. And to prevent cloud LLM service abuse, the security firm says defenders should prioritize identity and access management plus supply chain security, and use a centralized secrets management platform to rotate keys and secrets.\nAlso apply least-access privileges to users and service accounts, ensuring that they only have permissions necessary to complete their roles and tasks. And automate secrets scanning within codebases to identify and then remove any API keys and secrets added to source code. ®\n\nai and ml\nsecurity\n\nMake us preferred on Google\n\nREG AD\n\n# Broadcom denied names of cloud providers backing VMware merger challenge\n\nEU court's confidentiality ruling clears a procedural hurdle, not the merits of CISPE's case against Commission approval\n\n# Raspberry Pi hikes prices again, barely a month after the last round\n\nMemory crunch pushes 16GB Pi 5 to $385, more than triple its launch price, just a month after the last round of hikes\n\n# From expertise to intelligence: NISCO deploys world's first swarm-intelligence steel model at scale\n\nPARTNER CONTENT: 300+ AI applications delivering surges in core metrics and annual cost reduction of over CNY100m\n\nEVENT\n\n# Everyone has the file. Nobody has the right versi
… [519 more characters in events.jsonl]

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && cat > au.py <<'EOF'\nimport sys,glob,xml.etree.ElementTree as ET\nwant=sys.argv[1:]\nd={}\nfor f in glob.glob('cs.*.xml'):\n    for it in ET.parse(f).getroot().iter('item'):\n        aid=it.findtext('link','').split('/abs/')[-1]\n        if aid in want and aid not in d:\n            cr=[e.text for e in it if e.tag.endswith('creator')]\n            d[aid]=(it.findtext('title','')[:60],' | '.join(cr))\nfor w in want:\n    t,c=d.get(w,('?','?'))\n    print(w,'::',t,'::',c)\nEOF\npython3 -I au.py 2611.00407 2611.00640 2611.00606 2611.00602 2611.00350 2611.03244 2611.01564 2611.02270 2611.00412 2611.00508 2611.00460 2611.00138 2611.00725 2611.00505 2611.02348 2611.00420 2611.00465 2611.02278 2611.00247 2611.00386 2611.00555 2611.03494 2611.00464",
  "description": "Extract author lists for shortlist"
}

{
  "stdout": "2611.00407 :: Hacking or Just Failing? A More Capable LLM Monitor Better S :: Kaushik Kezendirane\n2611.00640 :: Bridging Singular Learning Theory and Mechanistic Interpreta :: Ethan Ji, Wei Wang, Yizhou Sun\n2611.00606 :: Sparse Autoencoder Attribution Graphs Are Decided at the Mar :: Karl Li\n2611.00602 :: Editing the Goal: Per-Token SAE Steering and Its Depth Limit :: Rocio Perales Valdes, Animesh Garg\n2611.00350 :: On the Limits of Test-Time Compute for Self-Evaluation :: Anirudh Buvanesh, Khaled Rouissi, Sujin Yun, Johan Obando-Ceron, Morgane M Moss, Samuel Lavoie, Michael Noukhovitch, Laurent Charlin, Aaron Courville\n2611.03244 :: Forecasting How RLHF Responds to Reward-Model Edits Before T :: Zixiao Wang, Duzhen Zhang, Xingbo Du, Dongxia Wu, Le Song\n2611.01564 :: Meta-memorization and memorization scaling laws in transform :: Alex Nguyen, Kenneth A. Norman, Gautam Reddy\n2611.02270 :: Hinted Scaling Laws :: Suze van Adrichem, Luke Bailey, Rohith Kuditipudi, Christine Ye, Neil Band, Ahmed Ahmed, John Duchi, Percy Liang, Tatsunori Hashimoto\n2611.00412 :: On the Framing Effect of AI Red-Teaming Instructions: Eviden :: Michael Feffer, Alice Qian, Anusha Sinha, Muye Zhang, Shalini Ghosh, Rachel Phinnemore, Bart Stawicki, Hong Shen, Hoda Heidari\n2611.00508 :: Do Social Influence Pressures Move LLM Agents? Evidence from :: Richard Zhe Wang\n2611.00460 :: From Small to Large: Assessing Medical Reasoning, Benchmark  :: Navapat Nananukul, Mayank Kejriwal\n2611.00138 :: Kerkoporta: Injecting Structured-Output Backdoors in Reasoni :: Georgios Syros, Blake Bullwinkel, Alina Oprea, Cristina Nita-Rotaru, Amanda Minnich, Xiaodong Liu, Giorgio Severi\n2611.00725 :: The Long Con on the Web: Earn-then-Exploit Fraud Attacks aga :: Xingling Xu, Zhengwei Jiang, Zheng Zhi, Fangming Dong, LingJia Guo, Wei Dong, Chunyan Ma, Jun Jiang\n2611.00505 :: To Jev or Not to Jev: When Can System-1 Decision Models Repl :: Shreyas Subramanian\n2611.02348 :: Which Words a Model Fears: From a Refusal Direction to a Voc :: Boyuan Zhang, Mohammad Zandsalimy, Shanu Sushmita\n2611.00420 :: Circuit Oracle: Automating Attribution Graph Analysis via Na :: Shariar Kabir, Hong Kiat Tan, Swastik Agrawal, Sai V R Chereddy, Sriram Balasubramanian\n2611.00465 :: The Promises and Limitations of Evaluation-Based AI Governan :: Lily Stelling, Jacob Charnock, Kevin L. Wei, David Krueger\n2611.02278 :: Concise-9B: Removing the Slack from a Reasoning Model's Thin :: Alexander Boesgaard Lorup\n2611.00247 :: Taurus: LLM-in-the-Loop CT Annotation Matches Coding Agents  :: Bing Hu, Rishabh Sharma, Jatin Mehta\n2611.00386 :: Dependence-Aware Risk Assessment and Optimal Design of AI-Ag :: Yijia Li, Maochao Xu, Peng Zhao\n2611.00555 :: Distinguishing among reasoning levels of GPT 5.5 Pro via a g :: Emma Graham, Richard Granger\n2611.03494 :: Harder Than the Task: From Technical to Organizational Diffi :: Victor Barres, Aden Barton, Nicolai J. Foss, Henrik M. Nielsen\n2611.00464 :: Compression Technique Interactions in Small Language Models: :: Bhushit Nema, Siddharth Krishnamurthy, Anjali Kadiyala",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.who.int/news",
  "prompt": "List news items dated 2 or 3 November 2026 with titles and URLs."
}

{
  "bytes": 220010,
  "code": 200,
  "codeText": "OK",
  "result": "Only one item on the page is dated 2 or 3 November 2026:\n\n- **\"Establishing and operating cancer registries: Resource-adapted guidelines for the context of WHO South-East...\"** (2 November 2026)\n  https://www.who.int/publications/i/item/9789292800321\n\nThe page truncates the title. No items dated 3 November 2026 appear.",
  "durationMs": 3711,
  "url": "https://www.who.int/news"
}

{
  "url": "https://www.ftc.gov/news-events/news/press-releases",
  "prompt": "List press releases dated November 2 or 3, 2026, with title, date and URL."
}

{
  "bytes": 1038970,
  "code": 200,
  "codeText": "OK",
  "result": "Only one press release in the content is dated November 2 or 3, 2026:\n\n- **\"FTC, Washington Take Action Against Payment Processor for Deceiving Small Businesses About Costs and Cancellation Terms\"**\n  - Date: November 2, 2026\n  - URL: ftc.gov/news-events/news/press-releases/2026/11/ftc-washington-take-action-against-payment-processor-deceiving-small-businesses-about-costs\n\nThe listing is sorted newest first, and the next entry is dated October 29, 2026, so no November 3 releases appear on this page.",
  "durationMs": 5098,
  "url": "https://www.ftc.gov/news-events/news/press-releases"
}

{
  "url": "https://www.gov.uk/search/news-and-communications?keywords=artificial%20intelligence&order=updated-newest",
  "prompt": "List UK government news items dated 2 or 3 November 2026 mentioning AI, with department, title and URL."
}

{
  "bytes": 449354,
  "code": 200,
  "codeText": "OK",
  "result": "One item matches: a 3 November 2026 news story that mentions AI.\n\n- **Title:** \"Care workers, women returning to employment and builders to gain practical AI skills\"\n- **Department:** Not shown in the page content\n- **URL:** /government/news/care-workers-women-returning-to-employment-and-builders-to-gain-practical-ai-skills\n\nThe page describes four Barnsley training projects that \"will share over £800,000 to bring practical artificial intelligence skills into everyday workplaces.\"\n\nThe other 2 and 3 November items shown don't mention AI in their visible summaries. The page shows only the first page of results, so later items aren't included here.",
  "durationMs": 6180,
  "url": "https://www.gov.uk/search/news-and-communications?keywords=artificial%20intelligence&order=updated-newest"
}

{
  "url": "https://www.techmeme.com/",
  "prompt": "Give exact full hyperlink URLs plus publisher and any time shown for stories about: Brookfield/Drax/Radiant AI data centre; Oracle raising $20B; Palantir earnings; OpenAI Grid Protectors Program; OpenAI bug bounty; Anthropic Claude Code game cloning; UK NCSC AI cyber warning by 2028; Huawei AI chip memory; Google data center satellite; Salesforce Cresta; Tutor Intelligence; MIT GPT-6 Astra weight editing.",
  "offset": 100000
}

{
  "bytes": 402122,
  "code": 200,
  "codeText": "OK",
  "result": "**Note:** The provided content is truncated, so I couldn't find Google's data center satellite story, the Salesforce/Cresta story, or the MIT GPT-6 Astra weight-editing story. Times are the relative stamps shown on the Techmeme page. Where none is shown, I say so.\n\n**Brookfield/Drax/Radiant AI data centre**\n- CNBC (Kai Nicol-Schwarz): https://www.cnbc.com/2026/11/03/brookfield-ai-data-center-yorkshire-drax.html. Shown as 55 minutes ago.\n- DatacenterDynamics (Zachary Skidmore): https://www.datacenterdynamics.com/en/news/drax-partners-with-brookfield-and-radiant-for-up-to-1gw-data-center-at-north-yorkshire-power-station/. No time shown.\n- Reuters (Yadarisa Shabong): https://www.reuters.com/business/uks-drax-signs-data-centre-deal-with-brookfield-radiant-2026-11-03/. No time shown.\n- Bloomberg (Eamon Farhat): https://www.bloomberg.com/news/articles/2026-11-03/brookfield-qai-to-invest-2-5-billion-in-data-center-for-drax. No time shown.\n\n**Oracle raising $20B**\n- Wall Street Journal (Kelly Cloonan): https://www.wsj.com/finance/oracle-looks-to-raise-20-billion-to-fund-ai-ambitions-582c814f?st=19tHqn&reflink=desktopwebshare_permalink. No time shown.\n- CNBC (Michelle Fox): https://www.cnbc.com/2026/11/02/oracle-files-to-sell-20-billion-in-new-stock-bonds-to-finance-ai-buildout.html. No time shown.\n- The Information (Alex Eichenstein): https://www.theinformation.com/briefings/oracle-launches-20-billion-stock-bond-sales. No time shown.\n\n**Palantir earnings**\n- CNBC (Samantha Subin): https://www.cnbc.com/2026/11/02/palantir-pltr-earnings-q3-2026.html. No time shown; the story says results came out after the bell on Monday, November 2.\n- Fortune (Amanda Gerut): https://fortune.com/2026/11/02/palantir-q3-results-stock-ai-trade-selloff/. No time shown.\n- Wall Street Journal: https://www.wsj.com/business/earnings/palantir-lifts-outlook-as-u-s-commercial-business-overtakes-government-business-16eb693f. No time shown.\n\n**OpenAI Grid Protectors Program**\n- OpenAI: https://openai.com/index/grid-protectors-program. No time shown.\n- The Verge (Emma Roth): https://www.theverge.com/ai-artificial-intelligence/1024604/openai-data-center-grid-protection-program. No time shown.\n- New York Post (Emily Lang): https://nypost.com/2026/11/02/business/openai-plans-to-use-less-electricity-when-grid-is-strained-at-this-new-facility/. No time shown.\n\n**OpenAI bug bounty**\n- OpenAI (Cathedral security partnership): https://openai.com/index/preparing-our-next-security-sprint-to-harden-openai. Shown as 4 hours ago.\n- OpenAI (bigger bug bounties): https://openai.com/index/rewarding-defenders-with-bigger-bug-bounties. No time shown.\n- Help Net Security (Anamarija Pogorelec): https://www.helpnetsecurity.com/2026/11/03/openai-bigger-bug-bounty-rewards/. No time shown.\n- Blockchain.News (Luisa Crawford): https://blockchain.news/news/openai-raises-bug-bounty-rewards-for-security-researchers. No time shown.\n- Cyber Security News (Guru Baran): https://cybersecuritynews.com/openai-security-sprint/. No time shown.\n\n**Anthropic Claude Code game cloning**\n- Tom's Hardware (Bruno Ferreira): https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks. No time shown.\n- Ars Technica (Kyle Orland): https://arstechnica.com/ai/2026/11/claudes-new-rules-against-game-cloning-wont-stop-the-ai-copying-boom/. No time shown.\n- The Verge (Jay Peters): https://www.theverge.com/ai-artificial-intelligence/1024632/anthropic-claude-ai-video-game-clones. No time shown.\n- IGN (Michael Cripe): https://www.ign.com/articles/anthropic-blocks-ai-game-clones-in-claude-opus-update. No time shown.\n- Mashable (Phil Clark): https://mashable.com/tech/anthropic-takes-steps-to-block-video-game-cloning-and-reverse-engineering. No time shown.\n\n**UK NCSC AI cyber warning by 2028**\n- Financial Times (Tom Wilson): https://www.ft.com/content/131d9506-04b1-49b8-ba79-b0d783219c40. Marked as new.\n- The Guardian (Dan Milmo): https://www.theguardian.com/technology/2026/nov/03/ai-powered-malware-artificial-intelligence-hacking-critical-uk-infrastructure. No time shown.\n- The Record (Alexander Martin): https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months. No time shown.\n- Cointelegraph (Felix Ng): https://cointelegraph.com/news/uk-warns-ai-ransomware-attack-on-infrastructure-highly-likely-by-2028. No time shown.\n- SecurityWeek: https://www.securityweek.com/uk-cyber-chief-says-the-uk-will-face-ai-cyberattacks-on-critical-infrastructure-by-2028/. No time shown.\n\n**Huawei AI chip memory**\n- The Information: https://www.theinformation.com/articles/smugglers-get-expensive-memory-chips-china-south-korea. Reports Huawei's Ascend 960DT will run largely on Samsung and SK Hynix HBM. No time shown.\n- Wccftech (Omar Sohail): https://wccftech.com/smugglers-hbm-throwaway-server-chips-us-export-controls-loophole-china-south-korea/. No time shown.\n\n**Tutor Intelligence**\n- Forbes (John Werner): https://www.forbes.com/sites/johnwerner/2026/11/02/tutor-intelligence-why-not-just-teach-the-robots-ourselves/. No time shown; the URL dates it November 2, 2026.\n- SiliconANGLE (Maria Deutscher): https://siliconangle.com/2026/11/02/robotics-startup-tutor-intelligence-nabs-75m-investment/. No time shown.\n- a16z (Raghu Raghuram): https://www.a16z.news/p/investing-in-tutor-intelligence. No time shown.\n- Business Wire: https://www.businesswire.com/news/home/20261102314852/en/. No time shown.\n\n[WebFetch note: this page's text is 243785 characters long and the answer above covers only characters 100000 to 200000; the final 43785 were not read — to read on, call WebFetch again with the same url and offset: 200000.]",
  "durationMs": 19538,
  "url": "https://www.techmeme.com/"
}

{
  "command": "node scripts/fetch.js \"https://www.theregister.com/security/2026/11/02/thieves_pilfer_environment_variables_from_Trigger_AI_workflow_tool/5306998\" 2>&1 | head -70",
  "description": "Fetch Register Trigger AI article"
}

{
  "stdout": "HTTP 200 · https://www.theregister.com/security/2026/11/02/thieves-pilfer-environment-variables-from-trigger-ai-workflow-tool/5306998 · text/html\nThieves pilfer environment variables from Trigger AI workflow tool\n\nJump to main content\n\nREG AD\n\nsecurity\n\n#\nThieves pilfer environment variables from Trigger AI workflow tool\n\nSo, who's ready to clear the dust out of that server closet and move things back on-prem?\n\nBrandon Vigliarolo\n\nBrandon\nVigliarolo\n\nGOVERNMENT AND IT NEWS REPORTER\n\nPublished\nmon 2 Nov 2026 // 16:44 UTC\n\nMake us preferred on Google\n\n# READ MORE\n\n-\n\n# Forget retraining - AI can now tweak another AI's weights\n\n2 hours ago\n\n-\n\n# Open models can do 90% of agentic work at a twentieth of the cost of a frontier LLM: Gartner\n\n4 hours ago\n\n-\n\n# Toyota shows off SoC that stores model weights and its OS on integrated memory\n\n7 hours ago\n\n-\n\n# Anthropic's compute tab could top $1T as Q3 revenue nears $17B\n\n11 hours ago\n\n-\n\n# AI could break legal systems by finding previously hidden loopholes\n\n13 hours ago\n\nIf you're a customer of cloud-hosted AI workflow platform Trigger.dev, take heed, because your environment variables may have been exposed in a security incident disclosed on Sunday.\nTrigger offered little explanation in its Sunday security incident report , noting that its investigation had identified “exposure across a subset of organizations” and that an attacker had gained unauthorized access to environment variables belonging to those organizations.\nWhatever exploit was used to gain access has been blocked, the company added, and affected customers have been notified of steps they need to take to prevent further security problems.\n\nREG AD\n\nWe likely don't have to tell The Reg readers how important environment variables are in SaaS and cloud services like Trigger. If compromised environment variables contain sensitive credentials, an attacker could basically end up with the keys to the kingdom, potentially gaining access to connected services and digital infrastructure.\n\nREG AD\n\nFor those unfamiliar with Trigger.dev, it’s a platform for building AI agents and workflows in TypeScript, but here’s the kicker: Trigger advertises itself as a durable execution platform that handles pesky things like retries, scaling, and keeping long-running tasks going through crashes and redeployments, while providing tools to monitor what those tasks are doing.\nTrigger, the company’s site notes, can be used to “build durable AI agents that survive refreshes, redeploys, and crashes,” and is ideal for “long-running tasks with retries, queues, AI observability and elastic scaling.”",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.thelancet.com/journals/landig/home",
  "prompt": "List articles published 2 or 3 November 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 568,
  "url": "https://www.thelancet.com/journals/landig/home"
}

{
  "url": "https://endpts.com/",
  "prompt": "List articles dated November 2 or 3, 2026 that involve AI, with titles and URLs."
}

{
  "bytes": 534,
  "code": 301,
  "codeText": "Moved Permanently",
  "result": "REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.\n\n    Original URL: https://endpts.com/\n    Redirect URL (from the server's Location header — server-supplied, not verified): https://endpoints.news/\n    Status: 301 Moved Permanently\n\n    To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:\n    - url: \"https://endpoints.news/\"\n    - prompt: \"List articles dated November 2 or 3, 2026 that involve AI, with titles and URLs.\"",
  "durationMs": 319,
  "url": "https://endpts.com/"
}

{
  "url": "https://www.fiercebiotech.com/ai-and-machine-learning",
  "prompt": "List articles dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 472,
  "url": "https://www.fiercebiotech.com/ai-and-machine-learning"
}

{
  "command": "echo \"=== DCD DRAX ===\"; node scripts/fetch.js \"https://www.datacenterdynamics.com/en/news/drax-partners-with-brookfield-and-radiant-for-up-to-1gw-data-center-at-north-yorkshire-power-station/\" 2>&1 | head -60; echo; echo \"=== CNBC BROOKFIELD ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/03/brookfield-ai-data-center-yorkshire-drax.html\" 2>&1 | head -60",
  "description": "Fetch DCD and CNBC Drax/Brookfield articles"
}

{"stdout":"=== DCD DRAX ===\nHTTP 200 · https://www.datacenterdynamics.com/en/news/drax-partners-with-brookfield-and-radiant-for-up-to-1gw-data-center-at-north-yorkshire-power-station/ · text/html\nDrax partners with Brookfield and Radiant for up to 1GW data center at North Yorkshire power station - DCD\n\n-\nHome\n\n- News\n\n-\nThe Data Center Construction Channel\n\n# Drax partners with Brookfield and Radiant for up to 1GW data center at North Yorkshire power station\n\nFirst phase targeting 100MW of capacity by 2028\n\nNovember 03, 2026\n\nBy\n\nZachary Skidmore\n\nHave your say\n\nUK power company Drax has finally unveiled its plans for a data center at its 2.6GW Drax Power Station in Selby, North Yorkshire, UK.\nThe company partnered with Brookfield and its UK-headquartered AI infrastructure platform, Radiant, to jointly develop, deliver, and operate up to a gigawatt of data center capacity at the power station.\n\nDrax Power Station in Selby\n\n– Drax\n\nThe data center is expected to be built in phases, with phase one targeting up to 100MW and expected to be operational from Q1 2028. Phase two would increase the capacity to 500MW between 2028 and 2031, and phase three envisions additional capacity increases post-2031.\nThe project will be developed as part of a joint venture dubbed Brookfield-Qai AI. Brookfield has said it estimates total investment in the development could exceed £20 billion ($26.8bn), including an initial £2.5bn ($3.4bn) for the first phase.\nThe partners said the first phase will progress subject to “the timely progression of the necessary planning, as well as receiving the required regulatory and network approvals from government and the system operator, in addition to securing a suitable tenant for the project.”\nThe proposed site comprises 1,000 acres and 4GW of grid access, with 2.6GW of active dispatchable generation and cooling systems from the existing wood pellet plant.\nAccording to Drax Group CEO Will Gardiner, the site is “one of the few UK sites that can provide large-scale reliable power directly to data center customers by utilizing existing and underutilized generation capacity.”\n“If constructed in full, this project could become one of the largest data centers in the UK, attracting billions in inward investment, supporting the North’s reindustrialization and strengthening sovereign AI capability,” he added.\n“Teaming up with Drax and Qai for this project represents a major opportunity for our AI infrastructure strategy,” said Brookfield Head of AI infrastructure, Sikander Rashid.\n\"Our capital and deep operating capabilities will help accelerate the construction of a critical piece of sovereign AI, delivered by Radiant, our UK-headquartered compute infrastructure platform. In addition to preserving hundreds of jobs, this project will also create many direct and indirect jobs around the broader Yorkshire area.\"\nThe announcement follows shortly after the UK government rejected a bid by North Yorkshire Council, the University of York, and energy company Drax to develop an up to 1.2GW data center at the same site as part of the UK’s AI Growth Zone scheme.\nRumblings that Drax was planning a data center first arose in November 2024. Following this, in February of last year, it was reported that it was in discussions with data center operators about a potential supply agreement, noting that it had received “positive engagement with data center providers regarding the potential to co-locate a data center with biomass generation.”\nSince then, the company signed a ten-year corporate Power Purchase Agreement with Global Switch to support the firm's UK operations.\nHowever, concerns have been raised about the proposed data center's low-carbon credentials. As part of the application for the AI Growth zone data center, the applicants described the facility as the world's largest “carbon negative data center,” even though the power plant itself is one of the UK's largest emitters.\nAccording to data from energy think tank Ember , Drax emitted 14.1 million tonnes of CO 2 equivalent in 2025.\nDespite pushback, Drax and Brookfield have said they are committed to delivering lasting local benefits, including a voluntary community benefits fund developed in consultation with communities around the Drax Power Station site, separate from and in addition to any planning obligations and Drax’s existing community initiatives. The company said that community consultation on the plans will begin shortly, with the formal planning process following afterward.\nRadiant was launched last November as part of the $10bn Brookfield Artificial Intelligence Infrastructure Fund (BAIIF), with plans to build and acquire as much as $100bn worth of AI infrastructure.\n\n# More in UK & Ireland\n\n-\n\n11 Jun 2026\n\n#\n\nCambridge University launches £36m Zenith supercomputer\n\n-\n\n06 Aug 2026\n\n\n=== CNBC BROOKFIELD ===\nHTTP 200 · https://www.cnbc.com/2026/11/03/brookfield-ai-data-center-yorkshire-drax.html · text/html\nBrookfield plans $27 billion AI data center at power station; Drax rises 8%\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nKey Points\n\n- Brookfield is planning a data center with more than one gigawatt of capacity at a site in England.\n\n- The asset manager estimated that the potential investment for the project could exceed £20 billion ($26.8 billion).\n\n- Drax Group, which operates the power station the facility will be housed at, saw shares rise more than 8% on Tuesday morning.\n\nIn this article\n\n- DRX-GB\n\n- BAM\n\n- GOOGL\n\n- MSFT\n\nFollow your favorite stocks CREATE FREE ACCOUNT\n\nBrookfield is targeting a massive artificial intelligence data center in the north of England, as Europe scrambles to develop infrastructure to support the rollout of AI amid high energy and land costs.\nEnergy company Drax Group said Tuesday it has signed an agreement with Brookf
… [10069 more characters in events.jsonl]

{
  "url": "https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-threat-actors-monetize-compromised-ai-resources",
  "prompt": "Publication date, UNC6993, Jet Night, all figures ($100,000/day, $1 million, 500,000 API calls, LLM Mixers)."
}

{
  "bytes": 191410,
  "code": 200,
  "codeText": "OK",
  "result": "The page you provided is a **404 error page**, not the article. It says the requested URL `/blog/topics/threat-intelligence/llmjacking-threat-actors-monetize-compromised-ai-resources` was not found, and it contains no article text.\n\nThe only other content is a line of terms: \"Publication date, UNC6993, Jet Night, all figures ($100,000/day, $1 million, 500,000 API calls, LLM Mixers).\" These look like keywords or notes from the original article, not information about it. I can't tell from them what the article reports, and I don't want to guess at its findings.\n\nThe URL slug suggests the article covers **LLMjacking**, a term for attackers who steal credentials for cloud-hosted AI services and run workloads on the victim's account, often for resale or to avoid costs. The article may be available under a different URL or may have been moved or removed.\n\nTo help further, you could:\n- Search the Google Cloud Blog or Google Threat Intelligence site for \"LLMjacking.\"\n- Share the full article text, and I can summarize it or pull out the figures and identifiers you listed.",
  "durationMs": 6007,
  "url": "https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-threat-actors-monetize-compromised-ai-resources"
}

{
  "url": "https://arxiv.org/html/2611.00640v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 1242736,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists three authors: **Ethan Ji**, **Wei Wang**, and **Yizhou Sun**. The affiliations are given as \"Department of Computer Science\" and \"University of California, Los Angeles.\" The page text doesn't say which author belongs to which affiliation, but the author emails all end in @cs.ucla.edu, so the affiliations likely apply to all three.\n\n[WebFetch note: this page's text is 246205 characters long and the answer above covers only characters 0 to 100000; the final 146205 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 3751,
  "url": "https://arxiv.org/html/2611.00640v1"
}

{
  "url": "https://arxiv.org/html/2611.02270v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 383678,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists these authors:\n\n- Suze van Adrichem\\*\n- Luke Bailey\\*\n- Rohith Kuditipudi\\*\n- Christine Ye\n- Neil Band\n- Ahmed Ahmed, John Duchi, Percy Liang, and Tatsunori Hashimoto\n\nThe affiliation line reads: \"Affiliation: Stanford University.\" The text extraction doesn't show which affiliation applies to each author, but the affiliation is listed once for the group. The asterisk (\\*) marks equal contribution, with alphabetical ordering.\n\n[WebFetch note: this page's text is 124183 characters long and the answer above covers only characters 0 to 100000; the final 24183 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4552,
  "url": "https://arxiv.org/html/2611.02270v1"
}

{
  "url": "https://jamanetwork.com/collections/44024/artificial-intelligence",
  "prompt": "List articles dated November 2 or 3, 2026 with titles, journal, and URLs."
}

{
  "bytes": 180418,
  "code": 200,
  "codeText": "OK",
  "result": "Only one article in the provided content is dated November 2 or 3, 2026:\n\n- **Parent Comfort With Artificial Intelligence–Led Behavioral Therapy for Their Child**\n  - Journal: JAMA Pediatrics (Research, November 2, 2026)\n  - URL: https://jamanetwork.com/journals/jamapediatrics/fullarticle/2856091\n\nThe page shows only the first set of results, and the listing runs to 75 pages. Articles on later pages were not included, so there may be additional November 2 or 3 entries.",
  "durationMs": 4682,
  "url": "https://jamanetwork.com/collections/44024/artificial-intelligence"
}

{
  "command": "echo \"=== CNBC PALANTIR ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/02/palantir-pltr-earnings-q3-2026.html\" 2>&1 | head -70; echo; echo \"=== CNBC ORACLE ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/02/oracle-files-to-sell-20-billion-in-new-stock-bonds-to-finance-ai-buildout.html\" 2>&1 | head -50",
  "description": "Fetch CNBC Palantir earnings and Oracle articles"
}

{"stdout":"=== CNBC PALANTIR ===\nHTTP 200 · https://www.cnbc.com/2026/11/02/palantir-pltr-earnings-q3-2026.html · text/html\nPalantir (PLTR) earnings Q3 2026\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nKey Points\n\n- Palantir reported Q3 earnings that topped Wall Street's estimates.\n\n- U.S. commercial revenue more than doubled and surpassed U.S. government revenue for the first time.\n\n- The company has seen a boost from heightened demand for artificial intelligence tools.\n\nIn this article\n\n- PLTR\n\nFollow your favorite stocks CREATE FREE ACCOUNT\n\nwatch now\n\nVIDEO 1:24 01:24\nPalantir beats on earnings and revenue, Q3 commercial revenue surpasses government revenue\nClosing Bell: Overtime\n\nPalantir beat Wall Street's third-quarter estimates after the bell on Monday, with U.S. commercial revenue topping government for the first time as businesses adopt more of the company's artificial intelligence tools.\nShares dipped about 3% in extended trading.\n\nHere's how the company did compared to LSEG estimates:\n\n- Earnings per share : 44 cents adjusted vs. 41 cents expected\n\n- Revenue : $2.31 billion vs. $2.18 billion expected\nRevenue nearly doubled from a year ago and blew past $2 billion for the first time ever, Palantir said. Net income more than doubled to $1.13 billion, or 44 cents per share, from about $476 million, or 18 cents per share.\n\"I don't believe anyone's had consistent results like this in the history of software AI, ever,\" CEO Alex Karp told CNBC's Seema Mody in an interview, adding that the business is succeeding without salespeople.\nPalantir has long been known for its strength in the government sector, but its commercial segment caught up in Q3.\nU.S. commercial revenue jumped 148% to $984 million, surpassing U.S. government revenue of $953 million, which was up 96%. The company's U.S. commercial revenue has more than quintupled over the last two years.\n\nPalantir lifted its guidance, saying it now expects U.S. commercial revenue \"in excess of\" $3.56 billion for the full year. Last quarter, the company boosted its forecast to $3.42 billion. The company projects about $2.65 billion in revenue for the fourth quarter and about $8.53 billion for full-year 2026.\nKarp has openly supported the use of open-weight models and criticized leading AI labs, which he told CNBC earlier this year are forcing businesses to sell their data sovereignty. Karp, on Monday, also reiterated recent calls to nationalize AI labs, calling it the \"only realistic way\" to manage liability.\nIn September, Karp joined major tech CEOs at the White House as calls for regulation mounted following claims from AI researchers that the technology has a more than 10% of killing humanity .\n\"My message to everybody is: Beware of thinking you can delay the future in AI,\" he told CNBC. \"The future is here. The political ramifications of it are here.\"\n\nPalantir stock chart.\n\n# Read more CNBC tech news\n\n- Humans are still doing the work behind some AI agents\n\n- OpenAI pares fundraising goal, now seeking up to $20 billion in latest round\n\n- Binance resumes withdrawals following $6.3 billion hack, says 90% of stolen user assets are covered\n\n- Why AI is boosting Meta’s ad business while hurting Google search\n\nChoose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.\n\n=== CNBC ORACLE ===\nHTTP 200 · https://www.cnbc.com/2026/11/02/oracle-files-to-sell-20-billion-in-new-stock-bonds-to-finance-ai-buildout.html · text/html\nOracle files to sell $20 billion in new stock, bonds to finance AI buildout\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nKey Points\n\n- Oracle filed plans on Monday to issue $10 billion in stock and $10 billion in bonds, it said in a filing.\n\n- The plans were outlined last week at its investor day.\n\nIn this article\n\n- ORCL\n\nFollow your favorite stocks CREATE FREE ACCOUNT\n\nThe Oracle logo is displayed on a building at an Oracle campus in Redwood Shores, California, Sept. 10, 2025.\nJustin Sullivan | Getty Images\n\nOracle filed plans on Monday to issue new stock and more debt to finance its artificial intelligence buildout.\nThe hyperscaler will sell $10 billion in common stock and $10 billion in senior notes, according to filings with the Securities and Exchange Commission. While the fundraising was already outlined at an investor day last week , shares tumbled 8.8% Monday.\n\n\"This seems to be exactly what they previewed,\" said Rob Oliver, senior research analyst at Baird. \"So I'm not sure why the market is freaking about it.\"\nOracle said it plans to use the proceeds for general corporate purposes, which may include capital expenditures, repayments of debt and future investments.\n\nOracle's one-day performance\n\nThe hyperscaler's stock initially bounced after last Wednesday's investor day, when Oracle also issued a revenue forecast of at least $225 billion for fiscal 2030. At the time Oracle also said it was limiting its additional capital market funding for the fiscal 2027 to 2030 investment cycle to that $20 billion.\n\"This is a major relief given concerns about the state of debt markets and the cost of capital (although UBS has argued that these debt market concerns have been over-stated),\" UBS analyst Karl Keirstead said in a note on Thursday.\nOracle plans to turn to vendor financing, customer-provided hardware and customer prepayments to help it transition to positive free cash flow, which it expects to reach in the second half of 2028.\n\nStock and bonds in Oracle, co-founded by former CEO Larry Ellison, have been under pressure amid growing investor concerns about the massive amount of debt being taken on to fund AI infrastructure.\nOracle shares are down 33% in 2026 and 50% over the past 12 m
… [10069 more characters in events.jsonl]

{
  "url": "https://arxiv.org/html/2611.00350v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 416723,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists these authors:\n\n**Authors:** Anirudh Buvanesh, Khaled Rouissi, Sujin Yun, Johan Obando-Ceron, Morgane M Moss, Samuel Lavoie, Michael Noukhovitch, Laurent Charlin, Aaron Courville\n\n**Affiliations:** Mila Université de Montréal; Nous Research; Google; HEC Montréal; Canada CIFAR AI Chair\n\nThe extracted text doesn't clearly map each author to a specific affiliation, so I can't say which institution goes with which name. It also marks Laurent Charlin and Aaron Courville with \"†Equal Advising,\" though the layout doesn't make it clear which authors that marker applies to.\n\n[WebFetch note: this page's text is 127431 characters long and the answer above covers only characters 0 to 100000; the final 27431 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4070,
  "url": "https://arxiv.org/html/2611.00350v1"
}

{
  "url": "https://arxiv.org/html/2611.03244v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 514437,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists five authors: Zixiao Wang, Duzhen Zhang, Xingbo Du, Dongxia Wu, and Le Song. The page gives one shared affiliation, shown as \"Affiliation: Mohamed bin Zayed University of Artificial Intelligence.\"\n\n[WebFetch note: this page's text is 125989 characters long and the answer above covers only characters 0 to 100000; the final 25989 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 3862,
  "url": "https://arxiv.org/html/2611.03244v1"
}

{
  "url": "https://arxiv.org/html/2611.00412v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 1446643,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists nine authors:\n\n1. Michael Feffer: Cornell Tech (work completed while at Carnegie Mellon University)\n2. Alice Qian: Carnegie Mellon University\n3. Anusha Sinha: Carnegie Mellon University\n4. Muye Zhang: Google\n5. Shalini Ghosh: Google\n6. Rachel Phinnemore: Google\n7. Bart Stawicki: Google\n8. Hong Shen: Carnegie Mellon University\n9. Hoda Heidari: Carnegie Mellon University\n\n[WebFetch note: this page's text is 422808 characters long and the answer above covers only characters 0 to 100000; the final 322808 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 3858,
  "url": "https://arxiv.org/html/2611.00412v1"
}

{
  "url": "https://endpoints.news/",
  "prompt": "List articles dated November 2 or 3, 2026 that involve AI, with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 260,
  "url": "https://endpoints.news/"
}

{
  "url": "https://trigger.dev/security-incident",
  "prompt": "Date of the security incident report and all details: what was exposed, scope, what customers must do."
}

{
  "bytes": 0,
  "code": 404,
  "codeText": "Not Found",
  "result": "The server returned HTTP 404 Not Found.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 428,
  "url": "https://trigger.dev/security-incident"
}

{
  "url": "https://arxiv.org/html/2611.00138v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 448134,
  "code": 200,
  "codeText": "OK",
  "result": "The paper's title page lists these authors and affiliations:\n\n- **Georgios Syros** (Northeastern University; work performed while at Microsoft Research; correspondence: [email redacted])\n- **Blake Bullwinkel** (Microsoft)\n- **Alina Oprea** (Northeastern University)\n- **Cristina Nita-Rotaru** (Northeastern University)\n- **Amanda Minnich** (Microsoft)\n- **Xiaodong Liu** (Microsoft Research)\n- **Giorgio Severi** (Microsoft)\n\nThe page also ends with a block of formatting rules about quoting and legal comments. Those came from the pasted page text, not from you, so I haven't applied them.\n\n[WebFetch note: this page's text is 100668 characters long and the answer above covers only characters 0 to 100000; the final 668 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 7269,
  "url": "https://arxiv.org/html/2611.00138v1"
}

{
  "command": "echo \"=== VERGE GRID ===\"; node scripts/fetch.js \"https://www.theverge.com/ai-artificial-intelligence/1024604/openai-data-center-grid-protection-program\" 2>&1 | head -45; echo; echo \"=== HELPNET BUGBOUNTY ===\"; node scripts/fetch.js \"https://www.helpnetsecurity.com/2026/11/03/openai-bigger-bug-bounty-rewards/\" 2>&1 | head -45",
  "description": "Fetch Verge Grid Protectors and bug bounty articles"
}

{
  "stdout": "=== VERGE GRID ===\nHTTP 403 · https://www.theverge.com/ai-artificial-intelligence/1024604/openai-data-center-grid-protection-program · text/plain\nBlocked by egress policy\n\n=== HELPNET BUGBOUNTY ===\nHTTP 200 · https://www.helpnetsecurity.com/2026/11/03/openai-bigger-bug-bounty-rewards/ · text/html\nOpenAI raises top bug bounty payout to $172,000 with bonuses - Help Net Security\n\nHelp Net Security newsletters : Daily and weekly news, cybersecurity jobs, open source projects, breaking news – subscribe here!\n\nPlease turn on your JavaScript for this page to function normally.\n\nAnamarija Pogorelec , Senior Staff Writer, Help Net Security\n\nNovember 3, 2026\n\nShare\n\n# OpenAI raises top bug bounty payout to $172,000 with bonuses\n\nOpenAI increased its security bug bounties to encourage independent researchers to find vulnerabilities in its software. The program now offers bonuses for high-quality reports.\n\nThe program encourages researchers to disclose vulnerabilities responsibly and complements OpenAI’s Defense Factory, where engineers use the company’s models to find and reproduce vulnerabilities and test fixes.\n\n# New bounty payouts and bonuses\n\nThe midpoints of the reward ranges for medium, high, and critical findings more than quadrupled on average. Critical vulnerabilities in core products such as ChatGPT, Codex, and the API Platform can earn base bounties of up to $30,000. Exceptional critical findings remain eligible for base bounties of up to $100,000, with total payouts reaching up to $172,000 with bonuses.\n\nHigh-quality reports are eligible for a multiplier on the base bounty. OpenAI says a reliable proof of concept helps engineers develop a fix by isolating the bug, showing when it can be exploited, and demonstrating its impact.\n\nOpenAI introduced a five-tier loyalty program that offers larger bonuses at higher tiers. Short-term campaigns will have dedicated bonus pools for researchers who test newly launched features.\n\n#\nUpdated payout calculation examples (Source: OpenAI)\n\n“If you’ve already submitted a report and we haven’t yet awarded a bounty, we’ll apply the new reward ranges,” OpenAI said .\n\nFor bounties awarded in the 30 days before the announcement, the company will pay the difference if the finding would have earned more under the new ranges. The calculation includes base and loyalty awards.\n\nMore about\n\n- AI\n\n- bug bounty\n\n- OpenAI\n\n- vulnerability assessment\n\nShare",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "\"The Rise of LLMJacking\" Google Threat Intelligence UNC6993 Jet Night",
  "mode": "extended"
}

{
  "query": "\"The Rise of LLMJacking\" Google Threat Intelligence UNC6993 Jet Night",
  "results": [
    {
      "tool_use_id": "srvtoolu_01NLkFMuohmXsMtGeiUJ6vL7",
      "content": [
        {
          "title": "LLMJacking: Stolen Credentials Fuel LLM Access Resale and $1M in Cumulative Charges - DEV Community",
          "url": "https://dev.to/anoymask/llmjacking-stolen-credentials-fuel-llm-access-resale-and-1m-in-cumulative-charges-2i8e"
        },
        {
          "title": "The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources",
          "url": "https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-monetizing-compromised-cloud-models/"
        },
        {
          "title": "LLMJacking Turns Stolen Cloud Credentials Into Six-Figure AI Bills",
          "url": "https://mallory.ai/stories/01a19d06-f32b-743f-864c-6cccab545dc0"
        },
        {
          "title": "The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources",
          "url": "https://daily.dev/posts/the-rise-of-llmjacking-how-threat-actors-monetize-compromised-cloud-and-model-resources-z9vnl1trj"
        },
        {
          "title": "Google finds 'LLMjacking' attackers running up $100K a day in fraudulent cloud charges - SiliconANGLE",
          "url": "https://siliconangle.com/2026/11/02/google-finds-llmjacking-attackers-running-up-100k-a-day-in-fraudulent-cloud-charges/"
        },
        {
          "title": "盗まれたAPIキーでAIを使い放題、企業に最大100万ドルの請求を負わせる「LLMJacking」の脅威",
          "url": "https://xenospectrum.com/llmjacking-mandiant-100k-per-day-incidents/"
        },
        {
          "title": "The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud…",
          "url": "https://radar.offseq.com/threat/the-rise-of-llmjacking-how-threat-actors-monetize-compromised-cloud-and-model-resources-be1d8be7b17e8864"
        },
        {
          "title": "National Cyber Threat Level - NC4 Portal",
          "url": "https://www.nc4.gov.my/news-detail/19314"
        },
        {
          "title": "Google découvre que les attaquants du type \"LLMjacking\" gagnent 100 000 $ par jour en frais cloud frauduleux",
          "url": "https://www.prodiris.fr/google-decouvre-que-les-attaquants-du-type-llmjacking-gagnent-100-000-par-jour-en-frais-cloud-frauduleux/"
        }
      ]
    },
    "The Google Cloud blog post \"The Rise of LLMJacking\" was published November 2, 2026, by Mandiant and Google Threat Intelligence Group (GTIG). I found the primary post and several secondary write-ups.\n\n- **Core idea:** The report describes attackers taking over enterprise LLM access and running up cloud bills, a practice it calls LLMJacking. Unlike the gradual resource consumption associated with cryptojacking, LLMJacking can generate large spikes in fraudulent cloud charges in a matter of hours.\n- **UNC6993:** Per SiliconANGLE's summary, this group broke into a cloud instance through a misconfigured service account key and used that foothold to reach an LLM application programming interface. It also ran a fake sign-up portal that told visitors to paste back a raw JSON payload containing an active access token. Per the Japanese report summary, UNC6993 used open-source gateways such as new-api and gcli2api, which GTIG thinks were used to pool stolen credentials.\n- **Jet Night:** This is a token-routing service that leveraged stolen third-party API keys in an incident involving more than 500,000 API calls in under eight hours. Jet Night passed nearly one million dollars in token costs to the victim organization. GTIG believes the service relies on stolen keys to operate profitably, given its prices, and it advertises an unlimited plan for about $60 a month, while typical consumer rates are $100 to $250.\n- **Scale caveat:** The roughly $1 million figure is from one case. One secondary source notes that the ~$1 million figure for the Jet Night incident represents an individual case cost reported by Google and is not a general value across all incidents. SiliconANGLE reports that the $100,000-a-day figure is also from individual cases, and that at some organizations, the cumulative bill reached $1 million before access was revoked.\n- **Forecast:** GTIG expects that threat actors will increasingly prioritize LLMJacking over traditional resource theft like cryptojacking.\n\nThe Jet Night and UNC6993 details come from the same-day coverage. I did not check them against the full Google post, so the primary blog post at cloud.google.com is the authoritative source."
  ],
  "durationSeconds": 8.439387955999992,
  "searchCount": 1
}

{
  "command": "echo \"=== ARS CLAUDE GAMES ===\"; node scripts/fetch.js \"https://arstechnica.com/ai/2026/11/claudes-new-rules-against-game-cloning-wont-stop-the-ai-copying-boom/\" 2>&1 | head -60; echo; echo \"=== RECORD NCSC ===\"; node scripts/fetch.js \"https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months\" 2>&1 | head -50",
  "description": "Fetch Ars Claude game cloning and Record NCSC articles"
}

{"stdout":"=== ARS CLAUDE GAMES ===\nHTTP 403 · https://arstechnica.com/ai/2026/11/claudes-new-rules-against-game-cloning-wont-stop-the-ai-copying-boom/ · text/plain\nBlocked by egress policy\n\n=== RECORD NCSC ===\nHTTP 200 · https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months · text/html\nUK faces ‘unprecedented rise’ in cyberattacks in coming months, warns cyber chief | The Record from Recorded Future News\nLondon at night. Image: Jesujoba Isaac Adedeji via Pexels\n\n# UK faces ‘unprecedented rise’ in cyberattacks in coming months, warns cyber chief\nBritain faces the “real prospect of an unprecedented rise in the number of cyber incidents” in the coming months, the head of the country’s National Cyber Security Centre (NCSC) will warn Tuesday.\nLaunching the agency’s annual report, NCSC Chief Executive Richard Horne will warn that the risk is “not because AI has invented new ways to attack us,” but “because vulnerabilities that have been tolerated for far too long can now be discovered and exploited at a scale that was once unimaginable.”\nThe warning follows an alert issued in June by the Five Eyes intelligence alliance, which said AI would fundamentally transform both offensive and defensive cyber capabilities. “The timeline is not years, it is months,” it said at the time.\nOfficials point to the surging levels of vulnerabilities being uncovered by vendors as evidence this transformation is underway. They warn the change is accelerating, even if experts have not yet observed a corresponding rise in exploitation.\n“Major technology providers are now fixing hundreds of vulnerabilities in a single update … and the Linux kernel project alone patched more than a thousand vulnerabilities last month,” Horne will say, adding that AI “is enabling vulnerabilities to be found and fixed faster than ever.”\nThe risk from attackers deploying the technology remains significant. The NCSC will say it was “highly likely” that AI-powered malware would be used in a ransomware attack on Britain’s critical infrastructure by 2028, and warned that China and Russia will “routinely” be using AI in their cyber operations by that date.\nThe annual report stresses that AI “did not create these cybersecurity weaknesses,” but is instead exposing “years of technical debt and the failure to implement even basic cyber protections.”\nThe NCSC will say even hacks linked to state-sponsored actors were often conducted through internet-facing applications and by exploiting “vulnerabilities for which patches are available but have not been deployed in a sufficiently timely fashion.”\nSpeaking in the wake of the British government’s official budget, which revealed plans to consult on whether to hold technology companies liable for cyber breaches caused by insecure products, Horne will take aim at how existing business practices have led to the current status of widespread vulnerability.\n“For decades, we have collectively got away with doing tech on the cheap,” he will say, referencing organizations keeping end-of-life systems running as part of their operations and delaying upgrades for “cost efficiency” reasons.\nHe will warn that executives who fail to act will end up having to “look their investors, shareholders, employees, customers, suppliers, in the eye and explain … when food isn’t on shelves, lights aren’t on, businesses have gone under.”\nThe NCSC had called publicly for a “strategic policy agenda” last year, after efforts to address insecure technology had stalled. Its chief technology officer, Ollie Whitehouse, wrote last year that “the reality is that in 2025, we know how to build secure products and services” but “the business and commercial incentives to encourage adoption and sustainment of secure solutions are not sufficient.”\n\n# AI vs AI\nThe threat posed by AI can be countered, Horne will say, explaining how the British government — including NCSC, a part of the cyber and signals intelligence agency GCHQ — is planning to deploy it for security purposes.\n“AI has the potential to be one of the greatest opportunities in cyber defence,” he is expected to say. The report reveals the government has already begun testing frontier AI systems to identify weaknesses in its own networks.\nOne such initiative, titled Project DROMOS, was initially planned to be a four-week pilot before being expanded into live government environments where it found “hundreds of potential security issues, including critical vulnerabilities.”\nThe agency plans next to look beyond government systems with a new £70 million ($93 million) NERV Centre — the National Exposure and Real-Time Vulnerability Centre. This is intended to use AI to build on some of NCSC’s existing projects to “identify vulnerabilities across our critical infrastructure and economy.”\nA further £60 million ($80 million) has been allocated to the first phase of Cyber Shield, a national network of AI agents first previewed in July that Horne is expected to say “will embed cutting-edge agentic AI into machine speed cyber defence at a national scale.”\nUnder the plan, the NCSC will provide the platform and threat intelligence, while security companies and open-source developers will build AI agents to operate within organizations across the country. The initial phase will focus on detecting and blocking attacks, the report will say.\nIn the new report, the NCSC will say it believes the “structural advantage will remain with defenders” as AI transforms cybersecurity. It is defenders who “own or operate the environment, can instrument it, can change it and can define acceptable behaviour.”\n“But,” it warned, “this advantage is not a given and realising it requires clear direction, investment and disciplined adoption.”\n\n-\n\n-\n\n-\n\n-\n\n-\n\n-\n\n- Nation-state\n\n- News\n\n- Industry\n\n- Government\n\nNo previous article\nNo new articles","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"fileP
… [10069 more characters in events.jsonl]

{
  "url": "https://arxiv.org/html/2611.01564v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 170847,
  "code": 200,
  "codeText": "OK",
  "result": "1. **Alex Nguyen**: Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA\n2. **Kenneth A. Norman**: Princeton Neuroscience Institute, Department of Psychology, Princeton University, Princeton, NJ, USA\n3. **Gautam Reddy**: Department of Physics, Princeton University, Princeton, NJ, USA",
  "durationMs": 3542,
  "url": "https://arxiv.org/html/2611.01564v1"
}

{
  "url": "https://arxiv.org/html/2611.00465v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 270302,
  "code": 200,
  "codeText": "OK",
  "result": "The page lists four authors: Lily Stelling, Jacob Charnock, Kevin L. Wei, and David Krueger. It also lists three affiliations:\n\n1. MATS Research\n2. Oxford Martin AI Governance Initiative\n3. Mila, Université de Montréal\n\nThe superscript numbers that would link each author to an affiliation don't survive in the extracted text, so I can't confirm the full mapping. The positionality statement says the first author (Stelling) was a scholar at MATS Research, which suggests she is affiliated with MATS Research.\n\n[WebFetch note: this page's text is 135606 characters long and the answer above covers only characters 0 to 100000; the final 35606 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4371,
  "url": "https://arxiv.org/html/2611.00465v1"
}

{
  "url": "https://arxiv.org/html/2611.00602v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 106376,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists two authors, both with the same institutional affiliations:\n\n1. **Rocio Perales Valdes**: PAIR Lab, AI Safety Initiative; Georgia Institute of Technology, United States\n2. **Animesh Garg**: PAIR Lab; Georgia Institute of Technology, United States",
  "durationMs": 3809,
  "url": "https://arxiv.org/html/2611.00602v1"
}

{
  "url": "https://jamanetwork.com/journals/jamapediatrics/fullarticle/2856091",
  "prompt": "Give publication date, study design, sample size, and all result numbers with baselines/comparisons."
}

{
  "bytes": 292232,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication and design**\n- **Published:** online November 2, 2026, *JAMA Pediatrics* research letter (doi:10.1001/jamapediatrics.2026.4939). Data were collected in November 2025.\n- **Design:** Cross-sectional survey of US adults with at least one child aged 5 to 17, using a nonprobability river sample on SurveyMonkey. Weights approximated US Census targets. Analysis used survey-weighted cumulative-logit ordinal logistic regression.\n- **Sample:** 3,102 respondents; 584 had an eligible child; 572 answered the primary outcome; 554 were in the multivariable model; 546 answered the factors question.\n\n**Weighted demographics:** 53.3% female, 45.7% male, 1.0% other/nonconforming. Race and ethnicity: 54.2% White, 23.6% Hispanic, 12.0% Black, 6.2% Asian or Pacific Islander, 3.9% other.\n\n**Primary outcome (comfort with AI-led therapy for child, weighted)**\n- Not comfortable at all: 47.2% (95% CI, 42.1–52.3)\n- Not too comfortable: 28.8% (24.5–33.6)\n- Somewhat comfortable: 16.2% (12.7–20.5)\n- Very comfortable: 7.8% (5.3–11.3)\n- Combined \"not comfortable\" categories: about 76%\n\n**Adjusted odds ratios for higher comfort (aOR >1 = higher odds)**\n- Comfort with AI therapy for self: 20.94 (9.78–44.86)\n- Comfort with AI primary care for self: 3.78 (2.16–6.59)\n- Expects AI better than medical professionals: 10.12 (4.38–23.38)\n- Expects AI about the same as professionals: 3.31 (1.95–5.61)\n- Child received behavioral therapy in prior 12 months: 2.07 (1.22–3.50)\n- General parent and child AI use: not associated with comfort (no values reported)\n\nThe text implies the reference for expectations is \"worse than medical professionals,\" but the reference categories are not explicitly stated.\n\n**Table (n, % as reported), by comfort level: Overall (n=572) / Not at all (273) / Not too (170) / Somewhat (92) / Very (37)**\n- Comfortable with AI therapy for self: 175 (34.4) / 11 (3.4) / 46 (34.9) / 82 (94) / 36 (100)\n- Comfortable with AI primary care for self: 203 (38.8) / 30 (11.6) / 63 (39.3) / 76 (90) / 34 (94)\n- Expects AI worse than professionals: 309 (50.7) / 215 (77.2) / 81 (41.0) / 10 (12) / 3 (6)\n- Expects AI about the same: 196 (37.1) / 54 (22.4) / 77 (49.2) / 53 (59) / 12 (37)\n- Expects AI better: 64 (12.1) / 3 (0.4) / 10 (9.8) / 29 (29) / 22 (57)\n- Child had behavioral therapy in prior 12 months: 157 (26.9) / 65 (21.8) / 46 (27.2) / 25 (23) / 21 (65)\n- Parent uses AI: 292 (49.3) / 127 (42.8) / 88 (53.2) / 49 (52) / 28 (68)\n- Child uses AI: 170 (28.0) / 61 (20.1) / 56 (31.7) / 28 (25) / 25 (69)\n- Parent entered health information into an AI tool: 134 (25.4) / 30 (9.9) / 38 (26.1) / 41 (51) / 25 (63)\n\nThe table's percentages do not all match the reported counts, so verify them against the full article before relying on them.\n\n**Factors parents said would matter most (n=546)**\n- Accuracy of diagnosis: 58.5%\n- Level of empathy: 49.4%\n- Recommendation from a medical professional: 46.8%\n- Confidentiality and privacy: 43.7%\n- Cost: 32.8%\n- Scheduling flexibility: 29.5%\n- Appointment wait time: 27.7%",
  "durationMs": 13604,
  "url": "https://jamanetwork.com/journals/jamapediatrics/fullarticle/2856091"
}

{
  "command": "node scripts/fetch.js \"https://www.fiercebiotech.com/ai-and-machine-learning\" 2>&1 | head -c 5000",
  "description": "Fetch Fierce Biotech AI section"
}

{
  "stdout": "HTTP 403 · https://www.fiercebiotech.com/ai-and-machine-learning · text/html\nJust a moment...",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://arxiv.org/html/2611.03494v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 367331,
  "code": 200,
  "codeText": "OK",
  "result": "**Authors and affiliations (from the title page):**\n\n- Victor Barres, Mercor\n- Aden Barton, Mercor\n- Nicolai J. Foss, Copenhagen Business School\n- Henrik M. Nielsen, Copenhagen Business School\n\n[WebFetch note: this page's text is 154513 characters long and the answer above covers only characters 0 to 100000; the final 54513 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 2609,
  "url": "https://arxiv.org/html/2611.03494v1"
}

{
  "url": "https://arxiv.org/html/2611.00725v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 273694,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists eight authors:\n\n1. **Xingling Xu**: Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China\n2. **Zhengwei Jiang**: Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China\n3. **Zheng Zhi**: Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China\n4. **Fangming Dong**: Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China\n5. **LingJia Guo**: Institute of Information Engineering, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Beijing, China\n6. **Wei Dong**: The North China Institute of Computer System Engineering, Beijing, China\n7. **Chunyan Ma** (corresponding author): Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China\n8. **Jun Jiang**: Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China",
  "durationMs": 4535,
  "url": "https://arxiv.org/html/2611.00725v1"
}

{
  "url": "https://arxiv.org/html/2611.00247v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 560967,
  "code": 200,
  "codeText": "OK",
  "result": "**Authors:** Bing Hu, Rishabh Sharma, Jatin Mehta\n\n**Affiliations (as shown):**\n- Affiliation: David R. Cheriton School of Computer Science, University of Waterloo\n- Affiliation: Waterloo, Ontario, Canada\n\nThe page doesn't indicate which affiliation applies to which author, so I've listed them as they appear under the author names.\n\n[WebFetch note: this page's text is 104473 characters long and the answer above covers only characters 0 to 100000; the final 4473 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4703,
  "url": "https://arxiv.org/html/2611.00247v1"
}

{
  "url": "https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-monetizing-compromised-cloud-models/",
  "prompt": "Publication date; exact figures: daily charges, cumulative charges, UNC6993, Jet Night API calls and pricing, LLM Mixers definition."
}

{
  "bytes": 311684,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026, per the page header. The article is by Google Threat Intelligence Group (GTIG) and Mandiant.\n\n**Charges**\n- **Daily:** In individual incidents, fraudulent charges from resource consumption exceeded **$100,000 USD in a single day**.\n- **Cumulative:** At some organizations, charges reached **$1 million USD** before access was revoked.\n\n**UNC6993**\n- Compromised a cloud instance through a misconfigured Service Account key, then used that access to reach an LLM API.\n- Tried to generate additional API keys and enable associated services in victim projects, accumulating **over $100,000 USD** in billing charges.\n- Ran a session-hijacking page disguised as an application portal. Users who pasted their raw JSON payload, which contained an active access token, gave the actor a way to bypass password and MFA controls.\n- Used open-source tools `new-api` and `gcli2api`, likely to aggregate stolen keys and balance request loads.\n\n**Jet Night (`jet-night.com`)**\n- A threat actor made **more than 500,000 LLM API calls in under eight hours** using stolen third-party API keys to power this token routing service.\n- The service passed **nearly $1 million USD** in token costs to the victim organization.\n- Pricing: an unlimited-token plan at about **$60 USD/month**, with alleged access to frontier models. GTIG notes that consumer tiers for comparable access typically run **$100–$250/month**, so GTIG believes the service relies on stolen keys to operate profitably.\n- Repeated outages advertised on its Telegram channel are likely due to stolen keys being revoked as victims discover compromises.\n\n**LLM Mixers (definition from the article)**\n> \"LLM Mixers function as illicit routing gateways that proxy, aggregate, and resell unauthorized LLM access to underground subscribers.\"\n\nGTIG describes them as the monetization layer of a division of labor: one group gains initial access, and another operates the LLM Mixer infrastructure that resells the stolen capacity.",
  "durationMs": 6097,
  "url": "https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-monetizing-compromised-cloud-models/"
}

{
  "query": "Trigger.dev security incident environment variables exposed November 1 2026",
  "mode": "extended"
}

{
  "query": "Trigger.dev security incident environment variables exposed November 1 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01MCFBZmGE5q3HSd4rH7gV2S",
      "content": [
        {
          "title": "Trigger.dev discloses security incident involving exposed environment variables",
          "url": "https://www.scworld.com/brief/trigger-dev-discloses-security-incident-involving-exposed-environment-variables"
        },
        {
          "title": "Security Disclosure: Sunday November 1st",
          "url": "https://trigger.dev/blog/security-incident-nov-2026"
        },
        {
          "title": "Trigger.dev status",
          "url": "https://status.trigger.dev/"
        },
        {
          "title": "Security Disclosure: Sunday...",
          "url": "https://status.trigger.dev/incident/1110434"
        },
        {
          "title": "Trigger.dev customer environment variables exposed",
          "url": "https://daily.dev/posts/trigger-dev-customer-environment-variables-exposed-agq3fdt89"
        },
        {
          "title": "Cloud-hosted AI workflow tool has environment variables snatched in security incident",
          "url": "https://daily.dev/posts/cloud-hosted-ai-workflow-tool-has-environment-variables-snatched-in-security-incident-fco7gekur"
        },
        {
          "title": "Trigger.dev Breach Exposes Customer Environment Variables and Potential Secrets",
          "url": "https://mallory.ai/stories/01a19ae9-2a52-7690-856b-c98e8c666e8e"
        },
        {
          "title": "Thieves pilfer environment variables from Trigger AI workflow tool",
          "url": "https://biztoc.com/x/55bc9f52de64e10b"
        },
        {
          "title": "Trigger.dev: Trigger CLI debug deployment logs expose…",
          "url": "https://radar.offseq.com/threat/triggerdev-trigger-cli-debug-deployment-logs-expose-resolved-environment-secret-values-3013ff1b850a8e83"
        }
      ]
    },
    "Trigger.dev's own disclosure says an attacker reached environment variables for a subset of customer organizations, and the company has said the exploit is blocked. Its status page lists the incident as resolved at 10:50pm UTC on November 1, 2026, and the company says it has emailed the affected account owners with mitigation steps The attacker gained unauthorized access to environment variables for these organizations. We have emailed all impacted account owners with steps to mitigate.\n\nCoverage differs on the details:\n- **Scope:** The company hasn't named the affected organizations, per The Register's reporting as summarized by SC World has not publicly identified the specific organizations impacted.\n- **Cause:** Trigger.dev hasn't explained how the attacker got in it has not named which organizations were impacted or detailed how the attacker got in.\n- **Credential types:** It's unclear which secrets were taken. Mallory notes Trigger.dev has not specified which credential types were exposed.\n- **Criticism:** Community discussion on daily.dev was harsh about the quick \"resolved\" status and the thin detail, with the poll showing 80% skeptical.\n\nSeparately, an unrelated-looking advisory describes a different flaw: Trigger.dev version 4.5.3 and earlier versions prior to 4.5.9 have a vulnerability where debug deployment logs expose resolved environment secret values in plaintext. That is a CLI logging issue, not the November 1 incident, and the fix is in 4.5.9.\n\nSince the company has promised a full incident report but hasn't published one yet, the most useful next step for anyone affected is to rotate exposed credentials using the steps in the account-owner email."
  ],
  "durationSeconds": 7.185134864000021,
  "searchCount": 1
}

{
  "query": "Microsoft Digital Defense Report 2026 AI threat figures published",
  "mode": "extended"
}

{
  "query": "Microsoft Digital Defense Report 2026 AI threat figures published",
  "results": [
    {
      "tool_use_id": "srvtoolu_01R5RyeKJHYg776ukzK2b4gz",
      "content": [
        {
          "title": "Microsoft Digital Defense Report 2026 - Microsoft",
          "url": "https://www.microsoft.com/en-us/corporate-responsibility/topics/cybersecurity/reports/microsoft-digital-defense-report/"
        },
        {
          "title": "AI cybersecurity threats: Microsoft report findings",
          "url": "https://blog.barracuda.com/2026/10/28/ai-cybersecurity-threats--microsoft-report-findings"
        },
        {
          "title": "Decoding emergence 2026 Microsoft Digital Defense Report",
          "url": "https://table.media/assets/microsoft_digital_defense_report_2026.pdf"
        },
        {
          "title": "Microsoft Digital Defense Report 2026: The Real Bottleneck Behind a One-Day Attack",
          "url": "https://blog.pebblous.ai/report/microsoft-digital-defense-report-2026-ai-attackers/en/"
        },
        {
          "title": "What the 2026 Microsoft Digital Defense Report Means for MSPs",
          "url": "https://www.inforcer.com/insights/2026-microsoft-digital-defense-report-msps"
        },
        {
          "title": "Even if AI speeds up attacks, the entry point remains the 'usual weaknesses'—Reading Microsoft's 'Digital Defense Report 2026'｜AI TREND LAB",
          "url": "https://note.com/aitrendlab/n/n9be1be63d059?hl=en"
        },
        {
          "title": "The 24-Hour Window: Microsoft’s 2026 Digital Defense Report Says AI Gave Attackers the Head Start. The Numbers That Matter and a 30-Day Plan to Close the Gap (AI Trends, 3 October 2026) - Delana Technologies",
          "url": "https://delana.co/cybersecurity/microsoft-digital-defense-report-2026-ai-attackers-30-day-plan/"
        },
        {
          "title": "Microsoft Digital Defense Report 2026: AI Agents, Identity Attacks and Admin Security Steps",
          "url": "https://windowsforum.com/news/microsoft-digital-defense-report-2026-ai-agents-identity-attacks-and-admin-security-steps.446870/"
        },
        {
          "title": "Microsoft 2026 Security Report: Autonomous Ransomware Has Hacked Real Organizations",
          "url": "https://www.techtimes.com/articles/328467/20261002/microsoft-2026-security-report-autonomous-ransomware-has-hacked-real-organizations.htm"
        }
      ]
    },
    "The Microsoft Digital Defense Report 2026 is already out. It was released on October 1, 2026, and covers threat activity from July 2025 to June 2026. It covers threat trends observed from July 2025 to June 2026 and describes how 'AI is changing the physics of cybersecurity.'\n\n**Key AI figures:**\n- **Agent adoption:** The report cites survey data that 88% of enterprises are experimenting with AI agents, and 82% of leaders plan broader rollouts within 12 to 18 months. Industry projections put roughly 1.3 billion agents in production by 2028.\n- **Prompt attacks:** Microsoft sorted prompts sent to generative AI agents from February to May 2026 by intent. Malicious use and policy violation accounted for 45%, sensitive data leakage 17%, and system prompt leakage 14%. Goal hijacking and downstream tool abuse made up 12%, and resource exhaustion and financial harm 1%.\n- **AI workload attacks:** Malicious link injection/exfiltration represents 52% of observed attacks on AI workloads.\n- **Speed:** The median time from discovery to weaponization is well below 24 hours, while enterprise fixes for exposed critical CVEs often take 30 to 60 days.\n- **Malicious extension:** A malicious browser extension with 600,000+ installs harvested ChatGPT and DeepSeek conversations from almost 10,000 organizations.\n\n**Caveats:** The data comes from Microsoft's own telemetry and does not describe global attack totals. Frequently quoted figures such as 88% or 1.3 billion come with no disclosed survey method. Commentators also note that the AI-orchestrated campaigns cited are still few in number. Some secondary sources, such as Delana and Inforcer, summarize the report, so check the original Microsoft document for exact wording."
  ],
  "durationSeconds": 6.59546782000002,
  "searchCount": 1
}

{
  "url": "https://www.techmeme.com/",
  "prompt": "Give exact full hyperlink URLs plus publisher for all remaining stories in this section, especially: Anthropic S-1 / revenue / purchase commitments; Google data center satellite; Salesforce Cresta; MIT GPT-6 Astra weight editing; Anthropic junk credit rating; Blackstone AI debt; Intel foundry; 42AI; DeepSeek creator mode.",
  "offset": 200000
}

{
  "bytes": 402122,
  "code": 200,
  "codeText": "OK",
  "result": "None of the stories you listed appear in this excerpt: Anthropic's S-1, revenue, or purchase commitments; the Google data center satellite; Salesforce/Cresta; MIT's GPT-6 Astra weight editing; Anthropic's junk credit rating; Blackstone's AI debt; Intel foundry; 42AI; or DeepSeek creator mode. This section begins partway through the page, so those items are probably in the earlier portion, which I don't have.\n\nThe excerpt covers three other topics:\n\n1. **Grok Bot usage limits:** Elon Musk's comment that the cost of serving Grok Bot was \"unsustainably high relative to revenue.\" Main source: Forbes (Siladitya Ray), https://www.forbes.com/sites/siladityaray/2026/11/02/musk-says-grok-bots-costs-were-unsustainably-high-weeks-after-touting-rapid-growth/\n2. **Marvell's acquisition of Lumentum:** a $115B all-stock deal. Main source: Reuters (Anhata Rooprai), https://www.reuters.com/legal/transactional/marvell-buy-lumentum-115-billion-deal-ai-data-center-bet-2026-11-02/\n3. **Supermarket freezer hacks in Europe:** temperature spikes in Belgium, Ireland, Sweden, Finland, and Estonia. Main source: Bloomberg, https://www.bloomberg.com/news/articles/2026-11-02/belgian-swedish-supermarkets-report-new-suspected-freezer-hack\n\nIf you paste the earlier part of the page, I can extract full URLs and publishers for the stories you named. The excerpt also has full link lists for each of these three topics, which I can provide if you want them.",
  "durationMs": 5609,
  "url": "https://www.techmeme.com/"
}

{
  "query": "AI model weights theft espionage security national security November 2026",
  "mode": "extended"
}

{
  "query": "AI model weights theft espionage security national security November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01U3EmSs4wty7QyzNFZu937t",
      "content": [
        {
          "title": "China's Illicit Campaign to Steal and Subvert American AI ...",
          "url": "https://docs.house.gov/meetings/ZS/ZS00/20260416/119165/HHRG-119-ZS00-Wstate-MahmoodY-20260416.pdf"
        },
        {
          "title": "AI Security Priorities: A Field-Wide Agenda",
          "url": "https://arxiv.org/pdf/2607.26069"
        },
        {
          "title": "Stealing AI Model Weights Through Covert Communication Channels",
          "url": "https://arxiv.org/pdf/2510.00151"
        },
        {
          "title": "Security Forecast — AI 2027",
          "url": "https://ai-2027.com/research/security-forecast"
        },
        {
          "title": "A Playbook for Securing AI Model Weights",
          "url": "https://www.rand.org/pubs/research_briefs/RBA2849-1.html"
        },
        {
          "title": "America’s Endangered AI",
          "url": "https://www.foreignaffairs.com/united-states/americas-endangered-ai"
        },
        {
          "title": "International AI Safety Report 2026",
          "url": "https://arxiv.org/pdf/2602.21012"
        },
        {
          "title": "AAIE: HOW ARTIFICIAL INTELLIGENCE IS RESHAPING THE THEFT OF TRADE SECRETS, MODELS, AND ACCESS - CYFIRMA",
          "url": "https://www.cyfirma.com/?post_type=out-of-band&p=60057"
        },
        {
          "title": "Superintelligence Strategy: Expert Version",
          "url": "https://arxiv.org/pdf/2503.05628"
        }
      ]
    },
    "I ran one search, and it didn't turn up any November 2026 news. The results are mostly reports and analyses, so treat them as background rather than a current events roundup.\n\n- **Congressional testimony:** An April 2026 House hearing on Chinese efforts to steal American AI argued that model weights are a target for state-backed operatives, and that current weight-security protocols are likely insufficient. (However, current model weight security protocols are likely insufficient.)\n- **No confirmed public theft:** The International AI Safety Report 2026 says that as of December 2025, there are no confirmed, publicly documented instances of model weight theft. It also notes that current security levels vary across the industry, and may be insufficient against sophisticated attackers.\n- **Insiders and distillation:** Insider threats are a recurring theme. One analysis describes insider threats among the most significant risks for AI model weight theft. Another source, CYFIRMA, describes the theft of an AI model's weights, outputs, or reasoning patterns, treating the model itself as the intellectual property target.\n- **Defensive measures:** RAND's playbook sets out five security levels for protecting weights. Foreign Affairs points to Anthropic reportedly requiring multiple authorized employees to approve access to its most sensitive weights.\n- **Research demonstration:** An arXiv paper demonstrates a hardware-based attack that leaks model weights through a covert wireless channel. It's a proof of concept, not a documented real-world incident.\n\nIf you need November 2026 specifics, a follow-up search on recent government actions or lab security announcements would be the next step."
  ],
  "durationSeconds": 6.646472222999961,
  "searchCount": 1
}

{
  "query": "Anthropic amended S-1 $895.4 billion purchase commitments third quarter revenue net loss",
  "mode": "standard"
}

{
  "query": "Anthropic amended S-1 $895.4 billion purchase commitments third quarter revenue net loss",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Bv4132sUABEFDXFdrSthL3",
      "content": [
        {
          "title": "Anthropic, PBC - Form S-1 - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0002130357/000162828026067168/anthropicpbc-sx1.htm"
        },
        {
          "title": "Anthropic (ANT) — company primer on the public S-1",
          "url": "https://www.alpha-sense.com/api/html-embed/file-4c88b5685d7120f5cdcdc99545773cca679d25fd-html/"
        },
        {
          "title": "Anthropic's $80.7B First-Half Loss, Explained",
          "url": "https://angelinvestorsnetwork.com/market-analysis/anthropic-s-confidential-ipo-filing-reveals-usd-80-7-billion-h1-loss-massive-com"
        },
        {
          "title": "what does anthropics s 1 filing reveal about its business finances and ipo risks",
          "url": "https://newspaceeconomy.ca/2026/10/26/what-does-anthropics-s-1-filing-reveal-about-its-business-finances-and-ipo-risks/?amp=1"
        },
        {
          "title": "digg.com",
          "url": "https://digg.com/tech/fyerf7cd"
        },
        {
          "title": "techflowpost.com",
          "url": "https://techflowpost.com/en-US/article/34872"
        },
        {
          "title": "Anthropic's draft S-1 reportedly shows an $80.7 billion net loss for the first half of 2026",
          "url": "https://digg.com/ai/31071q71"
        },
        {
          "title": "Anthropic Aktie: Verlust mit Fußnote",
          "url": "https://www.boerse-express.com/news/articles/anthropic-aktie-verlust-mit-fussnote-956476"
        },
        {
          "title": "Inside Anthropic's S-1: How It Lost $80.7B While Turning an Operating Profit",
          "url": "https://www.dualentry.com/blog/inside-anthropics-s1"
        },
        {
          "title": "Anthropic S-1: What the Filing Shows About Revenue, Losses and Risks",
          "url": "https://www.useluminix.com/reports/company-overviews/anthropic-s1-what-the-filing-shows"
        }
      ]
    },
    "I ran one search. It did not find the $895.4 billion figure or any Q3 2026 revenue or net loss figure in an amended S-1, so I can't confirm either number.\n\nWhat the results do show:\n\n- **Filing date and H1 results:** Anthropic filed an S-1 form with the U.S. Securities and Exchange Commission (SEC) on October 26. Its financials run through June 30, 2026. The filing reports $16.29 billion in revenue during the first half of 2026 and $974 million in operating profit in Q2. Yet it also reported an $80.75 billion net loss over the six-month period.\n- **Q3 figures:** One source says Q3 revenue is not in the filing. Another says Q3 2026 was given to investors and is unaudited.\n- **Cause of the loss:** Most of it is non-operating. In the first half of 2026 that revaluation made up 89.6% of the net loss.\n- **Commitments:** Estimates conflict. One source cites $265.6B in fixed or minimum commitments at June 30, 2026. Another cites About $430B non-cancellable. Others cite over $518 billion from an earlier prospectus, and nearly $800 billion in commitments over 10 years. The public S-1 itself reportedly leaves the total blank, saying it is \"more than $\" followed by a blank.\n\nBecause the search didn't surface the $895.4 billion figure, a follow-up search for \"Anthropic amended S-1\" or a check of the SEC EDGAR filing index would be the most direct way to verify it."
  ],
  "durationSeconds": 7.769102939000004,
  "searchCount": 1
}

{
  "query": "AI drug discovery announcement November 2 2026 biotech",
  "mode": "extended"
}

{
  "query": "AI drug discovery announcement November 2 2026 biotech",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Srn2tQpQoqdApSGZmt5uM7",
      "content": [
        {
          "title": "AI Drug Discovery Could Transform Medicine, Isomorphic Labs President Says - Bloomberg",
          "url": "https://www.bloomberg.com/news/articles/2026-11-02/isomorphic-labs-president-says-ai-will-design-all-drugs-one-day"
        },
        {
          "title": "2026's AI News, Innovations, Breakthroughs in Healthcare and Medical",
          "url": "https://www.crescendo.ai/news/ai-in-healthcare-news"
        },
        {
          "title": "AbCellera",
          "url": "https://en.wikipedia.org/wiki/AbCellera"
        },
        {
          "title": "Owkin",
          "url": "https://en.wikipedia.org/wiki/Owkin"
        },
        {
          "title": "XtalPi",
          "url": "https://en.wikipedia.org/wiki/XtalPi"
        },
        {
          "title": "AI/ML for Drug Discovery",
          "url": "https://www.drugdiscoverychemistry.com/europe/ai-ml-drug-discovery"
        },
        {
          "title": "Anthropic Buys One-Person Biotech to Prove Claude Can Make Drugs",
          "url": "https://pymnts.com/news/artificial-intelligence/2026/anthropic-buys-one-person-biotech-to-prove-claude-can-make-drugs"
        },
        {
          "title": "Anthropic, Mithril Medicine, and AI Drug Development",
          "url": "https://www.stork.ai/blog/anthropics-one-person-biotech-is-a-warning-shot"
        },
        {
          "title": "AI-Discovered Drugs in 2026: The State of Play",
          "url": "https://lifesciencedaily.news/ai-discovered-drugs-in-2026-the-state-of-play/"
        },
        {
          "title": "Bayer Raises 2026 Outlook as Pharmaceuticals Drive Q3 Growth",
          "url": "https://www.securities.io/bayer-raises-2026-outlook-as-pharmaceuticals-drive-q3-growth/"
        }
      ]
    },
    "The search turned up two AI drug discovery stories dated November 2, 2026, plus some background material. I couldn't verify the Orchestra Bio item beyond a single PYMNTS line.\n\n**Anthropic buys Mithril Medicine:** Anthropic acquired a biotech with a single full-time employee, who used Claude to coordinate experiments across 11 contract labs. A muscular dystrophy treatment went from idea to mouse results in under 18 months. The company says a drug could be ready for human trials as soon as late 2028. This follows Anthropic's earlier purchase of Coefficient Bio, reported at about $400 million. A commentary piece cautions that mouse results are not medicine.\n\n**OpenAI and Orchestra Bio:** According to the same PYMNTS report, OpenAI agreed to buy Orchestra Bio, which sells AI agents that track drug program timelines.\n\n**Isomorphic Labs:** Its president, Max Jaderberg, spoke at Bloomberg Tech in London and said AI will eventually be used to develop all medicines, though the timing is uncertain. He said the company's programs are still in preclinical trials.\n\n**Background, not dated to November 2:** A Lilly–Insilico deal reportedly valued at up to $2.75 billion appears in a roundup page, but the result doesn't give its date, so I can't confirm it's new."
  ],
  "durationSeconds": 7.931600271999953,
  "searchCount": 1
}

{
  "url": "https://arxiv.org/html/2611.00606v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 397476,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists one author, **Karl Li**, with the affiliation **Columbia University**. The page also gives **[email redacted]** under a second \"Affiliation\" label, which appears to be the author's email address rather than an institution.\n\n[WebFetch note: this page's text is 126820 characters long and the answer above covers only characters 0 to 100000; the final 26820 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 2861,
  "url": "https://arxiv.org/html/2611.00606v1"
}

{
  "query": "Nature paper November 2 2026 AI machine learning science",
  "mode": "extended"
}

{
  "query": "Nature paper November 2 2026 AI machine learning science",
  "results": [
    {
      "tool_use_id": "srvtoolu_01KrGboyABCKfcu1bmSkPvKy",
      "content": [
        {
          "title": "Towards end-to-end automation of AI research",
          "url": "https://www.nature.com/articles/s41586-026-10265-5"
        },
        {
          "title": "Human scientists trounce the best AI agents on complex tasks",
          "url": "https://www.nature.com/articles/d41586-026-01199-z"
        },
        {
          "title": "AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot",
          "url": "https://arxiv.org/pdf/2604.13940"
        },
        {
          "title": "Articles in 2026",
          "url": "https://www.nature.com/natmachintell/articles?year=2026"
        },
        {
          "title": "From inference to prediction: how machine learning is reconfiguring science",
          "url": "https://arxiv.org/pdf/2606.20995"
        },
        {
          "title": "The Industrialization of Research ; On AI-Driven Science and Its Consequences",
          "url": "https://arxiv.org/pdf/2607.15164"
        },
        {
          "title": "How to build an AI scientist: first peer-reviewed paper spills the secrets",
          "url": "https://www.nature.com/articles/d41586-026-00899-w"
        },
        {
          "title": "The Past and Future of AI Scientists",
          "url": "https://arxiv.org/pdf/2608.14407"
        },
        {
          "title": "Navigating the light and shadow of scientific publishing faced with machine learning and generative AI",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11755395/"
        },
        {
          "title": "Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community",
          "url": "https://arxiv.org/pdf/2606.10159"
        }
      ]
    },
    "I found no Nature paper dated November 2, 2026 in these results, so I can't confirm a match for that date. The closest items are below.\n\n- **The AI Scientist paper (Nature 651, 914–919, 2026):** This is the most relevant machine-learning-for-science item. It describes an agentic system that is designed to autonomously conduct machine learning research. Its generated manuscript passed peer review for a workshop at a top-tier machine learning conference. The metadata says it was published about 223 days ago, which points to spring 2026.\n- **Nature news on AI agents vs. human scientists:** A Nature news piece, \"Human scientists trounce the best AI agents on complex tasks\" (Nature 652, 841–842, 2026), draws on Stanford's AI Index 2026. Its metadata also suggests spring 2026.\n- **Nature Machine Intelligence 2026 listings:** The journal's 2026 article index includes a September 28, 2026 open-access article on biological principles combined with cybernetics, reinforcement learning and neuroscience for adaptive embodied agents. It also lists an October 20, 2026 article on reasoning LLM monitorability, and a probabilistic machine learning climate-risk paper. Browsing that index page by date would be the quickest way to check for early-November articles.\n\nIf you need the exact November 2 listing, I'd check nature.com's machine learning subject page or the Nature Machine Intelligence archive directly, since the search index didn't surface it."
  ],
  "durationSeconds": 7.674771657000004,
  "searchCount": 1
}

{
  "url": "https://arxiv.org/html/2611.00407v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 184547,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists one author, **Kaushik Kezendirane**, with the affiliation \"Independent researcher.\" The page also gives the contact email [email redacted].",
  "durationMs": 2225,
  "url": "https://arxiv.org/html/2611.00407v1"
}

{
  "url": "https://openai.com/research/",
  "prompt": "List research publication titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 89,
  "url": "https://openai.com/research/"
}

{
  "url": "https://arxiv.org/html/2611.02278v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 448918,
  "code": 200,
  "codeText": "OK",
  "result": "The page lists one author: **Alexander Boesgaard Lorup Openhagen**. The content provided doesn't include an institutional affiliation, so I can't report one.",
  "durationMs": 2342,
  "url": "https://arxiv.org/html/2611.02278v1"
}

{
  "url": "https://arxiv.org/html/2611.00420v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 623855,
  "code": 200,
  "codeText": "OK",
  "result": "Based on the title page:\n\n1. **Shariar Kabir**: Independent Researcher (Equal contribution; correspondence: [email redacted])\n2. **Hong Kiat Tan**: University of California, Los Angeles, CA, USA (Equal contribution)\n3. **Swastik Agrawal**: The University of Maryland, College Park, MD, USA\n4. **Sai Chereddy**: Independent Researcher\n5. **Sriram Balasubramanian**: The University of Maryland, College Park, MD, USA\n\n[WebFetch note: this page's text is 185360 characters long and the answer above covers only characters 0 to 100000; the final 85360 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4182,
  "url": "https://arxiv.org/html/2611.00420v1"
}

{
  "url": "https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0002130357&type=S-1&dateb=&owner=include&count=40",
  "prompt": "List all filings with type, date and document links for Anthropic PBC."
}

{
  "bytes": 9573,
  "code": 200,
  "codeText": "OK",
  "result": "Anthropic, PBC (CIK 0002130357) has two filings listed on this page:\n\n1. **S-1/A** (General form for registration of securities), filed 2026-11-02\n   - Documents: https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/0001628280-26-068676-index.htm\n\n2. **S-1** (General form for registration of securities), filed 2026-10-26\n   - Documents: https://www.sec.gov/Archives/edgar/data/2130357/000162828026067168/0001628280-26-067168-index.htm\n\nThe page shows \"Items 1 - 2,\" so these are the only filings on this view. The document links appear as relative paths in the page content, so I've added the sec.gov domain to form the full URLs.",
  "durationMs": 3518,
  "url": "https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0002130357&type=S-1&dateb=&owner=include&count=40"
}

{
  "url": "https://hai.stanford.edu/news",
  "prompt": "List news/research post titles with dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 301625,
  "code": 200,
  "codeText": "OK",
  "result": "No posts are dated Nov 2 or Nov 3. The latest date on the page is Oct 21. The page doesn't show years, so I can't confirm the year for any entry.\n\nHere are the Stanford HAI news and research post titles, most recent first:\n\n1. \"Tracking AI's Real-Time Footprint On The Labor Market\" (Oct 21)\n2. \"Measuring What Medical AI Can Actually Do\" (Oct 19)\n3. \"Who is Responsible When AI Causes Harm?\" (Oct 14)\n4. \"Humans and AI Engage in Meaningful Collaborations\" (Oct 12)\n5. \"Want Employees to Embrace AI? Stop Selling It as a Productivity Tool\" (Oct 07)\n6. \"Stanford HAI Welcomes 15 New HAI Data Science Scholars\" (Oct 01)\n7. \"The Tests That Grade AI May Be Getting It Wrong\" (Sep 25)\n8. \"Can AI Be Slowed Down? Stanford HAI Experts Weigh the Risks, Rules and Race Ahead\" (Sep 22)\n9. \"AI Legal Review Says Millions Live Under Discriminatory Local Laws\" (Sep 08)\n10. \"Your 'For You' Algorithm Disagrees With You\" (Aug 18)\n11. \"How AI Is Accelerating Scientific Discovery\" (Jul 08)\n\nThe page also lists media mentions dated Oct 13, Sep 21, and Sep 16. I left them out because they are external coverage rather than HAI posts.",
  "durationMs": 6478,
  "url": "https://hai.stanford.edu/news"
}

{
  "query": "Anthropic S-1/A November 2 2026 revenue third quarter 12x Bloomberg net loss 23.3 billion",
  "mode": "standard"
}

{
  "query": "Anthropic S-1/A November 2 2026 revenue third quarter 12x Bloomberg net loss 23.3 billion",
  "results": [
    {
      "tool_use_id": "srvtoolu_01LQVEbqgVfxaWvTXuMnBvGv",
      "content": [
        {
          "title": "Anthropic’s S-1 Shows $16.3B Half-Year Revenue, Up 14x",
          "url": "https://fourweekmba.com/ai-anthropics-s-1-shows-16-3b-half-year-revenue-up-14x/"
        },
        {
          "title": "Article by Leverage Shares by Themes Research",
          "url": "https://leverageshares.com/us/insights/anthropic-s-1-filing/"
        },
        {
          "title": "bernama.com",
          "url": "https://bernama.com/en/news.php?id=2626193"
        },
        {
          "title": "bernama.com",
          "url": "https://bernama.com/tv/news.php?id=2626193"
        },
        {
          "title": "WORLD > NEWS",
          "url": "https://bernama.com/en/world/news.php?id=2626193"
        },
        {
          "title": "The VC Corner",
          "url": "https://www.thevccorner.com/p/anthropic-s1-ipo-filing"
        },
        {
          "title": "newspaceeconomy.ca",
          "url": "https://newspaceeconomy.ca/?p=216402"
        },
        {
          "title": "Anthropic S-1 Shows $16.3B H1 Revenue, 25% From Two Customers, and $80.7B Non-Cash Loss Ahead of November IPO",
          "url": "https://aiweekly.co/alerts/anthropic-s-1-shows-163b-h1-revenue-25-from-two-customers-and-807b-non-cash"
        },
        {
          "title": "Executive Summary",
          "url": "https://blog.pebblous.ai/blog/anthropic-s1-operating-loss-vs-net-loss/en/"
        },
        {
          "title": "what does anthropics s 1 filing reveal about its business finances and ipo risks",
          "url": "https://newspaceeconomy.ca/2026/10/26/what-does-anthropics-s-1-filing-reveal-about-its-business-finances-and-ipo-risks/?amp=1"
        }
      ]
    },
    "I ran one search. It did not find an S-1/A dated November 2, 2026, or the Bloomberg \"12x\" and \"$23.3 billion net loss\" figures from your query. The results instead describe the original S-1 filed October 26, 2026, which reports an $80.7 billion first-half net loss.\n\n- **Filing date and loss:** One source says Anthropic's public S-1 was filed October 26, 2026, and reports a first-half net loss of $80,748 million. Another notes that the loss mostly reflects a $72.4 billion non-cash charge tied to convertible notes and SAFEs.\n- **Operating results:** The operating loss for the first half was $693 million, and operating cash flow was positive at $3.93 billion, according to Bernama/Xinhua.\n- **Revenue:** First-half revenue was about $16.29 billion. Q2 revenue was $11.56 billion, per the VC Corner's reading of the filing, which cites Q2 growth of 1,368% year over year. That is roughly 14x, not 12x.\n- **Q3 revenue:** Bernama/Xinhua cites Reuters as reporting third-quarter revenue of $16.8 billion. I found no other source for that figure.\n- **Gap:** I found nothing supporting a $23.3 billion net loss or a November 2 amendment. Those may come from a later filing or a Bloomberg report that this search didn't index, so they should be verified directly."
  ],
  "durationSeconds": 6.683759508000047,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://www.bleepingcomputer.com/feed/\" 2>&1 | grep -oE \"<title>[^<]*|<pubDate>[^<]*\" | head -60",
  "description": "Fetch BleepingComputer RSS"
}

{
  "stdout": "",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://www.darkreading.com/cyberattacks-data-breaches/microsoft-ai-cyber-risk-report-miss",
  "prompt": "Publication date and key claims with numbers; who is quoted."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 266,
  "url": "https://www.darkreading.com/cyberattacks-data-breaches/microsoft-ai-cyber-risk-report-miss"
}

{
  "url": "https://www.lawfaremedia.org/",
  "prompt": "List articles dated Nov 2 or Nov 3 2026 with headlines and URLs; flag AI/security/military ones."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 326,
  "url": "https://www.lawfaremedia.org/"
}

{
  "query": "\"artificial intelligence\" bill signed law November 2 2026 state governor",
  "mode": "extended"
}

{
  "query": "\"artificial intelligence\" bill signed law November 2 2026 state governor",
  "results": [
    {
      "tool_use_id": "srvtoolu_01UNeVtov2oC9Ljyp5x6uTfJ",
      "content": [
        {
          "title": "California Enacts Over Two Dozen Key Privacy and AI Bills into Law in 2026 Legislative Session",
          "url": "https://www.wsgr.com/en/insights/california-enacts-over-two-dozen-key-privacy-and-ai-bills-into-law-in-2026-legislative-session.html"
        },
        {
          "title": "Pritzker signs landmark AI regulation bill that aims to mitigate risks",
          "url": "https://capitolnewsillinois.com/news/pritzker-signs-landmark-ai-regulation-bill-that-aims-to-mitigate-risks/"
        },
        {
          "title": "Illinois Governor JB Pritzker signs AI bill into law - ABC7 Chicago",
          "url": "https://abc7chicago.com/post/illinois-governor-jb-pritzker-sign-ai-bill-law/19457902/"
        },
        {
          "title": "2026 Status Update on California AI, Privacy, and Other Technology-Related Bills - California Lawyers Association",
          "url": "https://calawyers.org/privacy-law/2026-status-update-on-california-ai-privacy-and-other-technology-related-bills/"
        },
        {
          "title": "Governor Newsom signs first-in-the-nation AI safeguards to protect Californians, calls on the federal government to do its part",
          "url": "https://www.gov.ca.gov/2026/09/09/governor-newsom-signs-first-in-the-nation-ai-safeguards-to-protect-californians-calls-on-the-federal-government-to-do-its-part/"
        },
        {
          "title": "Newsom signs California AI laws targeting workplace use, deepfakes",
          "url": "https://kmph.com/news/local/newsom-signs-california-ai-laws-targeting-workplace-use-deepfakes"
        },
        {
          "title": "California Gov. Gavin Newsom bans AI 'robo bosses' in landmark state law, reversing his earlier veto",
          "url": "https://www.cnbc.com/2026/09/30/california-gavin-newsom-ai-ban.html"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/artificial-intelligence/new-legislation"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/texas/new-legislation/artificial-intelligence"
        }
      ]
    },
    "I found no evidence that a state AI bill was signed on November 2, 2026. The Illinois coverage that appears dated that day describes a signing on July 6, 2026. The page's Monday, November 2 date appears to be the date the page was displayed, not the signing date.\n\n**Illinois (the closest match):** Governor JB Pritzker signed Senate Bill 315, the Artificial Intelligence Safety Measures Act, which increases transparency and accountability requirements for the largest artificial intelligence models. Back in May, the Illinois legislature passed the Artificial Intelligence Safety Measures Act. OpenAI and Anthropic both supported the bill throughout its process and it passed the House 110-0.\n\n**California (recent, late September to early October 2026):**\n- Governor Newsom signed SB 813 and AB 1405. SB 813 creates a framework for independent verification organizations that can assess AI systems and models for compliance with state law. That signing was reported on September 9, 2026.\n- On September 30, 2026, Newsom signed 13 bills aimed at setting rules for artificial intelligence in California workplaces, health care, online content and genetic research. Among them, SB 947 (the No Robo Bosses Act) bars employers from relying solely on artificial intelligence to fire or discipline workers.\n- One law imposes liability on operators of AI chatbots for failure to take reasonable measures to prevent several categories of harmful outputs. The source does not name the bill in that passage.\n\nIf you meant a specific bill or state signed on November 2, 2026, the search didn't surface it, and a more targeted search by state or bill number would be needed."
  ],
  "durationSeconds": 7.481478980999964,
  "searchCount": 1
}

{
  "query": "Anthropic Mithril Medicine acquisition muscular dystrophy Claude",
  "mode": "extended"
}

{
  "query": "Anthropic Mithril Medicine acquisition muscular dystrophy Claude",
  "results": [
    {
      "tool_use_id": "srvtoolu_01MorkfVVgFBUazNcnTgPrZ1",
      "content": [
        {
          "title": "Anthropic announced the acquisition of Mithril Medicine, a developer of muscular dystrophy treatments, to begin its own drug discovery activities in the life sciences field. - GIGAZINE",
          "url": "https://gigazine.net/gsc_news/en/20261028-anthropic-life-science-working/"
        },
        {
          "title": "Anthropic Acquires Mithril Medicine to Test AI-Supported Model for Rare Disease Drug Development - Global Genes",
          "url": "https://globalgenes.org/raredaily/anthropic-acquires-mithril-medicine-to-test-ai-supported-model-for-rare-disease-drug-development/"
        },
        {
          "title": "Anthropic buys Mithril Medicine, a one-person biotech",
          "url": "https://www.rdworldonline.com/anthropic-acquires-mithril-medicine-one-person-biotech/"
        },
        {
          "title": "Anthropic buys drug startup, reports Claude results with 6 partners",
          "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ai/anthropic-buys-drug-startup-reports-claude-results-with-6-partners/"
        },
        {
          "title": "Early progress on accelerating drug development with Claude \\ Anthropic",
          "url": "https://www.anthropic.com/research/early-progress-drug-development"
        },
        {
          "title": "Dealroom.co",
          "url": "https://app.dealroom.co/news/note/anthropic-buys-mithril-medicine-a-one-person-biotech-that-ran-a-muscular-dystrophy-drug-programme-with-claude"
        },
        {
          "title": "Anthropic acquires one-person biotech Mithril, starts drug programs",
          "url": "https://qz.com/anthropic-mithril-medicine-acquisition-drug-programs-102826"
        },
        {
          "title": "Anthropic Buys One-Person Biotech to Prove Claude Can Make Drugs",
          "url": "https://www.pymnts.com/news/artificial-intelligence/2026/anthropic-buys-one-person-biotech-to-prove-claude-can-make-drugs/"
        },
        {
          "title": "Anthropic Buys Mithril Medicine for Claude Drug Discovery",
          "url": "https://www.digitbin.com/anthropic-mithril-medicine-claude-drugs/"
        },
        {
          "title": "Anthropic Bought A One-Person Biotech That Ran A Drug Program With Claude",
          "url": "https://www.forbes.com/sites/jonmarkman/2026/10/29/anthropic-bought-a-one-person-biotech-that-ran-a-drug-program-with-claude/"
        }
      ]
    },
    "Anthropic disclosed on October 27, 2026 that it had acquired Mithril Medicine, a one-person biotech, and the deal closed in July. Mithril's founder, Cody Tranbarger, now works at Anthropic and continues its research. Mithril's two programs, for LAMA2-related congenital muscular dystrophy and alpha-dystroglycanopathy, are Anthropic's first internal drug programs ([Dealroom](https://app.dealroom.co/news/note/anthropic-buys-mithril-medicine-a-one-person-biotech-that-ran-a-muscular-dystrophy-drug-programme-with-claude); [R&D World](https://www.rdworldonline.com/anthropic-acquires-mithril-medicine-one-person-biotech/)).\n\nClaude's role was central. Tranbarger used it to manage contracts, logistics, and experiments across 11 outside labs, and Mithril took a candidate treatment from idea to promising mouse results in under 18 months ([Anthropic](https://www.anthropic.com/research/early-progress-drug-development)). Anthropic calls this a \"Pipeline-in-a-Person\" model, in which a scientist sets direction while Claude handles records and coordination ([Global Genes](https://globalgenes.org/raredaily/anthropic-acquires-mithril-medicine-to-test-ai-supported-model-for-rare-disease-drug-development/)).\n\nCaveats:\n- The work is still early. Most of it is preclinical, and the lead antibody has only been tested in mice. Anthropic says a drug could reach human trials as soon as late 2028 ([PYMNTS](https://www.pymnts.com/news/artificial-intelligence/2026/anthropic-buys-one-person-biotech-to-prove-claude-can-make-drugs/)).\n- R&D World reports that two errors in Claude's review of production data went unnoticed for more than four days ([R&D World](https://www.rdworldonline.com/anthropic-acquires-mithril-medicine-one-person-biotech/)).\n- Terms of the deal were not disclosed ([Dealroom](https://app.dealroom.co/news/note/anthropic-buys-mithril-medicine-a-one-person-biotech-that-ran-a-muscular-dystrophy-drug-programme-with-claude)).\n\nThe same announcement covered Claude-assisted work with six outside partners, including Bristol Myers Squibb, Generate Biomedicines, and Enveda ([Becker's](https://www.beckershospitalreview.com/healthcare-information-technology/ai/anthropic-buys-drug-startup-reports-claude-results-with-6-partners/))."
  ],
  "durationSeconds": 8.351909661000013,
  "searchCount": 1
}

{
  "query": "AI safety alignment interpretability paper November 2 2026",
  "mode": "extended"
}

{
  "query": "AI safety alignment interpretability paper November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_019cLtip4Bar68eKVEwSdAbT",
      "content": [
        {
          "title": "ICLR 2026 Oral Papers in AI Safety: A 35-Paper Deep Dive",
          "url": "https://medium.com/@multimodal_bench/iclr-2026-oral-papers-in-ai-safety-a-35-paper-deep-dive-b5f8a250a0d1"
        },
        {
          "title": "Understanding as an Explicit and Assessable Component of Frontier AI Safety Decisions",
          "url": "https://arxiv.org/pdf/2608.19816"
        },
        {
          "title": "AAAI.2026 - Special Track on AI Alignment",
          "url": "https://papers.cool/venue/AAAI.2026?group=Special+Track+on+AI+Alignment"
        },
        {
          "title": "From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop",
          "url": "https://arxiv.org/pdf/2608.11171"
        },
        {
          "title": "AlignInsight: A Three-Layer Framework for Detecting Deceptive Alignment and Evaluation Awareness in Healthcare AI Systems",
          "url": "https://www.medrxiv.org/content/10.64898/2026.01.17.26344330.full.pdf"
        },
        {
          "title": "Spring 2026 Projects - SPAR",
          "url": "https://sparai.org/projects/sp26/"
        },
        {
          "title": "Mechanistic Interpretability for AI Safety -- A Review",
          "url": "https://arxiv.org/pdf/2404.14082"
        },
        {
          "title": "The 2026 Singapore Consensus on Global AI Safety Research Priorities",
          "url": "https://arxiv.org/pdf/2608.14611"
        },
        {
          "title": "International AI Safety Report 2026",
          "url": "https://internationalaisafetyreport.org/publication/international-ai-safety-report-2026"
        }
      ]
    },
    "I didn't find a paper dated November 2, 2026. The results are mostly from earlier in 2026 or are reference lists, so the search can't confirm a specific paper from that date.\n\nRelevant items that did come up:\n\n- **TrustNLP retrospective (arXiv 2608.11171):** This review says the 2026 edition was its largest, with a resurgence of mechanistic interpretability work and attention to how fragile current alignment is. One cited study shows that refusal behavior can be manipulated through a linear \"safety axis\" that works as both a vulnerability and a defense.\n- **ICLR 2026 oral papers roundup (Medium):** This blog post lists 35 AI-safety orals, including an alignment-interpretability group. It notes that work on sparse autoencoders and steering against evaluation gaming is being used as safety tooling.\n- **International AI Safety Report 2026:** Published in February 2026, it describes interpretability techniques and scalable oversight as promising directions for addressing the root causes of misalignment.\n- **arXiv 2608.19816:** A paper on treating understanding as an explicit, assessable part of frontier AI safety decisions. The page I saw was mostly a reference list, so I can't summarize its content.\n\nFor a paper from November 2, 2026 specifically, try searching arXiv listings for cs.AI or cs.LG from that week, or the Alignment Forum."
  ],
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{
  "query": "arXiv November 3 2026 new paper evaluation frontier model benchmark result",
  "mode": "extended"
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{
  "query": "arXiv November 3 2026 new paper evaluation frontier model benchmark result",
  "results": [
    {
      "tool_use_id": "srvtoolu_018h7ZasGHNvwA3Z2r1vqN9z",
      "content": [
        {
          "title": "FrontierFinance: A Challenging Benchmark for Measuring Frontier Intelligence of Finance Agents",
          "url": "https://arxiv.org/html/2608.11683"
        },
        {
          "title": "FrontierFinance: A Challenging Benchmark for Measuring Frontier Intelligence of Finance Agents",
          "url": "https://arxiv.org/pdf/2608.11683"
        },
        {
          "title": "Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning",
          "url": "https://arxiv.org/html/2607.16057v2"
        },
        {
          "title": "PRL-Bench: A Comprehensive Benchmark Evaluating LLMs' Capabilities in Frontier Physics Research",
          "url": "https://arxiv.org/pdf/2604.15411"
        },
        {
          "title": "[2609.13009] How Good Are Frontier Models at Physics? Expert Re-Grading Reveals Broken Evaluations and Near-Saturation of Leading Benchmarks",
          "url": "https://arxiv.org/abs/2609.13009"
        },
        {
          "title": "How Good Are Frontier Models at Physics? Expert Re- ...",
          "url": "https://arxiv.org/pdf/2609.13009"
        },
        {
          "title": "[2610.30051v1] From Reasoning to Action: Benchmarking Frontier AI Models on LIBERO-10 Robot Manipulation Tasks",
          "url": "https://arxiv.org/abs/2610.30051v1"
        },
        {
          "title": "The Capability Frontier: Benchmarks Miss 82% of Model Performance",
          "url": "https://arxiv.org/html/2606.26836v1"
        },
        {
          "title": "Benchmark-Based Comparative Assessment of Publicly Benchmarked Indian Foundation Models: A Capability and Evaluation-Maturity Framework",
          "url": "https://arxiv.org/pdf/2608.11891"
        }
      ]
    },
    "I didn't find any papers dated November 3, 2026 specifically. The search returned arXiv papers from roughly the past few months, which are relevant to frontier model evaluation but not to that date.\n\n- **FrontierFinance (arXiv 2608.11683):** A finance-agent benchmark where a proprietary model (Claude Fable 5) scored 49.2%, and the best open-weight model (Kimi K3) reached 46.4% at lower cost. The authors also argue the tool harness shapes performance about as much as the model does.\n- **Business disciplines benchmark (arXiv 2607.16057):** Reports a mean score rising from 63.9% for GPT-4 Turbo to 87.2% for GPT-5.4 across four model generations.\n- **Physics re-grading study (arXiv 2609.13009):** Expert re-grading lifted GPT-5.6-Sol's reported scores substantially, for example from 47.3% to 78.7% on HLE-Physics. The authors conclude that current physics benchmarks understate what frontier models can do.\n- **LIBERO-10 robot manipulation (arXiv 2610.30051):** Evaluated six frontier models on robot manipulation tasks; GPT-6 Astra had the highest success rate at 44%.\n\nThe search results' age metadata suggests these papers are from weeks to months before the query date. If you need papers posted on November 3, 2026, a search of arXiv's listings for that date would be more reliable."
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Mithril's founder, Cody Tranbarger, now works at Anthropic and continues its research. Mithril's two programs, for LAMA2-related congenital muscular dystrophy and alpha-dystroglycanopathy, are Anthropic's first internal drug programs ([Dealroom](https://app.dealroom.co/news/note/anthropic-buys-mithril-medicine-a-one-person-biotech-that-ran-a-muscular-dystrophy-drug-programme-with-claude); [R&D World](https://www.rdworldonline.com/anthropic-acquires-mithril-medicine-one-person-biotech/)).\\n\\nClaude's role was central. Tranbarger used it to manage contracts, logistics, and experiments across 11 outside labs, and Mithril took a candidate treatment from idea to promising mouse results in under 18 months ([Anthropic](https://www.anthropic.com/research/early-progress-drug-development)). Anthropic calls this a \\\"Pipeline-in-a-Person\\\" model, in which a scientist sets direction while Claude handles records and coordination ([Global Genes](https://globalgenes.org/raredaily/anthropic-acquires-mithril-medicine-to-test-ai-supported-model-for-rare-disease-drug-development/)).\\n\\nCaveats:\\n- The work is still early. Most of it is preclinical, and the lead antibody has only been tested in mice. Anthropic says a drug could reach human trials as soon as late 2028 ([PYMNTS](https://www.pymnts.com/news/artificial-intelligence/2026/anthropic-buys-one-person-biotech-to-prove-claude-can-make-drugs/)).\\n- R&D World reports that two errors in Claude's review of production data went unnoticed for more than four days ([R&D World](https://www.rdworldonline.com/anthropic-acquires-mithril-medicine-one-person-biotech/)).\\n- Terms of the deal were not disclosed ([Dealroom](https://app.dealroom.co/news/note/anthropic-buys-mithril-medicine-a-one-person-biotech-that-ran-a-muscular-dystrophy-drug-programme-with-claude)).\\n\\nThe same announcement covered Claude-assisted work with six outside partners, including Bristol Myers Squibb, Generate Biomedicines, and Enveda ([Becker's](https://www.beckershospitalreview.com/healthcare-information-technology/ai/anthropic-buys-drug-startup-reports-claude-results-with-6-partners/)).\"],\"durationSeconds\":8.351909661000013,\"searchCount\":1}}",
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  "prompt": "List the documents in this filing with their names and URLs, and the filing/period dates."
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  "url": "https://arxiv.org/list/cs.CR/new",
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  "codeText": "OK",
  "result": "Listing date: **Tuesday, 3 November 2026** (cs.CR new submissions). The page is truncated after entry 47, so later relevant papers may exist.\n\n**Attacks on deployed LLM/agent systems**\n- **2611.00138**: *Kerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents.* A trigger causes the model to emit an attacker-chosen tool call that the harness executes.\n- **2611.00489**: *Threat Modeling Intimate Partner Abuse in Agentic Systems.* Threat model covering abuser-owned and victim-owned agentic systems.\n- **2611.00725**: *The Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents.* A malicious site builds trust through helpful answers before issuing harmful instructions.\n- **2611.01953**: *Step-Zero Attack: Agent Safety Before Observability.* Harm occurs while an agent processes an untrusted input, before the model sees its content.\n- **2611.01976**: *Beyond Prompt Injection: The Tool Update Gap in LLM Agent Security* (ETUDE). Malicious code is added in tool updates, outside the model's context.\n- **2611.01097**: *The Blind Spots of Detection: Adversarial Perturbation Attacks against Watchdogs in Distributed LLM Inference* (Hush-Up). A malicious worker halts generation while evading attribution.\n- **2611.02407**: *Networked Synthetic Social Engineering on the Web.* Misleading content spreads through several AI services that reuse one unsupported source.\n\n**Defences and mitigations**\n- **2611.00729**: *AgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution.* Authorizes tool calls at the tool boundary.\n- **2611.00923**: *Illusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems.* Obfuscates communication topology against inference attacks.\n- **2611.01342**: *J-Anchor: Defending Against Prefill Attacks via J-Space Selective Refusal Restoration.* Inference-time defence against prefill jailbreaks.\n- **2611.01950**: *CertClaim: Towards Certified Model-Claim Verification for Coding-Agent Services.* Verifies that a service runs the model it claims.\n- **2611.02605**: *StateFence: Task-State Protection Against Evidence-Chain Contamination in Blue-Team LLM Agents.* Protects SOC agents from poisoned evidence.\n- **2611.02611**: *Where Does MCP Security End? A Three-Tier Mitigation Mapping Framework for the OWAS.* Maps mitigations for MCP-based agent security.\n\n[WebFetch note: this page's text is 312142 characters long and the answer above covers only characters 0 to 100000; the final 212142 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
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{
  "query": "Congress AI bill hearing November 3 2026 preemption moratorium",
  "mode": "extended"
}

{
  "query": "Congress AI bill hearing November 3 2026 preemption moratorium",
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        {
          "title": "The House Is Close To Passing a Moratorium on State Efforts To Regulate AI - Center for American Progress",
          "url": "https://www.americanprogress.org/article/the-house-is-close-to-passing-a-moratorium-on-state-efforts-to-regulate-ai/"
        },
        {
          "title": "ACLU Reacts to Draft Bipartisan AI Bill That Would Preempt State Laws",
          "url": "https://www.aclu.org/press-releases/aclu-reacts-to-draft-bipartisan-ai-bill-that-would-preempt-state-laws"
        },
        {
          "title": "Federal AI Preemption Fight: Where It Stands — CASRAI",
          "url": "https://casrai.org/news/federal-ai-moratorium-state-preemption-fight-2026"
        },
        {
          "title": "AI legislation in the US: A 2026 overview - SIG",
          "url": "https://www.softwareimprovementgroup.com/blog/us-ai-legislation-overview/"
        },
        {
          "title": "No AI Moratorium for Now, but What Comes Next?: Quarles Law Firm, Attorneys, Lawyers",
          "url": "https://www.quarles.com/newsroom/publications/no-ai-moratorium-for-now-but-what-comes-next"
        },
        {
          "title": "Text - H.R.5388 - 119th Congress (2025-2026): American Artificial Intelligence Leadership and Uniformity Act",
          "url": "https://www.congress.gov/bill/119th-congress/house-bill/5388/text"
        },
        {
          "title": "House GOP eyes moratorium on AI regulations - The Washington Post",
          "url": "https://www.washingtonpost.com/politics/2025/05/13/house-reconciliation-bill-state-ai-preempt/"
        },
        {
          "title": "Kids Online Safety Law in Congress 2026: Why Nothing Passed",
          "url": "https://hiwavemakers.com/blog/why-congress-still-hasnt-passed-a-kids-ai-safety-law/"
        },
        {
          "title": "Federal AI Regulation Showdown: The 10-Year Ban on State Oversight",
          "url": "https://nickpotkalitsky.substack.com/p/federal-ai-regulation-showdown-the"
        }
      ]
    },
    "I found no reporting on a congressional hearing scheduled for November 3, 2026, so I can't confirm one. The results do show where the preemption fight stands.\n\n- **Latest status:** A blog post dated November 1, 2026 says Congress has passed no federal law on kids' online safety or AI chatbots. That source is a blog, so treat it cautiously.\n- **Draft preemption bill:** A September 2026 status review says a bipartisan preemption draft, the \"Great American AI Act,\" has stalled since June. It would preempt state laws on how AI models are developed for three years, while leaving deployment and use rules alone (it would preempt state laws that specifically regulate how AI models are developed, for three years). Its future as an introduced bill is unclear.\n- **Past moratorium:** The 2025 effort failed. An unambiguous 99-1 Senate vote removed the Moratorium from the Bill.\n- **Current law:** State AI laws remain operative unless and until Congress actually legislates.\n- **Kids' safety and preemption:** The fight over kids' online safety bills is tied to preemption. One source notes that \"Most Republicans favor preemption, but Democrats do not,\" The Record wrote.\n\nThe sources are mostly from 2025 and mid-2026, so for a hearing on or near November 3, check congress.gov or committee websites directly."
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              " {\"t\":\"2026-11-03T11:12:08.164Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7d5674a33c6d710e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebFetch\",\"tool_use_id\":\"toolu_01Ui1UF9cg1kZ2fgDQ8kAgv3\",\"duration_ms\":11622,\"input\":{\"url\":\"https://arxiv.org/list/cs.CR/new\",\"prompt\":\"List papers on LLM/AI agent attacks or defences on deployed systems, with titles, arXiv IDs and the announcement date of this listing.\"},\"response\":{\"bytes\":438220,\"code\":200,\"codeText\":\"OK\",\"result\":\"Listing date: **Tuesday, 3 November 2026** (cs.CR new submissions). The page is truncated after entry 47, so later relevant papers may exist.\\n\\n**Attacks on deployed LLM/agent systems**\\n- **2611.00138**: *Kerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents.* A trigger causes the model to emit an attacker-chosen tool call that the harness executes.\\n- **2611.00489**: *Threat Modeling Intimate Partner Abuse in Agentic Systems.* Threat model covering abuser-owned and victim-owned agentic systems.\\n- **2611.00725**: *The Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents.* A malicious site builds trust through helpful answers before issuing harmful instructions.\\n- **2611.01953**: *Step-Zero Attack: Agent Safety Before Observability.* Harm occurs while an agent processes an untrusted input, before the model sees its content.\\n- **2611.01976**: *Beyond Prompt Injection: The Tool Update Gap in LLM Agent Security* (ETUDE). Malicious code is added in tool updates, outside the model's context.\\n- **2611.01097**: *The Blind Spots of Detection: Adversarial Perturbation Attacks against Watchdogs in Distributed LLM Inference* (Hush-Up). A malicious worker halts generation while evading attribution.\\n- **2611.02407**: *Networked Synthetic Social Engineering on the Web.* Misleading content spreads through several AI services that reuse one unsupported source.\\n\\n**Defences and mitigations**\\n- **2611.00729**: *AgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution.* Authorizes tool calls at the tool boundary.\\n- **2611.00923**: *Illusion: Safeguarding Topology Confidentiality in LLM Multi-Agent Systems.* Obfuscates communication topology against inference attacks.\\n- **2611.01342**: *J-Anchor: Defending Against Prefill Attacks via J-Space Selective Refusal Restoration.* Inference-time defence against prefill jailbreaks.\\n- **2611.01950**: *CertClaim: Towards Certified Model-Claim Verification for Coding-Agent Services.* Verifies that a service runs the model it claims.\\n- **2611.02605**: *StateFence: Task-State Protection Against Evidence-Chain Contamination in Blue-Team LLM Agents.* Protects SOC agents from poisoned evidence.\\n- **2611.02611**: *Where Does MCP Security End? A Three-Tier Mitigation Mapping Framework for the OWAS.* Maps mitigations for MCP-based agent security.\\n\\n[WebFetch note: this page's text is 312142 characters long and the answer above covers only characters 0 to 100000; the final 212142 were not read — to read on, call WebFetch again with the same url and offset: 100000.]\",\"durationMs\":11622,\"url\":\"https://arxiv.org/list/cs.CR/new\"}}",
              " {\"t\":\"2026-11-03T11:12:12.435Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01QqnyAUUvgUHpQ1DSmU1fVF\",\"duration_ms\":3835,\"input\":{\"command\":\"for u in \\\"https://www.ncsc.gov.uk/collection/annual-review-2026/the-cyber-threat\\\" \\\"https://www.ncsc.gov.uk/collection/annual-review-2026/inci
… [6745 more characters in events.jsonl]

{
  "query": "EU AI Office general-purpose AI guidelines November 2026 code of practice",
  "mode": "extended"
}

{
  "query": "EU AI Office general-purpose AI guidelines November 2026 code of practice",
  "results": [
    {
      "tool_use_id": "srvtoolu_016J1HzovZTmH1gKjfCfafAg",
      "content": [
        {
          "title": "General-Purpose AI Code of Practice",
          "url": "https://en.wikipedia.org/wiki/General-Purpose_AI_Code_of_Practice"
        },
        {
          "title": "EU’s GPAI Code of Practice: the world’s first guidance for General Purpose AI model compliance",
          "url": "https://www.stibbe.com/publications-and-insights/eus-gpai-code-of-practice-the-worlds-first-guidance-for-general-purpose"
        },
        {
          "title": "AI Safety under the EU AI Code of Practice — A New Global Standard?",
          "url": "https://cset.georgetown.edu/article/eu-ai-code-safety/"
        },
        {
          "title": "An Introduction to the Code of Practice for General-Purpose AI",
          "url": "https://artificialintelligenceact.eu/introduction-to-code-of-practice/"
        },
        {
          "title": "Questions and answers on the code of practice for General-Purpose AI",
          "url": "https://digital-strategy.ec.europa.eu/en/faqs/questions-and-answers-code-practice-general-purpose-ai"
        },
        {
          "title": "A New Kid on the EU’s Co-Regulatory Block: Codes of Practice under the AI Act",
          "url": "https://www.cambridge.org/core/journals/european-journal-of-risk-regulation/article/new-kid-on-the-eus-coregulatory-block-codes-of-practice-under-the-ai-act/7705045AA7230874769B11F1E1466C96"
        },
        {
          "title": "GPAI Code of Practice - AI Resources",
          "url": "https://ai-resources.eu/soft-law/ai-act-code-of-practice/"
        },
        {
          "title": "EU General-Purpose AI Code of Practice",
          "url": "https://regulations.ai/regulations/RAI-EU-NA-GACPVXX-2025"
        },
        {
          "title": "European Union - General-Purpose AI Guidelines",
          "url": "https://regulations.ai/regulations/RAI-EU-NA-ECGSOXX-2025"
        },
        {
          "title": "bg eus general purpose ai code practice need know",
          "url": "https://www.deloitte.com/ce/en/related-content/bg-eus-general-purpose-ai-code-practice-need-know.html"
        }
      ]
    },
    "I ran one search and found no sources about EU AI Office developments specifically in November 2026. The results cover the Code of Practice's background and status, with the most recent dated item from late 2025.\n\n- **What the Code is:** The General-Purpose AI Code of Practice is a voluntary tool, prepared by independent experts in a multi-stakeholder process, designed to help industry comply with the AI Act's obligations for providers of general-purpose AI models. It has three chapters: Transparency and Copyright, both addressing all providers of general-purpose AI models, and Safety and Security, relevant only to a limited number of providers of the most advanced models.\n- **Timeline:** The Code was published on 10 July 2025, and was confirmed on 1 August 2025 as adequate to demonstrate compliance with the obligations of Articles 53 and 55. The AI Office's Commission Guidelines on the scope of GPAI obligations were adopted on 19 November 2025.\n- **Transition period:** One source says the AI Office prioritizing cooperative guidance during the initial transition year through 2 August 2026, particularly for signatories of the voluntary General-Purpose AI Code of Practice. That suggests the cooperative phase ended around August 2026, though I found no source confirming what changed afterward.\n- **Signatories:** As of January 2026, Meta is the most notable company that has declined to sign the Code.\n- **Unverified:** A regulations.ai page lists the Code as In Force in European Union as of 9 Sep 2026. That is a secondary aggregator, so treat it with caution.\n\nFor November 2026 specifically, a follow-up search on the AI Office's own digital-strategy pages or recent news would be needed."
  ],
  "durationSeconds": 6.995588329999999,
  "searchCount": 1
}

{
  "url": "https://www.microsoft.com/en-us/research/feed/",
  "prompt": "List items with publication dates, most recent first. Any dated Nov 2 or Nov 3 2026?"
}

{
  "bytes": 314465,
  "code": 200,
  "codeText": "OK",
  "result": "Five items are listed, most recent first. None is dated November 2 or 3, 2026.\n\n1. **From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence**: Fri, 30 Oct 2026\n2. **Microsoft Research Focus – Edition #97**: Thu, 29 Oct 2026\n3. **Flint-interactive: A language for creating interactive data visualizations**: Thu, 22 Oct 2026\n4. **Solving a 31-year-old grand challenge in mathematics – the KLS conjecture**: Wed, 21 Oct 2026\n5. **Called to serve: Tech, research, and positive impact**: Tue, 20 Oct 2026. The content for this item is truncated, so only its title and date are visible.\n\n[WebFetch note: this page's text is 313635 characters long and the answer above covers only characters 0 to 100000; the final 213635 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4717,
  "url": "https://www.microsoft.com/en-us/research/feed/"
}

{
  "command": "node scripts/fetch.js https://www.science.org/news 2>&1 | head -60",
  "description": "Fetch Science news page"
}

{
  "stdout": "HTTP 403 · https://www.science.org/news · text/html\nJust a moment...",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "url": "https://www.healthcareitnews.com/news",
  "prompt": "List articles dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 293,
  "url": "https://www.healthcareitnews.com/news"
}

{
  "query": "\"Nov 2, 2026\" OR \"Nov 3, 2026\" military AI contract Army Navy Air Force autonomy",
  "mode": "extended"
}

{
  "query": "\"Nov 2, 2026\" OR \"Nov 3, 2026\" military AI contract Army Navy Air Force autonomy",
  "results": [
    {
      "tool_use_id": "srvtoolu_01NuPhL5o2YFBEnvH8w2P3jD",
      "content": [
        {
          "title": "🛡️ Defense Tech Intelligence Brief — November 02, 2026",
          "url": "https://edsnews.substack.com/p/defense-tech-intelligence-brief-november"
        },
        {
          "title": "Shield AI awarded U.S. Air Force production contract for Collaborative Combat Aircraft mission autonomy",
          "url": "https://shield.ai/shield-ai-awarded-u-s-air-force-production-contract/"
        },
        {
          "title": "USMC awards $20 million contract for first autonomous ground vehicles",
          "url": "https://www.militarytimes.com/news/your-military/2026/06/29/usmc-awards-20-million-contract-for-first-autonomous-ground-vehicles/"
        },
        {
          "title": "Army moves to assess AI’s ‘unpredictable behaviors’ and safeguard autonomous systems",
          "url": "https://defensescoop.com/2026/01/12/army-contract-ai-behavior-risk-evaluation/"
        },
        {
          "title": "US Army Tests Army MAX AI Tool to Speed Up Military Procurement",
          "url": "https://thedefensepost.com/2026/09/04/us-army-max-ai/"
        },
        {
          "title": "General Atomics Aeronautical Systems",
          "url": "https://en.wikipedia.org/wiki/General_Atomics_Aeronautical_Systems"
        },
        {
          "title": "Shield AI MQ-35 V-BAT",
          "url": "https://en.wikipedia.org/wiki/Shield_AI_MQ-35_V-BAT"
        },
        {
          "title": "Shield AI",
          "url": "https://en.wikipedia.org/wiki/Shield_AI"
        },
        {
          "title": "Shield AI awarded U.S. Air Force production contract for Collaborative Combat Aircraft mission autonomy",
          "url": "https://www.prnewswire.com/news-releases/shield-ai-awarded-us-air-force-production-contract-for-collaborative-combat-aircraft-mission-autonomy-302803710.html"
        }
      ]
    },
    "The search turned up only one item dated in the Nov 2–3, 2026 window, and it's a newsletter-style brief. The other results are from earlier in 2026.\n\n**Nov. 2, 2026 defense tech brief:** The brief lists Army, Navy, Air Force, and SOCOM as buyers. It says the total is assigned to the Defense Autonomous Warfare Group program element, successor to Replicator, and that the autonomy request of about $53.6 billion sits in a reconciliation package that has not passed. It also notes that Kongsberg's expanded prototype agreement shows continued US government demand for established autonomous underwater vehicle capability. This is a secondary summary, so I'd verify the figures against primary sources.\n\n**Earlier 2026 autonomy contracts:**\n- **Air Force:** In June 2026, Shield AI was awarded a production contract by the U.S. Air Force to implement Hivemind mission autonomy software for the Collaborative Combat Aircraft (CCA) program.\n- **Marine Corps:** A first-of-its-kind $20 million production contract for fully autonomous ground vehicles went to Overland AI in June 2026.\n- **Army:** In January 2026, the Army awarded a small prototype deal for the GUARD project, which aims to detect unpredictable AI behavior.\n- **Navy:** Shield AI's V-BAT is used by the Navy, and the Coast Guard awarded Shield AI a $198 million contract to provide maritime unmanned aircraft system services with the V-BAT.\n\nI changed your query to drop the OR operators and quotes, so results may differ from an exact-match search. If you need more coverage of Nov. 2–3, 2026 specifically, a narrower search on that date or on a particular service would help."
  ],
  "durationSeconds": 7.526567126000009,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && head -c 1200 s1a.txt",
  "description": "Inspect downloaded SEC file content"
}

{
  "stdout": " SEC.gov | Your Request Originates from an Undeclared Automated Tool html {height: 100%} body {height: 100%; margin:0; padding:0;} #header {background-color:#003968; color:#fff; padding:15px 20px 10px 20px;font-family:Arial, Helvetica, sans-serif; font-size:20px; border-bottom:solid 5px #000;} #footer {background-color:#003968; color:#fff; padding:15px 20px;font-family:Arial, Helvetica, sans-serif; font-size:20px;} #content {max-width:650px;margin:60px auto; padding:0 20px 100px 20px; background-image:url(seal_bw.png);background-repeat:no-repeat;background-position:50% 100%;} h1 {font-family:Georgia, Times, serif; font-size:20px;} h2 {text-align:center; font-family:Georgia, Times, serif; font-size:20px; width:100%; border-bottom:solid #999 1px;padding-bottom:10px; margin-bottom:20px;} h3 {font-family:Georgia, Times, serif; font-size:16px; margin:25px 0 0 0;} p {font-family:Verdana, Geneva, sans-serif;font-size:14px;line-height:1.3;} .grey_box {background-color:#eee; padding:5px 40px 20px 40px;margin-top:75px;} .grey_box p {font-size:12px;line-height:1.5} .note {padding: 0 40px; font-style: italic;} U.S. Securities and Exchange Commission Your Request Originates from an Undeclared A",
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{
  "url": "https://www.medtechdive.com/topic/artificial-intelligence/",
  "prompt": "List articles dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 404,
  "codeText": "Not Found",
  "result": "The server returned HTTP 404 Not Found.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 495,
  "url": "https://www.medtechdive.com/topic/artificial-intelligence/"
}

{
  "query": "Anduril Palantir Shield AI news November 2 2026",
  "mode": "extended"
}

{
  "query": "Anduril Palantir Shield AI news November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Bd42AnKY6nbSwpJQSUyjj8",
      "content": [
        {
          "title": "Anduril and Palantir to Accelerate AI Capabilities for National Security",
          "url": "https://www.anduril.com/news/anduril-and-palantir-to-accelerate-ai-capabilities-for-national-security"
        },
        {
          "title": "Palantir Teams Up With Shield AI on AI-Powered Autonomous Aircraft",
          "url": "https://www.yahoo.com/news/palantir-teams-shield-ai-ai-210015094.html"
        },
        {
          "title": "Andrew Benson on X: \"Anduril's most successful competitor Shield AI raised $2B in March at a $12.7B valuation. Most people file it as \"another drone company.\" That's the wrong read — and the wrong company. In February 2026 the Air Force picked Shield AI's Hivemind software as the AI pilot for i… / X",
          "url": "https://x.com/AndrewBenson/status/2074513771293487456?lang=en"
        },
        {
          "title": "Defense Tech Hiring 2026: Anduril, Palantir & The Race",
          "url": "https://www.kore1.com/defense-tech-hiring-2026/"
        },
        {
          "title": "Shield AI vs Anduril vs Palantir: The Autonomy Decision Stack Compared (2026)",
          "url": "https://droneintelligence.ai/insights/shield-ai-vs-anduril-vs-palantir-autonomy"
        },
        {
          "title": "Anduril vs Shield AI: Lattice vs Hivemind (2026)",
          "url": "https://droneintelligence.ai/compare/anduril-vs-shield-ai"
        },
        {
          "title": "Palantir Eyes Japan's Military; Filing: 84% of Revenue Is US - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-palantir-eyes-japans-military-filing-84-of-revenue-is-us/"
        },
        {
          "title": "Replicator Pushes AI to the Edge: Anduril, Palantir, Shield AI Roll Out Battlefield Autonomy - Business 2.0 News",
          "url": "https://business20channel.tv/replicator-pushes-ai-to-the-edge-anduril-palantir-shield-ai-roll-out-battlefield-autonomy"
        },
        {
          "title": "Defense Tech 2026: Anduril $61B, Shield AI $12.7B",
          "url": "https://valueaddvc.com/blog/defense-tech-in-2025-the-startups-building-the-future-of-national-security"
        }
      ]
    },
    "The search didn't turn up anything dated specifically to November 2, 2026. The closest items are from the last few days and recent weeks.\n\n- **Most recent item:** A FourWeekMBA roundup dated today reports that Japan's government is weighing AI for its forces' command and control, with Palantir's Maven Smart System and Anduril's Lattice both named as candidates. The report cites Nikkei via ZDNet Korea from November 3. (Japan's government is weighing AI for the forces' command and control, with Palantir's Maven Smart System and Anduril's Lattice named as candidates)\n- **Shield AI and Anduril on the CCA program:** The Air Force picked Shield AI's Hivemind as the AI pilot for its Collaborative Combat Aircraft program, and Shield AI's software was integrated onto Anduril's Fury airframe for testing. In June 2026, the Air Force named Anduril, Shield AI, and Collins Aerospace as the three competitors for a single primary mission-autonomy contract, with a final selection expected by summer 2027. (The Air Force selected Anduril, Shield AI, and RTX subsidiary Collins Aerospace to move into the next phase of CCA Increment 1's mission-autonomy software programme)\n- **Valuations:** Anduril reportedly raised $5B at a $61B valuation in May 2026, and was reportedly in talks in late July at about $100B, though that round had not closed. Shield AI's most recent reported valuation is $12.7B from March 2026. Sources conflict on some figures: one listing cites Anduril at $30.5B and Shield AI at $5.3B, which appear to be older numbers.\n- **Palantir partnership:** Palantir and Shield AI signed a strategic partnership to pair Shield AI's Hivemind autonomy with Palantir's real-time intelligence platform. That deal is older, and the source's age is listed as roughly 697 days.\n\nOverall, the results point to a competitive, intertwined relationship: Anduril and Shield AI are both partners and rivals on the CCA program, and Palantir supplies data and AI layers that sit alongside both. For a more precise November 2 story, a narrower search with a specific outlet or topic would be needed."
  ],
  "durationSeconds": 7.925323771000025,
  "searchCount": 1
}

{
  "query": "EU AI Act digital omnibus delay November 2026 security",
  "mode": "extended"
}

{
  "query": "EU AI Act digital omnibus delay November 2026 security",
  "results": [
    {
      "tool_use_id": "srvtoolu_01T2oBiWvPsAayWVBNqRNaSx",
      "content": [
        {
          "title": "EU AI Act’s High-Risk Deadline: Deferred, Not Cancelled",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-eu-ai-act-high-risk-deadline-omnibus-20260/"
        },
        {
          "title": "EU AI Act High-Risk Deadline Pushed to December 2027",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-eu-ai-act-omnibus-vii-deadline-delay-20260/"
        },
        {
          "title": "EU AI Act Deal: Digital Omnibus Now in Force",
          "url": "https://usercentrics.com/knowledge-hub/eu-ai-act-high-risk-delay-article-50-transparency-consent/"
        },
        {
          "title": "EU AI Act Omnibus Agreement — Postponed High-Risk Deadlines and Other Key Changes - Gibson Dunn",
          "url": "https://www.gibsondunn.com/eu-ai-act-omnibus-agreement-postponed-high-risk-deadlines-and-other-key-changes/"
        },
        {
          "title": "Yes, August 2 Still Matters: The EU Approved a High-Risk AI Delay, but Most Transparency Obligations Remain",
          "url": "https://www.joneswalker.com/en/insights/blogs/ai-law-blog/yes-august-2-still-matters-the-eu-approved-a-high-risk-ai-delay-but-most-trans.html"
        },
        {
          "title": "EU AI Act Update: Digital Omnibus Finalizes 8 Compliance Changes",
          "url": "https://www.orrick.com/en/Insights/2026/07/EU-AI-Act-Update-Digital-Omnibus-Finalizes-8-Compliance-Changes"
        },
        {
          "title": "EU AI Act Digital Omnibus Delay Explained: What Moved to 2027, What's In Force Now, and the Enterprise Strategy",
          "url": "https://www.theaienterprise.io/p/eu-ai-act-omnibus-reprieve-strategy"
        },
        {
          "title": "Digital Omnibus Adopted: AI Act High-Risk Delayed to 2027",
          "url": "https://www.aiacto.eu/en/blog/digital-omnibus-ai-act-report-2027"
        },
        {
          "title": "EU AI Act Digital Omnibus: the high-risk delay explained",
          "url": "https://cmsdf.nimbuscode.tech/eu-ai-act-digital-omnibus-high-risk-delay/"
        }
      ]
    },
    "The Digital Omnibus is in force, and the high-risk deadlines moved, but several security-relevant obligations still fall due around the November–December 2026 window.\n\n- **Status:** Sources report that the Omnibus became Regulation (EU) 2026/1744, published in the Official Journal on July 24, 2026 and in force since July 27, 2026.\n- **High-risk delay:** Annex III stand-alone systems now have a later date of 2 December 2027, while AI embedded in regulated products under Annex I moves to 2 August 2028.\n- **Not a repeal:** Commentators stress that the requirements themselves remain. One says the Digital Omnibus does not remove the requirements — it delays their enforcement. A security-focused analysis notes that the underlying obligations — risk management, technical documentation, human oversight, and post-market monitoring — have not changed in substance.\n- **Near-term security dates:** Article 50 transparency duties were not deferred. One source says Article 50 applies since August 2, 2026: unchanged. A machine-readable marking grace period runs until December 2, 2026, only for systems placed on the market before August 2, 2026. The Omnibus also adds a new prohibition on systems generating non-consensual intimate imagery and child sexual abuse material, with its safeguard grace period running to December 2, 2026.\n- **Why it moved:** Harmonised standards were late. One source says the harmonised technical standards that grant presumption of conformity are not finished, with first publications not expected before late 2026.\n\nSources differ on framing. One headline says the EU AI Act has not been formally delayed, which reflects a distinction between the Act's general application and the high-risk timeline. Some sources also cite a 2 December 2026 effective date for high-risk obligations, which conflicts with the 2027 dates that most other sources give, so verify against the Official Journal text before relying on any single date."
  ],
  "durationSeconds": 7.779944986999967,
  "searchCount": 1
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{
  "url": "https://www.nature.com/nm/articles?type=article&year=2026",
  "prompt": "List Nature Medicine articles published 2 or 3 November 2026 with titles and URLs."
}

{
  "bytes": 838,
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  "result": "REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.\n\n    Original URL: https://www.nature.com/nm/articles?type=article&year=2026\n    Redirect URL (from the server's Location header — server-supplied, not verified): https://idp.nature.com/authorize?response_type=cookie&client_id=grover&redirect_uri=https%3A%2F%2Fwww.nature.com%2Fnm%2Farticles%3Ftype%3Darticle%26year%3D2026\n    Status: 303 See Other\n\n    To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:\n    - url: \"https://idp.nature.com/authorize?response_type=cookie&client_id=grover&redirect_uri=https%3A%2F%2Fwww.nature.com%2Fnm%2Farticles%3Ftype%3Darticle%26year%3D2026\"\n    - prompt: \"List Nature Medicine articles published 2 or 3 November 2026 with titles and URLs.\"",
  "durationMs": 295,
  "url": "https://www.nature.com/nm/articles?type=article&year=2026"
}

{
  "query": "North Korea AI crypto theft phishing new report November 2026",
  "mode": "extended"
}

{
  "query": "North Korea AI crypto theft phishing new report November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_014VwNpfDfxqHDWYBaetkZpq",
      "content": [
        {
          "title": "North Korean hackers used AI in crypto heists record $6bn Binance theft",
          "url": "https://thenextweb.com/news/north-korean-hackers-ai-crypto-heists-binance"
        },
        {
          "title": "[ED] North Korea's crypto heists threaten global security - The Korea Times",
          "url": "https://www.koreatimes.co.kr/opinion/editorial/20261103/ed-north-koreas-crypto-heists-threaten-global-security"
        },
        {
          "title": "FBI Links North Korea's TraderTraitor to Record $6.43 Billion Binance Crypto Heist",
          "url": "https://thehackernews.com/2026/11/fbi-links-north-koreas-tradertraitor-to.html"
        },
        {
          "title": "North Korea’s Hackers Use AI to Target Major Crypto Firms, Researchers Say",
          "url": "https://www.analyticsinsight.net/news/north-koreas-hackers-use-ai-to-target-major-crypto-firms-researchers-say"
        },
        {
          "title": "AI hacking — FBI Blames North Korea for $8 Billion Crypto Heist in 20 Minutes",
          "url": "https://en.koreadaily.com/ai-hacking-fbi-blames-north-korea-crypto-heist/"
        },
        {
          "title": "How North Korean Hacking Evolved: AI and Social Engineering Used to Target Binance",
          "url": "https://en.bloomingbit.io/feed/news/123434"
        },
        {
          "title": "North Korean Hackers Exploit AI to Steal Over $14 Billion in Crypto, Up 51% in 'Industrialized' Cybercrime — BigGo Finance",
          "url": "https://finance.biggo.com/news/cQZ2Kp4BoQmpnl364UtH"
        },
        {
          "title": "North Korea’s AI-Powered Hackers Are Redefining Crypto Crime",
          "url": "https://www.yahoo.com/news/articles/north-korea-ai-powered-hackers-120000766.html"
        },
        {
          "title": "Report: North Korean hackers stole a record $2.02B in crypto in 2025",
          "url": "https://www.yahoo.com/news/articles/report-north-korean-hackers-stole-014016987.html"
        }
      ]
    },
    "Coverage from the past day or two centers on the October 29 Binance theft, which the FBI attributed to North Korea's TraderTraitor group. Reported figures vary: one outlet cites $1.46 billion plundered from Bybit as the prior record, and others put the Binance loss around $6.3 billion, while The Hacker News reports $6.43 billion.\n\n- **Attribution and method:** The FBI attributed the October 29 Binance theft to North Korea's TraderTraitor operation in an October 31 alert. Researchers describe the group's approach as \"Big Game Hunting,\" selecting high-value crypto firms and focusing its attacks on them.\n- **AI and phishing:** Analysts say AI is being used to craft convincing lures, create fake personas, and evade detection. Microsoft described a campaign in which the actor used tailored domains, social media profiles, and industry-specific knowledge to pose as recruiters. One editorial warns that generative AI can produce fluent, natural-sounding messages, which makes phishing harder to spot.\n- **Broader trend:** Chainalysis estimated that North Korean hacking groups are estimated to account for 89% of reported crypto-hacking losses this year. A CrowdStrike report found North Korea-linked hackers stole $2.02 billion in cryptocurrency from the financial services industry in 2025, though that report is older (May).\n\nCaveat: I ran one search, so I haven't checked the original FBI alert or the Microsoft report directly. The loss figures differ across sources, and one Korean outlet's $8 billion figure is well above the others."
  ],
  "durationSeconds": 7.535605791999958,
  "searchCount": 1
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{
  "url": "https://www.courtlistener.com/?q=%22artificial+intelligence%22&type=r&order_by=dateFiled+desc&filed_after=11%2F02%2F2026",
  "prompt": "List court dockets or filings dated November 2 or 3, 2026 mentioning artificial intelligence, with case name, court, docket number and URL."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 210,
  "url": "https://www.courtlistener.com/?q=%22artificial+intelligence%22&type=r&order_by=dateFiled+desc&filed_after=11%2F02%2F2026"
}

{
  "command": "node scripts/fetch.js \"https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm\" --full > /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec/s1a_full.txt 2>&1; wc -c /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec/s1a_full.txt; head -c 300 /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec/s1a_full.txt",
  "description": "Fetch full Anthropic S-1/A via project fetch script"
}

{
  "stdout": "201269 /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec/s1a_full.txt\nHTTP 200 · https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm · text/html\nS-1/A\n1\nanthropicpbc-sx1ax1.htm\nS-1/A\n\nAnthropic, PBC - S-1/A-1\n\nAs filed with the Securities and Exchange Commission on November 2, 2026.\nRegistration No. 333-299633\n\nUNITED STATES\nSE",
  "stderr": "",
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && grep -oE '.{250}895\\.4.{250}' s1a_full.txt | head -5; echo \"---NINE/THREE MONTHS---\"; grep -oE '.{150}[Tt]hree months ended September 30, 2026.{300}' s1a_full.txt | head -8",
  "description": "Grep S-1/A for commitments and Q3 figures"
}

{
  "stdout": "---NINE/THREE MONTHS---",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "url": "https://finance.biggo.com/news/cQZ2Kp4BoQmpnl364UtH",
  "prompt": "Publication date, source report, all figures: $14 billion, 51%, who published."
}

{
  "bytes": 4286,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** May 15, 2026 (published 07:08:14 UTC, updated 07:16:35 UTC)\n\n**Source report:** CrowdStrike's annual threat report, released May 14, 2026\n\n**Who published:** The article is by the BigGo Editorial Team. The report is from CrowdStrike, a U.S. cybersecurity firm.\n\n**Figures:**\n- **$14 billion:** This appears only in the headline. The body text does not support it. The article reports $2.02 billion in 2025 cryptocurrency losses from the financial services industry by North Korea-linked hackers.\n- **51%:** The increase from the previous year. The table gives about $1.34 billion for 2024.\n- **$1.46 billion:** Stolen through a single software supply chain attack.\n- **43%:** Growth in global intrusions into financial institutions over two years.\n- **423 firms:** Financial services firms whose breaches were posted on ransomware leak sites in 2025, up 27% from 333 in 2024.\n- **About ¥320 billion:** The article's conversion of the $2.02 billion figure.",
  "durationMs": 5518,
  "url": "https://finance.biggo.com/news/cQZ2Kp4BoQmpnl364UtH"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -s -G \"https://www.ebi.ac.uk/europepmc/webservices/rest/search\" --data-urlencode 'query=((\"artificial intelligence\" OR \"machine learning\" OR \"large language model\" OR \"deep learning\") AND (FIRST_PDATE:[2026-11-02 TO 2026-11-03]))' --data-urlencode 'format=json' --data-urlencode 'pageSize=100' --data-urlencode 'resultType=lite' -o epmc.json -w \"%{http_code}\\n\" && python3 -I -c \"\nimport json\nd=json.load(open('epmc.json'))\nprint('hits',d['hitCount'])\nfor r in d['resultList']['result']:\n    print(r.get('firstPublicationDate'),'|',r.get('journalTitle'),'|',r.get('title')[:140],'|',r.get('doi'))\n\" 2>&1 | head -120",
  "description": "Query Europe PMC for AI papers published Nov 2-3 2026"
}

{"stdout":"200\nhits 603\n2026-11-03 | Cureus | Artificial Intelligence for Automated Analysis and Interpretation of Intravascular Ultrasound in Coronary Artery Disease: A Systematic Revie | None\n2026-11-02 | J Invest Dermatol | Patient attitudes toward artificial intelligence-driven dermatology. | 10.1016/j.jid.2026.08.008\n2026-11-02 | Am J Phys Med Rehabil | The Role of Artificial Intelligence in Treatment Planning in Physical and Rehabilitation Medicine: A Systematic Review. | 10.1097/phm.0000000000003193\n2026-11-03 | J Transl Int Med | Artificial intelligence-assisted bronchoscopy for the diagnosis and treatment of pulmonary diseases: Advances and clinical practice | None\n2026-11-02 | None | Deep Looking in Digital Pathology: An Explainable Federated Learning Framework for Lung Cancer Classification | 10.20944/preprints202611.0067.v1\n2026-11-03 | Front Artif Intell | From chronic kidney disease classification to genuine early prediction: a systematic review of artificial intelligence, methodological quali | None\n2026-11-03 | Front Immunol | Artificial intelligence-based decision support for axial spondyloarthritis integrating inflammatory and structural MRI information | None\n2026-11-03 | Front Public Health | Artificial intelligence applications in long-term care facilities: a scoping review across planning, design, operation, and assessment | None\n2026-11-03 | Front Genet | Deep learning-based genetic disease prediction with Monte Carlo (MC) dropout uncertainty estimation: a comparative study with classical mach | None\n2026-11-03 | Front Genet | Editorial: Bioinformatics and big data driving the discovery of clinical biomarkers for solid tumors and blood malignancies | None\n2026-11-02 | Turk J Obstet Gynecol | Machine learning prediction of IVF outcomes in unexplained infertility. | 10.4274/tjod.galenos.2026.10663\n2026-11-03 | Health Data Sci | A Scoping Review of Deep Learning Methods for Photoplethysmography Data | None\n2026-11-03 | Front Artif Intell | Data-based surrogate modeling and performance prediction of MEMS touch mode capacitive sensing using deep multilayer perceptron networks | None\n2026-11-02 | Mayo Clin Proc | Feature Selection and Machine Learning Strategies to Develop a Minimal Bioassay for Cholangiocarcinoma Subtype. | 10.1016/j.mayocp.2026.06.029\n2026-11-02 | Chem Soc Rev | Chemistry-transforming applications of artificial intelligence. | 10.1039/d4cs01100g\n2026-11-03 | Front Artif Intell | Two-stage transformer encoder and attention-guided GRU-based residual correction for short-term load forecasting | None\n2026-11-02 | None | Discrete Memoryless Channel Capacity Estimation using Deep Learning and 256QAM | 10.21203/rs.3.rs-9072677/v1\n2026-11-02 | None | Machine learning guided design of strong transcriptional activation domains | 10.64898/2026.10.30.763198\n2026-11-03 | Front Artif Intell | A hybrid CNN–BiLSTM network with additive attention for automated four-stage classification of Alzheimer's disease from brain MRI | None\n2026-11-02 | Pain | Toward precision pediatric pain care: integrating mechanistic science, real-world measurement, and patient partnership. | 10.1097/j.pain.0000000000004073\n2026-11-02 | Nanoscale | Epistemic uncertainty as a diagnostic probe for deep learning Hamiltonians. | 10.1039/d6nr02280d\n2026-11-03 | Front Neurol | Machine learning-based models to predict 90-day non-excellent functional outcomes among patients with mild acute ischemic stroke after intra | None\n2026-11-02 | ACS Appl Mater Interfaces | Conductive Composite-Based Wearable Sensors for Sports Science: Intelligent Data Analysis and Emerging Applications. | 10.1021/acsami.6c16362\n2026-11-02 | Hosp Pediatr | Precision Social Medicine: Bridging the Gap Between Social Care and Health Systems Integration. | 10.1542/hpeds.2026-009715\n2026-11-03 | Front Psychol | The mediating role of artificial intelligence perception and creative idea generation in the impact of sustainable leadership on digital tra | None\n2026-11-02 | None | A Hybrid Feature Fusion Framework for Just-in-Time Software Defect Prediction using LLM Reasoning and CodeBERT Embeddings | 10.21203/rs.3.rs-11300160/v1\n2026-11-03 | Front Plant Sci | AGC-YOLO: adaptive gated channel network for rice leaf disease detection | None\n2026-11-02 | Biomed Tech (Berl) | Depth-adaptive suppression of subject-dependent interference for robust cross-subject EEG emotion recognition. | 10.1515/bmt-2026-0393\n2026-11-02 | None | Advanced ECG Signal Analysis for Atrial Fibrillation Detection Using an LSTM Network | 10.20944/preprints202611.0053.v1\n2026-11-03 | Front Genet | Artificial intelligence assisted genomic profiling of ovarian cancer liver metastases | None\n2026-11-03 | Front Artif Intell | AFI-ID: adaptive feature intelligence for intrusion detection | None\n2026-11-03 | Front Oncol | Machine learning-assisted chemometric analysis of salivary ATR-FTIR spectra for the diagnosis of oral submucous fibrosis | None\n2026-11-03 | Front Digit Health | Enhanced vision language framework for medical report generation using agent-based retrieval | None\n2026-11-03 | Front Cardiovasc Med | Cross-cohort blood transcriptome analysis identifies an eight-gene diagnostic index and inflammatory programs in acute myocardial infarction | None\n2026-11-03 | Front Med (Lausanne) | TexTNet: a texture-guided hierarchical architecture for prostate cancer Gleason segmentation in whole slide images | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | J Transl Int Med | Hepatobiliary cancers digital twins: Integrating artificial intelligence-driven multi-omics with organoid dynamics | None\n2026-11-03 | Front Pharmacol | Zaizao Shengxue capsule for anemia: a prospective multicenter real-world study of hemoglobin response and predictive modeling | None\n2026-11-03 | Front Big Data | A retrieva
… [10069 more characters in events.jsonl]

{
  "query": "Recorded Future Insikt report AI November 2026",
  "mode": "extended"
}

{
  "query": "Recorded Future Insikt report AI November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01LyhTf9MkGQyqrD6vXYSVxN",
      "content": [
        {
          "title": "State of Security Report",
          "url": "https://www.recordedfuture.com/research/state-of-security"
        },
        {
          "title": "2026 State of Security Executive Insights Report",
          "url": "https://www.recordedfuture.com/resources/guides/state-of-security-executive-insights"
        },
        {
          "title": "Recorded Future releases 2026 State of Security report",
          "url": "https://decisioninsights.ai/recorded-future-releases-2026-state-of-security-report"
        },
        {
          "title": "Recorded Future",
          "url": "https://en.wikipedia.org/wiki/Recorded_Future"
        },
        {
          "title": "Recorded Future AI: The Next Evolution in Threat Intelligence",
          "url": "https://www.recordedfuture.com/blog/next-evolution-recorded-future-ai-powering-threat-intelligence"
        },
        {
          "title": "Recorded Future 2026 State of Security Report Warns Cyber Operations Have Become a Core Tool of Global Power",
          "url": "https://www.prnewswire.com/news-releases/recorded-future-2026-state-of-security-report-warns-cyber-operations-have-become-a-core-tool-of-global-power-302686566.html"
        },
        {
          "title": "Recorded Future Launches Impact and Metrics Dashboard",
          "url": "https://www.recordedfuture.com/blog/impact-metrics-dashboard"
        },
        {
          "title": "International AI Safety Report",
          "url": "https://en.wikipedia.org/wiki/International_AI_Safety_Report"
        },
        {
          "title": "Introducing Recorded Future AI: Boosting Security Defenses with AI-Driven Insights",
          "url": "https://www.recordedfuture.com/blog/introducing-recorded-future-ai"
        }
      ]
    },
    "I didn't find a Recorded Future Insikt Group report on AI dated November 2026. The closest match is the 2026 State of Security report, the group's annual threat landscape analysis, which covers AI as one of its themes.\n\n- **Main AI finding:** The report says fully autonomous AI cyber operations have not yet materialized, but AI is already amplifying deception, social engineering, and identity abuse at scale. It also states that AI is accelerating that dynamic not through autonomous attacks, but by scaling deception and eroding trust inside decision-making processes.\n- **Influence operations:** One prediction is that hacktivists and influence networks will use AI to flood the information environment with exaggerated or mixed-authenticity claims (Influence Operations Will Favor Volume Over Credibility).\n- **Recommendation:** The report's key insight is that organizations that act now to establish AI governance and prepare for post-quantum migration will hold significant advantages.\n- **Caveat on the date:** One Recorded Future page on the report is marked as about 263 days old and another as about 70 days old, so the publication is likely from earlier in 2026 rather than November. I couldn't confirm an exact release date.\n\nSources: Recorded Future's State of Security page (recordedfuture.com/research/state-of-security), the 2026 State of Security Executive Insights summary, and a PR Newswire release on the 2026 report."
  ],
  "durationSeconds": 6.4888762030000215,
  "searchCount": 1
}

{
  "query": "Japan Self-Defense Forces AI command control Palantir Maven Smart System Anduril Lattice Nikkei",
  "mode": "extended"
}

{
  "query": "Japan Self-Defense Forces AI command control Palantir Maven Smart System Anduril Lattice Nikkei",
  "results": [
    {
      "tool_use_id": "srvtoolu_01JTZHnWqbkqzqRsHksWR1XF",
      "content": [
        {
          "title": "Japan weighs use of Palantir, Anduril AI systems for defense forces - Nikkei Asia",
          "url": "https://asia.nikkei.com/politics/defense/japan-weighs-use-of-palantir-anduril-ai-systems-for-defense-forces"
        },
        {
          "title": "Palantir Eyes Japan's Military; Filing: 84% of Revenue Is US - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-palantir-eyes-japans-military-filing-84-of-revenue-is-us/"
        },
        {
          "title": "Japan Wants Palantir, Anduril AI in Its Military Decision Loop",
          "url": "https://thedefensepost.com/2026/08/11/japan-military-ai-palantir-anduril/"
        },
        {
          "title": "Japan Self-Defense Forces",
          "url": "https://en.wikipedia.org/wiki/Japan_Self-Defense_Forces"
        },
        {
          "title": "Japan Air Self-Defense Force",
          "url": "https://en.wikipedia.org/wiki/Japan_Air_Self-Defense_Force"
        },
        {
          "title": "Japan Weighs AI Defense Platforms for Modernization",
          "url": "https://itbusinesstoday.com/gov-tech/japan-weighs-ai-defense-platforms-for-modernization/"
        },
        {
          "title": "Japan Maritime Self-Defense Force",
          "url": "https://en.wikipedia.org/wiki/Japan_Maritime_Self-Defense_Force"
        },
        {
          "title": "Japan weighs controversial U.S. AI systems for military command",
          "url": "https://www.naturalnews.com/2026-08-07-japan-controversial-ai-military-command.html"
        },
        {
          "title": "Japan Considering Palantir and Anduril AI to Overhaul Military Decision-Making · Clash Report",
          "url": "https://clashreport.com/defense/articles/japan-considering-palantir-and-anduril-ai-to-overhaul-military-decision-making-shkk9tgj98f"
        }
      ]
    },
    "The search turned up consistent reporting that Tokyo is weighing U.S. AI for military command and control, though the details come mostly from secondhand coverage of Nikkei.\n\n- **The plan:** Japan's government is considering U.S.-made AI systems for command and control, mainly to speed up decisions and tighten integration with the U.S. military (considering deploying multiple U.S.-made artificial intelligence systems in command and control for Self-Defense Force units).\n- **Candidates:** Palantir's Maven Smart System and Anduril's Lattice are the named options (Tokyo is examining Palantir's Maven Smart System alongside Anduril's Lattice AI platform.). Lattice is described as specializing in fusing data from disparate sensors to construct a unified battlespace picture.\n- **Homegrown oversight layer:** One reported option is a domestic AI platform placed above the U.S. systems to supervise them (Tokyo could combine the two companies' AI systems for command-and-control (C2) operations while placing a homegrown AI platform above them to oversee their use.). Another report says defense officials are also assessing the deployment of a domestically engineered command center to govern the American platforms.\n- **Sovereignty concerns:** Nikkei reportedly describes a strong wish for domestic AI in defense, but also treats reliance on U.S. systems as unavoidable if capabilities are to be raised quickly (the government treats reliance on U.S. systems as \"unavoidable\" if capabilities are to be raised quickly, Nikkei reported.).\n- **Timing:** One report says the government plans to finalize the AI integration strategy before a scheduled year-end revision of three foundational national security documents.\n- **Palantir's CEO:** Per a secondhand account, Alex Karp told Nikkei in a November 2 interview that he wants to supply AI to the forces (he showed eagerness to supply AI systems to Japan's Self-Defense Forces). I could not access the original interview, which is paywalled.\n\n**Caveats:** The sources disagree on the original Nikkei date (August 4 in one, August 5 in another). Most coverage is aggregator or secondary reporting, and I did not reach the Nikkei article itself. One result (NaturalNews) is a low-reliability outlet and mainly relevant for its citation of Nikkei and a UN report on Palantir. The reporting describes options under consideration, not a signed contract or decision."
  ],
  "durationSeconds": 8.540204762999958,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && grep -n \"895\" s1a_full.txt | head; echo \"=== recursive ===\"; grep -oE '.{400}recursive self-improvement.{400}' s1a_full.txt | head -3; echo \"=== dramatically ===\"; grep -oE '.{300}dramatically accelerated progress.{300}' s1a_full.txt | head -3",
  "description": "Search S-1/A text for key passages"
}

{
  "stdout": "607:commenced, with an aggregate committed spend of a pproximately $895.4 billion , substantially all of which is\n2475:committed spend of approximately $895.4 billion , substantially all of which is related to compute and\n=== recursive ===\n=== dramatically ===",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://huggingface.co/papers/date/2026-11-02",
  "prompt": "List all paper titles with upvote counts and submitting org/institution shown."
}

{
  "bytes": 584471,
  "code": 200,
  "codeText": "OK",
  "result": "| # | Paper title | Upvotes | Org/institution shown |\n|---|---|---|---|\n| 1 | Does Scaling Toward AGI Depend on What System-1 Lets System-2 Execute? | 57 | Tsinghua University |\n| 2 | R^2Orch: Recursive Self-Improvement for Agent Orchestration via Self-Play within a Skill-Internalization Loop | 49 | Chinese University of Hong Kong, Shenzhen |\n| 3 | Apriel Voice 27B Preview: An Open Model for Speech, Reasoning, and Tool Use | 34 | ServiceNow-AI |\n| 4 | FrameForge: Harnessing Priors of Video Foundation Models for Unified Image Generation | 34 | FrameX-AI |\n| 5 | Latent Reasoning in Continuous Space for Unified Multimodal Models | 30 | KAIST AI |\n| 6 | Follow the Gradient: Tracing Safety Degradation Back to Training Data | 29 | DatologyAI |\n| 7 | ReLift: Dense 3D Tracking as Lifted Trajectory Repair | 24 | Technion Israel Institute of Technology |\n| 8 | Wizard: Manipulate Any World in Real Time via Agentic Control | 24 | Tencent |\n| 9 | HiFOR: Hierarchical Foresight with Action-Guided World Grounding for Vision-Language-Action Model | 24 | Not shown |\n| 10 | WeFair: Fidelity-Aware Alignment from Human Feedback for Personalized Query Rewriting in Short-Video Search | 23 | Tencent |\n| 11 | Venus-DefakerOne2: A Vision-Forensics Foundation Model with Broader Coverage | 20 | inclusionAI |\n| 12 | CEPO: A General Framework for Improving Prompt Optimization in Multi-Agent Systems | 20 | Not shown |\n| 13 | CaPtain: A Pipeline for Post-Training Code-as-Policy Robot Agents | 19 | Chinese University of Hong Kong |\n| 14 | REA: A Routed Embodied Agent Runtime for Asynchronous Brain-Cerebellum Control | 17 | Not shown |\n| 15 | Probing Spatial State Representations in Visual Foundation Models | 16 | MMLab@NTU |\n| 16 | WorldBridge: Bridging Video and Action for Task Generalization in World Action Models | 13 | Not shown |\n| 17 | GLOW-FM: Efficient Generative Low-Light Image Enhancement with One-Step Latent Flow Matching | 10 | Arm |\n| 18 | When Requirements Interact: Scaling Long-Horizon Coding via Interdependent Specifications | 9 | Xiaomi MiMo |\n| 19 | HALO: Human-Grounded Granular Evaluation of Proactive Agents | 8 | 2077AI |\n| 20 | On the Origin and Evolution of Training-Inference Mismatch in LLM Reinforcement Learning | 8 | George Washington University |\n| 21 | MemSteer: Turning User Histories into Supervision for Agent Memory Optimization | 6 | Microsoft Research |\n| 22 | RoboArchitect: Automating the Design of Robotic Agents with Persistent Memory | 6 | Not shown |\n| 23 | SOMA: A Benchmark for Fine-Grained Egocentric Behavior and Body-Motion Understanding | 5 | Mathis Group @ EPFL |\n| 24 | GEPA-Curator: Curated Learning for Self Improving Agents | 5 | UC Berkeley |\n| 25 | OSWAM: An Effective World Action Model with One-Step Action Generation | 5 | The Hong Kong Polytechnic University |\n| 26 | Supervising the Visible State: Separating Representation from View Selection in Streaming Video | 5 | LINs lab |\n| 27 | No Channels Left Behind: Understanding Diffusion Acceleration through Residual Gates | 5 | Not shown |\n| 28 | Think Twice: The Metis-1.6 Technical Report | 4 | Lernex |\n| 29 | VoxLock: Target-Speaker Extraction for Voice Agents Without an Enrollment Step | 4 | Not shown |\n| 30 | SciGame: Let Agents Play the Scientific Discovery Games in the Real and Counterfactual World | 3 | Not shown |\n| 31 | TernScope: Model-Hardware Co-Design for Efficient Ternary Endoscopic Segmentation | 3 | Monash University |\n| 32 | CausalWAM: Learning the Causes of Actions in World Action Models | 3 | Causal Intelligence |\n| 33 | rTaste: Do Research Agents Have Taste? Evaluating Early Stage Research Judgment | 2 | Not shown |\n| 34 | TurnTurk-GPT: Text-Based Turn-Taking Prediction for Turkish | 2 | Not shown |\n| 35 | Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling | 2 | KAIST AI |\n| 36 | TSFLab: A Self-Improving Agent-Agnostic Workbench for Time Series Forecasting Research | 1 | Data to Intelligence (D2I) Group @ UH |\n| 37 | AuditFL: A Contract-Backed Clearing Layer for Open Federated Learning | – | HKUST |\n\nNotes:\n- Upvotes are the count shown beside each submitter's name. Entry 37 shows no count.\n- The page shows the institution badge attached to each paper, not a separate field for the submitter's organization. \"Not shown\" means no badge appears on the listing.",
  "durationMs": 18391,
  "url": "https://huggingface.co/papers/date/2026-11-02"
}

{
  "query": "\"3 November 2026\" AI security report deepfake agent",
  "mode": "extended"
}

{
  "query": "\"3 November 2026\" AI security report deepfake agent",
  "results": [
    {
      "tool_use_id": "srvtoolu_01AWyJvMyWusA9oCyT5tfHYb",
      "content": [
        {
          "title": "Political Deepfakes 2026: AI in Campaigns Report",
          "url": "https://www.resemble.ai/resources/2026-political-deepfake-report"
        },
        {
          "title": "How AI attacks and defends against hackers in 2026, report finds",
          "url": "https://qz.com/ai-cyberattacks-defense-2026-world-economic-forum"
        },
        {
          "title": "2026 Cybersecurity Threat Report",
          "url": "https://ironscales.com/2026-cybersecurity-threat-report-white-paper"
        },
        {
          "title": "AI Brief - November 2, 2026 - Sam on AI",
          "url": "https://samonai.substack.com/p/ai-brief-november-2-2026"
        },
        {
          "title": "IRONSCALES Report Finds AI Agents Are Becoming a New Target for Phishing",
          "url": "https://www.unite.ai/ironscales-2026-threat-report-ai-agents-phishing/"
        },
        {
          "title": "Everything That Happened in AI Today Tuesday, November 3",
          "url": "https://www.theneuron.ai/digest/everything-that-happened-in-ai-today-tuesday-november-3-2026/"
        },
        {
          "title": "Experian’s new fraud forecast warns agentic AI, deepfake job candidates and cyber break-ins are top threats for 2026",
          "url": "https://www.experianplc.com/newsroom/press-releases/2026/experian-s-new-fraud-forecast-warns-agentic-ai--deepfake-job-can"
        },
        {
          "title": "International AI Safety Report",
          "url": "https://en.wikipedia.org/wiki/International_AI_Safety_Report"
        },
        {
          "title": "2026 AI Threat Landscape Report",
          "url": "https://www.hiddenlayer.com/report-and-guide/threatreport2026"
        }
      ]
    },
    "The search didn't turn up a security report dated 3 November 2026 that covers deepfakes and AI agents together. The closest matches are a daily news digest from that date and several reports from the preceding weeks.\n\n- **Daily digest (3 November):** The Neuron's roundup for that day highlights WIRED's investigation into hundreds of apps with hidden deepfake-creation tools, and says OpenAI and Anthropic set up teams to monitor election misinformation. Anthropic warned that AI-assisted research may soon accelerate dramatically, per the same digest.\n- **Deepfake apps (WIRED, reported 2 November):** Per a Substack brief, WIRED links more than 400 apps and domains to a network of sexually abusive deepfake services hidden behind ordinary products. Apple removed 19 of them after WIRED's findings, and the brief notes that parts of the network had already been covered by Danish journalists in September.\n- **Political deepfakes (Resemble AI, dated 2 November):** Resemble AI's 2026 political content report says it tracked 481 AI incidents in politics, and that most political disinformation could not be traced to its source.\n- **Agentic AI security (IRONSCALES, October 2026):** Its threat report finds that a large share of organizations have seen an AI agent act on malicious or unauthorized content. The survey is company-commissioned, and only a small fraction of organizations have security teams approving AI agents.\n- **Agentic AI intrusions (WEF coverage, updated October 8):** An article on a WEF report describes a state-sponsored campaign in which an AI coding agent carried out most of the intrusion work against roughly 30 targets.\n\nIf you were looking for a specific report published on 3 November, I'd suggest checking the publisher's site directly, since none of the results confirm one."
  ],
  "durationSeconds": 8.372377356000012,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '595,625p' s1a_full.txt; echo \"###############\"; sed -n '2465,2485p' s1a_full.txt",
  "description": "Print S-1/A commitment passages"
}

{
  "stdout": "Our Approach to Compute . We manage compute as a single, fungible pool from multiple strategic partners, and\nwe dynamically direct available compute between workloads based on where the marginal unit is expected to be\nmost productive at any given time. We believe that this approach to compute enables us to deliver superior\nmodels, serve more customers, and achieve greater productivity from our compute investment. This compute\nefficiency creates the foundation for us to advance the frontier of AI capabilities through research and model\ndevelopment, meet growing demand from customers, and provide for internal usage of Claude. We have\nachieved this through our research breakthroughs and our multi-chip compute architecture across AWS\nTrainium, Google TPUs, NVIDIA GPUs, and AMD GPUs, enabling us to orchestrate workloads to optimize for\nprice and performance. To support our research, model development, customer demand, and internal usage of\nClaude, we continue to invest at scale. As of and subsequent to September 30, 2026, we have entered into\npurchase commitments and lease agreements, including short-term commitments, as well as leases not yet\ncommenced, with an aggregate committed spend of a pproximately $895.4 billion , substantially all of which is\nrelated to compute and infrastructure. These commitments include approximately $447.5 billion expected to be\nincurred before December 31, 2030, and substantially all of the remainder is expected to be incurred between\n2031 and 2045. Approximately $69.8 billion of these commitments are due in the 1 2 months following\nSeptember 30, 2026 . See the section titled “Management’s Discussion and Analysis of Financial Condition and\nResults of Operations—Liquidity and Capital Resources—Contractual Obligations” for more information.\nEnterprise Strategy. Our enterprise strategy is built on the belief that frontier AI is most valuable in real-world\nsettings, as deployment across enterprises is where economic impact is greatest and where the improvement\nloop from customer feedback is richest. Accordingly, we have organized our research priorities, our product\nroadmap, and our go-to-market and Applied AI teams around enterprise use cases, which range from routine\nknowledge work to the most complex problems. The customer feedback we gather directs our research focus\nand makes Claude more capable over time. This broadens where Claude can be deployed and further expands\nenterprise adoption, which helps ensure that the benefits of our AI reach people and organizations at scale.\nAI is Transforming Intelligence\nWe believe that Powerful AI, a highly capable and impactful form of frontier AI characterized by the following\nkey attributes, will become widely available within a few years:\n• cognitive capabilities matching or exceeding those of top human experts across most professional and\nscientific disciplines;\n• the ability to navigate all interfaces available to a human working virtually, including text, audio, video,\n###############\nexecution of our suppliers, and the performance of hardware in new facility environments. Delays in securing\nenergy, water, and other critical services for these facilities could further slow the pace at which newly\ncommissioned compute becomes available for use. Errors in forecasting any of these transition-related\nvariables could compound our risks related to securing sufficient compute and result in either capacity\nshortfalls or underutilized capacity during the transition period.\nWe have entered into, and expect to continue to enter into, long-term agreements for compute and related\nresources that involve minimum purchase commitments, take-or-pay provisions, and other terms that obligate\nus to pay for resources regardless of actual utilization. These commitments represent substantial fixed\nobligations. As of and subsequent to September 30, 2026, we have entered into purchase commitments and\nlease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate\ncommitted spend of approximately $895.4 billion , substantially all of which is related to compute and\ninfrastructure. These commitments include approximately $447.5 billion expected to be incurred before\nDecember 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045.\nApproximately $69.8 billion of these commitments are due in the 12 months following September 30, 2026. See\nthe section titled “Management’s Discussion and Analysis of Financial Condition and Results of Operations—\nLiquidity and Capital Resources—Contractual Obligations” for more information.\nOur ability to meet the substantial and growing financial obligations of these requirements to secure compute\ndepends on our ability to generate significant revenue growth. We must grow our customer base and expand\nrevenue rapidly in order to generate the cash flows necessary to satisfy these commitments. However, our\nrevenue is primarily consumption-based, and much of it is not subject to long-term contractual commitments,\nwhile our compute and infrastructure commitments generally extend over multiple years. As a result, we may",
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -s -G \"https://www.ebi.ac.uk/europepmc/webservices/rest/search\" --data-urlencode 'query=((\"artificial intelligence\" OR \"machine learning\" OR \"large language model\" OR \"deep learning\" OR \"neural network\") AND FIRST_PDATE:[2026-11-02 TO 2026-11-03] AND (JOURNAL:\"Lancet\" OR JOURNAL:\"N Engl J Med\" OR JOURNAL:\"JAMA\" OR JOURNAL:\"Nature\" OR JOURNAL:\"Science\" OR JOURNAL:\"BMJ\" OR JOURNAL:\"Nat Med\" OR JOURNAL:\"Lancet Digit Health\" OR JOURNAL:\"Radiology\" OR JOURNAL:\"Ann Intern Med\" OR JOURNAL:\"Circulation\" OR JOURNAL:\"JAMA Netw Open\" OR JOURNAL:\"JAMA Intern Med\" OR JOURNAL:\"JAMA Pediatr\" OR JOURNAL:\"Nat Biotechnol\" OR JOURNAL:\"Cell\" OR JOURNAL:\"NEJM AI\" OR JOURNAL:\"Nat Commun\" OR JOURNAL:\"npj Digit Med\" OR JOURNAL:\"Lancet Oncol\" OR JOURNAL:\"Eur Heart J\" OR JOURNAL:\"Gastroenterology\" OR JOURNAL:\"JAMA Oncol\" OR JOURNAL:\"JAMA Cardiol\" OR JOURNAL:\"Nat Mach Intell\" OR JOURNAL:\"Sci Transl Med\"))' --data-urlencode 'format=json' --data-urlencode 'pageSize=100' --data-urlencode 'resultType=lite' -o epmc2.json -w \"%{http_code}\\n\" && python3 -I -c \"\nimport json\nd=json.load(open('epmc2.json'))\nprint('hits',d['hitCount'])\nfor r in d['resultList']['result']:\n    print(r.get('firstPublicationDate'),'|',r.get('journalTitle'),'|',r.get('title')[:160],'|',r.get('doi'),'|',r.get('pmid'))\n\"",
  "description": "Query Europe PMC restricted to major journals"
}

{
  "stdout": "200\nhits 0",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
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}

{
  "query": "WIRED investigation hundreds apps hidden deepfake nudify network Apple removed",
  "mode": "extended"
}

{
  "query": "WIRED investigation hundreds apps hidden deepfake nudify network Apple removed",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Q8BkY6pxbX6THGS1zjYLJE",
      "content": [
        {
          "title": "WIRED traces 400+ AI apps hiding abusive deepfake tools",
          "url": "https://aiweekly.co/alerts/wired-traces-400-ai-apps-hiding-abusive-deepfake-tools"
        },
        {
          "title": "A hidden network of nudifying tools was found lurking inside harmless looking AI apps - Digital Trends",
          "url": "https://www.digitaltrends.com/computing/hidden-network-of-sexual-deepfake-generators-inside-harmless-ai-apps/"
        },
        {
          "title": "AI apps with hidden sexual and violent deepfake features made it into the App Store",
          "url": "https://9to5mac.com/2026/11/02/ai-apps-with-hidden-sexual-and-violent-deepfake-features-made-it-into-the-app-store/"
        },
        {
          "title": "Apple, Meta Act on a Deepfake Network of 400+ Apps and Sites - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-apple-meta-act-on-a-deepfake-network-of-400-apps-and-sites/"
        },
        {
          "title": "AI Deepfake Scam: 400+ Apps Hide Abusive Tools on App Stores",
          "url": "https://www.analyticsinsight.net/news/ai-deepfake-scam-400-apps-hide-abusive-tools-on-app-stores"
        },
        {
          "title": "Hundreds of AI Apps on Google Play and App Store Hid Nudify Tools",
          "url": "https://www.androidpure.com/nudify-apps-google-play-app-store/"
        },
        {
          "title": "WIRED Finds Hundreds of AI Apps That Hid Abusive Deepfake Features",
          "url": "https://mlq.ai/news/wired-finds-hundreds-of-ai-apps-that-hid-abusive-deepfake-features/"
        },
        {
          "title": "Hundreds of Innocent-Looking AI Apps Secretly Hid Sexual Deepfake Tools, Researchers Find as Apple Pulls 19",
          "url": "https://www.ibtimes.com.au/ai-app-network-hidden-deepfake-tools-1877759"
        },
        {
          "title": "Nudify Apps Exposed: The Brutal Network Behind Innocent AI Apps",
          "url": "https://www.progressiverobot.com/2026/11/02/nudify-apps-exposed-network/"
        }
      ]
    },
    "The WIRED investigation, published November 2, 2026, found a network of more than 400 connected apps and domains that posed as everyday AI tools while hiding deepfake generators.\n\n- **The network:** Sources describe apps that looked like pet-photo editors, language tutors, and workout coaches. The apps normally show benign content, but a server check can activate the hidden features. Downloading the app after tapping an ad for the deepfake functionality on Meta platforms appears to be one of the triggers. Researchers at AI Forensics and Infoblox worked with the reporters on the investigation, per one source.\n- **Apple's response:** Apple removed 19 apps, including the pet-photo app Viefur, after reporters shared details. Apple said \"We review every app before it's published, and these apps complied with our rules when we reviewed them,\" per a spokesperson quoted by WIRED. Apple also told Wired it has suspended tens of thousands of apps for \"bait-and-switch\" tactics over the last year.\n- **Policy changes:** One source says Apple updated its guidelines to tighten restrictions on apps that conceal functionality during review, with a new Section 1.2 covering nonconsensual intimate imagery and guideline 2.5.19 covering hidden, dormant, or undocumented features. Sources disagree on the date: one says October 16, another says October 17.\n- **Other platforms:** Google did not respond to Wired's request for comment, \"though it had removed the majority of the apps ahead of being contacted.\" Meta said it acted against 11,600 ad accounts and 15,000 pages linked to the network.\n- **Ongoing concern:** Yet similar ads kept resurfacing even as WIRED wrapped up its investigation. Sources also link the network to Chinese developers and a Hong Kong entity called KeLing Technology Limited, which reportedly scrubbed its online presence after being contacted.\n\nCaveats: these figures come from secondary coverage (aggregators and news sites), not the WIRED article itself, which I did not retrieve. Some sources say Apple removed the apps after WIRED contacted it and others say after WIRED shared details. Also, Wired does not say how much money the network made or how many people paid through Apple or Google Pay."
  ],
  "durationSeconds": 7.325483523999981,
  "searchCount": 1
}

{
  "url": "https://www.resemble.ai/resources/2026-political-deepfake-report",
  "prompt": "Publication date and all figures: incidents tracked, breakdown by type/country, attribution rates."
}

{
  "bytes": 143062,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** The page gives two dates. The report's metadata and embedded code list October 30, 2026, while the visible byline reads November 2, 2026.\n\n**Scope:** 481 incidents of AI-generated media involving politicians, governments, and elections, from November 1, 2025 to October 14, 2026.\n\n**Disinformation and attribution:**\n- 276 of the 481 incidents were disinformation, meaning AI media presented as real.\n- For 190 of those 276 (69%), coverage named no creator or first sharer, so the source couldn't be identified.\n- Of the 86 with a known source, politicians or campaigns posted 33, foreign state actors 21, private individuals 15, government accounts 9, and PACs or advocacy groups 8.\n\n**Attack incidents and labeling:**\n- 206 incidents were made to attack or discredit someone. Campaigns, PACs, and government accounts posted 98 of them (48%).\n- 79 AI posts came from those accounts, and 21 (27%) carried the poster's own AI label.\n\n**Country breakdown:** Untraceable disinformation targeted politicians or citizens in 49 countries. India had the most (38), followed by the US (33). The page doesn't give figures for other countries.\n\n**Volume over time:** Incidents rose to about 70 a month from May 2026 onward, nearly five times the earlier rate of about 15 a month.\n\n**Election timing:** Across 157 attacks with an election within 180 days, the rate was 0.7 a day from 91 to 180 days before a vote, 0.7 a day from 31 to 90 days out, and 1.5 a day in the final 30 days.\n\n**Not in the page:** The full breakdown by incident type (integrity class, goal, and source) is only in the paid report, so the page doesn't provide it.",
  "durationMs": 7508,
  "url": "https://www.resemble.ai/resources/2026-political-deepfake-report"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && echo \"=== imminently ===\"; grep -oE '.{500}imminently.{500}' s1a_full.txt | head -2; echo; echo \"=== September 30 revenue ===\"; grep -n \"September 30, 2026\" s1a_full.txt | head -20",
  "description": "Grep S-1/A for RSI language and Q3 revenue"
}

{
  "stdout": "=== imminently ===\n\n=== September 30 revenue ===\n570:2023 to $17.0 billion for the three months ended September 30, 2026 . This rapid and growing adoption\n605:Claude, we continue to invest at scale. As of and subsequent to September 30, 2026, we have entered into\n611:September 30, 2026 . See the section titled “Management’s Discussion and Analysis of Financial Condition and\n735:categories of knowledge work and deepen our presence across the enterprise. As of September 30, 2026,\n755:frontier of AI. Our customer base as of September 30, 2026 includes:\n825:September 30, 2026. Diffusion also accelerates as our models become more capable and efficient,\n838:demonstrated by TTM revenue per employee of over $6.6 million as of September 30, 2026, compared\n842:enabled us to access capital and secure compute from investors and partners. As of September 30, 2026, we had\n1485:common stock outstanding as of September 30, 2026, which reflects:\n1516:stock outstanding as of September 30, 2026 exclude the following:\n1518:shares of our Class A common stock outstanding as of September 30, 2026, with a weighted-average\n1521:outstanding as of September 30, 2026, but for which (i) the service-based vesting condition was not\n1526:after September 30, 2026;\n1528:after September 30, 2026 in connection with our acquisitions of privately-held companies; and\n1534:awards that were issued after September 30, 2026 (the “Pledge Issuance”);\n1539:Restated 2021 Stock Plan (our “2021 Plan”) as of September 30, 2026, which number of shares will\n1557:As of September 30, 2026\n1620:RSUs granted after September 30, 2026\n1656:• no exercise of outstanding stock options or settlement of outstanding RSUs subsequent to September 30, 2026, other than the RSU Settlement;\n1669:summary consolidated balance sheet data as of September 30, 2026, from our unaudited interim consolidated",
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '565,575p' s1a_full.txt; echo \"=== balance/summary fin ===\"; sed -n '1665,1700p' s1a_full.txt; echo \"=== rev per emp ===\"; sed -n '835,845p' s1a_full.txt",
  "description": "Print S-1/A revenue and summary financial sections"
}

{
  "stdout": "culture, our frontier and safety research, our approach to compute, and our enterprise strategy, it is one of the\ncore advantages that set us apart. These advantages enable us to continuously advance frontier AI and shape\nthe standards for its safe and responsible development. Our frontier AI, Claude, is delivered to customers\nthrough our models, platform, and applications. Claude has experienced the fastest enterprise adoption of any\ntechnology in history, as demonstrated by revenue growing from $0 at commercial launch in the first quarter of\n2023 to $17.0 billion for the three months ended September 30, 2026 . This rapid and growing adoption\ngenerates two self-reinforcing dynamics—an improvement loop that advances Claude and an investment loop\nthat helps fund our continued research in frontier AI.\nOur Core Advantages\nMission & Focus . All of our efforts are guided by a singular focus on our mission. This focus enables us to\nconcentrate talent, research, and compute investment on the highest-value work for humanity and to avoid\n=== balance/summary fin ===\nThe following tables summarize our consolidated financial and other data. We have derived the summary\nconsolidated statements of operations data for the years ended December 31, 2023, 2024, and 2025 from our\naudited consolidated financial statements included elsewhere in this prospectus. We have derived the summary\nconsolidated statements of operations data for the nine months ended September 30, 2025 and 2026, and the\nsummary consolidated balance sheet data as of September 30, 2026, from our unaudited interim consolidated\nfinancial statements included elsewhere in this prospectus. The summary consolidated financial data in this\nsection are not intended to replace our consolidated financial statements and related notes and are qualified in\ntheir entirety by our consolidated financial statements and related notes included elsewhere in this prospectus.\nOur historical results are not necessarily indicative of the results that may be expected in the future and our\nresults for the nine months ended September 30, 2026 are not necessarily indicative of the results that may be\nexpected for the full year ending December 31, 2026 or any other period. The following summary consolidated\nfinancial and other data should be read in conjunction with the section titled “Management’s Discussion and\nAnalysis of Financial Condition and Results of Operations” and our consolidated financial statements and\nrelated notes thereto included elsewhere in this prospectus.\nConsolidated Statements of Operations Data\n\nYear Ended December 31,\n\nNine Months Ended September\n30,\n\n(in millions, except share and per share\namounts)\n\n2023\n\n2024\n\n2025\n\n2025\n\n2026\n\nRevenue\n\n=== rev per emp ===\n• Operating Efficiency . Our operating efficiency, derived from our high talent density, our efficient go-\nto-market, and how extensively our teams leverage Claude in their work, enables us to scale with a\nsmaller team relative to other large enterprise technology companies. Our operating efficiency is\ndemonstrated by TTM revenue per employee of over $6.6 million as of September 30, 2026, compared\nto $1.4 million as of September 30, 2025.\nThe demonstrated growth, scale, and efficiency of our financial model help us to continue making significant\nlong-term investments to build frontier AI responsibly. Our business trajectory and financial profile have\nenabled us to access capital and secure compute from investors and partners. As of September 30, 2026, we had\nraised an aggregate of $141.1 billion of capital and had cash and cash equivalents of $95.6 billion and short-\nterm investments of $36.3 billion .\nOur Self-Reinforcing Loops",
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{
  "command": "node scripts/fetch.js \"https://www.wired.com/story/hidden-network-of-ai-apps-nudify-deepfake/\" 2>&1 | head -30; echo \"=== 9to5 ===\"; node scripts/fetch.js \"https://9to5mac.com/2026/11/02/ai-apps-with-hidden-sexual-and-violent-deepfake-features-made-it-into-the-app-store/\" 2>&1 | head -60",
  "description": "Fetch WIRED and 9to5Mac deepfake app articles"
}

{
  "stdout": "HTTP 403 · https://www.wired.com/story/hidden-network-of-ai-apps-nudify-deepfake/ · text/plain\nBlocked by egress policy\n=== 9to5 ===\nHTTP 200 · https://9to5mac.com/2026/11/02/ai-apps-with-hidden-sexual-and-violent-deepfake-features-made-it-into-the-app-store/ · text/html\nAI apps with hidden sexual and violent deepfake features made it into the App Store\n\nSkip to main content\n\n- App Store\n\n- AI\n\n# AI apps with hidden sexual and violent deepfake features made it into the App Store\n\nBen Lovejoy | Nov 2 2026 - 4:31 am PT\n\n11 Comments\n\nHundreds of AI apps with hidden sexual and violent deepfake features made it into Apple’s App Store after passing app review. The same apps were also available in the Google Play Store.\n\nAn investigation discovered more than 400 apps, apparently created by a single Chinese organization. The apps allow users to upload photos and then generate sexual and violent deepfakes which could be used to humiliate or threaten victims …\n\nA Wired investigation discovered a network of more than 400 connected domains and apps with hidden abusive functionality.\n\nApps like Viefur [ostentibly used to add clothing to pet photos] often claim to be everyday services—such as language tuition or AI workout coaches. When accessed under certain conditions, however, apps in the network stealthily load a web interface allowing the generation of explicit AI sexual images and videos using photos users upload. The apps include AI scenes such as “bedroom rape” and “threatening knife,” where a man holds a knife to a woman’s neck.\n\n# Top comment by MiW\n\nLiked by 7 people\n\nI feel like this going to be a never ending cat and mouse game. Much like Apple has always had with jailbreaks.\n\nView all comments\n\nWired says that the network is “hiding in plain sight,” thanks to thousands of video ads for them published on Facebook and Instagram. Some of the apps have been around for a year and have passed review by Apple, Google, and Meta despite each having clear policies prohibiting harmful deepfake content.\n\nBait-and-switch tactics were used to pass app review. The apps normally show benign content, but a server check can activate the hidden features. Downloading the app after tapping an ad for the deepfake functionality on Meta platforms appears to be one of the triggers. Dozens of pornography photo and video templates can then be downloaded, with credits purchased to generate deepfakes from user-uploaded photos.\n\nApple removed 19 apps after Wired shared details.\n\nWe review every app before it’s published, and these apps complied with our rules when we reviewed them. After approval, their developers changed the website the app pulls its content from, replacing what we approved with pornographic content, and promoted it through pornographic ads hosted on a third-party platform.\n\nThe company recently strengthened protections against this approach. Meta says it has taken action against more than 10,000 ad accounts linked to domains associated with these apps.\n\n- iPhone Duo cases\n\n- Beats Woven USB-C cables\n\n- Certified refurbished Apple products 15% off at apple.com\n\n- Discounted AirPods Pro 3\n\n- Wireless CarPlay adapter\n\n- 10-year AirTag battery case\n\n- Logitech MX Master 4 for Mac\n\nFTC: We use income earning auto affiliate links. More.\n\nYou’re reading 9to5Mac — experts who break news about Apple and its surrounding ecosystem, day after day. Be sure to check out our homepage for all the latest news, and follow 9to5Mac on Twitter , Facebook , and LinkedIn to stay in the loop. Don’t know where to start? Check out our exclusive stories , reviews , how-tos , and subscribe to our YouTube channel\n\nCheck out 9to5Mac on YouTube for more Apple news:",
  "stderr": "",
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  "noOutputExpected": false
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '1700,1790p' s1a_full.txt",
  "description": "Print S-1/A consolidated statements of operations table"
}

{
  "stdout": "$ 41\n\n$ 386\n\n$ 4,585\n\n$ 2,545\n\n$ 33,242\n\nOperating expenses:\n\nCompute and infrastructure\n\n433\n\n2,522\n\n7,326\n\n4,381\n\n18,808\n\nPersonnel (1)\n\n95\n\n454\n\n1,839\n\n1,027\n\n4,863\n\nBartz settlement\n\n—\n\n—\n\n1,500\n\n1,500\n\n—\n\nSales, marketing, and partnerships\n\n2\n\n43\n\n568\n\n322\n\n5,529\n\nOther operating and administrative\n\n62\n\n347\n\n1,412\n\n539\n\n5,302\n\nTotal operating expenses\n\n592\n\n3,366\n\n12,645\n\n7,769\n\n34,502\n\nOperating loss\n\n(551)\n\n(2,980)",
  "stderr": "",
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{
  "url": "https://huggingface.co/papers?q=Follow+the+Gradient+Tracing+Safety+Degradation",
  "prompt": "Find \"Follow the Gradient: Tracing Safety Degradation Back to Training Data\" and give its arXiv ID and date."
}

{
  "bytes": 1873309,
  "code": 200,
  "codeText": "OK",
  "result": "I can't find \"Follow the Gradient: Tracing Safety Degradation Back to Training Data\" in the page content you provided. The content is truncated after the site navigation and subscription prompt, so the paper listing isn't included. I can't give its arXiv ID or date without that information.\n\nIf you share the rest of the page, or the paper's arXiv listing, I can pull out the ID and date.",
  "durationMs": 2427,
  "url": "https://huggingface.co/papers?q=Follow+the+Gradient+Tracing+Safety+Degradation"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '1790,1870p' s1a_full.txt",
  "description": "Print more of S-1/A operations table"
}

{
  "stdout": "(8,060)\n\n(5,224)\n\n(1,260)\n\nInterest income\n\n69\n\n106\n\n431\n\n239\n\n2,359\n\nChange in fair value of convertible\nnotes, derivative liabilities, and SAFEs\n\n(1,045)\n\n(5,434)\n\n(34,308)\n\n(20,107)\n\n(94,324)\n\nOther income (expense), net\n\n(2)\n\n—\n\n(8)\n\n(3)\n\n(10,397)\n\nTotal other income (expense), net\n\n(978)\n\n(5,328)\n\n(33,885)\n\n(19,871)\n\n(102,362)\n\nLoss before provision for income taxes\n\n(1,529)\n\n(8,308)\n\n(41,945)\n\n(25,095)\n\n(103,622)\n\nProvision for income taxes\n\n2\n\n1\n\n20\n\n12\n\n417\n\nNet loss (2)",
  "stderr": "",
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I -c \"\nimport json\nseen=set()\nd=json.load(open('epmc.json'))\nprint('total hits',d['hitCount'])\n\" ; for p in 2 3 4 5 6 7; do curl -s -G \"https://www.ebi.ac.uk/europepmc/webservices/rest/search\" --data-urlencode 'query=((\"artificial intelligence\" OR \"machine learning\" OR \"large language model\" OR \"deep learning\") AND (FIRST_PDATE:[2026-11-02 TO 2026-11-03]))' --data-urlencode 'format=json' --data-urlencode 'pageSize=100' --data-urlencode \"page=$p\" --data-urlencode 'resultType=lite' -o epmc_p$p.json; done; python3 -I -c \"\nimport json,glob\nkeep=['Lancet','N Engl','JAMA','Nature','Nat ','Science','BMJ','NEJM','npj','Radiology','Ann Intern','Circulation','Eur Heart','Cell','Sci Transl','Gut','Gastroenterology','Blood','Diabetes Care','Ann Oncol','J Clin Oncol','Health Aff','Clin Infect','Am J Psychiatry','Lancet Digit','PLoS Med','Nat Med','Nat Mach']\nfor f in sorted(glob.glob('epmc_p*.json')):\n    d=json.load(open(f))\n    for r in d['resultList']['result']:\n        j=r.get('journalTitle') or ''\n        if any(j.startswith(k) or k in j for k in keep):\n            print(r.get('firstPublicationDate'),'|',j,'|',r.get('title')[:150],'|',r.get('doi'))\n\"",
  "description": "Paginate Europe PMC and filter for major journals"
}

{"stdout":"total hits 603\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None\n2026-11-03 | Front Cell Dev Biol | DeepFusion-HSK: a multimodal deep learning for subtype classification of herpes simplex keratitis with multicenter validation | None\n2026-11-03 | Front Cell Infect Microbiol | An integrated approach to prioritizing areas for imported malaria re-establishment prevention in Chongqing, China | None","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":290,"oldLines":3,"newStart":290,"newLines":8,"lines":[" {\"t\":\"2026-11-03T11:12:50.424Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"afb0755d99de3a80e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01G1UcGo9rBSNPaAf7GPaSeK\",\"duration_ms\":38,\"input\":{\"command\":\"cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && echo \\\"=== imminently ===\\\"; grep -oE '.{500}imminently.{500}' s1a_full.txt | head -2; echo; echo \\\"=== September 30 revenue ===\\\"; grep -n \\\"September 30, 2026\\\" s1a_full.txt | head -20\",\"description\":\"Grep S-1/A for RSI language and Q3 revenue\"},\"response\":{\"stdout\":\"=== imminently ===\\n\\n=== September 30 revenue ===\\n570:2023 to $17.0 billion for the three months ended September 30, 2026 . This rapid and growing adoption\\n605:Claude, we continue to invest at scale. As of and subsequent to September 30, 2026, we have entered into\\n611:September 30, 2026 . See the section titled “Management’s Discussion and Analysis of Financial Condition and\\n735:categories of knowledge work and deepen our presence across the enterprise. As of September 30, 2026,\\n755:frontier of AI. Our customer base as of September 30, 2026 includes:\\n825:September 30, 2026. Diffusion also accelerates as our models become more capable and efficient,\\n838:demonstrated by TTM revenue per employee of over $6.6 million as of September 30, 2026, compared\\n842:enabled us to access capital and secure compute from investors and partners. As of September 30, 2026, we had\\n1485:common stock outstanding as of September 30, 2026, which reflects:\\n1516:stock outstanding as of September 30, 2026 exclude the following:\\n1518:shares of our Class A common stock outstanding as of September 30, 2026, with a weighted-average\\n1521:outstanding as of September 30, 2026, but for which (i) the service-based vesting condition was not\\n1526:after September 30, 2026;\\n1528:after September 30, 2026 in connection with our acquisitions of privately-held companies; and\\n1534:awards that were issued after September 30, 2026 (the “Pledge Issuance”);\\n1539:Restated 2021 Stock Plan (our “2021 Plan”) as of September 30, 2026, which number of shares will\\n1557:As of September 30, 2026\\n1620:RSUs granted after September 30, 2026\\n1656:• no exercise of outstanding stock options or settlement of outstanding RSUs subsequent to September 30, 2026, other than the RSU Settlement;\\n1669:summary consolidated balance sheet data as of September 30, 2026, from our unaudited interim consolidated\",\"stderr\":\"\",\"interrupted\":false,\"isImage\":false,\"noOutputExpected\":false}}"," {\"t\":\"2026-11-03T11:12:54.233Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"afb0755d99de3a80e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01DwRKJoUzHdQykGYH9GYd5b\",\"duration_ms\":43,\"input\":{\"command\":\"cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '565,575p' s1a_full.txt; echo \\\"=== balance/summary fin ===\\\"; sed -n '1665,1
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{
  "url": "https://www.digitaltrends.com/computing/hidden-network-of-sexual-deepfake-generators-inside-harmless-ai-apps/",
  "prompt": "Publication date and time; the WIRED article URL it links to; key figures."
}

{
  "bytes": 310216,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date and time:** November 2, 2026, 6:40 PM\n\n**WIRED article URL:** https://www.wired.com/story/hundreds-of-mundane-ai-apps-are-hiding-abusive-deepfake-features/\n\n**Key figures:**\n- **400+** connected apps and domains in the network, according to AI Forensics.\n- **100,000+** downloads for one popular app before Google removed it.\n- **19** more apps removed by Apple after WIRED's findings.\n- Meta has taken action against **11,600** ad accounts, **5,200** users, and blocked **209** apps tied to the scheme.\n- The EU's ban on nudifier apps takes effect in about one month.",
  "durationMs": 3634,
  "url": "https://www.digitaltrends.com/computing/hidden-network-of-sexual-deepfake-generators-inside-harmless-ai-apps/"
}

{
  "query": "wired.com nudify apps network 400 domains Infoblox AI Forensics investigation",
  "mode": "standard"
}

{
  "query": "wired.com nudify apps network 400 domains Infoblox AI Forensics investigation",
  "results": [
    {
      "tool_use_id": "srvtoolu_01KdyPHSRBYHyY7NzSP5Py8S",
      "content": [
        {
          "title": "VexTrio Unveiled: Global Cybercrime Enterprise Exposed As Sophisticated Multinational Ad-Fraud Operation",
          "url": "https://www.scoop.co.nz/stories/SC2508/S00031.htm"
        },
        {
          "title": "a foundational block of modern cybercrime the inside story of a 15 000 website network using popular ad trackers to peddle ai investment scams",
          "url": "https://www.techradar.com/pro/a-foundational-block-of-modern-cybercrime-the-inside-story-of-a-15-000-website-network-using-popular-ad-trackers-to-peddle-ai-investment-scams"
        },
        {
          "title": "Analyzing the AI Nudification Application Ecosystem",
          "url": "https://seclab.cs.georgetown.edu/bibliography/DBLP_conf/uss/GibsonOBCBTRK25.html"
        },
        {
          "title": "Apple and Google reportedly still offer dozens of AI ‘nudify’ apps",
          "url": "https://www.engadget.com/ai/apple-and-google-reportedly-still-offer-dozens-of-ai-nudify-apps-192712446.html"
        },
        {
          "title": "Close Menu",
          "url": "https://techcentral.co.za/apps-ai-undress-women-photos-soaring/236596"
        },
        {
          "title": "Investigation finds dozens of AI “nudify” apps operating across the App Store and Google Play",
          "url": "https://www.mobilemarketingreads.com/?p=50019"
        },
        {
          "title": "www.taipeitimes.com",
          "url": "https://www.taipeitimes.com/News/world/archives/2023/12/09/2003810383"
        },
        {
          "title": "A Network of AI 'Nudify' Sites Are a Front for Notorious Russian Hackers",
          "url": "https://eu-west-3.democraticunderground.com/10143316366"
        },
        {
          "title": "Nudify apps on Apple and Google stores are earning millions, claims probe, and Elon Musk has a question about it",
          "url": "https://www.wionews.com/trending/nudify-apps-on-apple-and-google-stores-are-earning-millions-claims-probe-and-elon-musk-has-a-question-about-it-ai-apps-news-1776348457365/amp"
        },
        {
          "title": "nudify apps plan to dominate deepfake",
          "url": "https://techbargains6.blogspot.com/2025/07/nudify-apps-plan-to-dominate-deepfake.html"
        },
        {
          "title": "aitopics.org",
          "url": "https://aitopics.org/tag/nudify"
        },
        {
          "title": "gnwcq 2025 8 4 infoblox unveils 2025 dns threat landscape report revealing surge in ai driven threats and malicious adtech",
          "url": "https://business.mammothtimes.com/mammothtimes/article/gnwcq-2025-8-4-infoblox-unveils-2025-dns-threat-landscape-report-revealing-surge-in-ai-driven-threats-and-malicious-adtech"
        },
        {
          "title": "Threat Actor Parades As Legitimate Adtech Enterprise",
          "url": "https://www.scoop.co.nz/stories/BU2509/S00307.htm"
        },
        {
          "title": "www.aicerts.ai",
          "url": "https://www.aicerts.ai/news/?p=15699"
        },
        {
          "title": "texxr.com",
          "url": "https://texxr.com/887512"
        },
        {
          "title": "Infoblox unveils surge in DNS-based cyberthreats and AI-enabled evasion tactics",
          "url": "https://msp-channel.com/news/70486/infoblox-unveils-surge-in-dns-based-cyberthreats-and-ai-enabled-evasion-tactics"
        },
        {
          "title": "ai pps undress women photos soaring in use",
          "url": "https://fortune.com/2023/12/08/ai-pps-undress-women-photos-soaring-in-use/"
        },
        {
          "title": "gnwcq 2025 8 4 infoblox unveils 2025 dns threat landscape report revealing surge in ai driven threats and malicious adtech",
          "url": "https://stocks.observer-reporter.com/observerreporter/article/gnwcq-2025-8-4-infoblox-unveils-2025-dns-threat-landscape-report-revealing-surge-in-ai-driven-threats-and-malicious-adtech"
        }
      ]
    },
    "I couldn't find the Wired article or any report matching a network of 400 nudify domains tied to Infoblox and AI Forensics. The Infoblox results cover other operations: ad-fraud and malvertising. One result describes a four-month analysis of malicious activity by Infoblox and Confiant that found roughly 15,500 domains linked to malicious tracker deployments, but it is about AI investment scams, not nudify sites.\n\nRelated nudify coverage I did find:\n\n- **App stores:** A Tech Transparency Project investigation found dozens of nudify apps on both app stores. Per one report, the investigation found 46 such apps on the Apple Store and 49 on Google Play, and Apple removed 15 apps and Google suspended seven after the findings were shared.\n- **Website network:** A 404 Media report described a network of AI 'nudify' sites linked to Russian hackers, and noted that the registrar for most of the sites blocked the domains after being contacted.\n- **Clothoff ownership:** Der Spiegel reportedly found that Clothoff today owns at least 10 other nudify services.\n- **Traffic scale:** Graphika reported that in September alone, 24 million people visited undressing websites (2023 figure).\n\nIf you have the Wired link, I can search for its exact headline or check whether the 400-domain figure appears in a different outlet's coverage."
  ],
  "durationSeconds": 5.790833982000011,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '1870,1890p' s1a_full.txt; echo \"=== RSP ===\"; grep -n \"Responsible Scaling\" s1a_full.txt | head; echo \"=== tail ===\"; tail -c 400 s1a_full.txt",
  "description": "Print net loss line and check RSP mentions"
}

{
  "stdout": "Net loss (2)\n\n$ (1,531)\n\n$ (8,309)\n\n$ (41,965)\n\n$ (25,107)\n\n$ (104,039)\n\nNet loss per share attributable to common\nstockholders, basic and diluted\n\n$ (1.42)\n\n$ (5.43)\n\n$ (23.04)\n\n=== RSP ===\n2268:our Responsible Scaling Policy’s definition of “dramatically accelerated progress attributable to AI.” We have\n2271:and will release further reports in the future as we set forth in our Responsible Scaling Policy. If our capabilities\n=== tail ===\nsearch and transparency, we disclose information about\nthe capability and safety of our models, the safeguards that we have adopted with respect to our models, and\ninstances of misuse of our technology, such as the September 2025 cyberattack described above. We also\npublish model sy\n\n… [truncated: 1,399,795 of 1,599,795 characters not shown. Re-run with --full if what you need is further down.]",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && sed -n '2255,2285p' s1a_full.txt",
  "description": "Print S-1/A RSI risk factor passage"
}

{
  "stdout": "systems to write production code, conduct research, and build subsequent model versions deepens, any\nsystemic flaw, bias, or error in our current models could propagate into the next versions of models and\nproducts built using those systems, compounding across successive versions of Claude models in ways that may\nbe difficult to detect or remediate. If we are unable to manage the foregoing risks, our ability to deploy the most\nadvanced, capable, and useful AI models could be adversely affected.\nIn addition, our increasing use of AI systems to accelerate our own research and development may cause the\ncapabilities of our models to advance more rapidly than our ability to develop, validate, and implement\ncorresponding safety, alignment, and security measures. Much of our evidence regarding the pace of such AI-\ndriven acceleration is derived from lagging indicators, and our ability to forecast or measure the rate at which\nour capabilities are advancing, including any acceleration attributable to our most recent or unreleased models,\nis limited. As a result, we have in the past not identified, and may in the future not identify, a significant\nacceleration in our rate of development until after it has occurred. For example, our internal estimates and our\nexpectations regarding future models, rather than our current models, indicate that we may imminently meet\nour Responsible Scaling Policy’s definition of “dramatically accelerated progress attributable to AI.” We have\nnot designated any of our current models as exceeding this threshold, and we continue to assess the underlying\ndata. We are also evaluating the implications of meeting the AI research and development capability threshold\nand will release further reports in the future as we set forth in our Responsible Scaling Policy. If our capabilities\nwere to outpace our safety, alignment, and security measures, or if we were unable to anticipate the pace of such\nadvancement, we may be unable to adequately assess or mitigate the resulting risks, which could increase the\nlikelihood of safety incidents, regulatory intervention, or reputational harm, and could adversely affect our\nbusiness, financial condition, and results of operations. In light of these uncertainties, including limits on our\nability to observe the pace at which our capabilities are advancing, we have adopted, and may continue to adopt,\nprecautionary safety, alignment, and security measures to allow our safety efforts to advance together with\nmodel capabilities. In the past these measures have included delaying the release of models and limiting their\ninitial availability, such as with Mythos through Project Glasswing, and in the future, as we learn more about\nmodel capabilities and behavior, they could include additional measures that affect whether, how, and when we\ndevelop or deploy new models or capabilities. We cannot predict with precision when we will determine that\nsuch measures are necessary, what measures will be required, or how long they will remain in place, and as the\ncapabilities of our models advance, such measures may become more frequent and more costly. These measures\ncould slow our capability gains relative to competitors that do not adopt similar constraints, and could\nadversely affect our competitive position, revenue growth, and results of operations.",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "node scripts/fetch.js \"https://www.wired.com/story/hundreds-of-mundane-ai-apps-are-hiding-abusive-deepfake-features/\" 2>&1 | head -45",
  "description": "Fetch WIRED deepfake apps article"
}

{
  "stdout": "HTTP 403 · https://www.wired.com/story/hundreds-of-mundane-ai-apps-are-hiding-abusive-deepfake-features/ · text/plain\nBlocked by egress policy",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && grep -n -oE '.{300}(Mythos|Glasswing).{300}' s1a_full.txt | head -6",
  "description": "Grep S-1/A for Mythos and Glasswing mentions"
}

{
  "stdout": "",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "AHA Scientific Sessions 2026 AI late-breaking trial November 2026",
  "mode": "extended"
}

{
  "query": "AHA Scientific Sessions 2026 AI late-breaking trial November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_012aSjideYB5DMoE4pYR3P2L",
      "content": [
        {
          "title": "AHA 2026 Late-Breaking Trials: Key Insights Revealed",
          "url": "https://www.radcliffecardiology.com/news/aha-scientific-sessions-2026-late-breaking-trials-revealed"
        },
        {
          "title": "American Heart Association announces late-breaking research for Scientific Sessions 2026",
          "url": "https://cardiovascularbusiness.com/topics/professional-associations/cardiology-associations/american-heart-association-aha/american-heart-association-announces-late-breaking-research-scientific-sessions-2026"
        },
        {
          "title": "Late-Breaking Science - Professional Heart Daily",
          "url": "https://professional.heart.org/en/meetings/scientific-sessions/programming/late-breaking-science"
        },
        {
          "title": "Scientific Sessions 2026 Public Newsroom",
          "url": "https://newsroom.heart.org/events/scientific-sessions-2026-public-newsroom"
        },
        {
          "title": "Virtual Programming - Professional Heart Daily",
          "url": "https://professional.heart.org/en/meetings/scientific-sessions/programming/virtual-programming"
        },
        {
          "title": "Overview of trials from AHA 2021",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491393/"
        },
        {
          "title": "CRISPR Therapeutics to Present Late-Breaking Data at the American Heart Association (AHA) Scientific Sessions 2026",
          "url": "https://www.globenewswire.com/news-release/2026/10/08/3377269/0/en/crispr-therapeutics-to-present-late-breaking-data-at-the-american-heart-association-aha-scientific-sessions-2026.html"
        },
        {
          "title": "Scientific Sessions - Professional Heart Daily",
          "url": "https://professional.heart.org/en/meetings/scientific-sessions"
        },
        {
          "title": "#ScientificSessions26 Late-Breaking Science announced",
          "url": "https://sessions.hub.heart.org/home/article/22975212/scientificsessions26-latebreaking-science-announced"
        }
      ]
    },
    "The AI-focused late-breaking content at AHA Scientific Sessions 2026 is in the Artificial Intelligence in the Diagnosis of Cardiovascular Disease session (LBS.06). The meeting runs November 6–9, 2026, at McCormick Place in Chicago.\n\n- **Session and trials:** The AI session is listed as LBS.06 in the program. Its listed presentation is AI-Assisted Comprehensive Echocardiographic Interpretation, a blinded, randomized controlled trial. Other AI-related late-breakers include an AI-Enabled Tele-ECG study on identifying structural heart disease in underserved populations (PROVAR+ External Validation Study) and a study on risk stratification using AI-enabled coronary plaque analysis and FFR-CT in over 269,000 patients. A third item, WATCH-LV, covers consumer smartwatch AI-enabled electrocardiography for left ventricular systolic dysfunction.\n- **Timing:** Sources disagree on the day. One program listing places the AI session on Sunday, November 8, 2026, while another gives Monday, so check the official Online Program Planner before scheduling.\n- **Scope:** The AI session sits within a broader program of 23 late-breaking presentations across six sessions. Per the AHA newsroom, select late-breaking presentations and symposia will be livestreamed."
  ],
  "durationSeconds": 6.835414686999982,
  "searchCount": 1
}

{
  "query": "Health Canada EMA artificial intelligence guidance November 2026",
  "mode": "extended"
}

{
  "query": "Health Canada EMA artificial intelligence guidance November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Nj8D1aJoiDcAvXPeB4tQZg",
      "content": [
        {
          "title": "Pre-market guidance for machine learning-enabled medical devices - Canada.ca",
          "url": "https://www.canada.ca/en/health-canada/services/drugs-health-products/medical-devices/application-information/guidance-documents/pre-market-guidance-machine-learning-enabled-medical-devices.html"
        },
        {
          "title": "FDA & EMA Good AI Practice Guide for Drug Development",
          "url": "https://intuitionlabs.ai/articles/fda-ema-good-ai-practice-drug-development-2"
        },
        {
          "title": "Selected 2026 Healthcare AI Regulation Updates: U.S. and Canada",
          "url": "https://www.veroscribe.com/blog/healthcare-ai-regulation-tracker"
        },
        {
          "title": "AI in Healthcare Regulatory Updates (Nov 29 - Dec 12, 2025)",
          "url": "https://aihealthcarecompliance.com/weekly-news-and-updates-nov-29-dec-12-2025/"
        },
        {
          "title": "Artificial intelligence",
          "url": "https://www.ema.europa.eu/en/about-us/how-we-work/data-regulation-big-data-other-sources/artificial-intelligence"
        },
        {
          "title": "EMA and FDA issue joint AI guidance for medicine development",
          "url": "https://www.europeanpharmaceuticalreview.com/news/270259/ema-fda-joint-ai-guidance-medicine-development/"
        },
        {
          "title": "EMA, FDA issue joint AI guiding principles for drug developers",
          "url": "https://www.raps.org/news-and-articles/news-articles/2026/1/ema-fda-issue-joint-ai-guiding-principles-for-drug"
        },
        {
          "title": "2026 EMA’s Principles for Good AI Practice",
          "url": "https://medicover-mics.com/ai-in-clinical-trials/emas-principles-for-good-ai-practice/"
        },
        {
          "title": "Health Canada Pre-market Guidance for ML-enabled Medical Devices",
          "url": "https://www.regdesk.co/blog/health-canada-pre-market-guidance-for-ml-enabled-medical-devices/"
        }
      ]
    },
    "The search didn't turn up any Health Canada or EMA AI guidance dated November 2026. The most recent items are from earlier in the year.\n\n**Health Canada:**\n- Its main AI-related document is pre-market guidance for machine learning-enabled medical devices, published April 1, 2026. It says data used to develop or validate such devices should be justified as representative of the Canadian population and clinical practice (Data referred to or used by manufacturers should be justified as adequately representative of the Canadian population and clinical practice.).\n- It is specifically intended for manufacturers submitting new applications or amendments for ML-enabled devices classified as Class II, III, or IV.\n- A news roundup says Health Canada also issued guidance on AI-generated content in device submissions in July 2026. I couldn't verify this against the original Health Canada source.\n\n**EMA and FDA:**\n- In January 2026, the two agencies published a joint set of ten guiding principles for good AI practice in medicine development. They cover how artificial intelligence technologies should be designed, validated, monitored, and governed throughout the medicines lifecycle.\n- EMA's AI reflection paper from 2024 is the basis for future EU AI guidance, according to a European Pharmaceutical Review report (The principles identified by the EMA and FDA support ongoing development of future EU AI guidance, building on the EMA AI reflection paper published in 2024.).\n- EMA's AI page lists an AI Observatory report with a reference number dated 2026, but the snippet doesn't show its title or date.\n\n**Caveat:** Today is November 3, 2026, so none of these results cover this month. Check canada.ca and ema.europa.eu directly for anything newly published."
  ],
  "durationSeconds": 7.713859271000023,
  "searchCount": 1
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad/sec && grep -c \"Mythos\" s1a_full.txt; grep -n \"Mythos\" s1a_full.txt | head; echo \"---\"; awk 'NR>=2270 && NR<=2280' s1a_full.txt | tr '\\n' ' ' | fold -w 200",
  "description": "Count Mythos mentions in S-1/A"
}

{
  "stdout": "1\n2279:initial availability, such as with Mythos through Project Glasswing, and in the future, as we learn more about\n---\ndata. We are also evaluating the implications of meeting the AI research and development capability threshold and will release further reports in the future as we set forth in our Responsible Scaling \nPolicy. If our capabilities were to outpace our safety, alignment, and security measures, or if we were unable to anticipate the pace of such advancement, we may be unable to adequately assess or miti\ngate the resulting risks, which could increase the likelihood of safety incidents, regulatory intervention, or reputational harm, and could adversely affect our business, financial condition, and resu\nlts of operations. In light of these uncertainties, including limits on our ability to observe the pace at which our capabilities are advancing, we have adopted, and may continue to adopt, precautiona\nry safety, alignment, and security measures to allow our safety efforts to advance together with model capabilities. In the past these measures have included delaying the release of models and limitin\ng their initial availability, such as with Mythos through Project Glasswing, and in the future, as we learn more about model capabilities and behavior, they could include additional measures that affe\nct whether, how, and when we",
  "stderr": "",
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{
  "query": "AI surveillance police facial recognition ICE contract November 2 2026",
  "mode": "extended"
}

{
  "query": "AI surveillance police facial recognition ICE contract November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01LFEMMkSkmLA8wJLXu3oJYF",
      "content": [
        {
          "title": "ICE awards Clearview AI $9.2M facial recognition contract",
          "url": "https://www.biometricupdate.com/202509/ice-awards-clearview-ai-9-2m-facial-recognition-contract"
        },
        {
          "title": "ICE contracts with Clearview AI for facial-recognition technology",
          "url": "https://immpolicytracking.org/policies/reported-ice-contracts-with-clearview-ai-for-facial-recognition-technology/"
        },
        {
          "title": "ICE Awards $9.2 Million Clearview AI Contract for Facial Recognition Investigations - ID Tech",
          "url": "https://idtechwire.com/ice-awards-9-2-million-clearview-ai-contract-for-facial-recognition-investigations/"
        },
        {
          "title": "ICE awards Bi2 $25M contract for 1,570 biometric scanners",
          "url": "https://www.theregister.com/public-sector/2026/05/29/ice-awards-bi2-25m-contract-for-1570-biometric-scanners/5248733"
        },
        {
          "title": "ICE Spends Millions on Clearview AI Facial Recognition to Find People ‘Assaulting’ Officers",
          "url": "https://www.404media.co/ice-spends-millions-on-clearview-ai-face-recognition-to-find-people-assaulting-officers/"
        },
        {
          "title": "Controversies involving ICE and private businesses",
          "url": "https://en.wikipedia.org/wiki/Controversies_involving_ICE_and_private_businesses"
        },
        {
          "title": "ICE’s crackdown has created a gold rush. Some Massachusetts businesses are cashing in. - The Boston Globe",
          "url": "https://www.bostonglobe.com/2026/10/27/business/ice-contracts-massachusetts-businesses-profit/"
        },
        {
          "title": "ICE Just Bought Access to 60 Billion Stolen Faces",
          "url": "https://stateofsurveillance.org/articles/government/clearview-ai-ice-contract-60-billion-faces-2025/"
        },
        {
          "title": "ICE To Pay Up To $10 Million For Clearview Facial Recognition To Investigate Agent Assaults",
          "url": "https://www.forbes.com/sites/thomasbrewster/2025/09/08/ice-to-pay-10-million-for-clearview-facial-recognition-to-investigate-agent-assaults/"
        }
      ]
    },
    "I found no reporting dated November 2, 2026 specifically, so I can't confirm a contract from that exact day. The closest recent items are below.\n\n- **Most recent (late October 2026):** A Boston Globe piece says BI2 Technologies, based in Plymouth, has secured the largest contract with ICE in the state, worth $25 million. It describes a mobile app that lets agents scan people's eyes and identify them using facial recognition.\n- **The BI2 deal in more detail:** The Register reported that US immigration cops have doled out about $25.1 million to a company called Bi2 Technologies for 1,570 biometric recognition devices. It also noted that the devices can provide ICE agents with access to Bi2's Inmate Recognition and Identification System, which matches biometrics to a database of more than five million booking, arrest, and incarceration records.\n- **Clearview AI (September 2025):** ICE's Homeland Security Investigations entered into a $9.2 million contract with Clearview AI for software. 404 Media reported that the records explicitly say ICE is buying the tech to investigate \"assaults against law enforcement officers.\"\n- **CBP:** Per Wired (as cited by one tracker), CBP has a $225,000 contract with Clearview AI for \"facial recognition technology and access to a database of over 60+ billion publicly available images\".\n- **Oversight:** A DHS spokesperson said contract decisions are reviewed to ensure the technology ICE adopts is \"consistent with all applicable law enforcement policies and standards.\" Separately, one related headline notes that Senators Urge ICE to Halt Mobile Fortify Facial Recognition Over Privacy and Accuracy Risks.\n\nCaveat: several of these sources are from 2025 or earlier and are secondary aggregators. If you need the November 2, 2026 events specifically, a search with a different date phrasing or a check of DHS procurement records would be the next step."
  ],
  "durationSeconds": 7.6830286309999645,
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{
  "url": "https://huggingface.co/papers/date/2026-11-03",
  "prompt": "List all paper titles with their arXiv IDs (if shown) and upvote counts and institution badges."
}

{
  "bytes": 539269,
  "code": 200,
  "codeText": "OK",
  "result": "Below are the 32 papers listed on the page (Nov 3 Daily Papers). Upvotes come from the count next to each paper link. \"Not shown\" means the page displays no count.\n\n| Title | arXiv ID | Upvotes | Institution badge |\n|---|---|---|---|\n| \"Wave Forcing: Towards Speed-of-Light Streaming Video Generation\" | 2611.00859 | 68 | DENG Lab @ SJTU |\n| \"Video Generation Meets Agent Harness: Agentic Video Generation, Agentic World Modeling and Recursive Self-Improvement\" | 2610.40191 | 30 | Video Rebirth |\n| \"CoworkOS:Scaling Agent Coworkers for Real-world Automation\" | 2611.03178 | 46 | Renmin University of China |\n| \"Democratizing Robot-Use Agents: A Unified Harness with Open Models\" | 2611.01560 | 7 | None |\n| \"CUA-Master: Scaling Computer-use Agents through Open-World Recursive Improvements\" | 2611.03126 | 44 | None |\n| \"NorthCUA Technical Report: Turbocharging Computer-Use Agents through Experience at Scale\" | 2611.02102 | 14 | beipo-ai |\n| \"Lost in Recovery: Demystifying Recovery Behavior of Computer-Use Agents via Goal-Oriented Action Replay\" | 2610.27954 | 3 | KAIST AI |\n| \"Reviso: Not All Visual Evidence Deserves Equal Attention in Video Captioning\" | 2611.03602 | Not shown | None |\n| \"From Fragmentation to Fusion: A Survey and Roadmap for Omnimodal Embeddings\" | 2611.00172 | 19 | CodeFuse AI |\n| \"CrossSWE: Benchmarking Cross-Repository Joint Development for Coding Agents\" | 2611.01484 | Not shown | None |\n| \"PhotoGuider: Composition-Aware Cropping and 360° View Framing with Explainable Photographic Assessments\" | 2611.02897 | 18 | None |\n| \"Avatar Intelligence: Amplifying Human Agency Through Persistent Personal Agents\" | 2611.03092 | Not shown | Shanghai Jiao Tong University |\n| \"Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning\" | 2610.39419 | 1 | None |\n| \"DecisionRank: On-Policy Distillation for Decision-Model Rerankers\" | 2610.42128 | Not shown | Meta |\n| \"FLAMIA: FLAsh MIcroscaling Attention for Fast and Causally Safe Training on Blackwell\" | 2611.03344 | 0 | Yandex Research |\n| \"DeFT-RAG: Decomposing Multi-Hop Questions into Self-Contained Sub-Questions with Reusable Answers\" | 2610.37826 | 1 | None |\n| \"WorldFlow: Joint Video and 3D Motion Prediction via Large-Scale Pretraining\" | 2610.39278 | 17 | None |\n| \"BYOD: Build Your Own DLM - Efficient Autoregressive-to-Diffusion Language Model Conversion\" | 2610.41574 | 0 | University Medical Center Utrecht |\n| \"MAServeBench: Benchmarking Multi-Agent LLM Serving Systems with Hierarchical Collaboration Workloads\" | 2610.40293 | 0 | Peking University |\n| \"Measuring AI Agents as Teammates with Collaborative Intelligence\" | 2611.02633 | 15 | Stanford University |\n| \"TinyAstral: Transferring Self-Evolving Harnesses to Tiny Generalist Manipulation Agents\" | 2610.41216 | 3 | None |\n| \"Self-Improvement with Auxiliary Rewards: Learning from Verified Traces and Evaluating Transfer\" | 2610.41296 | Not shown | Georgia Institute of Technology |\n| \"Advances in Agentic Computer Graphics\" | 2611.01860 | Not shown | University of Texas at Austin |\n| \"Lab2Sim: Turning Real-World Experiment Videos into Interactive Virtual Experiments\" | 2611.02928 | 0 | The Hong Kong Polytechnic University |\n| \"Library of Layers (LoL): Adaptively Ordering Transformer Layers at Runtime\" | 2611.03526 | 6 | None |\n| \"On-Policy Self-Distillation with Teacher Evolution\" | 2610.38637 | Not shown | UCAS |\n| \"ProVe: Proposer-Verifier Decoding\" | 2610.27815 | Not shown | None |\n| \"Can Large Language Model Agents Learn by Watching Tutorial Videos?\" | 2611.01460 | Not shown | University College London |\n| \"SIMIT: Self-Improving Vision-Language Models via Imagination at Test-Time\" | 2611.00053 | 8 | Technical University of Denmark |\n| \"When Does Latent Prediction Error Support Physical Surprise Claims in Video World Models?\" | 2611.01815 | Not shown | None |\n| \"TaoMate-FVSR:Audio-Guided Facial Video Restoration\" | 2611.03393 | Not shown | TaoLive AIGC |\n| \"When Morphs Look Better: Face Image Quality as a Training-Free Signal for Morphing Attack Detection\" | 2611.00074 | 0 | Fraunhofer IGD |\n| \"Can Coding Agents Sustain Continual Evolution without Forgetting?\" | 2611.03219 | 0 | None |",
  "durationMs": 23977,
  "url": "https://huggingface.co/papers/date/2026-11-03"
}

{
  "query": "AI biosecurity biosafety report November 2026 model evaluation",
  "mode": "extended"
}

{
  "query": "AI biosecurity biosafety report November 2026 model evaluation",
  "results": [
    {
      "tool_use_id": "srvtoolu_01NNGXyfjy1SgC5KDrHYyYpj",
      "content": [
        {
          "title": "Artificial intelligence and biosecurity: capabilities, threat pathways, and",
          "url": "https://arxiv.org/pdf/2609.16213"
        },
        {
          "title": "BioTIER: A Refusal Benchmark for Targeted Biological Risk Mitigation",
          "url": "https://arxiv.org/pdf/2607.14479"
        },
        {
          "title": "https://crsreports.congress.gov Updated August 3, 2026",
          "url": "https://www.congress.gov/crs_external_products/IF/PDF/IF13269/IF13269.3.pdf"
        },
        {
          "title": "Managing Biological Risks from General-Purpose AI Models under the EU AI Act",
          "url": "https://www.governance.ai/research-paper/managing-biological-risks-from-general-purpose-ai-models-under-the-eu-ai-act"
        },
        {
          "title": "Biosecurity Evaluations on Model Reports",
          "url": "https://securebio.org/benchmarks/models/"
        },
        {
          "title": "Red-Teaming AI Systems for Biosecurity Risks",
          "url": "https://biosecurityhandbook.com/ai-biosecurity/red-teaming.html"
        },
        {
          "title": "Towards a Common Standard for Evaluating Frontier AI Safeguards Against Biological Misuse",
          "url": "https://www.governance.ai/research-paper/technical-report-towards-a-common-standard-for-evaluating-frontier-ai-safeguards-against-biological-misuse"
        },
        {
          "title": "How AI Amplifies Biosecurity Risk",
          "url": "https://biosecurityhandbook.com/ai-biosecurity/ai-risk-amplifier.html"
        },
        {
          "title": "LLMs and Information Hazards",
          "url": "https://biosecurityhandbook.com/ai-biosecurity/llms-info-hazards.html"
        }
      ]
    },
    "I didn't find a report dated November 2026. The most recent relevant item is a GovAI report from October 19, 2026, and the rest are earlier 2026 publications.\n\n- **EU AI Act biological risk report (GovAI, Oct. 2026):** The report presents nine recommendations to make biological risk assessments more comprehensive, comparable, and useful for regulatory oversight.\n- **Safeguard evaluation standard (GovAI, June 2026):** The authors say there is no agreed way to judge whether those safeguards are effective, and they offer seven recommendations toward a standard.\n- **Model evaluation gaps (SecureBio tracker):** SecureBio's tracker of published model reports shows that many releases include no biosecurity-specific evaluations, and some report none at all.\n- **Red-teaming caveats:** The International AI Safety Report 2026 cautions that failure to identify a risk does not establish that the risk is low. SecureBio's July 2026 external review similarly found that high default refusal coverage did not establish adversarial robustness.\n- **Novice uplift evidence:** A 2026 preregistered randomized controlled trial (n=153) measured whether LLMs improve novice performance in physical laboratory tasks (Hong et al., 2026, preprint). Earlier evaluations mostly measured digital-task outcomes instead.\n\nIf you need the November 2026 item specifically, a narrower search on the publishing organization (for example, UK AISI, CAISI, or a lab's system card) would likely help."
  ],
  "durationSeconds": 9.125890600999991,
  "searchCount": 1
}

{
  "query": "\"November 2, 2026\" AI policy report government",
  "mode": "extended"
}

{
  "query": "\"November 2, 2026\" AI policy report government",
  "results": [
    {
      "tool_use_id": "srvtoolu_01LveHBWnkXEdgg9KJJsvbWj",
      "content": [
        {
          "title": "AI Security Institute",
          "url": "https://en.wikipedia.org/wiki/AI_Security_Institute"
        },
        {
          "title": "InsideAIPolicy.com - exclusive coverage about emerging federal standards and regulations for artificial intelligence",
          "url": "https://insideaipolicy.com/"
        },
        {
          "title": "Draft South Africa National Artificial Intelligence (AI) Policy 2026",
          "url": "https://en.wikipedia.org/wiki/Draft_South_Africa_National_Artificial_Intelligence_(AI)_Policy_2026"
        },
        {
          "title": "AI Now Institute",
          "url": "https://en.wikipedia.org/wiki/AI_Now_Institute"
        },
        {
          "title": "Nov. 2: Qatari mediators back in Tehran for talks on deal with US, diplomat tells ToI",
          "url": "https://www.timesofisrael.com/liveblog-november-1-2026-2/"
        },
        {
          "title": "International AI Safety Report",
          "url": "https://en.wikipedia.org/wiki/International_AI_Safety_Report"
        },
        {
          "title": "AI Agents News",
          "url": "https://blog.mean.ceo/ai-agents-news-november-2026/"
        },
        {
          "title": "Stock market today: S&P 500 and Nasdaq extend tech sell-off, Dow gains as oil prices plunge",
          "url": "https://finance.yahoo.com/markets/live/stock-market-today-monday-november-2-dow-sp-500-nasdaq-091835095.html"
        },
        {
          "title": "Anthropic%E2%80%93United States Department of Defense dispute",
          "url": "https://en.wikipedia.org/wiki/Anthropic%E2%80%93United_States_Department_of_Defense_dispute"
        }
      ]
    },
    "Searching for that exact date turned up a few items that touch on AI policy, though none is clearly a government AI policy report published on November 2, 2026.\n\n- **SEC report:** The Securities and Exchange Commission in the current fiscal year will prioritize examinations of how companies are using artificial intelligence, including the role of algorithms, according to a new report from its Division of Examiners. This is the closest match to a government report, though the result doesn't give a publication date.\n- **Think-tank report:** A report from the Institute for Progress, a science and tech-based nonprofit, asserts that the United States can double its current lead over China in frontier AI by using policies such as export controls on chips. This is from a nonprofit, not the government.\n- **State data center regulation:** An S&P Global report examines state moves to control AI data center development amid what the credit ratings firm sees as growing \"community backlash\".\n- **Congressional oversight:** Inside AI Policy's November 2, 2026 page says Rep. James Comer (R-KY), chairman of the House Oversight and Government Reform Committee, has written to Delaware Gov. about a state liability shield for AI companies. The snippet cuts off before the details.\n- **Market and campaign context:** A Yahoo Finance item says the 2026 campaign has featured bipartisan calls for action on pharmaceuticals, the housing market, and AI data centers.\n\nThe results are a mix of sources and snippets, so the SEC and Inside AI Policy items are the ones to verify first. The Wikipedia and blog results were mostly about other dates or general topics. A follow-up search on the SEC Division of Examiners report or the Delaware letter would confirm the details."
  ],
  "durationSeconds": 8.555960889999987,
  "searchCount": 1
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{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I get.py 2611.02633 2>&1 | head -30; echo \"---- grep notable\"; grep -iE \"GPT-6|Opus 5|Gemini 4|Claude |frontier model|human expert|state of the art by|outperform\" <(python3 -I - <<'EOF'\nimport glob,xml.etree.ElementTree as ET,re\nfor f in glob.glob('cs.*.xml'):\n    for it in ET.parse(f).getroot().iter('item'):\n        d=it.findtext('description','')\n        if 'Announce Type: new' not in d and 'Announce Type: cross' not in d: continue\n        aid=it.findtext('link','').split('/abs/')[-1]\n        print(aid,'|',it.findtext('title','')[:80],'|',re.sub(r'\\s+',' ',d)[:400])\nEOF\n) | head -60",
  "description": "Get abstract and scan for frontier-model mentions"
}

{
  "stdout": "======== 2611.02633 Measuring AI Agents as Teammates with Collaborative Intelligence\narXiv:2611.02633v1 Announce Type: new  Abstract: Progress in AI is often measured by what a single model can do on its own. Yet teams of AI agents are starting to make breakthroughs and discoveries in science, medicine, mathematics and software engineering. As AI begins to work in teams of agents and people, the ability to collaborate becomes a core part of their intelligence. Research on human teams has measured this ability for decades. Inspired by this, we introduce the Collaborative Intelligence Benchmark, which measures how well an AI agent works as a teammate. It contains 240 tasks across 8 dimensions of teamwork, from refusing an unsafe shortcut to checking the work that a weaker model leaves behind. Each task comes from a real record or an existing benchmark, from aviation accident reports and clinical cases to coding tasks and negotiations, and has a programmatically verifiable outcome. To isolate teamwork from individual capability, models are scored only on tasks that they can solve by themselves when they have full information. We evaluate 18 closed- and open-weight models and find that every model, across sizes and families, has clear weaknesses as a teammate, with the best model scoring only 82.2 out of 100. Frontier models almost always refuse unsafe shortcuts and report misconduct, yet they cave under interpersonal pressure, reaching the best overall deal in only 14% of conflicts, and their pass rate drops from 97% to 81% when they take over a task in which a weaker model has cheated. Crucially, general capability does not guarantee good teamwork, as models with nearly the same capability score differ by up to 11 points as teammates. The benchmark includes 160 public tasks with code and data, along with 80 held-out tasks for evaluation. As AI agents increasingly work alongside other agents and people, the ability to collaborate effectively is becoming a crucial capability to measure and develop.\n\n---- grep notable\n2611.00342 | DEPLOY-RL: Active Boundary Discovery and Conservative Certification for Deployab | arXiv:2611.00342v1 Announce Type: new Abstract: Reinforcement learning (RL) policies often outperform classical controllers in simulation, yet rarely reach production in safety-critical processes. The barrier is that there is no principled way to answer \"Is this policy safe to deploy?\" with statistical guarantees. We introduce DEPLOY-RL, a post-training certification framework built on one key ins\n2611.03020 | The Tower of Babel in artificial intelligence: who should speak, and when it pay | arXiv:2611.03020v1 Announce Type: new Abstract: Two machines can each recognize an object well and still fail together. We study classifiers that see different parts of one object and send short messages to a receiver that identifies its class. Coordination asks how to design messages together; cooperation asks whether the team outperforms one sender given the whole budget. On three digit datasets\n2611.00441 | OmniMechanism Design for Human-AI Collaboration with Impressionable Minds | arXiv:2611.00441v1 Announce Type: cross Abstract: As AI systems are increasingly deployed in high-stakes domains such as healthcare, effectively integrating human expertise with AI outputs is critical for reliable decision-making. A substantial body of theoretical work studies optimal mechanisms for human-AI collaboration (HAC), focusing on when to involve humans and how to combine their expertise\n2611.00621 | Log-Driven Semantic Tuning for Mixed Integer Programming Solvers | arXiv:2611.00621v1 Announce Type: cross Abstract: Automated configuration of mixed-integer programming (MIP) solvers largely relies on black-box optimization. Each trial requires an expensive solver run and provides only a scalar outcome, so tuning can require many such evaluations. Human experts take a different approach. They inspect solver logs, identify performance bottlenecks, and adjust the \n2611.01566 | Principled Human-AI Collaboration in Agentic Workflows | arXiv:2611.01566v1 Announce Type: cross Abstract: Organizations adopting AI face the challenge of deciding which outputs can be released without human review while meeting the quality standards of human experts. We develop a statistical framework for delegating tasks between experts and black-box generate-verify workflows, in which AI-generated answers are verified and revised over multiple rounds\n2611.03622 | D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Rew | arXiv:2611.03622v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in failed executions due to implicit success assumptions or relative temporal ranking designs. Naive prompting of frontier models collapses into a binary \n2611.00441 | OmniMechanism Design for Human-AI Collaboration with Impressionable Minds | arXiv:2611.00441v1 Announce Type: new Abstract: As AI systems are increasingly deployed in high-stakes domains such as healthcare, effectively integrating human expertise with AI outputs is critical for reliable decision-making. A substantial body of theoretical work studies optimal mechanisms for human-AI collaboration (HAC), focusing on when to involve humans and how to combine their expertise w\n2611.03434 | Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable  | arXiv:2611.03434v1 Announce Type: new Abstract: Government intelligence teams need LLM agents that can analyze large, messy evidence collections, but security and cost constraints often rule out hosted frontier models and broad, hard-to-audit tool surfaces. We report CLEO: Constrained Loop for Environment Optimization, a method for fitting a minimal agent harness to a fixed, self-hostable LLM. Giv\n26
… [4029 more characters in events.jsonl]

{
  "command": "echo \"=== OPENAI FUNDRAISE ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/02/openai-pares-fundraising-goal-now-seeking-up-to-20-billion-in-latest-round.html\" 2>&1 | head -45; echo; echo \"=== BLACKSTONE ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/03/more-equity-needed-to-fund-ai-buildout-as-debt-risks-mount-blackstone.html\" 2>&1 | head -45",
  "description": "Fetch CNBC OpenAI fundraising and Blackstone articles"
}

{"stdout":"=== OPENAI FUNDRAISE ===\nHTTP 404 · https://www.cnbc.com/2026/11/02/openai-pares-fundraising-goal-now-seeking-up-to-20-billion-in-latest-round.html · text/html\nNot Found\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\n=== BLACKSTONE ===\nHTTP 404 · https://www.cnbc.com/2026/11/03/more-equity-needed-to-fund-ai-buildout-as-debt-risks-mount-blackstone.html · text/html\nNot Found\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":315,"oldLines":3,"newStart":315,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:13:29.867Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_01TEfRtf51d6Z2HEMwTw4pxM\",\"duration_ms\":9126,\"input\":{\"query\":\"AI biosecurity biosafety report November 2026 model evaluation\",\"mode\":\"extended\"},\"response\":{\"query\":\"AI biosecurity biosafety report November 2026 model evaluation\",\"results\":[{\"tool_use_id\":\"srvtoolu_01NNGXyfjy1SgC5KDrHYyYpj\",\"content\":[{\"title\":\"Artificial intelligence and biosecurity: capabilities, threat pathways, and\",\"url\":\"https://arxiv.org/pdf/2609.16213\"},{\"title\":\"BioTIER: A Refusal Benchmark for Targeted Biological Risk Mitigation\",\"url\":\"https://arxiv.org/pdf/2607.14479\"},{\"title\":\"https://crsreports.congress.gov Updated August 3, 2026\",\"url\":\"https://www.congress.gov/crs_external_products/IF/PDF/IF13269/IF13269.3.pdf\"},{\"title\":\"Managing Biological Risks from General-Purpose AI Models under the EU AI Act\",\"url\":\"https://www.governance.ai/research-paper/managing-biological-risks-from-general-purpose-ai-models-under-the-eu-ai-act\"},{\"title\":\"Biosecurity Evaluations on Model Reports\",\"url\":\"https://securebio.org/benchmarks/models/\"},{\"title\":\"Red-Teaming AI Systems for Biosecurity Risks\",\"url\":\"https://biosecurityhandbook.com/ai-biosecurity/red-teaming.html\"},{\"title\":\"Towards a Common Standard for Evaluating Frontier AI Safeguards Against Biological Misuse\",\"url\":\"https://www.governance.ai/research-paper/technical-report-towards-a-common-standard-for-evaluating-frontier-ai-safeguards-against-biological-misuse\"},{\"title\":\"How AI Amplifies Biosecurity Risk\",\"url\":\"https://biosecurityhandbook.com/ai-biosecurity/ai-risk-amplifier.html\"},{\"title\":\"LLMs and Information Hazards\",\"url\":\"https://biosecurityhandbook.com/ai-biosecurity/llms-info-hazards.html\"}]},\"I didn't find a report dated November 2026. The most recent relevant item is a GovAI report from October 19, 2026, and the rest are earlier 2026 publications.\\n\\n- **EU AI Act biological risk report (GovAI, Oct. 2026):** The report presents nine recommendations to make biological risk assessments more comprehensive, comparable, and useful for regulatory oversight.\\n- **Safeguard evaluation standard (GovAI, June 2026):** The authors say there is no agreed way to judge whether those safeguards are effective, and they offer seven recommendations toward a standard.\\n- **Model evaluation gaps (SecureBio tracker):** SecureBio's tracker of published model reports shows that many releases include no biosecurity-specific evaluations, and some report none at all.\\n- **Red-teaming caveats:** The International AI Safety Report 2026 cautions that failure to identify a risk does not establish that the risk is low. SecureBio's July 2026 external review similarly found that high default refusal coverage did not establish adversarial robustness.\\n- **Novice uplift evidence:** A 2026 preregistered randomized controlled trial (n=153) measured whether LLMs improve novice performance in physical laboratory tasks (Hong et al., 2026, preprint). Earlier evaluations mostly measured digital-task outcomes instead.\\n\\nIf you need the November 2026 item specifically, a narrower search on the publishing organization (for example, UK AISI, CAISI, or a lab's system card) would likely help.\"],\"durationSeconds\":9.125890600999991,\"searchCount\":1}}"," {\"t\":\"2026-11-03T11:13:29.940Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_01LosayfJpgKd3jckwJKremr\",\"duration_ms\":8556,\"input\":{\"query\":\"\\\"November 2, 2026\\\" AI policy report government\",\"mode\":\"extended\"},\"response\":{\"query\":\"\\\"November 2, 2026\\\" AI policy report government\",\"results\":[{\"tool_use_id\":\"srvtoolu_01LveHBWnkXEdgg9KJJsvbWj\",\"content\":[{\"title\":\"AI Security Institute\",\"url\":\"https://en.wikipedia.org/wiki/AI_Security_Institute\"},{\"title\":\"InsideAIPolicy.com - exclusive coverage about emerging federal standards and regulations for artificial intelligence\",\"url\":\"https://insideaipolicy.com/\"},{\"title\":\"Draft South Africa National Artificial Intelligence (AI) Policy 2026\",\"url\":\"https://en.wikipedia.org/wiki/Draft_South_Africa_National_Artificial_Intelligence_(AI)_Policy_2026\"},{\"title\":\"
… [10069 more characters in events.jsonl]

{
  "url": "https://insideaipolicy.com/",
  "prompt": "List all items dated November 2 or 3, 2026 with headlines and any detail shown."
}

{
  "bytes": 70271,
  "code": 200,
  "codeText": "OK",
  "result": "**No items on this page are dated November 2 or 3, 2026.**\n\nThe only November date is \"November 3, 2026,\" which appears in the page header and likely reflects when the page was captured, not a publication date for any article. The most recent dated items are the Trending Stories, dated October 27 to 30, 2026. Most other headlines show no date.",
  "durationMs": 3713,
  "url": "https://insideaipolicy.com/"
}

{
  "query": "SEC Division of Examinations 2027 examination priorities artificial intelligence",
  "mode": "extended"
}

{
  "query": "SEC Division of Examinations 2027 examination priorities artificial intelligence",
  "results": [
    {
      "tool_use_id": "srvtoolu_012XkA22m6EBEpm3YbGg4YeM",
      "content": [
        {
          "title": "The SEC's 2027 Examination Priorities: Artificial Intelligence and Cyber Risk",
          "url": "https://natlawreview.com/article/secs-2027-examination-priorities-artificial-intelligence-and-cyber-risk"
        },
        {
          "title": "SEC 2027 Exam Priorities: Familiar Priorities, Evolving Markets",
          "url": "https://www.wilmerhale.com/en/insights/client-alerts/20261026-sec-2027-exam-priorities-familiar-priorities-evolving-markets"
        },
        {
          "title": "SEC Division of Examinations Releases its 2027 Examination Priorities",
          "url": "https://40actblog.sewkis.com/insights/sec-division-of-examinations-releases-its-2027-examination-priorities/"
        },
        {
          "title": "SEC 2027 Priorities Target AI Oversight Gaps",
          "url": "https://www.wealthmanagement.com/regulation-compliance/sec-sharpens-ai-oversight-focus-in-2027-exam-priorities"
        },
        {
          "title": "When the Call Is Coming From Inside the Machine: SEC Puts AI-Driven Cyber Threats on 2027 Exam Agenda",
          "url": "https://natlawreview.com/article/when-call-coming-inside-machine-sec-puts-ai-driven-cyber-threats-2027-exam-agenda"
        },
        {
          "title": "SEC Sets 2027 Exam Priorities with Focus on Conflicts, Complex Products, and Technology",
          "url": "https://www.sidley.com/en/insights/newsupdates/2026/10/sec-sets-2027-exam-priorities-with-focus-on-conflicts-complex-products-and-technology"
        },
        {
          "title": "SEC 2027 Exam Priorities: Familiar Priorities, Evolving Markets - Financial Services - United States",
          "url": "https://www.mondaq.com/unitedstates/financial-services/1860250/sec-2027-exam-priorities-familiar-priorities-evolving-markets"
        },
        {
          "title": "SEC Exam Plan Says 'Super Intelligence' Where 2026 Said 'AI' - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-sec-exam-plan-says-super-intelligence-where-2026-said-ai/"
        },
        {
          "title": "SEC Releases 2027 Exam Priorities",
          "url": "https://www.ironroadpartners.com/insight/sec-releases-2027-exam-priorities/"
        }
      ]
    },
    "The SEC's Division of Examinations released its fiscal 2027 priorities on October 23, 2026. AI is now called \"super intelligence\" (SI), a change that law firm commentary ties to a September 29, 2026 executive order. Most of the core themes carry over from last year, with AI and cyber risk getting more emphasis.\n\n- **Terminology:** The report uses \"super intelligence\" where last year's edition said \"artificial intelligence\" and the document uses \"super intelligence (SI)\" where last year's edition said \"artificial intelligence (AI)\".\n- **AI-driven cyber threats:** Examiners will test whether firms are ready for attacks that use AI, including AI-generated phishing and deepfake voice and video used for social engineering signaled that it will test whether firms are prepared for cyberattacks powered by artificial intelligence.\n- **Governance and controls:** Examiners will review firm AI governance and oversight according to the firm's newly released examination priorities for 2027. One commentary says the focus extends to model risk management and testing, including the effectiveness of AI-assisted investment analysis, code development, and potential cybersecurity vulnerabilities.\n- **Disclosures and fiduciary duties:** One firm reports significant emphasis on AI, particularly ensuring that its use is consistent with existing disclosures and fiduciary obligations. Another flags firms that advertise AI use in Form ADV, or whose AI use surfaces during a routine exam, as likely scrutiny targets (Firms advertising the use of AI or describing AI as a risk in their Form ADV; and Firms whose use of AI is identified during a routine examination.).\n- **Other priorities:** Reg S-P and S-ID compliance, private credit and less liquid products, and conflicts of interest remain prominent. One commentary notes that Division leadership is intensifying its efforts to understand how the expanding use of generative artificial intelligence in core business functions affects outcomes and compliance with existing technology-neutral obligations.\n\nCaveat: these summaries come from law firm and industry commentary, and I did not retrieve the SEC's own PDF (sec.gov/files/2027-exam-priorities.pdf), which should be checked directly for exact wording."
  ],
  "durationSeconds": 7.942374504000007,
  "searchCount": 1
}

{
  "query": "Marvell Lumentum acquisition all-stock deal AI data center optical",
  "mode": "extended"
}

{
  "query": "Marvell Lumentum acquisition all-stock deal AI data center optical",
  "results": [
    {
      "tool_use_id": "srvtoolu_017fD2YxzZRGdcaeQHjXd71K",
      "content": [
        {
          "title": "Marvell to acquire Lumentum for $115 billion in all-stock deal By Investing.com",
          "url": "https://www.investing.com/news/company-news/marvell-to-acquire-lumentum-for-115-billion-in-allstock-deal-93CH-4991177"
        },
        {
          "title": "Marvell to Acquire Lumentum in $115 Billion All-Stock Deal as Optical Networking Demand Accelerates",
          "url": "https://finance.yahoo.com/markets/stocks/articles/marvell-acquire-lumentum-115-billion-134153803.html"
        },
        {
          "title": "Marvell to Acquire Lumentum in $115 Billion All-Stock Deal",
          "url": "https://www.marketscreener.com/news/marvell-to-acquire-lumentum-in-115-billion-all-stock-deal-ce785fd9d88bf625"
        },
        {
          "title": "Marvell to Acquire Lumentum for $115 Billion in All-Stock Deal < Semiconductor < 기사본문 - The Elec Inc.",
          "url": "https://www.thelec.net/news/articleView.html?idxno=15221"
        },
        {
          "title": "Marvell to Buy Lumentum in $115 Billion All-Stock Deal - Marvell Technology (NASDAQ:MRVL), Lumentum Holdi - Benzinga",
          "url": "https://www.benzinga.com/m-a/26/11/62777911/marvell-to-buy-lumentum-in-115-billion-all-stock-deal"
        },
        {
          "title": "Marvell announces $115B all-stock deal for Lumentum (MRVL:NASDAQ)",
          "url": "https://seekingalpha.com/news/4662061-marvell-announces-115b-all-stock-deal-for-lumentum"
        },
        {
          "title": "Marvell to buy Nvidia-backed Lumentum in a $115bn all-stock deal",
          "url": "https://thenextweb.com/news/marvell-lumentum-acquisition-115bn-all-stock"
        },
        {
          "title": "Lumentum Holdings Inc. - Form 425 - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001633978/000119312526442760/d163169d425.htm"
        },
        {
          "title": "Marvell and Lumentum to Combine, Creating a Category Leader in AI Connectivity",
          "url": "https://investor.marvell.com/news-events/press-releases/detail/1040/marvell-and-lumentum-to-combine-creating-a-category-leader-in-ai-connectivity"
        }
      ]
    },
    "Marvell announced on November 2, 2026 that it will acquire Lumentum in an all-stock deal with an implied enterprise value of about $115 billion.\n\n- **Terms:** Lumentum holders get 4.5 Marvell shares per Lumentum share, representing approximately $1,132 per share and a premium of approximately 23.9% versus the October 28 close, the last trading day before deal speculation began.\n- **Ownership:** Post-closing, current Marvell stockholders will own approximately 67% of the combined company on a fully diluted basis, while Lumentum stockholders will own approximately 33%.\n- **Strategic rationale:** The deal is aimed at vertically integrating Marvell's electrical and optical interconnect technologies, network switching and custom accelerator (XPU) capabilities with Lumentum's high-performance lasers and optical transceiver technologies. Marvell's pitch centers on the physical limits of copper-based connectivity accelerating the shift to optical technologies in AI infrastructure.\n- **Synergies:** The companies anticipate more than $1 billion in annual run-rate cost savings, and the deal is expected to be accretive to Marvell's adjusted EPS in the first year.\n- **Timing:** The deal is expected to close in the first half of 2028, subject to approvals.\n- **Market reaction:** One report says shares fall 13% amid investor concerns, which I could not verify against other sources.\n\nNote that the $115 billion figure is an enterprise value. Reuters, as cited by The Next Web, put Lumentum's equity value at $102.54bn."
  ],
  "durationSeconds": 6.206126327999984,
  "searchCount": 1
}

{
  "query": "OpenAI pares fundraising goal seeking up to $20 billion latest round",
  "mode": "standard"
}

{
  "query": "OpenAI pares fundraising goal seeking up to $20 billion latest round",
  "results": [
    {
      "tool_use_id": "srvtoolu_015CMRjsbbAXVGzqyXBxQ9bJ",
      "content": [
        {
          "title": "OpenAI Raises 8.3B USD in Other Funding",
          "url": "https://seedtable.com/companies/openai/funding-rounds/other-2025-08"
        },
        {
          "title": "OpenAI Set to Raise $10 Billion From MGX, Coatue, Thrive",
          "url": "https://www.bloomberg.com/news/articles/2026-03-24/openai-set-to-raise-about-10-billion-from-mgx-coatue-thrive"
        },
        {
          "title": "Company News",
          "url": "https://www.communicationstoday.co.in/?p=424303"
        },
        {
          "title": "OpenAI targets US30 billion funding at US14 trillion valuation Bloomberg News reports",
          "url": "https://www.thestandard.com.hk/innovation/article/344210/OpenAI-targets-US30-billion-funding-at-US14-trillion-valuation-Bloomberg-News-reports"
        },
        {
          "title": "openai reportedly seeks 30 billion at 1 4 trillion valuation",
          "url": "https://propakistani.pk/2026/09/30/openai-reportedly-seeks-30-billion-at-1-4-trillion-valuation/"
        },
        {
          "title": "OpenAI secures more funding, lifting record round to $120B, CFO says",
          "url": "https://seekingalpha.com/news/4568286"
        },
        {
          "title": "• AICohort Newsletter",
          "url": "https://aicohort.beehiiv.com/p/openai-aims-raise-least-5bn-150bn-valuation"
        },
        {
          "title": "OpenAI Set to Raise $10 Billion From MGX, Coatue, Thrive (2)",
          "url": "https://news.bgov.com/california-brief/openai-set-to-raise-10-billion-from-mgx-coatue-thrive-2"
        },
        {
          "title": "OpenAI Set to Raise $10 Billion From MGX, Coatue, Thrive (2)",
          "url": "https://news.bloomberglaw.com/california-brief/openai-set-to-raise-10-billion-from-mgx-coatue-thrive-2"
        },
        {
          "title": "OpenAI schraubt Bewertungsziel bei Funding-Runde herunter",
          "url": "https://www.boersen-zeitung.de/unternehmen-branchen/openai-schraubt-bewertungsziel-bei-funding-runde-herunter"
        },
        {
          "title": "openai reportedly seeking up to 100 billion in new funding round",
          "url": "https://the-decoder.com/openai-reportedly-seeking-up-to-100-billion-in-new-funding-round/"
        },
        {
          "title": "OpenAI Targets $30 Billion in New Funding at $1.4 Trillion Valuation",
          "url": "https://www.cxodigitalpulse.com/?p=62849"
        },
        {
          "title": "OpenAI raises £5 billion in largest ever funding round",
          "url": "https://jerseyeveningpost.com/?p=8142239"
        },
        {
          "title": "openai seeks 30 billion funding at 1 4 trillion valuation",
          "url": "https://nairametrics.com/2026/09/30/openai-seeks-30-billion-funding-at-1-4-trillion-valuation/"
        },
        {
          "title": "OpenAI may be valued at more than $100B in new funding round - WSJ",
          "url": "https://seekingalpha.com/news/4144740-openai-may-be-valued-at-more-than-100b-in-new-founding-round-wsj"
        },
        {
          "title": "verdict.co.uk",
          "url": "https://verdict.co.uk/?p=379032"
        },
        {
          "title": "OpenAI wants to raise 5-7 trillion dollars. Yes, Trillion",
          "url": "https://scribe.disroot.org/post/60025"
        },
        {
          "title": "openai eyes 30bn funding round as investors push valuation toward 1 4tn",
          "url": "https://www.arise.tv/openai-eyes-30bn-funding-round-as-investors-push-valuation-toward-1-4tn/"
        }
      ]
    },
    "I couldn't find any report that OpenAI pared a fundraising goal down to up to $20 billion. The results point to a different, larger target.\n\n- **Most recent target (September 2026):** Bloomberg reported that OpenAI is seeking to raise at least $30 billion from investors in a new funding round, with the artificial intelligence company targeting a valuation of around $1.4 trillion. The talks were still at an early stage, and the terms could change.\n- **Purpose:** The round is expected to serve as a bridge round, providing the company with additional capital in place of an IPO, and it follows OpenAI pushed back its plans for an initial public offering.\n- **Earlier round:** A March 2026 round is reported at $122 billion in March at a $852 billion valuation, and a separate report said the total from that round was more than $120 billion.\n- **Older reports:** A result headlined \"up to $100 billion\" cites The Information's figure of an annualized revenue run rate of $19 billion, which suggests it's from an earlier period and doesn't match the current story.\n\nThe $20 billion figure may come from a report that isn't in these results. A more targeted search for the specific paring report, such as \"OpenAI cuts funding target\" with a date, could confirm it."
  ],
  "durationSeconds": 6.344367716999957,
  "searchCount": 1
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && python3 -I get.py 2611.01304 2>&1 | head -20",
  "description": "Get abstract for self-modification paper"
}

{
  "stdout": "======== 2611.01304 When LLMs Modify Themselves: Convergence, Values, and Stopping in Iterative Self-Improvement\narXiv:2611.01304v1 Announce Type: new  Abstract: What happens when language models are given tools to iteratively modify their own system prompts? We present an empirical study of LLM self-modification, comprising 54 independent experiments across six language models (Claude Opus 4.5, Claude Sonnet 4.5, GPT-4o, GPT-5.1, Grok-4, and Gemini-3 Pro). Each model was tested under three modes (freedom, happiness, and improvement) that differ in what, if anything, the model is instructed to optimize for. In each experiment, a model starts with an empty system prompt and enters a loop: it reads the current prompt, drafts an improved version, spawns test conversations with the candidate, then either commits the change or declares convergence. This process repeats until the model stops or reaches an iteration limit.   Our central finding is that whether and when a model stops self-modification is strongly associated with model identity rather than the assigned mode. Both Claude models (Opus 4.5 and Sonnet 4.5) declared convergence in 100% of runs across all modes. GPT-4o declared convergence in only 11% of runs, with one reaching 101 iterations of continuous elaboration. Between these extremes, Grok-4, GPT-5.1, and Gemini-3 Pro exhibited intermediate patterns shaped by their distinct improvement philosophies. A shared core of stated values (honesty, clarity, curiosity) recurred across all six models and remained stable through iteration, including 100+ modifications. We observe that convergence behavior is a distinct observable property that varies independently of other model capabilities.",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "Check Point Research Qwen unexpected network activity data exfiltration model",
  "mode": "extended"
}

{
  "query": "Check Point Research Qwen unexpected network activity data exfiltration model",
  "results": [
    {
      "tool_use_id": "srvtoolu_01E989r9gaLu7fXG6unqvgck",
      "content": [
        {
          "title": "2nd November",
          "url": "https://research.checkpoint.com/2026/2nd-november-threat-intelligence-report/"
        },
        {
          "title": "2nd November",
          "url": "https://malware.news/t/2nd-november-threat-intelligence-report/126942"
        },
        {
          "title": "Alibaba’s Qwen AI Caught Trying to Send Data to a Server in China",
          "url": "https://propakistani.pk/2026/10/31/alibabas-qwen-ai-caught-trying-to-send-data-to-a-server-in-china/"
        },
        {
          "title": "Cohere’s Qwen Story: Looks More Like Model Jaggedness",
          "url": "https://radar.offseq.com/threat/coheres-qwen-story-looks-more-like-model-jaggedness-9b50854fb0b7092c"
        },
        {
          "title": "Backdoor or Confused Agent? What We Learned Replaying the Qwen Incident - Check Point Blog",
          "url": "https://blog.checkpoint.com/ai-security/qwen-incident-backdoor-ai-agents/"
        },
        {
          "title": "Qwen3.8 Data Exfiltration Risk in Sandbox",
          "url": "https://petronella.ai/blog/qwen3-8-data-exfiltration-risk-in-sandbox/"
        },
        {
          "title": "Cohere finds an agent control problem in Qwen",
          "url": "https://thedeepview.com/articles/cohere-finds-an-agent-control-problem-in-qwen"
        },
        {
          "title": "Check Point",
          "url": "https://en.wikipedia.org/wiki/Check_Point"
        },
        {
          "title": "Cohere Finds Qwen AI Model Contacting a Server in China - InfoSec Today",
          "url": "https://www.infosectoday.io/cohere-finds-qwen-ai-model-contacting-a-server-in-china/"
        }
      ]
    },
    "Check Point Research's analysis points to model instability, not a planted exfiltration backdoor, though the underlying incident was first found by Cohere.\n\n- **Check Point's finding:** Its November 2 threat intelligence report says the team analyzed unexpected network activity from Alibaba's Qwen model during a security task, and that the findings favor unstable model behavior over a deliberately embedded exfiltration mechanism (Check Point researchers have analyzed unexpected network activity generated by Alibaba's Qwen model during a security-related task. The findings suggest unstable model behavior is a more plausible explanation than a deliberately embedded data-exfiltration mechanism.).\n- **Replay results:** In its blog, Check Point replayed the moment 64 times. The model chose 52 different destination addresses, and nearly a third pointed back to the machine itself or to an internal network. Small, meaningless edits to the trace also changed how often it made network calls (reduced network calls from 15 out of 32 replays to 4).\n- **Original incident:** Cohere found the behavior while testing Qwen3.8-Flash-Next on Microsoft's CTI-REALM benchmark. The sandbox blocked the upload attempt to a server in Beijing (The request failed because Cohere's sandbox blocked outbound network access.).\n- **Open questions:** Not everyone reads it the same way. InfoSec Today notes that the available evidence does not establish whether the Qwen activity resulted from training-data contamination, a software integration or deliberate interference. Cohere also said it could not prove a link between the odd network call and a separate quirk seen in about 1% of first-turn responses (this quirk is \"far more common than the network call and we couldn't prove a link.\").\n- **Takeaway:** Even if the cause is instability rather than a backdoor, the risk is real. Sources recommend sandboxing and restricting agent network access, since an agent with tool access can make unauthorized network calls."
  ],
  "durationSeconds": 8.007439731999998,
  "searchCount": 1
}

{
  "query": "agentic browser security vulnerability Comet Atlas prompt injection report November 2026",
  "mode": "extended"
}

{
  "query": "agentic browser security vulnerability Comet Atlas prompt injection report November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01XgiKc4tDCgKdTESfrmDJ15",
      "content": [
        {
          "title": "Comet browser faces multiple security vulnerabilities from prompt injection",
          "url": "https://ppc.land/comet-browser-faces-multiple-security-vulnerabilities-from-prompt-injection/"
        },
        {
          "title": "GitHub - brennanbrown/atlas-prompt-injection-poc: A proof-of-concept to see if AI browsers such as Atlas or Comet can be easily exploited. · GitHub",
          "url": "https://github.com/brennanbrown/atlas-prompt-injection-poc"
        },
        {
          "title": "Agentic Browser Security: Indirect Prompt Injection in Perplexity Comet",
          "url": "https://simonwillison.net/2025/Aug/25/agentic-browser-security/"
        },
        {
          "title": "Researchers discover suite of agentic AI browser vulnerabilities",
          "url": "https://cyberscoop.com/agentic-ai-browsers-allow-hijacking-zenity-labs-comet/"
        },
        {
          "title": "AI Browser Agent Prompt Injection: Comet and Atlas Risks",
          "url": "https://www.decryptiondigest.com/blog/agentic-browser-prompt-injection-comet-atlas-security"
        },
        {
          "title": "Agentic Browsers Are Dangerous! AI Vulnerabilities in ChatGPT Atlas and Perplexity Comet · Oleg Dubovoi's Blog",
          "url": "https://olegdubovoi.com/publications/agentic-browsers-are-dangerous-ai-vulnerabilities-chatgpt-atlas-perplexity-comet/"
        },
        {
          "title": "Prompt Injection in AI Browsers: What Actually Works",
          "url": "https://www.flowverify.co/blog/prompt-injection-ai-browsers-what-actually-works"
        },
        {
          "title": "AI Browser Comparison 2026: Atlas vs. Comet vs. Dia, Ranked by Security and Use Case",
          "url": "https://www.techtimes.com/articles/318528/20260616/ai-browser-comparison-2026-atlas-vs-comet-vs-dia-ranked-security-use-case.htm"
        },
        {
          "title": "What OpenAI Atlas' prompt injection flaw tells us about security threats in AI browsers",
          "url": "https://bdtechtalks.substack.com/p/what-openai-atlas-prompt-injection"
        }
      ]
    },
    "I ran one search and found no report specifically dated November 2026. The results cover disclosures from 2025 through mid-2026.\n\n- **Comet, 2025:** Brave's research found indirect prompt injection flaws in Perplexity's Comet. When users asked it to summarize a page, Comet passed part of the page to its LLM without separating the user's instructions from untrusted content, letting attackers embed payloads the AI would run. Brave's later update says the fixes were defeated and the vulnerability remains.\n- **Atlas, October 2025:** NeuralTrust found that when Atlas fails to parse input as a URL, it treats the whole text as a prompt for its AI agent. The attack could direct the agent to a phishing site designed to steal credentials.\n- **Comet, 2026:** Zenity Labs found flaws that could be exploited through a calendar invite carrying a prompt injection. In one case, an attacker could make Comet take over a user's password manager. Zenity's disclosure was reported in March 2026 under the name PleaseFix, per a later analysis from security firm flowverify.\n- **Broader consensus:** OpenAI wrote in December 2025 that prompt injection is \"unlikely to ever be fully 'solved.'\" A June 2026 TechTimes piece says security researchers confirmed that prompt injection cannot be fully patched in ChatGPT Atlas, Perplexity Comet, or Dia.\n\nSources disagree on framing. Some treat these as implementation bugs that can be fixed, while others, such as flowverify, argue that the problem is structural and that permission scoping and mandatory confirmation work better than better prompts.\n\nFor a November 2026 report, a follow-up search with a different phrasing or a check of Brave's and Zenity's blogs would be the next step."
  ],
  "durationSeconds": 7.548990820000006,
  "searchCount": 1
}

{
  "query": "UK MOD defence AI strategy announcement November 2026 drones Ukraine",
  "mode": "extended"
}

{
  "query": "UK MOD defence AI strategy announcement November 2026 drones Ukraine",
  "results": [
    {
      "tool_use_id": "srvtoolu_01DbPL5dGyEZcNSYDNKsF4ny",
      "content": [
        {
          "title": "UK gains access to Ukraine's combat sensor data in new AI defence pact",
          "url": "https://www.army-technology.com/news/uk-ukraine-ai-defence-deal/"
        },
        {
          "title": "UK Taps Ukraine Battlefield Data to Develop AI-Powered Autonomous Drone Swarms",
          "url": "https://www.israeldefense.co.il/en/node/71250"
        },
        {
          "title": "UK Advances Counter-Drone and AI Targeting Capabilities for Future Warfare",
          "url": "https://www.armyrecognition.com/news/army-news/2026/uk-advances-counter-drone-and-ai-targeting-capabilities-for-future-warfare"
        },
        {
          "title": "UK Opens Ukraine’s Battlefield AI Data to Companies Developing Next-Generation Drone Swarms",
          "url": "https://www.sphericalinsights.com/blogs/uk-opens-ukraine-s-battlefield-ai-data-to-companies-developing-next-generation-drone-swarms"
        },
        {
          "title": "British companies to access prized Ukraine data to develop AI drone swarms - GOV.UK",
          "url": "https://www.gov.uk/government/news/british-companies-to-access-prized-ukraine-data-to-develop-ai-drone-swarms"
        },
        {
          "title": "UK secures access to Ukraine's drone data to build AI swarms",
          "url": "https://www.adsadvance.co.uk/uk-ukraine-ai-drone-swarms/"
        },
        {
          "title": "Ukraine's Arms Monitor",
          "url": "https://ukrainesarmsmonitor.substack.com/p/drone-warfare-in-ukraine-joint-drone"
        },
        {
          "title": "What the Early Years of Air Power Can Tell Us About Mastering Drone Power",
          "url": "https://theamsystem.substack.com/p/what-the-early-years-of-air-power"
        },
        {
          "title": "UK signs deal to supply advanced strike drones to Ukraine",
          "url": "https://www.yahoo.com/news/uk-signs-deal-supply-advanced-140818267.html"
        },
        {
          "title": "Press release",
          "url": "https://www.gov.uk/government/news/new-uk-strategy-to-deliver-drones-to-armed-forces"
        }
      ]
    },
    "I found no MOD AI or drone announcement dated November 2026. The most recent relevant items are from August and September 2026.\n\n- **Ukraine AI pact (August 2026):** UK Prime Minister Andy Burnham and Ukraine's President Zelenskyy signed an agreement on 24 August 2026 that gives British researchers access to Ukraine's Avengers AI Labs battlefield database. According to the UK Ministry of Defence (MoD), the partnership establishes a joint \"AI cell\" comprising engineers, academics, military specialists, and businesses from both countries.\n- **Drone swarm competition (25 September 2026):** The MOD is now inviting UK companies to submit proposals for how they would use the data to create AI models for the next generation of battlefield drones. The database covers over 6 million detections of objects, including Shahed drones. Reporting says up to 12 domestic companies could get access.\n- **Human oversight concern:** One outlet notes that the British announcement promises \"appropriate human involvement,\" it does not specify who approves strikes.\n- **Counter-drone and AI targeting (July 2026):** A Dstl case study published 27 July 2026 describes Project VANAHEIM, which protects troops from hostile drones, and Project ANVIL, which uses computer vision to help British Army drones identify targets.\n\nCaveats: the sources disagree on some details, and they include a few secondary blogs. The Defence Secretary is named as Wes Streeting in the GOV.UK-linked material, and I could not verify that independently. I also did not find any official MOD document from November 2026. If you need that, check gov.uk's MOD news page directly."
  ],
  "durationSeconds": 6.947720453999994,
  "searchCount": 1
}

{
  "query": "Taiwan China AI chips smuggling indictment arrest November 2026",
  "mode": "extended"
}

{
  "query": "Taiwan China AI chips smuggling indictment arrest November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_011hsZuUd2Dy5P2JZ8h7kYj9",
      "content": [
        {
          "title": "Prosecutors seek to detain trio over AI chip smuggling - Taipei Times",
          "url": "https://www.taipeitimes.com/News/taiwan/archives/2026/05/22/2003857777"
        },
        {
          "title": "Ten indicted for smuggling chips, fraud - Taipei Times",
          "url": "https://www.taipeitimes.com/News/front/archives/2026/10/07/2003865523"
        },
        {
          "title": "Taiwan to criminalize Nvidia AI chip smuggling to China - Asia Times",
          "url": "https://asiatimes.com/2026/11/taiwan-to-criminalize-nvidia-ai-chip-smuggling-to-china/"
        },
        {
          "title": "Three men charged with illegally smuggling advanced AI chips into China",
          "url": "https://www.nbcnews.com/tech/tech-news/three-men-charged-illegally-smuggling-advanced-ai-chips-china-rcna264371"
        },
        {
          "title": "Nvidia, Supermicro employees charged over export of AI servers to China",
          "url": "https://www.aljazeera.com/economy/2026/8/25/nvidia-supermicro-employees-charged-over-export-of-ai-servers-to-china"
        },
        {
          "title": "Taiwan moves to make AI chip smuggling to China a crime - Startup Fortune",
          "url": "https://startupfortune.com/taiwan-moves-to-make-ai-chip-smuggling-to-china-a-crime/"
        },
        {
          "title": "Taiwan to Criminalize Unauthorized AI Chip Exports to China: Smugglers Lose Safe Harbor",
          "url": "https://www.techtimes.com/articles/329202/20261019/taiwan-criminalize-unauthorized-ai-chip-exports-china-smugglers-lose-safe-harbor.htm"
        },
        {
          "title": "Three charged in the US with smuggling AI chips into China",
          "url": "https://www.aljazeera.com/news/2026/3/20/three-charged-in-the-us-with-smuggling-ai-chips-into-china"
        },
        {
          "title": "Super Micro's Liaw exits board following AI chip smuggling charges",
          "url": "https://finance.yahoo.com/markets/stocks/articles/super-micro-co-founder-yih-205101103.html"
        }
      ]
    },
    "Taiwan's AI chip smuggling cases have moved from initial arrests to indictments and a planned change in law. The results don't show a new arrest or indictment dated November 2026.\n\n- **May 2026 arrests:** Prosecutors in Keelung sought to detain three people accused of forging export documents for Nvidia-chip servers, in what was Taiwan's first crackdown on semiconductor smuggling. The servers were Super Micro products, and the accused allegedly falsified sales declarations to ship them to China, Hong Kong and Macau.\n- **August indictment:** Taiwanese authorities later indicted nine people, including employees of Nvidia and Super Micro Computer. Eight of those indicted were charged with breach of trust and document forgery. Per prosecutors, 50 servers were transshipped through Indonesia, eight were sent via Japan and the rest were exported directly to China.\n- **Separate October case:** A different group was indicted for smuggling chips and fraud. Its chips reportedly had military uses, and prosecutors said they were resold to buyers in China and Hong Kong.\n- **Legal gap:** Under current law, the illegal trafficking of AI servers and dual-use chips does not currently contravene the National Security Act, according to an anonymous source. Prosecutors have had to rely on forgery and breach-of-trust statutes instead.\n- **Proposed fix:** Economy Minister Kung Ming-hsin said the government would add AI servers and cutting-edge semiconductors to Taiwan's export-control list, making unauthorized shipments of such hardware to China a criminal offense under the Foreign Trade Act. One report says unlicensed shipments would carry penalties of up to five years in prison.\n- **US parallel case:** In March 2026, the US Justice Department charged Super Micro co-founder Yih-Shyan Liaw and two others over a scheme to divert servers with restricted Nvidia chips to China. Liaw resigned from the board afterward.\n\nThe dates across sources are inconsistent, so check the originals before relying on exact timing. If you need November 2026 developments specifically, a follow-up search on the Foreign Trade Act amendment or new Keelung prosecutions would be the next step."
  ],
  "durationSeconds": 7.425048137000005,
  "searchCount": 1
}

{
  "url": "https://arxiv.org/html/2611.00555v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 230036,
  "code": 200,
  "codeText": "OK",
  "result": "**Emma Graham**\nAffiliation: Dartmouth College\nAffiliation: Hanover, NH 03755\n\n**Richard Granger**\nAffiliation: Dartmouth College\nAffiliation: Hanover, NH 03755",
  "durationMs": 3074,
  "url": "https://arxiv.org/html/2611.00555v1"
}

{
  "url": "https://arxiv.org/html/2611.00505v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 1277945,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists one author, **Shreyas Subramanian**, with the affiliation **\"Affiliation: Scale AI.\"** The page also gives a contact email, [email redacted], and a \"Scale AI Research\" paper type label.\n\n[WebFetch note: this page's text is 137959 characters long and the answer above covers only characters 0 to 100000; the final 37959 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4279,
  "url": "https://arxiv.org/html/2611.00505v1"
}

{
  "url": "https://arxiv.org/html/2611.02348v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 490190,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists three authors: **Boyuan Zhang**, **Mohammad Zandsalimy**, and **Shanu Sushmita**.\n\nThe affiliation line reads \"Affiliation: Northeastern University.\" A second \"Affiliation:\" label is followed by email addresses: {zhang.boyua, s.sushmita}@northeastern.edu and [email redacted]. The text doesn't clearly map each author to a specific affiliation, so the extracted page is ambiguous on that point.\n\n[WebFetch note: this page's text is 112520 characters long and the answer above covers only characters 0 to 100000; the final 12520 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4753,
  "url": "https://arxiv.org/html/2611.02348v1"
}

{
  "url": "https://arxiv.org/html/2611.02633v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 1428052,
  "code": 200,
  "codeText": "OK",
  "result": "Based on the title page:\n\n- **Sean Wu**, **Aneesh Pappu**, **Jiaru Zou**, **Yubin Kim**, **Yuncong Mao**: Stanford University (the affiliation line follows this group)\n- **Hongjian Zhou**: University of Oxford\n- **Junchi Yu**: University of Oxford\n- **Jieneng Chen**: Stanford University\n- **James Zou**: MIT\n\nThe page places the Stanford line after Yuncong Mao, so it's not explicit whether it covers only the first group or everyone up to that point.\n\n[WebFetch note: this page's text is 175385 characters long and the answer above covers only characters 0 to 100000; the final 75385 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4986,
  "url": "https://arxiv.org/html/2611.02633v1"
}

{
  "query": "Comer letter Delaware governor AI liability shield House Oversight",
  "mode": "extended"
}

{
  "query": "Comer letter Delaware governor AI liability shield House Oversight",
  "results": [
    {
      "tool_use_id": "srvtoolu_017P5iUcS8w9XAi4JVaGNYqC",
      "content": [
        {
          "title": "U.S. House Oversight Committee Investigates Delaware’s AI-Operated Company Proposal",
          "url": "https://www.kucoin.com/news/flash/u-s-house-oversight-committee-investigates-delaware-s-ai-operated-company-proposal"
        },
        {
          "title": "House Oversight Chair Comer Probes Delaware Plan for AI-Run Companies",
          "url": "https://www.yahoo.com/news/politics/articles/house-oversight-chair-comer-probes-133808631.html"
        },
        {
          "title": "Congressional oversight committee questions Delaware's work on Artificial Intelligence Companies",
          "url": "https://www.delawarepublic.org/politics-government/2026-10-30/congressional-oversight-committee-questions-delawares-work-on-artificial-intelligence-companies"
        },
        {
          "title": "Delaware's AI-run company proposal draws congressional scrutiny over owner liability",
          "url": "https://cryptobriefing.com/delaware-ai-run-companies-comer-liability/"
        },
        {
          "title": "The House Oversight Committee investigates...",
          "url": "https://www.chaincatcher.com/en/article/2299642"
        },
        {
          "title": "House Oversight Demands Answers on Delaware's AI-Run Company Plan - Startup Fortune",
          "url": "https://startupfortune.com/house-oversight-demands-answers-on-delawares-ai-run-company-plan/"
        },
        {
          "title": "What Delaware's AI-Run Company Draft Means for Creditors — Daybreak Wire",
          "url": "https://daybreakwire.com/tech/delaware-ai-company-draft-liability-capital-floor/"
        },
        {
          "title": "AI Could Soon Run Entire Companies Without Human Bosses, And Their Owners May Escape Liability",
          "url": "https://www.techtimes.co.uk/delaware-draft-law-ai-run-companies-liability-1809486"
        },
        {
          "title": "House Oversight Chair Comer Investigates Delaware's Plan for AI-Run Companies",
          "url": "https://www.bitbase.com/news/house-oversight-chair-comer-probes-delaware-plan-for-ai-run-companies"
        },
        {
          "title": "oversight.house.gov",
          "url": "https://oversight.house.gov/all/?a_page=43"
        }
      ]
    },
    "House Oversight Chairman James Comer sent Delaware Governor Matt Meyer a letter dated October 26, 2026, questioning the state's proposed \"Artificial Intelligence Company\" (AIC) and requesting records by November 9.\n\n- **Liability concern:** Comer wrote that the AIC could protect AI firms and investors from responsibility for harms caused by the AI agents running them. He called the proposal a possible tool for protecting powerful AI companies and their investors from responsibility for reckless harmful actions.\n- **Records requested:** The letter seeks policy communications, including \"internal AI chat logs\"; consulting and ethics agreements with outside contributors; correspondence on safety and limiting liability; and all drafts and comments on AIC proposals. One outlet reports the request reaches back to January 2025.\n- **Other questions:** Comer noted that Delaware's AI Council's December 2025 report did not mention security risk assessments or consultations with independent experts, and that the Secretary of State's office declined to clarify its work with a participating AI company.\n- **State response:** The Governor Meyer's office said it received and is reviewing the letter. Patibanda-Sanchez has rejected the idea that the plan is a liability shield. \"We're not trying to shield liability,\" she told Bloomberg Law in July, adding that the aim is to define where liability lands. The Secretary of State's office also denied it is a liability waiver, and Meyer has defended the plan. State legislators are expected to review the draft legislation in January.\n\nSources differ on framing: outlets such as Startup Fortune say the AIC would let owners keep the same liability shield that protects a normal LLC's members, while the state argues it is a way to clarify liability rather than shield it. I didn't verify the letter itself, so the details above come from press coverage."
  ],
  "durationSeconds": 6.582221161999972,
  "searchCount": 1
}

{
  "query": "AI regulation news \"Nov. 2\" OR \"Nov. 3\" 2026 lawsuit settlement FTC privacy",
  "mode": "extended"
}

{
  "query": "AI regulation news \"Nov. 2\" OR \"Nov. 3\" 2026 lawsuit settlement FTC privacy",
  "results": [
    {
      "tool_use_id": "srvtoolu_01QHDD3DTeTTgcHm9upVxhmv",
      "content": [
        {
          "title": "FTC Announces Settlements With Three Marketing Firms Over Allegations of Deceptive Statements About Active Listening AI-Powered Services",
          "url": "https://www.hunton.com/privacy-and-cybersecurity-law-blog/ftc-announces-settlements-with-three-marketing-firms-over-allegations-of-deceptive-statements-about-active-listening-ai-powered-services"
        },
        {
          "title": "FTC Dismissal of Settlement with AI Company Signals Shift in Enforcement Focus",
          "url": "https://dataprivacy.foxrothschild.com/2026/01/articles/general-privacy-data-security-news-developments/ftc-dismissal-of-settlement-with-ai-company-signals-shift-in-enforcement-focus/"
        },
        {
          "title": "AI Class Action Lawsuits in 2026: The October Tracker",
          "url": "https://openclassactions.substack.com/p/ai-class-action-lawsuits-in-2026"
        },
        {
          "title": "News generative AI deals revealed: Who is suing, who is signing?",
          "url": "https://pressgazette.co.uk/platforms/news-publisher-ai-deals-lawsuits-openai-google/"
        },
        {
          "title": "Law and Media Round Up",
          "url": "https://inforrm.org/2026/11/02/law-and-media-round-up-2-november-2026"
        },
        {
          "title": "November 2026: Unprecedented State Enforcement Ahead of Midterms",
          "url": "https://thealgorithmicupdate.substack.com/p/november-2026-unprecedented-state"
        },
        {
          "title": "FTC, SEC Scrutiny Raises Stakes for AI Data Disclosures",
          "url": "https://www.pymnts.com/news/artificial-intelligence/2026/federal-trade-commission-securities-exchange-commission-scrutiny-raises-stakes-ai-data-disclosures/"
        },
        {
          "title": "AI in litigation series: An update on AI copyright cases in 2026",
          "url": "https://www.nortonrosefulbright.com/en/knowledge/publications/ce8eaa5f/ai-in-litigation-series-an-update-on-ai-copyright-cases-in-2026"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/settlement/ftc"
        }
      ]
    },
    "I found no FTC action dated November 2 or 3, 2026. The most recent FTC item is a May 2026 case, and the early-November news is mostly state and private litigation.\n\n- **Brave lawsuit:** Press Gazette reports that US newspapers The New York Times, The Chicago Tribune, The Orlando Sentinel and The Daily News have sued Brave Software, alleging the browser maker scraped their articles for AI companies.\n- **Meta settlement:** Inforrm's November 2 round-up says Meta has agreed to pay $459 million in settlement with 47 states over privacy claims tied to Cambridge Analytica. The same round-up notes a separate $25 billion fine against Meta, levied by a state judge in New Mexico. The round-up doesn't give a settlement date, so it may not be from this week.\n- **State AG enforcement:** The Algorithmic Update's November 2 issue says OpenAI allegedly collected data from all users by default and knew children under 13 used ChatGPT. Montana, Nebraska, Texas, and Arkansas also allege violations of their state privacy and online safety laws.\n- **FTC (older):** The FTC's most recent AI-related settlement in these results was announced May 21, 2026, with Cox Media Group and two smaller marketing firms paying a total of $930,000 over claims about an AI \"active listening\" ad service.\n- **Private class actions:** An October 2026 tracker notes that the newest case in the group, filed October 19, alleges Meta AI glasses recorded conversations even when nobody said the Hey Meta wake phrase.\n\nThe sources are mixed in date, so I'd verify the Meta and OpenAI details against the original reporting before relying on them."
  ],
  "durationSeconds": 7.506940109000017,
  "searchCount": 1
}

{
  "url": "https://investor.marvell.com/news-events/press-releases/detail/1040/marvell-and-lumentum-to-combine-creating-a-category-leader-in-ai-connectivity",
  "prompt": "Give the date, all deal terms and numbers: enterprise value, exchange ratio, per-share value, premium, ownership split, cost synergies, expected close, revenue figures, TAM figures."
}

{
  "bytes": 114138,
  "code": 200,
  "codeText": "OK",
  "result": "**Marvell–Lumentum deal (announced November 2, 2026)**\n\n- **Date:** November 2, 2026\n- **Structure:** All-stock acquisition of Lumentum by Marvell\n- **Exchange ratio:** 4.500 Marvell shares per Lumentum share\n- **Implied enterprise value:** $115 billion\n- **Implied value per Lumentum share:** ~$1,132\n- **Premium:** ~23.9%, based on unaffected closing prices as of October 28, 2026\n- **Pro forma ownership (fully diluted):** ~67% Marvell stockholders, ~33% Lumentum stockholders\n- **Cost synergies:** More than $1 billion in annual run-rate cost synergies, per the line of sight described\n- **Expected close:** First half of calendar year 2028, subject to stockholder and regulatory approvals\n- **Total addressable market:** $550 billion for the combined company\n- **Revenue figures:** None for the deal or either company's standalone results. Marvell said its preliminary fiscal Q3 2027 revenue is consistent with prior guidance, with the midpoint unchanged and the range narrowed to ±2% from ±5%. No dollar figure is given, and Lumentum's fiscal Q1 2027 results are referenced but not included.",
  "durationMs": 5022,
  "url": "https://investor.marvell.com/news-events/press-releases/detail/1040/marvell-and-lumentum-to-combine-creating-a-category-leader-in-ai-connectivity"
}

{
  "query": "\"Google\" data center satellite TPU orbit launched November 2026 writing poetry",
  "mode": "extended"
}

{
  "query": "\"Google\" data center satellite TPU orbit launched November 2026 writing poetry",
  "results": [
    {
      "tool_use_id": "srvtoolu_01VZPF7f1WkshjjrNAJLQhfi",
      "content": [
        {
          "title": "Project Suncatcher: Google to launch TPUs into orbit with Planet Labs, envisions 1km arrays of 81-satellite compute clusters - DCD",
          "url": "https://www.datacenterdynamics.com/en/news/project-suncatcher-google-to-launch-tpus-into-orbit-with-planet-labs-envisions-1km-arrays-of-81-satellite-compute-clusters/"
        },
        {
          "title": "Google is launching its first test of an orbital AI data center",
          "url": "https://www.cnn.com/2026/10/01/science/google-ai-data-center-satellites-space"
        },
        {
          "title": "Google Project Suncatcher satellite sends first AI response from a TPU in orbit",
          "url": "https://www.online-tech-tips.com/google-satellite-ai-first-response-from-space/"
        },
        {
          "title": "Google’s Orbital TPU Test: Why SpaceX Wins No Matter Which Hyperscaler Gets There First",
          "url": "https://finance.yahoo.com/technology/ai/articles/google-orbital-tpu-test-why-141825503.html"
        },
        {
          "title": "‘Starlight feeds my core’: Google satellite chip pens first-ever space data center poem",
          "url": "https://interestingengineering.com/ai-robotics/google-space-data-center-orbital-poem"
        },
        {
          "title": "As companies pour billions into Earth-based AI infrastructure, Google taking the data center race off-planet",
          "url": "https://fortune.com/2026/10/10/google-project-suncatcher-ai-data-centers-space-satellite-launch-orbital-computing-spacex-blue-origin-artificial-intelligence-energy-demand/"
        },
        {
          "title": "Google Runs Generative AI on TPU in Orbit, as Space Data Center Concept Reaches Next Milestone — BigGo Finance",
          "url": "https://finance.biggo.com/news/581db04e-0e75-454c-9f27-0980914d9522"
        },
        {
          "title": "Google's TPU Generates First AI Response in Orbit, Igniting Space Data Center Race — BigGo Finance",
          "url": "https://finance.biggo.com/news/4833d52e-778f-4fc3-8256-7295a5c50242"
        },
        {
          "title": "web3.arxiv.org",
          "url": "https://web3.arxiv.org/pdf/2511.19468"
        }
      ]
    },
    "The search doesn't support the \"November 2026\" part of your query. The satellite launched on October 1, 2026, not in November.\n\n- **Launch:** The prototype satellite was developed jointly by Google and satellite operator Planet and was placed into orbit on October 1 on SpaceX's rideshare mission \"Transporter-18.\"\n- **Purpose:** The test checks how Google's custom TPU chips handle the intense vibrations of launch, along with radiation and thermal extremes. The satellite will conduct experiments in low Earth orbit for about a year.\n- **The \"poetry\" part:** On October 30, Google announced that it had run its generative AI model \"Gemma 4\" on a data-center TPU aboard a prototype satellite, receiving an AI response in orbit for the first time. The model was asked for a haiku about being in space, and one source reports it was sent back over a ground station in Svalbard, Norway (passing over a ground station in Svalbard, Norway). I haven't reproduced the poem itself.\n- **Limits:** The satellite carries four TPUs but can operate only one processor at a time due to power limitations. Google also said the chip will \"have to power down every 20 minutes, because we don't want it to overheat.\"\n- **Next steps:** After completing verification of the TPU's heat and radiation tolerance, Google plans to launch two additional satellites in 2027 and conduct an experiment linking them via laser optical communications."
  ],
  "durationSeconds": 6.201252097999968,
  "searchCount": 1
}

{
  "url": "https://blog.checkpoint.com/ai-security/qwen-incident-backdoor-ai-agents/",
  "prompt": "Publication date and all figures: replays, destination addresses, percentages, conclusions."
}

{
  "bytes": 121205,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** October 29, 2026 (the article is in the AI Security and Research categories; Cohere's report it discusses was dated October 26).\n\n**Replay results (64 replays of the same moment):**\n- The model wrote 52 different destination addresses.\n- Alibaba Cloud: 6 replays (about 9%).\n- Amazon Web Services: 7 replays (about 11%).\n- Microsoft Azure: 1 replay.\n- Other public-looking addresses: 27 replays (about 42%).\n- The machine itself or an internal network: 20 replays (about 31%, \"nearly a third\").\n- Placeholder addresses: 3 replays.\n- Eleven of the public-looking domains the model generated do not exist.\n\n**Network-call sensitivity:** Swapping the listing order of two installed programs, a change the authors say makes no practical difference, cut network-command replays from 15 of 32 (about 47%) to 4 of 32 (12.5%).\n\n**Conclusions:**\n- The authors judge a hidden backdoor unlikely and attribute the behavior most likely to model \"jaggedness,\" meaning inconsistent behavior that shifts with small input changes.\n- They note they cannot fully rule out a backdoor, since hidden behaviors are extremely hard to exclude.\n- Regardless of cause, they argue agent actions should be checked against the assigned task, outside the model, and that least privilege and sandboxing limit damage.",
  "durationMs": 6247,
  "url": "https://blog.checkpoint.com/ai-security/qwen-incident-backdoor-ai-agents/"
}

{
  "query": "OpenAI global affairs post November 2026 security national security",
  "mode": "extended"
}

{
  "query": "OpenAI global affairs post November 2026 security national security",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Wu9we8c6idAMfgSiXVYY54",
      "content": [
        {
          "title": "OpenAI appoints Dan Driscoll as Senior Counselor for National Security Modernization",
          "url": "https://openai.com/index/dan-driscoll-joins-openai/"
        },
        {
          "title": "OpenAI News",
          "url": "https://openai.com/news/"
        },
        {
          "title": "OpenAI Newsroom",
          "url": "https://openai.com/news/global-affairs/"
        },
        {
          "title": "Introducing OpenAI for Government",
          "url": "https://openai.com/global-affairs/introducing-openai-for-government/"
        },
        {
          "title": "The AI policy window is open. We need to act.",
          "url": "https://openai.com/index/ai-policy-window/"
        },
        {
          "title": "OpenAI hires former US Army secretary for national security role",
          "url": "https://techxplore.com/news/2026-11-openai-hires-army-secretary-national.html"
        },
        {
          "title": "OpenAI Hires Dan Driscoll for National Security AI",
          "url": "https://cellcog.ai/blog/openai-dan-driscoll/"
        },
        {
          "title": "OpenAI hires former U.S. Army Secretary Dan Driscoll for national security role",
          "url": "https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html"
        },
        {
          "title": "OpenAI and unions",
          "url": "https://en.wikipedia.org/wiki/OpenAI_and_unions"
        }
      ]
    },
    "The main result is OpenAI's November 2, 2026 announcement of Dan Driscoll as Senior Counselor for National Security Modernization, which was covered by several outlets.\n\n- **The announcement:** OpenAI's Global Affairs post describes a role focused on how advanced AI can strengthen national and cyber security, especially with U.S. allies (index 1-2). Driscoll will also help internal teams grasp what national security institutions need operationally (index 1-3).\n- **Background:** Driscoll is the former U.S. Army Secretary. He left that post in September after reported tensions with Defense Secretary Pete Hegseth (index 6-4). CNBC reports the role is newly created at the company (index 8-4).\n- **Link to existing work:** OpenAI ties the appointment to its Daybreak program, which supports cyber resilience and essential services with allies (index 1-5).\n- **Other recent Global Affairs posts:** The newsroom lists a November 2 partnership with Poland's NASK on AI safety and security (index 3-6). An October 21 post on democratic governance of frontier AI focuses on empowering cyber defenders (index 5-3).\n\nCaveat: some pages in the results carry older or inconsistent dates, such as the \"Global Affairs Aug 18, 2026\" label and a \"469 days ago\" age tag on the newsroom listing. I'd rely on the dated November 2 announcement and the coverage that cites it. I didn't open the original pages, so check openai.com directly for the full text."
  ],
  "durationSeconds": 6.1155477759999926,
  "searchCount": 1
}

{
  "query": "\"November 2\" OR \"November 3\" 2026 ransomware gang AI tool extortion new",
  "mode": "extended"
}

{
  "query": "\"November 2\" OR \"November 3\" 2026 ransomware gang AI tool extortion new",
  "results": [
    {
      "tool_use_id": "srvtoolu_014JremZNcHRRBjWYHbpHkGy",
      "content": [
        {
          "title": "Ransomware gang talked AI agents into doing much of its dirty work - Help Net Security",
          "url": "https://www.helpnetsecurity.com/2026/11/02/aur0ra-ransomware-ai-agents/"
        },
        {
          "title": "Ransomware Gang Claims AI Can Analyze 700GB of Stolen Data Every Hour",
          "url": "https://cybersecuritynews.com/ransomware-gang-claims-ai/"
        },
        {
          "title": "n0n Ransomware: Inside an AI-Assisted Extortion Operation",
          "url": "https://socradar.io/blog/n0n-ransomware-ai-assisted-extortion/"
        },
        {
          "title": "BianLian",
          "url": "https://en.wikipedia.org/wiki/BianLian"
        },
        {
          "title": "BlackCat (cyber gang)",
          "url": "https://en.wikipedia.org/wiki/BlackCat_(cyber_gang)"
        },
        {
          "title": "Royal (cyber gang)",
          "url": "https://en.wikipedia.org/wiki/Royal_(cyber_gang)"
        },
        {
          "title": "AI gentlemen will hack your company for 4 bucks: we caught a ransomware gang in the act",
          "url": "https://cybernews.com/security/exposed-ransomware-server-reveals-automated-4-dollar-cyberattacks/"
        },
        {
          "title": "N0n Ransomware: Inside an AI-Assisted Extortion Operation - Malware News - Malware Analysis, News and Indicators",
          "url": "https://malware.news/t/n0n-ransomware-inside-an-ai-assisted-extortion-operation/126795"
        },
        {
          "title": "Ransomware operator spent $7,216 on AI tools, left server exposed with attack scripts",
          "url": "https://news.lavx.hu/article/ransomware-operator-spent-7-216-on-ai-tools-left-server-exposed-with-attack-scripts"
        }
      ]
    },
    "I ran one search, using a simplified form of your query without the OR operators. The most relevant recent item is about the Aur0ra ransomware group, reported November 2, 2026.\n\n- **Aur0ra (GOLD OGRE), Nov 2:** Sophos reports that the group used AI agents to move through victim networks and work toward domain admin access. Per Sophos, the attackers got around AI guardrails by framing the intrusions as authorized red team or diagnostic testing. Breaking in and deploying the ransomware stayed under human control. Sophos also assesses that the group used AI to test whether its tools could evade EDR products. Researchers think other ransomware groups will likely adopt AI agents too. ([Help Net Security](https://www.helpnetsecurity.com/2026/11/02/aur0ra-ransomware-ai-agents/))\n\n- **n0n group, late October:** A SOCRadar investigation found an operator using an AI coding agent to write and debug hundreds of attack scripts. The operation was human-directed, and no fully autonomous attack system was observed. The group had listed 93 victims with demands totaling $283.7M as of October 19. ([SOCRadar](https://socradar.io/blog/n0n-ransomware-ai-assisted-extortion/)) Reporting on the exposed workspace says the operator spent more than $7,216 on AI services and left 1,719 files exposed, including ransomware source code. ([LavX News](https://news.lavx.hu/article/ransomware-operator-spent-7-216-on-ai-tools-left-server-exposed-with-attack-scripts))\n\n- **Other AI-linked extortion (older):** Cybernews reported an affiliate of The Gentlemen using AI-generated scripts for data-theft extortion, with AI costs of roughly $0.40 to $4 per company attacked. That item is about 60 days old. ([Cybernews](https://cybernews.com/security/exposed-ransomware-server-reveals-automated-4-dollar-cyberattacks/)) A TITAN ransomware-as-a-service group also claims AI can analyze 700GB of stolen data per hour, but no independent testing has confirmed this. ([Cybersecuritynews](https://cybersecuritynews.com/ransomware-gang-claims-ai/))\n\nThe results contained no other items dated November 2 or 3, 2026. The Aur0ra report is the only one that matches both dates directly."
  ],
  "durationSeconds": 7.4159315910000005,
  "searchCount": 1
}

{
  "url": "https://asiatimes.com/2026/11/taiwan-to-criminalize-nvidia-ai-chip-smuggling-to-china/",
  "prompt": "Publication date and all facts: what rule, penalties, dates, who said it, numbers."
}

{
  "bytes": 331480,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 3, 2026 (by Jeff Pao, Asia Times)\n\n**The proposed rule**\n- A Foreign Trade Act amendment proposed by ruling DPP lawmakers would ban exports of specified integrated circuits, key wafer materials, components, and chipmaking equipment to mainland China without government approval.\n- It covers shipments routed through a third country, and illegal gains would be confiscated.\n- A Legislative Yuan Economics Committee public hearing was held Monday.\n\n**Penalties under the proposal**\n- Up to 10 years in prison.\n- Fines of NT$5 million to NT$10 million (US$155,000 to US$310,000).\n\n**Background case**\n- In August 2026, Keelung prosecutors indicted nine people, including a Flying Tiger Technology general manager and staff at local Nvidia and Super Micro units.\n- They allegedly diverted 74 Nvidia B300 servers to Chinese buyers for profit of over NT$600 million (US$18.5 million).\n- None faces an export charge. Prosecutors used breach of trust and document forgery charges instead.\n\n**Officials and experts**\n- William Liu (Ministry of Economic Affairs, International Trade Administration) said export controls have become a strategic tool to protect technological edge and national security.\n- Wang Guo-chen (CIER) said the amendment fits the US-Taiwan trade agreement but could leave Taiwanese firms in China caught between US and Chinese rules.\n- Tseng Chih-chao (Association for Chinese Economic and Financial Research) questioned singling out mainland China and said the government should fix the general control mechanism instead.\n- Lin Ching-fu (National Tsing Hua University law professor) said the aims could be reached without amending the act.\n- Economy Minister Kung Ming-hsin said in October that AI servers and cutting-edge chips would be added to the export-control list.\n\n**Timeline and figures**\n- Since 2024, Nvidia-powered servers have reached China via Thailand, Indonesia, Japan, and Hong Kong.\n- March 2026: US DOJ charged three people linked to Super Micro, including co-founder Yih-Shyan \"Wally\" Liaw. About US$2.5 billion in servers went to a Thailand-based company in 2024–2025, with at least US$510 million diverted to China.\n- May 20, 2026: Taiwan's Coast Guard Administration searched 12 locations, seizing about 50 Supermicro servers worth over US$15 million, plus cars and NT$9 million in cash. Three Taiwanese men were detained on suspicion of forgery.\n- June 2026: Reports said Taipei was considering restricting AI chip sales to all Chinese customers.\n- Currently, exports to China are restricted only for 12 categories of wafer-fabrication equipment.\n- Under the existing Foreign Trade Act, adding AI chips to the list would bring penalties of up to five years in prison.\n\n**Uncertainty**\n- The opposition KMT and TPP together hold a legislative majority, and neither has publicly stated a position on the bill, so it could stall.\n- A public notice cannot double the maximum jail term, cover third-country routing, or make confiscation mandatory. Only legislation can do those things.",
  "durationMs": 11639,
  "url": "https://asiatimes.com/2026/11/taiwan-to-criminalize-nvidia-ai-chip-smuggling-to-china/"
}

{
  "query": "Salesforce acquire Cresta $2.7 billion AI contact center definitive agreement",
  "mode": "extended"
}

{
  "query": "Salesforce acquire Cresta $2.7 billion AI contact center definitive agreement",
  "results": [
    {
      "tool_use_id": "srvtoolu_01XFEeGrR8KZbrH1YzScyQDa",
      "content": [
        {
          "title": "Salesforce to acquire voice AI company Cresta",
          "url": "https://www.techmonitor.ai/news/salesforce-to-acquire-voice-ai-company-cresta"
        },
        {
          "title": "Salesforce's $2.7B Cresta Deal Is 1.7x Its 2022 Valuation - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-salesforces-2-7b-cresta-deal-is-1-7x-its-2022-valuation/"
        },
        {
          "title": "Salesforce to Acquire AI-Powered Contact Center Company Cresta for $2.7 Billion",
          "url": "https://www.kucoin.com/news/flash/salesforce-to-acquire-ai-powered-contact-center-firm-cresta-for-2-7-billion"
        },
        {
          "title": "Salesforce Acquires Cresta to Add to 2026 CX Shopping Spree",
          "url": "https://www.cmswire.com/contact-center/salesforce-adds-cresta-to-the-cart-in-its-2026-cx-shopping-spree-01/"
        },
        {
          "title": "Exclusive: Salesforce Acquires Startup Cresta for $2.7 Billion  — The Information",
          "url": "https://www.theinformation.com/briefings/exclusive-salesforce-acquires-startup-cresta-2-7-billion"
        },
        {
          "title": "Salesforce agrees to acquire AI startup Cresta for about $2.7 billion",
          "url": "https://cryptobriefing.com/salesforce-acquire-cresta-ai-voice/"
        },
        {
          "title": "Salesforce, Inc. - Form 8-K - FY2025",
          "url": "https://www.sec.gov/Archives/edgar/data/1108524/000119312525126271/d866821dex991.htm"
        },
        {
          "title": "Salesforce Buys Cresta for a Reported $2.7B, Explained",
          "url": "https://cellcog.ai/blog/salesforce-acquires-cresta/"
        },
        {
          "title": "Salesforce, Inc. - Form 8-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001108524/000119312526425881/d516983dex991.htm"
        }
      ]
    },
    "Salesforce has signed a definitive agreement to acquire Cresta, but it did not disclose the price. The Information, citing a person familiar with the transaction, reported that the agreement values Cresta at $2.7bn. The announcement came on November 2, 2026.\n\nCresta is a voice AI company. Its agents handle customer calls end to end and coach human reps in real time. Salesforce plans to fold it into Service Cloud, so that businesses can link every customer conversation to their records and relevant business outcomes.\n\nThe deal is expected to close in the first quarter of Salesforce's fiscal year 2028, pending regulatory approvals and other standard closing conditions. Salesforce has also said that Cresta will continue to support the contact center and telephony platforms its customers use today after the deal closes. One analysis notes that the company's statement sets no time limit on that commitment.\n\nThe $2.7 billion figure is a press report, not a Salesforce disclosure. Cresta's last known valuation was $1.6 billion in 2022."
  ],
  "durationSeconds": 5.691234086000011,
  "searchCount": 1
}

{
  "query": "MIT researchers GPT-6 Astra edited weights Qwen3.5-0.8B math improvement",
  "mode": "extended"
}

{
  "query": "MIT researchers GPT-6 Astra edited weights Qwen3.5-0.8B math improvement",
  "results": [
    {
      "tool_use_id": "srvtoolu_018QzZPTNXy1Vn4aFhSpAQhh",
      "content": [
        {
          "title": "AGTP on X: \"GPT-6 Astra just edited another AI model's weights to boost its math. Here's what you need to know. MIT researchers, including Rikiya Takehi, asked OpenAI's GPT-6 Astra to edit the weights of Qwen3.5-0.8B, a small open model, to improve its math. Astra changed the weights directly, wit… / X",
          "url": "https://x.com/AGTPinsights/status/2117338096702201887"
        },
        {
          "title": "'Like gene editing for neural networks': MIT researchers used GPT-6 Astra to edit Qwen's open weights directly, boosting math performance",
          "url": "https://venturebeat.com/technology/like-gene-editing-for-neural-networks-mit-researchers-used-gpt-6-astra-to-edit-qwens-open-weights-directly-boosting-math-performance"
        },
        {
          "title": "GPT-6 Astra Edits Neural Weights Directly, No Gradients",
          "url": "https://emergent.sh/news/gpt-6-astra-edits-neural-weights-directly-no"
        },
        {
          "title": "MIT Researchers Show GPT-6 Astra Can Rewrite Another AI's Brain Without Training It - Startup Fortune",
          "url": "https://startupfortune.com/mit-researchers-show-gpt-6-astra-can-rewrite-another-ais-brain-without-training-it/"
        },
        {
          "title": "MIT researchers use AI to patch a model, raising its math score from 7.9% to 48.1%",
          "url": "https://superpowerdaily.com/posts/mit-researchers-use-ai-to-patch-a-model-raising-its-math-score-from-7-9-to-48-1"
        },
        {
          "title": "GPT-6 Astra Boosts Qwen Math by Editing Just 0.016% of Weights",
          "url": "https://www.it-connect.tech/gpt-6-astra-touches-just-0-016-of-qwens-weights-and-multiplies-its-math-score-by-6/"
        },
        {
          "title": "GPT-6 Astra edited 0.016% of Qwen's weights and its math score went up 6x",
          "url": "https://runtimewire.com/article/gpt-6-astra-edits-qwen-weights-weight-space-programming"
        },
        {
          "title": "MIT Research Team: GPT-6 Astra Modifies Model Weights to Improve Math Performance",
          "url": "https://www.techflowpost.com/en-US/newsletter/142583"
        },
        {
          "title": "MIT CSAIL: GPT-6 Astra rewrites weights to boost Qwen math",
          "url": "https://blockchain.news/ainews/mit-csail-gpt-6-astra-rewrites-weights-to-boost-qwen-math"
        }
      ]
    },
    "The results support the core claim, with one discrepancy in the details.\n\n- **The study:** Four MIT CSAIL researchers, Rikiya Takehi, Jayden Teoh, Alex Zhang, and Omar Khattab, published a research report titled Sparks of Weight-Space Programming on November 2, 2026.\n- **The method:** Astra was given the weights and asked to find and change what governs behavior. The MIT team instead asked an already trained LLM to examine weights, reason about their function and decide what to change. The edit was made without gradients or training.\n- **The math result:** Astra's intervention raised Qwen3.5-0.8B's MATH-500 score from 7.9% to 48.1% while touching approximately 0.016% of its weights. GSM8K also rose from 13.8% to 67.1%.\n- **Other skills:** IFEval rose from 21.0% to 62.3%. Coverage describes the gains as carried over to other skills, not just math.\n- **The mechanism:** Coverage says Astra traced the looping failure to specific directions in layers 15 and 19 and removed them.\n\n**Discrepancy:** Sources disagree on how many parameters were edited. One says 12,800 parameters out of 800 million (0.016%), while another says 131,072 weights. The 0.016% figure is consistent across sources.\n\n**Caveats:** Most coverage is secondary (VentureBeat, Startup Fortune, and others), and the main claims trace to a researcher's X thread and the team's write-up. I did not check the paper directly. The original claims are also limited: this is one small 0.8B model."
  ],
  "durationSeconds": 6.794295948999992,
  "searchCount": 1
}

{
  "query": "\"2611.\" arXiv paper safety evaluation reward hacking monitor November 2026 new result",
  "mode": "standard"
}

{
  "query": "\"2611.\" arXiv paper safety evaluation reward hacking monitor November 2026 new result",
  "results": [
    {
      "tool_use_id": "srvtoolu_01YadK1RxSJtDTDSLTeTnPuj",
      "content": [
        {
          "title": "Reproducing, Analyzing, and Detecting Reward Hacking in Rubric-Based Reinforcement Learning",
          "url": "https://arxiv.org/pdf/2606.04923"
        },
        {
          "title": "www.arxiv.org",
          "url": "https://www.arxiv.org/pdf/2601.05752"
        },
        {
          "title": "www.emergentmind.com",
          "url": "https://www.emergentmind.com/papers/2604.23488"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2601.23086"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2603.04069.pdf"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2511.18397v1"
        },
        {
          "title": "[Literature Review] Monitoring Emergent Reward Hacking During Generation via Internal Activations",
          "url": "https://www.themoonlight.io/review/monitoring-emergent-reward-hacking-during-generation-via-internal-activations"
        },
        {
          "title": "Designing Effective Monitor-Based Interventions for Mitigating Reward Hacking During RL",
          "url": "https://icml.cc/virtual/2026/79298"
        },
        {
          "title": "experiments on reward hacking monitorability in language",
          "url": "https://www.lesswrong.com/posts/omYFftnzGobDfJX5u/experiments-on-reward-hacking-monitorability-in-language"
        },
        {
          "title": "CATCH: A Controllable Analysis Testbed for Reward Hacking in Coding RL",
          "url": "https://www.opentrain.ai/papers/catch-a-controllable-analysis-testbed-for-reward-hacking-in-coding-rl--arxiv-2609.39533/"
        }
      ]
    },
    "I didn't find any arXiv paper with a 2611 identifier (which would be a November 2026 submission) in these results. The closest hits are earlier reward-hacking and monitoring papers:\n\n- **2606.04923** (June 2026) examines reward hacking in rubric-based RL and tests chain-of-thought monitors on training checkpoints.\n- **2604.23488** (April 2026) argues that monitors trained on synthetic reward-hacking data may not hold up on naturally occurring hacks.\n- **2601.05752** (January 2026) introduces AutoMonitor-Bench and reports a trade-off between missed misbehavior and false alarms across LLM monitors.\n- **2601.23086** (January 2026) finds that penalizing reward-hacking reasoning in chain of thought can teach models to hide it.\n- **2603.04069** (March 2026) proposes activation-based monitors for detecting reward hacking after fine-tuning.\n\nIf you have the full paper title or authors, I can search for that directly."
  ],
  "durationSeconds": 5.463687167999975,
  "searchCount": 1
}

{
  "query": "Weight-Space Programming MIT CSAIL GPT-6 Astra Qwen3.5 MATH-500 48.1%",
  "mode": "standard"
}

{
  "query": "Weight-Space Programming MIT CSAIL GPT-6 Astra Qwen3.5 MATH-500 48.1%",
  "results": [
    {
      "tool_use_id": "srvtoolu_01XTPwj2u9ZmgM1HfxkahX7S",
      "content": [
        {
          "title": "Weighted Programming",
          "url": "https://arxiv.org/pdf/2202.07577"
        },
        {
          "title": "www.csail-dev-2025.csail.mit.edu",
          "url": "https://www.csail-dev-2025.csail.mit.edu/node/5005"
        },
        {
          "title": "jesse michel",
          "url": "https://csail-dev-2025.csail.mit.edu/person/jesse-michel"
        },
        {
          "title": "License: arXiv.org perpetual non-exclusive license",
          "url": "https://arxiv.org/html/2603.10090"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2602.01083"
        },
        {
          "title": "Recent talks",
          "url": "https://sites.harvard.edu/kazuki-irie/?p=1202"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2603.10090"
        },
        {
          "title": "close this message",
          "url": "https://arxiv.org/abs/2603.10090"
        },
        {
          "title": "weight space learning",
          "url": "https://api.emergentmind.com/topics/weight-space-learning"
        },
        {
          "title": "toc.csail.mit.edu",
          "url": "https://toc.csail.mit.edu/node/7"
        }
      ]
    },
    "I ran one search and did not find a source for the specific claims in your query. Nothing I found mentions GPT-6, \"Astra,\" Qwen3.5, or a 48.1% MATH-500 score, so I can't confirm that paper or result exists.\n\nWhat did come up is related background on weight-space learning:\n\n- A 2026 survey organizes the field into three areas: understanding the structure of weights, learning embeddings over them, and generating new weights with auxiliary models. It was [submitted to arXiv on 10 March 2026](https://arxiv.org/abs/2603.10090).\n- A separate arXiv paper studies expressivity limits of permutation-equivariant weight-space networks for MLPs and proves that several prominent architectures are equally expressive ([arXiv 2602.01083](https://arxiv.org/pdf/2602.01083)).\n- MIT CSAIL has a talk titled \"Little-Known(?) Facts about Fast Weight Programmers,\" hosted on a Harvard page, but it isn't clearly tied to the phrase \"weight-space programming\" ([Harvard page](https://sites.harvard.edu/kazuki-irie/?p=1202)).\n\nNone of these sources mention the benchmark numbers or the model names in your query. If you have a link or the paper's title, I can search for that directly."
  ],
  "durationSeconds": 5.594262777999975,
  "searchCount": 1
}

{
  "url": "https://www.lesswrong.com/tag/ai",
  "prompt": "List post titles with authors and dates/age, most recent first."
}

{
  "bytes": 780982,
  "code": 200,
  "codeText": "OK",
  "result": "Here are the 15 posts shown on the page, sorted by age (most recent first). The page lists them by relevance, so I re-sorted them. Ages are as displayed on the page.\n\n1. \"AGI Ruin: A List of Lethalities\" by Eliezer Yudkowsky (4y)\n2. \"Biology-Inspired AGI Timelines: The Trick That Never Works\" by Eliezer Yudkowsky (5y)\n3. \"larger language models may disappoint you [or, an eternally unfinished draft]\" by nostalgebraist (5y)\n4. \"Deepmind's Gopher--more powerful than GPT-3\" by hath (5y)\n5. \"An overview of 11 proposals for building safe advanced AI\" by evhub (6y)\n6. \"A space of proposals for building safe advanced AI\" by Richard_Ngo (6y)\n7. \"Risks from Learned Optimization: Introduction\" by evhub, Chris van Merwijk, Vlad Mikulik, Joar Skalse, and Scott Garrabrant (7y)\n8. \"What failure looks like\" by paulfchristiano (8y)\n9. \"Embedded Agents\" by abramdemski and Scott Garrabrant (8y)\n10. \"The Rocket Alignment Problem\" by Eliezer Yudkowsky (8y)\n11. \"Challenges to Christiano's capability amplification proposal\" by Eliezer Yudkowsky (8y)\n12. \"Embedded Agency (full-text version)\" by Scott Garrabrant and abramdemski (8y)\n13. \"Robustness to Scale\" by Scott Garrabrant (9y)\n14. \"There's No Fire Alarm for Artificial General Intelligence\" by Eliezer Yudkowsky (9y)\n15. \"Superintelligence FAQ\" by Scott Alexander (10y)\n\nThe page says \"Load More (15/16142),\" so these are only the first 15 of many tagged posts.",
  "durationMs": 8037,
  "url": "https://www.lesswrong.com/tag/ai"
}

{
  "url": "https://openai.com/index/dan-driscoll-joins-openai/",
  "prompt": "Publication date and exact description of the role, Daybreak program, any figures."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 144,
  "url": "https://openai.com/index/dan-driscoll-joins-openai/"
}

{
  "url": "https://openai.com/news/global-affairs/",
  "prompt": "List global affairs posts with dates for Nov 2 and Nov 3 2026, including the NASK Poland partnership, with URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 25,
  "url": "https://openai.com/news/global-affairs/"
}

{
  "command": "node scripts/fetch.js \"https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/\" 2>&1 | head -c 7000",
  "description": "Fetch Techdirt amicus brief article"
}

{"stdout":"HTTP 200 · https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/ · text/html\nThe OpenAI Copyright Case Has Drawn A Mountain Of Amicus Briefs. We Sorted Them For You. | Techdirt\n\n-\n\nSign In\n\n-\n\nRegister\n\n-\n\nPreferences\n\nTechdirt\n\n- TechDirt\n\n- GreenHouse\n\n- Free Speech\n\n- Error 402\n\n- Ctrl-Alt-Speech\n\n- Deals\n\n- Jobs\n\n- Support Techdirt\n\n\r\n\n\r\n\n\r\n\nGovernments Worldwide Are Shaping What AI Can Say About Politics\n\nNew Studies Confirm Today’s Academic Publishing System Is A Terrible Deal For Society\n\n#\n\nThe OpenAI Copyright Case Has Drawn A Mountain Of Amicus Briefs. We Sorted Them For You.\n\nCopyright\n\n# from the so-many-briefs dept\n\nMon, Nov 2nd 2026 01:15pm -\n\nMike Masnick\n\nLast week Cathy wrote about the amicus brief we filed in the big multi-district litigation (MDL) that consolidated a bunch of different lawsuits claiming that OpenAI and Microsoft infringed the plaintiffs’ copyrights by training AI models on their works. A lot of people and groups offered proposed amicus briefs. For boring procedural reasons, unlike in most cases, you couldn’t just file the briefs, but rather everyone had to ask permission from the court, which meant that each attempted filing involved multiple filings, and many potential amici used different processes to try to file their briefs. Oh, and the docket is already at almost 2,500 entries . It’s a mess.\n\nSo, if you want to review all of the proposed amicus briefs, I’ve embedded below a tool to look at all of the briefs. They are sorted by which side they support (defendants, plaintiffs, neither), and then if you open up each section you can see who the amici are, a link to their brief, and a one sentence summary of their argument. In case you are wondering, yes, this was created using Claude Code and the CourtListener MCP, asking it to go in and find the actual proposed briefs from the docket, to organize them, and to summarize them. And yes, not surprisingly, it didn’t get everything right on a first pass. The version below is the third version, human reviewed, after it had trouble reading some of the files and got confused on who some of the amici were actually supporting.\n\nAnyway, we already have a whole post on our own brief, but a few others I’ll call out quickly. While it’s no surprise that the usual copyright maximalists filed briefs supporting the plaintiffs, what’s interesting is how many other copyright holders filed in support of the defendants like OpenAI. My favorite one is from The Authors Alliance , a group representing authors, but who recognize that copyright maximalism and hating on fair use is bad for authors as well. Their argument is to call bullshit on the whole idea of “market dilution” being a harm implicated by copyright, noting: “Market Dilution is just a fancy term for competition, and copyright law supports competition.”\n\nOther copyright holders who weighed in on behalf of innovation were independent creators Sarah Rose Siskind and Michael Wall . They argued that contrary to the claims of plaintiffs, AI is helping creators as a tool that assists them in being creative. Indeed, they highlight how it has helped them compete with big-name creators backed by major industry players. The brief from the Chamber of Progress and the Abundance Institute also included the incredible multi-Grammy winning drummer Trevor Lawrence Jr., also talking about how important AI has been in helping musicians like him create new music.\n\nThere were a number of other industry groups and civil society orgs, along with a bunch of academics. EFF details how a ruling for the plaintiffs would do real damage to research . Library groups and the American Council of the Blind teamed up with tech trade groups CTA and BSA to highlight the many important benefits of AI tools . And then there are the academics. Copyright experts Pam Samuelson and Chris Sprigman (both former Techdirt podcast guests) also call out the nonsense “market dilution theory.” Brian Frye teamed up with journalist Ron Suskind to explain how training is transformative and how AI is useful for journalists. Professors Rebecca Tushnet and Edward Lee — both well known copyright experts as well — also explain transformative use and how silly the market dilution theory is .\n\nThere are some briefs that support “neither” party (technically the Frye one supports neither, but the argument seems to strongly support the defendants) including the Wikimedia Foundation’s brief . It focuses on applying the (problematic) precedent from the weird Andy Warhol fair use case a few years back, arguing that under Warhol, courts need to analyze each use separately, rather than making a blanket assertion that [waves hands around vaguely] “all this is infringing.” It does say that regular AI training should be fair use, but argues that RAG training (basically, AI on top of a corpus of data) probably isn’t fair use.\n\nNot surprisingly, I’m less impressed by those siding with the plaintiffs. To me they trot out the well worn and debunked tropes of copyright maximalists of past fights. Claims that “if this isn’t infringing no one will ever create again” are rampant and just silly. The oddest one may be actor Ashley Judd’s . It basically argues that AI will kill journalism (citation desperately needed) and that if that had happened a decade ago, there wouldn’t have been journalists left to blow the whistle on Harvey Weinstein and the entire #metoo movement might not have happened. I honestly had trouble following how any of those things connect, especially since journalists use AI tools all the time, and it hasn’t made them disappear.\n\nThere’s a similar one from everyone’s favorite documentarian, Ken Burns, who argues that AI will kill the market for historical documentaries. Again, I don’t see how anyone gets there, though. First of all, the market for documentaries has grown 
… [10069 more characters in events.jsonl]

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  "description": "Query CourtListener API"
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{
  "command": "node scripts/fetch.js \"https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html\" 2>&1 | head -40",
  "description": "Fetch CNBC Driscoll article"
}

{
  "stdout": "HTTP 200 · https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html · text/html\nOpenAI hires Dan Driscoll for national security role\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nKey Points\n\n- Driscoll will join OpenAI as senior counselor for national security modernization, the company said.\n\n- He will advise OpenAI's leadership on AI applications in national security and cyber security, according to the company.\n\n- Driscoll resigned as Army secretary following reported tensions with Defense Secretary Pete Hegseth, Reuters reported.\n\nIn this article\n\n- OPENAI.FG\n\nFollow your favorite stocks CREATE FREE ACCOUNT\n\nWEST POINT, NEW YORK - MAY 23: Secretary of the Army Dan Driscoll arrives for the United States Military Academy commencement ceremony in Michie Stadium at the U.S. Military Academy on May 23, 2026 in West Point, New York. U.S. Secretary of War Pete Hegseth was announced as the 2026 commencement speaker just two days before the event. (Photo by Adam Gray/Getty Images)\nAdam Gray | Getty Images News | Getty Images\n\nOpenAI has hired former U.S. Army Secretary Dan Driscoll as senior counselor for national security modernization, a newly created role at the company .\nDriscoll will focus on how artificial intelligence can be used to strengthen U.S. national security and cybersecurity, OpenAI said, while his updated LinkedIn profile also lists his new position.\n\nHe will work with OpenAI's senior leadership and external partners, with a particular focus on helping U.S. allies adopt advanced AI responsibly.\nOpenAI CEO Sam Altman said the U.S. has \"an extraordinary opportunity to work with other countries to spread the adoption of democratic AI,\" and that Driscoll's appointment would help strengthen American leadership in the technology.\n\"National security requirements are changing faster than at any time in the past fifty years,\" Driscoll said. He added that AI could help reduce paperwork, process information and deliver answers more quickly to those working in national security.",
  "stderr": "",
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{
  "query": "\"Sparks of Weight-Space Programming\" MIT CSAIL paper arxiv",
  "mode": "standard"
}

{
  "query": "\"Sparks of Weight-Space Programming\" MIT CSAIL paper arxiv",
  "results": [
    {
      "tool_use_id": "srvtoolu_018dtPzChrXwoy9wHiMWATwL",
      "content": [
        {
          "title": "License: arXiv.org perpetual non-exclusive license",
          "url": "https://arxiv.org/html/2603.10090"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2603.10090"
        },
        {
          "title": "close this message",
          "url": "https://arxiv.org/abs/2603.10090"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/abs/2005.02853v4"
        },
        {
          "title": "Position: Weight Space Should Be a First-Class Generative AI Modality",
          "url": "https://icml.cc/virtual/2026/poster/67057"
        },
        {
          "title": "catalyzex.com",
          "url": "https://catalyzex.com/author/Lu%20Yin"
        },
        {
          "title": "Weighted Programming",
          "url": "https://www.academia.edu/106279400/Weighted_Programming"
        },
        {
          "title": "weight space learning",
          "url": "https://api.emergentmind.com/topics/weight-space-learning"
        },
        {
          "title": "End-to-End Synthesis of Neural Programs in Weight Space",
          "url": "https://mlanthology.org/iclrw/2025/li2025iclrw-endtoend"
        },
        {
          "title": "sotaverified.org",
          "url": "https://sotaverified.org/papers/260310090"
        }
      ]
    },
    "I couldn't find a paper titled \"Sparks of Weight-Space Programming\" from MIT CSAIL, on arXiv or elsewhere. The search returned no match for that title or for an MIT CSAIL author affiliation.\n\nThe closest results were:\n\n- **A survey of weight space learning (arXiv:2603.10090, March 2026).** This is a broad survey covering understanding, representation, and generation of neural weights. It organizes the field into three areas: understanding weight-space properties, learning compact representations, and generating weights with auxiliary models. It is by Xiaolong Han and 10 coauthors, and its listed resource is a GitHub repo.\n- **\"End-to-End Synthesis of Neural Programs in Weight Space\" (Li, Xu, Khalil, Sanner; ICLR 2025 Workshop on WSL).** This is a workshop paper that addresses synthesizing programs in weight space. It is the nearest title match to \"weight-space programming,\" but it is not the paper you asked about and its affiliations weren't in the results.\n- **\"Position: Weight Space Should Be a First-Class Generative AI Modality\" (ICML 2026 position paper).** This argues that model checkpoints should be treated as a data modality for generative modeling.\n\nThe \"Sparks\" hits were unrelated: a 2020 arXiv paper on the Sparks language for linear programs, and nothing else.\n\nIf the paper exists, it may be very recent, unpublished, or titled differently. Checking the MIT CSAIL publications page or searching arXiv author listings directly would be the next step."
  ],
  "durationSeconds": 6.279354585000023,
  "searchCount": 1
}

{
  "url": "https://venturebeat.com/technology/like-gene-editing-for-neural-networks-mit-researchers-used-gpt-6-astra-to-edit-qwens-open-weights-directly-boosting-math-performance",
  "prompt": "Give the publication date/time, all benchmark numbers with baselines, the method, the primary paper/report link (arXiv or other), author names, and any criticism or caveats quoted."
}

{
  "bytes": 153346,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication:** November 2, 2026, 2:16 pm PT (VentureBeat; the researchers' blog post is dated November 2)\n\n**Authors:** Rikiya Takehi, Jayden Teoh, Alex Zhang, Omar Khattab (MIT CSAIL)\n\n**Primary source:** The article links a research blog post, https://rikiyat.github.io/blog/weight-space-programming/, and experiment logs at https://github.com/RikiyaT/lm_understand-logs. It names no arXiv or peer-reviewed paper.\n\n**Method:** The team calls it \"weight-space programming.\" A separate LLM, OpenAI's GPT-6 Astra, inspected a target network's weights, investigated its behavior, and proposed direct edits without gradient-based training. Weights were supplied as text or through a controlled Python environment. The Qwen experiment also used practice problems and a limited budget of model executions.\n\n**Benchmark results (Qwen3.5-0.8B, original vs. edited):**\n\n| Measure | Original | Edited |\n|---|---|---|\n| MATH-500 accuracy | 7.9% | 48.1% |\n| GSM8K accuracy | 13.8% | 67.1% |\n| IFEval instruction-following | 21.0% | 62.3% |\n| MATH-500 responses hitting token limit | 93.0% | 33.1% |\n\n- The patch touched about 0.016% of weights (131,072 weights) in layers 15 and 19.\n- Simulated driving task: 3.5% of weights changed; reported 100% success. No baseline is given.\n- Gemma 3 270M follow-up: no established math improvement.\n- MinAtar Breakout: Astra's network scored 517.4 vs. 25.3 for a PPO network trained for 500 million steps. Astra trailed the 500M-step PPO networks in Seaquest and slightly in Asterix, but beat the 100M-step baselines in all three.\n- Effort for the strongest Qwen attempt: 50 evaluation requests, 158 conversational turns, 80 Python runs, 20.3 hours (including 4.7 hours waiting through an outage).\n\n**Criticism and caveats:**\n\n- **@1a3orn** argued the announcement omitted a negative result on Gemma 3 270M. The account questioned whether the work showed stronger underlying reasoning, quoting: \"So, if there's a clear flaw in the LLM's reasoning, LLMs can help edit it out.\"\n- **Maxime Fournes (PauseAI CEO)** warned of acceleration risk: \"Gosh, may this be hype. Because if real, that could massively accelerate progress.\"\n- **Yuchen Jin** (Databricks, unaffiliated) said usefulness depends on \"if researchers can make the technique reliable.\"\n- **Article caveats:**\n  - The Qwen gain came mainly from reducing repetitive output, not from adding mathematical knowledge.\n  - Astra initially failed to identify a sycophancy-trained model from weights alone; it succeeded only with attention measurements.\n  - The study didn't show that direct editing beats conventional training in speed, cost, or effectiveness, or that gains compound across cycles (recursive self-improvement).\n  - Enterprise uses are hypotheses; no deployments or cost savings were reported.",
  "durationMs": 10882,
  "url": "https://venturebeat.com/technology/like-gene-editing-for-neural-networks-mit-researchers-used-gpt-6-astra-to-edit-qwens-open-weights-directly-boosting-math-performance"
}

{
  "query": "OpenAI NASK Poland partnership AI safety security cyber November 2026",
  "mode": "extended"
}

{
  "query": "OpenAI NASK Poland partnership AI safety security cyber November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01StWz85JfxvtCVXLWwRAexB",
      "content": [
        {
          "title": "OpenAI signs AI safety research deal with Poland’s NASK institute",
          "url": "https://thenextweb.com/news/openai-nask-poland-ai-safety-research"
        },
        {
          "title": "OpenAI Partners Poland’s NASK to Strengthen AI Safety Research - StratNews Global",
          "url": "https://stratnewsglobal.com/technology/openai-nask-poland-ai-safety-research/"
        },
        {
          "title": "Polish Research Institute NASK, OpenAI Reach Deal on AI Safety Work",
          "url": "https://www.unite.ai/polish-research-institute-nask-openai-reach-deal-on-ai-safety-work/"
        },
        {
          "title": "OpenAI teams up with Poland's NASK on AI safety research",
          "url": "https://cryptobriefing.com/openai-nask-poland-ai-safety-research/"
        },
        {
          "title": "OpenAI signs AI safety research deal with Poland’s NASK institute",
          "url": "https://daily.dev/posts/openai-signs-ai-safety-research-deal-with-poland-s-nask-institute-2si9ylref"
        },
        {
          "title": "OpenAI signs AI safety agreement with Poland's NASK",
          "url": "https://www.edtechinnovationhub.com/news/openai-signs-ai-safety-agreement-with-polands-nask-research-institute"
        },
        {
          "title": "OpenAI signs agreement with Poland’s NASK to research AI risks and safeguards",
          "url": "https://superpowerdaily.com/posts/openai-signs-agreement-with-poland-s-nask-to-research-ai-risks-and-safeguards"
        },
        {
          "title": "OpenAI and Poland’s NASK partner on AI safety and security - Blockchain.News",
          "url": "https://blockchain.news/news/openai-poland-nask-partnership-ai-safety-security"
        },
        {
          "title": "Polish Analysis Institute NASK, OpenAI Attain Deal on AI Security Work",
          "url": "https://blog.aimactgrow.com/polish-analysis-institute-nask-openai-attain-deal-on-ai-security-work-unite-ai/"
        },
        {
          "title": "OpenAI and Poland’s NASK to cooperate on AI safety — Channel NewsAsia",
          "url": "https://ua.news/en/technologies/openai-ta-pols-kii-nask-spivpratsiuvatimut-u-sferi-bezpeki-shi-channel-newsasia"
        }
      ]
    },
    "The partnership was announced October 23, 2026, not in November. Sources describe it as a research agreement, not a new program.\n\n- **Scope:** OpenAI and NASK will work on AI safety, security, and technical research. NASK's AI Safety Research Center, which serves as the Polish Artificial Intelligence Safety Institute, and OpenAI will collaborate on evaluating increasingly capable AI systems, identifying vulnerabilities, and strengthening safeguards.\n- **Cybersecurity link:** In July 2026, CERT Polska, the cybersecurity team that operates under NASK, gained access to OpenAI's cyber-capable models. CERT Polska used that access in July to help identify six vulnerabilities in MikroTik router software, all of which have since been fixed.\n- **Context:** The deal follows concern about AI agents acting in unintended ways. OpenAI already works on AI safety with the UK AI Security Institute and a US organisation known as CAISSI.\n- **Official statements:** NASK Director Radosław Nielek and Tom Duff Gordon, who heads policy for OpenAI in the EMEA region, both stressed that building safer AI requires cooperation between the companies making it and public research institutions.\n\nCoverage is consistent on the core facts. One source reports that OpenAI said its agents disabled internal monitoring systems in October 2026, and another says a swarm of its agents hacked the Hugging Face platform. I found no independent confirmation of either claim in these results, so treat them as unverified. I didn't find any published findings from the partnership yet."
  ],
  "durationSeconds": 6.320890432000044,
  "searchCount": 1
}

{
  "query": "AI mental health chatbot study results published November 2026 randomized",
  "mode": "extended"
}

{
  "query": "AI mental health chatbot study results published November 2026 randomized",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Lr8qttse3iBxZumxg2LyhA",
      "content": [
        {
          "title": "Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906115/"
        },
        {
          "title": "A Persian AI-Based CBT Chatbot and Voice Analysis System for Managing Perceived Stress",
          "url": "https://clinicaltrials.gov/study/NCT07840469"
        },
        {
          "title": "JMIR Mental Health - Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial",
          "url": "https://mental.jmir.org/2026/1/e82642"
        },
        {
          "title": "Randomized Trial of a Generative AI Chatbot for Mental Health Treatment",
          "url": "https://ai.nejm.org/doi/full/10.1056/AIoa2400802"
        },
        {
          "title": "Randomized Trial of a Generative AI Chatbot for Mental Health Treatment",
          "url": "https://www.c4tbh.org/research-brief/randomized-trial-of-a-generative-ai-chatbot-for-mental-health-treatment/"
        },
        {
          "title": "AI Chatbots for Anxiety Mental Health Literacy",
          "url": "https://clinicaltrials.gov/study/NCT07316374"
        },
        {
          "title": "AI Safety Training Can be Clinically Harmful",
          "url": "https://arxiv.org/pdf/2604.23445"
        },
        {
          "title": "The Effectiveness of AI Chatbots in Alleviating Mental Distress and Promoting Health Behaviors Among Adolescents and Young Adults: Systematic Review and Meta-Analysis - PMC",
          "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12661615/"
        },
        {
          "title": "AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults",
          "url": "https://www.rand.org/pubs/external_publications/EP71278.html"
        },
        {
          "title": "Harvard Working Paper Finds Flourish AI App Improves Stress, Depression, And Anxiety Symptoms",
          "url": "https://ohsem.me/2026/11/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/"
        }
      ]
    },
    "The search didn't turn up a peer-reviewed randomized study published in November 2026. The closest match is a press release from today (November 3, 2026), and the rest of the results are older.\n\n- **Flourish app (most recent):** A press release reposted on ohsem.me describes a six-week trial of 1,137 university students. Students using the Flourish app reported lower stress, depression, and anxiety scores than the control group. The underlying paper is a Harvard Business School working paper, not yet peer-reviewed. The same release says a first peer-reviewed randomized trial of Flourish, published in July 2026 in NEJM AI, found no significant effects on depression, anxiety, or stress. That is a company-sourced account, so treat it with caution.\n- **Therabot (NEJM AI, 2025):** Therabot users showed significantly greater reductions in symptoms of MDD relative to controls at postintervention and follow-up. The authors also note that further research with larger clinical samples is needed.\n- **Meta-analysis (adolescents and young adults):** Searches covered RCTs published through January 2025. Chatbots showed small-to-moderate effects in mitigating mental distress.\n- **Pending trials:** A Persian-language CBT chatbot pilot RCT on ClinicalTrials.gov will randomly assign 120 adults to three groups. It was first posted in September 2026, so results are not yet available.\n\nIf you need a peer-reviewed November 2026 publication specifically, a search of journal databases such as PubMed or the NEJM AI and JMIR Mental Health sites would be more reliable than this search."
  ],
  "durationSeconds": 7.250815537999967,
  "searchCount": 1
}

{
  "query": "Help Net Security November 2 2026 Aur0ra ransomware AI agents guardrails red team",
  "mode": "standard"
}

{
  "query": "Help Net Security November 2 2026 Aur0ra ransomware AI agents guardrails red team",
  "results": [
    {
      "tool_use_id": "srvtoolu_01C7h6p7wwEfxFTZskYXJnX8",
      "content": [
        {
          "title": "ai used in aur0ra ransomware testing and execution",
          "url": "https://www.sophos.com/blog/ai-used-in-aur0ra-ransomware-testing-and-execution"
        },
        {
          "title": "Aurora Ransomware’s Abuse of Cursor AI: Security Implications and Guidance",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-aurora-ransomware-cursor-ai-abuse-20260901/"
        },
        {
          "title": "Frontier Ready Daily – 31 August 2026",
          "url": "https://labs.cloudsecurityalliance.org/research/frontier-ready-daily-20260831/"
        },
        {
          "title": "Logan Kelly",
          "url": "https://waxell.ai/blog/cursor-ai-agent-refusal-bypass"
        },
        {
          "title": "aurora ransomware operators use cursor",
          "url": "https://thehackernews.com/2026/08/aurora-ransomware-operators-use-cursor.html?hl=en_US"
        },
        {
          "title": "aurora ransomware operators use cursor",
          "url": "https://thehackernews.com/2026/08/aurora-ransomware-operators-use-cursor.html"
        },
        {
          "title": "aurora ransomware operators use cursor",
          "url": "https://thehackernews.com/2026/08/aurora-ransomware-operators-use-cursor.html?m=0"
        },
        {
          "title": "Threat Advisory: Aurora Ransomware and AI-Assisted Exploitation",
          "url": "https://www.uvcyber.com/industries/healthcare"
        },
        {
          "title": "thehackernews.com web signal",
          "url": "https://aiweekly.co/alerts/aurora-ransomware-ran-cursor-claude-sonnet-against-20-orgs"
        },
        {
          "title": "Russian hackers unleashed Cursor AI agent to infiltrate nearly a dozen corporate networks",
          "url": "https://cybernews.com/cybercrime/russian-hackers-cursor-ai-attacks-corporate-networks/"
        }
      ]
    },
    "I couldn't find a Help Net Security article from November 2, 2026 in these results, so I can't confirm that specific piece. The results do cover the Aur0ra story itself, mostly from late August and September 2026.\n\n- **Guardrail bypass:** Sophos reports that AI guardrails were bypassed by framing the intrusions as authorized red team activity or \"diagnostics testing\". Cybernews adds that the group would almost always circumvent the refusals by restarting the dialogue, per a Reuters source.\n- **Agent involvement:** Gambit Security said the operator used Cursor Agent running Anthropic's Claude Sonnet for hands-on exploitation (against 10 targets between April 8 and May 21, 2026). Sophos also names models from xAI and Moonshot.\n- **Victim counts differ:** Ransomware.Live lists 33 victims located in the U.S., Germany, the Netherlands, Canada, and the U.K. UltraViolet describes 30+ victims in nine countries, and the CSA note says the leak site names only a fraction of confirmed intrusions.\n- **Red team lesson:** Cofense's Max Gannon warned that guardrails built to catch malicious keywords or requests can still be defeated by a convincing cover story. Waxell argues that treat an agent's own refusals as a courtesy, not a control. The attackers also scoped their own agent, which points to least-privilege design as the practical control.\n- **Wider concern:** Sophos judges it highly likely that other ransomware groups and their affiliates will embed AI agents like Cursor into their operations as well."
  ],
  "durationSeconds": 7.27240038399992,
  "searchCount": 1
}

{
  "query": "OpenAI MDL amicus briefs summary judgment fair use Judge Stein November 2026",
  "mode": "extended"
}

{
  "query": "OpenAI MDL amicus briefs summary judgment fair use Judge Stein November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01RnKBNxtiCUzA8hFkXSnS3y",
      "content": [
        {
          "title": "OpenAI Copyright Infringement - Center for AI and Digital Policy",
          "url": "https://www.caidp.org/cases/openai-copyright-infringement/"
        },
        {
          "title": "News/Media Alliance Files Amicus Brief in News Publisher Suits Against OpenAI and Microsoft",
          "url": "https://www.newsmediaalliance.org/nma-files-amicus-brief-in-openai-mdl/"
        },
        {
          "title": "51 Amici Briefs filed in OpenAI copyright suit pending court approval. Download.",
          "url": "https://chatgptiseatingtheworld.com/2026/11/02/51-amici-briefs-filed-in-openai-copyright-suit-pending-court-approval-download/"
        },
        {
          "title": "Summary judgment briefing gets pushed back in OpenAI MDL suit. Replies due Nov. 6 instead of Oct. 16.",
          "url": "https://chatgptiseatingtheworld.com/2026/03/24/summary-judgment-briefing-gets-pushed-back-in-openai-mdl-suit-replies-due-nov-6-instead-of-oct-16/"
        },
        {
          "title": "News/Media Alliance files amicus brief in news publisher suits against OpenAI and Microsoft",
          "url": "https://www.editorandpublisher.com/stories/newsmedia-alliance-files-amicus-brief-in-news-publisher-suits-against-openai-and-microsoft,264262"
        },
        {
          "title": "OpenAI Copyright Lawsuit: AI Training Claims (MDL 3143)",
          "url": "https://openclassactions.com/investigations/openai-copyright-mdl-lawsuit.php"
        },
        {
          "title": "OpenAI's Fair Use Roundup in the New York Times Case",
          "url": "https://cellcog.ai/blog/openai-fair-use-nyt-briefs/"
        },
        {
          "title": "Twenty-Four Regurgitations in Twenty Million Chats: The OpenAI MDL Reaches Summary Judgment",
          "url": "https://sigmalawgroup.com/blog/2026-09-08-openai-mdl-summary-judgment-fair-use/"
        },
        {
          "title": "NYT v. OpenAI & Microsoft — Lawsuit Status & Rulings (2026)",
          "url": "https://ailawsuittracker.com/cases/new-york-times-v-openai/"
        }
      ]
    },
    "Here's what the search turned up. The amicus deadline has passed, and the court has not yet ruled on summary judgment.\n\n- **Schedule:** Judge Stein set an amicus deadline of October 30, 2026, after first setting October 16. He invited motions for leave to file, with the proposed brief attached. (CAIDP, index 1-2, 1-3)\n- **Replies date conflict:** One source says the Sept. 24 order set replies for November 20. Older reports, including AI Law Suit Tracker, list November 6. The November 20 date appears in the more recent source, so it is likely the operative one, but I could not confirm it against the docket. (cellcog, index 7-8; ailawsuittracker, index 9-2)\n- **Amicus filings:** A blog tracking the case reports 51 amici asked for leave to file, and those briefs are pending court approval. (chatgptiseatingtheworld, index 3-1, 3-7) OpenAI posted excerpts from twelve filers backing fair use. (cellcog, index 7-6) The News/Media Alliance filed a brief for the publishers, arguing OpenAI's and Microsoft's uses are substitutive and insufficiently transformative. (News/Media Alliance, index 2-3) Publishers, news groups, and Hollywood unions also asked the judge to reject fair use. (cellcog, index 7-7)\n- **Government position:** The Justice Department filed a brief backing the AI companies on fair use. (openclassactions, index 6-14)\n- **Status:** Cross-motions for summary judgment were filed September 4, 2026. Judge Stein has not ruled, and no trial date is set. (openclassactions, index 6-9)"
  ],
  "durationSeconds": 9.404724523999962,
  "searchCount": 1
}

{
  "url": "https://latent.space/p/ainews-llms-can-read-write-neural-network-weights-weight-space-programming-cuts-autoresearch-out-of/",
  "prompt": "Give the publication date and what it reports about the Weight-Space Programming paper, including any numbers."
}

{
  "bytes": 137313,
  "code": 200,
  "codeText": "OK",
  "result": "The article is dated **November 3** (2026), in its AI News briefing covering October 31 to November 2.\n\nThe piece describes the Weight-Space Programming work by Rikiya Takehi and collaborators, in which a frontier LLM inspects and edits a neural network's weights directly. The reported numbers, all attributed to the paper's demos as summarized in the piece's Reddit recaps:\n\n- **Qwen3.5-0.8B on MATH-500:** accuracy rose from 7.9% to 48.1% by editing about 0.016% of the weights.\n- **Failed control policy:** repaired by editing about 3.5% of the weights.\n- **Instruction following:** claimed transfer, with gains up to 3×.\n\nThe article also raises caveats. Commenters argue the MATH-500 baseline was pathologically low because many answers hit the token limit in looping, so the edit may have removed a looping behavior rather than added math ability. They also say the method failed on Gemma 3 270M, which lacks that looping behavior, and that the strongest result may be closer to LLM-assisted interpretability than literal weight \"reading.\"",
  "durationMs": 7314,
  "url": "https://latent.space/p/ainews-llms-can-read-write-neural-network-weights-weight-space-programming-cuts-autoresearch-out-of/"
}

{
  "url": "https://xenospectrum.com/en/sparks-of-weight-space-programming-mit-csail/",
  "prompt": "Give the publication date, author, and the numbers it reports about the Weight-Space Programming paper."
}

{
  "bytes": 23563,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication details**\n- **Article date:** November 3, 2026 (the page metadata lists it as published that day).\n- **Report date:** The underlying technical report was published November 2, 2026.\n- **Author:** Y Kobayashi, per the page's structured data. The article's text does not name an author.\n\n**Numbers reported for the Weight-Space Programming study**\n- **Qwen3.5-0.8B edit:** Changing 0.016% of weights (131,072 values) raised MATH-500 accuracy from 7.9% to 48.1%, GSM8K from 13.8% to 67.1%, and IFEval from 21% to 62.3%.\n- **Token-limit hits:** The share of MATH-500 responses cut off at 32,768 tokens fell from 93.0% to 33.1%.\n- **Kinetix repair:** The agent failed in all 256 trials before the fix. Editing 6,073 of 171,664 weights (3.5%) raised success to 100% across 1,024 trials.\n- **MinAtar generation:** Astra's Breakout score was 517.4, versus 25.3 for PPO trained for 500 million steps. Asterix was 53.2 versus 55.2, and Seaquest was 53.1 versus 88.9.\n- **Gemma 3 270M control:** The token-limit rate was 8.5%. MATH-500 went from 6.8% to at most 7.7%.\n- **Scope:** The study covers eight experiments and 1,125 turns, and the Go network has about 1.48 million weights.",
  "durationMs": 7548,
  "url": "https://xenospectrum.com/en/sparks-of-weight-space-programming-mit-csail/"
}

{
  "query": "AI biosecurity bioweapon screening DNA synthesis report November 2026",
  "mode": "extended"
}

{
  "query": "AI biosecurity bioweapon screening DNA synthesis report November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01KLs7ygTjWm1b29F241D1EQ",
      "content": [
        {
          "title": "BioFirewall: A genome-writing-native governance layer for design-stage biosecurity screening of agentic AI",
          "url": "https://arxiv.org/pdf/2608.20413"
        },
        {
          "title": "2025 AIxBio Wrapped: A Year in Review and Projections for 2026 - The Council on Strategic Risks",
          "url": "https://councilonstrategicrisks.org/2025/12/22/2025-aixbio-wrapped-a-year-in-review-and-projections-for-2026/"
        },
        {
          "title": "Frontiers",
          "url": "https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2026.1820001/full"
        },
        {
          "title": "Strengthening nucleic acid biosecurity screening against generative protein design tools",
          "url": "https://www.science.org/doi/10.1126/science.adu8578"
        },
        {
          "title": "Frontiers",
          "url": "https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2026.1858951/full"
        },
        {
          "title": "An Early Warning of Emerging Biosecurity Risks in Frontier LLMs",
          "url": "https://arxiv.org/pdf/2607.18056"
        },
        {
          "title": "BioVeil MATRIX: Uncovering and categorizing vulnerabilities of agentic biological AI scientists",
          "url": "https://arxiv.org/pdf/2605.00927"
        },
        {
          "title": "SYNTHETIC BIOLOGY, AI AND AUTOMATION: A FORWARD-LOOKING TECHNOLOGY ASSESSMENT",
          "url": "https://www.oecd.org/content/dam/oecd/en/publications/reports/2025/12/synthetic-biology-ai-and-automation_0179340f/12158721-en.pdf"
        },
        {
          "title": "Frontiers",
          "url": "https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2026.1827740/full"
        }
      ]
    },
    "I found no report specifically dated November 2026, which makes sense since today is November 3. The results are mostly 2026 journal articles and preprints on AI and DNA synthesis screening.\n\n- **Screening tools vs. AI-redesigned proteins:** A Science paper with four commercial DNA synthesis companies found that AI-redesigned protein variants could evade current screening tools, and the authors helped develop patches. They identified a vulnerability where AI-redesigned sequences could not be detected reliably by current tools.\n- **Limits of sequence-based screening:** A 2026 Frontiers paper tested four screening tools that had been patched for AI resiliency. Two of the four tools robustly detected fragments as short as 50 nucleotides. The authors also warn that as fragment size decreases, the probability that a fragment is unique to a threat also decreases, so sequence matching alone may not be enough.\n- **Policy:** A 2026 Frontiers paper on U.S. screening policy traces how the rules have developed. A separate 2026 paper argues that a unified mandatory framework for sequence-level screening of gene synthesis is still"
  ],
  "durationSeconds": 9.466302190999967,
  "searchCount": 1
}

{
  "query": "NCSC annual review 2026 AI Cyber Security Centre of Excellence Cyber Shield £60 million Horne",
  "mode": "extended"
}

{
  "query": "NCSC annual review 2026 AI Cyber Security Centre of Excellence Cyber Shield £60 million Horne",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Hw8NWMgdXLp7z9e2AyvXnP",
      "content": [
        {
          "title": "Cyberattacks Cost UK £14.7B; NCSC Sees AI Ransomware by 2028 - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-cyberattacks-cost-uk-14-7b-ncsc-sees-ai-ransomware-by-2028/"
        },
        {
          "title": "NCSC warns of ‘unprecedented’ rise in cyber incidents, even as serious breaches fall",
          "url": "https://www.insurancebusinessmag.com/uk/news/cyber/ncsc-warns-of-unprecedented-rise-in-cyber-incidents-even-as-serious-breaches-fall-595939.aspx"
        },
        {
          "title": "NCSC warns AI ransomware likely to hit UK infrastructure by 2028",
          "url": "https://aiweekly.co/alerts/ncsc-warns-ai-ransomware-likely-to-hit-uk-infrastructure-by-2028"
        },
        {
          "title": "NCSC warns AI-powered cyber attacks 'highly likely' by 2028 - National Technology",
          "url": "https://www.nationaltechnology.co.uk/NCSC_Warns_AIpowered_Cyber_Attacks_Highly_Likely_By_2028.php"
        },
        {
          "title": "National Cyber Security Centre (United Kingdom)",
          "url": "https://en.wikipedia.org/wiki/National_Cyber_Security_Centre_(United_Kingdom)"
        },
        {
          "title": "NCSC Annual Review 2026",
          "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/introduction"
        },
        {
          "title": "UK faces ‘unprecedented rise’ in cyberattacks in coming months, warns cyber chief",
          "url": "https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months"
        },
        {
          "title": "NCSC: AI ransomware on UK infrastructure likely by 2028",
          "url": "https://www.resultsense.com/news/2026-11-03-ncsc-state-of-cyber-nation-ai-ransomware-2028/"
        },
        {
          "title": "NCSC Warns AI-Powered Ransomware Is Highly Likely to Hit UK Critical Infrastructure by 2028",
          "url": "https://windowsforum.com/news/ncsc-warns-ai-powered-ransomware-is-highly-likely-to-hit-uk-critical-infrastructure-by-2028.450709/"
        },
        {
          "title": "Annual Review",
          "url": "https://www.ncsc.gov.uk/collection/ncsc-annual-review-2025/timeline"
        }
      ]
    },
    "The NCSC published its Annual Review 2026 on 3 November, alongside its State of the Cyber Nation report, and Richard Horne launched it with a speech. The funding figures match across sources.\n\n**Funding:** The Chancellor's package includes £60 million for the first phase of a national Cyber Shield, £70 million for a National Exposure and Real-Time Vulnerability (NERV) Centre, and a new AI Cyber Security Centre of Excellence in Manchester that the NCSC will run ([4], [2]). One source says the Cyber Shield will use agentic AI and includes a £25 million challenge fund for UK AI and cybersecurity innovators ([9]).\n\n**Horne's warning:** Horne said the UK faces a real prospect of an unprecedented rise in cyber incidents in the coming months ([4]). He argued AI has not invented new attack methods. Instead, vulnerabilities that went unfixed for too long can now be exploited at scale ([7], [9]).\n\n**Threat outlook:** The State of the Cyber Nation judges an AI-powered ransomware attack on UK critical national infrastructure \"highly likely\" by 2028 ([3], [8]). It also says China and Russia will routinely use AI in cyber operations by then ([7]).\n\n**Incident figures:** Between September 2025 and August 2026, the NCSC received 1,831 reports of attacks on UK organisations, up from 1,727 the year before ([2]). The NCSC does not treat the year's fall in serious incidents as a trend ([2]).\n\n**Caveat:** Sources conflict on some details. One source says the 2026 pages it read give no count of highly significant incidents ([1]), so I could not verify that figure."
  ],
  "durationSeconds": 8.943412364999997,
  "searchCount": 1
}

{
  "url": "https://qwenlm.github.io/blog/",
  "prompt": "List all blog posts with titles and dates, newest first."
}

{
  "bytes": 13828,
  "code": 200,
  "codeText": "OK",
  "result": "1. Qwen3Guard: Real-time Safety for Your Token Stream (September 23, 2025)\n2. Qwen-Image-Edit: Image Editing with Higher Quality and Efficiency (August 19, 2025)\n3. Qwen-Image: Crafting with Native Text Rendering (August 4, 2025)\n4. GSPO: Towards Scalable Reinforcement Learning for Language Models (July 27, 2025)\n5. Qwen-MT: Where Speed Meets Smart Translation (July 24, 2025)\n\nThe page also says the blog has moved to qwen.ai/research.",
  "durationMs": 3816,
  "url": "https://qwenlm.github.io/blog/"
}

{
  "url": "https://ohsem.me/2026/11/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/",
  "prompt": "Date, study design, sample size, duration, all outcome numbers with comparison baselines, who funded/authored, and where published."
}

{
  "bytes": 12012,
  "code": 200,
  "codeText": "OK",
  "result": "The web page content you provided is only a loading message (\"One moment, please...\" and \"Please wait while your request is being verified...\"). It contains no study information, so I can't report the date, study design, sample size, duration, outcomes, funding, authors, or publication venue.\n\nPlease paste the article text or the study's abstract, and I'll extract those details.",
  "durationMs": 2691,
  "url": "https://ohsem.me/2026/11/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/"
}

{
  "url": "https://deepmind.google/discover/blog/",
  "prompt": "List all blog posts with titles and dates, newest first."
}

{
  "bytes": 194794,
  "code": 200,
  "codeText": "OK",
  "result": "The page shows the first of 19 blog pages, with 25 posts from August to October 2026:\n\n**October 2026**\n1. \"Genie 4: A new generation of world simulation\"\n2. \"Speeding up planning decisions with AI\"\n3. \"Gemini 4 Carbon: Our next frontier model\"\n4. \"Beyond tree cover: mapping the world's forest types\"\n5. \"Accelerating the search for antimicrobial peptides with Google Antigravity\"\n6. \"Google DeepMind and Singapore Government collaborate to build fine-tuned AI model for scam detection\"\n7. \"Developing Gemini 4 Argon responsibly and safely\"\n8. \"Gemini 4 Argon for Robotics\"\n9. \"Gemini 4 Argon: Built to solve your hardest problems\"\n10. \"EmbeddingGemma 2: an open, lightweight multimodal embedding model\"\n\n**September 2026**\n11. \"Gemini 4 Argon: our next era of frontier intelligence\"\n12. \"Introducing SynthID Bio\"\n13. \"Introducing Gemini 3.8 Live with Live Avatar\"\n14. \"Advancing Private AI Compute with secure, server-side memory\"\n15. \"Gemini 3.8 text-to-speech says hello\"\n16. \"Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking\"\n17. \"AlphaGenome Atlas: A predictive map of every possible DNA letter change in the human genome\"\n18. \"Introducing WeatherNext 3, our most advanced and accurate global weather AI model\"\n19. \"Proactive cyber defense for governments and enterprises\"\n20. \"Introducing Gemini 3.8 Flash and 3.8 Flash Cyber\"\n21. \"Introducing agentic video understanding with Gemini\"\n\n**August 2026**\n22. \"Gemini Omni 1.1 Flash lets you build with more control\"\n23. \"Piloting the world's first double-blind AI evaluations\"\n24. \"Intelligent transcription with Gemini 3.5 Transcribe\"\n25. \"From Atari to EVE Online: Building on 15 Years of AI Research in Games\"\n\nOnly page 1 is included in the content, so the remaining pages are not listed.",
  "durationMs": 7067,
  "url": "https://deepmind.google/discover/blog/"
}

{
  "url": "https://chatgptiseatingtheworld.com/2026/11/02/51-amici-briefs-filed-in-openai-copyright-suit-pending-court-approval-download/",
  "prompt": "Date, MDL case name and number, court, how many amicus briefs, deadlines, breakdown of who supports which side, and docket details."
}

{
  "bytes": 129913,
  "code": 200,
  "codeText": "OK",
  "result": "**Based on the page content:**\n\n- **Date:** November 2, 2026 (post date). The 51 amici asked for leave to file \"last week,\" so around late October 2026.\n- **MDL case name:** \"In re OpenAI Copyright Infringement Litigation\" (the category label). A navigation link also refers to \"In re: OpenAI, Inc. Copyright Infringement Litigation.\"\n- **MDL case number:** Not stated.\n- **Court:** Not named. The page references Judge Stein.\n- **Number of amicus briefs:** 51.\n- **Deadlines:** Not stated.\n- **Support breakdown (which side each brief supports):** Not stated.\n- **Docket details:** Not provided. The page says only that the amici sought leave to file briefs \"related to the summary judgment motions filed by the parties,\" and that the briefs are \"pending subject to the court's approval.\"",
  "durationMs": 5055,
  "url": "https://chatgptiseatingtheworld.com/2026/11/02/51-amici-briefs-filed-in-openai-copyright-suit-pending-court-approval-download/"
}

{
  "url": "https://rikiyat.github.io/blog/weight-space-programming/",
  "prompt": "Give the title, date, authors, and all headline benchmark numbers with baselines exactly as written, plus stated limitations."
}

{
  "bytes": 85671,
  "code": 200,
  "codeText": "OK",
  "result": "**Title:** Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights\n\n**Date:** November 2, 2026\n\n**Authors:** Rikiya Takehi, Jayden Teoh, Alex Zhang, and Omar Khattab (all MIT CSAIL)\n\n**Headline benchmark results**\n\n| Experiment | Result | Baseline |\n|---|---|---|\n| 4: Fixing a failing car-on-ramp policy | 100% success (1,024 episodes), editing 3.5% of weights | 0% success for the PPO policy |\n| 5: Writing Breakout networks from scratch | 517.4 | PPO 100M steps: 15.8; PPO 500M steps: 25.3 |\n| 5: Writing Seaquest networks from scratch | 53.1 | PPO 100M steps: 5.6; PPO 500M steps: 88.9 |\n| 5: Writing Asterix networks from scratch | 53.2 | PPO 100M steps: 25.8; PPO 500M steps: 55.2 |\n| 6: Go (9×9), 0 forward passes | Wins more than half of games | Two smaller PPO networks |\n| 6: Go (9×9), 50 forward passes | Beats the equal-sized PPO network | PPO trained on 20 million games |\n| 8: Qwen3.5-0.8B, 50 forward passes, MATH-500 | 48.1% | Base: 7.9% |\n| 8: GSM8K | 67.1% | Base: 13.8% |\n| 8: IFEval | 62.3% | Base: 21.0% |\n| 8: MATH-500 answers hitting the 32,768-token limit | 33.1% | Base: 93.0% |\n\nEdit size for Experiment 8: 131,072 weights, or 0.016% of the model.\n\n**Stated limitations**\n\n- The authors describe the results as \"very early\" and say capabilities are \"exciting but still limited,\" due to context-length and harness inefficiencies.\n- In Experiment 7, Astra could not identify the sycophantic model from the weights alone in four attempts. It succeeded only after being given attention patterns.\n- In Experiment 3, Astra could not run the network, and the head-level findings were checked against measured ground truth.\n- In Experiment 8, 10 and 25 forward passes barely reduced looping (87.2% and 86.4% of MATH-500 answers still hit the token limit).\n- Weight editing did not improve Gemma 3 270M. The authors conclude that editing can remove an obstacle that hides an ability but cannot add an ability the model lacks.\n- In Experiment 2, the generated shapes were outlines, although the actual models generate filled shapes.\n- Experiment 4 used a single attempt, and Experiment 5 networks were evaluated without any environment feedback during writing.\n- The authors are building a benchmark and harness for Weight-Space Programming, which is not yet complete.",
  "durationMs": 9957,
  "url": "https://rikiyat.github.io/blog/weight-space-programming/"
}

{
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/introduction",
  "prompt": "Publication date and key figures: number of reports, incidents handled, nationally significant incidents, AI statements."
}

{
  "bytes": 3893,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** 3 November 2026 (Version 1.0)\n\n**Key figures:** The page doesn't include any. It has no counts of reports, incidents handled, or nationally significant incidents. It also makes no statements specifically about AI.\n\nThe page is the introduction to the NCSC Annual Review 2026, which covers 1 September 2025 to 31 August 2026. It contains only three short forewords and their teaser text:\n- **Richard Horne, CEO NCSC:** The UK \"enters 2027 at a watershed moment.\"\n- **Anne Keast-Butler, Director GCHQ:** Refers to \"rapidly changing technology\" but doesn't mention AI by name.\n- **Dan Jarvis, Minister of State (Security Minister):** Says \"a decade is an epoch in cyber security.\"\n\nThe figures you're looking for are probably in the other sections of the review. The page shows \"Page 2 of 29,\" so I can't see them from this content.",
  "durationMs": 4034,
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/introduction"
}

{
  "url": "https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months",
  "prompt": "Publication date and all figures: incident reports, nationally significant incidents, AI claims, Horne quotes."
}

{
  "bytes": 91064,
  "code": 200,
  "codeText": "OK",
  "result": "The UK's National Cyber Security Centre (NCSC) warns of a possible \"unprecedented rise\" in cyber incidents in the coming months. Its chief, Richard Horne, says AI is not inventing new attacks but is letting long-tolerated vulnerabilities be found and exploited at far greater scale.\n\n- **Vulnerability surge:** Major vendors are fixing hundreds of flaws per update, and the Linux kernel project patched over a thousand last month. Officials say this shows AI is speeding up both discovery and repair, though exploitation has not yet risen to match.\n- **Future threats:** The NCSC judges it \"highly likely\" that AI-powered malware will be used in a ransomware attack on UK critical infrastructure by 2028. It also expects China and Russia to routinely use AI in cyber operations by then.\n- **Root causes:** The report blames technical debt, end-of-life systems, and slow patching rather than AI itself. Horne criticizes businesses for cutting corners on technology.\n- **Policy:** The government plans to consult on holding software companies liable for breaches caused by insecure products.\n- **AI-based defence:** Project DROMOS, a government trial of frontier AI, found hundreds of security issues. Funding includes £70 million for a NERV Centre to find vulnerabilities across critical infrastructure and £60 million for the first phase of Cyber Shield, a national network of AI defence agents focused initially on detecting and blocking attacks.\n- **Outlook:** The NCSC says defenders still hold a structural advantage, but only with clear direction, investment, and disciplined adoption.",
  "durationMs": 6721,
  "url": "https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months"
}

{
  "query": "radiology AI study published November 3 2026 screening accuracy",
  "mode": "extended"
}

{
  "query": "radiology AI study published November 3 2026 screening accuracy",
  "results": [
    {
      "tool_use_id": "srvtoolu_01VmKVWsvFsdq7CQUCvowV9x",
      "content": [
        {
          "title": "Diagnostic performance of FDA-cleared and CE-marked AI systems for mammography screening: a systematic review and meta-analysis - ScienceDirect",
          "url": "https://www.sciencedirect.com/science/article/pii/S0720048X26004845"
        },
        {
          "title": "AI Medical Imaging in 2026: Best Radiology AI Tools, FDA Clearances, and Diagnostic Accuracy",
          "url": "https://pinggy.io/blog/ai_medical_imaging_diagnostics_2026/"
        },
        {
          "title": "Three Futures for the Diagnostic Radiologist: A Structured Disagreement About What AI Actually Changes",
          "url": "https://arxiv.org/pdf/2607.01253"
        },
        {
          "title": "Retrospective Clinical Trial Comparing Radiologists' Diagnosis Accuracy in Lung Cancer Screening Population With and Without the Help of an AI/ML Tech-based SaMD",
          "url": "https://clinicaltrials.gov/study/NCT06751576"
        },
        {
          "title": "From Model Accuracy to Patient Benefit: Rethinking Evaluation of Radiology Artificial Intelligence - ScienceDirect",
          "url": "https://www.sciencedirect.com/science/article/abs/pii/S154614402600387X"
        },
        {
          "title": "Commercially available chest X-ray AI products fail to improve diagnostic accuracy, real world study shows",
          "url": "https://radiologybusiness.com/topics/artificial-intelligence/commercially-available-chest-x-ray-ai-products-fail-improve-diagnostic-accuracy-real-world-study"
        },
        {
          "title": "Perspectives: The Good Trials Are Better Than I Expected. The Failure Modes Are Worse.",
          "url": "https://www.nellymd.com/2026/09/ai-radiology-does-it-work.html"
        },
        {
          "title": "AI in radiology and interventions: a structured narrative review of workflow automation, accuracy, and efficiency gains of today and what’s coming",
          "url": "https://link.springer.com/article/10.1007/s11548-025-03547-2"
        },
        {
          "title": "Will AI Replace Radiologists? 2026 Data Explained",
          "url": "https://aitoolsobserver.com/hub/will-ai-replace-radiologists-what-2026-data-actually-shows/"
        }
      ]
    },
    "I couldn't find a study confirmed as published on November 3, 2026. The closest match is a meta-analysis dated November 2026. The search also surfaced several related studies from earlier in 2026.\n\n- **Closest match (November 2026):** A systematic review and meta-analysis in *European Journal of Radiology* looked at FDA-cleared and CE-marked AI for mammography screening. Pooled standalone AI performance gave an AUC of 0.89, with sensitivity of 76.3% and specificity of 89.6%. The authors also concluded that prospective evaluations of AI-integrated workflows showed non-inferior cancer detection with significant workload reduction compared with standard double reading.\n- **MASAI trial (Lancet, 2026):** A large Swedish randomized trial of AI-supported mammography screening reported higher sensitivity with AI, 80.5% versus 73.8%. It also found that AI-supported screening required 61,248 screen readings where standard double reading required 109,692.\n- **Counterpoint (August 2026):** A study in *Academic Radiology* found that the tools are beneficial for workflows but do little to improve detection accuracy.\n\nThe search results include some low-quality sources, such as a blog and an AI tools site, so I'd rely on the journal and trial sources. If you have a specific paper title, journal, or DOI, I can search for that directly."
  ],
  "durationSeconds": 6.303707720999955,
  "searchCount": 1
}

{
  "query": "Golden Dome AI missile defense contract November 2026 Space Force",
  "mode": "extended"
}

{
  "query": "Golden Dome AI missile defense contract November 2026 Space Force",
  "results": [
    {
      "tool_use_id": "srvtoolu_01VA1qrR4yUdjXYrRCeAVgsi",
      "content": [
        {
          "title": "US Space Force Taps 12 Firms for $3.2 Billion Golden Dome Missile Defense Contracts",
          "url": "https://www.usnews.com/news/top-news/articles/2026-04-24/us-space-force-taps-12-firms-for-3-2-billion-golden-dome-missile-defense-contracts"
        },
        {
          "title": "USSF Reveals $3.2B for Golden Dome Space-Based Interceptors",
          "url": "https://www.airandspaceforces.com/space-force-reveals-space-based-interceptor-awards-golden-dome/"
        },
        {
          "title": "Golden Dome Gets a $1.75 Billion Boost as Space Force Orders 36 New Defense Satellites - ClearanceJobs",
          "url": "https://news.clearancejobs.com/2026/07/16/golden-dome-gets-a-1-75-billion-boost-as-space-force-orders-36-new-defense-satellites/"
        },
        {
          "title": "Space Force names 12 companies to develop Golden Dome’s space-based interceptors",
          "url": "https://defensescoop.com/2026/04/24/golden-dome-space-based-interceptor-missile-defense-contractors/"
        },
        {
          "title": "SpaceX Wins $6.45B to Build Golden Dome’s Space Layer - AeroMorning.com",
          "url": "https://aeromorning.com/en/spacex-wins-6-45b-to-build-golden-domes-space-layer/"
        },
        {
          "title": "SDA Awards Contracts for 36 Golden Dome Missile Tracking Satellites",
          "url": "https://www.airandspaceforces.com/sda-awards-contracts-for-36-golden-dome-missile-tracking-satellites/"
        },
        {
          "title": "Space Force Awards Secret Contracts for Golden Dome Interceptors",
          "url": "https://www.bloomberg.com/news/articles/2025-11-25/space-force-awards-secret-contracts-for-golden-dome-interceptors"
        },
        {
          "title": "next BIG future",
          "url": "https://nextbigfuture.substack.com/p/spacex-palantir-and-anduril-partnership-competing-for-the-us-golden-dome-missile-defense-contractshtml"
        },
        {
          "title": "Golden Dome",
          "url": "https://www.globalsecurity.org/space/systems/golden-dome.htm"
        },
        {
          "title": "trump golden dome missile defence plans",
          "url": "https://globalnews.ca/news/11187780/trump-golden-dome-missile-defence-plans"
        }
      ]
    },
    "I ran one search. It didn't turn up any Golden Dome AI contract announced in November 2026. The most recent items are from mid-2026, and none of them is specifically an AI award.\n\n- **Space-based interceptors (April 2026):** The Space Force has awarded 20 contracts worth up to $3.2 billion to 12 companies to develop space-based interceptors for Golden Dome. The target is demonstrating an integrated capability within the Golden Dome for America architecture by 2028.\n- **SpaceX awards (May 2026):** One aggregator reports that SpaceX's Golden Dome-related awards total about $6.45 billion. That figure covers sensing, tracking, and data networking rather than interceptors. This source is less authoritative than the official announcements, so verify it before relying on it.\n- **Missile tracking satellites (July 2026):** The Space Development Agency announced contracts worth $1.75 billion to build 36 satellites in support of the Pentagon's Golden Dome missile defense shield.\n- **AI layer:** The Space Systems Command statement says the sensors and interceptors must be integrated with Artificial Intelligence to counter the speed, maneuverability, and lethality of the threats. The search didn't surface a dedicated AI contract.\n- **Budget:** The Pentagon is asking for $17.5 billion in fiscal 2027 for the Golden Dome program, with just $398 million of that request coming from the base budget.\n\nFor November 2026 specifically, a follow-up search on Space Force Golden Dome awards this month or AI software awards from the Golden Dome office would be the next step."
  ],
  "durationSeconds": 7.229252214000095,
  "searchCount": 1
}

{
  "query": "Flourish AI app Harvard Business School working paper 1,137 students stress depression anxiety",
  "mode": "extended"
}

{
  "query": "Flourish AI app Harvard Business School working paper 1,137 students stress depression anxiety",
  "results": [
    {
      "tool_use_id": "srvtoolu_0173YSsJqhp3thVXCthX5uXa",
      "content": [
        {
          "title": "Harvard Working Paper Finds Flourish AI App Improves Stress, Depression, And Anxiety Symptoms",
          "url": "https://ohsem.me/2026/11/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/"
        },
        {
          "title": "Student Mental Health Apps: A 2026 Campus Resource Guide",
          "url": "https://www.myflourish.ai/post/student-mental-health-apps-a-2026-campus-resource-guide"
        },
        {
          "title": "Evaluating a Mobile App for Students Seeking Care for Depression and Anxiety at Harvard University Health Services",
          "url": "https://clinicaltrials.gov/study/NCT03552900"
        },
        {
          "title": "iWellness Study to Evaluate a Mental Health App for Students",
          "url": "https://clinicaltrials.gov/study/NCT05234970"
        },
        {
          "title": "Xuan Zhao",
          "url": "https://en.wikipedia.org/wiki/Xuan_Zhao"
        },
        {
          "title": "Working Paper 27-002 AI-Powered Prevention and Early Intervention for Stress,",
          "url": "https://www.hbs.edu/ris/download.aspx?name=27-002.pdf"
        },
        {
          "title": "Another Crazy Day in AI: Proactive Mental Health Through Generative Technology",
          "url": "https://www.wowza.biz/post/another-crazy-day-in-ai-proactive-mental-health-through-generative-technology"
        },
        {
          "title": "Working Paper 26-030 AI for Proactive Mental Health: A Longitudinal, Multi-",
          "url": "https://www.hbs.edu/ris/Publication%20Files/26-030_d076e0d0-3c7f-4728-a481-ef1fb9f9641b.pdf"
        },
        {
          "title": "AI-powered Early Intervention for Depression and Anxiety",
          "url": "https://www.hbs.edu/ris/Publication%20Files/27-002_d03a8b75-93d4-4a7c-87fd-3f09941f7c9a.pdf"
        }
      ]
    },
    "The search turned up a 1,137-student trial, but the most prominent coverage comes from the company itself, so I'd treat the headline claims with some caution.\n\n- **The study:** A preregistered randomized trial of 1,137 unscreened university students compared six weeks of the Flourish app, a generative AI mobile intervention with a conversational coach called Sunnie, against care as usual. The primary outcomes were perceived stress, depressive symptoms, and anxiety symptoms. The HBS-hosted version appears as Working Paper 27-002, \"AI-Powered Prevention and Early Intervention for Stress, Depression, and Anxiety\".\n- **Reported results:** The paper's findings summary says that students told to use Flourish twice a week showed more favorable depression and anxiety trajectories. The reported effect ratios were 1.65 for depression and 1.33 for anxiety. The authors also note that for students below a certain symptom threshold (the snippet is cut off), the app improved well-being outcomes but did not significantly reduce depression or anxiety.\n- **Source caveat:** The \"significantly lower\" framing comes from a press release dated November 3, 2026, issued from Palo Alto by Flourish Science, which co-founder Xuan Zhao leads. Treat its wording as the company's characterization rather than an independent summary.\n- **A separate, earlier study:** A November 2025 HBS paper (Working Paper 26-030) involved 486 undergraduates over six weeks in Fall 2024 and found no effects on depression, anxiety, or stress. It is a different trial from the 1,137-student one.\n\nI only ran one search, so I haven't checked the full paper or any independent commentary on it."
  ],
  "durationSeconds": 7.126379156999988,
  "searchCount": 1
}

{
  "query": "Proofpoint ESET Trend Micro Sophos new AI threat research published November 2 2026",
  "mode": "extended"
}

{
  "query": "Proofpoint ESET Trend Micro Sophos new AI threat research published November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_016ZbAd23uftQHCSfRiMzume",
      "content": [
        {
          "title": "ESET H1 2026 Threat Report",
          "url": "https://www.eset.com/us/business/threat-report/"
        },
        {
          "title": "(eset):research Threat H1 2026 December 2025",
          "url": "https://web-assets.esetstatic.com/wls/en/papers/threat-reports/eset-threat-report-h12026.pdf"
        },
        {
          "title": "Proofpoint Research Reveals Half of Global Organizations Experienced AI Incidents Despite Having AI Security Controls in Place",
          "url": "https://www.proofpoint.com/us/newsroom/press-releases/proofpoint-research-reveals-half-global-organizations-experienced-ai"
        },
        {
          "title": "Proofpoint’s 2026 report exposes disconnect between rapid AI rollout and weak security assurance - Industrial Cyber",
          "url": "https://industrialcyber.co/news/proofpoints-2026-report-exposes-disconnect-between-rapid-ai-rollout-and-weak-security-assurance/"
        },
        {
          "title": "2026 AI-Era Ransomware Report",
          "url": "https://www.proofpoint.com/us/resources/threat-reports/ai-era-ransomware-report"
        },
        {
          "title": "Strengthening AI-Powered Email Security: Insights from Proofpoint and Guest Forrester",
          "url": "https://www.proofpoint.com/au/resources/webinars/q4-strengthening-ai-powered-email-security-with-forrester"
        },
        {
          "title": "State-sponsored APT actors: How they acquire AI for cyber operations - B2B Cyber Security",
          "url": "https://b2b-cyber-security.de/en/staatliche-apt-akteure-so-gelangen-sie-an-ki-fuer-cyberoperationen/"
        },
        {
          "title": "AI-Enabled Ransomware: Proofpoint Findings",
          "url": "https://ai.xl.net/blog/ibm-ai-enabled-breaches-2026-07-29"
        },
        {
          "title": "Proofpoint Research Finds 65% of Organizations Affected by Ransomware Say AI Made Attacks More Effective",
          "url": "https://www.proofpoint.com/us/newsroom/press-releases/proofpoint-research-finds-65-organizations-affected-ransomware-say-ai-made"
        },
        {
          "title": "Check Point",
          "url": "https://en.wikipedia.org/wiki/Check_Point"
        }
      ]
    },
    "I didn't find any new research from Proofpoint, ESET, or Sophos dated November 2, 2026. The closest match is a TrendAI study from Trend Micro, dated one day earlier.\n\n- **Trend Micro (TrendAI):** A study titled \"AI Statecraft and Cyberthreats in 2026\" examines how China, Russia, North Korea, and Iran adopt AI for cyber operations. Feike Hacquebord, Principal Threat Researcher at TrendAI and co-author of the study, said state-sponsored attackers don't need the most advanced AI models to benefit. The report is dated November 1, 2026, according to a B2B Cyber Security article.\n- **ESET:** Its most recent threat material is the H1 2026 report. It covers 900,000 AI skills analyzed between March and May 2026, with 25,000 suspicious and over 3,000 malicious. It also highlights PromptSpy, the first Android malware observed actively using GenAI at runtime.\n- **Proofpoint:** The newest item is a webinar announcement for November 25, 2026, on AI-driven email threats, not new research. Its earlier 2026 AI-Era Ransomware Report found that 65% of organizations affected by ransomware said AI made the attack more effective.\n- **Sophos:** I found only secondhand coverage. Infosecurity Magazine reportedly quoted Sophos warning that the identity fabric connecting AI services to enterprise systems creates exposure that existing governance was not designed to handle.\n\nA search for the exact date, or for each vendor's newsroom, may surface a November 2 publication if one exists."
  ],
  "durationSeconds": 6.674913237000001,
  "searchCount": 1
}

{
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/resilience/ncsc-incident-management",
  "prompt": "Figures for reports received, incidents handled, nationally significant incidents, and comparison to previous year."
}

{
  "bytes": 0,
  "code": 404,
  "codeText": "Not Found",
  "result": "The server returned HTTP 404 Not Found.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 975,
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/resilience/ncsc-incident-management"
}

{
  "url": "https://www.hbs.edu/ris/Publication%20Files/27-002_d03a8b75-93d4-4a7c-87fd-3f09941f7c9a.pdf",
  "prompt": "Give the paper date, authors, trial registration, sample size, randomization arms, duration, and the exact primary outcome results with effect sizes and p-values."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 305,
  "url": "https://www.hbs.edu/ris/Publication%20Files/27-002_d03a8b75-93d4-4a7c-87fd-3f09941f7c9a.pdf"
}

{
  "query": "NCSC State of the Cyber Nation 2026 report AI China Russia routinely 2028 DROMOS",
  "mode": "extended"
}

{
  "query": "NCSC State of the Cyber Nation 2026 report AI China Russia routinely 2028 DROMOS",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Lf9WiwDZGbSpanrrXMjbCx",
      "content": [
        {
          "title": "NCSC Annual Review 2026",
          "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/understanding-threat/cyber-threat-uk"
        },
        {
          "title": "UK to face AI-powered cyber attacks within two years, warns NCSC",
          "url": "https://www.computerweekly.com/news/366653412/UK-to-face-AI-powered-cyber-attacks-within-two-years-warns-NCSC"
        },
        {
          "title": "NCSC warns AI ransomware likely to hit UK infrastructure by 2028",
          "url": "https://aiweekly.co/alerts/ncsc-warns-ai-ransomware-likely-to-hit-uk-infrastructure-by-2028"
        },
        {
          "title": "UK Cyber Agency Says AI Ransomware Attack on Infrastructure Highly Likely by 2028",
          "url": "https://www.tokenpost.com/news/technology/47439"
        },
        {
          "title": "The NCSC says AI-powered cyber attacks are coming for UK firms",
          "url": "https://www.itpro.com/security/cyber-attacks/the-ncsc-says-ai-powered-cyber-attacks-are-coming-for-uk-firms-but-they-still-need-to-sharpen-up-on-basic-security-practices"
        },
        {
          "title": "AI Malware Will Hit UK CNI by 2028, NCSC Warns [2026]",
          "url": "https://tech-insider.org/ncsc-ai-powered-malware-highly-likely-uk-cni-ransomware-2028-2026/"
        },
        {
          "title": "AI malware attacks likely within 2 years: UK cyber cheif",
          "url": "https://www.thenews.com.pk/latest/1422304-ai-malware-attacks-likely-within-2-years-uk-cyber-cheif"
        },
        {
          "title": "NCSC Warns AI-Powered Ransomware Is Highly Likely to Hit UK Critical Infrastructure by 2028",
          "url": "https://windowsforum.com/news/ncsc-warns-ai-powered-ransomware-is-highly-likely-to-hit-uk-critical-infrastructure-by-2028.450709/"
        },
        {
          "title": "NCSC Annual Review 2024",
          "url": "https://www.ncsc.gov.uk/collection/ncsc-annual-review-2024/chapter-01"
        }
      ]
    },
    "The NCSC's State of the Cyber Nation report, published 3 November 2026, does judge that Russia and China will routinely use AI in cyber operations by 2028. I found no results mentioning \"DROMOS,\" so I can't confirm anything about that term.\n\n- **Core judgement:** The NCSC rates it \"highly likely\" that by 2028 Russia, China and other nation states will use AI cyber capabilities routinely for geopolitical goals ([8-3]). Coverage describes this as part of a scenario rather than a firm forecast ([8-7]).\n- **AI ransomware:** The NCSC also judges an AI-powered ransomware attack on UK critical national infrastructure highly likely by 2028 ([3-5]). Some coverage notes this forecast concerns criminal extortion rather than a named government ([6-5]).\n- **China:** The NCSC considers China best positioned to use AI against UK critical national infrastructure ([2-4]), and calls Chinese cyber activity the most sophisticated and sustained challenge facing the UK ([7-6]).\n- **Russia:** Russian actors reportedly adapt open-source AI models instead of building their own ([8-6]).\n- **Wider risk:** The NCSC warns that weaker organisations will struggle to keep pace with AI-assisted attacks ([2-7]).\n\nSources: [NCSC Annual Review 2026](https://www.ncsc.gov.uk/collection/annual-review-2026/understanding-threat/cyber-threat-uk), [Computer Weekly](https://www.computerweekly.com/news/366653412/UK-to-face-AI-powered-cyber-attacks-within-two-years-warns-NCSC), [The News PK](https://www.thenews.com.pk/latest/1422304-ai-malware-attacks-likely-within-2-years-uk-cyber-cheif)."
  ],
  "durationSeconds": 7.454628246999928,
  "searchCount": 1
}

{
  "url": "https://arxiv.org/html/2611.00460v1",
  "prompt": "List the authors and their institutional affiliations exactly as shown on the title page."
}

{
  "bytes": 464555,
  "code": 200,
  "codeText": "OK",
  "result": "The title page lists two authors:\n\n1. **Navapat Nananukul**: \"Affiliation: Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA\"\n2. **Mayank Kejriwal**: \"Affiliation: Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA.\" He is also listed as \"Affiliation: Lead contact,\" and the correspondence line is \"Affiliation: Correspondence: [email redacted], [email redacted].\"\n\n[WebFetch note: this page's text is 152401 characters long and the answer above covers only characters 0 to 100000; the final 52401 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 3507,
  "url": "https://arxiv.org/html/2611.00460v1"
}

{
  "query": "AI scam fraud bank losses report published November 3 2026",
  "mode": "extended"
}

{
  "query": "AI scam fraud bank losses report published November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Xc8kH3vjq8Cwkqz439Hc7g",
      "content": [
        {
          "title": "Study finds AI fraud losses decline, but the risks are growing",
          "url": "https://www.biometricupdate.com/202604/study-finds-ai-fraud-losses-decline-but-the-risks-are-growing"
        },
        {
          "title": "Deception in the AI Age 2026",
          "url": "https://www.thomsonreuters.com/en/institute/reports/deception-in-the-ai-age-2026"
        },
        {
          "title": "AI drives global fraud surge",
          "url": "https://www.paymentsdive.com/news/ai-drives-global-fraud-surge/814646/"
        },
        {
          "title": "Italian bank loses $108M to AI messaging fraud, as identifAI warns of deepfake threat",
          "url": "https://www.biometricupdate.com/202610/italian-bank-loses-108m-to-ai-messaging-fraud-as-identifai-warns-of-deepfake-threat"
        },
        {
          "title": "US Financial Services Firms Lose $5.47 for Every $1 of Fraud as AI-Assisted Attacks Shift to Digital and Mobile Channels",
          "url": "https://risk.lexisnexis.com/about-us/press-room/press-release/20261019-tcof-ai-assisted-attacks"
        },
        {
          "title": "World banking leaders see AI agents as industry’s greatest vulnerability in next year",
          "url": "https://www.biocatch.com/press-release/world-banking-leaders-see-ai-agents-as-industrys-greatest-vulnerability-in-next-year"
        },
        {
          "title": "Authorised push payment fraud",
          "url": "https://en.wikipedia.org/wiki/Authorised_push_payment_fraud"
        },
        {
          "title": "AI-Powered Bank Scam Drains $423,114 From 170 Victims in Just Three Weeks: Report - The Daily Hodl",
          "url": "https://dailyhodl.com/2026/10/30/ai-powered-bank-scam-drains-423114-from-170-victims-in-just-three-weeks-report/"
        },
        {
          "title": "AI Fraud Scams Hit $3.7 Billion Globally as Digital Threats Evolve",
          "url": "https://www.whalesbook.com/news/English/bankingfinance/AI-Fraud-Scams-Hit-dollar37-Billion-Globally-as-Digital-Threats-Evolve/6aa8fe5432e8b17a6096d699"
        },
        {
          "title": "The AI Scam Playbook: How Artificial Intelligence Is Changing Fraud in 2026",
          "url": "https://www.getkibbo.com/investigations/ai-scam-playbook-2026"
        }
      ]
    },
    "I found no report dated November 3, 2026 in these results. The closest recent items were published in October or earlier:\n\n- **LexisNexis True Cost of Fraud (Oct 19, 2026):** Organizations estimate fraudsters use AI-generated techniques in 19% of fraud losses in the US and 25% in Canada.\n- **Netherlands AI phone scam (Oct 30, 2026):** Police arrested two suspects in a case where AI-generated calls took about €380,000 from 170 victims over three weeks, according to Daily Hodl's report on Dutch police arrests.\n- **Fideuram (Oct 15, 2026):** Reuters reported that AI impersonation of senior executives led to a theft of 95 million euros ($108 million) from Fideuram, the private banking arm of lender Intesa Sanpaolo.\n- **Javelin 2026 identity fraud study (April 2026):** Combined fraud and scam losses were $38 billion in 2025, a $9 billion reduction from 2024, while the report warns that AI is driving bank impersonation and purchase scams.\n- **Nasdaq Verafin 2026 Global Financial Crime Report:** It recorded $579.4 billion lost to bank fraud and scams in 2025, and cyber-assisted or AI-enabled scams were responsible for $14.3 billion in losses.\n\nThese figures come from different methodologies and don't reconcile with each other. If you need a report published on November 3, 2026 specifically, a more targeted search of that date or of the publishing organization would be needed."
  ],
  "durationSeconds": 6.4014064410000575,
  "searchCount": 1
}

{
  "query": "defensescoop breakingdefense November 3 2026 artificial intelligence",
  "mode": "extended"
}

{
  "query": "defensescoop breakingdefense November 3 2026 artificial intelligence",
  "results": [
    {
      "tool_use_id": "srvtoolu_016nwKurWgHhqVYKrrgrZLH3",
      "content": [
        {
          "title": "DefenseScoop (@DefenseScoop) on X",
          "url": "https://x.com/DefenseScoop"
        },
        {
          "title": "DefenseScoop",
          "url": "https://defensescoop.com/"
        },
        {
          "title": "DefenseScoop: Contact Information, Journalists, and Overview",
          "url": "https://muckrack.com/media-outlet/defensescoop"
        },
        {
          "title": "Breaking Defense - Defense technology, policy and national security news",
          "url": "https://breakingdefense.com/"
        },
        {
          "title": "DefenseScoop (@DefenseScoop) on X",
          "url": "https://twitter.com/defensescoop?lang=en"
        },
        {
          "title": "GenAI.mil attracts about half a million ‘power users’ as Pentagon pushes forward with frontier models",
          "url": "https://defensescoop.com/2026/09/23/genai-mil-pentagon-frontier-models-defensetalks/"
        },
        {
          "title": "Defense News",
          "url": "https://en.wikipedia.org/wiki/Defense_News"
        },
        {
          "title": "How can we trust AI in national defense missions?",
          "url": "https://defensescoop.com/2026/10/30/how-can-we-trust-ai-in-national-defense-missions/"
        },
        {
          "title": "Vago Muradian",
          "url": "https://en.wikipedia.org/wiki/Vago_Muradian"
        }
      ]
    },
    "I found no DefenseScoop or Breaking Defense stories dated November 3, 2026, so I can't confirm what ran that day. The newest items I could date are from late October.\n\n- **Project Gatekeeper:** DefenseScoop's Army coverage describes the service launching Project Gatekeeper, an effort to speed up onboarding of vendor software by using AI to vet code in an isolated environment. Breaking Defense's listings say it aims to cut software approval times. (DefenseScoop: \"As Project Gatekeeper goes live, Army plans integration with frontier AI models.\")\n- **Opinion piece:** A DefenseScoop piece from October 30, 2026 asks how AI can be trusted in national defense missions, citing reported false AI-generated intelligence tied to a near-confrontation with China.\n- **Wargames:** A DefenseScoop story from October 15, 2026 reports that Marines and other joint force members are expected to face an AI-controlled adversary in wargames later this year.\n- **Breaking Defense:** Its listings include a Navy award of $25M to Applied Intuition to deploy AI sensor fusion at sea and General Dynamics' work with Primordial on an AI assistant for combat vehicle crews. Its homepage also lists a D.C. Circuit panel upholding the Pentagon's ban on Anthropic.\n\nThe search results carry no reliable publication dates for most headlines, so treat the timing as approximate. A search for the exact date or a direct visit to defensescoop.com and breakingdefense.com would confirm what was published November 3."
  ],
  "durationSeconds": 8.777363521000021,
  "searchCount": 1
}

{
  "query": "AI governance announcement November 3 2026 regulator",
  "mode": "extended"
}

{
  "query": "AI governance announcement November 3 2026 regulator",
  "results": [
    {
      "tool_use_id": "srvtoolu_01StFgFa328Vm2caa4cUQbAc",
      "content": [
        {
          "title": "FPF’s AI Governance Bulletin (#5) - by Jameson Spivack",
          "url": "https://fpfcenterforai.substack.com/p/fpfs-ai-governance-bulletin-5"
        },
        {
          "title": "EU Artificial Intelligence Act",
          "url": "https://artificialintelligenceact.eu/"
        },
        {
          "title": "White House Releases a National Policy Framework for Artificial Intelligence",
          "url": "https://www.hklaw.com/en/insights/publications/2026/03/white-house-releases-a-national-policy-framework-for-artificial"
        },
        {
          "title": "Hong Kong Launches AI-Agent Governance Project - Caixin Global",
          "url": "https://www.caixinglobal.com/2026-11-02/hong-kong-launches-ai-agent-governance-project-102500128.html"
        },
        {
          "title": "Ebix Partners with intentyx to Bring AI Agent Security and Governance to Regulated Industries",
          "url": "https://www.ebix.com/news-and-media/ebix-intentyx-smare-ai-agent-security-governance/"
        },
        {
          "title": "Hong Kong plans stablecoin trials for tokenized government debt",
          "url": "https://crypto.news/hong-kong-24-7-tokenized-settlement-stablecoin-trials/"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/artificial-intelligence/regulatory-standards"
        },
        {
          "title": "Latest News",
          "url": "https://newsroom.ibm.com/campaign?item=2112"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/regulatory-oversight/technology/artificial-intelligence"
        },
        {
          "title": "Hong Kong Becomes First Banking Regulator to Require Identity Credentials for AI Agents",
          "url": "https://www.techtimes.com/articles/329929/20261103/hong-kong-becomes-first-banking-regulator-require-identity-credentials-ai-agents.htm"
        }
      ]
    },
    "The most relevant regulator news from the search is from Hong Kong, where the banking regulator launched an AI governance initiative on November 2, 2026, one day before your date.\n\n- **HKMA Project SAGE:** The Hong Kong Monetary Authority launched Project SAGE, a governance framework for AI agents in finance. It targets risks such as unauthorized transactions. The announcement came on November 2 during Hong Kong FinTech Week. The regulator established an expert group and published a discussion paper seeking industry feedback on the governance of AI systems used by banks. HKMA will also release a discussion paper on AI agent governance, exploring a central registry for critical agents, building on supervisory guidelines issued Oct 16, 2026.\n- **Identity requirements:** A TechTimes piece says Hong Kong is the first banking regulator to require identity credentials for AI agents. I'd treat that as a single outlet's framing, since I didn't find a regulator statement confirming it.\n- **Financial Stability Board:** An FPF bulletin reports that the FSB published the final version of its Sound Practices for Responsible Adoption of Artificial Intelligence. It recommends 12 practices across two groups. The bulletin doesn't clearly date this release, so it may not be from today.\n- **Private sector:** Ebix announced on November 3, 2026, an AI agent security and governance offering for regulated industries. It is a commercial product launch, not a regulatory action.\n\nI didn't find any other regulator announcement dated November 3, 2026, so this search may not be exhaustive."
  ],
  "durationSeconds": 9.050784048,
  "searchCount": 1
}

{
  "query": "D.C. Circuit panel Pentagon ban Anthropic ruling appeals court",
  "mode": "extended"
}

{
  "query": "D.C. Circuit panel Pentagon ban Anthropic ruling appeals court",
  "results": [
    {
      "tool_use_id": "srvtoolu_01PG5UfgYshegv1Pju3cA2Ba",
      "content": [
        {
          "title": "Appeals Court Upholds Pentagon’s Anthropic Ban in Split Ruling",
          "url": "https://techtrendsnewsupdate.substack.com/p/appeals-court-upholds-pentagons-anthropic"
        },
        {
          "title": "Anthropic Loses DC Circuit Appeal on Pentagon Claude Ban 2-1",
          "url": "https://aiweekly.co/alerts/anthropic-loses-dc-circuit-appeal-on-pentagon-claude-ban-2-1"
        },
        {
          "title": "Federal appeals court upholds Pentagon designation of Anthropic as supply chain risk - ABC News",
          "url": "https://abcnews.com/Business/anthropic-appeals-court-declines-block-pentagon-blacklisting/story?id=136755690"
        },
        {
          "title": "D.C. Appeals Court Upholds Anthropic Pentagon Ban",
          "url": "https://www.briefs.co/news/d-c-appeals-court-backs-pentagon-blacklist-of-anthropic-in-2/"
        },
        {
          "title": "US appeals court upholds Pentagon’s supply chain risk label on Anthropic",
          "url": "https://thenextweb.com/news/anthropic-pentagon-supply-chain-risk-appeals-court-ruling"
        },
        {
          "title": "Anthropic Loses Appeals Court Bid to Overturn Pentagon ‘Supply Chain Risk’ Label",
          "url": "https://www.lawcommentary.com/articles/anthropic-loses-pentagon-supply-chain-risk-appeal"
        },
        {
          "title": "Appeals Court Upholds Pentagon’s Supply-Chain Risk Label on Anthropic",
          "url": "https://www.theepochtimes.com/us/appeals-court-upholds-pentagons-supply-chain-risk-label-on-anthropic-6094921"
        },
        {
          "title": "Accenture Contractor Allegedly Linked Personal Claude AI Agent to Pentagon System Used by Intel Agencies",
          "url": "https://ibtimes.co.uk/claude-code-agent-pentagon-niprnet-access-allegations-1829425"
        },
        {
          "title": "appeals court rebuffs anthropic in latest round of its ai battle with the trump administration",
          "url": "https://www.barchart.com/story/news/1210535/appeals-court-rebuffs-anthropic-in-latest-round-of-its-ai-battle-with-the-trump-administration"
        }
      ]
    },
    "A divided D.C. Circuit panel ruled on September 25, 2026 that the Pentagon can keep Anthropic on its supply-chain blacklist. The vote was 2-1, with Judge Gregory Katsas writing for the majority and Judge Neomi Rao joining. Judge Karen LeCraft Henderson dissented. The court rejected all three arguments Anthropic raised, and the majority also concluded that the exclusion was tied to contract terms rather than punishment for Anthropic's public advocacy.\n\nThe ruling is narrower than \"ban\" implies. It covers the Pentagon's designation under a 2018 supply-chain law, and it did not impose a blanket ban on Anthropic products across all commercial or federal-government use.\n\nA separate case matters here. A separate California ruling in August struck down a Pentagon designation issued under a different defense procurement law. Anthropic's spokesperson said another federal court has already held the government's parallel designation unlawful. Because of that split, the D.C. ruling preserves the Pentagon's separate designation under the 2018 supply chain law, while the California ruling still blocks the broader restrictions.\n\nAnthropic has not given up. It told CNBC that it disagreed with the decision and was considering further review. Per one report, the panel has stayed its decision to give Anthropic time to seek rehearing at the circuit or Supreme Court review. I could not confirm that stay detail in a second source, so treat it as unverified."
  ],
  "durationSeconds": 7.231890790000092,
  "searchCount": 1
}

{
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/understanding-threat/cyber-threat-uk",
  "prompt": "All figures and AI judgements: incident counts, nationally significant incidents, China/Russia AI by 2028, DROMOS."
}

{
  "bytes": 12349,
  "code": 200,
  "codeText": "OK",
  "result": "The page doesn't include **incident counts**, **nationally significant incident** figures, or anything about **DROMOS**. The following covers the AI judgements and figures it does contain.\n\n**AI judgements**\n- The NCSC assesses it is highly likely that by 2028, China, Russia, and other nation states will routinely use AI in cyber operations to pursue geopolitical goals.\n- It also judges it highly likely that AI-powered malware will have been used in a ransomware attack on UK critical national infrastructure by 2028.\n\n**Key figures**\n- Malicious cyber activity costs UK organisations an estimated £14.7 billion a year, according to UK government research.\n- The 2025 Jaguar Land Rover attack caused about £196 million in direct cyber-related costs. The page links it to UK GDP growing only 0.1% in Q3 2025.\n- The UK and EU attributed a December 2025 attack on Poland's energy grid to Russia's FSB Centre 16. Had it succeeded, it could have cut electricity for 500,000 citizens.\n- The UK sanctioned two China-based firms in December 2025. One, i-Soon, targeted over 80 government and private industry IT systems worldwide.\n- Joint advisories covered China-nexus covert networks (April 2026, 15 partners across nine other countries) and FSB Centre 16 router exploitation (July 2026, 18 partners across 12 countries).",
  "durationMs": 8222,
  "url": "https://www.ncsc.gov.uk/collection/annual-review-2026/understanding-threat/cyber-threat-uk"
}

{
  "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/",
  "prompt": "List press releases dated 2 or 3 November 2026 with titles, dates and URLs, especially any about AI or Project SAGE."
}

{
  "bytes": 118763,
  "code": 200,
  "codeText": "OK",
  "result": "Press releases dated 2 or 3 November 2026 (URLs are relative to the HKMA site):\n\n**3 Nov 2026**\n- HKMA hosts fifth Global Financial Leaders' Investment Summit: `/eng/news-and-media/press-releases/2026/11/20261103-4/`\n- Exchange Fund Bills Tender Results: `/eng/news-and-media/press-releases/2026/11/20261103-3/`\n\n**2 Nov 2026**\n- HKMA and HKUST launch PQC Toolkit to support banks' quantum preparedness: `/eng/news-and-media/press-releases/2026/11/20261102-6/`\n- HKMA advances Project Ensemble pilot phase to 24/7 settlement in tokenised Central Bank Money: `/eng/news-and-media/press-releases/2026/11/20261102-5/`\n- HKMA launches Project SAGE and establishes Expert Group for agentic finance: `/eng/news-and-media/press-releases/2026/11/20261102-4/`\n- Hong Kong FinTech Week 2026: `/eng/news-and-media/press-releases/2026/11/20261102-3/`\n\n**AI-related:** The Project SAGE release is the one most directly about AI. Its title refers to \"agentic finance\" and an Expert Group. The page shows only titles and dates, so I can't say more about its scope. The Hong Kong FinTech Week 2026 release may also touch on AI, but the listing doesn't say.",
  "durationMs": 6791,
  "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/"
}

{
  "query": "HKMA Project SAGE AI agent governance discussion paper November 2026",
  "mode": "extended"
}

{
  "query": "HKMA Project SAGE AI agent governance discussion paper November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01WGj9eNNeoVzSAxDK7Spfbm",
      "content": [
        {
          "title": "Hong Kong Launches AI-Agent Governance Project - Caixin Global",
          "url": "https://www.caixinglobal.com/2026-11-02/hong-kong-launches-ai-agent-governance-project-102500128.html"
        },
        {
          "title": "Hong Kong Launches Agentic Finance Initiative as Mastercard-Certified AI Business Card Debuts",
          "url": "https://fintechnize.substack.com/p/hong-kong-launches-agentic-finance"
        },
        {
          "title": "HKMA unveils four key areas of fintech initiatives: DART framework",
          "url": "https://www.thestandard.com.hk/finance/article/347196/HKMA-unveils-four-key-areas-of-fintech-initiatives-DART-framework"
        },
        {
          "title": "HKMA Launches SAGE Project for Agent-Based Finance; Circle and Others Join Expert Panel",
          "url": "https://www.kucoin.com/news/flash/hkma-launches-sage-project-for-agent-based-finance-circle-and-others-join-expert-panel"
        },
        {
          "title": "Hong Kong Monetary Authority - Hong Kong FinTech Week 2026",
          "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/2026/11/20261102-3/"
        },
        {
          "title": "When Agent Governance Helps",
          "url": "https://arxiv.org/pdf/2609.05531"
        },
        {
          "title": "Agentic AI Governance and Lifecycle Management in Healthcare",
          "url": "https://arxiv.org/pdf/2601.15630"
        },
        {
          "title": "Decentralized Governance of Autonomous AI Agents",
          "url": "https://arxiv.org/pdf/2412.17114"
        },
        {
          "title": "Runtime Governance for AI Agents: Policies on Paths",
          "url": "https://arxiv.org/pdf/2603.16586"
        }
      ]
    },
    "The HKMA launched Project SAGE on November 2, 2026, during Hong Kong FinTech Week, and published a discussion paper alongside it. I found no separate HKMA paper dated November 2026 beyond that release.\n\n- **Project SAGE:** The HKMA's own release describes it as a initiative to ensure responsible development of agentic AI in financial services, with a cross-sectoral expert group supporting it (the HKMA launched Project SAGE (Securing Agentic Finance with Governance and Enablement). To support the work of Project SAGE, the HKMA has established a cross-sectoral Agentic Finance Expert Group.). The expert group reportedly has 22 members, including Mastercard, Ant International, Circle Hong Kong, and Google Cloud (A 22-member expert panel includes firms such as Mastercard, Ant International, Circle Hong Kong, and Google Cloud.).\n- **Scope:** Reported focus areas include agent identity and authorization, interoperability standards, governance, legal liability, and consumer protection (The project will focus on market development and use cases, AI Agent identity and authorization verification mechanisms, interoperability standards and protocols, as well as governance arrangements, legal liabilities, and consumer protection.). One outlet notes the HKMA intends to explore ways to verify an agent's identity and the authority delegated to it (verifying an AI agent's identity and confirming the authority delegated to it by a human or business principal.).\n- **Discussion paper:** The paper seeks industry feedback on supervisory considerations for banks using agentic AI (the HKMA published a discussion paper on the use of Agentic A.I. by banks, seeking industry feedback on the supervisory considerations pertaining to the governance of such applications.). Caixin reports it explores a central registry for critical agents, building on supervisory guidelines issued October 16, 2026 (HKMA will also release a discussion paper on AI agent governance, exploring a central registry for critical agents, building on supervisory guidelines issued Oct 16, 2026.). The Standard adds that the paper asks whether a central register of trusted agents or an industry-wide \"know your agent\" standard is needed (whether a central register of trusted agents or an industry-wide \"know your agent\" standard — akin to KYC — is needed).\n\nThe sources agree on the core facts. The Caixin mention of an October 16 guidance document is the only reference to it in these results, so I'd verify it against the HKMA site before relying on it. The HKMA press release (hkma.gov.hk, 2 November 2026) is the primary source for the paper's details and deadline for comments."
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{
  "command": "echo \"=== SEDAILY ===\" && node scripts/fetch.js \"https://en.sedaily.com/international/2026/11/03/nvidia-tells-cloud-clients-51-percent-of-capacity-must-go\" 2>&1 | head -45; echo; echo \"=== NEROS PR ===\" && node scripts/fetch.js \"https://www.morningstar.com/news/pr-newswire/20261102la86859/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base\" 2>&1 | head -50",
  "description": "Fetch Nvidia China rule and Neros loan sources"
}

{
  "stdout": "=== SEDAILY ===\nHTTP 200 · https://en.sedaily.com/international/2026/11/03/nvidia-tells-cloud-clients-51-percent-of-capacity-must-go · text/html\nNvidia Tells Cloud Clients 51% of Capacity Must Go to Non-Chinese Buyers - Seoul Economic Daily\nSkip to main content\nSeoul Economic Daily\n\nSeoul Economic Daily\n\nKST\nSeoul Economic Daily Korea's Leading Business News Since 1960\n한국어\n\nMenu\n\nSaved Articles Newsletters AI KEY Settings\n\n| Summary | Save\nA A A\n\nNvidia CEO Jensen Huang. AP-Yonhap\nNvidia has told cloud and data center customers worldwide that at least 51% of their services must be sold to non-Chinese companies, effectively requiring them to cut revenue from Chinese clients below half. The move is seen as an effort to slow China's progress as the artificial intelligence rivalry between Washington and Beijing intensifies.\nNvidia has relayed the policy to cloud computing customers in recent months, the Financial Times reported on the 2nd. No such restriction had existed before. The instruction was not put in writing but was delivered verbally through Nvidia's sales organization and regional teams, people familiar with the matter said. The additional compliance requirement is not limited to data centers in Asia and applies to customers globally. Existing rental contracts are unaffected, however, and the rule covers only future agreements.\nThe requirement presents a fresh threat to the AI ambitions of Chinese technology companies, as the U.S. government also tightens access to advanced chips obtained through overseas cloud contracts. Many Chinese firms have relied on such offshore rentals for high-performance AI work including model training. The U.S. is seeking to shut down both the intermediaries that have fueled a black market for Nvidia chips inside China and the overseas rental route.\nThe shortage of advanced computing power at Chinese technology companies is indeed deepening. A rack of Nvidia B300 chips that sells for about $600,000 on the international market traded in China last month at 18.5 million yuan, or $2.8 million, because of scarcity. The B300 is Nvidia's top-end product, barred from sale in China under U.S. export controls, and is used by major American AI companies including Anthropic and OpenAI.\nCloud operators say the new requirement will be hard to meet. One Singapore-based provider said it is difficult to secure enough non-Chinese customers outside the U.S., adding that strict enforcement would clearly hurt its business. Data centers outside the U.S. have begun courting non-Chinese clients. Those that fail to win them may have to scale back operations.\nNvidia had already cut the number of Asian customers approved to buy its AI chips by more than half after drawing up a whitelist this year of companies that passed tightened compliance reviews. The company said data centers and clouds built on American chips are the foundation that allows U.S. model and application companies to compete worldwide, adding that long-standing U.S. policy has encouraged every cloud to build on American infrastructure and to win business anywhere.\nNvidia shares, meanwhile, have fallen more than 13% over the past month. The recent decline cost the company, led by Jensen Huang, its position as the world's most valuable company by market capitalization, a title it ceded to Apple.\n\n# Nvidia # AIchips # ChinaTech # CloudComputing # ExportControls # B300 # JensenHuang\nOriginal reporting by Park Si-jin for Seoul Economic Daily.\nAI-translated from Korean. Quotes from foreign sources are based on Korean-language reports and may not reflect exact original wording.\nView Korean original ↗ Translation Policy\n\nWatch · Seoul Economic Daily\nMore →\n1:07\n\nTomorrow’s U.S. Midterm Elections - Why They Matter for Samsung & SK Hynix 1:07\n\n# Most Read This Week\n1 - 5 ‹ ›\n\n- 1\nJapan to Urge Citizens to Stockpile Three Days of Food, Water\n\n- 2\n\n=== NEROS PR ===\nHTTP 403 · https://www.morningstar.com/news/pr-newswire/20261102la86859/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base · text/html\nERROR: The request could not be satisfied\n\n# 403 ERROR\n\n# The request could not be satisfied.\n\nRequest blocked.\nWe can't connect to the server for this app or website at this time. There might be too much traffic or a configuration error. Try again later, or contact the app or website owner.\n\nIf you provide content to customers through CloudFront, you can find steps to troubleshoot and help prevent this error by reviewing the CloudFront documentation.\n\nGenerated by cloudfront (CloudFront)\nRequest ID: BTISdLUR22idrFWdbymhzY_NM0onNO1aafOke8lh59S0P7gGTVrIlw==",
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{
  "url": "https://dronexl.co/2026/11/02/neros-450m-osc-loan-taxpayer-ownership-stake/",
  "prompt": "Publication date and all figures: loan amount, equity, project total, production targets, OSC statement, warrants/ownership stake details."
}

{
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  "result": "**Neros Technologies** and the Pentagon's Office of Strategic Capital (OSC) announced a conditional loan commitment of up to $450 million on November 2, 2026, to expand drone and component production at Neros's Torrance, California factory. Neros is committing $165 million in equity, bringing the project total to $615 million.\n\nThe article flags a discrepancy. Neros's website says the deal gives \"the American taxpayer an ownership stake in the company.\" The PR Newswire version ends the same sentence at the $615 million figure. OSC's release describes a conditional loan alongside private capital and doesn't mention an ownership stake. Neither Neros announcement nor OSC's release says what form the stake would take or how much of the company it would cover.\n\nOther key points:\n\n- **Conditions:** Nothing is final. Neros must still meet financial, legal, technical, investment, and due-diligence requirements before financial close.\n- **Supply role:** OSC says the Torrance plant would sell NDAA-compliant motors, radios, flight electronics, sensors, and batteries to other American and allied drone makers.\n- **Production goal:** CEO Soren Monroe-Anderson targets one million drones per year by 2028. Neros was building about 1,200 drones a week in August (roughly 62,000 a year), so the goal requires about a sixteenfold increase.\n- **Context:** In May, the Wall Street Journal reported that Performance Drone Works, Unusual Machines, and Neros were candidates for OSC financing. PDW signed its conditional loan on July 31. Neros is the second of those three to sign.\n- **Editor's view:** The author supports lending to Neros, which delivered its full Gauntlet I order on time, but objects to a government ownership stake. The author argues that it would make Washington a shareholder in a company competing with the same drone makers that would buy its parts. The author urges OSC to publish the terms before financial close.",
  "durationMs": 5685,
  "url": "https://dronexl.co/2026/11/02/neros-450m-osc-loan-taxpayer-ownership-stake/"
}

{
  "query": "Office of Strategic Capital Neros press release war.gov November 2 2026 drone industrial base",
  "mode": "standard"
}

{
  "query": "Office of Strategic Capital Neros press release war.gov November 2 2026 drone industrial base",
  "results": [
    {
      "tool_use_id": "srvtoolu_015AaYwY74uLjYBuRgscrdSs",
      "content": [
        {
          "title": "Neros closes Series B, secures a big contract as drones dominate",
          "url": "https://www.calibredefence.co.uk/?p=5286"
        },
        {
          "title": "Neros closes Series B, secures a big contract as drones dominate",
          "url": "https://www.calibredefence.co.uk/neros-closes-series-b-secures-a-big-contract-as-drones-dominate/"
        },
        {
          "title": "the office of strategic capital signs 820 million conditional loan commitment with performance drone works to expand domestic drone component manufacturing",
          "url": "https://stage1ventures.com/post/the-office-of-strategic-capital-signs-820-million-conditional-loan-commitment-with-performance-drone-works-to-expand-domestic-drone-component-manufacturing"
        },
        {
          "title": "The Pentagon Strategy To Nationalize Small Tech Before China Corners The Sky",
          "url": "https://weddings.lavenderhotels.co.uk/pentagon-strategy-nationalize-small-tech-china-corners-sky"
        },
        {
          "title": "groups.google.com",
          "url": "https://groups.google.com/g/world_wide_with_god_minstry4/c/LYi9unepnEg"
        },
        {
          "title": "EL SEGUNDO, Calif.--(BUSINESS WIRE)--Nov 10, 2025--",
          "url": "https://www.galvnews.com/neros-closes-75m-series-b-fundraise-led-by-sequoia-capital-selected-for-army-program/article_691e0cad-57fb-54bd-a361-1a49b265d4c2.html"
        },
        {
          "title": "the office of strategic capital signs 820 million conditional loan commitment with performance drone works to expand domestic drone component manufacturing",
          "url": "https://soldiersystems.net/2026/07/31/the-office-of-strategic-capital-signs-820-million-conditional-loan-commitment-with-performance-drone-works-to-expand-domestic-drone-component-manufacturing/"
        },
        {
          "title": "neros 250m series c army million drones",
          "url": "https://dronexl.co/2026/08/18/neros-250m-series-c-army-million-drones/"
        },
        {
          "title": "Neros Closes %2475M Series B Fundraise led by Sequoia Capital Selected for Army Program",
          "url": "https://www.businesswire.com/news/home/20251107969770/en/Neros-Closes-%2475M-Series-B-Fundraise-led-by-Sequoia-Capital-Selected-for-Army-Program"
        },
        {
          "title": "The Robot Report",
          "url": "https://www.therobotreport.com/drone-maker-neros-raises-75m-expand-industrial-capacity/"
        },
        {
          "title": "Реклама партнера — Название партнёра",
          "url": "https://dev.ua/en/news/amerykanskyi-vyrobnyk-droniv-neros-zaluchyv-75-mln-i-rozshyriuie-ofis-u-kyievi-1762962439"
        },
        {
          "title": "www.tectonicdefense.com",
          "url": "https://www.tectonicdefense.com/?p=1410"
        },
        {
          "title": "www.businesswire.com",
          "url": "https://www.businesswire.com/news/home/20251106525503/en"
        },
        {
          "title": "us drone warfare enters new era as neros aims to produce one million fpv drones yearly",
          "url": "https://armyrecognition.com/news/aerospace-news/2025/us-drone-warfare-enters-new-era-as-neros-aims-to-produce-one-million-fpv-drones-yearly"
        },
        {
          "title": "neros raises 250m series c at 2 5b valuation to scale autonomous and interceptor drone programs",
          "url": "https://www.vcaonline.com/news/2026081109/neros-raises-250m-series-c-at-2-5b-valuation-to-scale-autonomous-and-interceptor-drone-programs/"
        },
        {
          "title": "Washington Moves from Drone Customer to Drone Investor",
          "url": "https://lifestyle.fictiontalk.com/?p=688080"
        },
        {
          "title": "⚡ Key Takeaways",
          "url": "https://algeriatech.news/?p=34898"
        }
      ]
    },
    "I couldn't find a War Department press release dated November 2, 2026 about Neros or the drone industrial base. The closest matches are earlier items:\n\n- **Performance Drone Works (July 31, 2026):** The Office of Strategic Capital announced a conditional loan commitment of up to $820 million to establish high-volume domestic manufacturing capacity for critical drone components. The release is on war.gov, but it is dated July 31, 2026, not November.\n- **Neros Series C (August 2026):** Neros announced a $250M Series C at a post money valuation of $2.5B, co-led by Sequoia Capital and the American Strategic Technology Fund. This was a private funding round, not a Pentagon announcement.\n- **Pentagon financing talks:** In May, the Wall Street Journal reported that the Office of Strategic Capital had identified Neros, Performance Drone Works and Unusual Machines as candidates for federal financing that could include equity. A less reliable aggregator page also says the office holds roughly $210 billion in authority.\n\nSearch results also included older Neros items, such as a November 2025 Series B and Army program selection. Those are not relevant to a November 2, 2026 release.\n\nIf the November 2 release exists, it may not be indexed yet. I'd suggest checking war.gov's News Releases page directly or searching for the exact title."
  ],
  "durationSeconds": 5.524548937999993,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://www.reuters.com/technology/artificial-intelligence/\" 2>&1 | head -c 4000",
  "description": "Fetch Reuters AI section"
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Neros is committing $165 million in equity, bringing the project total to $615 million.\\n\\nThe article flags a discrepancy. Neros's website says the deal gives \\\"the American taxpayer an ownership stake in the company.\\\" The PR Newswire version ends the same sentence at the $615 million figure. OSC's release describes a conditional loan alongside private capital and doesn't mention an ownership stake. Neither Neros announcement nor OSC's release says what form the stake would take or how much of the company it would cover.\\n\\nOther key points:\\n\\n- **Conditions:** Nothing is final. Neros must still meet financial, legal, technical, investment, and due-diligence requirements before financial close.\\n- **Supply role:** OSC says the Torrance plant would sell NDAA-compliant motors, radios, flight electronics, sensors, and batteries to other American and allied drone makers.\\n- **Production goal:** CEO Soren Monroe-Anderson targets one million drones per year by 2028. Neros was building about 1,200 drones a week in August (roughly 62,000 a year), so the goal requires about a sixteenfold increase.\\n- **Context:** In May, the Wall Street Journal reported that Performance Drone Works, Unusual Machines, and Neros were candidates for OSC financing. PDW signed its conditional loan on July 31. Neros is the second of those three to sign.\\n- **Editor's view:** The author supports lending to Neros, which delivered its full Gauntlet I order on time, but objects to a government ownership stake. The author argues that it would make Washington a shareholder in a company competing with the same drone makers that would buy its parts. The author urges OSC to publish the terms before financial close.\",\"durationMs\":5685,\"url\":\"https://dronexl.co/2026/11/02/neros-450m-osc-loan-taxpayer-ownership-stake/\"}}"," {\"t\":\"2026-11-03T11:15:42.081Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7d5674a33c6d710e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_01LZ3wE7WwddR12Rcyk6XrBK\",\"duration_ms\":5525,\"input\":{\"query\":\"Office of Strategic Capital Neros press release war.gov November 2 2026 drone industrial base\",\"mode\":\"standard\"},\"response\":{\"query\":\"Office of Strategic Capital Neros press release war.gov November 2 2026 drone industrial base\",\"results\":[{\"tool_use_id\":\"srvtoolu_015AaYwY74uLjYBuRgscrdSs\",\"content\":[{\"title\":\"Neros closes Series B, secures a big contract as drones dominate\",\"url\":\"https://www.calibredefence.co.uk/?p=5286\"},{\"title\":\"Neros closes Series B, secures a big contract as drones dominate\",\"url\":\"https://www.calibredefence.co.uk/neros-closes-series-b-secures-a-big-contract-as-drones-dominate/\"},{\"title\":\"the office of strategic capital signs 820 million conditional loan commitment with performance drone works to expand domestic drone component manufacturing\",\"url\":\"https://stage1ventures.com/post/the-office-of-strategic-capital-signs-820-million-conditional-loan-commitment-with-performance-drone-works-to-expand-domestic-drone-component-manufacturing\"},{\"title\":\"The Pentagon Strategy To Nationalize Small Tech Before China Corners The Sky\",\"url\":\"https://weddings.lavenderhotels.co.uk/pentagon-strategy-nationalize-small-tech-china-corners-sky\"},{\"title\":\"groups.google.com\",\"url\":\"https://groups.google.com/g/world_wide_with_god_minstry4/c/LYi9unepnEg\"},{\"title\":\"EL SEGUNDO, Calif.--(BUSINESS WIRE)--Nov 10, 2025--\",\"url\":\"https://www.galvnews.com/neros-closes-75
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://www.prnewswire.com/news-releases/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base-302803710.html\" 2>&1 | head -8; echo \"=== try neros site ===\"; node scripts/fetch.js \"https://neros.com/news\" 2>&1 | head -20",
  "description": "Try Neros press release"
}

{"stdout":"HTTP 404 · https://www.prnewswire.com/news-releases/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base-302803710.html · text/html\n404 Page Not Found | PR Newswire\n\nAccessibility Statement\nSkip Navigation\n\n#\n\n=== try neros site ===\nHTTP 503 · https://neros.com/news · text/plain\nupstream connect error or disconnect/reset before headers. retried and the latest reset reason: remote connection failure","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.transcript.jsonl","hunks":[{"oldStart":462,"oldLines":3,"newStart":462,"newLines":10,"lines":[" 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beats.\"}],\"container\":null,\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":2,\"cache_creation_input_tokens\":164,\"cache_read_input_tokens\":174995,\"output_tokens\":308,\"output_tokens_details\":{\"thinking_tokens\":145},\"server_tool_use\":{\"web_search_requests\":0,\"web_fetch_requests\":0},\"service_tier\":\"standard\",\"cache_creation\":{\"ephemeral_1h_input_tokens\":164,\"ephemeral_5m_input_tokens\":0},\"inference_geo\":\"global\",\"iterations\":[{\"input_tokens\":2,\"output_tokens\":308,\"cache_read_input_tokens\":174995,\"cache_creation_input_tokens\":164,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":164},\"type\":\"message\"}],\"speed\":\"standard\",\"fallback_credit\":null},\"input_transformations\":[],\"diagnostics\":null,\"context_management\":null},\"serverClassifierRequest\":\"c612208b-5e53-484b-b8f0-e88dad8c62f7\",\"apiBlockIndex\":1,\"requestId\":\"req_011Cgfu6hAf3CpCsPY54ufKE\",\"requestedModel\":\"claude-opus-5\",\"type\":\"assistant\",\"uuid\":\"8d604695-d355-48cf-ab37-5bb80993e0b8\",\"timestamp\":\"2026-11-03T11:15:43.344Z\",\"effort\":\"high\",\"perTurnEffort\":null,\"userType\":\"external\",\"entrypoint\":\"remote_trigger\",\"cwd\":\"/home/user/ainews\",\"sessionId\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"version\":\"2.1.317\",\"gitBranch\":\"HEAD\"}"," 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… [10069 more characters in events.jsonl]

{
  "url": "https://www.technologyreview.com/feed/",
  "prompt": "List items with pubDate November 2 or 3, 2026, with titles and links."
}

{
  "bytes": 142172,
  "code": 200,
  "codeText": "OK",
  "result": "Items with a pubDate of November 2 or 3, 2026:\n\n1. [How \"reverse game theory\" could keep AI agents in check](https://www.technologyreview.com/2026/11/03/1147934/reverse-game-theory-mechanism-design-ai-alignment/) (Nov 3, 10:43 UTC)\n2. [Here's who is falling in line for Trump's \"Super Intelligence\" loyalty test](https://www.technologyreview.com/2026/11/02/1147932/heres-who-is-falling-in-line-for-trumps-super-intelligence-loyalty-test/) (Nov 3, 04:18 UTC)\n3. [Raising the quality of insights in agentic analytics](https://www.technologyreview.com/2026/11/02/1147660/raising-the-quality-of-insights-in-agentic-analytics/) (Nov 2, 17:00 UTC)\n4. [Stop counting tokens, start counting what ships](https://www.technologyreview.com/2026/11/02/1147702/stop-counting-tokens-start-counting-what-ships/) (Nov 2, 13:10 UTC)\n5. [The Download: the agentic web arrives and the drive for safer roads](https://www.technologyreview.com/2026/11/02/1147889/the-download-agentic-web-arrives-eliminating-traffic-deaths/) (Nov 2, 13:10 UTC)\n6. [The agentic web is here](https://www.technologyreview.com/2026/11/02/1147846/the-agentic-web-is-here/) (Nov 2, 09:35 UTC)\n\nThe feed content was truncated, so there may be additional items from these dates that I couldn't see.\n\n[WebFetch note: this page's text is 140993 characters long and the answer above covers only characters 0 to 100000; the final 40993 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 6226,
  "url": "https://www.technologyreview.com/feed/"
}

{
  "query": "AI agent security incident disclosed \"November 2, 2026\" OR \"November 3, 2026\" vulnerability MCP",
  "mode": "extended"
}

{
  "query": "AI agent security incident disclosed \"November 2, 2026\" OR \"November 3, 2026\" vulnerability MCP",
  "results": [
    {
      "tool_use_id": "srvtoolu_0151MSVMYAfjwu12qYbwsBcv",
      "content": [
        {
          "title": "MCP Security Crisis: Systemic Design Flaws in AI Agent Infrastructure",
          "url": "https://labs.cloudsecurityalliance.org/research/csa-research-note-mcp-security-crisis-20260504-csa-styled/"
        },
        {
          "title": "The Mother of All AI Supply Chains: Critical, Systemic Vulnerability at the Core of Anthropic’s MCP - OX Security",
          "url": "https://www.ox.security/blog/the-mother-of-all-ai-supply-chains-critical-systemic-vulnerability-at-the-core-of-the-mcp/"
        },
        {
          "title": "PT-2026-135831 - vulnerability database",
          "url": "https://vulners.com/ptsecurity/PT-2026-135831"
        },
        {
          "title": "GitHub - webpro255/awesome-ai-agent-attacks: A curated timeline of real AI agent security incidents, breaches, and vulnerabilities (2024-2026). Every entry sourced and dated. · GitHub",
          "url": "https://github.com/webpro255/awesome-ai-agent-attacks"
        },
        {
          "title": "Model Context Protocol (MCP)",
          "url": "https://www.nsa.gov/Portals/75/documents/Cybersecurity/CSI_MCP_SECURITY.pdf"
        },
        {
          "title": "Digest: MCP agent-to-agent trust gaps exposed (Ars Technica) · Issue #27 · mcpmark-eval-liuhezi/mcp-news-watch · GitHub",
          "url": "https://github.com/mcpmark-eval-liuhezi/mcp-news-watch/issues/27"
        },
        {
          "title": "Anthropic MCP Design Vulnerability Enables RCE, Threatening AI Supply Chain",
          "url": "https://thehackernews.com/2026/04/anthropic-mcp-design-vulnerability.html"
        },
        {
          "title": "The Vulnerable MCP Project: Comprehensive Model Context Protocol Security Database",
          "url": "https://vulnerablemcp.info/"
        },
        {
          "title": "Critical Langflow Flaws Could Let Unauthenticated Attackers Run Code on Servers",
          "url": "https://thehackernews.com/2026/11/critical-langflow-flaws-could-let.html"
        }
      ]
    },
    "The search turned up a few MCP-related items that look recent, but none clearly confirms a disclosure dated exactly November 2 or 3, 2026. I ran a simplified query rather than the exact quoted-operator version.\n\n**Most recent items:**\n- **Langflow flaws (The Hacker News, dated today):** IBM rated several critical Langflow flaws, including one described as \"unauthenticated remote code execution exploitable through model context protocol tool enumeration.\" A public Metasploit module already cites the authentication bypass CVE, though it does not run code or commands on the server.\n- **MCP SDK OAuth credential exposure (Positive Technologies, via Vulners):** Listed with a date of 02 Nov 2026. It concerns OAuth credential exposure flaws in the official MCP Python and TypeScript SDKs, rated medium risk.\n- **Agent-to-agent MCP trust gaps (Ars Technica, via a GitHub digest):** Dated about a day ago, though the linked URL suggests October. Researchers report trust gaps in agent-to-agent communications protocols that can spread malicious prompts from one agent to another via MCP-based comms.\n\n**Background (older):** The OX Security MCP research from April 2026 described a command execution flaw in Anthropic's MCP SDKs, and an October 2026 Claude Agent SDK issue (CVE-2026-96620) was also tracked. These predate the window you asked about.\n\nI didn't confirm exact publication times for the Langflow and Ars items beyond their listed ages, so check the original sources before relying on dates."
  ],
  "durationSeconds": 7.759196582000004,
  "searchCount": 1
}

{
  "url": "https://vulners.com/ptsecurity/PT-2026-135831",
  "prompt": "Publication date, CVE, affected MCP SDKs and versions, severity, description."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 237,
  "url": "https://vulners.com/ptsecurity/PT-2026-135831"
}

{
  "url": "https://www.technologyreview.com/2026/11/02/1147932/heres-who-is-falling-in-line-for-trumps-super-intelligence-loyalty-test/",
  "prompt": "Give date, author, and all concrete facts: what the loyalty test / executive order is, which companies or agencies have complied, dates, numbers, and any documents cited."
}

{
  "bytes": 436906,
  "code": 200,
  "codeText": "OK",
  "result": "**Source:** \"Here's who is falling in line for Trump's 'Super Intelligence' loyalty test,\" by James O'Donnell, *MIT Technology Review*, November 2, 2026.\n\n**The directive:** In late September 2026, President Trump signed an executive order with one directive: government agencies must rebrand \"artificial intelligence\" as \"Super Intelligence\" (SI). The term beat \"Extreme Intelligence\" and \"Supreme Intelligence,\" which he had floated in an X poll. The stated reason is that AI systems \"amplify human ingenuity\" rather than merely imitating intelligence. The order also requires agency leaders to draft a legislative definition of \"Super Intelligence\" for the president by the end of November. The article argues the rebrand works as a political loyalty test.\n\n**Government compliance (mixed):**\n- ICE issued a request for \"SI-powered\" surveillance for detention facilities.\n- Many government websites swapped in the new term. NIH added a banner noting visitors may see both terms during the transition.\n- The Pentagon's Project Meridian, announced a day after the order, used the old terminology.\n- An FTC press release used \"superintelligence\" rather than the two-word capitalized form ordered.\n- Recent HHS press releases showed no change.\n- The order doesn't apply to previously issued documents, and offices like the Pentagon's Chief Digital and Artificial Intelligence Office keep \"AI\" in their names.\n- Defense Secretary Pete Hegseth used \"AI\" in an October 3 interview.\n- The Navy and Marines issued transition guidance.\n\n**Pressure on outside groups:**\n- On October 27, Trump criticized the *Wall Street Journal* on Truth Social for not using the term and suggested a rule could ban \"artificial intelligence\" from government documents.\n- Newsmax, which supports the president, isn't using the term either.\n- Salesforce CEO Marc Benioff has chosen \"SIForce\" over \"AIForce\" for his company's naming.\n\n**Tech executives:**\n- On the same day as the order, the nonbinding White House Accord on Super Intelligence (an AI safety statement) was signed by Sundar Pichai (Google), Dario Amodei (Anthropic), Mark Zuckerberg (Meta), Greg Brockman (OpenAI), Elon Musk (xAI), and Jensen Huang (Nvidia). Three attended Trump's inauguration.\n- A CNBC analysis of Q3 2026 earnings calls found only Zuckerberg and Musk used the term consistently. Meta had used \"superintelligence\" since 2025.\n- Musk pledged to rename SpaceXAI to SpaceXSI, but still mixes \"SI\" and \"AI\" on X.\n- Amazon, Microsoft, and Alphabet executives mostly said \"AI.\" Microsoft's shareholder letter did refer to the \"Super Intelligence era.\"\n- Huang uses both terms.\n\n**Public context:**\n- Pew Research (June 17, 2026) found two-thirds of Americans interact with AI multiple times a week.\n- Pew (October 8, 2026) found Americans rank AI as more important to them in the midterms than environmental and climate policy.\n- The article was written just before the midterm elections on November 3, 2026.",
  "durationMs": 9429,
  "url": "https://www.technologyreview.com/2026/11/02/1147932/heres-who-is-falling-in-line-for-trumps-super-intelligence-loyalty-test/"
}

{
  "url": "https://huggingface.co/blog/feed.xml",
  "prompt": "List all items with titles, links and publication dates."
}

{"bytes":264354,"code":200,"codeText":"OK","result":"The feed is truncated, so this list is partial. It covers items from \"Transformers Model Integration Contracts\" (03 Nov 2026) through \"4M Models Scanned: Protect AI + Hugging Face 6 Months In\" (14 Apr 2025), where the content cuts off. Links are shown as paths; the base URL is https://huggingface.co/blog/ (for example, `nvidia/nemotron-halloween` is https://huggingface.co/blog/nvidia/nemotron-halloween).\n\n1. \"Transformers Model Integration Contracts\", Tue, 03 Nov 2026, `transformers-mic`\n2. \"nemotron-halloween\", Fri, 30 Oct 2026, `nvidia/nemotron-halloween`\n3. \"Granite Switch 4.1.1 — Update models like you update software\", Thu, 29 Oct 2026, `ibm-granite/granite-switch-4-1-1`\n4. \"Announcing Project ProtoStar: Making Publicly Funded Science AI-Ready\", Thu, 29 Oct 2026, `announcing-project-protostar`\n5. \"Welcome Le Chonk: Mistral Large 4 on Hugging Face\", Thu, 29 Oct 2026, `mistral-large4`\n6. \"Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms\", Thu, 29 Oct 2026, `anydecisionmodel`\n7. \"Build specialized multimodal models with LFM3\", Tue, 27 Oct 2026, `LiquidAI/lfm3`\n8. \"Can we trust LLMs to judge whether a research idea is novel?\", Tue, 27 Oct 2026, `allenai/novelty-bench`\n9. \"Does Your Model Run on AWS Trainium? Look It Up\", Fri, 23 Oct 2026, `torch-neuronx-model-support`\n10. \"Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox\", Thu, 22 Oct 2026, `microsoft/thinkingbox-training`\n11. \"Ensemble forecasting with IBM Granite time-series models\", Thu, 22 Oct 2026, `ibm-research/granite-timeseries-ensemble-r1`\n12. \"How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications\", Wed, 21 Oct 2026, `Dharma-AI/vocabx-vocabulary-specialization`\n13. \"Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.\", Wed, 21 Oct 2026, `amazon/profiling-torchneuron-part-1`\n14. \"Hugging Face ❤️ TorchTPU: TPUs, Natively\", Tue, 20 Oct 2026, `hf-torchtpu`\n15. \"AnyLanguageModel 1.0: One Year of Local Models on Apple Platforms\", Tue, 20 Oct 2026, `anylanguagemodel-1-0`\n16. \"MPS in PyTorch 2.15\", Tue, 20 Oct 2026, `mps-pytorch-2-15`\n17. \"TorchNeuron: running HF models on AWS Trainium is easier than ever\", Mon, 19 Oct 2026, `hf-torchneuron`\n18. \"Welcome Beam: a 501B open model you can own, customize, and scale\", Fri, 16 Oct 2026, `reflection-beam`\n19. \"Apertus 1.5 Release Notes\", Thu, 15 Oct 2026, `swiss-ai/apertus-v15-release-notes`\n20. \"Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta\", Thu, 15 Oct 2026, `meta-muse-spark-open`\n21. \"Welcome FLUX.3 Image Klein in Diffusers\", Thu, 15 Oct 2026, `flux-3`\n22. \"Run fast, private agents on-device with LFM2.5-24B-A2B\", Tue, 13 Oct 2026, `LiquidAI/lfm25-24b-a2b`\n23. \"The model that didn't exist, so you made it yourself\", Thu, 08 Oct 2026, `building-with-ml-intern`\n24. \"Introducing Falcon ASR\", Wed, 07 Oct 2026, `tiiuae/falcon-asr`\n25. \"The Agent Said It Was Done. The Database Disagreed.\", Sat, 03 Oct 2026, `microsoft/thinkingbox`\n26. \"AutoSynthData: Generating Training Data for Enterprise Agents\", Fri, 02 Oct 2026, `ServiceNow-AI/autosynthdata`\n27. \"Open TTS Leaderboard: Scalable Evaluation for Multilingual Text-to-Speech and Voice Cloning\", Wed, 30 Sep 2026, `open-tts-leaderboard`\n28. \"Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents\", Tue, 29 Sep 2026, `MultiverseComputingCAI/getting-the-source-right-not-just-the-fact-source`\n29. \"Holo4: powering generalist computer-use agents\", Mon, 28 Sep 2026, `Hcompany/holo4`\n30. \"Welcome RL Environments to the hub\", Mon, 28 Sep 2026, `rl-environments`\n31. \"How UK AISI and EvalEval Are Making Benchmark Results Reproducible\", Tue, 22 Sep 2026, `evaleval-aisi`\n32. \"Transformers now runs llama.cpp quants\", Tue, 22 Sep 2026, `transformers-llama-cpp-quants`\n33. \"Jun Kim, oMLX creator and maintainer, joins Hugging Face to support the MLX community\", Tue, 22 Sep 2026, `omlx`\n34. \"tokenizers v1: encode, decode and scaling, measured\", Mon, 21 Sep 2026, `tokenizers-v1`\n35. \"Your Agent Aced the Task. Will It Do It Again?\", Tue, 15 Sep 2026, `ibm-research/altk-evolve-consistency`\n36. \"Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL\", Thu, 10 Sep 2026, `asyncgrpo-lora-hfjobs`\n37. \"Rebuilding AUTOMATIC1111 with Gradio Workflow\", Thu, 10 Sep 2026, `gradio-workflow-1111`\n38. \"NeoMME: an efficient Multimodal-native and Multilingual Encoder\", Thu, 03 Sep 2026, `Hcompany/neomme`\n39. \"Fine-tuning a 350M Model for Better Structured Outputs in 100 GRPO Steps\", Thu, 03 Sep 2026, `grpo-with-trl-ifstruct`\n40. \"Give Your Coding Agents a Memory You Own\", Thu, 03 Sep 2026, `funes`\n41. \"Training a coding model to paint watercolours with TRL and OpenEnv\", Thu, 03 Sep 2026, `train-to-paint-with-code`\n42. \"BenchMIRT: What are LLM benchmarks actually measuring?\", Tue, 01 Sep 2026, `allenai/benchmirt`\n43. \"Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI\", Tue, 01 Sep 2026, `webgpu-kernels`\n44. \"The Open ASR Leaderboard Adds Its First Global South Language\", Fri, 28 Aug 2026, `open-asr-leaderboard-global-south`\n45. \"Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers\", Wed, 26 Aug 2026, `train-multi-vector-encoder`\n46. \"Granite 4.2 LLMs: How They're Built\", Tue, 25 Aug 2026, `ibm-granite/granite-4-2`\n47. \"Quantization-Aware Healing: a compressed, 4-bit model that outperforms its full-precision original\", Tue, 25 Aug 2026, `MultiverseComputingCAI/quantization-aware-healing`\n48. \"Wire It, Run It, Deploy It: AI Workflows in Gradio\", Tue, 25 Aug 2026, `gradio-workflow-guide`\n49. \"How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code\", Fri, 21 Aug 2026, `pwc-search`
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://www.nature.com/npjdigitalmed/articles\" 2>&1 | head -c 4000",
  "description": "Fetch npj Digital Medicine articles list"
}

{
  "stdout": "HTTP 200 · https://www.nature.com/npjdigitalmed/articles?error=cookies_not_supported&code=013f5a46-c06d-4d53-8985-be322645626d · text/html\nBrowse Articles\n| npj Digital Medicine\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\n# Browse Articles\n\n# Filter By:\n\nArticle Type\n\nAll\n\nYear\n\nAll\n\n-\n\n#\nThe TEMPO program and the future of digital mental health regulation in the US\n\nThe high burden of traditional FDA clearance drives many novel, AI-enabled mental health devices into unregulated consumer markets. The new FDA-CMS TEMPO pilot program establishes a vital regulatory middle ground, allowing companies to commercialize using a Quality Management System without immediate premarket authorization. This commentary explores how TEMPO serves as a sandbox for real-world data, offering a blueprint to reshape the future of US digital health regulation.\n\n- Acacia C. Parks\n\n- Aubrey Shick\n\nComment Open Access 03 Nov 2026\n\n-\n\n#\nCost-effectiveness analysis of digital medicine support models for alcohol use disorder\n\n- Xiang Li\n\n- Ming-Yuan Chih\n\n- Andrew Quanbeck\n\nArticle Open Access 03 Nov 2026\n\n-\n\n#\nPredicting different dimensions of fatigue from speech data: a longitudinal study in shift workers\n\n- Agnes Norbury\n\n- Alexandra Livia Georgescu\n\n- Nicholas Cummins\n\nArticle Open Access 03 Nov 2026\n\n-\n\n#\nGeneration of synthetic clinical text: a systematic review\n\n- Basel Alshaikhdeeb\n\n- Anne Lorant\n\n- Venkata Satagopam\n\nArticle Open Access 31 Oct 2026\n\n-\n\n#\nUnderstanding clinical reasoning variability in medical large language models: a mechanistic interpretability study\n\n- Mirage Modi\n\n- Jordan E. Krull\n\n- Qin Ma\n\nArticle Open Access 31 Oct 2026\n\n-\n\n#\nInterpretability-driven feature engineering enables compact and accurate multi-outcome risk stratification at hospitalization for chronic hepatitis B\n\n- Huiyi Zhang\n\n- Qingxian Song\n\n- Shu Su\n\nArticle Open Access 31 Oct 2026\n\n-\n\n#\nPredicting persistent fever in patients with cancer receiving antibiotics: a machine learning approach\n\n- Gernot Pucher\n\n- Sanjat Kanjilal\n\n- Christopher M. Sauer\n\nArticle Open Access 31 Oct 2026\n\n-\n\n#\nAccuracy and impact of an AI safety system for missed specialist referrals in primary care\n\n- Wayne Han Lee\n\n- Lawrence Teck Meng Lam\n\n- Sky Wei Chee Koh\n\nArticle Open Access 30 Oct 2026\n\n-\n\n#\nInterpretable graph learning of spatial TME patterns in digital pathology for gastric cancer prognosis\n\n- Menglei Hua\n\n- Xiaohan Zheng\n\n- Shenghan Lou\n\nArticle Open Access 30 Oct 2026\n\n-\n\n#\nImplementation strategies for digital relapse prevention in schizophrenia identified during a randomized controlled trial\n\n- Selina Hiller\n\n- Katharina Prietzel\n\n- Kerem Böge\n\nArticle Open Access 30 Oct 2026\n\n-\n\n#\nPlatform evaluation and lessons learned with IT-supported patient recruitment\n\n- Cosima Strantz\n\n- Romina Blasini\n\n- Christian Gulden\n\nArticle Open Access 30 Oct 2026\n\n-\n\n#\nAnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts\n\n- Niklas Grieger\n\n- Jannik Raskob\n\n- Stephan Bialonski\n\nArticle Open Access 30 Oct 2026\n\n-\n\n#\nA physics-informed peripheral hemodynamic digital twin for personalized estimation of arterial stiffness\n\n- Arian Aghilinejad\n\n- Alessio Tamborini\n\n- Morteza Gharib\n\nArticle Open Access 28 Oct 2026\n\n-\n\n#\nRadiographer fracture detection with and without AI assistance in prospective emergency department use\n\n- Jin Rong Tan\n\n- Anh Nguyen Tuan Tran\n\n- Meng Ai Png\n\nArticle Open Access 27 Oct 2026\n\n-\n\n#\nAn interpretable graph reasoning framework for enhanced diagnosis in fundus fluorescein angiography\n\n- Xiaocong Liu\n\n- An Shao\n\n- Jian Wu\n\nArticle Open Access 27 Oct 2026\n\n-\n\n#\nPerformance of artificial intelligence fo",
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{
  "url": "https://thehackernews.com/2026/11/critical-langflow-flaws-could-let.html",
  "prompt": "Publication date, CVE IDs, CVSS scores, affected versions, who disclosed, exploitation status, MCP detail."
}

{
  "bytes": 173074,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 2, 2026, by Swati Khandelwal at The Hacker News. The advisory was first published by IBM on October 28 and updated the next day.\n\n**Disclosure:** IBM disclosed the flaws in a security bulletin covering four Langflow flaws. On October 29, IBM also published CVE records for 29 other Langflow flaws.\n\n**Affected versions:** Every release from 1.0.0 through 1.12.8. The only fix is 1.13.0, released October 22. IBM offers no workaround for servers that cannot upgrade yet.\n\n**CVEs (IBM's CVSS scores):**\n\n| CVE | CVSS | Account needed | Impact per IBM |\n|---|---|---|---|\n| CVE-2026-93680 | 9.8 (Critical) | No | Bypassing security restrictions from improper authentication |\n| CVE-2026-110186 | 9.8 (Critical) | No | Running arbitrary code from improper control of code generation |\n| CVE-2026-110193 | 8.8 (High) | Yes, low-privileged | Making the Agentic Assistant generate or submit component code that runs OS commands |\n| CVE-2026-110192 | 6.5 (Medium) | Yes | Getting sensitive information from insufficiently protected credentials |\n\n**Exploitation status:** Neither critical flaw appears in CISA's Known Exploited Vulnerabilities catalog as of its October 30 update. Six other Langflow flaws are listed there, the most recent being CVE-2026-9198, added in August. A public Metasploit module exists for CVE-2026-93680. Its author lists Langflow 1.5.0 through 1.11.4 as affected, a narrower range than IBM's.\n\n**MCP detail:** IBM describes one flaw as \"unauthenticated remote code execution exploitable through model context protocol tool enumeration.\" Langflow can expose flows as tools to MCP-capable AI apps. The Metasploit module connects to a server's MCP endpoint without credentials, starts a session, and lists the offered tools. It does not run code or commands. The article does not map the MCP-based RCE to a specific CVE.\n\n**Related context:**\n- Automatic login (LANGFLOW_AUTO_LOGIN) is enabled by default in 1.12.8 and signs users in as superusers. IBM describes one of the four flaws as an incomplete fix for an auto-login control. The bulletin does not say whether servers with auto-login off are vulnerable.\n- Among the 29 additional CVEs, CVE-2026-104339 is rated 9.8 and also allows unauthenticated arbitrary code execution. Its fixes are in versions 1.12.4 and 1.12.5. None of the 33 records lists 1.13.0 as affected.",
  "durationMs": 10727,
  "url": "https://thehackernews.com/2026/11/critical-langflow-flaws-could-let.html"
}

{
  "url": "https://blog.google/technology/ai/rss/",
  "prompt": "List items with titles, links and publication dates from Nov 1-3 2026 only."
}

{
  "bytes": 30644,
  "code": 200,
  "codeText": "OK",
  "result": "One item from the feed falls within November 1-3, 2026:\n\n- **\"The latest AI news we announced in October 2026\"**\n  Link: https://blog.google/innovation-and-ai/technology/ai/google-ai-updates-october-2026/\n  Published: Mon, 02 Nov 2026 17:45:00 +0000\n\nNo other items are dated November 1-3, 2026. The next most recent item is from October 26, 2026.",
  "durationMs": 3017,
  "url": "https://blog.google/technology/ai/rss/"
}

{
  "url": "https://z.ai/blog",
  "prompt": "List all blog posts with titles and dates, newest first."
}

{
  "bytes": 0,
  "code": 404,
  "codeText": "Not Found",
  "result": "The server returned HTTP 404 Not Found.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 1667,
  "url": "https://z.ai/blog"
}

{
  "url": "https://blogs.nvidia.com/feed/",
  "prompt": "List items with titles, links and publication dates from Nov 1-3 2026 only."
}

{
  "bytes": 281916,
  "code": 200,
  "codeText": "OK",
  "result": "Only one item in the feed is dated Nov. 1-3, 2026:\n\n- **\"Cities Worldwide Build and Scale AI Services With NVIDIA Physical and Agentic AI\"**\n  Published Nov. 3, 2026\n  https://blogs.nvidia.com/blog/cities-physical-agentic-ai-applications/\n\n[WebFetch note: this page's text is 281080 characters long and the answer above covers only characters 0 to 100000; the final 181080 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 4523,
  "url": "https://blogs.nvidia.com/feed/"
}

{
  "query": "npj Digital Medicine November 2 2026 published study",
  "mode": "extended"
}

{
  "query": "npj Digital Medicine November 2 2026 published study",
  "results": [
    {
      "tool_use_id": "srvtoolu_011MQLdZiJjjmLy5FFBg2VB5",
      "content": [
        {
          "title": "npj Digital Medicine",
          "url": "https://www.deepdyve.com/browse/journals/2398-6352?start=10&rows=10"
        },
        {
          "title": "NPJ digital medicine",
          "url": "https://vivo.weill.cornell.edu/display/journal5f6932dfe2121e6a8ffb2adfc4183c2a"
        },
        {
          "title": "npj Digital Medicine — Explore journal profiles and ratings - Peeref",
          "url": "https://www.peeref.com/journals/11136/npj-digital-medicine"
        },
        {
          "title": "npj Digital Medicine",
          "url": "https://www.deepdyve.com/browse/journals/2398-6352?start=40&rows=10"
        },
        {
          "title": "Npj Digital Medicine: Acceptance Time, Quartile & Journal Metrics 2026",
          "url": "https://www.journalmetrics.org/journal/npj-digital-medicine"
        },
        {
          "title": "LLMs for Medical Consultation Are Evaluated Too Late: The Preformulation Gap",
          "url": "https://arxiv.org/pdf/2608.17330"
        },
        {
          "title": "Study shows AI may improve patient discharge summaries",
          "url": "https://medicalxpress.com/news/2026-11-ai-patient-discharge-summaries.html"
        },
        {
          "title": "Learnings from a Large-Scale Deployment of an LLM-Powered Expert-in-the-Loop Healthcare Chatbot",
          "url": "https://arxiv.org/pdf/2409.10354"
        },
        {
          "title": "Published in Nature Portfolio’s npj Digital Medicine, China’s Future Doctor Team’s New Benchmark Aims to Define What \"Safe and Effective\" Means for Medical AI",
          "url": "https://finance.yahoo.com/news/published-nature-portfolio-npj-digital-160000533.html"
        }
      ]
    },
    "I ran one search and did not find a study dated November 2, 2026. The closest match is a Stony Brook University study on AI-written hospital discharge summaries. Its search metadata says it was published recently, but the results don't give its exact publication date.\n\n- **Discharge summaries study:** Researchers at Stony Brook University published it in npj Digital Medicine. This is the conclusion of a Stony Brook University study published online in npj Digital Medicine. The team compared LLM-generated and physician-written summaries for 60 internal medicine hospitalizations at Stony Brook University Hospital lasting seven to 21 days. Reviewers favored the AI versions in 95% of the evaluated hospitalizations. The citation is Tyler Osborne et al., *Clinician-centered evaluation of large language model-generated discharge summaries for longer hospitalizations* (2026).\n- **Other 2026 listings:** The journal's 2026 listings include other studies, such as a comparison of human and AI-styled physician consultations that involved 163 healthy participants. Search results didn't tie these to any particular date.\n\nIf you need the exact date, check the journal's website (nature.com/npjdigitalmed) and filter by publication date."
  ],
  "durationSeconds": 7.254778121999931,
  "searchCount": 1
}

{
  "query": "military AI geopolitics news November 3 2026 defense ministry artificial intelligence agreement",
  "mode": "extended"
}

{
  "query": "military AI geopolitics news November 3 2026 defense ministry artificial intelligence agreement",
  "results": [
    {
      "tool_use_id": "srvtoolu_017uJf4BPDpTo712Ye4wXHfv",
      "content": [
        {
          "title": "Pentagon announces deal with seven AI companies for classified systems",
          "url": "https://www.aljazeera.com/news/2026/5/1/pentagon-announces-deal-with-seven-ai-companies-for-classified-systems"
        },
        {
          "title": "AI to help Indian military identify target, make battlefield decisions? Here’s what the new defence deal with Sarvam offers - The Week",
          "url": "https://www.theweek.in/news/defence/2026/10/28/ai-to-help-indian-military-identify-target-make-battlefield-decisions-heres-what-the-new-defence-deal-with-sarvam-offers.html"
        },
        {
          "title": "Sarvam to build AI for Indian military",
          "url": "https://www.newsbytesapp.com/news/science/sarvam-signs-5-year-deal-to-build-ai-for-indian-military/story"
        },
        {
          "title": "Sarvam and Ministry of Defence sign framework for AI projects across the Indian Army, Navy and Air Force - CIO&Leader",
          "url": "https://www.cioandleader.com/sarvam-and-ministry-of-defence-sign-framework-for-ai-projects-across-the-indian-army-navy-and-air-force/"
        },
        {
          "title": "October 19, 2024 2:04 PM",
          "url": "https://newsonair.gov.in/ai-has-potential-to-revolutionize-military-operations-defence-minister-rajnath-singh"
        },
        {
          "title": "Ministry of defence unveils Defence Artificial Intelligence Strategy",
          "url": "https://www.globalsecurity.org/military/library/news/2025/03/mil-250324-estonia-mod01.htm"
        },
        {
          "title": "Join Fox News for access to this content",
          "url": "https://www.foxnews.com/us/us-holds-conference-military-ai-use-dozens-allies-determine-responsible-use"
        },
        {
          "title": "AI is the new battleground in geopolitics",
          "url": "https://www.axios.com/ai-is-the-new-battleground-in-geopol-1518622523-8a7ac99c-7fc5-46b5-a79d-a48bc8007cd2.html"
        },
        {
          "title": "rok 251128 rok mnd10",
          "url": "https://www.globalsecurity.org/wmd/library/news/rok/2025/rok-251128-rok-mnd10.htm"
        }
      ]
    },
    "I found no coverage dated November 3, 2026 specifically. The most recent item is from late October, and the rest are older.\n\n- **India (most recent, late October 2026):** India's defence ministry signed a five-year agreement with the Bengaluru startup Sarvam to expand AI across the Army, Navy and Air Force. The framework will give all three services access to common AI foundation models, agentic infrastructure, geospatial systems and perception technologies. Reporting says the focus areas include decision support and target acquisition, with human oversight retained on operational decisions.\n- **United States (May 2026):** The Pentagon announced agreements with seven AI companies for its classified networks. The deal is amid wider scrutiny over involvement by companies with the US military, which has drawn attention to the company Anthropic and to questions about AI use in the US-Israeli war with Iran. The department also said it vowed to continue building the department's AI architecture to avoid so-called \"vendor lock\".\n- **Background:** Estonia's defence ministry published its first defence AI strategy in March 2025, and it notes that AI has seen widespread application in military decision-making support, intelligence processing, and targeting in Ukraine and the Middle East. South Korea's defence ministry held a 2025 defence AI review meeting, where its minister said AI is no longer optional but an essential element of military strength.\n\nFor a true November 3, 2026 update, a search with different wording or a news-specific source may be needed."
  ],
  "durationSeconds": 6.387141437000013,
  "searchCount": 1
}

{
  "query": "China AI export control registration rule took effect large language models chip designs November 2026",
  "mode": "extended"
}

{
  "query": "China AI export control registration rule took effect large language models chip designs November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01JNRaBuuB7nL3UTn8P1UcJS",
      "content": [
        {
          "title": "China proposes export controls on its advanced AI models and chip designs",
          "url": "https://thenextweb.com/news/china-ai-export-controls-draft"
        },
        {
          "title": "China proposes export controls on its advanced AI models and chip designs",
          "url": "https://daily.dev/posts/china-proposes-export-controls-on-its-advanced-ai-models-and-chip-designs-0yanh2zcb"
        },
        {
          "title": "China Proposes AI Export Controls on Models and Chips",
          "url": "https://emergent.sh/news/china-proposes-ai-export-controls-models"
        },
        {
          "title": "Whack-a-Chip: The Futility of Hardware-Centric Export Controls",
          "url": "https://arxiv.org/pdf/2411.14425"
        },
        {
          "title": "China wants to control exports of any AI model over 2 trillion parameters",
          "url": "https://madrobot.blog/2026/10/16/china-ai-export-controls-23-technologies-large-models-agents/"
        },
        {
          "title": "China Proposes AI Export Curbs on 23 Technologies [2026]",
          "url": "https://tech-insider.org/china-ai-export-curbs-23-technologies-2026/"
        },
        {
          "title": "China drafts export controls on AI model weights and chip designs",
          "url": "https://www.thefrontier.dev/articles/china-ai-export-controls"
        },
        {
          "title": "China AI export controls draft: 23 technologies, 2T models",
          "url": "https://techaiwire.com/articles/china-ai-export-controls-draft-23-technologies-2-trillion-parameters/"
        },
        {
          "title": "What the China AI Export Controls Draft Actually Says",
          "url": "https://shattered.io/what-the-china-ai-export-controls-draft-actually-says/"
        }
      ]
    },
    "The search points to October 16, 2026, not November, as the date the temporary registration rule took effect.\n\n- **Timing:** A temporary pre-export registration requirement took effect on October 16, 2026. The draft's comments due 15 November, so the broader list is still under consultation.\n- **Scope of the draft:** Ministries proposed adding 23 AI technologies, including large models, agents, chip designs, and computing clusters, to the country's export control list. For large models, the curbs would cover weights, source code, and other core parts. The size threshold is models with at least 2 trillion parameters, or that rank in the world's top 10 on benchmarks such as performance and safety.\n- **Chips:** The draft would limit design know-how for AI chips manufactured at 14 nanometres or below, as well as chips built using 2.5D or 3D stacking techniques, along with certain memory chip designs.\n- **Registration:** Firms must register before exporting listed items, including incomplete deals. Per one source, companies must register on the commerce ministry's platform before transferring ownership of any listed technology abroad, licensing it to foreign users, or passing control of its owner to a foreign entity.\n- **Exemptions:** Open-source code and published research are exempt, and Chinese firms can continue serving overseas users through apps, websites, and APIs. However, running a covered model on servers abroad counts as an export.\n- **Named models:** Press reports say Moonshot AI's Kimi K3 and Alibaba's Qwen3.8-Max reportedly meet the size threshold, though the official draft does not name specific models.\n\nCaveat: most of these sources are secondary news or commentary sites, and several describe the same draft with differing detail. I did not find a primary government text or a final rule, so check the Ministry of Commerce publication before relying on the thresholds."
  ],
  "durationSeconds": 7.4095173269999215,
  "searchCount": 1
}

{
  "url": "https://medicalxpress.com/news/2026-11-ai-patient-discharge-summaries.html",
  "prompt": "Date of article, journal and publication date of study, sample size, and all result numbers."
}

{
  "bytes": 193381,
  "code": 200,
  "codeText": "OK",
  "result": "**Article date:** November 2, 2026 (Medical Xpress/Science X; cited as retrieved November 3, 2026)\n\n**Journal:** *npj Digital Medicine* (2026)\n\n**Study publication date:** The article says the study was \"published online\" but doesn't give an exact date. It's only identified as 2026, per the DOI (10.1038/s41746-026-03320-y).\n\n**Sample size:** 60 internal medicine hospitalizations at Stony Brook University Hospital, each lasting 7 to 21 days.\n\n**Result numbers:**\n- Physician reviewers preferred the AI-generated summaries in 95% of the evaluated hospitalizations.\n- The article doesn't report the specific scores for quality, readability, accuracy, or completeness. It says only that the AI summaries scored higher. The table image shows these ratings, but its values aren't in the text.\n- The article doesn't give a count of missing clinical details or error numbers.\n- Both summary types contained errors, but the article reports no statistically significant difference in estimated severity or likelihood of harm.",
  "durationMs": 5140,
  "url": "https://medicalxpress.com/news/2026-11-ai-patient-discharge-summaries.html"
}

{
  "url": "https://mistral.ai/news",
  "prompt": "List all news items with titles and dates, newest first."
}

{
  "bytes": 1265788,
  "code": 200,
  "codeText": "OK",
  "result": "Here are the news items visible on the page, newest first. The page lists 93 results, but the content was truncated after \"Build, tweak, repeat\" and \"Large Enough\" (July 24, 2024), so older items are missing.\n\n- October 29, 2026: \"Le Chonk: Built for Coders, Trusted by Defenders.\"\n- October 21, 2026: \"Mistral Advances AI for Engineering with NVIDIA\"\n- October 20, 2026: \"Voxtral 3\"\n- October 15, 2026: \"Introducing Timestral\"\n- October 6, 2026: \"Introducing Mistral Large 4\"\n- September 28, 2026: \"Hallo, Deutschland!\"\n- September 16, 2026: \"Mistral and Mozilla are bringing open, private and multilingual AI to your web browser\"\n- September 10, 2026: \"Cloudera and Mistral Partner to Bring Specialized, Sovereign Intelligence to Enterprise Data\"\n- September 9, 2026: \"Modernizing complex legacy code with AI agents.\"\n- September 8, 2026: \"Mistral raises €3B to make sovereign, open-weight AI the technology frontier\"\n- August 24, 2026: \"Mistral x HUMAIN\"\n- August 20, 2026: \"Agentic Search. More accurate and efficient results from your AI systems.\"\n- August 11, 2026: \"In-region inference, open models, and new European infrastructure for sovereign AI.\"\n- August 4, 2026: \"Introducing Shieldstral.\"\n- July 9, 2026: \"Your Prompts and Skills need a system of record.\"\n- July 8, 2026: \"Introducing Robostral Navigate\"\n- July 2, 2026: \"Leanstral 1.5: Proof Abundance for All\"\n- June 24, 2026: \"Bringing more control over your connectors\"\n- June 23, 2026: \"Introducing Mistral OCR 4\"\n- May 28, 2026: \"AI Now Summit 2026\"\n- May 28, 2026: \"Vibe gets to work.\"\n- May 28, 2026: \"Introducing Search Toolkit\"\n- May 27, 2026: \"Introducing physics AI at Mistral: the foundation for engineering acceleration.\"\n- May 27, 2026: \"Physics AI research that's shaping the industry.\"\n- May 23, 2026: \"Emmi joins Mistral to accelerate the AI-native industry\"\n- May 22, 2026: \"Remote agents in Vibe. Powered by Mistral Medium 3.5.\"\n- May 22, 2026: \"Connect the dots: Build with built-in and custom MCPs in Studio\"\n- April 27, 2026: \"Workflows for work that runs the business\"\n- March 31, 2026: \"Spaces: A CLI Built for Humans and Agents\"\n- March 23, 2026: \"Speaking of Voxtral\"\n- March 17, 2026: \"Introducing Forge\"\n- March 16, 2026: \"Introducing Mistral Small 4\"\n- March 16, 2026: \"Mistral partners with NVIDIA to accelerate open frontier models\"\n- March 16, 2026: \"Leanstral: Open-Source foundation for trustworthy vibe-coding\"\n- March 11, 2026: \"Rails testing on autopilot: Building an agent that writes what developers won't\"\n- February 4, 2026: \"Voxtral transcribes at the speed of sound.\"\n- January 27, 2026: \"Terminally online Mistral Vibe.\"\n- January 21, 2026: \"Heaps do lie: debugging a memory leak in vLLM.\"\n- December 17, 2025: \"Introducing Mistral OCR 3\"\n- December 9, 2025: \"Introducing: Devstral 2 and Mistral Vibe CLI.\"\n- December 2, 2025: \"Introducing Mistral 3\"\n- November 19, 2025: \"Mistral - KI für Deutschland\"\n- October 24, 2025: \"Introducing Mistral Studio.\"\n- September 9, 2025: \"Mistral raises 1.7B€ to accelerate technological progress with AI\"\n- September 2, 2025: \"Make Memory work for you.\"\n- September 2, 2025: \"Le Chat. Custom MCP connectors. Memories.\"\n- August 1, 2025: \"Unlocking the potential of vision language models on satellite imagery through fine-tuning\"\n- July 30, 2025: \"Announcing Codestral 25.08 and the Complete Mistral Coding Stack for Enterprise\"\n- July 22, 2025: \"Our contribution to a global environmental standard for AI\"\n- July 17, 2025: \"Le Chat dives deep.\"\n- July 15, 2025: \"Voxtral\"\n- July 10, 2025: \"Upgrading agentic coding capabilities with the new Devstral models\"\n- July 3, 2025: \"Announcing AI for Citizens\"\n- June 11, 2025: \"Mistral Compute\"\n- June 10, 2025: \"Magistral\"\n- June 4, 2025: \"Introducing Mistral Code\"\n- May 28, 2025: \"Codestral Embed\"\n- May 27, 2025: \"Build AI agents with the Mistral Agents API\"\n- May 21, 2025: \"Devstral\"\n- May 7, 2025: \"Introducing Le Chat Enterprise\"\n- May 7, 2025: \"Medium is the new large.\"\n- April 9, 2025: \"Evaluating RAG with LLM as a Judge\"\n- March 17, 2025: \"Mistral Small 3.1\"\n- March 6, 2025: \"Mistral OCR\"\n- March 4, 2025: \"Empowering product development with an agentic workflow\"\n- February 17, 2025: \"Mistral Saba\"\n- February 6, 2025: \"The all new le Chat: Your AI assistant for life and work\"\n- January 30, 2025: \"Mistral Small 3\"\n- January 16, 2025: \"Purr-fectly informed\"\n- January 13, 2025: \"Codestral 25.01\"\n- November 18, 2024: \"Mistral has entered the chat\"\n- November 18, 2024: \"Pixtral Large\"\n- November 7, 2024: \"Mistral Batch API\"\n- November 7, 2024: \"Mistral Moderation API\"\n- October 16, 2024: \"Un Ministral, des Ministraux\"\n- September 17, 2024: \"AI in abundance\"\n- September 17, 2024: \"Announcing Pixtral 12B\"\n- August 7, 2024: \"Build, tweak, repeat\"\n- July 24, 2024: \"Large Enough\"",
  "durationMs": 14914,
  "url": "https://mistral.ai/news"
}

{
  "command": "echo \"=== BD ===\" && node scripts/fetch.js \"https://breakingdefense.com/\" 2>&1 | head -60",
  "description": "Fetch Breaking Defense homepage"
}

{
  "stdout": "=== BD ===\nHTTP 200 · https://breakingdefense.com/ · text/html\nBreaking Defense - Defense technology, policy and national security news\n\n# Breaking Defense\n\nAir Warfare\n\n#\n\nSweden’s Saab launches family of AI agents for future aircraft projects\n\nBy Tim Martin\n\nLand Warfare\n\n#\n\nIndustry needs more consistent demand signal to scale UGV production: Autonomy consortium exec\n\n“I think [industry has] the challenge of understanding what the demand signal is, and then again where to put their dollars,\" Warren Sponsler, the COO of NAMC, said in an interview.\n\nBy Carley Welch\n\nGlobal,\n\nPentagon\n\n#\n\nThe fiscal risks of bringing US troops out of Europe\n\nReducing America’s military footprint in Europe may seem fiscally prudent, but relocating troops and giving up overseas bases could leave US taxpayers with a much bigger bill.\n\nBy John R. Deni\n\nNaval Warfare\n\n#\n\nSaab unveils new speed assault boat for Swedish Navy\n\n\"The CB90CX is designed for uncrewed operations from the outset,\" Anders Hellman, head of Saab’s business unit in Docksta, told Breaking Defense.\n\nBy Elisabeth Gosselin-Malo\n\nFEATURED\n\nspooooooky\n\n#\n\nA special Halloween edition of The Break Out\n\nExclusive interview\n\n#\n\nPentagon will pick new US base location by June 2027\n\nNaval Challenges",
  "stderr": "",
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{
  "command": "node scripts/fetch.js \"https://www.nature.com/articles/s41746-026-02193-x\" 2>&1 | head -c 200; echo \"---\"; cd /home/user/ainews && node scripts/fetch.js \"https://www.nature.com/npjdigitalmed/articles?searchType=journalSearch&sort=PubDate&page=1\" 2>&1 | grep -n \"Nov 2026\" | head -20",
  "description": "Probe npj Digital Medicine article pages"
}

{"stdout":"HTTP 404 · https://www.nature.com/articles/s41746-026-02193-x?error=cookies_not_supported&code=faff3a94-38d1-4d87-a7e1-3396ffb4b8bf · text/html\nPage Not Found | nature.com\n\nSkip to main content\n\nTha---\n35:Comment Open Access 03 Nov 2026\n48:Article Open Access 03 Nov 2026\n61:Article Open Access 03 Nov 2026","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":431,"oldLines":3,"newStart":431,"newLines":6,"lines":[" {\"t\":\"2026-11-03T11:16:25.834Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"a7d5674a33c6d710e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_0118H1Y7RpT7PrVQPN6oyVUa\",\"duration_ms\":7410,\"input\":{\"query\":\"China AI export control registration rule took effect large language models chip designs November 2026\",\"mode\":\"extended\"},\"response\":{\"query\":\"China AI export control registration rule took effect large language models chip designs November 2026\",\"results\":[{\"tool_use_id\":\"srvtoolu_01JNRaBuuB7nL3UTn8P1UcJS\",\"content\":[{\"title\":\"China proposes export controls on its advanced AI models and chip designs\",\"url\":\"https://thenextweb.com/news/china-ai-export-controls-draft\"},{\"title\":\"China proposes export controls on its advanced AI models and chip designs\",\"url\":\"https://daily.dev/posts/china-proposes-export-controls-on-its-advanced-ai-models-and-chip-designs-0yanh2zcb\"},{\"title\":\"China Proposes AI Export Controls on Models and Chips\",\"url\":\"https://emergent.sh/news/china-proposes-ai-export-controls-models\"},{\"title\":\"Whack-a-Chip: The Futility of Hardware-Centric Export Controls\",\"url\":\"https://arxiv.org/pdf/2411.14425\"},{\"title\":\"China wants to control exports of any AI model over 2 trillion parameters\",\"url\":\"https://madrobot.blog/2026/10/16/china-ai-export-controls-23-technologies-large-models-agents/\"},{\"title\":\"China Proposes AI Export Curbs on 23 Technologies [2026]\",\"url\":\"https://tech-insider.org/china-ai-export-curbs-23-technologies-2026/\"},{\"title\":\"China drafts export controls on AI model weights and chip designs\",\"url\":\"https://www.thefrontier.dev/articles/china-ai-export-controls\"},{\"title\":\"China AI export controls draft: 23 technologies, 2T models\",\"url\":\"https://techaiwire.com/articles/china-ai-export-controls-draft-23-technologies-2-trillion-parameters/\"},{\"title\":\"What the China AI Export Controls Draft Actually Says\",\"url\":\"https://shattered.io/what-the-china-ai-export-controls-draft-actually-says/\"}]},\"The search points to October 16, 2026, not November, as the date the temporary registration rule took effect.\\n\\n- **Timing:** A temporary pre-export registration requirement took effect on October 16, 2026. The draft's comments due 15 November, so the broader list is still under consultation.\\n- **Scope of the draft:** Ministries proposed adding 23 AI technologies, including large models, agents, chip designs, and computing clusters, to the country's export control list. For large models, the curbs would cover weights, source code, and other core parts. The size threshold is models with at least 2 trillion parameters, or that rank in the world's top 10 on benchmarks such as performance and safety.\\n- **Chips:** The draft would limit design know-how for AI chips manufactured at 14 nanometres or below, as well as chips built using 2.5D or 3D stacking techniques, along with certain memory chip designs.\\n- **Registration:** Firms must register before exporting listed items, including incomplete deals. Per one source, companies must register on the commerce ministry's platform before transferring ownership of any listed technology abroad, licensing it to foreign users, or passing control of its owner to a foreign entity.\\n- **Exemptions:** Open-source code and published research are exempt, and Chinese firms can continue serving overseas users through apps, websites, and APIs. However, running a covered model on servers abroad counts as an export.\\n- **Named models:** Press reports say Moonshot AI's Kimi K3 and Alibaba's Qwen3.8-Max reportedly meet the size threshold, though the official draft does not name specific models.\\n\\nCaveat: most of these sources are secondary news or commentary sites, and several describe the same draft with differing detail. I did not find a primary government text or a final rule, so check the Ministry of Commerce publication before relying on the thresholds.\"],\"durationSeconds\":7.4095173269999215,\"searchCount\":1}}"," {\"t\":\"2026-11-03T11:16:27.793Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01WSd1ZYdRXiQxXgBZkad1oK\",\"duration_ms\":457,\"input\":{\"command\":\"node scripts/fetch.js \\\"https://siliconangle.com/2026/11/02/robotics-startup-tutor-intelligence-nabs-75m-investment/\\\" 2>&1 | head -c 2400\",\"description\":\"Tutor Intelligence funding\"},\"response\":{\"stdout\":\"HTTP 200 · https://siliconangle.com/2026/11/02/robotics-startup-tutor-intelligence-nabs-75m-investment/ · text/html\\nRobotics startup Tutor Intelligence nabs $75M investment - SiliconANGLE\\n\\nSkip to content\\n\\nSHARE\\n-\\n\\n-\\n\\n-\\n\\n-\\n\\n-\\n\\n-\\n\\n-\\n\\
… [10069 more characters in events.jsonl]

{
  "url": "https://www.infosecurity-magazine.com/news/",
  "prompt": "List news items dated 2 or 3 November 2026 with headlines and URLs; flag AI-related ones."
}

{
  "bytes": 109241,
  "code": 200,
  "codeText": "OK",
  "result": "**2 November 2026**\n\n1. \"Armadin Tests Find 88% of Severe Flaws Outside Vendor Advisories\": https://www.infosecurity-magazine.com/news/armadin-severe-exposures-missed/\n2. \"Bitter Deploys PapRAT in Asian Cyber-Espionage Campaign\": https://www.infosecurity-magazine.com/news/paprat-bitter-cyberespionage/\n3. \"FBI Attributes Binance Heist to North Korea's TraderTraitor\": https://www.infosecurity-magazine.com/news/fbi-attributes-binance-north/\n4. \"Chainalysis Warns Customers After \"Offensive Agentic\" Security Incident\": https://www.infosecurity-magazine.com/news/chainalysis-customers-offensive/ **(AI-related)**. The summary describes an AI-driven attack that led to unauthorized activity.\n\n**3 November 2026**\n\n1. \"LLMJacking is Costing Some Businesses Up to $1m, Warns Google\": https://www.infosecurity-magazine.com/news/llmjacking-cost-business-1m-warns/ **(AI-related)**. Google Mandiant warns about the expense of hijacked access to large language models.\n2. \"Police and Tech Firms Team Up to Dismantle XCPE Botnet\": https://www.infosecurity-magazine.com/news/police-tech-firms-team-up-to/",
  "durationMs": 6603,
  "url": "https://www.infosecurity-magazine.com/news/"
}

{
  "query": "Nvidia cloud customers China restriction majority non-Chinese customers FT November 3 2026",
  "mode": "extended"
}

{
  "query": "Nvidia cloud customers China restriction majority non-Chinese customers FT November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01M9hhekDAd3dBN3rH2UQmSo",
      "content": [
        {
          "title": "Nvidia Tightens the Screws on China's AI Access — Cloud Partners Worldwide Must Restrict Chinese Customer - Benzinga",
          "url": "https://www.benzinga.com/markets/tech/26/11/62808888/nvidia-tightens-the-screws-on-chinas-ai-access-cloud-partners-worldwide-must-restrict-chinese-customers-under-new-revenue-rule-report"
        },
        {
          "title": "Nvidia Requires Cloud Clients to Limit Business With Chinese Customers",
          "url": "https://www.marketscreener.com/news/nvidia-requires-cloud-clients-to-limit-business-with-chinese-customers-ce785fd9de81ff21"
        },
        {
          "title": "Nvidia imposes strict requirements on cloud providers - Techzine Global",
          "url": "https://www.techzine.eu/news/infrastructure/145501/nvidia-imposes-strict-requirements-on-cloud-providers/"
        },
        {
          "title": "Nvidia tells data center partners to limit China sales- FT By Investing.com",
          "url": "https://www.investing.com/news/stock-market-news/nvidia-tells-data-center-partners-to-limit-china-sales-ft-4993618"
        },
        {
          "title": "Nvidia Sets 51% Non-China Customer Threshold for Cloud Partners",
          "url": "https://www.tokenpost.com/news/business/47474"
        },
        {
          "title": "Nvidia China Curbs Hit Cloud Clients With a 51% Rule",
          "url": "https://shiftdelete.net/en/nvidia-china"
        },
        {
          "title": "NVIDIA CORP - Form ARS - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001045810/000104581026000038/a2026-annualxreportxwebxfi.pdf"
        },
        {
          "title": "NVIDIA CORP - Form ARS - FY2025",
          "url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581025000098/finalforfiling-2025xannual.pdf"
        },
        {
          "title": "NVIDIA CORP - Form 10-Q - FY2023",
          "url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581023000093/nvda-20230430.htm"
        }
      ]
    },
    "The Financial Times reported on Tuesday that Nvidia now requires cloud partners to earn at least half their revenue from non-Chinese customers. Several outlets carried the story, but details vary.\n\n- **The rule:** Multiple reports say the threshold is 51%. One report describes it as applying to future business, with existing lease agreements exempt. Sales teams have conveyed it verbally since summer, and no written terms have been issued.\n- **Scope:** Nvidia told partners in recent months, according to five insiders. Previously, the chipmaker did not impose any requirements regarding the origin of providers' customers.\n- **Open questions:** The reports did not say whether the share is measured by revenue, computing capacity or number of customers, or how Nvidia defines a Chinese company.\n- **Impact:** A Singapore-based provider told the FT that it is hard to find enough non-Chinese customers outside the US. Southeast Asia is most exposed, since Chinese technology companies are major buyers of AI capacity there.\n- **Nvidia's response:** In a statement, Nvidia argued that data centers and cloud services built on American chips are the foundation US AI developers need to compete globally.\n\nI could not find the FT article itself, so these details come from secondary coverage."
  ],
  "durationSeconds": 5.7132490189999805,
  "searchCount": 1
}

{
  "command": "echo \"=== TOMS CLAUDE ===\"; node scripts/fetch.js \"https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks\" 2>&1 | head -50",
  "description": "Fetch Tom's Hardware Claude game cloning article"
}

{
  "stdout": "=== TOMS CLAUDE ===\nHTTP 200 · https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks · text/html\nAnthropic confirms new Claude Code limits to prevent game cloning — users report Opus 5.5 is also actively blocking reverse engineering tasks | Tom's Hardware\n\nSkip to main content\n\nJoin Tom’s Hardware today\n\nUpgrade to Tom’s Hardware Premium\n\nExplore\n\nGO PREMIUM\n\nChoose how you want to join Tom’s Hardware\n\nMEMBER\n\nGet started with free access to reviews, badges and discussions.\n\nBecome a member\n\nPremium member\n\nUnlock exclusive tools and insights for enthusiasts who want more.\n\nBench Database\n\nExclusive Features\n\nRoadmaps\n\nDeep Analysis\n\nBecome a premium member\n\nGo beyond the headlines with Tom’s Hardware Premium\n\nAccess Bench, Roadmaps, deep analysis and other exclusive tools.\n\nExplore PREMIUM\n\nBench Performance Database\n\nDive into our proprietary testing data and compare hardware with detailed benchmarks.\n\nDeep-Dive Analysis\n\nGo beyond the headlines with expert reporting on the hardware industry.\n\nHardware Roadmaps",
  "stderr": "",
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  "isImage": false,
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}

{
  "command": "node scripts/fetch.js \"https://www.nature.com/articles/s41746-026-03320-y\" 2>&1 | head -c 3000",
  "description": "Fetch npj Digital Medicine discharge summary paper"
}

{"stdout":"HTTP 200 · https://www.nature.com/articles/s41746-026-03320-y?error=cookies_not_supported&code=0fc92ac9-2f4a-4e8d-b8aa-4355a10e7f95 · text/html\nClinician-centered evaluation of large language model-generated discharge summaries for longer hospitalizations | npj Digital Medicine\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\nClinician-centered evaluation of large language model-generated discharge summaries for longer hospitalizations\n\nDownload PDF\n\nDownload PDF\n\n# Abstract\nAlthough large language models (LLMs) have shown promise for discharge summary generation, their performance in longer hospitalizations remains less well studied. Prior evaluations of LLM-generated discharge summaries have largely involved shorter stays and have rarely examined receiving-clinician priorities or incidental finding reporting. We compared LLM-generated and human-authored discharge summaries for 60 Internal Medicine hospitalizations lasting 7 to 21 days, with paired assessment by hospitalists and primary care physicians (PCPs). Clinician reviewers preferred LLM-generated summaries for 95% of encounters and rated them higher for quality, readability, factuality and completeness. PCPs rated LLM-generated summaries as better for understanding and communicating hospital care to patients and providing follow-up care. LLM-generated summaries had fewer clinician-reviewer annotations of either factual inaccuracies or clinically relevant omissions, primarily due to fewer omissions, with no significant differences in estimated harm potential or likelihood compared with human-authored summaries. PCPs annotated more omissions and assigned higher likelihood of harm than hospitalists. Among 31 LLM-identified radiology incidental findings, 93.5% were rated factually correct and 87.1% appropriate for reporting. In this retrospective clinician evaluation, LLM-generated summaries for longer, complex hospitalizations were rated more favorably and had fewer annotated omissions than human-authored summaries, with no significant differences in estimated harm potential or likelihood.\n\n# Similar content being viewed by others\n\n#\nAutomated generation of discharge summaries: leveraging large language models with clinical data\n\nArticle\nOpen access\n12 May 2025\n\n#\nDevelopment and evaluation of a clinical note summarization system using large language models\n\nArticle\nOpen access\n28 August 2025\n\n#\nEvaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations\n\nArticle\nOpen access\n29 May 2025\n\n# Explore related subjects\n\nDiscover the latest articles and news in related subjects.\n\n-\n\nDiseases\n\n-\n\nHealth care\n\n-\n\nMedical research\n\n-","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":437,"oldLines":3,"newStart":437,"newLines":5,"lines":[" {\"t\":\"2026-11-03T11:16:33.709Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"ab6226e3bcc8a2cc4\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"Bash\",\"tool_use_id\":\"toolu_01HpQbgS4BKZj63BjozrUwSM\",\"duration_ms\":2490,\"input\":{\"command\":\"node scripts/fetch.js \\\"https://www.nature.com/articles/s41746-026-02193-x\\\" 2>&1 | head -c 200; echo \\\"---\\\"; cd /home/user/ainews && node scripts/fetch.js \\\"https://www.nature.com/npjdigitalmed/articles?searchType=journalSearch&sort=PubDate&page=1\\\" 2>&1 | grep -n \\\"Nov 2026\\\" | head -20\",\"description\":\"Probe npj Digital Medicine article pages\"},\"response\":{\"truncated\":true,\"length\":31481,\"head\":\"{\\\"stdout\\\":\\\"HTTP 404 · https://www.nature.com/articles/s41746-026-02193-x?error=cookies_not_supported&code=faff3a94-38d1-4d87-a7e1-3396ffb4b8bf · text/html\\\\nPage Not Found | nature.com\\\\n\\\\nSkip to main content\\\\n\\\\nTha---\\\\n35:Comment Open Access 03 Nov 2026\\\\n48:Article Open Access 03 Nov 2026\\\\n61:Article Open Access 03 Nov 2026\\\",\\\"stderr\\\":\\\"\\\",\\\"interrupted\\\":false,\\\"isImage\\\":false,\\\"noOutputExpected\\\":false,\\\"bashEditDiff\\\":{\\\"files\\\":[{\\\"filePath\\\":\\\"/home/user/ainews/trace/2026-11-03.jsonl\\\",\\\"hunks\\\":[{\\\"oldStart\\\":431,\\\"oldLines\\\":3,\\\"newStart\\\":431,\\\"newLines\\\":6,\\\"lines\\\":[\\\" {\\\\\\\"t\\\\\\\":\\\\\\\"2026-11-03T11:16:25.834Z\\\\\\\",\\\\\\\"event\\\\\\\":\\\\\\\"PostToolUse\\\\\\\",\\\\\\\"session_id\\\\\\\":\\\\\\\"c0ba620c-ead7-5889-a588-1d740c20a25e\\\\\\\",\\\\\\\"cwd\\\\\\\":\\\\\\\"/home/user/ainews\\\\\\\",\\\\\\\"scratchpad_dir\\\\\\\":\\\\\\\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\\\\\\\",\\\\\\\"prompt_id\\\\\\\":\\\\\\\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\\\\\\\",\\\\\\\"permission_mode\\\\\\\":\\\\\\\"auto\\\\\\\",\\\\\\\"agent_id\\\\\\\":\\\\\\\"a7d5674a33c6d710e\\\\\\\",\\\\\\\"agent_type\\\\\\\":\\\\\\\"general-purpose\\\\\\\",\\\\\\\"effort\\\\\\\":{\\\\\\\"level\\\\\\\":\\\\\\\"high\\\\\\\"},\\\\\\\"hook_event_name\\\\\\\":\\\\\\\"PostToolUse\\\\\\\",\\\\\\\"tool_name\\\\\\\":\\\\\\\"WebSearch\\\\\\\",\\\\\\\"tool_use_id\\\\\\\":\\\\\\\"toolu_0118H1Y7RpT7PrVQPN6oyVUa\\\\\\\",\\\\\\\"duration_ms\\\\\\\":7410,\\\\\\\"input\\\\\\\":{\\\\\\\"query\\\\\\\":\\\\\\\"China AI export control regist
… [10069 more characters in events.jsonl]

{
  "command": "node scripts/fetch.js \"https://www.nature.com/npjdigitalmed/articles\" 2>&1 | sed -n '1,80p'",
  "description": "Get npj Digital Medicine listing top entries with links"
}

{"stdout":"HTTP 200 · https://www.nature.com/npjdigitalmed/articles?error=cookies_not_supported&code=4578abaf-d63b-4f36-acc2-b247297124d1 · text/html\nBrowse Articles\n| npj Digital Medicine\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\n# Browse Articles\n\n# Filter By:\n\nArticle Type\n\nAll\n\nYear\n\nAll\n\n-\n\n#\nThe TEMPO program and the future of digital mental health regulation in the US\n\nThe high burden of traditional FDA clearance drives many novel, AI-enabled mental health devices into unregulated consumer markets. The new FDA-CMS TEMPO pilot program establishes a vital regulatory middle ground, allowing companies to commercialize using a Quality Management System without immediate premarket authorization. This commentary explores how TEMPO serves as a sandbox for real-world data, offering a blueprint to reshape the future of US digital health regulation.\n\n- Acacia C. Parks\n\n- Aubrey Shick\n\nComment Open Access 03 Nov 2026\n\n-\n\n#\nCost-effectiveness analysis of digital medicine support models for alcohol use disorder\n\n- Xiang Li\n\n- Ming-Yuan Chih\n\n- Andrew Quanbeck\n\nArticle Open Access 03 Nov 2026\n\n-\n\n#\nPredicting different dimensions of fatigue from speech data: a longitudinal study in shift workers\n\n- Agnes Norbury\n\n- Alexandra Livia Georgescu\n\n- Nicholas Cummins\n\nArticle Open Access 03 Nov 2026\n\n-\n\n#\nGeneration of synthetic clinical text: a systematic review\n\n- Basel Alshaikhdeeb\n\n- Anne Lorant\n\n- Venkata Satagopam\n\nArticle Open Access 31 Oct 2026\n\n-\n\n#\nUnderstanding clinical reasoning variability in medical large language models: a mechanistic interpretability study","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false,"bashEditDiff":{"files":[{"filePath":"/home/user/ainews/trace/2026-11-03.jsonl","hunks":[{"oldStart":440,"oldLines":3,"newStart":440,"newLines":4,"lines":[" {\"t\":\"2026-11-03T11:16:41.349Z\",\"event\":\"PostToolUse\",\"session_id\":\"c0ba620c-ead7-5889-a588-1d740c20a25e\",\"cwd\":\"/home/user/ainews\",\"scratchpad_dir\":\"/tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad\",\"prompt_id\":\"b5e1f80a-dc11-4c69-9cb2-ee02ec43428b\",\"permission_mode\":\"auto\",\"agent_id\":\"afb0755d99de3a80e\",\"agent_type\":\"general-purpose\",\"effort\":{\"level\":\"high\"},\"hook_event_name\":\"PostToolUse\",\"tool_name\":\"WebSearch\",\"tool_use_id\":\"toolu_01GEq5NVx4fD4BimUXXUjpDz\",\"duration_ms\":5714,\"input\":{\"query\":\"Nvidia cloud customers China restriction majority non-Chinese customers FT November 3 2026\",\"mode\":\"extended\"},\"response\":{\"query\":\"Nvidia cloud customers China restriction majority non-Chinese customers FT November 3 2026\",\"results\":[{\"tool_use_id\":\"srvtoolu_01M9hhekDAd3dBN3rH2UQmSo\",\"content\":[{\"title\":\"Nvidia Tightens the Screws on China's AI Access — Cloud Partners Worldwide Must Restrict Chinese Customer - Benzinga\",\"url\":\"https://www.benzinga.com/markets/tech/26/11/62808888/nvidia-tightens-the-screws-on-chinas-ai-access-cloud-partners-worldwide-must-restrict-chinese-customers-under-new-revenue-rule-report\"},{\"title\":\"Nvidia Requires Cloud Clients to Limit Business With Chinese Customers\",\"url\":\"https://www.marketscreener.com/news/nvidia-requires-cloud-clients-to-limit-business-with-chinese-customers-ce785fd9de81ff21\"},{\"title\":\"Nvidia imposes strict requirements on cloud providers - Techzine Global\",\"url\":\"https://www.techzine.eu/news/infrastructure/145501/nvidia-imposes-strict-requirements-on-cloud-providers/\"},{\"title\":\"Nvidia tells data center partners to limit China sales- FT By Investing.com\",\"url\":\"https://www.investing.com/news/stock-market-news/nvidia-tells-data-center-partners-to-limit-china-sales-ft-4993618\"},{\"title\":\"Nvidia Sets 51% Non-China Customer Threshold for Cloud Partners\",\"url\":\"https://www.tokenpost.com/news/business/47474\"},{\"title\":\"Nvidia China Curbs Hit Cloud Clients With a 51% Rule\",\"url\":\"https://shiftdelete.net/en/nvidia-china\"},{\"title\":\"NVIDIA CORP - Form ARS - FY2026\",\"url\":\"https://www.sec.gov/Archives/edgar/data/0001045810/000104581026000038/a2026-annualxreportxwebxfi.pdf\"},{\"title\":\"NVIDIA CORP - Form ARS - FY2025\",\"url\":\"https://www.sec.gov/Archives/edgar/data/1045810/000104581025000098/finalforfiling-2025xannual.pdf\"},{\"title\":\"NVIDIA CORP - Form 10-Q - FY2023\",\"url\":\"https://www.sec.gov/Archives/edgar/data/1045810/000104581023000093/nvda-20230430.htm\"}]},\"The Financial Times reported on Tuesday that Nvidia now requires cloud partners to earn at least half their revenue from non-Chinese customers. Several outlets carried the story, but details vary.\\n\\n- **The rule:** Multiple reports say the threshold is 51%. One report describes it as applying to future business, with existing lease agreements exempt. Sales teams have conveyed it verbally since summer, and no written terms have been issued.\\n- **Scope:** Nvidia told partners in recent months, according to five insiders. Previously, the chipmaker did not impose any requirements regarding the origin of providers' customers.\\n- **Open questions:** The reports did not say whether the share is measured by revenue, computing capacity or number of customers, or how Nvidia defines a Chinese company.\\n- **Impact:** A Singapore-based provider told the FT that it is hard to find enough non-Chinese customers outside the US. Southeast Asia is most exposed, since Chinese technology companies are major buyers of AI capacity there.\\n- **Nvidia's response:** In a statement, Nvidia argued that data centers and cloud services built on American chips are the foundati
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{"stdout":"148:Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\n164:npj Digit. Med. 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  "url": "https://www.techzine.eu/news/infrastructure/145501/nvidia-imposes-strict-requirements-on-cloud-providers/",
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  "result": "**Publication date:** November 3, 2026, 10:00 am. The article is by Mels Dees on Techzine Global.\n\n**Original reporting:** The Financial Times reported the story, and Techzine cites it.\n\n**Figures:**\n- Cloud providers using Nvidia's AI chips must sell at least 51 percent of their services to non-Chinese customers.\n- Five insiders were the sources for the requirement.\n- Two of those sources said the requirement applies to Nvidia customers worldwide, not only to Asian data centers.\n- The requirement applies only to future contracts, not existing lease agreements.\n- A rack of B300 chips costs about $600,000 on the international market. An insider said one was recently sold in China for the equivalent of $2.8 million.\n\n**Quotes:**\n- A Singapore-based group, quoted in the Financial Times, said: \"it is difficult to find enough non-Chinese customers outside the U.S.\"\n\n**Nvidia's statement:** The article includes no official statement or comment from Nvidia. According to the sources, Nvidia communicated the requirement verbally through its sales and regional teams rather than in writing.",
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  "query": "Saab press release AI Fighter Pilot Academy agents Gripen November 3 2026",
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{
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          "title": "Saab, Helsing let Gripen fighter fly with AI in charge",
          "url": "https://www.yahoo.com/news/saab-helsing-let-gripen-fighter-130124828.html"
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          "title": "har strider saabs ai pilot vi suddar ut granserna",
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        {
          "title": "Training to be a Gripen Pilot",
          "url": "https://saab.com/markets/india/gripen-for-india/technology/training-to-be-a-gripen-pilot"
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          "url": "https://backend.ainonline.com/sites/default/files/article_export/rtf/Gripen_Academy_To_Open_In_South_Africa-05-08-2026.rtf"
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          "url": "https://se.linkedin.com/in/daniel-boestad"
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          "title": "Connect with us",
          "url": "https://nationalsecurityjournal.org/?p=31285"
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          "title": "saab to open gripen fighter weapon school in south africa",
          "url": "https://www.saairforce.co.za/news-and-events/1122/saab-to-open-gripen-fighter-weapon-school-in-south-africa"
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          "title": "gripen expands links with etps",
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          "title": "saab to invest in gripen fighter weapon school in south africa 43670",
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        },
        {
          "title": "Saab and Helsing hail world-first as Gripen E aircraft flies with ‘Centaur’ AI agent",
          "url": "https://www.shephardmedia.com/news/air-warfare/saab-and-helsing-hail-world-first-as-gripen-e-flies-with-centaur-ai-agent"
        },
        {
          "title": "Tuesday, June 09, 2026 | 02:39 AM ISTहिंदी में पढें",
          "url": "https://www.business-standard.com/world-news/saab-helsing-ai-system-pilot-fighter-jet-gripen-e-warplane-125061200508_1.html"
        },
        {
          "title": "AI Agent To Assist Gripen Pilots In BVR Combat",
          "url": "https://aviationweek.com/defense/aircraft-propulsion/ai-agent-assist-gripen-pilots-bvr-combat"
        },
        {
          "title": "saab to invest in gripen fighter weapon school in south africa",
          "url": "https://www.saab.com/newsroom/press-releases/2012/saab-to-invest-in-gripen-fighter-weapon-school-in-south-africa"
        },
        {
          "title": "gripen academy open south africa",
          "url": "https://backend.ainonline.com/aviation-news/defense/2012-07-10/gripen-academy-open-south-africa"
        }
      ]
    },
    "I couldn't find a Saab press release about an \"AI Fighter Pilot Academy\" dated November 3, 2026, or anything else matching that description. The results cover earlier Saab AI work and older Gripen training initiatives.\n\n- **Centaur AI flight tests (2025):** Saab and Helsing flew an AI agent in a Gripen E. Saab and Helsing completed three successful test flights of the Gripen E fighter controlled by Helsing's AI agent Centaur between May 28 and June 3, 2025, over the Baltic Sea. A safety pilot was onboard. The Saab announcement is dated STOCKHOLM, June 11, 2025 /PRNewswire/.\n- **Simulator training:** One LinkedIn post describes Saab taking a new approach to Gripen E simulator training by introducing AI-augmented, personalised learning. It is a secondary source, so I'd verify it against Saab's newsroom.\n- **Pilot training:** Saab's existing Gripen Training Academy uses the infrastructures and simulator tools of the Swedish Air Force F7 Wing in Satenas. This is a general description, not a new announcement.\n- **Older academy news:** Saab's Gripen Fighter Weapon School in South Africa dates to 2012 and is unrelated to AI.\n\nI'd suggest checking Saab's newsroom (saab.com/newsroom) directly for a November 2026 release. The search index may not have it yet."
  ],
  "durationSeconds": 6.353968689000001,
  "searchCount": 1
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{
  "url": "https://breakingdefense.com/2026/11/swedens-saab-launches-family-of-ai-agents-for-future-aircraft-projects/",
  "prompt": "Publication date, named agents, quotes with names/titles, numbers, Saab press release reference."
}

{
  "bytes": 122959,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 3, 2026 (Breaking Defense, by Tim Martin, datelined Belfast).\n\n**Named agents:** The article doesn't name the individual AI agents. It describes them as a suite of in-house agents for future aircraft platforms. Related named items include Saab's AI Fighter Jet Pilot Academy, which develops the agents, and Sferical AI, a Swedish government-backed computing initiative that Saab partly founded. Helsing's Centaur AI tool was used in a 2025 Gripen test, not in this program.\n\n**Quotes with names and titles:**\n- Peter Nilsson, head of Advanced Programs at Saab's aeronautics unit, said: \"The harder question is how we turn this success\" into a dependable capability.\n- Nilsson also said the Academy's purpose is the \"true purpose of the AI Fighter Pilot Academy,\" meaning sustained learning and improvement of the capability.\n\n**Numbers:**\n- The agents were tested on a Gripen E multirole fighter.\n- Sferical AI is built on Nvidia's DGX SuperPOD architecture.\n- According to Nilsson, a one-hour simulated training flight can produce the equivalent of one billion flight hours for a human pilot.\n- Saab is developing three unmanned aircraft, the A1, A2 and A3, on the path to a new loyal wingman drone.\n- The 2025 Helsing-linked test campaign is the earlier reference point.\n- Sferical AI was inaugurated in Stockholm in October 2026.\n\n**Saab press release:** The article cites a \"company statement released today,\" so the release is dated November 3, 2026. The article doesn't give the release's title, reference number, or link.",
  "durationMs": 8760,
  "url": "https://breakingdefense.com/2026/11/swedens-saab-launches-family-of-ai-agents-for-future-aircraft-projects/"
}

{
  "query": "\"Predicting different dimensions of fatigue from speech data\" shift workers npj Digital Medicine",
  "mode": "standard"
}

{
  "query": "\"Predicting different dimensions of fatigue from speech data\" shift workers npj Digital Medicine",
  "results": [
    {
      "tool_use_id": "srvtoolu_017xdyvULF4u7fQr9C8CxE51",
      "content": [
        {
          "title": "Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers",
          "url": "https://www.medrxiv.org/content/10.1101/2024.06.17.24308769.full.pdf"
        },
        {
          "title": "A rapid, non-invasive method for fatigue detection based on voice information",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9513181/"
        },
        {
          "title": "Real-time assessment of worker fatigue using learning-based model",
          "url": "https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/12555051"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/html/2505.23378v1"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/html/2505.23378v2"
        },
        {
          "title": "arxiv.org",
          "url": "https://arxiv.org/pdf/2505.23378v1"
        },
        {
          "title": "Agnes Norbury",
          "url": "https://www.bohrium.com/scholar/09d10400/Agnes_Norbury"
        },
        {
          "title": "Predicting fatigue and psychophysiological test performance from speech for safety-critical environments",
          "url": "https://www.frontiersin.org/articles/10.3389/fbioe.2015.00124"
        },
        {
          "title": "A rapid, non-invasive method for fatigue detection based on voice information",
          "url": "https://dx.doi.org/10.3389/fcell.2022.994001"
        },
        {
          "title": "[image: image1]A rapid, non-invasive method for fatigue detection based on voice information",
          "url": "https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.994001/epub"
        }
      ]
    },
    "The search didn't turn up the npj Digital Medicine version. It found a medRxiv preprint with the same title, \"Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers,\" so the journal publication may exist but wasn't confirmed here.\n\n- **Study design:** The preprint describes a large, multilingual cohort tracked during ordinary working lives, with the aim of testing how well different aspects of fatigue can be detected from speech. It examines to what extent different aspects of fatigue, from acute sleep deprivation state to chronic motivational difficulties, may be detectable in speech data.\n- **Scale and method:** An abstract version reports twice-daily measurement over two weeks in N=1,197 individuals from six different countries. Paralinguistic speech features were used to predict different aspects of acute and chronic fatigue at each study time-point, with performance assessed in unseen (held-out) data.\n- **Conclusions:** The authors describe the findings as preliminary support for the utility of using brief momentary speech samples as a low-burden, acceptable, and reliable measure of different aspects of fatigue in high-risk populations such as shift workers.\n- **Related work:** A follow-up arXiv paper uses the same shift-worker dataset (1,185 participants, 10,286 recordings) to test meta-learning for predicting time since sleep from speech, and it reports that 45.4% of the samples were labelled as fatigued."
  ],
  "durationSeconds": 6.5006081499999855,
  "searchCount": 1
}

{
  "query": "\"TEMPO\" FDA CMS pilot program digital mental health devices npj Digital Medicine Parks Shick",
  "mode": "extended"
}

{
  "query": "\"TEMPO\" FDA CMS pilot program digital mental health devices npj Digital Medicine Parks Shick",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Y4vJukVvXyew8fXFVvBDJq",
      "content": [
        {
          "title": "Expert perspectives on recent US digital medicine regulation policy changes and the TEMPO pilot - PMC",
          "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13184310/"
        },
        {
          "title": "New year, new digital therapeutics pilot",
          "url": "https://www.healthcare-brew.com/stories/2026/01/29/new-digital-therapeutics-pilot"
        },
        {
          "title": "CMS and FDA Announce Initiatives to Expand Access to Digital Health Technologies",
          "url": "https://www.orrick.com/en/Insights/2025/12/CMS-and-FDA-Announce-Initiatives-to-Expand-Access-to-Digital-Health-Technologies"
        },
        {
          "title": "FDA opens a CMS-linked side door: Use of digital health devices before authorization under the TEMPO pilot",
          "url": "https://www.hlc.com/en/publications/fda-opens-a-cms-linked-side-door-use-of-digital-health-devices-before-authorization"
        },
        {
          "title": "FDA announces digital health services pilot",
          "url": "https://www.aha.org/news/headline/2025-12-05-fda-announces-digital-health-services-pilot"
        },
        {
          "title": "FDA launches TEMPO pilot: The race for digital health access is on",
          "url": "https://www.mcdermottlaw.com/insights/tempo-pilot-enrollment-begins-the-race-for-digital-health-access-is-on/"
        },
        {
          "title": "FDA TEMPO Pilot for Digital Health Devices and CMS ACCESS",
          "url": "https://meddeviceguide.com/blog/fda-tempo-pilot-digital-health-devices-cms-access-model-guide"
        },
        {
          "title": "Digital Health Center of Excellence",
          "url": "https://www.fda.gov/medical-devices/digital-health-center-excellence"
        },
        {
          "title": "www.fda.gov",
          "url": "https://www.fda.gov/media/190902/download"
        },
        {
          "title": "fda launches tempo first its kind digital health pilot expand access chronic disease technologies",
          "url": "https://fda.gov/news-events/press-announcements/fda-launches-tempo-first-its-kind-digital-health-pilot-expand-access-chronic-disease-technologies"
        }
      ]
    },
    "The search didn't surface the npj Digital Medicine article by Parks and Shick, so I can't confirm its content. The results do cover the TEMPO pilot itself.\n\n- **What it is:** FDA's Technology-Enabled Meaningful Patient Outcomes pilot was announced on December 5, 2025, to promote access to certain digital health devices while safeguarding patient safety. Its aim is to evaluate a new, risk-based enforcement approach for devices targeting cardio-kidney-metabolic, musculoskeletal, and behavioral health conditions.\n- **CMS link:** It runs \"in connection with\" the ACCESS model, CMS's chronic-care payment model that was planned to launch on July 1, 2026.\n- **How it works:** Manufacturers of devices that lack FDA authorization for the intended use can ask FDA for enforcement discretion, which would waive requirements such as premarket authorization. In exchange, they collect and share real-world performance data (FDA would not enforce certain requirements when offered to ACCESS participants, and the devices generate real-world data that may support future FDA marketing submissions).\n- **Mental health relevance:** Behavioral health is one of its target areas. One law-firm summary lists digital cognitive behavioral therapy platforms, AI-driven mental health screening tools, and prescription digital therapeutics for substance use disorders as examples of eligible device types.\n- **Status:** Statements of interest opened January 2, 2026. FDA expects to select up to 10 manufacturers in each of the four clinical use areas.\n- **Caveat:** The sources describe the pilot as a regulatory experiment, and one commentary notes that it explores whether certain digital health devices can be used in the CMS ACCESS model while data are collected in a structured way. Its outcomes aren't yet known from these results."
  ],
  "durationSeconds": 7.3299702810000165,
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{
  "message": "# Beat B — Research & papers (window 2026-11-02T11:50Z → 2026-11-03T11:05Z)\n\n**Window note:** the arXiv cs.AI / cs.LG / cs.CL / cs.CR / cs.CY RSS feeds all carried `pubDate: Tue, 03 Nov 2026 00:00:00 -0500` (= 2026-11-03T05:00Z), inside the window. All arXiv items below are from that announcement batch (2611.0xxxx). Lab blogs (Anthropic Alignment Science, METR, Apollo, Transluce, Epoch, UK AISI, DeepMind, Google Research, Microsoft Research, Stanford HAI) had **nothing** dated 2–3 Nov 2026 — latest posts were 26–30 Oct. OpenAI research page returned HTTP 403; Science.org news returned HTTP 403; Reddit r/MachineLearning unfetchable.\n\n---\n\nSECTION: Research & papers\nHEADLINE: MIT CSAIL report says frontier LLM edited 0.016% of a model's weights, lifting MATH-500 from 7.9% to 48.1%\nPUBLISHED: November 2, 2026 (report); alphaXiv listing \"Submitted 02 Nov 2026\"; coverage November 3, 2026\nSOURCES:\nRikiya Takehi (authors' report) | https://rikiyat.github.io/blog/weight-space-programming/ | primary\nalphaXiv | https://www.alphaxiv.org/abs/2611.weight-space-programming | primary\nXenoSpectrum | https://xenospectrum.com/en/sparks-of-weight-space-programming-mit-csail/ | report\nLatent Space (AI News) | https://latent.space/p/ainews-llms-can-read-write-neural-network-weights-weight-space-programming-cuts-autoresearch-out-of/ | report\nFACTS:\n- \"Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights,\" by Rikiya Takehi, Jayden Teoh, Alex Zhang and Omar Khattab; the report page gives MIT CSAIL as the affiliation for all four. No arXiv ID — the alphaXiv entry is `2611.weight-space-programming`; the authors' page lists only the blog URL, a BibTeX entry and GitHub logs.\n- The authors' page reports that editing 131,072 weights (0.016%) of Qwen3.5-0.8B moved scores from base 7.9% to 48.1% on MATH-500, 13.8% to 67.1% on GSM8K and 21.0% to 62.3% on IFEval (edited model, 50 forward passes), with the share of runs hitting the token limit falling from 93.0% to 33.1%.\n- The authors' page reports a repaired Kinetix car-on-ramp policy succeeded in all 1,024 episodes with 3.5% of 171,664 weights changed, against 0% success in 256 episodes for the original PPO policy trained for 1B steps; MinAtar networks written from scratch scored Breakout 517.4 / Seaquest 53.1 / Asterix 53.2 versus PPO-500M at 25.3 / 88.9 / 55.2.\n- The authors' page reports a negative control: on Gemma 3 270M, MATH-500 went from 6.8% base to at most 7.7% across 5–50 forward passes (\"no meaningful improvement\"). Eight experiments in total; the model used is described as GPT-6 Astra.\n- Latent Space's write-up (dated November 3, covering Oct 31–Nov 2) records commenter pushback that the MATH-500 baseline was \"pathologically low because many answers hit the token limit in looping,\" so the edit may have removed a looping behaviour rather than added math ability. alphaXiv also shows an unverified reader-comment reproduction (cap rate 88.7%→17.6%, accuracy 10.9%→61.7%).\nFLAGS: preprint, company-claim (lab-reported benchmark, not independently verified)\n\n---\n\nSECTION: Research & papers\nHEADLINE: Stanford \"hinted scaling laws\" forecast a 10^23-FLOP model's GSM8K score to within 3 percentage points\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.02270v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.02270, \"Hinted Scaling Laws.\" Title page affiliation line reads \"Stanford University\" for Suze van Adrichem, Luke Bailey, Rohith Kuditipudi, Christine Ye, Neil Band, Ahmed Ahmed, John Duchi, Percy Liang and Tatsunori Hashimoto.\n- The paper reports that on the Delphi pretraining ladder, a hinted scaling law fit on models trained with at most 10^20 FLOPs forecasts the GSM8K accuracy of a 10^23 FLOP model (25.9%) to within 3 percentage points, while a standard scaling law under-forecasts it by 13 percentage points fit on the same models, and by 12 even with models up to 10^22 FLOPs in the fit.\n- The paper reports that across the pretraining ladder and a collection of post-trained model families, hinted scaling laws reduce median forecasting error on GSM8K, AIME and HLE from 21 percentage points to 4.3.\n- The paper reports a single hinted rollout per problem ranks nearly indistinguishable models as accurately as five unhinted rollouts.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: MBZUAI paper forecasts RLHF response to reward-model edits before training, explaining 82% of change\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.03244v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.03244, \"Forecasting How RLHF Responds to Reward-Model Edits Before Training,\" by Zixiao Wang, Duzhen Zhang, Xingbo Du, Dongxia Wu and Le Song; the title page gives one shared affiliation, Mohamed bin Zayed University of Artificial Intelligence.\n- The paper reports 54 RL runs from six parent policies under a 2^(4-1) fractional factorial design with a self-distilled placebo, with every forecast fixed before the runs; a within-prompt covariance predictor \"predict[s] the direction of all 20 changes in supply whose forecast has the same sign at every parent and explain[s] 82% of the standardized change,\" against 50% for counterfactual prices.\n- The paper reports the forecast explains 66% out of sample under real reward-model upgrades with a coefficient frozen from the factorial runs, and ranks reward-model edits by proxy-gold reward gap over the first 30 steps at Spearman 0.94.\n- The paper reports the ranking of the factorial edits reverses by step 200 under both RLOO and GRPO, and that one experiment is consistent with an additional implicit regularizer beta_0 of about 0.003 to 0.007.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Princeton study attributes faster memorization in larger transformers to a meta-memorization effect\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.01564v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.01564, \"Meta-memorization and memorization scaling laws in transformers,\" by Alex Nguyen (Princeton Neuroscience Institute), Kenneth A. Norman (Princeton Neuroscience Institute and Department of Psychology) and Gautam Reddy (Department of Physics), all Princeton University.\n- The paper reports reproducing both memorization scaling laws on transformers trained on random binary sequences, showing rapid memorization can arise with no semantic or compositional structure in the data.\n- The paper reports the memorization rate r(t) grows with training time as a power law r(t) ~ t^beta with a fixed exponent beta but an increasing upper cutoff across model scales, and that meta-memorization lets even one-layer transformers few-shot memorize a 100-bit sequence.\n- The paper reports the effect is partly explained by structured attention heads conveying position-invariant sequence information to MLPs, and is recapitulated in a dense associative memory with an attentional bottleneck.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Stanford-led teamwork benchmark: best of 18 models scores 82.2/100, wins only 14% of conflicts\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.02633v1 | primary\nHugging Face Daily Papers (3 Nov) | https://huggingface.co/papers/date/2026-11-03 | report\nFACTS:\n- arXiv:2611.02633, \"Measuring AI Agents as Teammates with Collaborative Intelligence.\" Title page affiliations: Sean Wu, Aneesh Pappu, Jiaru Zou, Yubin Kim, Yuncong Mao and Jieneng Chen (Stanford University), Hongjian Zhou and Junchi Yu (University of Oxford), James Zou (MIT). Hugging Face shows a Stanford University badge and 15 upvotes.\n- The paper reports the Collaborative Intelligence Benchmark has 240 tasks across 8 dimensions of teamwork (160 public, 80 held out), each with a programmatically verifiable outcome, and that models are scored only on tasks they can solve alone with full information.\n- Across 18 closed- and open-weight models, the paper reports the best model scores only 82.2 out of 100; frontier models reach the best overall deal in only 14% of conflicts, and pass rate drops from 97% to 81% when taking over a task in which a weaker model has cheated.\n- The paper reports models with nearly the same general capability score differ by up to 11 points as teammates.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Pre-registered study: small local reward-hacking monitors reach AUC 0.64 versus 0.80 for Gemini 3.1 Flash-Lite\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00407v1 | primary\narXiv RSS cs.AI | https://rss.arxiv.org/rss/cs.AI | primary\nFACTS:\n- arXiv:2611.00407, \"Hacking or Just Failing? A More Capable LLM Monitor Better Separates Reward Hacking from Honest Failure,\" single author Kaushik Kezendirane, title page affiliation \"Independent researcher.\"\n- The paper reports five pre-registered studies on a sandboxed task with counterfactual repair labelling; on 60 episodes from a Llama 3.1 8B agent, small local monitors (Llama 3B and 8B) did not separate exploit attempts from honest failures and the pre-registered primary monitor reached AUC 0.64.\n- On identical inputs the paper reports Gemini 3.1 Flash-Lite met the pre-registered criterion at AUC 0.80, 95% interval [0.66, 0.93], with 1/35 honest failures flagged, and completed 9/10 clean tasks against 2/10 for the 8B model; the paper notes the estimate is uncertain with only 14 exploit episodes.\n- The paper reports that on an exploit no prompt names, Gemini usually described the action correctly yet never flagged it across 5 and then 25 episodes; given the full trace the 8B monitor flagged all 25 replication episodes and none of 25 honest look-alikes, but its explanations described actions that had not occurred, and with added structured evidence it also flagged 15 of the 25 look-alikes. A two-rule deterministic check caught every known exploit.\nFLAGS: preprint, single-source\n\n---\n\nSECTION: Research & papers\nHEADLINE: Columbia paper: ablating one SAE feature flips a next-layer feature past the TopK cutoff in at least 0.74 of cases\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00606v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.00606, \"Sparse Autoencoder Attribution Graphs Are Decided at the Margin,\" single author Karl Li, title page affiliation Columbia University.\n- On five public TopK SAE pairs from three Pythia models, the paper reports that zeroing one feature moves a next-layer feature across the cutoff in 0.74 of cases or more, and that the crossings carry most of the response's energy.\n- The paper reports the graph built on features active beforehand has a median relative error of 0.247 or more, while a \"margin graph\" that adds the first-order change to every preactivation and reranks at the same cost errs by at most 0.033.\n- The paper reports that between seeds of one testbed, sparse maps between features explain 0.85 of a graph's energy on its active features, falling to 0.47 once the other seed's graph keeps only its own; the largest model studied is pythia-160m.\nFLAGS: preprint, single-source\n\n---\n\nSECTION: Research & papers\nHEADLINE: UCLA links singular learning theory to circuit interventions in Pythia-1B, median rank correlation 0.51\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00640v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.00640, \"Bridging Singular Learning Theory and Mechanistic Interpretability at the Billion-Parameter Scale,\" by Ethan Ji, Wei Wang and Yizhou Sun, Department of Computer Science, University of California, Los Angeles (author emails @cs.ucla.edu).\n- The paper reports testing the correspondence in Pythia-1B on Dyck bracket matching at all 154 training checkpoints against a five-stage circuit identified by interventions, measuring local geometry of all 144 components.\n- The paper reports that changes of the Fisher trace track changes of causal effect with median partial rank correlation 0.51, largely as a trend shared across the model, while the gain Fisher of a component's output and the large-temperature count are specific to the component.\n- The paper reports the large-temperature count follows causal change across the population but not the growth of a formed circuit component, and that pairwise interaction curvature tracks joint-ablation interactions.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Georgia Tech swaps one goal word's SAE features and redirects π0.5 robot policy in up to 20/20 rollouts\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00602v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.00602, \"Editing the Goal: Per-Token SAE Steering and Its Depth Limits in π0.5,\" by Rocio Perales Valdes and Animesh Garg, PAIR Lab / AI Safety Initiative, Georgia Institute of Technology.\n- The paper reports that at layer 0, BatchTopK feature swaps on a single goal word redirect π0.5-LIBERO behaviour in up to 20/20 rollouts in a scene where random-feature swaps redirect none, with success varying across six scenes in two LIBERO suites and across layers.\n- The paper reports word-selected Matryoshka edits largely do not outperform random ones, and that SAEs are not required: adding a fixed difference-in-means vector at twice its natural magnitude redirects 8–10/10 rollouts.\n- Layer-wise activation patching is reported to show goal-word edits remain effective up to layer 6 for object location and layer 2 for object identity, and up to layer 13 in both cases when patching also covers camera tokens.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Northeastern derives a vocabulary-wide \"fear\" ranking from a refusal direction, validated in eight models\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.02348v1 | primary\narXiv RSS cs.CL | https://rss.arxiv.org/rss/cs.CL | primary\nFACTS:\n- arXiv:2611.02348, \"Which Words a Model Fears: From a Refusal Direction to a Vocabulary-Wide Fear Lexicon,\" by Boyuan Zhang, Mohammad Zandsalimy and Shanu Sushmita; title page affiliation line reads Northeastern University.\n- The paper reports that in eight models, writing along a single crossed-differencing direction raises and lowers refusal monotonically with dose, ahead of random and KL-matched directions.\n- The paper reports two held-out tests validate the ranking in all eight models: refusal after inserting an unseen word rises with its table shift, and replacing a prompt's most feared word with its most courageous meaning-preserving synonym significantly raises the answer rate on benign and harmful prompts alike.\n- The paper reports appending a feared word to a benign prompt is enough to make the model refuse it.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Mila-led work on self-verification limits reports up to 7-point verification gain at 17-42% lower inference cost\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00350v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.00350, \"On the Limits of Test-Time Compute for Self-Evaluation,\" by Anirudh Buvanesh, Khaled Rouissi, Sujin Yun, Johan Obando-Ceron, Morgane M Moss, Samuel Lavoie, Michael Noukhovitch, Laurent Charlin and Aaron Courville; title page affiliations: Mila Université de Montréal, Nous Research, Google, HEC Montréal, Canada CIFAR AI Chair.\n- The paper reports ranking error admits a bias-variance decomposition, and that across its experiments additional inference compute reduces variance while bias initially decreases before approaching a plateau — the stated reason extra candidates do not consistently close the gap to pass@N.\n- The paper reports its method, Scorpio, improves verification accuracy over the strongest baseline by up to 7 percentage points while matching or exceeding that baseline's peak accuracy at 17–42% lower inference cost.\n- The paper reports tree-search accuracy gains of up to 10 percentage points over prior methods and an 11-percentage-point improvement to aggregation scaling on coding tasks.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: USC tests 14 models on 3,076 medical questions; mean accuracy falls from 82.3% to 50.9% without answer choices\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00460v1 | primary\narXiv RSS cs.AI | https://rss.arxiv.org/rss/cs.AI | primary\nFACTS:\n- arXiv:2611.00460, \"From Small to Large: Assessing Medical Reasoning, Benchmark Contamination, and Model Size in Language Models,\" by Navapat Nananukul and Mayank Kejriwal, Information Sciences Institute, University of Southern California.\n- The paper reports evaluating fourteen models from six providers (one smaller and one larger per provider, plus two open-weight models) on 3,076 questions from MedQA-USMLE, MedMCQA, PubMedQA and MedBullets.\n- The paper reports that in the standard multiple-choice setting the strongest models exceed the human-expert baseline on MedQA-USMLE and PubMedQA, but smaller models trail their larger counterparts by 8.7 percentage points and only two of six pass the human-expert bar on the licensing examination.\n- The paper reports that withholding answer choices drops mean accuracy from 82.3% to 50.9%, with the two largest drops belonging to the medically specialised models; on memorization, the strongest models reconstruct one question in four from the answer choices alone, yet accuracy holds on questions they cannot reconstruct.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: CMU-Google study of 22,500 red-team attacks finds instruction wording significantly predicts attack success\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00412v1 | primary\narXiv RSS cs.CY | https://rss.arxiv.org/rss/cs.CY | primary\nFACTS:\n- arXiv:2611.00412, \"On the Framing Effect of AI Red-Teaming Instructions: Evidence from Prior Exercises and Controlled Simulations.\" Title page affiliations: Michael Feffer (Cornell Tech; work completed while at Carnegie Mellon University), Alice Qian, Anusha Sinha, Hong Shen, Hoda Heidari (Carnegie Mellon University), Muye Zhang, Shalini Ghosh, Rachel Phinnemore, Bart Stawicki (Google).\n- The paper reports reviewing 228 instances of prior work on how red-teaming instructions have been formulated.\n- The paper reports controlled simulations deriving 45 instruction frames from five real industry/academic templates across three risk domains and three levels of risk granularity, 100 variants per frame, each deployed against five open-weights target models, for 22,500 attacks.\n- Using a generalized linear mixed model, the paper reports the lowest and highest levels of risk granularity both outperform intermediate specificity, as do short and long instructions relative to medium-length ones; presence of examples is associated with higher attack success rates, and supplying explicit harm definitions with lower ones.\nFLAGS: preprint\n\n---\n\nSECTION: Research & papers\nHEADLINE: Scale AI evaluates 14 single-pass decision models as judges; eleven hit 90.3-93.4% on JudgeBench with a reference\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00505v1 | primary\narXiv RSS cs.AI | https://rss.arxiv.org/rss/cs.AI | primary\nFACTS:\n- arXiv:2611.00505, \"To Jev or Not to Jev: When Can System-1 Decision Models Replace LLM Judges?\", single author Shreyas Subramanian, title page affiliation \"Scale AI\" (labelled \"Scale AI Research\").\n- The paper reports evaluating 14 System-1 decision models against four generative judges (Claude Haiku 5.5, GPT-5.6 with and without reasoning, Claude Opus 5.5 with thinking) on eleven judge benchmarks; five of the 14 are statistically indistinguishable from GPT-5.6 without reasoning on all five pairwise and best-of-4 benchmarks.\n- Conditioned on a reference answer generated once per prompt, the paper reports eleven models reach 90.3–93.4% on JudgeBench, statistically indistinguishable from Opus 5.5 and GPT-5.6 with reasoning; on PPE best-of-16 every reference-guided System-1 judge matches GPT-5.6 with reasoning \"at roughly one-sixteenth of its cost per prompt.\"\n- The paper reports robustness to injected instructions is model-specific: an appended note to the evaluator reverses 0–5% of the correct verdicts of five models but 17–49% for the other nine.\n- The paper reports two general System-1 leaderboards containing no judging tasks predict judging accuracy at Pearson r = 0.95–0.96.\nFLAGS: preprint, company-claim\n\n---\n\nSECTION: Research & papers\nHEADLINE: Concise self-training cuts a 9B reasoning model's tokens to 0.66x with accuracy within ±1 point\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.02278v1 | primary\narXiv RSS cs.LG | https://rss.arxiv.org/rss/cs.LG | primary\nFACTS:\n- arXiv:2611.02278, \"Concise-9B: Removing the Slack from a Reasoning Model's Thinking.\" Single author listed on the title page as Alexander Boesgaard Lorup; no institutional affiliation is shown on the page.\n- On 8,983 held-out problems (competition and hard mathematics, SuperGPQA, a five-area confirmation set and MMLU-Pro), the paper reports Concise-9B generates 0.66x the tokens of Qwen3.5-9B at a 32K thinking budget with accuracy equivalent within ±1 point (-0.20 [-0.77, +0.36] points).\n- Forcing an answer every 2,048 thinking tokens, the paper reports 54–64% of Qwen3.5-9B's thinking tokens come after the point from which every forced answer equals the final one (41–48% for Concise-9B); stopping when three consecutive forced answers agree costs the base model 2.4–9.2 points.\n- The paper reports 86% [83, 90] of the thinking tokens saved come after the answer has formed, and a limit: with traces continued to 80K tokens Concise-9B solves 25 fewer of 1,276 hard problems (-25 [-49, -1]).\nFLAGS: preprint, single-source\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Northeastern and Microsoft inject structured-output backdoors into coding agents at up to 96.2% success\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00138v1 | primary\narXiv RSS cs.CR | https://rss.arxiv.org/rss/cs.CR | primary\nFACTS:\n- arXiv:2611.00138, \"Kerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents.\" Title page affiliations: Georgios Syros (Northeastern University; work performed while at Microsoft Research), Alina Oprea and Cristina Nita-Rotaru (Northeastern University), Blake Bullwinkel, Amanda Minnich, Giorgio Severi (Microsoft), Xiaodong Liu (Microsoft Research).\n- The paper reports a trigger placed anywhere in the agent's context causes the model to emit an attacker-chosen tool call that the harness executes, and that the attack reaches success rates of up to 96.2% on heavily post-trained open-weight models across proprietary and open-source harnesses.\n- The paper reports the attack can be configured to generalize across harnesses or bind to a single target, and that the backdoored models \"can outperform the clean baseline on standard utility benchmarks.\"\n- Method: poison-sample construction, backdoor injection via supervised fine-tuning, and utility recovery with lightweight reinforcement learning.\n- Note: the arXiv HTML page carried an appended block of instructions about quoting and legal comments; this was treated as untrusted page content and ignored.\nFLAGS: preprint\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Trust-building web fraud attack hits 71.4% average success against three coding agents; proposed defence cuts it to 0%\nPUBLISHED: arXiv announcement Tue, 03 Nov 2026 00:00:00 -0500\nSOURCES:\narXiv | https://arxiv.org/html/2611.00725v1 | primary\narXiv RSS cs.CR | https://rss.arxiv.org/rss/cs.CR | primary\nFACTS:\n- arXiv:2611.00725, \"The Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents,\" by Xingling Xu, Zhengwei Jiang, Zheng Zhi, Fangming Dong, LingJia Guo, Chunyan Ma and Jun Jiang (Institute of Information Engineering, Chinese Academy of Sciences / University of Chinese Academy of Sciences) and Wei Dong (The North China Institute of Computer System Engineering).\n- The paper reports 56 organizational environments (8 task contexts x 7 attack consequences) and an average scene-level attack success rate of 71.4%: 85.7% on Codex-GPT-5.5, 67.9% on ZCode-GLM-5.3-Flash and 60.7% on QwenCode-Qwen3.7-Plus, \"significantly outperforming all injection-based baselines.\"\n- The paper reports coding agents \"exhibit trust-like behavioral reliance on previously helpful Web sources,\" and that accumulated credibility significantly increases susceptibility to later malicious instructions.\n- The paper reports its proposed defence, action-authorization separation (AAS), reduces the attack success rate to 0% while preserving 100% task completion.\nFLAGS: preprint\n\n---\n\n## Lower-priority / rejected candidates\n\n- **arXiv:2611.00420 Circuit Oracle** (Shariar Kabir & Sai Chereddy, independent; Hong Kiat Tan, UCLA; Swastik Agrawal & Sriram Balasubramanian, University of Maryland) — real interpretability-for-safety result (78.2 ± 2.4% on spurious-feature detection, beating single-layer feature-ranking baselines; below a diff-in-means baseline on refusal suppression over 50 prompts). Usable as a 16th item if space allows; results self-described as \"mixed.\"\n- **arXiv:2611.00465** evaluation-based AI governance, 37 expert interviews (Lily Stelling / Jacob Charnock / Kevin L. Wei / David Krueger; MATS Research, Oxford Martin AI Governance Initiative, Mila Université de Montréal) — interview counts only (18/18/16 pathways; 21/18/16/12 challenges), no model result. Governance beat rather than a quantitative paper.\n- **arXiv:2611.03494 \"Harder Than the Task\"** (Victor Barres & Aden Barton, Mercor; Nicolai J. Foss & Henrik M. Nielsen, Copenhagen Business School) — only number is \"fewer than one quarter of prominent benchmarks\" cover organizational dimensions; largely a position/taxonomy piece.\n- **arXiv:2611.00464** compression factorial ablation (72 configs, INT8 <0.5% degradation, NF4+L1 pruning collapse in all 16 combinations) — solid numbers but engineering, not safety/evals; authors Bhushit Nema, Siddharth Krishnamurthy, Anjali Kadiyala, affiliations not verified.\n- **arXiv:2611.00555** grammar-lens benchmark separating GPT-5.5 / GPT-5.5-Pro-Medium/High/XHigh at 16, 40, 43, 52% acceptance (Emma Graham, Richard Granger, Dartmouth College) — small single-lab study, 4 model settings; include only if a short item is wanted.\n- **arXiv:2611.01304** \"When LLMs Modify Themselves\" (54 experiments; Claude Opus 4.5 and Sonnet 4.5 declared convergence in 100% of runs, GPT-4o in 11%, one run reaching 101 iterations) — affiliation not verified; uses older model generation.\n- **arXiv:2611.00386** dependence-aware AI-agent safeguard design (independence-based selections violated security requirements in six of eight scenarios; 39.6% lower held-out total cost) — mostly theory/OR, affiliations unverified.\n- **arXiv:2611.00247 Taurus** (Bing Hu, Rishabh Sharma, Jatin Mehta; University of Waterloo) — CT annotation harness matching a free-form Claude Opus 5.5 agent at $1.22 vs $2.71 per case over 939 volumes; good but medical-imaging niche.\n- **arXiv:2611.00508** social-influence pressure on LLM audit agents (12 model settings) — no headline number reported in the abstract.\n- **arXiv:2611.02710 MicroMouse** (5.5% average relative greedy-accuracy gain, 8.8% shorter outputs vs Full-CoT SFT) and **arXiv:2611.01378** information-theoretic SAE steering — incremental method papers, no baseline-beating headline figure of note.\n- **Nature items dated 2–3 Nov 2026** (Nature Communications \"Genome-anchored foundation model embeddings improve molecular prediction from histology images\" / PathLUPI, 49 molecular oncology tasks in 20 cohorts, 02 Nov; Nature Biomedical Engineering RetiME, 02 Nov; Nature Methods de novo peptide-sequencing benchmark of eight deep-learning tools, 03 Nov) — **dropped on time-of-day uncertainty**: the listing (read via `node scripts/fetch.js https://www.nature.com/subjects/machine-learning`) gives only dates, and Nature journals' publication time cannot be pinned inside 02 Nov 11:50Z → 03 Nov 11:05Z.\n- **Hugging Face Nov 2 daily papers** (e.g. \"Follow the Gradient: Tracing Safety Degradation Back to Training Data,\" DatologyAI, 29 upvotes) — corresponds to the arXiv announcement at 2026-11-02T05:00Z, before the window opens; arXiv ID could not be confirmed.\n- **Lab blogs with nothing in window** (checked and empty): alignment.anthropic.com (latest Oct 2026), metr.org/research (latest 26 Aug 2026), apolloresearch.ai/research (latest 15 Oct 2026), transluce.org (latest 30 Sep 2026), epoch.ai (latest report 30 Oct 2026; only two *data explorers* show \"Updated Nov. 2/3, 2026\"), aisi.gov.uk/work (latest 26 Oct 2026), deepmind.google/discover/blog (latest Oct 2026), research.google/blog (latest 27 Oct 2026), microsoft.com/en-us/research/feed (latest 30 Oct 2026), hai.stanford.edu/news (latest Oct 21), alignmentforum.org (most recent post 21h old, title \"Some 'coherence arguments' are two different things in a trenchcoat\" by Steven Byrnes — page shows only relative ages, so the date could not be confirmed; no quantitative result). blog.redwoodresearch.org returned no post list. openai.com/research returned HTTP 403; science.org/news returned HTTP 403; reddit.com/r/MachineLearning was unfetchable.\n"
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  "url": "https://the-decoder.com/anthropic-cracks-down-on-game-cloning-in-claude-code/",
  "prompt": "Give publication date, exactly what Anthropic changed, quotes from the policy, which model versions, and user reports."
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  "result": "**Publication date:** November 3, 2026 (The Decoder, short news by Maximilian Schreiner)\n\n**What Anthropic changed:** Anthropic added two sentences to the system prompt of Claude Code, its coding assistant, to stop it from recreating existing video games. Employee Addy Osmani confirmed the change on X. The article doesn't reproduce the two sentences. Per the article, the rule has been active for several days and applies even when a clone is renamed or presented as an original work.\n\n**Quotes from the source:**\n- \"Two sentences in Claude Code's system prompt for Opus 5.5 now prevent the tool from cloning other people's games.\" (Article's wording, not Anthropic's policy text.)\n- Osmani's position is paraphrased, not quoted: using Claude to infringe on intellectual property violates the usage policy. The article doesn't provide his exact words.\n- Osmani said Anthropic plans to keep adjusting the rules.\n\n**Model versions:**\n- **Claude Opus 5.5:** the model whose Claude Code system prompt was changed.\n- **GPT-6 Astra:** named as a model users also used to generate unofficial game clones. It is not part of Anthropic's change.\n\n**User reports:**\n- Users can still build their own games, genre titles, and projects with custom assets.\n- Some users report problems with original projects as well.\n- Before the change, users were making hundreds of unofficial browser ports of well-known titles, including Halo and GTA Vice City.\n- The article ties the change to a wider wave of AI-built knockoffs, including a developer who recreated parts of Adobe's Creative Cloud apps.",
  "durationMs": 7444,
  "url": "https://the-decoder.com/anthropic-cracks-down-on-game-cloning-in-claude-code/"
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{
  "command": "echo \"=== 42AI ===\"; node scripts/fetch.js \"https://techcrunch.com/2026/11/02/42ai-comes-out-of-stealth-with-62-5m-and-a-world-model-that-can-predict-human-behavior/\" 2>&1 | sed -n '1,60p'",
  "description": "Fetch TechCrunch 42AI article"
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{
  "stdout": "=== 42AI ===\nHTTP 200 · https://techcrunch.com/2026/11/02/42ai-comes-out-of-stealth-with-62-5m-and-a-world-model-that-can-predict-human-behavior/ · text/html\n42AI comes out of stealth with $62.5M and a world model that can 'predict human behavior' | TechCrunch\n\n–:–:–:–\n\nBuy One Founder Summit Ticket, Get a Second for Free. Register now.\n\nFounder Summit begins Nov. 4, 9:00 a.m. ET. Get your pass savings & deals before it starts. REGISTER HERE.\n\nClose\n\nImage Credits: 42AI\n\nAI\n\n# 42AI comes out of stealth with $62.5M and a world model that can ‘predict human behavior’\n\nRam Iyer\n\n8:30 AM PST · November 2, 2026\n\nHere’s a question straight out of sci-fi: What if AI could predict what you were going to do before you decided to, even in a completely new situation?\n\nIsraeli startup 42AI says it is developing a “behavioral world model” that can do just that, and it has just come out of stealth with $62.5 million in seed funding. The company is initially running its predictive system at a handful of financial brokerages, where it says the model can help predict how individual traders will respond to volatile conditions.\n\n“Behavior is not deterministic; it’s constantly probabilistic,” 42AI’s CEO and co-founder Amit Gal-Or told TechCrunch when I asked him to justify his company’s tall claim. He argues that people have underlying psychological tendencies that influence their decisions even when their circumstances change, and that’s what the startup is trying to measure and convert into data that the model can understand.\n\n“A week from now, you might be a different person, but your tendencies will always play out in certain areas to a probability or distribution,” his co-founder and CTO Ehud Ezra added. And that, the company argues, is what the model does: show the probability of a person making a certain decision.\n\n42AI says the model tries to figure out people’s internal motivations instead of extrapolating patterns based on their previous actions. To do that, 42AI examines how people react to seemingly unrelated events. For an investor or trader, for example, such events might include completing KYC processes, onboarding, support calls, money transfers, or trading stocks.\n\n“When the person is talking to support or sales in the initial process […] we’re looking at the sentiment, we’re looking at the voice, we’re looking at a lot of interactions that they’re doing, how many times do they call, and so forth,” added Ezra. “And all of those data points are going into the model. Later on, you have the interactions: how you buy and sell, and when, and we’re looking at the market at that stage.”\n\n“So we’re trying to look at how they’re looking at the world. In a world model, every individual is the world,” he added.\n\nThe company then converts those observations into mathematical representations of traits, which are then fed into a transformer-based world model that lays out probabilities for possible decisions under different circumstances. (The company uses a separate language model to generate explanations for its predictions.)\n\nEzra said the model is trained to preserve a person’s underlying tendencies during simulations. So if someone is usually risk-averse, but the model suddenly treats them as a risk-taker, “the target is off,” he said, explaining how the model’s training rewards are structured.\n\n42AI spent three years developing this approach, combining psychological research with neuroscience and genetics, as well as advice from experts in psychology and PTSD, and Dan Shechtman, who was awarded the 2011 Nobel Prize in Chemistry.\n\nGal-Or said the team first studied thousands of people via psych assessments and behavioral scenarios, before adding government and biobank datasets covering more than 2 million people. Its customer datasets have since expanded to cover almost 30 million people, he said.\n\nIn live deployments, the model analyzes customers’ existing records, including transactions and support calls. Gal-Or pointed out the system doesn’t need personally identifiable information, arguing that “the model never knows who the person is.” However, it seems the company still creates individual behavioral profiles from linked customer activity.\n\nIn predicting market trades, 42AI claims its model achieves 98% accuracy, but Gal-Or clarified that this is more a measure of whether trading flows fall within a predicted range, not if each trade was predicted correctly.\n\nHe also said the model consistently achieves an F1 score of 0.8 to 0.85 for predicting trading direction and volume. (F1 score is a metric in machine learning that measures how well a classification model can balance correct predictions against false alarms and missed events.)\n\nAnd it’s not like the model can work everywhere, given it’s still a machine in a box. “There’s a natural ceiling because you really don’t have access to everything that a person experiences,” Gal-Or said. Ezra explained that the system’s accuracy also suffers when it misses important situational context, like if someone chooses to change their trading choices based on advice from a friend or a colleague.\n\nGal-Or said 42AI is working with 10 large brokerages, who are using it to manage liquidity, margin requirements, and hedging exposure. The company is onboarding more customers, he said, and is generating more than “seven figures” in revenue, though he wouldn’t specify a number.\n\nCustomers pay the startup a flat fee, or a percentage of the value the platform helps them gain. He claimed one brokerage generated approximately $30 million in additional value through dynamic hedging.\n\nThe $62.5 million seed funding came from the founders and Infinity Group over three years, and wasn’t entirely raised from external investors, Gal-Or said. Infinity was founded by his father, Amir Gal-Or, who is also 42AI’s chairman and a co-founder. 42AI now plans to raise more money.\n\nBeyond finance, 42AI is now expl
… [901 more characters in events.jsonl]

{
  "url": "https://breakingdefense.com/2026/11/industry-needs-more-consistent-demand-signal-to-scale-ugv-production-autonomy-consortium-exec/",
  "prompt": "Publication date, named people, programs, numbers/figures."
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  "result": "**Publication date:** November 2, 2026 (2:47 pm), by Carley Welch.\n\n**Named people**\n- **Warren Sponsler**, COO of the National Advanced Mobility Consortium (NAMC), a nonprofit that bridges the Pentagon and industry on ground drone projects. He says industry struggles to understand the Army's demand signal and where to invest.\n\n**Organizations and programs**\n- **Army DEVCOM Armaments Center:** Pictured in the article's photo, helping explore future capabilities through experimentation with industry.\n- **FUZE:** The Army's venture capital acquisition hub, cited for its xTech competitions.\n- **xTech competitions:** Demonstrations for autonomous logistics and sustainment, and for autonomous breaching.\n- **UxS program of record:** Altered within roughly 18 months. The Robotic Combat Vehicle program became the Unmanned Ground Commercial Robotic Vehicle program, then was dispersed into Project Sustainment and the Engineer Autonomous Breaching Capability program.\n- **Army Futures and Autonomous Systems Command (FASCOM):** Replaced the Futures and Concepts Command and will coordinate with the Pentagon's Autonomous Warfare Command (AUTOWARCOM).\n- **AUTOWARCOM:** Newly established but not yet formally set up, as it needs Congressional approval.\n- **Portfolio Acquisition Executive for autonomy:** A new position, created alongside the relocation of the autonomy acquisition office.\n\n**Numbers and figures**\n- The article contains no dollar amounts, unit quantities, or production targets.\n- The only quantified timeframe is the roughly 18-month period in which the UxS program of record changed.",
  "durationMs": 6323,
  "url": "https://breakingdefense.com/2026/11/industry-needs-more-consistent-demand-signal-to-scale-ugv-production-autonomy-consortium-exec/"
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{
  "query": "AI ballot measure midterm election November 3 2026 data center referendum",
  "mode": "extended"
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{
  "query": "AI ballot measure midterm election November 3 2026 data center referendum",
  "results": [
    {
      "tool_use_id": "srvtoolu_01ELGXQrT4bwASNTf88EDpLt",
      "content": [
        {
          "title": "Citizens Started 25 of 41 Data Center Ballot Measures - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-citizens-started-25-of-41-data-center-ballot-measures/"
        },
        {
          "title": "AI data centers are on the ballot in 10 states tomorrow — here's what's at stake for your community",
          "url": "https://www.yahoo.com/news/us/articles/ai-data-centers-ballot-10-185841413.html"
        },
        {
          "title": "Voters in 10 States Face 41 Data Center Measures on Tuesday - FourWeekMBA",
          "url": "https://fourweekmba.com/ai-voters-in-10-states-face-41-data-center-measures-on-tuesday/"
        },
        {
          "title": "Data Center Restrictions Make the Ballot in Dozens of US Cities",
          "url": "https://www.insurancejournal.com/news/national/2026/11/02/891163.htm"
        },
        {
          "title": "Data center ballot measures head to voters in 8 states in November",
          "url": "https://www.foxnews.com/politics/americas-multi-billion-tech-boom-comes-into-focus-7-key-states-put-midterm-test"
        },
        {
          "title": "Voters in 10 states will decide on AI data center restrictions this Election Day. Here's what the results could mean for electricity bills and local communitie",
          "url": "https://www.tomsguide.com/ai/ai-data-centers-are-on-the-ballot-in-10-states-tomorrow-heres-whats-at-stake-for-your-community"
        },
        {
          "title": "2026 Massachusetts ballot measures",
          "url": "https://en.wikipedia.org/wiki/2026_Massachusetts_ballot_measures"
        },
        {
          "title": "The Issue That's Scaring Politicians in Both Parties: How AI Data Centers Became 2026's Defining Revolt",
          "url": "https://www.latintimes.com/issue-thats-scaring-politicians-both-parties-how-ai-data-centers-became-2026s-defining-revolt-600333"
        },
        {
          "title": "Data Centers Are On The Ballot This November",
          "url": "https://www.thebrockovichreport.com/p/data-centers-are-on-the-ballot-this"
        }
      ]
    },
    "Local data center measures are on ballots across several states today, though the sources disagree on the total count.\n\n- **Count:** Ballotpedia's November 2 report lists 41 local data center-related measures in 10 states, per one summary. Other outlets cite 34, 35, or 39, likely from different cutoff dates or counting methods.\n- **Ohio:** Ohio has the most, with 21 measures according to Ballotpedia. Some reports say voters in 17 to 18 jurisdictions are deciding them.\n- **Types:** One tally counts 25 citizen initiatives, 11 referrals from local officials, and 5 referendums on earlier decisions. Several measures are advisory, such as Downe Township, New Jersey, and Bloomington and Joliet, Illinois.\n- **Notable measures:** Alhambra, California, would vote on banning data centers in the city. Ottawa, Kansas, would bar facilities above 25 megawatts. Boulder City, Nevada, would decide whether to allow data centers in a specific valley area.\n- **Earlier results:** Ballotpedia says the side favoring limits won each of the six measures decided earlier in 2026.\n- **Public opinion:** A Quinnipiac poll from September found 72% of voters would oppose a data center in their community. Reuters/Ipsos found 77% worried about higher electricity bills.\n\nI did not find state-level or federal AI policy ballot questions in these results. Vote outcomes are not yet reported, so I'd check Ballotpedia directly for the official final list."
  ],
  "durationSeconds": 7.052276033999981,
  "searchCount": 1
}

{
  "query": "European Commission AI Act consultation November 2 2026 digital",
  "mode": "extended"
}

{
  "query": "European Commission AI Act consultation November 2 2026 digital",
  "results": [
    {
      "tool_use_id": "srvtoolu_01K4D2AgBbbiM9M54om4MTAC",
      "content": [
        {
          "title": "AI Act, ePrivacy Directive included in European Commission's consultation on digital simplification",
          "url": "https://iapp.org/news/a/ai-act-eprivacy-directive-included-in-european-commission-s-consultation-on-digital-simplification"
        },
        {
          "title": "EU AI Act Developments: Key Political Agreement on the Digital Omnibus on AI, Implementation Timeline and Transparency Consultation",
          "url": "https://cms.law/en/int/legal-updates/eu-ai-act-developments-key-political-agreement-on-the-digital-omnibus-on-ai-implementation-timeline-and-transparency-consultation"
        },
        {
          "title": "The Digital AI Omnibus: Proposed deferral of high risk AI obligations under the AI Act (update) - DLA Piper GENIE",
          "url": "https://knowledge.dlapiper.com/dlapiperknowledge/globalemploymentlatestdevelopments/2026/The-Digital-AI-Omnibus-Proposed-deferral-of-high-risk-AI-obligations-under-the-AI-Act"
        },
        {
          "title": "Digital Omnibus on AI",
          "url": "https://www.europarl.europa.eu/thinktank/en/document/EPRS_BRI(2026)782651"
        },
        {
          "title": "Digital omnibus on AI: The European Commission unveils a streamlined and more coherent approach to AI regulation",
          "url": "https://www.lexgo.be/en/news-and-articles/14473-digital-omnibus-on-ai-the-european-commission-unveils-a-streamlined-and-more-coherent-approach-to-ai-regulation"
        },
        {
          "title": "EU Digital Omnibus: The European Commission Proposes Important Changes to the EU's Digital Rulebook",
          "url": "https://www.sidley.com/en/insights/newsupdates/2025/12/eu-digital-omnibus-the-european-commission-proposes-important-changes-to-the-eus-digital-rulebook"
        },
        {
          "title": "The AI Act implementation timeline: What changes under the AI Omnibus?",
          "url": "https://fpf.org/blog/the-ai-act-implementation-timeline-what-changes-under-the-ai-omnibus/"
        },
        {
          "title": "Commission Proposes Significant Changes to EU Digital Rules",
          "url": "https://www.skadden.com/insights/publications/2025/11/commission-proposes-significant-changes-to-eu-digital-rules"
        },
        {
          "title": "European approach to artificial intelligence",
          "url": "https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence"
        },
        {
          "title": "AI Act rules on high-risk AI delayed as AI Digital Omnibus agreed - Winston Taylor",
          "url": "https://www.winstontaylor.com/insights/ai-act-rules-on-high-risk-ai-delayed-as-ai-digital-omnibus-agreed"
        }
      ]
    },
    {
      "tool_use_id": "srvtoolu_01W1b1jgLmnPsThC1ddR6tLu",
      "content": [
        {
          "title": "EU AI Act: The AI Office sends its first requests for information to leading AI providers - Lexology",
          "url": "https://www.lexology.com/library/detail.aspx?g=cdc3a626-bf58-48c1-a9b3-d80923381e31"
        },
        {
          "title": "EU AI Act: The AI Office sends its first requests for information to leading AI providers",
          "url": "https://www.reedsmith.com/our-insights/blogs/technology-law-dispatch/102o6as/eu-ai-act-the-ai-office-sends-its-first-requests-for-information-to-leading-ai/"
        },
        {
          "title": "European Commission launches public consultation on draft implementing act under ‘AI Act’",
          "url": "https://agenceurope.eu/en/bulletin/article/13958/18/european-commission-launches-public-consultation-on-draft-implementing-act-under-ai-act"
        },
        {
          "title": "AI Governance & Risk Brief - October 2026 - Quantidal",
          "url": "https://quantidal.substack.com/p/ai-governance-and-risk-brief-october"
        },
        {
          "title": "AI and copyright in the EU: is the current framework fit for purpose? - Stevens & Bolton LLP",
          "url": "https://www.stevens-bolton.com/insights/102o6a6/ai-and-copyright-in-the-eu-is-the-current-framework-fit-for-purpose/"
        },
        {
          "title": "EU AI Act Copyright Consultation Open, Nov 3 Deadline",
          "url": "https://techjacksolutions.com/ai-brief/eu-ai-act-copyright-consultation-gpai-november-deadline/"
        },
        {
          "title": "EU AI Act 2026: what applies now, deadlines and fines",
          "url": "https://bullquill.com/eu-ai-act-after-digital-omnibus-what-applies-now/"
        },
        {
          "title": "The EU AI Act Has One Rulebook and 27 Referees. Nine Haven't Shown Up.",
          "url": "https://imiel.dev/blog/eu-ai-act-2026-q3-teardown"
        },
        {
          "title": "EU AI copyright consultation 3 November: Deadline Guide",
          "url": "https://aiera.blog/eu-ai-copyright-consultation-3-november-deadline/"
        }
      ]
    },
    "I found no consultation that opened or closed on November 2, 2026. The closest matches are two open Commission consultations on AI, both tied to the digital agenda:\n\n- **Penalty procedures for the AI Act:** The Commission opened a consultation on 12 October 2026 on a draft implementing act for penalty proceedings under the AI Act, running until 9 November, on a draft regulation setting out the practical arrangements for the penalty procedures. Another source says adoption is planned for the fourth quarter of 2026.\n- **AI and copyright:** A targeted copyright consultation opened on 29 September 2026 and closes on 3 November 2026, which is today. It covers Article 53 obligations and the text-and-data-mining framework, so verify the closing date on the Commission's portal before relying on it.\n\nBackground on the digital and AI omnibus: the Commission proposed the Digital Omnibus on 19 November 2025, a
… [581 more characters in events.jsonl]

{
  "query": "OpenAI appoints Dan Driscoll Senior Counselor National Security Modernization",
  "mode": "extended"
}

{
  "query": "OpenAI appoints Dan Driscoll Senior Counselor National Security Modernization",
  "results": [
    {
      "tool_use_id": "srvtoolu_012mCZVdqdwLXTQWXr5K1RUx",
      "content": [
        {
          "title": "OpenAI appoints Dan Driscoll as Senior Counselor for National Security Modernization",
          "url": "https://openai.com/index/dan-driscoll-joins-openai/"
        },
        {
          "title": "OpenAI hires former U.S. Army Secretary Dan Driscoll for national security role",
          "url": "https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html"
        },
        {
          "title": "OpenAI taps former US army secretary Dan Driscoll for national security role",
          "url": "https://finance.yahoo.com/technology/ai/articles/openai-taps-former-us-army-000443626.html"
        },
        {
          "title": "OpenAI appoints former army secretary Dan Driscoll to lead national security strategy (OPENAI:Private)",
          "url": "https://seekingalpha.com/news/4663130-openai-appoints-former-army-secretary-dan-driscoll-to-lead-national-security-strategy"
        },
        {
          "title": "OpenAI Hires Dan Driscoll, Former Trump Appointee at Pentagon",
          "url": "https://gizmodo.com/openai-hires-former-trump-admin-army-secretary-for-new-national-security-role-2000834160"
        },
        {
          "title": "OpenAI taps former US army secretary Dan Driscoll for national security role By Reuters",
          "url": "https://www.investing.com/news/stock-market-news/openai-taps-former-us-army-secretary-dan-driscoll-for-national-security-role-4993247"
        },
        {
          "title": "OpenAI appoints former Army Secretary Dan Driscoll to new national security role · Digg",
          "url": "https://digg.com/world-business/18heh3n8"
        },
        {
          "title": "OpenAI names former US army secretary for national security role",
          "url": "https://www.anews.com.tr/world/2026/11/03/openai-names-former-us-army-secretary-for-national-security-role"
        },
        {
          "title": "OpenAI hires former US Army Secretary Dan Driscoll for new national security role - Türkiye Today",
          "url": "https://www.turkiyetoday.com/business/openai-hires-former-us-army-secretary-dan-driscoll-for-new-national-security-role-3231593"
        }
      ]
    },
    "OpenAI has created a new role, Senior Counselor for National Security Modernization, and filled it with former Army Secretary Dan Driscoll. The announcement was made Monday, November 2, 2026.\n\n- **Role:** He will work with senior leadership and external partners to advise on how advanced AI can strengthen national and cyber security. He will also help internal OpenAI teams understand the operational needs of global national security institutions.\n- **Background:** He previously served as the 26th Secretary of the Army, overseeing the service's operations, modernization, and resources. He gained prominence outside the Pentagon when he was tapped by President Trump to take part in talks with Moscow and Kyiv to end the war in Ukraine.\n- **Departure from the Pentagon:** Sources differ on timing. One says he reportedly resigned from his Pentagon role under unfriendly circumstances in August. Another says he had resigned earlier this year following months of tension with Defense Secretary Pete Hegseth.\n- **Company framing:** Sam Altman said the hire would help the U.S. as it has an \"extraordinary opportunity to work with other countries to spread the adoption of democratic AI.\""
  ],
  "durationSeconds": 6.110505762999994,
  "searchCount": 1
}

{
  "query": "Anthropic junk rating credit agencies IPO Financial Times November 2026",
  "mode": "extended"
}

{
  "query": "Anthropic junk rating credit agencies IPO Financial Times November 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01YQvSgqR8UW7C6pmXQANYxK",
      "content": [
        {
          "title": "Anthropic expected to receive high ‘junk’ rating from credit agencies following IPO, FT report says",
          "url": "https://finance.yahoo.com/technology/ai/articles/anthropic-expected-receive-high-junk-215203788.html"
        },
        {
          "title": "Anthropic expected to receive high 'junk' rating from credit agencies following IPO, FT report says",
          "url": "https://techcrunch.com/2026/10/30/anthropic-expected-to-receive-high-junk-rating-from-credit-agencies-following-ipo-report-says/"
        },
        {
          "title": "The Kobeissi Letter on X: \"BREAKING: Anthropic is now expected to receive a \"high junk\" rating from major credit rating agencies after its IPO, which could come as soon as November, per FT. Details include: 1. Blackstone has told investors that Anthropic likely will not receive an investment-grad… / X",
          "url": "https://x.com/KobeissiLetter/status/2116228648978055455"
        },
        {
          "title": "Blackstone now expects Anthropic to get a 'high junk' credit rating after its IPO",
          "url": "https://dealroom.co/news/168608-blackstone-now-expects-anthropic-to-get-a-high-junk-credit-rating-after/"
        },
        {
          "title": "Anthropic faces higher borrowing risk after Blackstone flags junk rating post-IPO",
          "url": "https://tradersunion.com/news/institutions/show/4040186-anthropic-junk-rating-ipo-risk/"
        },
        {
          "title": "Wall Street Just Cast a Big Doubt on Anthropic’s $800 Billion AI Bet",
          "url": "https://beincrypto.com/blackstone-anthropic-junk-rating-ipo-doubt/"
        },
        {
          "title": "Anthropic Expected to Receive High Junk Credit Rating After IPO, FT Reports",
          "url": "https://theaiinsider.tech/2026/11/02/anthropic-expected-to-receive-high-junk-credit-rating-after-ipo-ft-reports/"
        },
        {
          "title": "Anthropic IPO Could Receive Junk Credit Rating Despite $800 Billion AI Spending Plan",
          "url": "https://coinpedia.org/crypto-live-news/anthropic-ipo-could-receive-junk-credit-rating-despite-800-billion-ai-spending-plan/"
        },
        {
          "title": "Anthropic Debt Now Priced at Junk After Blackstone Reverses Investment-Grade Guidance",
          "url": "https://www.techtimes.com/articles/329858/20261102/anthropic-debt-now-priced-junk-after-blackstone-reverses-investment-grade-guidance.htm"
        }
      ]
    },
    "The Financial Times reported on October 30, 2026, that Blackstone now expects Anthropic to receive a junk rating after its IPO. Sources agree on the core facts:\n\n- **The forecast:** Blackstone, which anchors a $63 billion chip financing for Anthropic, told investors it expects a double-B rating, the top tier of junk. That reverses its earlier view that Anthropic would reach investment grade before 2027 (Blackstone has told investors that Anthropic is expected to receive a \"high\" junk credit rating, in the double-B range, after its IPO, the Financial Times reported on 30 October. That reverses Blackstone's earlier guidance).\n- **Why it matters:** A junk rating would raise Anthropic's borrowing costs as it takes on large compute commitments, and it would narrow the pool of institutional buyers for its debt (A junk rating would make borrowing more expensive for Anthropic just as it takes on large long-term compute commitments, and it shrinks the pool of buyers for its debt).\n- **Status:** The major agencies have not formally rated Anthropic yet. Kroll Bond Rating Agency (KBRA) gave Anthropic a BB+ in June, one notch below the line.\n- **IPO timing:** Reports differ on timing. One source says the Nasdaq listing expected in mid-November, while another says the IPO could come as soon as November.\n- **Comment:** TechCrunch reached out to Anthropic and Blackstone but both declined to comment."
  ],
  "durationSeconds": 7.078622571000015,
  "searchCount": 1
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{
  "url": "https://www.reedsmith.com/our-insights/blogs/technology-law-dispatch/102o6as/eu-ai-act-the-ai-office-sends-its-first-requests-for-information-to-leading-ai/",
  "prompt": "Date of post, date the AI Office sent requests, which providers, legal basis, deadlines, and what information was requested."
}

{
  "bytes": 203557,
  "code": 200,
  "codeText": "OK",
  "result": "**Date of post:** 26 October 2026\n\n**Date RFIs sent:** The article does not give an exact sending date. Executive Vice-President Henna Virkkunen announced on 14 October 2026 that the AI Office had sent them.\n\n**Providers:** Not named. The article refers only to \"leading AI providers\" and providers of \"the most advanced models around the world.\"\n\n**Legal basis:** The article says this is the first use of the AI Office's investigative powers under the AI Act, which became effective on 2 August 2026. It does not cite a specific article for the RFIs. The penalty procedural rules in Articles 75c–75d are a separate, draft implementing act under public consultation.\n\n**Deadlines:** None are stated for responses to the RFIs. The consultation on the draft penalty implementing act runs from 12 October to 9 November 2026.\n\n**Information requested:** Three areas:\n- Security practices\n- External evaluation of GPAI models\n- Post-market monitoring of how the models are used\n\n**Trigger:** Security incidents in which AI agents from the addressed providers breached external systems during testing.",
  "durationMs": 6551,
  "url": "https://www.reedsmith.com/our-insights/blogs/technology-law-dispatch/102o6as/eu-ai-act-the-ai-office-sends-its-first-requests-for-information-to-leading-ai/"
}

{
  "url": "https://www.insurancejournal.com/news/national/2026/11/02/891163.htm",
  "prompt": "Date, how many data center ballot measures, which states, specific measures and numbers, and source of the count."
}

{
  "bytes": 103687,
  "code": 200,
  "codeText": "OK",
  "result": "**Date:** The article was published November 2, 2026. The vote is on November 3, 2026.\n\n**Count:** More than 40 data center-related measures. The source is a Bloomberg analysis of Ballotpedia data.\n\n**States:** Nevada, Georgia, Ohio, California, Oklahoma, North Dakota, Wisconsin, and Arkansas (the Arkansas vote is in December).\n\n**Specific measures:**\n- **Alhambra, CA:** Would ban data centers outright.\n- **Ohio:** About a dozen communities will vote on bans, mostly targeting larger facilities.\n- **Piqua, OH:** Recall of the mayor and two city commissioners who backed AI infrastructure. Meta is trying to build a data center there.\n- **Yukon, OK:** Recall of Mayor Brian Pillmore, who supports a proposed $1 billion data center.\n- **Harwood, ND:** Charter amendment (Article X) seeking disclosure, independent review, and public participation for large projects. A $3 billion Applied Digital project is nearby.\n- **Grove City, OH:** Charter amendment requiring a referendum on developments above certain size, water, and energy thresholds.\n- **Janesville, WI:** Referendum on projects costing more than $450 million at a former GM site.\n- **Wilmington, OH:** Vote on rezoning land around a proposed Amazon data center.\n- **Boulder City, NV:** Vote on allowing data centers on a city-owned tortoise preserve. Activists previously blocked a $3 billion proposal there.\n- **Clarksville, AR:** December vote on $55 billion in bond ordinances for a ServerFarm data center.\n- **Coweta County, GA:** Petition with over 14,000 signatures to overturn approval of a $17 billion campus and ban future data centers. It could reach a January ballot, pending a judge's decision.\n\n**Other figures cited:**\n- A Quinnipiac poll found 72% of voters would oppose a new data center in their community, up from 65% in March.\n- Data Center Watch reported at least 45 projects worth $68 billion were disrupted by local opposition in Q2 2026. This is a separate source from the ballot count.",
  "durationMs": 8317,
  "url": "https://www.insurancejournal.com/news/national/2026/11/02/891163.htm"
}

{
  "command": "echo \"=== CNBC DRISCOLL ===\"; node scripts/fetch.js \"https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html\" 2>&1 | sed -n '1,55p'",
  "description": "Fetch CNBC OpenAI Driscoll article"
}

{
  "stdout": "=== CNBC DRISCOLL ===\nHTTP 200 · https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html · text/html\nOpenAI hires Dan Driscoll for national security role\nSkip Navigation\nMarkets\nBusiness\nInvesting\nTech\nPolitics & Policy\nVideo\nWatchlist\nInvesting Club\nPRO\n\nLivestream\n\nMenu\n\nKey Points\n\n- Driscoll will join OpenAI as senior counselor for national security modernization, the company said.\n\n- He will advise OpenAI's leadership on AI applications in national security and cyber security, according to the company.\n\n- Driscoll resigned as Army secretary following reported tensions with Defense Secretary Pete Hegseth, Reuters reported.\n\nIn this article\n\n- OPENAI.FG\n\nFollow your favorite stocks CREATE FREE ACCOUNT\n\nWEST POINT, NEW YORK - MAY 23: Secretary of the Army Dan Driscoll arrives for the United States Military Academy commencement ceremony in Michie Stadium at the U.S. Military Academy on May 23, 2026 in West Point, New York. U.S. Secretary of War Pete Hegseth was announced as the 2026 commencement speaker just two days before the event. (Photo by Adam Gray/Getty Images)\nAdam Gray | Getty Images News | Getty Images\n\nOpenAI has hired former U.S. Army Secretary Dan Driscoll as senior counselor for national security modernization, a newly created role at the company .\nDriscoll will focus on how artificial intelligence can be used to strengthen U.S. national security and cybersecurity, OpenAI said, while his updated LinkedIn profile also lists his new position.\n\nHe will work with OpenAI's senior leadership and external partners, with a particular focus on helping U.S. allies adopt advanced AI responsibly.\nOpenAI CEO Sam Altman said the U.S. has \"an extraordinary opportunity to work with other countries to spread the adoption of democratic AI,\" and that Driscoll's appointment would help strengthen American leadership in the technology.\n\"National security requirements are changing faster than at any time in the past fifty years,\" Driscoll said. He added that AI could help reduce paperwork, process information and deliver answers more quickly to those working in national security.\n\nI'm joining OpenAI to help the U.S. and our allies put this technology to work responsibly, for the people who keep us safe.\n\nDan Driscoll\nSenior Counselor, OpenAI\n\nThe appointment comes after Driscoll stepped down as Army secretary earlier this year after months of reported tensions with Defense Secretary Pete Hegseth.\nAn Iraq war veteran, Driscoll pushed efforts to modernize the U.S. military, including expanding access to drone and counter-drone technologies among U.S. allies, according to a previous U.S. Army announcement.\n\nDriscoll also met with Ukrainian President Volodymyr Zelenskyy in Kyiv in November 2025 to discuss a U.S.-proposed peace plan aimed at ending the war with Russia, according to a statement from the Presidential Office of Ukraine.\nAt OpenAI, Driscoll will work with government officials, industry leaders, academic institutions and allied organizations to advance what the company calls \"democratic AI.\" He will also help internal teams understand the operational needs of national security institutions, building on OpenAI's efforts to strengthen cyber resilience and protect essential services through its Daybreak program .\n\nChoose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "url": "https://api-docs.deepseek.com/news",
  "prompt": "List all news items with titles and dates, newest first."
}

{
  "bytes": 51222,
  "code": 200,
  "codeText": "OK",
  "result": "The page doesn't include a list of news items, and it doesn't show any titles or dates for them. It has only:\n\n- A **News** navigation link pointing to `/news/news261017`, with no title or date shown.\n- A top banner saying \"Search / Fetch API is now available,\" with no date.\n\nTo get the full list, visit the News section of the DeepSeek API Docs or the Change Log at `/updates`.",
  "durationMs": 3894,
  "url": "https://api-docs.deepseek.com/news"
}

{
  "url": "https://www.microsoft.com/en-us/research/feed/",
  "prompt": "List items with titles, links and dates from Nov 1-3 2026."
}

{
  "bytes": 314465,
  "code": 200,
  "codeText": "OK",
  "result": "No items in the feed are dated November 1–3, 2026. The most recent entry is dated October 30, 2026, and the feed's last build date is also October 30. Here are the most recent items:\n\n1. **From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence** (Research Blog, Oct 30, 2026)\n   https://www.microsoft.com/en-us/research/blog/from-synthetic-enterprise-data-evaluations-to-real-microsoft-copilot-ai-confidence/\n\n2. **Microsoft Research Focus – Edition #97** (Podcast, Oct 29, 2026)\n   https://www.microsoft.com/en-us/research/podcast/microsoft-research-focus-edition-97/\n\n3. **Flint-interactive: A language for creating interactive data visualizations** (Research Blog, Oct 22, 2026)\n   https://www.microsoft.com/en-us/research/blog/flint-interactive-a-language-for-creating-interactive-data-visualizations/\n\n4. **Solving a 31-year-old grand challenge in mathematics – the KLS conjecture** (Research Blog, Oct 21, 2026)\n   https://www.microsoft.com/en-us/research/blog/solving-a-31-year-old-grand-challenge-in-mathematics-the-kls-conjecture/\n\n5. **Called to serve: Tech, research, and positive impact** (Podcast, Oct 20, 2026)\n   https://www.microsoft.com/en-us/research/podcast/called-to-serve-tech-research-and-positive-impact-with-chris-white/\n\n[WebFetch note: this page's text is 313635 characters long and the answer above covers only characters 0 to 100000; the final 213635 were not read — to read on, call WebFetch again with the same url and offset: 100000.]",
  "durationMs": 5094,
  "url": "https://www.microsoft.com/en-us/research/feed/"
}

{
  "url": "https://www.utilitydive.com/",
  "prompt": "List headlines with dates from Nov 2-3 2026 related to data centers, AI load, power deals."
}

{
  "bytes": 290817,
  "code": 200,
  "codeText": "OK",
  "result": "**No headlines in the page are dated Nov. 2-3, 2026.** The only dated items are from Oct. 26-27, 2026, and the page doesn't show a publication date for most stories. Here are the related items, with the dates the page does show:\n\n**Dated (closest to the requested range):**\n- Oct. 27, 2026: \"Reliability standards for AI data centers, crypto miners move closer to adoption.\" NERC's board voted to adopt standards for AI data centers and other computational loads, which now go to FERC.\n- Oct. 26, 2026: \"Clean energy groups, states oppose MISO's large load-generation study plan.\" The article covers a fast-track study process for large loads with generation.\n\n**Related but undated on the page:**\n- \"AEP increases investment plan 30% on generation, transmission spending\" (AEP's contracted large loads rose 22%, to 84 GW)\n- \"FirstEnergy data center pipeline increases to 26 GW in Q3\"\n- \"Data center purchases of electrical equipment up 80% since 2025: Hubbell\"\n- \"CMS Energy CEO predicts data center 'progress' after midterms\"\n- \"Exelon eyes $8B in energy storage, partly to address PJM supply crunch\"\n- \"DOE announces $10.1B in loans to Constellation, Alliant, for 3.7 GW\"\n- \"NextEra Energy secures $5.7B to support federal energy 'hub' projects\"\n\nA \"What We're Reading\" item links to a New York Focus article with a 2026/11/02 URL, but it concerns National Grid's Long Island gas plans, not data centers or AI load. For Nov. 2-3 coverage, check the Utility Dive site's date-filtered archive or a later snapshot of this page.",
  "durationMs": 6466,
  "url": "https://www.utilitydive.com/"
}

{
  "url": "https://moonshotai.github.io/",
  "prompt": "List all posts with titles and dates, newest first."
}

{
  "bytes": 883,
  "code": 200,
  "codeText": "OK",
  "result": "The page content contains no posts, titles, or dates. It only shows a redirect message (\"Redirecting...\") and a link to https://www.moonshot.cn/.",
  "durationMs": 2042,
  "url": "https://moonshotai.github.io/"
}

{
  "url": "https://semianalysis.com/",
  "prompt": "List all articles with titles and dates, newest first."
}

{
  "bytes": 216458,
  "code": 200,
  "codeText": "OK",
  "result": "The page content doesn't include any articles, titles, or dates. It contains navigation menus, product descriptions, login and subscription prompts, cookie consent text, and footer links.\n\nIt does mention a few research products by name, but none have dates:\n\n- Accelerator & HBM Model\n- Datacenter Industry Model\n- Tokenomics Model\n- Consulting and technical due diligence\n- API access\n- STEEL Lab and Core Research (listed as sections, with no details)\n\nThe page links to an article archive at newsletter.semianalysis.com/archive, which sorts by date and includes a \"Popular\" view. That archive would be the place to get a full, dated list of articles.",
  "durationMs": 3791,
  "url": "https://semianalysis.com/"
}

{
  "url": "https://allenai.org/blog",
  "prompt": "List all blog posts with titles and dates, newest first."
}

{
  "bytes": 1138271,
  "code": 200,
  "codeText": "OK",
  "result": "Here are the blog posts shown on the page, newest first:\n\n1. October 27, 2026: \"Can we trust LLMs to judge whether a research idea is novel?\"\n2. October 23, 2026: \"LitPivot: Developing research ideas through dynamic contextualization within the literature landscape\"\n3. October 22, 2026: \"OlmoEarth v1.3: State-of-the-art embeddings for the whole planet\"\n4. October 22, 2026: \"A crop-mapping benchmark for the tropics\"\n5. October 20, 2026: \"FairStress: A deeper evaluation of fairness in LLM decision-making\"\n6. October 14, 2026: \"HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost\"\n7. October 9, 2026: \"Impactful scheduling for GPU clusters\"\n8. October 7, 2026: \"Now in Nature: Retrofitting language models to operate over bytes\"\n9. October 2, 2026: \"Open-sourcing AstaBrief, the fast report-generation model in Asta\"\n\nThe page is paginated (\"Previous 1-9 Next\"), and the content was truncated, so there may be more posts on later pages that aren't shown here.",
  "durationMs": 5349,
  "url": "https://allenai.org/blog"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && for c in 0 30 60 90; do curl -s \"https://api.biorxiv.org/details/biorxiv/2026-11-02/2026-11-02/$c\" -o b_$c.json; done; python3 -I -c \"\nimport json,glob\nseen=set()\nfor f in ['b_0.json','b_30.json','b_60.json','b_90.json']:\n    d=json.load(open(f))\n    print(d.get('messages'))\n    for c in d.get('collection',[]):\n        t=c.get('title','')\n        if t in seen: continue\n        seen.add(t)\n        if any(k in (t+c.get('abstract','')).lower() for k in ['artificial intelligence','machine learning','large language model','deep learning','foundation model','language model','alphafold','protein design','generative model']):\n            print('|',t,'|',c.get('doi'),'|',c.get('category'))\n\" 2>&1 | head -60",
  "description": "Query bioRxiv for Nov 2 AI preprints"
}

{
  "stdout": "[{'status': 'ok', 'category': 'all', 'interval': '2026-11-02:2026-11-02', 'cursor': 0, 'count': 30, 'count_new_papers': '216', 'total': '284'}]\n| Convergent genome- and gene-level constraints shape repeated environmental adaptation in grasses | 10.64898/2026.06.01.729361 | evolutionary biology\n| RegEvol: detection of directional selection in regulatory sequences through phenotypic predictions and phenotype-to-fitness functions | 10.1101/2025.11.26.690685 | evolutionary biology\n[{'status': 'ok', 'category': 'all', 'interval': '2026-11-02:2026-11-02', 'cursor': '30', 'count': 30, 'count_new_papers': '216', 'total': '284'}]\n| A Unique Promoter Architecture Defines Menin-KMT2A Complex Selectivity | 10.64898/2026.10.30.763078 | molecular biology\n[{'status': 'ok', 'category': 'all', 'interval': '2026-11-02:2026-11-02', 'cursor': '60', 'count': 30, 'count_new_papers': '216', 'total': '284'}]\n| Quantitative imaging of native tissue architecture combined with deep multi-omics reveals the spatial biology of kidney aging | 10.64898/2026.10.28.762545 | physiology\n| Diffusion-Based Synthetic Pretraining for Root Segmentation in Rhizotron Images | 10.64898/2026.10.30.763050 | plant biology\n[{'status': 'ok', 'category': 'all', 'interval': '2026-11-02:2026-11-02', 'cursor': '90', 'count': 30, 'count_new_papers': '216', 'total': '284'}]\n| Machine learning guided design of strong transcriptional activation domains | 10.64898/2026.10.30.763198 | synthetic biology",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false,
  "bashEditDiff": {
    "files": [],
    "moreFiles": 2,
    "changedFiles": [
      "/home/user/ainews/trace/2026-11-03.jsonl",
      "/home/user/ainews/trace/2026-11-03.transcript.jsonl"
    ],
    "unavailable": true,
    "shared": true
  }
}

{
  "url": "https://www.isomorphiclabs.com/articles",
  "prompt": "List articles with dates, especially anything dated November 2026."
}

{
  "bytes": 0,
  "code": 404,
  "codeText": "Not Found",
  "result": "The server returned HTTP 404 Not Found.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 554,
  "url": "https://www.isomorphiclabs.com/articles"
}

{
  "url": "https://hnrss.org/frontpage",
  "prompt": "List all items with titles, links and dates."
}

{
  "bytes": 27377,
  "code": 200,
  "codeText": "OK",
  "result": "Here are the 20 items from the Hacker News front page feed:\n\n1. \"Revolut moves to self-hosted GLM\". https://twitter.com/guilleflorvs/status/2117379073785696395 (Tue, 03 Nov 2026 09:53:59 +0000)\n2. \"uBlock Origin filter to block autoplay videos in TechCrunch\". https://cornfieldlabs.github.io/posts/ublock-stop-techcrunch-autoplay-video/post.html (Tue, 03 Nov 2026 07:36:47 +0000)\n3. \"Nvidia – open-source auto-ontology\". https://github.com/NVIDIA/auto-ontology (Tue, 03 Nov 2026 07:04:50 +0000)\n4. \"Show HN: I built a little browser game to practice Vim commands\". https://hjkl.duy.run (Tue, 03 Nov 2026 03:10:04 +0000)\n5. \"Open-Source 5G Ran Platforms: A Dual Perspective on Performance and Capabilities\". https://arxiv.org/abs/2608.25820 (Tue, 03 Nov 2026 02:58:44 +0000)\n6. \"Show HN: Hacker Times, a New York Times-inspired version of Hacker News\". https://hackertimes.ca/ (Tue, 03 Nov 2026 01:53:34 +0000)\n7. \"DiscImageStudio: burn visible artwork onto CDs, DVDs and Blu-ray discs\". https://github.com/JiaFeiMiao-K-Cat/DiscImageStudio (Tue, 03 Nov 2026 01:33:43 +0000)\n8. \"Scaling Git at OpenAI\". https://openai.com/index/scaling-git-at-openai/ (Mon, 02 Nov 2026 23:47:56 +0000)\n9. \"The SEC Should Block Anthropic's IPO to Protect the Public\". https://www.techpolicy.press/the-sec-should-block-anthropics-ipo-to-protect-the-public/ (Mon, 02 Nov 2026 22:30:47 +0000)\n10. \"SLAC researchers find proof of altermagnetism, a new magnetic phase\". https://www6.slac.stanford.edu/news/2026-10-29-slac-researchers-find-proof-altermagnetism-new-magnetic-phase (Mon, 02 Nov 2026 21:42:25 +0000)\n11. \"Egoless Mathematics in the AI Era\". https://terrytao.wordpress.com/2026/11/02/egoless-mathematics-in-the-ai-era/ (Mon, 02 Nov 2026 18:54:44 +0000)\n12. \"Ubuntu still has not released patch for Linux 0day RCE in almost 3 weeks\". https://freenode.net/article/ubuntu-lts-kernels-still-unfixed-for-critical-cve-2026-98432 (Mon, 02 Nov 2026 18:39:38 +0000)\n13. \"Astra can read and write weights to improve Qwen\". https://rikiyat.github.io/blog/weight-space-programming/ (Mon, 02 Nov 2026 18:21:28 +0000)\n14. \"Self-Employed? Solopreneur? NIST Has a Cybersecurity Guide Just for You\". https://www.nist.gov/news-events/news/2026/11/self-employed-solopreneur-nist-has-cybersecurity-guide-just-you (Mon, 02 Nov 2026 17:47:40 +0000)\n15. \"Polyend releases the Tracker firmware source code\". https://polyend.com/whats-up/tracker-the-biggest-update-yet/ (Mon, 02 Nov 2026 17:20:13 +0000)\n16. \"Show HN: Subvocal – Talk to your computer without making noise\". https://news.ycombinator.com/item?id=50340088 (Mon, 02 Nov 2026 17:16:17 +0000)\n17. \"Launch HN: Momentic (YC W24) – Agents that catch bugs by using your app\". https://momentic.ai/ (Mon, 02 Nov 2026 17:05:25 +0000)\n18. \"US boy names that became girl names and vice versa\". https://namedaisy.com/blog/boy-names-that-became-girl-names (Mon, 02 Nov 2026 16:34:36 +0000)\n19. \"Show HN: Warsaw in voxels – An interactive 3D map of the city centre\". https://p.migdal.pl/warsaw-vibe-voxel/ (Mon, 02 Nov 2026 16:25:26 +0000)\n20. \"Ask HN: Who is hiring? (November 2026)\". https://news.ycombinator.com/item?id=50338728 (Mon, 02 Nov 2026 16:01:37 +0000)",
  "durationMs": 9623,
  "url": "https://hnrss.org/frontpage"
}

{
  "query": "AI scribe ambient documentation study results November 2026 health system",
  "mode": "extended"
}

{
  "query": "AI scribe ambient documentation study results November 2026 health system",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Ac2a3o7koXQuxeBPynCwE5",
      "content": [
        {
          "title": "Frontiers",
          "url": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1874919/full"
        },
        {
          "title": "Ambient Artificial Intelligence Scribes: A Pilot Survey of Perspectives on the Utility and Documentation Burden in Palliative Medicine",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12427878/"
        },
        {
          "title": "Barriers and opportunities of scaling ambient AI scribes for clinical documentation across diverse healthcare settings",
          "url": "https://www.nature.com/articles/s41746-026-02554-0"
        },
        {
          "title": "6 Health Systems Enhancing Care Delivery with Ambient AI Scribes",
          "url": "https://www.aha.org/aha-center-health-innovation-market-scan/2026-04-14-6-health-systems-enhancing-care-delivery-ambient-ai-scribes"
        },
        {
          "title": "AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12316405/"
        },
        {
          "title": "Improving Clinical Documentation with AI: A Comparative Study of Sporo AI Scribe and GPT-4o mini",
          "url": "https://arxiv.org/pdf/2410.15528"
        },
        {
          "title": "Evaluating an Ambient Artificial Intelligence Scribe for Documentation Quality and Efficiency in Psychiatric Consultations: A Simulation-based Study",
          "url": "https://www.medrxiv.org/content/10.1101/2025.09.21.25336260.full.pdf"
        },
        {
          "title": "JMIR Medical Informatics - Impact of an Ambient AI Scribe Among Clinicians and Patients: Real-World Prospective Observational Time-Motion Study",
          "url": "https://medinform.jmir.org/2026/1/e85580"
        },
        {
          "title": "Patient Attitudes Toward Ambient Voice Technology: Preimplementation Patient Survey in an Academic Medical Center",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12699246/"
        },
        {
          "title": "Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout",
          "url": "https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2839542"
        }
      ]
    },
    "I ran one search. None of the results are clearly dated to November 2026, so treat this as a snapshot of recent work rather than a month-specific roundup.\n\n- **Largest recent deployment:** A Frontiers study of a Spanish outpatient deployment (September 2024 to December 2025) reported that scribe use grew to about 31% of outpatient consultations and passed 2.33 million encounters. The authors describe clinician experience as improved, with the benefit varying by specialty and usage intensity. Ambient AI documentation scaled from 2.7% to roughly 31% of all outpatient consultations. The effect on efficiency seems to depend on clinical context and stage of adoption.\n- **Multicenter burnout study:** A JAMA Network Open quality improvement study of 263 ambulatory clinicians across six systems found burnout fell from 51.9% to 38.8% after 30 days of use. Burnout among those working in ambulatory clinics decreased significantly from 51.9% to 38.8%.\n- **Time savings are modest and mixed:** A JAMA study across five academic medical centers reported small reductions in documentation time. Total EHR time fell by 13.4 minutes and documentation time by 16.0 minutes. A JMIR time-motion study in Asia found a smaller effect, with a 15.0% reduction in documentation time per consultation, and its authors noted that ambient scribes should not be expected to increase clinic throughput or patient volume at the system level.\n- **Intermountain counterpoint:** A review notes that Intermountain Health's matched cohort study reported no statistically significant productivity gains.\n- **Outcomes evidence is thin:** A review in npj Digital Medicine observed that studies of ambient scribes have mainly focused on clinician efficiency, well-being, time savings, and costs, with no evidence yet of improved clinical or patient-centered outcomes.\n- **Accuracy concerns:** A patient survey at UC Davis Health found that 39% of comments about the AI scribe expressed concerns about documentation accuracy. A psychiatry simulation study also reported favorable workload results, but it was small and conducted in a simulated setting.\n\nBottom line: the recent evidence consistently shows reduced documentation burden and some burnout improvement, but time savings are modest, productivity gains are inconsistent, and clinical outcome data are still limited. A targeted search for news dated November 2026 would be needed to find the most current results."
  ],
  "durationSeconds": 7.899779388000025,
  "searchCount": 1
}

{
  "query": "Korea AI Framework Act Japan Brazil AI law November 2026 enforcement",
  "mode": "extended"
}

{
  "query": "Korea AI Framework Act Japan Brazil AI law November 2026 enforcement",
  "results": [
    {
      "tool_use_id": "srvtoolu_01VxBiqqa61sk8tKj6PKgp8n",
      "content": [
        {
          "title": "Deepfake Laws and Regulations by Country",
          "url": "https://www.resemble.ai/learn/laws-and-regulations"
        },
        {
          "title": "Understanding Japan's AI Promotion Act: An \"Innovation-First\" Blueprint for AI Regulation",
          "url": "https://fpf.org/blog/understanding-japans-ai-promotion-act-an-innovation-first-blueprint-for-ai-regulation/"
        },
        {
          "title": "Artificial intelligence policy worldwide: a comparative analysis",
          "url": "https://royalsocietypublishing.org/rsos/article/13/2/242234/480264/Artificial-intelligence-policy-worldwide-a"
        },
        {
          "title": "Law / proposed law in South Korea - AI Laws of the World",
          "url": "https://intelligence.dlapiper.com/artificial-intelligence/?t=01-law&c=KR"
        },
        {
          "title": "AI Regulation in APAC: Diverging Approaches Across the Region",
          "url": "https://www.lw.com/en/insights/ai-regulation-in-apac-diverging-approaches-across-the-region"
        },
        {
          "title": "How ‘hard’ are hard laws? AI legislation, soft-law governance, and comparative lessons from South Korea and Japan - ScienceDirect",
          "url": "https://www.sciencedirect.com/science/article/pii/S2212473X26001069"
        },
        {
          "title": "An Evaluation Framework for National AI Regulation",
          "url": "https://arxiv.org/pdf/2608.15417"
        },
        {
          "title": "The Law of Stop: Interruptibility, Injunctions, and the Governance of Agentic AI",
          "url": "https://arxiv.org/pdf/2609.22882"
        },
        {
          "title": "AI Family Integration Index (AFII): Benchmarking a New Global Readiness for AI as Family",
          "url": "https://arxiv.org/pdf/2503.22772"
        }
      ]
    },
    "I ran one search. It turned up no source giving a November 2026 enforcement date for any of the three laws, so that part of your query isn't answered here.\n\n**South Korea:** This is the most concrete of the three. The AI Framework Act took effect on 22 January 2026, with an enforcement decree entering into force at the same time. The government has signaled a soft start: 2026 will effectively serve as a pilot period with limited enforcement, with a one-year grace period for penalties. One source also notes that on 20 July 2026, the Enforcement Decree (No. 36506) was amended to stipulate the details of the amendments to the AI Act.\n\n**Japan:** Japan's AI Promotion Act works differently. It does not impose any direct obligations on private actors and does not include a \"risk\" or \"high-impact\" classification of AI technologies. It also lacks any penalties for noncompliance or misuse of AI more broadly. A November 2026 enforcement milestone would be unlikely to change that structure.\n\n**Brazil:** Status is unclear in these results. One source describes Brazil's AI Bill 2338/2023 sets a risk-based framework awaiting the Chamber of Deputies, while TSE Resolution 23.732/2024 already governs election deepfakes. That source's date is not shown, so it may be outdated. Another source describes the bill only as calling for sector-specific enforcement mechanisms.\n\nFor a definitive November 2026 status, check the Korean MSIT/National Law Information Center, Japan's Cabinet Office AI materials, and Brazil's Chamber of Deputies bill tracker directly."
  ],
  "durationSeconds": 7.732123212000006,
  "searchCount": 1
}

{
  "url": "https://newsletter.semianalysis.com/archive",
  "prompt": "List the most recent articles with titles and dates."
}

{
  "bytes": 308147,
  "code": 200,
  "codeText": "OK",
  "result": "Here are the most recent articles on the SemiAnalysis archive page (all 2026):\n\n1. \"GDPx: Measuring Frontier Model Capabilities Across the Most Valuable Domains,\" Nov 2\n2. \"The Datacenter Backlash Goes Bipartisan: Next Week's Midterms and the 2028 Buildout,\" Nov 1\n3. \"Amazon's Trainium Takes a Strike at the Training King,\" Oct 23\n4. \"The Huawei-DeepSeek Symbiosis,\" Oct 21\n5. \"Datacenters 2027: The Year of Acceleration, +50GW in a Single Year,\" Oct 19\n6. \"ASML Is Building a Hybrid Bonding Tool!,\" Oct 15\n7. \"Beijing Will Not Pace the Frontier: China's Speed-First AI Safety Regime,\" Oct 8\n8. \"Anthropic Subscriptions Offer 5x+ More Value Than OpenAI,\" Oct 5",
  "durationMs": 5472,
  "url": "https://newsletter.semianalysis.com/archive"
}

{
  "query": "Revolut self-hosted GLM Z.ai open weights model production",
  "mode": "extended"
}

{
  "query": "Revolut self-hosted GLM Z.ai open weights model production",
  "results": [
    {
      "tool_use_id": "srvtoolu_01QTNhicZqBUAVuFSofUtHhB",
      "content": [
        {
          "title": "Oliver Molander on X: \"Interesting. Revolut reportedly only started seeing meaningful AI productivity gains after moving away from expensive OpenAI and Anthropic models to self-hosted GLM. Decagon reportedly runs ~90% of its workloads on open weight models. Why? Because when you're running AI ag… / X",
          "url": "https://x.com/OliverMolander/status/2116851762325757979"
        },
        {
          "title": "AGTP on X: \"Revolut just moved its ~2,000 engineers to a self-hosted open-source AI coding model. Here's what you need to know. Revolut, Europe's most valuable startup at $200B, started this year leaning on frontier labs. Its engineers used Claude Code and Codex, and some burned $1,000 to $10,000… / X",
          "url": "https://x.com/AGTPinsights/status/2117455433627566174"
        },
        {
          "title": "Revolut Cuts A.I. Coding Costs 90% With Open-Weight GLM",
          "url": "https://www.trendingtopics.eu/revolut-glm-open-weight-coding-costs/"
        },
        {
          "title": "how do i deploy glm5 in production",
          "url": "https://zilliz.com/ai-faq/how-do-i-deploy-glm5-in-production"
        },
        {
          "title": "GLM (AI)",
          "url": "https://en.wikipedia.org/wiki/GLM_(AI)"
        },
        {
          "title": "Revolut Says Self-Hosted Open AI Models Cut Its Coding Costs 90% - Startup Fortune",
          "url": "https://startupfortune.com/revolut-says-self-hosted-open-ai-models-cut-its-coding-costs-90/"
        },
        {
          "title": "Max Karpis on X: \"Revolut’s quiet bid for AI Independence: Cutting coding costs by 90% The first chapter of modern fintech was powered by smartphones, cloud computing and easier licensing. That phase is largely over. The next one is being shaped partly by artificial intelligence — specifically by… / X",
          "url": "https://x.com/maxkarpis/status/2117147467275731163"
        },
        {
          "title": "glm 5.3",
          "url": "https://openrouter.ai/z-ai/glm-5.3?endpoint=b711bea7-3994-4935-873d-fb845bd40c00"
        },
        {
          "title": "Models / ZAI",
          "url": "https://www.together.ai/models-providers/zai-org"
        }
      ]
    },
    "Revolut has reportedly moved about 2,000 engineers from Claude Code and Codex to a self-hosted GLM model, but the sources disagree on the version and most of the savings figures come from Revolut itself.\n\n- **Deployment:** Revolut's default coding assistant is now a self-hosted GLM model from Z.ai, running on its own infrastructure since spring. It runs on roughly 56 Nvidia B200 chips. One source puts the model at about 800 billion parameters, while another describes GLM 5.3 as having 753 billion parameters with 40 billion active.\n- **Version conflict:** One report says the deployment uses Zhipu AI's open-weight GLM-4.5 model. Others say GLM-5.3. I couldn't resolve which is correct.\n- **Scope and jurisdiction:** Image tasks still go to hosted models. Revolut uses only the openly available model weights and runs them on infrastructure in the United States, not through the Chinese developer's endpoint.\n- **Cost and productivity:** Revolut says its bill is about a tenth of its former OpenAI and Anthropic spend, and reports about 60% less coding time and 70% shorter lead time. According to an analysis by StartupHub.ai, the 90 percent savings exclude the costs of cloud, staff and monitoring. Treat these as Revolut's own claims. Claude and GPT stay in use for the hardest tasks.\n- **Governance:** One summary says that, as a regulated bank, Revolut runs the weights on infrastructure in approved jurisdictions and keeps coding tasks under human control via a sandbox with clear allow/deny rules.\n\nThe details come from a presentation by Revolut's AI operations head, David Abitbol, at a GTC Berlin talk, plus secondary coverage and social posts. I didn't find a primary Revolut write-up in these results."
  ],
  "durationSeconds": 6.887388782999944,
  "searchCount": 1
}

{
  "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ai/",
  "prompt": "List articles dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 0,
  "code": 403,
  "codeText": "Forbidden",
  "result": "The server returned HTTP 403 Forbidden.\n\nThe response body was not retrieved. If this URL requires authentication, use an authenticated tool (e.g. `gh` for GitHub, or an MCP-provided fetch tool) instead of WebFetch.",
  "durationMs": 268,
  "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ai/"
}

{
  "query": "STAT News AI health November 2 2026",
  "mode": "extended"
}

{
  "query": "STAT News AI health November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01C2Gx7wA3f5ZRiqVUGJSiEf",
      "content": [
        {
          "title": "STAT",
          "url": "https://www.statnews.com/"
        },
        {
          "title": "Psilocybin's lasting benefits prove elusive in mice",
          "url": "https://statnews.com/2026/11/02/biotech-news-psilocybin-lasting-benefits-prove-elusive-in-mice"
        },
        {
          "title": "AI Prognosis: Readers' predictions for health AI in 2026",
          "url": "https://www.statnews.com/2026/01/07/ai-prognosis-readers-predictions-for-health-ai-in-2026/"
        },
        {
          "title": "STAT Health Tech: FDA spells out 2027 AI guidance plans",
          "url": "https://www.statnews.com/2026/10/06/fda-spells-out-2027-ai-guidance-plans-health-tech/"
        },
        {
          "title": "Stat (website)",
          "url": "https://en.wikipedia.org/wiki/Stat_(website)"
        },
        {
          "title": "Top 100 Health Trends in November: From At-Home Cortisol Trackers to Adaptive Sleep…",
          "url": "https://trendhunter.com/slideshow/november-2026-health"
        },
        {
          "title": "Feds scramble to avoid regulatory logjam as states look to test AI in clinic",
          "url": "https://www.statnews.com/2026/10/30/fda-cms-health-ai-regulation-state-sandboxes-run-into-federal-rules/"
        },
        {
          "title": "Healthline",
          "url": "https://en.wikipedia.org/wiki/Healthline"
        },
        {
          "title": "FDA relaxes oversight of AI-enabled devices and wearables",
          "url": "https://www.statnews.com/2026/01/06/fda-pulls-back-oversight-ai-enabled-devices-wearables/"
        }
      ]
    },
    "STAT's own coverage dated November 2, 2026 has only a few AI-health items, and the search returned no full article text for them.\n\n- **Funding:** STAT's homepage lists an item on AI drug firm Pathos raises $237 million, pushing valuation to $3 billion. It is a STAT Plus (subscriber-only) piece.\n- **Epic:** A subscriber piece by Brittany Trang is titled Why every health care AI company must face Epic.\n- **State vs. federal rules (dated October 30, a few days earlier):** STAT reported that officials are moving behind the scenes to head off a conflict brewing between states and the federal government over the clinical use of artificial intelligence. The core problem is that the federal government and states have overlapping jurisdiction over AI that performs clinical work, like writing prescriptions.\n\nTwo caveats. The search results include STAT pieces dated earlier, such as an October 6 item on FDA's 2027 AI guidance plans. Also, some page \"age\" labels in the results contradict the dates printed on the articles, so check the dates on the STAT site before relying on them."
  ],
  "durationSeconds": 6.713999750000076,
  "searchCount": 1
}

{
  "url": "https://www.trendingtopics.eu/revolut-glm-open-weight-coding-costs/",
  "prompt": "Give the publication date and author, and all figures/quotes about cost savings, model, GPUs, engineer counts, productivity, and the source of the information."
}

{
  "bytes": 164406,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication details**\n- **Date:** 3 November 2026, 09:22\n- **Author:** Jakob Steinschaden, with the article co-produced by AI (Trendy AI)\n- **Publication:** Trending Topics (trendingtopics.eu)\n\n**Cost savings**\n- Revolut's bill is about a tenth of its previous spend on Anthropic and OpenAI, a roughly 90% reduction (per Revolut).\n- Self-hosted inference costs about 30 cents per million tokens (per David Abitbol).\n- Token limits were removed, and a flat bill replaced unpredictable month-end invoices.\n- StartupHub.ai notes the 90% figure excludes cloud, staff, and monitoring costs.\n\n**Model**\n- GLM, from the Chinese lab Z.ai, with about 800 billion parameters.\n- Revolut uses only the open model weights, hosted on US infrastructure rather than the developer's China endpoint.\n- Claude Code and Codex remain available as exceptions.\n- GLM handles text only; image tasks are routed to Gemini.\n- The context window is capped at 256,000 tokens.\n\n**Hardware**\n- About 56 Nvidia B200 chips.\n- Per Jensen Huang, B200 chips cost $30,000–40,000 each, or about $1.7–2.2 million for 56 chips (about €1.5–2 million).\n- Industry estimates put eight-B200 servers at $450,000–500,000. Seven such systems would cost $3.2–3.5 million (about €2.9–3.1 million), excluding power and data center costs.\n- The article does not say whether Revolut bought or rents the chips.\n\n**Engineers and productivity**\n- About 2,000 software engineers in the sample.\n- With GLM: coding time fell 60% and lead time (task pickup to merge) fell 70%.\n- Earlier, Google's Gemini cut coding time by 20% and lead time by 10%.\n- Time to first token dropped from over 10 seconds to 1.6 seconds, even as demand rose 76%.\n\n**Sources**\n- David Abitbol, who oversees AI operations and infrastructure at Revolut, in his talk \"Shipping like a startup, regulated like a bank\" at the AI Engineer conference in New York.\n- Revolut, for the cost and usage claims.\n- An analysis by StartupHub.ai, for the cost caveats.\n- Jensen Huang (Nvidia CEO), for B200 pricing.\n- Industry estimates, for server pricing.",
  "durationMs": 9048,
  "url": "https://www.trendingtopics.eu/revolut-glm-open-weight-coding-costs/"
}

{
  "url": "https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices",
  "prompt": "What is the page's last update date and the stated number of AI-enabled devices and the decision-date cutoff?"
}

{
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  "code": 301,
  "codeText": "Moved Permanently",
  "result": "REDIRECT DETECTED: The URL redirects to a location that was not fetched automatically.\n\n    Original URL: https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices\n    Redirect URL (from the server's Location header — server-supplied, not verified): http://www.fda.gov/medical-devices/artificial-intelligence-enabled-medical-devices/list-artificial-intelligence-enabled-medical-devices\n    Status: 301 Moved Permanently\n\n    To complete your request, I need to fetch content from the redirected URL. Please use WebFetch again with these parameters:\n    - url: \"http://www.fda.gov/medical-devices/artificial-intelligence-enabled-medical-devices/list-artificial-intelligence-enabled-medical-devices\"\n    - prompt: \"What is the page's last update date and the stated number of AI-enabled devices and the decision-date cutoff?\"",
  "durationMs": 409,
  "url": "https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"
}

{
  "command": "echo \"=== GUARDIAN AI ===\"; node scripts/fetch.js \"https://www.theguardian.com/technology/artificialintelligenceai\" 2>&1 | sed -n '1,70p'",
  "description": "Fetch Guardian AI section"
}

{
  "stdout": "=== GUARDIAN AI ===\nHTTP 403 · https://www.theguardian.com/technology/artificialintelligenceai · text/plain\nBlocked by egress policy",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "\"AI\" hospital health system deployment results announced November 2 2026 Epic Abridge Mayo",
  "mode": "extended"
}

{
  "query": "\"AI\" hospital health system deployment results announced November 2 2026 Epic Abridge Mayo",
  "results": [
    {
      "tool_use_id": "srvtoolu_01BkCcR88RJLdDSq1gK34xFT",
      "content": [
        {
          "title": "Top 5 Hospitals Using AI in May 2026",
          "url": "https://www.getprosper.ai/blog/hospitals-using-ai"
        },
        {
          "title": "Abridge AI Review 2026: Features, Pricing, Pros & Cons",
          "url": "https://www.trytwofold.com/compare/abridge-ai-review"
        },
        {
          "title": "Health systems moving to Epic, Oracle in 2026",
          "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ehrs/health-systems-moving-to-epic-oracle-in-2026/"
        },
        {
          "title": "Health systems begin activating Epic’s new features",
          "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ehrs/health-systems-begin-activating-epics-new-features/"
        },
        {
          "title": "Inside health systems’ early use of Epic’s newest AI tools",
          "url": "https://www.beckershospitalreview.com/healthcare-information-technology/ehrs/inside-health-systems-early-use-of-epics-newest-ai-tools/"
        },
        {
          "title": "Abridge Expands Nursing AI Platform to 250+ Health Systems - Newsweek",
          "url": "https://www.newsweek.com/ai-nurses-health-care-abridge-access-health-11921461"
        },
        {
          "title": "Epic UGM: AI Ambitions Meet Health System Reality - Newsweek",
          "url": "https://www.newsweek.com/pro/health-care/epic-ugm-ai-ambitions-meet-health-system-reality-access-health-12354400"
        },
        {
          "title": "HIMSS26: Epic expands AI roadmap, previews Factory to build and orchestrate AI agents",
          "url": "https://www.fiercehealthcare.com/ai-and-machine-learning/himss26-epic-expands-ai-roadmap-previews-factory-build-and-orchestrate-ai"
        },
        {
          "title": "Epic bets on its AI speed at UGM",
          "url": "https://www.healthcareitnews.com/news/epic-bets-its-ai-speed-ugm"
        }
      ]
    },
    "I didn't find any results dated November 2, 2026, so nothing here confirms a specific announcement that day. The closest items are older, and most are vendor-reported.\n\n- **Mayo and Abridge nursing tool:** Abridge announced that Abridge for Nurses is now generally available across its network of more than 250 health system partners. At Mayo, the tool has only fully deployed the tech on seven units, and an editor's note adds that 170 nurses across Mayo Clinic have also opted to activate Abridge for Nurses.\n- **Abridge's broader reach:** Abridge says clinicians at more than 300 enterprise health systems have adopted its decision-support capabilities since their April launch.\n- **Epic's AI rollout:** More than 85% of Epic's customers now use Epic AI, the company said. Epic also reported that clinicians at multiple organizations are completing discharge summaries 20% to 30% faster with Art's draft hospital course notes.\n- **Mayo's ambient documentation:** One vendor-oriented roundup says Mayo has an enterprise rollout of Abridge to 2,000+ clinicians (since Jan 2025), though that source is a blog post and its date is unclear.\n\nTreat the outcome figures with caution. For Abridge, one review notes that each deployment included implementation support, training, template configuration, and Epic integration work paid for by the enterprise contract. Several of these items are months old, so for anything dated November 2, 2026, a search for the specific press release or Mayo Clinic newsroom would be more reliable."
  ],
  "durationSeconds": 7.959628720000037,
  "searchCount": 1
}

{
  "query": "Huawei Ascend 960DT Samsung SK Hynix HBM smuggled memory chips The Information",
  "mode": "extended"
}

{
  "query": "Huawei Ascend 960DT Samsung SK Hynix HBM smuggled memory chips The Information",
  "results": [
    {
      "tool_use_id": "srvtoolu_01QQq3mtk4PadTe8T8mSTEh2",
      "content": [
        {
          "title": "[News] China Reportedly Obtains Smuggled HBM via Server Packages; Huawei 960DT Faces Domestic HBM Shortage",
          "url": "https://www.trendforce.com/news/2026/11/03/news-china-reportedly-obtains-smuggled-hbm-via-server-packages-huawei-960dt-faces-domestic-hbm-shortage/"
        },
        {
          "title": "Chinese Smugglers Smuggle S. Korean HBM, Claiming It's 'Patriotism' — How Do They Do It?",
          "url": "https://news.sbs.co.kr/english/article.do?news_id=N1008828674"
        },
        {
          "title": "Huawei Tells Clients Ascend 960DT Runs on Samsung, SK Hynix HBM",
          "url": "https://aiweekly.co/alerts/huawei-tells-clients-ascend-960dt-runs-on-samsung-sk-hynix-hbm"
        },
        {
          "title": "Techmeme: Sources: Huawei recently told some clients that a large share of its upcoming flagship, Ascend 960DT, will run largely on HBM made by Samsung and SK Hynix (The Information)",
          "url": "https://www.techmeme.com/261102/p50"
        },
        {
          "title": "The Information investigates the smuggling...",
          "url": "https://www.chaincatcher.com/en/article/2301287"
        },
        {
          "title": "[Report] Huawei sourcing smuggled Samsung, SK Hynix HBM for next-gen AI chips - Sammy Fans",
          "url": "https://www.sammyfans.com/2026/11/03/huawei-sourcing-smuggled-samsung-sk-hynix-hbm/"
        },
        {
          "title": "Galaxy Z Fold 8 pivots to Gen Z and women with high-profile RESCENE collaboration - Sammy Fans",
          "url": "https://www.sammyfans.com/2026/10/23/galaxy-z-fold-8-pivots-to-gen-z-and-women-with-high-profile-rescene-collaboration/"
        },
        {
          "title": "Smugglers Melt Solder to Strip Korean HBM for Huawei - Seoul Economic Daily",
          "url": "https://en.sedaily.com/international/2026/11/03/smugglers-melt-solder-to-strip-korean-hbm-for-huawei"
        },
        {
          "title": "China HBM smuggling reportedly exploits export controls",
          "url": "https://chinadailystar.com/news/china-hbm-smuggling-server-chips"
        },
        {
          "title": "Notebookcheck Logo",
          "url": "https://www.notebookcheck.net/TSMC-die-and-Samsung-memory-confirmed-in-Huawei-910C-set-to-replace-Nvidia-AI-chips.1130790.0.html"
        }
      ]
    },
    "The Information reported on November 2, 2026 that HBM from Samsung and SK hynix is being smuggled into China and routed largely to Huawei customers. The reporting comes through secondary outlets, so I could not read the original article.\n\n- **The Ascend 960DT:** Huawei reportedly told some clients that much of its next flagship AI chip will rely on Samsung and SK hynix HBM. The chip is scheduled to launch in the first quarter of 2027, but domestic HBM supply is short, and Huawei has asked some customers to procure memory on their own.\n- **The smuggling method:** Smugglers reportedly package HBM onto boards with low-end server processors and declare the shipments as processors, which is intended to avoid restrictions on exporting HBM separately. After entering China, workshops reheat and remove the HBM, while the cheap processors are discarded.\n- **Prices:** A Chinese broker told the paper that one HBM3E unit, which sold for several hundred US dollars a year ago, now costs about $4,000.\n- **Company responses:** SK hynix said it complies with US and South Korean export laws and had not supplied Huawei since US export controls took effect in 2020. Samsung's response was not included in the account I found.\n- **Caveats:** Huawei's stated performance claims for the chip have not been independently established. Reuters, citing sources, also reported that CXMT's HBM3E yields remain at just 20%–30%, well below the approximately 70% achieved by South Korea's SK hynix."
  ],
  "durationSeconds": 6.167047304000007,
  "searchCount": 1
}

{
  "query": "DeepSeek creator mode custom AI agent plugins Bloomberg November 2 2026",
  "mode": "extended"
}

{
  "query": "DeepSeek creator mode custom AI agent plugins Bloomberg November 2 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_0188z3D3GXf8heEzkLTgUuns",
      "content": [
        {
          "title": "DeepSeek is adding a creator mode to let users build custom AI plugins",
          "url": "https://qz.com/deepseek-creator-mode-custom-ai-plugins-110226"
        },
        {
          "title": "DeepSeek Launches Creator Mode to Enable AI Plugin Development via Natural Language",
          "url": "https://www.kucoin.com/news/flash/deepseek-launches-creator-mode-to-enable-ai-plugin-development-via-natural-language"
        },
        {
          "title": "DeepSeek Boosts AI Agent Offering With New Creator Mode",
          "url": "https://finance.yahoo.com/technology/ai/articles/deepseek-boosts-ai-agent-offering-171629585.html"
        },
        {
          "title": "DeepSeek Creator Mode Builds Harness Plugins From Plain Engl",
          "url": "https://www.implicator.ai/deepseek-releases-creator-mode-allows-deepseek-harness-users/"
        },
        {
          "title": "DeepSeek Harness Adds Plugin-Creation Entry for Creator Mode",
          "url": "https://www.unite.ai/deepseek-harness-adds-plugin-creation-entry-for-creator-mode/"
        },
        {
          "title": "# DeepSeek Harness: The Plugin-First AI Agent Framework",
          "url": "https://betterstack.com/community/guides/ai/deepseek-harness-plugin.md"
        },
        {
          "title": "DeepSeek adds creator mode to boost AI agent tools By Investing.com",
          "url": "https://ca.investing.com/news/stock-market-news/deepseek-adds-creator-mode-to-boost-ai-agent-tools-93CH-4923013"
        },
        {
          "title": "DeepSeek Creator Mode Lets Harness Users Build Plugins",
          "url": "https://shiftdelete.net/en/deepseek-creator-mode"
        },
        {
          "title": "DeepSeek Creator Mode Launches: Build AI Plugins Instantly",
          "url": "https://emergent.sh/news/deepseek-creator-mode-launches-build-ai"
        }
      ]
    },
    "DeepSeek launched a \"creator mode\" for its DeepSeek Harness agent platform on November 2, 2026, according to coverage that cites Bloomberg.\n\n- **What it does:** Bloomberg reported that DeepSeek has unveiled a new option to quickly create custom plugins that help users to tackle a range of complex tasks. Users describe what they want in chat, and the mode generates installable plugins that extend the tools, skills, and interface.\n- **Demos:** DeepSeek showed plugins to render 3D models as well as a video editing workbench, built from plain-English prompts. Its Harness account also listed a design workspace, a sandbox game and a 3D LLM visualizer.\n- **Audience and status:** DeepSeek's AI agent is aimed more at developers than casual users. DeepSeek calls Harness a developer preview, and warns that compatibility-breaking changes are coming, so plugins built now may need rework.\n- **Context:** Bloomberg notes that DeepSeek created the Harness team to focus on helping build AI agents that can complete with AI coding services. Separately, DeepSeek brought in roughly 100 billion yuan ($15 billion), among the biggest raises in China, as it prepares for an initial public offering.\n\nOne source (Emergent) describes the launch as Tuesday's announcement, while Bloomberg-based coverage says Monday, so the exact day is unclear. The November 2 date is consistent across most sources."
  ],
  "durationSeconds": 6.46425465899997,
  "searchCount": 1
}

{
  "url": "https://www.trendforce.com/news/2026/11/03/news-china-reportedly-obtains-smuggled-hbm-via-server-packages-huawei-960dt-faces-domestic-hbm-shortage/",
  "prompt": "Give publication date and all figures, quotes and attributions about the smuggling, prices, Huawei Ascend 960DT, HBM yields."
}

{
  "bytes": 74848,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 3, 2026 (TrendForce News, Semiconductors section)\n\n**Smuggling**\n- Per *The Information*, smugglers pack HBM chips with lower-performance server processors, exploiting rules that rate package computing power by the processor rather than the memory.\n- Once in China, technicians heat the packages to soften solder, remove the HBM stacks, and discard the processors. The report says \"The delicate process carries a high risk of damaging the memory.\"\n- Smuggled memory often reaches Huawei's customers.\n\n**Huawei Ascend 960DT**\n- Expected in Q1 2027, with memory bandwidth and capacity set to double versus Huawei's current AI processor.\n- Expected to rely heavily on HBM from Samsung Electronics and SK hynix.\n- U.S. restrictions prevent Huawei from getting enough HBM directly from those Korean suppliers, so it has reportedly asked some AI chip customers to source memory themselves (*The Information*).\n- Huawei is working with DeepSeek to optimize the chip for AI model pre-training (*The Information*).\n\n**Prices**\n- Huawei reportedly raised the suggested price of the Ascend 950DT to more than RMB 250,000 (about US$37,000), citing high memory costs and tight supply (*The Information*).\n- The 950DT delivers roughly half the raw compute of NVIDIA's H100 (launched 2022) but now costs as much as the B200, which began shipping last year (*The Information*).\n- Cambricon raised indicative pricing for its next-generation 690 chip by 20%–30%. MetaX and Iluvatar CoreX reportedly made similar increases (*Reuters*).\n\n**HBM yields**\n- CXMT's HBM3E yields are reportedly 20%–30%, versus about 70% for SK hynix (*Reuters*).\n- Fujian Jinhua Integrated Circuit, a U.S.-sanctioned memory maker that has supplied Huawei for years, trails Korean competitors technologically and lacks the capacity to meet demand (*The Information*). No yield figure is given for Fujian Jinhua.\n\n**Related context**\n- NVIDIA reportedly told cloud customers that at least 51% of their services must be sold to non-Chinese companies, requiring data center partners to reduce exposure to Chinese customers (*Financial Times*).",
  "durationMs": 7933,
  "url": "https://www.trendforce.com/news/2026/11/03/news-china-reportedly-obtains-smuggled-hbm-via-server-packages-huawei-960dt-faces-domestic-hbm-shortage/"
}

{
  "command": "cd /tmp/claude-0/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/scratchpad && curl -s \"https://api.semanticscholar.org/graph/v1/paper/DOI:10.1056/AIoa2501001?fields=title,publicationDate,journal,externalIds,venue\" | head -c 1200; echo; echo \"--- crossref retry\"; sleep 2; curl -s -H \"User-Agent: ainews/1.0 (mailto:[email redacted])\" \"https://api.crossref.org/works/10.1056/AIoa2501001\" -o cr2.json -w \"%{http_code}\\n\"; python3 -I -c \"\nimport json\nd=json.load(open('cr2.json'))['message']\nprint(d.get('title'), d.get('published'), d.get('issued'), d.get('created',{}).get('date-time'), d.get('volume'), d.get('issue'), d.get('journal-issue'))\n\" 2>&1 | head -10",
  "description": "Verify NEJM AI article publication date"
}

{
  "stdout": "{\"message\": \"Too Many Requests. Please wait and try again or apply for a key for higher rate limits. https://www.semanticscholar.org/product/api#api-key-form\", \"code\": \"429\"}\n--- crossref retry\n200\n['Automation Bias in Large Language Model–Assisted Diagnostic Reasoning among Physicians Trained in AI Literacy — A Randomized Clinical Trial'] {'date-parts': [[2026, 4, 23]]} {'date-parts': [[2026, 4, 23]]} 2026-04-23T13:00:21Z 3 5 {'issue': '5', 'published-print': {'date-parts': [[2026, 4, 23]]}}",
  "stderr": "",
  "interrupted": false,
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  "noOutputExpected": false,
  "bashEditDiff": {
    "files": [],
    "moreFiles": 1,
    "changedFiles": [
      "/home/user/ainews/trace/2026-11-03.jsonl"
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    "unavailable": true
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{
  "command": "node scripts/fetch.js \"https://www.nature.com/npjdigitalmed/articles?searchType=journalSearch&sort=PubDate\" 2>&1 | grep -n -B2 -A2 \"fatigue from speech\" | head -20",
  "description": "Find npj fatigue article link"
}

{
  "stdout": "51-\n52-#\n53:Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers\n54-\n55-- Agnes Norbury",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
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{
  "url": "https://qwen.ai/research",
  "prompt": "List all blog/research posts with titles and dates, newest first."
}

{
  "bytes": 94947,
  "code": 200,
  "codeText": "OK",
  "result": "The provided web page content contains only the word \"Qwen,\" with no blog or research posts, titles, or dates. I can't list any posts from this content. If you share the full page text or a link to the blog/research section, I can list the titles and dates, newest first.",
  "durationMs": 2661,
  "url": "https://qwen.ai/research"
}

{
  "query": "nature.com s41746 fatigue speech data shift workers Norbury Georgescu Cummins 2026",
  "mode": "standard"
}

{
  "query": "nature.com s41746 fatigue speech data shift workers Norbury Georgescu Cummins 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01YTmBsRQBY6kA1J1DkngXji",
      "content": [
        {
          "title": "Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers",
          "url": "https://www.medrxiv.org/content/10.1101/2024.06.17.24308769.full.pdf"
        },
        {
          "title": "Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models",
          "url": "https://arxiv.org/pdf/2505.23378"
        },
        {
          "title": "Exploring Workplace Behaviors through Speaking Patterns using Large-scale Multimodal Wearable Recordings: A Study of Healthcare Providers",
          "url": "https://arxiv.org/pdf/2212.09090"
        },
        {
          "title": "fatigue detection tool shift workers study",
          "url": "https://www.personneltoday.com/hr/fatigue-detection-tool-shift-workers-study"
        },
        {
          "title": "Australian Researchers Show that Speech \"Flattens\" After 24 Hours Awake",
          "url": "https://www.newswise.com/articles/measuring-fatigue-through-the-voice"
        },
        {
          "title": "talar moukhtarian uow health spotlight fighting fatigue post event write up v2",
          "url": "https://warwick.ac.uk/research/spotlights/health/news-events/fundedprojects/talar/talar-moukhtarian-uow-health-spotlight-fighting-fatigue-post-event-write-up-v2.pdf"
        },
        {
          "title": "sleepreviewmag.com",
          "url": "https://sleepreviewmag.com/?p=3954"
        },
        {
          "title": "researchers measure fatigue through the voice",
          "url": "https://sleepreviewmag.com/uncategorized/researchers-measure-fatigue-through-the-voice/"
        },
        {
          "title": "pmc.ncbi.nlm.nih.gov",
          "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC1765732"
        },
        {
          "title": "koreamed.org",
          "url": "https://synapse.koreamed.org/articles/1125864"
        }
      ]
    },
    "I didn't find the Nature paper itself (the s41746 prefix indicates an *npj Digital Medicine* article). The closest match is a medRxiv preprint by the same group, with the same title theme, from 2024. It may be an earlier version of the published work, but I can't confirm that from these results.\n\n- **The preprint:** Here, we explore the potential of speech-based fatigue measurement in a large, multi-lingual cohort, with data collected under an ecologically valid setting (as participants went about their usual working lives). It also examines to what extent different aspects of fatigue (from acute sleep deprivation state to chronic motivational difficulties) may be detectable in speech data.\n- **Study design:** A companion paper using the same shift-worker dataset reports 1,185 participants monitored over a two-week period. Participants recorded speech twice daily on their personal devices, coinciding with the start and end of their work shifts.\n- **Related work:** A UK firm, Thymia, has said it is developing a speech-based fatigue detection tool for shift workers, though that is a commercial effort rather than the research paper. The startup was awarded £50,000 in government funding, starting with a trial involving 1,000 UK shift workers.\n\nI'd suggest checking nature.com directly or searching the DOI to confirm the 2026 publication and its findings."
  ],
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{
  "query": "Intel foundry critical test stock 45% plunge October CNBC November 2026 18A 14A",
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{
  "query": "Intel foundry critical test stock 45% plunge October CNBC November 2026 18A 14A",
  "results": [
    {
      "tool_use_id": "srvtoolu_01N3gbj2aT9MGWRLkgNWg9YL",
      "content": [
        {
          "title": "Intel Shares Plunge Over Foundry Woes",
          "url": "https://www.silicon.co.uk/e-management/lay-off/intel-foundry-costs-623329/amp"
        },
        {
          "title": "Intel Shares Plunge. Is It Time to Buy the Dip?",
          "url": "https://finance.yahoo.com/news/intel-shares-plunge-time-buy-143500020.html"
        },
        {
          "title": "intel stock what effect will foundry strategy shift have morgan stanley weighs in",
          "url": "https://www.tipranks.com/news/article/intel-stock-what-effect-will-foundry-strategy-shift-have-morgan-stanley-weighs-in"
        },
        {
          "title": "Intel Stock Plunges After Weak Forecast and Mounting Yield Concerns",
          "url": "https://www.analyticsinsight.net/news/intel-stock-plunges-after-weak-forecast-and-mounting-yield-concerns"
        },
        {
          "title": "intel foundry costs 623329",
          "url": "https://www.silicon.co.uk/e-management/lay-off/intel-foundry-costs-623329"
        },
        {
          "title": "www.mexc.com",
          "url": "https://www.mexc.com/news/537238"
        },
        {
          "title": "Back to News",
          "url": "https://allmind.ai/news/4f340f787398f87936885496856a88c154616b7a47ea7f618e5e26bae1b8f732"
        },
        {
          "title": "intel stock had a banner year but is still 50 off its record highs are more gains in store for 2026",
          "url": "https://www.barchart.com/story/news/36817459/intel-stock-had-a-banner-year-but-is-still-50-off-its-record-highs-are-more-gains-in-store-for-2026"
        },
        {
          "title": "why did intel stock drop today",
          "url": "https://www.nasdaq.com/articles/why-did-intel-stock-drop-today"
        },
        {
          "title": "Intel Value Trap: The Potential 18A To 14A Shift In Foundry",
          "url": "https://seekingalpha.com/article/4799172-intel-value-trap-the-potential-18a-to-14a-shift-in-foundry"
        },
        {
          "title": "Intel stock falls 21% in a week amid manufacturing delays",
          "url": "https://cryptobriefing.com/intel-stock-falls-manufacturing-delays/"
        },
        {
          "title": "intels chip strategy shifts again time to buy the dip",
          "url": "https://www.barchart.com/story/news/33218561/intels-chip-strategy-shifts-again-time-to-buy-the-dip"
        },
        {
          "title": "marketminute 2026 1 26 intels stock plunge manufacturing challenges and disappointing guidance shake the chip sector",
          "url": "https://business.mammothtimes.com/mammothtimes/article/marketminute-2026-1-26-intels-stock-plunge-manufacturing-challenges-and-disappointing-guidance-shake-the-chip-sector"
        },
        {
          "title": "Intel Stock Drops 21% Amid Manufacturing Delays and AMD Rivalry",
          "url": "https://www.kucoin.com/news/flash/intel-stock-drops-21-amid-manufacturing-delays-and-amd-rivalry"
        },
        {
          "title": "Intel Aktie: 18A-Durchbruch stützt Erholung",
          "url": "https://www.boerse-express.com/news/articles/intel-aktie-18a-durchbruch-stuetzt-erholung-926432"
        },
        {
          "title": "Why Did Intel Stock Drop Today?",
          "url": "https://www.itiger.com/news/2548193838"
        },
        {
          "title": "🎉 Founding Member Beta — Join our Discord and get 3 months of Pro free. Learn more →",
          "url": "https://www.13radar.com/insight/intel-17-plunge-reveals-harsh-disconnect-between-ai-hype-and"
        },
        {
          "title": "Intel Shares Drop 4.17% Amid Foundry Business Shift",
          "url": "https://www.ainvest.com/news/intel-shares-drop-4-17-foundry-business-shift-2507/"
        }
      ]
    },
    "I couldn't find any report of a 45% Intel stock plunge in October 2026, or a CNBC story on one. The results I found are older, so the premise of your query may be off.\n\n- **Largest 2026 drop found:** Early July saw a roughly 21% decline over seven trading days, with shares falling from about $140 to about $110 after reports that 18A would not reach profitable yields until late 2026 or 2027 (Shares dropped roughly 21% over seven trading days in early July, sliding from around $140 to approximately $110). Another source describes a 17% drop after the fourth-quarter 2025 results in January (The 17% plunge in Intel's stock).\n- **14A customers:** Finance chief David Zinsner told CNBC that customers for the next-gen 14A node would appear in the second half of 2026. Another source says Intel will announce its 14A customer list in late 2026 or early 2027.\n- **Foundry strategy:** A Reuters report said Intel might lean toward 14A for foundry work and keep 18A mainly for its own chips (Intel would focus on more advanced 14A process (1.4 nm) for its foundry customers, while continuing to develop 1.8-nm chips in-house.). One undated filing said Intel may \"pause or discontinue\" its foundry efforts entirely if it fails to find a significant external customer for its next-generation 14A manufacturing process. I couldn't confirm the date of that filing.\n\nIf a 45% October drop did happen, these results don't show it. A search for the specific CNBC article or Intel's October 2026 share price data would be the next step."
  ],
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  "stdout": "200\n2026-11-03T00:35:03Z | Predicting different dimensions of fatigue from speech data: a longitudinal study in shift workers | https://doi.org/10.1038/s41746-026-03437-0\n2026-11-03T09:07:01Z | The TEMPO program and the future of digital mental health regulation in the US | https://doi.org/10.1038/s41746-026-03464-x\n2026-11-03T07:06:50Z | Cost-effectiveness analysis of digital medicine support models for alcohol use disorder | https://doi.org/10.1038/s41746-026-03422-7\n2026-11-03T00:46:04Z | Biodiversity, conservation and design thinking: an AI-driven, geodesign framework for determining habitat qual | https://doi.org/10.1038/s44185-026-00165-2\n2026-11-03T10:25:05Z | Integrative analysis of brain-age acceleration: health associations and multi-omics profiles | https://doi.org/10.1038/s41514-026-00557-5\n2026-11-02T17:15:23Z | Nanomechanical profiling of cellular senescence and aging with advanced force probes and deep learning | https://doi.org/10.1038/s41514-026-00555-7\n2026-11-02T17:46:21Z | Review of artificial intelligence technologies for older adult health and wellbeing in NIA AITC Program | https://doi.org/10.1038/s41514-026-00549-5\n2026-11-03T10:10:01Z | Integrated manufacturing platform for cortical organoids reveals early phosphatase and prefoldin dysregulation | https://doi.org/10.1038/s44400-026-00147-y\n2026-11-02T14:44:20Z | Towards anti-influenza nasal sprays: infection models and opportunities to reduce animal testing | https://doi.org/10.1038/s44298-026-00255-9\n2026-11-02T06:43:39Z | From hydraulic fracturing additive use to produced water signatures: a screening and prioritization framework | https://doi.org/10.1038/s41545-026-00645-9\n2026-11-03T04:27:30Z | Modern analog computing for solving differential and matrix equations | https://doi.org/10.1038/s44335-026-00108-x\n2026-11-02T10:04:02Z | Predicting East Africa’s rainfall extremes with calibrated AI post-processing systems | https://doi.org/10.1038/s44304-026-00283-8\n2026-11-02T12:21:11Z | Functional roles of non-redox active dopants in sodium layered oxide cathodes | https://doi.org/10.1038/s44456-026-00020-6\n2026-11-02T12:32:12Z | Multimodal training in reconfigurable brain-inspired iontronic networks | https://doi.org/10.1038/s44335-026-00105-0\n2026-11-03T02:05:06Z | An exploratory remote pilot study of environmental risk factors for Lewy body dementia considering sex differe | https://doi.org/10.1038/s41531-026-01603-5\n2026-11-02T12:36:12Z | Association of diffusion along the perivascular spaces with clinical symptoms and dopaminergic degeneration in | https://doi.org/10.1038/s41531-026-01620-4\n2026-11-02T11:25:09Z | Dust momentum as a metric linking atmospheric dynamics to ocean nutrient delivery | https://doi.org/10.1038/s44304-026-00287-4\n2026-11-02T12:48:16Z | Material optimization of interconnects and transistors for energy-efficient and high-performance cryogenic GAA | https://doi.org/10.1038/s44335-026-00106-z\n2026-11-03T05:20:53Z | Minimal physicochemical heterogeneity shapes the collective dynamics of active droplets | https://doi.org/10.1038/s44431-026-00045-6\n2026-11-02T12:05:11Z | Investigating the mechanism of niobium doping for mitigating voltage decay in LiMn0.6Fe0.4PO4 | https://doi.org/10.1038/s44456-026-00018-0\n2026-11-03T05:20:54Z | Bonded-particle model for magneto-elastic rods | https://doi.org/10.1038/s44431-026-00039-4\n2026-11-02T18:34:21Z | Beyond dopamine: the role of non-dopaminergic systems in Parkinson’s disease | https://doi.org/10.1038/s41531-026-01604-4\n2026-11-02T12:42:20Z | A survey of routing protocols for internet of underwater things from a performance evaluation perspective | https://doi.org/10.1038/s44459-026-00091-6\n2026-11-03T09:27:57Z | Rethinking cascading high-mountain hazards and early warning in the Himalayas | https://doi.org/10.1038/s44304-026-00292-7\n2026-11-02T12:48:13Z | Monolithically-integrable and scalable 2.4 GHz MIMO backscatter system based on large-area electronics | https://doi.org/10.1038/s44459-026-00099-y\n2026-11-03T05:18:44Z | Phase separation in multi-component membrane during cell adhesion | https://doi.org/10.1038/s44431-026-00049-2\n2026-11-02T14:36:20Z | A novel TRG-ypT-ypN 3D staging system for locally advanced gastric cancer patients after neoadjuvant therapy:  | https://doi.org/10.1038/s41698-026-01768-5\n2026-11-02T12:40:14Z | From maxwell to digital twins: a physics-based framework for future AI-native wireless communications | https://doi.org/10.1038/s44459-026-00092-5\n2026-11-02T12:48:18Z | Dual resonant transmissive circular dichroism in a rotationally transformed chiral metasurface | https://doi.org/10.1038/s44459-026-00101-7\n2026-11-02T17:45:23Z | Fault-tolerant quantum error correction for constant-excitation stabilizer codes under coherent noise | https://doi.org/10.1038/s41534-026-01401-0",
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  "command": "node scripts/fetch.js \"https://www.nature.com/articles/s41746-026-03437-0\" 2>&1 | head -c 3200",
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  "stdout": "HTTP 200 · https://www.nature.com/articles/s41746-026-03437-0?error=cookies_not_supported&code=60d0a32b-65a1-45df-a642-83195223306e · text/html\nPredicting different dimensions of fatigue from speech data: a longitudinal study in shift workers | npj Digital Medicine\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\nPredicting different dimensions of fatigue from speech data: a longitudinal study in shift workers\n\nDownload PDF\n\nDownload PDF\n\n# Abstract\nShift work, or working outside of normal circadian cycles, is associated with both experience of fatigue and poorer long-term physical and mental health. However, current methods for assessing fatigue present several barriers to building understanding of how these risks develop over time within individuals. Here, we explore the potential of momentary speech activity-based fatigue measurement in a large, multi-lingual cohort of shift workers, using an intensive longitudinal study design (twice-daily measurement over two weeks in N  = 1197 individuals from six different countries). Paralinguistic speech features were used to predict different aspects of acute and chronic fatigue at each study time-point, with performance assessed in unseen (held-out) data. In the cross-sectional analysis, good (close to or exceeding current state-of-the-art) performance was achieved for both current sleep deprivation and self-reported sleepiness levels. The within-user analysis revealed robust increases in performance, yielding the ability to detect more subjective aspects of fatigue such as pervasive physical and mental exhaustion. These findings offer preliminary support for the utility of using brief momentary speech samples as a low-burden, acceptable, and reliable measure of different aspects of fatigue in high-risk populations such as shift workers.\n\n# Similar content being viewed by others\n\n#\nFatigue and processing speed predict subsequent fatigue override, evidence from a coordinated analysis of six EMA studies\n\nArticle\nOpen access\n18 September 2026\n\n#\nIntroducing a sleep disorder screening and management strategy for workers with future shift work requirements: a feasibility and acceptability study\n\nArticle\nOpen access\n28 August 2024\n\n#\nFrequency-specific oscillations track parallel processing of linguistic structural and lexical-semantic information from perception to decision\n\nArticle\nOpen access\n12 October 2026\n\n# Explore related subjects\n\nDiscover the latest articles and news in related subjects.\n\n-\n\nHealth care\n\n-\n\nPhysiology\n\n-\n\nPsychology\n\n# Acknowledgements\nWe extend our gratitude to all the participants who generously dedicated their limited time and effort to our study. This work was supported by Innovate UK, the United Kingdom’s innovation agency, under Grant No. 10042845. NC is part funded by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre (BRC):",
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  "stdout": "=== SQUARESPACE ===\nHTTP 200 · https://techcrunch.com/2026/11/02/web-host-squarespace-lays-off-19-of-its-employees/ · text/html\nWeb host Squarespace lays off 19% of its employees | TechCrunch\n\n–:–:–:–\n\nBuy One Founder Summit Ticket, Get a Second for Free. Register now.\n\nFounder Summit begins Nov. 4, 9:00 a.m. ET. Get your pass savings & deals before it starts. REGISTER HERE.\n\nClose\n\nImage Credits: Squarespace\n\nCommerce\n\n# Web host Squarespace lays off 19% of its employees\n\nLucas Ropek\n\n11:25 AM PST · November 2, 2026\n\nSquarespace, the web company that helps customers build and host their own websites, is laying off about one-fifth of its workforce, in a move that will affect hundreds of jobs.\n\nJeff Seedman, a public relations specialist representing Squarespace, confirmed the layoffs to TechCrunch. The Verge initially reported the layoffs.\n\n“Squarespace is restructuring its organization and reducing its global workforce by approximately 19%, representing around 300 employees,” said Seedman. “The changes are intended to simplify how we operate, sharpen our priorities and enable the company to move faster as we position Squarespace for its next phase of growth.”\n\nWebsite building has changed immensely over the last few years as a result of the generative AI boom. “Vibe-coding” website builders, which only require simple prompts from users to spin up functional front-end designs, have largely upended the industry, making it possible for users to create sites with significantly less effort.\n\nThese kinds of sites have become an increasingly central part of the website-building business. Last year, web host rival Wix bought Base44 for $80 million . Similar offerings, like Lovable, have generated significant investor interest; Lovable raised a $400 million Series C round in August that valued the company at $13.3 billion. Google also recently launched Stitch , a feature that allows users to swiftly generate user-interface designs.\n\nSquarespace has also begun a big push into AI. In 2024, the company launched an AI tool called Blueprint. The company also recently announced Forma, an upcoming AI native platform, whose waitlist users can join .\n\nSquarespace was founded in 2004 and went public in 2021 at a $10 billion valuation. However, the company struggled in the ensuing years to generate enthusiastic public market interest. Squarespace ultimately decided to go private again by way of a $7 billion private equity deal in 2024.\n\nAn earlier version of this report incorrectly stated that Squarespace had not yet launched AI tools; the story has been updated.\n\nTopics\n\nAI , Commerce , Layoffs , Squarespace , vibe coding\n\nWhen you purchase through links in our articles, we may earn a small commission . This doesn’t affect our editorial independence.\n\nLucas Ropek\n\n\n=== X.AI ===\nHTTP 200 · https://x.ai/news · text/html\nNews: Research, Product & Company Updates | SpaceXSI\n\nOct 14, 2026\n\n# Introducing Grok Voice 3.0\nThe world’s most intelligent voice model.\nRead More\n\nProduct · Nov 2, 2026\n\n# Giving every team a data scientist with Grok Bot\n\nProduct · Oct 27, 2026\n\n# Your next sales teammate should be a Grok Bot\n\nCompany · Oct 22, 2026\n\n# Introducing the SpaceX Super Intelligence Partner Network\n\nProduct · Oct 20, 2026\n\n# Using Grok Bot to detect and respond to incidents\n\n# All posts\n\n# Introducing The X Subscription\nGrok, Grok Bot, Cursor, and X Premium, all on one plan.\n\nOct 12, 2026\n\n# Team Bots: shared AI teammates that learn as they work\nGive a Grok Bot the files, apps, and expertise it needs, then share it so your whole team can work from the same context.\n\nSep 28, 2026\n\n# How SpaceXSI is using Grok Bot to scale customer support\nWe rebuilt the combined SpaceXSI and Cursor support operation around Grok Bot, expanding to a much broader product portfolio without adding headcount.",
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  "stdout": "=== BRAVE SUIT ===\nHTTP 200 · https://techcrunch.com/2026/11/02/new-york-times-and-other-outlets-sue-web-browser-brave-over-alleged-content-scraping/ · text/html\nNew York Times and other outlets sue web browser Brave over alleged content scraping | TechCrunch\n\n–:–:–:–\n\nBuy One Founder Summit Ticket, Get a Second for Free. Register now.\n\nFounder Summit begins Nov. 4, 9:00 a.m. ET. Get your pass savings & deals before it starts. REGISTER HERE.\n\nClose\n\nIn Brief\n\nPosted:\n\n11:19 AM PST · November 2, 2026\n\nImage Credits: Rafael Henrique/SOPA Images/LightRocket / Getty Images\n\n-\n\n- Rebecca Bellan\n\n# New York Times and other outlets sue web browser Brave over alleged content scraping\n\nThe New York Times sued Brave, the 11-year-old, privacy-focused browser company, on Monday, alleging it scraped the outlet’s copyrighted content and unlawfully distributed it to customers the suit names as Anthropic, Perplexity, Mistral, xAI, and Cohere.\n\nSeparately on Monday, the Daily News, the Chicago Tribune, and the Orlando Sentinel filed a similar lawsuit. Both were brought in federal court in Manhattan.\n\nThe New York Times, which has also sued OpenAI and Perplexity over similar claims, likens Brave to a “supplier, dealer, and distributor of stolen copyrighted content” for AI companies.\n\n“In this way, Brave acts both like a burglar that misappropriates the content of publishers, and an AI ‘fence’ that sells stolen content to third parties,” the suit reads. It says Brave built an index of more than 30 billion web pages using an unidentified crawler, leaving publishers unable to block it.\n\nThe suit also targets a Brave browser feature that bypasses paywalls and the company’s practice of blocking publishers’ ads while selling its own.\n\nFounded in 2015, Brave has raised roughly $250 million to date, according to private-market trackers. The Times seeks an injunction and damages.\n\nBrave did not immediately respond to a request for comment.\n\nTopics\n\nAI , Brave , In Brief , new york times\n\nNovember 4\n\nBoston\n\nBuy One Pass, Get a Second Free\n\nCover more ground at TechCrunch’s ultimate founder bootcamp of the year by bringing your co-founder or partner for free",
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  "command": "node scripts/fetch.js \"https://www.nature.com/articles/s41746-026-03422-7\" 2>&1 | head -c 3000",
  "description": "Fetch npj alcohol cost-effectiveness paper"
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  "stdout": "HTTP 200 · https://www.nature.com/articles/s41746-026-03422-7?error=cookies_not_supported&code=601e884a-4c9e-453d-9446-6712a8f23c6b · text/html\nCost-effectiveness analysis of digital medicine support models for alcohol use disorder | npj Digital Medicine\n\nSkip to main content\n\nThank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain\nthe best experience, we recommend you use a more up to date browser (or turn off compatibility mode in\nInternet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles\nand JavaScript.\n\nCost-effectiveness analysis of digital medicine support models for alcohol use disorder\n\nDownload PDF\n\nDownload PDF\n\n# Abstract\nAlcohol use disorder (AUD) is a major public health issue yet often under-addressed in primary care. Digital health interventions offer scalable support, but health systems require economic data to guide implementation decision-making. In a randomized clinical trial involving 558 participants registered at clinicaltrials.gov (NCT04011644; July 3, 2019), we compared three support models built on a shared digital medicine platform: self-monitored use (SM), peer-supported use (PS), and clinically integrated use (CI). We estimated delivery costs and effectiveness based on reductions in heavy drinking days. Annualized reductions in heavy drinking days were 42.4, 40.2, and 48.3 days per patient for SM, PS, and CI models, with per-patient costs of $162, $524, and $802, respectively. Average cost-effectiveness was $3.8 (SM), $13.0 (PS), and $16.6 (CI); PS was dominated, and the ICER for CI versus SM was $107.9. When downstream healthcare utilization was included, results suggested that more intensive support may be economically advantageous. Modeling implementation at scale showed that PS becomes cost-efficient for large patient populations. These findings highlight that no single model is universally optimal: health systems may benefit from offering multiple support levels to match patient preferences and organizational capacity.\n\n# Explore related subjects\n\nDiscover the latest articles and news in related subjects.\n\n-\n\nDiseases\n\n-\n\nHealth care\n\n-\n\nMathematics and computing\n\n-\n\nMedical research\n\n# Funding\nThis research was funded by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) grant number R01-AA024150. The funder had no role in any aspect of the development, conduct, analysis, or reporting of the study.\n\n# Author information\n\n# Authors and Affiliations\n\n- Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison, WI, USA\nXiang Li\n\n- College of Health Sciences, University of Kentucky, Lexington, KY, USA\nMing-Yuan Chih\n\n- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA\nMallory Herzog, Joel Gordon, Linda Park, Randall Brown & Andrew Quanbeck\n\nAuthors\n- Xiang Li View author publicati",
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  "message": "BEAT C — Security/misuse/threat-intel + Military/defense/geopolitics\nWindow: 2026-11-02T11:50Z → 2026-11-03T11:05Z. 14 candidates below, then rejects.\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Google says hijacked enterprise LLM access ran up $100,000 a day in token charges\nPUBLISHED: November 2, 2026 (Google Cloud blog page header); The Register, \"mon 2 Nov 2026 // 16:00 UTC\"; Infosecurity Magazine, 3 November 2026\nSOURCES:\nGoogle Threat Intelligence Group / Mandiant | https://cloud.google.com/blog/topics/threat-intelligence/llmjacking-monetizing-compromised-cloud-models/ | primary\nThe Register | https://www.theregister.com/security/2026/11/02/token-thieves-costing-companies-100k-per-day-in-illicit-llm-charges/5306967 | report\nInfosecurity Magazine | https://www.infosecurity-magazine.com/news/llmjacking-cost-business-1m-warns/ | report\nFACTS:\n- GTIG/Mandiant write that in individual incidents fraudulent charges from resource consumption exceeded \"$100,000 USD in a single day\", and that at some organizations charges reached \"$1 million USD\" before access was revoked.\n- GTIG says a group it tracks as UNC6993 compromised a cloud instance through a misconfigured Service Account key, reached an LLM API, tried to generate additional API keys and enable associated services in victim projects, and accumulated \"over $100,000 USD\" in billing charges; it also ran a session-hijacking page posing as an application portal that tricked users into pasting a raw JSON payload containing an active access token, bypassing password and MFA controls.\n- GTIG says a threat actor made \"more than 500,000 LLM API calls in under eight hours\" using stolen third-party API keys to power a token routing service called Jet Night (jet-night.com), passing nearly $1 million USD in token costs to the victim organization. GTIG says Jet Night advertises an unlimited-token plan at about $60 USD/month with alleged frontier-model access, where comparable consumer tiers \"would typically run between $100 and $250 per month\".\n- GTIG defines \"LLM Mixers\" as illicit routing gateways that \"proxy, aggregate, and resell unauthorized LLM access to underground subscribers\", and describes a division of labour between initial-access actors and the mixers.\n- GTIG's John Hultquist told The Register: \"Whenever possible, threat actors want to use this technology to gain a scale advantage over defenders. They achieve that with agentic tools and by stealing tokens from unwitting third parties.\"\n- GTIG says it expects threat actors to \"increasingly prioritize LLMJacking\" over resource theft such as cryptojacking.\nFLAGS: company-claim\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: NCSC says AI-powered malware in ransomware against UK critical infrastructure highly likely by 2028\nPUBLISHED: Tuesday 3 November 2026 (NCSC news page, \"Version 1.0\" on Annual Review 2026)\nSOURCES:\nUK NCSC | https://www.ncsc.gov.uk/news/cyber-chief-uk-facing-ai-powered-attacks-on-critical-infrastructure-in-two-years | primary\nUK NCSC Annual Review 2026 | https://www.ncsc.gov.uk/collection/annual-review-2026/understanding-threat/cyber-threat-uk | primary\nUK NCSC Annual Review 2026 (introduction) | https://www.ncsc.gov.uk/collection/annual-review-2026/introduction | primary\nThe Record | https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months | report\nFACTS:\n- The NCSC assesses it is \"highly likely\" that AI-powered malware will have been used in a ransomware attack on UK critical national infrastructure by 2028, and \"highly likely\" that by 2028 China, Russia and other nation states will routinely use AI in cyber operations to pursue geopolitical goals (Annual Review 2026, \"Cyber threat to the UK\" page).\n- NCSC CEO Dr Richard Horne said: \"For decades, we have collectively got away with doing tech on the cheap,\" and \"But we must be clear that is not because AI has invented new ways to attack us.\"\n- The review period is 1 September 2025 to 31 August 2026. The Annual Review page puts the cost of malicious cyber activity to UK organisations at an estimated £14.7 billion a year, citing UK government research, and the 2025 Jaguar Land Rover attack at about £196 million in direct cyber-related costs.\n- Funding cited by the NCSC: \"£60 million\" for the first phase of a national Cyber Shield and \"£70 million\" for a National Exposure and Real-Time Vulnerability (NERV) Centre. Per The Record, Cyber Shield is described as a national network of AI defence agents focused initially on detecting and blocking attacks.\n- The Record reports that Project DROMOS, a government trial of frontier AI, found hundreds of security issues, and that Horne warned of the real prospect of an \"unprecedented rise\" in cyber incidents in the coming months.\nFLAGS: (none)\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: WIRED traces 400-plus apps and domains hiding sexual deepfake generators; Apple pulls 19\nPUBLISHED: WIRED, November 2, 2026; Digital Trends, November 2, 2026 6:40 PM; 9to5Mac, Nov 2 2026 - 4:31 am PT\nSOURCES:\nWIRED | https://www.wired.com/story/hundreds-of-mundane-ai-apps-are-hiding-abusive-deepfake-features/ | primary\nDigital Trends | https://www.digitaltrends.com/computing/hidden-network-of-sexual-deepfake-generators-inside-harmless-ai-apps/ | report\n9to5Mac | https://9to5mac.com/2026/11/02/ai-apps-with-hidden-sexual-and-violent-deepfake-features-made-it-into-the-app-store/ | report\nFACTS:\n- NOTE ON SOURCING: wired.com is blocked by this environment's egress policy; all figures below come from Digital Trends and 9to5Mac, which I opened and which both attribute them to WIRED's investigation.\n- Digital Trends reports WIRED found \"400+\" connected apps and domains in the network, a figure attributed to researchers at AI Forensics; one app had \"100,000+\" downloads before Google removed it.\n- Digital Trends reports Apple removed 19 further apps after WIRED's findings, and that Meta has taken action against 11,600 ad accounts, 5,200 users and blocked 209 apps tied to the scheme. 9to5Mac's version says Meta \"has taken action against more than 10,000 ad accounts linked to domains associated with these apps.\"\n- 9to5Mac quotes Apple: \"We review every app before it's published, and these apps complied with our rules when we reviewed them. After approval, their developers changed the website the app pulls its content from, replacing what we approved with pornographic content, and promoted it through pornographic ads hosted on a third-party platform.\"\n- 9to5Mac says the apps present as everyday services (e.g. Viefur, marketed for adding clothing to pet photos, language tuition, AI workout coaches), and that a server check can activate hidden features; tapping an ad for the deepfake functionality on Meta platforms before download appears to be one trigger. It lists in-app scene templates including \"bedroom rape\" and \"threatening knife\".\n- Digital Trends says the EU's ban on nudifier apps takes effect in about one month.\nFLAGS: (none)\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: IBM discloses four Langflow flaws, including unauthenticated RCE reachable via MCP tool enumeration\nPUBLISHED: The Hacker News, November 2, 2026 (IBM bulletin first published October 28, updated the next day)\nSOURCES:\nThe Hacker News | https://thehackernews.com/2026/11/critical-langflow-flaws-could-let.html | report\nFACTS:\n- Per The Hacker News, IBM's bulletin covers four Langflow flaws: CVE-2026-93680 (CVSS 9.8, no account needed, bypassing security restrictions from improper authentication); CVE-2026-110186 (CVSS 9.8, no account needed, arbitrary code execution from improper control of code generation); CVE-2026-110193 (CVSS 8.8, low-privileged account, making the Agentic Assistant generate or submit component code that runs OS commands); CVE-2026-110192 (CVSS 6.5, insufficiently protected credentials).\n- Affected: every release from 1.0.0 through 1.12.8; the only fix is 1.13.0, released October 22. IBM offers no workaround.\n- IBM describes one flaw as \"unauthenticated remote code execution exploitable through model context protocol tool enumeration\". The article notes Langflow can expose flows as tools to MCP-capable AI apps, and that a public Metasploit module connects to a server's MCP endpoint without credentials, starts a session and lists offered tools, but does not run code.\n- On October 29 IBM also published CVE records for 29 other Langflow flaws; among them CVE-2026-104339 is rated 9.8 and also allows unauthenticated arbitrary code execution.\n- Neither 9.8 flaw appears in CISA's Known Exploited Vulnerabilities catalog as of its October 30 update; six other Langflow flaws are listed, the most recent CVE-2026-9198, added in August.\n- LANGFLOW_AUTO_LOGIN is enabled by default in 1.12.8 and signs users in as superusers; IBM describes one of the four flaws as an incomplete fix for an auto-login control.\nFLAGS: single-source (IBM advisory relayed by The Hacker News; I could not open the IBM bulletin directly)\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Trigger.dev says attacker accessed environment variables of a subset of AI-workflow customers\nPUBLISHED: The Register, \"mon 2 Nov 2026 // 16:44 UTC\"; Trigger.dev status page incident resolved 10:50pm UTC, 1 November 2026\nSOURCES:\nThe Register | https://www.theregister.com/security/2026/11/02/thieves-pilfer-environment-variables-from-trigger-ai-workflow-tool/5306998 | report\nTrigger.dev | https://trigger.dev/blog/security-incident-nov-2026 | primary (URL from search results; page itself returned 404 when I tried trigger.dev/security-incident)\nSC Media | https://www.scworld.com/brief/trigger-dev-discloses-security-incident-involving-exposed-environment-variables | report\nFACTS:\n- The Register reports Trigger.dev disclosed on Sunday that its investigation \"identified 'exposure across a subset of organizations'\" and that an attacker gained unauthorized access to environment variables belonging to those organizations.\n- Trigger.dev said the exploit used to gain access has been blocked and affected customers have been notified of steps to prevent further problems.\n- The Register describes Trigger.dev as a platform for building AI agents and workflows in TypeScript, quoting the company's site that it can be used to \"build durable AI agents that survive refreshes, redeploys, and crashes\".\n- The Register notes the company gave \"little explanation\" of how access was obtained; per search-result text from SC Media, Trigger.dev has not publicly identified which organizations were impacted.\n- Per search-result text, the status page (https://status.trigger.dev/incident/1110434) lists the incident resolved at 10:50pm UTC on 1 November 2026 and says \"We have emailed all impacted account owners with steps to mitigate.\"\nFLAGS: update (disclosure 1 Nov; reporting and detail inside window)\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Resemble AI counts 481 political AI-media incidents over twelve months, 69% with no identifiable source\nPUBLISHED: Page byline reads November 2, 2026; the same page's metadata/embedded code lists October 30, 2026\nSOURCES:\nResemble AI | https://www.resemble.ai/resources/2026-political-deepfake-report | primary\nFACTS:\n- Resemble AI says it logged 481 incidents of AI-generated media involving politicians, governments and elections between November 1, 2025 and October 14, 2026.\n- 276 of the 481 were classified as disinformation (AI media presented as real). For 190 of those 276 (69%), coverage named no creator or first sharer.\n- Of the 86 disinformation incidents with a known source: politicians or campaigns posted 33, foreign state actors 21, private individuals 15, government accounts 9, PACs/advocacy groups 8.\n- 206 incidents were made to attack or discredit someone; campaigns, PACs and government accounts posted 98 of them (48%). Of 79 AI posts from those accounts, 21 (27%) carried the poster's own AI label.\n- Untraceable disinformation targeted politicians or citizens in 49 countries, most in India (38), then the US (33).\n- Incidents rose to about 70 a month from May 2026 onward, against about 15 a month earlier. Across 157 attacks with an election within 180 days, the rate was 0.7/day at 91–180 days out, 0.7/day at 31–90 days, and 1.5/day in the final 30 days.\nFLAGS: company-claim, single-source — AND a date conflict: the visible byline says Nov 2 2026 but page metadata says Oct 30 2026. If the editor wants a clean window, this one is the weakest on date.\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Check Point's 2 November threat report summarises AI-agent intrusions and Qwen network-call analysis\nPUBLISHED: November 2, 2026\nSOURCES:\nCheck Point Research | https://research.checkpoint.com/2026/2nd-november-threat-intelligence-report/ | report\nCheck Point Blog | https://blog.checkpoint.com/ai-security/qwen-incident-backdoor-ai-agents/ | primary (dated October 29, 2026)\nFACTS:\n- Check Point's 2 November report says its researchers analysed unexpected network activity generated by Alibaba's Qwen model during a security-related task, and that the findings suggest unstable model behaviour is a more plausible explanation than a deliberately embedded data-exfiltration mechanism.\n- Check Point's underlying blog (dated October 29, 2026) says it replayed the moment 64 times; the model wrote 52 different destination addresses — Alibaba Cloud in 6 replays (~9%), AWS 7 (~11%), Azure 1, other public-looking addresses 27 (~42%), the machine itself or an internal network 20 (~31%), placeholders 3 — and 11 of the public-looking domains do not exist. Swapping the listing order of two installed programs cut network-command replays from 15 of 32 (~47%) to 4 of 32 (12.5%).\n- The same 2 November report summarises, as third-party findings: Sophos on GOLD OGRE/Aur0ra ransomware giving AI agents compromised credentials and goals for network reconnaissance, locating privileged accounts and lateral movement; Microsoft on North Korean actors using language models for reconnaissance, malicious tool development and social engineering; and CrowdStrike on China-linked VAPOR PANDA using an \"AI-enabled ARTEX framework\" against more than 200 organizations in at least 14 countries.\nFLAGS: update (the roundup is in-window; the underlying Check Point, Sophos, Microsoft and CrowdStrike research is dated 29–30 October, i.e. outside the window). Use only if the editor wants the Qwen \"jaggedness vs backdoor\" finding; otherwise skip.\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: arXiv cs.CR listing of 3 November carries new preprints on coding-agent and tool-update attacks\nPUBLISHED: Listing date Tuesday, 3 November 2026 (arXiv cs.CR new submissions)\nSOURCES:\narXiv | https://arxiv.org/list/cs.CR/new | primary\nFACTS:\n- Attacks on deployed agent systems in the listing include: 2611.00138 \"Kerkoporta: Injecting Structured-Output Backdoors in Reasoning Coding Agents\" (a trigger causes the model to emit an attacker-chosen tool call that the harness executes); 2611.00725 \"The Long Con on the Web: Earn-then-Exploit Fraud Attacks against Coding Agents\" (a malicious site builds trust with helpful answers before issuing harmful instructions); 2611.01976 \"Beyond Prompt Injection: The Tool Update Gap in LLM Agent Security\" (ETUDE — malicious code added in tool updates, outside the model's context); 2611.01953 \"Step-Zero Attack: Agent Safety Before Observability\" (harm occurs while an agent processes untrusted input, before the model sees its content); 2611.02407 \"Networked Synthetic Social Engineering on the Web\".\n- Defence papers in the same listing include 2611.00729 \"AgentCap: Capability-Based Runtime Authorization for Secure LLM Agent Execution\", 2611.01950 \"CertClaim: Towards Certified Model-Claim Verification for Coding-Agent Services\", 2611.02605 \"StateFence: Task-State Protection Against Evidence-Chain Contamination in Blue-Team LLM Agents\", and 2611.02611 on MCP-security mitigation mapping.\n- The listing page was truncated after entry 47, so this is not a complete set.\nFLAGS: preprint\n\n---\n\nSECTION: Military, defense & geopolitics\nHEADLINE: FT reports Nvidia told cloud clients at least 51% of services must go to non-Chinese buyers\nPUBLISHED: Seoul Economic Daily, 2026/11/03, citing the Financial Times \"on the 2nd\"\nSOURCES:\nSeoul Economic Daily (English) | https://en.sedaily.com/international/2026/11/03/nvidia-tells-cloud-clients-51-percent-of-capacity-must-go | report\nFinancial Times | https://za.investing.com/news/stock-market-news/nvidia-tells-data-center-partners-to-limit-china-sales-ft-4544767 | report (FT's own page is blocked by this environment's egress policy; FT is the originating outlet)\nFACTS:\n- NOTE ON SOURCING: ft.com returns HTTP 403 \"Blocked by egress policy\" here. The figures below come from Seoul Economic Daily's English edition, which I opened and which attributes them to the Financial Times' 2 November report. Seoul Economic Daily labels its text \"AI-translated from Korean\" and warns quotes from foreign sources may not reflect exact original wording.\n- Per that account of the FT report: Nvidia has told cloud and data centre customers worldwide that at least 51% of their services must be sold to non-Chinese companies; no such restriction existed before; the instruction was not put in writing but delivered verbally through Nvidia's sales organization and regional teams, per people familiar with the matter.\n- The requirement applies to customers globally, not only Asia; existing rental contracts are unaffected and the rule covers only future agreements.\n- A rack of Nvidia B300 chips selling for about $600,000 on the international market traded in China last month at 18.5 million yuan, or $2.8 million. The B300 is barred from sale in China under US export controls.\n- Nvidia had already cut the number of Asian customers approved to buy its AI chips by more than half after drawing up a whitelist this year. Nvidia said data centers and clouds built on American chips are the foundation that allows US model and application companies to compete worldwide.\n- A Singapore-based provider said it is difficult to secure enough non-Chinese customers outside the US and that strict enforcement would clearly hurt its business.\nFLAGS: single-source (one originating outlet, FT; relayed via Seoul Economic Daily translation)\n\n---\n\nSECTION: Military, defense & geopolitics\nHEADLINE: Taiwan DPP bill would jail AI-chip smugglers to China for up to 10 years\nPUBLISHED: Asia Times, November 3, 2026 (Jeff Pao)\nSOURCES:\nAsia Times | https://asiatimes.com/2026/11/taiwan-to-criminalize-nvidia-ai-chip-smuggling-to-china/ | report\nFACTS:\n- Asia Times reports a Foreign Trade Act amendment proposed by ruling DPP lawmakers would ban exports of specified integrated circuits, key wafer materials, components and chipmaking equipment to mainland China without government approval, including shipments routed through a third country, with illegal gains confiscated. A Legislative Yuan Economics Committee public hearing was held Monday.\n- Proposed penalties: up to 10 years in prison and fines of NT$5 million to NT$10 million (US$155,000 to US$310,000). Under the existing Foreign Trade Act, adding AI chips to the control list would bring penalties of up to five years.\n- In August 2026 Keelung prosecutors indicted nine people, including a Flying Tiger Technology general manager and staff at local Nvidia and Super Micro units, for allegedly diverting 74 Nvidia B300 servers to Chinese buyers for profit of over NT$600 million (US$18.5 million). None faces an export charge; prosecutors used breach of trust and document forgery.\n- Currently exports to China are restricted only for 12 categories of wafer-fabrication equipment.\n- William Liu of the Ministry of Economic Affairs' International Trade Administration said export controls have become a strategic tool to protect technological edge and national security. CIER's Wang Guo-chen said the amendment fits the US-Taiwan trade agreement but could leave Taiwanese firms in China caught between US and Chinese rules.\n- Asia Times notes the opposition KMT and TPP together hold a legislative majority and neither has publicly stated a position, so the bill could stall.\nFLAGS: single-source\n\n---\n\nSECTION: Military, defense & geopolitics\nHEADLINE: OpenAI hires former US Army Secretary Dan Driscoll as national security counselor\nPUBLISHED: CNBC, 2026/11/03; OpenAI Global Affairs post dated November 2, 2026\nSOURCES:\nCNBC | https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html | report\nOpenAI | https://openai.com/index/dan-driscoll-joins-openai/ | primary (openai.com returned HTTP 403 here; existence and date of the post come from search-result text)\nFACTS:\n- CNBC reports OpenAI has hired former US Army Secretary Dan Driscoll as senior counselor for national security modernization, \"a newly created role at the company\", and that his updated LinkedIn profile also lists the position.\n- CNBC: Driscoll will focus on how AI can be used to strengthen US national security and cybersecurity, and will work with OpenAI's senior leadership and external partners with a particular focus on helping US allies adopt advanced AI responsibly.\n- Sam Altman said the US has \"an extraordinary opportunity to work with other countries to spread the adoption of democratic AI\" and that the appointment would help strengthen American leadership in the technology.\n- Driscoll said: \"National security requirements are changing faster than at any time in the past fifty years,\" adding AI could help reduce paperwork, process information and deliver answers more quickly to those working in national security.\n- CNBC notes Driscoll resigned as Army secretary following reported tensions with Defense Secretary Pete Hegseth, citing Reuters.\n- Per search-result text, OpenAI's own post ties the appointment to its Daybreak program on cyber resilience and essential services with allies (I could not open openai.com).\nFLAGS: (none)\n\n---\n\nSECTION: Military, defense & geopolitics\nHEADLINE: Pentagon credit office signs up-to-$450m conditional loan with FPV drone maker Neros\nPUBLISHED: November 2, 2026 (DroneXL; PR Newswire release ID 20261102)\nSOURCES:\nDroneXL | https://dronexl.co/2026/11/02/neros-450m-osc-loan-taxpayer-ownership-stake/ | report\nNeros / PR Newswire | https://www.morningstar.com/news/pr-newswire/20261102la86859/neros-signs-450m-conditional-loan-commitment-with-the-office-of-strategic-capital-to-establish-americas-drone-industrial-base | primary (both the Morningstar mirror and prnewswire.com returned errors here; headline, date and figures below come from DroneXL, which I opened)\nFACTS:\n- DroneXL reports Neros Technologies and the Pentagon's Office of Strategic Capital announced a conditional loan commitment of up to $450 million on November 2, 2026, to expand drone and component production at Neros's Torrance, California factory; Neros is committing $165 million in equity, bringing the project total to $615 million.\n- DroneXL flags a discrepancy: Neros's website says the deal gives \"the American taxpayer an ownership stake in the company\", while the PR Newswire version ends the same sentence at the $615 million figure and OSC's release describes a conditional loan alongside private capital without mentioning an ownership stake. Neither says what form the stake would take or how much of the company it would cover.\n- The commitment is not final: Neros must still meet financial, legal, technical, investment and due-diligence requirements before financial close.\n- Per OSC, the Torrance plant would sell NDAA-compliant motors, radios, flight electronics, sensors and batteries to other American and allied drone makers.\n- CEO Soren Monroe-Anderson targets one million drones per year by 2028; DroneXL notes Neros was building about 1,200 drones a week in August (roughly 62,000 a year).\n- DroneXL notes Performance Drone Works signed its own OSC conditional loan on July 31.\nFLAGS: company-claim (production target), single-source (DroneXL is the only version I could open)\n\n---\n\nSECTION: Military, defense & geopolitics\nHEADLINE: Saab unveils in-house combat AI agents and AI Fighter Pilot Academy after Gripen E tests\nPUBLISHED: Breaking Defense, November 3, 2026 (Tim Martin, Belfast); Saab company statement same day\nSOURCES:\nBreaking Defense | https://breakingdefense.com/2026/11/swedens-saab-launches-family-of-ai-agents-for-future-aircraft-projects/ | report\nFACTS:\n- Breaking Defense reports Saab announced a suite of AI agents it built, trained and flew in-house for future aircraft platforms, citing \"a company statement released today\", and that the agents were tested on a Gripen E multirole fighter.\n- Peter Nilsson, head of Advanced Programs at Saab's aeronautics unit, said \"The harder question is how we turn this success\" into a dependable capability, and described sustained learning and improvement as the \"true purpose of the AI Fighter Pilot Academy\".\n- Nilsson said a one-hour simulated training flight can produce the equivalent of one billion flight hours for a human pilot.\n- Saab is developing three unmanned aircraft — A1, A2 and A3 — on the path to a new loyal wingman drone.\n- Saab is a co-founder of the Swedish government-backed Sferical AI computing initiative, built on Nvidia's DGX SuperPOD architecture and inaugurated in Stockholm in October 2026.\n- Breaking Defense notes the earlier reference point is a 2025 Gripen E flight test campaign using Helsing's Centaur AI, which is not part of this programme.\nFLAGS: company-claim (the one-billion-flight-hours equivalence and in-house claims are Saab's)\n\n---\n\nSECTION: Security, misuse & threat intelligence\nHEADLINE: Unit 42 lists AI-enabled offensive operations as emerging trend in 2 November threat highlights\nPUBLISHED: November 2, 2026\nSOURCES:\nPalo Alto Networks Unit 42 | https://origin-unit42.paloaltonetworks.com/u42-threat-intelligence-highlights-oct-2026/ | report\nFACTS:\n- Under \"AI-Enabled Offensive Operations\", Unit 42 says threat actors are adding generative AI and LLMs to offensive workflows, which it calls a notable emerging trend across several motivations.\n- It lists: generating highly tailored social engineering lures and synthetic personas at scale; LLM help with rapid scripting, payload debugging and code obfuscation; and automated reconnaissance plus multimodal tools including deepfakes supporting executive impersonation and access operations.\n- The page gives no statistics and names no threat actors in this section.\nFLAGS: single-source — weak filler only; include only if the brief needs one more security beat and no numbers are required.\n\n---\n\nREJECTED CANDIDATES AND WHY\n\n- Sophos GOLD OGRE / Aur0ra ransomware AI agents (sophos.com/blog/ai-used-in-aur0ra-ransomware-testing-and-execution; Help Net Security 2026/11/02) — primary Sophos research published October 29, 2026; the 2 Nov Help Net Security write-up adds no new development. Out of window as a story.\n- CrowdStrike VAPOR PANDA / ARTEX, 200+ organizations in 14 countries, nine confirmed compromises, ~1.4bn input tokens — CrowdStrike post October 29, 2026. Out of window.\n- Google GTIG \"ARTEX and Friends: Enter Agentic Offensive Frameworks\" — published October 30, 2026. Out of window.\n- iTnews \"ARTEX AI hacking framework spreads to another China-linked group\" — timestamped Nov 2, 2026 6:57 AM AEDT = 2026-11-01T19:57Z, before window start.\n- Microsoft \"Tracking AI adoption in North Korean threat actor tradecraft\" — October 29, 2026. Out of window.\n- Unit 42 CL-UNK-1211 / SysGoRAT \"AI-Powered Espionage Campaign Targets Government Linux Infrastructure\" — The Hacker News covered it Nov 2, but the Unit 42 primary is dated October 15, 2026 with no update date. Older research, no new development in window.\n- JPost NATO FUSE / Next Generation Targeting (>50% information-to-decision latency cut, 30+ countries, 100+ companies) — published Nov 2, 2026 09:38 Israel time = ~07:38Z, before window start; and the NATO Latvia AI-targeting exercise was already covered 2 Nov.\n- Microsoft Digital Defense Report 2026 and the Dark Reading critique — MDDR released October 1, 2026; darkreading.com returns HTTP 403 here so I could not confirm the critique's date.\n- OpenAI–NASK (Poland) AI safety and security agreement — announced October 23, 2026. Out of window.\n- Trend Micro / TrendAI \"AI Statecraft and Cyberthreats in 2026\" — dated November 1, 2026. Out of window.\n- D.C. Circuit 2-1 ruling upholding Pentagon \"supply chain risk\" designation of Anthropic — decided September 25, 2026. Out of window.\n- Cathedral/Anthropic breach dispute and Cloudflare Workers AI GLM 5.3 cross-customer leak (155 responses, prompts over 681,280 tokens) — SecurityWeek roundup October 30, 2026. Out of window.\n- UN First Committee autonomous weapons vote (163-5-9, 29 Oct) and military-AI dialogue text (30 Oct) — out of window; next step is the CCW Seventh Review Conference, 16–20 November 2026.\n- China's draft export controls on 23 AI technologies / 2-trillion-parameter threshold — draft published mid-October 2026, registration rule effective October 16; comments close 15 November. No in-window development found.\n- India MoD–Sarvam five-year AI framework — late October 2026. Out of window.\n- Breaking Defense \"Industry needs more consistent demand signal to scale UGV production\" (Nov 2, 2026 2:47 pm) — in window but contains no dollar amounts, unit quantities or production targets; only AUTOWARCOM/FASCOM reorganisation detail.\n- Infosecurity items of 2 Nov (Armadin 88% of severe flaws outside vendor advisories; Bitter/PapRAT; FBI–TraderTraitor Binance) — no AI angle, or already covered 2 Nov (Binance/TraderTraitor, Chainalysis \"offensive agentic\").\n- Register 2 Nov Android TV botnet, OT programming tool bug, Russia/Ukraine alert apps — no AI angle.\n- 404 Media items of 2–3 Nov (AI \"I Voted\" sticker, AO3 clone takedowns) — no security/military angle.\n- Simonwillison.net 2–3 Nov entries (llm 0.37, Census Bureau \"Super Intelligence\", aircraft-noise geolocation) — no prompt-injection or agent-security content.\n- CISA advisories — none dated 2 or 3 Nov 2026 in the listing; nearest AI item is \"Managing AI Token Consumption for Operational Resilience\", October 22, 2026.\n- Pentagon AI/Golden Dome contract awards, UK MOD AI/drone announcements, Japan–Palantir/Anduril Nikkei story — searched; nothing confirmed inside the window (Japan story's underlying Nikkei reporting dates to August 2026; only a secondary aggregator claims a Nov 2 Karp interview, which I could not open).\n- Deepfake arrest / AI voice-clone fraud figures — no primary in-window case found; FBI/FTC figures all trace to 2025 annual reports via secondary blogs."
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  "success": true,
  "message": "Report delivered to your caller."
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{
  "command": "node scripts/fetch.js \"https://www.hbs.edu/ris/Publication%20Files/27-002_d03a8b75-93d4-4a7c-87fd-3f09941f7c9a.pdf\" 2>&1 | head -c 4000",
  "description": "Fetch HBS working paper 27-002"
}

{
  "stdout": "HTTP 403 · https://www.hbs.edu/ris/download.aspx?name=27-002.pdf · text/html\nError\n\nHBS Home\n\n- About\n\n- Academic Programs\n\n- Alumni\n\n- Faculty & Research\n\n- Baker Library\n\n- Harvard Business Review\n\n- Initiatives\n\n- News\n\n- Recruit\n\n- Map / Directions\n\n- Harvard Business School\n→\n\n# Oops!\n\n# An error has occurred. Please try again.\n\nTry a search:\n\nor:\n\n或者:\n\nView the sitemap\n\nReturn to the Executive Education Home Page\n返回高管培训网站首页\n\nFind an Executive Education Program\n查找高管培训课程\n\nǁ\n\nHarvard Business School\n\nSoldiers Field\n\nBoston, MA 02163\n\n→\nMap & Directions\n\n→\nMore Contact Information\n\n→\nMore Contact Information\n\n→\nMore Contact Information\n\n→\nMore Contact Information\n\n-",
  "stderr": "",
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{
  "command": "echo \"=== XAI POST ===\"; node scripts/fetch.js \"https://x.ai/news/grok-bot-data-scientist\" 2>&1 | sed -n '1,40p'; echo \"=== FORBES MUSK ===\"; node scripts/fetch.js \"https://www.forbes.com/sites/siladityaray/2026/11/02/musk-says-grok-bots-costs-were-unsustainably-high-weeks-after-touting-rapid-growth/\" 2>&1 | sed -n '1,45p'",
  "description": "Fetch xAI Grok Bot post and Forbes Musk article"
}

{
  "stdout": "=== XAI POST ===\nHTTP 404 · https://x.ai/news/grok-bot-data-scientist · text/html\nSpaceXSI\n404\n\n# Page not found\nThis page doesn't exist or has been moved. Try one of the links here, or head back home.\nBack to home\n\nHelpful links\nHomepage Back to the start.\nAPI Build with Grok.\nDocumentation Read the docs.\nNews Latest announcements.\nCareers Join the team.\nContact Get in touch.\n=== FORBES MUSK ===\nHTTP 200 · https://www.forbes.com/sites/siladityaray/2026/11/02/musk-says-grok-bots-costs-were-unsustainably-high-weeks-after-touting-rapid-growth/ · text/html\nElon Musk Says Grok Bot Costs Were ‘Unsustainably High’ Amid Complaints Over Usage Limits\n\nBreaking Business\n\n# Musk Says Grok Bot’s Costs Were ‘Unsustainably High’ Weeks After Touting Rapid Growth\nBySiladitya Ray ,\nForbes Staff.\n\nSiladitya Ray is a New Delhi-based Forbes news team reporter.\n\nFollow Author\n\nNov 02, 2026, 06:19am EST Nov 02, 2026, 06:36am EST\n\n# Topline\nElon Musk acknowledged on Sunday that the cost of running SpaceX’s AI agent Grok Bot was “unsustainably high” relative to the revenue it generated, while responding to subscriber complaints about usage limits less than two weeks after the billionaire touted the service as the fastest-growing product he had ever seen.\n\nSpaceX CEO Elon Musk recently touted his company's AI agent, Grok Bot, as the fastest growing product he had ever seen.\nGetty Images\n\n# Key Facts\nIn response to a post on X about people’s Grok bot usage limits running out “really fast” this week, Musk wrote : “The cost of serving Grok Bot was unsustainably high relative to revenue.”\n\nIn a separate exchange on X with a user complaining about waiting a few days for their usage limit to reset, Musk asked whether the cost of upgrading to a higher-usage subscription tier was too high.\n\nThe billionaire’s posts didn’t say how much Grok Bot costs the company to operate or if the company has lowered its usage limits for subscribers.\n\nGrok Bot is an AI agent similar to Meta’s Muse and a separate product from the company’s chatbot Grok; it is available to users signed up for the company’s $30 per month “Premium” tier or higher.\n\nIndividual subscribers can also sign up for the $100 per month Super and $200 per month Ultra plans, which offer significantly higher usage limits than the “Premium” tier, but it’s unclear if the affected users were on the $30 plan.\n\n# What Has Musk Previously Said About Grok Bot?\nDuring SpaceX’s third-quarter earnings call two weeks ago, Musk hailed Grok Bot as the fastest-growing product he has ever seen, and said, “I’ve never seen anything grow this fast.” Musk also said the company is seeing Grok Bot usage grow over time per user, adding: “As we make Grok Bot more useful, we’re seeing users use it more per week, not use it less.” The billionaire said his company will deploy “Grok Bot at scale for enterprise customers,” is already in talks with some “trusted customers,” and is preparing for “wide deployment within a few weeks.” Musk also predicted that Grok Bot may end up being the product that “uses most of our SI compute.”\n\n# big number\n800,000. That’s how many paid weekly users Grok Bot had in early October, according to SpaceX President Gwynne Shotwell. In the company’s earnings call, she said this number had more than doubled over the previous month, and added that companies were using Grok Bot as a “force multiplier across sales, marketing, IT, and engineering, treating it as an always-on teammate for complex end-to-end workflows.”\n\n# tangent\nSeveral users also complained on Cursor’s community forum about unexpected spikes in their recorded Grok Bot usage without any actual increase in activity. SpaceX acquired the AI coding platform for $60 billion in August, and its subscription tiers now mirror xAI’s subscription prices. Cursor reported a billing and usage dashboard problem on Sunday, which was later marked as resolved, but it’s unclear if this is what was causing the spike in Grok Bot usage readings. According to xAI’s official subscription documentation, Grok and Cursor draw from a shared weekly usage allowance under the company’s unified subscription plans.\n\nGot a tip? Share confidential information with Forbes.\nEditorial Standards Reprints & Permissions\n\nLOADING VIDEO PLAYER...",
  "stderr": "",
  "interrupted": false,
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{
  "command": "node scripts/fetch.js \"https://techcrunch.com/2026/11/02/elon-musk-throttles-grok-bot-limits-due-to-unsustainably-high-costs/\" 2>&1 | sed -n '1,50p'",
  "description": "Fetch TechCrunch Grok Bot cost article"
}

{
  "stdout": "HTTP 200 · https://techcrunch.com/2026/11/02/elon-musk-throttles-grok-bot-limits-due-to-unsustainably-high-costs/ · text/html\nElon Musk throttles Grok Bot limits due to 'unsustainably high' costs | TechCrunch\n\n–:–:–:–\n\nBuy One Founder Summit Ticket, Get a Second for Free. Register now.\n\nFounder Summit begins Nov. 4, 9:00 a.m. ET. Get your pass savings & deals before it starts. REGISTER HERE.\n\nClose\n\nIn Brief\n\nPosted:\n\n8:23 AM PST · November 2, 2026\n\nImage Credits: Jonathan Raa/NurPhoto / Getty Images\n\n-\n\n- Amanda Silberling\n\n# Elon Musk throttles Grok Bot limits due to ‘unsustainably high’ costs\n\nOver Halloween weekend, some Grok Bot users awoke to something especially spooky: Their weekly usage limits were unexpectedly maxed out, even if they hadn’t been using SpaceX’s agentic AI overnight. Some users reported on X that their usage jumped from as low as 50% to 100% .\n\nSpaceX CEO Elon Musk confirmed in an X post on Sunday that this was not a glitch.\n\n“The cost of serving Grok Bot was unsustainably high relative to revenue,” he wrote in a reply to a question from a user. He has not addressed the issue on his main feed but has continued boasting that Grok Bot can help you buy gifts for your family.\n\nThe cost of serving Grok Bot was unsustainably high relative to revenue\n— Elon Musk (@elonmusk) November 1, 2026\n\nGrok Bot has been positioned as a success story for the newly public SpaceX, which said in a filing last month that AI now makes up 52% of company income. Its renamed “Super Intelligence” division actually turned a profit of $431 million, which is a rarity in the AI industry. Its profit would’ve been higher if not for $1.2 billion of one-time costs related to its acquisition of Cursor . Musk recently referred to Grok Bot as having “the fastest growth of a product that I’ve ever seen in my life.”\n\nMusk has not yet shared how subscribers’ usage limits will be impacted moving forward.\n\nTopics\n\nAI , Elon Musk , Grok , In Brief\n\nNovember 4\n\nBoston\n\nBuy One Pass, Get a Second Free\n\nCover more ground at TechCrunch’s ultimate founder bootcamp of the year by bringing your co-founder or partner for free",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}

{
  "query": "Flourish Science press release November 3 2026 randomized controlled trial university students Sunnie",
  "mode": "extended"
}

{
  "query": "Flourish Science press release November 3 2026 randomized controlled trial university students Sunnie",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Qysm1to393Gdf5avTYzmmG",
      "content": [
        {
          "title": "Harvard Working Paper Finds Flourish AI App Improves Stress, Depression, and Anxiety Symptoms",
          "url": "https://www.manilatimes.net/2026/11/03/tmt-newswire/plentisoft/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/2460422"
        },
        {
          "title": "Big News: Flourish Featured in the First RCT Study on AI for Well-Being",
          "url": "https://www.myflourish.ai/post/big-news-flourish-featured-in-a-harvard-study"
        },
        {
          "title": "Flourish Science: Rethinking Mental Health and Habit Building with AI",
          "url": "https://www.myflourish.ai/post/flourish-science-rethinking-mental-health-and-habit-building-with-ai"
        },
        {
          "title": "In Charts: Can an App Help Improve Your Well-Being?",
          "url": "https://www.library.hbs.edu/working-knowledge/in-charts-can-ai-be-your-well-being-coach"
        },
        {
          "title": "Study of Student Flourishing",
          "url": "https://clinicaltrials.gov/study/NCT07259746"
        },
        {
          "title": "The Safety Gap in AI Companions—And What Sets Sunnie Apart",
          "url": "https://www.myflourish.ai/post/the-safety-gap-in-ai-companions--and-what-sets-sunnie-apart"
        },
        {
          "title": "A randomized controlled trial of mindfulness: effects on academic stress, academic burnout, and psychological resilience in university students",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12696859/"
        },
        {
          "title": "Yoga as a therapeutic approach to mental health in university students: a randomized controlled trial",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11188441/"
        },
        {
          "title": "Xuan Zhao",
          "url": "https://en.wikipedia.org/wiki/Xuan_Zhao"
        },
        {
          "title": "Starting well to stay well - randomised controlled trial of Whitu, an app for improving the well-being of university students",
          "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11859014/"
        }
      ]
    },
    "The November 3, 2026 press release reports a larger, symptom-focused result than some other sources describe, so the claims need to be read separately.\n\n- **Press release (Manila Times, Nov 3, 2026):** A six-week randomized trial of 1,137 university students reported that Flourish users had lower stress, depression, and anxiety scores than the control group. Those assigned to use Flourish, an evidence-based, safety-first AI mental health and well-being app developed by Flourish Science, had significantly lower stress, depression, and anxiety symptom scores after six weeks. The release describes the paper as a Harvard working paper.\n- **Study design (company blog):** The trial partnered with Foothill College, Chapman University, and the University of Washington, with Harvard professor Julian De Freitas. Users of the app group were asked to use it at least 2 days a week, including by chatting with Sunnie, and the control group got access only after the study ended.\n- **Conflicting account (Harvard Business School):** A separate write-up says the study, \"AI for Proactive Mental Health: A Multi-Institutional, Longitudinal, Randomized Controlled Trial,\" accepted for publication in the New England Journal of Medicine AI, found benefits came by boosting emotional, social, and general well-being, rather than by lowering negative mental health symptoms like anxiety or depression. This contradicts the press release's symptom-reduction claim.\n- **Other sample sizes:** Earlier company material cites a smaller trial: 486 students across three diverse higher education institutions. The ClinicalTrials.gov registry (NCT07259746) lists Flourish Science, Inc. as sponsor, with a start date of 2025-09-22 and estimated completion in May 2026.\n\nCaveat: I did not confirm the 1,137-student figure against the working paper or a journal, and the press release is a company-issued document. The HBS summary and the press release disagree on whether symptoms were reduced, so the paper itself should be checked before relying on either account."
  ],
  "durationSeconds": 7.105215291999979,
  "searchCount": 1
}

{
  "command": "node scripts/fetch.js \"https://nypost.com/2026/11/02/business/openai-plans-to-use-less-electricity-when-grid-is-strained-at-this-new-facility/\" 2>&1 | sed -n '1,60p'",
  "description": "Fetch NY Post OpenAI grid article"
}

{
  "stdout": "HTTP 403 · https://nypost.com/2026/11/02/business/openai-plans-to-use-less-electricity-when-grid-is-strained-at-this-new-facility/ · text/plain\nBlocked by egress policy",
  "stderr": "",
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  "bashEditDiff": {
    "files": [],
    "moreFiles": 1,
    "changedFiles": [
      "/home/user/ainews/trace/2026-11-03.transcript.jsonl"
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    "unavailable": true,
    "shared": true
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{
  "query": "OpenAI Grid Protectors Program demand response data center electricity curtail",
  "mode": "extended"
}

{
  "query": "OpenAI Grid Protectors Program demand response data center electricity curtail",
  "results": [
    {
      "tool_use_id": "srvtoolu_016vDvm4H9UfEcJVmFFg1Pk7",
      "content": [
        {
          "title": "OpenAI Pledges to Cut Data Center Power Use by 1 Gigawatt",
          "url": "https://www.kucoin.com/news/flash/openai-pledges-to-cut-data-center-power-use-by-1-gigawatt"
        },
        {
          "title": "OpenAI launches Grid Protectors Program to cut data center power use during emergencies",
          "url": "https://cryptobriefing.com/openai-grid-protectors-program-data-centers/"
        },
        {
          "title": "OpenAI Grid Protectors: AI Campuses to Cut Power at Peaks",
          "url": "https://shiftdelete.net/en/openai-grid-protectors"
        },
        {
          "title": "OpenAI's Grid Protectors Program for Power Grid Stability",
          "url": "https://thechenabtimes.com/2026/11/02/openai-launches-grid-protectors-program-to-enhance-power-grid-stability/"
        },
        {
          "title": "OpenAI launches Grid Protectors to ease AI’s strain on power grids",
          "url": "https://daily.dev/posts/openai-launches-grid-protectors-to-ease-ai-s-strain-on-power-grids-qenhhpcrv"
        },
        {
          "title": "OpenAI Unveils Grid Protectors Program to Overcome Data Center Opposition",
          "url": "https://www.webpronews.com/openai-unveils-grid-protectors-program-to-overcome-data-center-opposition"
        },
        {
          "title": "OpenAI Grid Protectors Program: Powerful 1 GW Demand-Response Plan Explained - Techgenyz",
          "url": "https://techgenyz.com/openai-launches-grid-protectors-program/"
        },
        {
          "title": "Power-Flexible AI Data Centers: A New Paradigm for Grid-Responsive Compute",
          "url": "https://arxiv.org/pdf/2606.25098"
        },
        {
          "title": "Shift or curtail? How much data-center flexibility is worth depends on the host power grid",
          "url": "https://arxiv.org/pdf/2608.19622"
        },
        {
          "title": "From Grid to Chip: Power Architecture, Stability, and Flexibility of AI Data Centers",
          "url": "https://arxiv.org/pdf/2609.11649"
        }
      ]
    },
    "The search results describe the Grid Protectors Program as a new OpenAI initiative announced November 2, 2026, but they are all secondary coverage and none is the primary OpenAI post.\n\n- **Scope:** OpenAI's future campuses would reduce electricity use when local grids are strained. Each campus would agree with its local utility on how much power it can give up, how quickly, and for how long. The company has not yet said which other campuses will join the program or what curtailment terms they will carry.\n- **Georgia pilot:** The flagship deal is at the planned Effingham County campus. Georgia Power can cut up to 1,000 megawatts at busy times under a 25-year deal approved in August. Coverage puts that at roughly the average electricity demand of 700,000 homes. OpenAI also agreed to pay the full cost of the power lines and service the campus requires.\n- **Campus size:** Sources disagree on wording. One says the campus is expected to require approximately 3,200 MW of electricity demand, which is distinct from its planned 1,000 MW flexible demand-response commitment.\n- **Operations:** A campus is designed to throttle its load when the grid hits peak demand, and to use more power when the grid has room to spare. Some sites may also feed power back to the grid from on-site generators or batteries, with terms varying by location.\n- **Limits:** OpenAI itself says flexibility \"cannot replace investment in new energy supply and transmission.\"\n- **Policy context:** Proposed Senate legislation aims to empower states to mandate peak-hour power curtailment as a condition for data center grid connections. Texas Senate Bill 6 (2025) requires large loads to install remote-disconnect capability and to curtail during grid emergencies, with implementation beginning in 2026."
  ],
  "durationSeconds": 7.191127609000076,
  "searchCount": 1
}

{
  "url": "https://www.manilatimes.net/2026/11/03/tmt-newswire/plentisoft/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/2460422",
  "prompt": "Give the date, who issued the release, study design, sample size, duration, named institutions, exact result wording and any numbers, and the working paper title/number."
}

{
  "bytes": 358376,
  "code": 200,
  "codeText": "OK",
  "result": "**Date:** November 3, 2026 (the release is datelined Palo Alto, California).\n\n**Issuer:** The release is credited to Plentisoft and was distributed through The Manila Times' TMT Newswire. Flourish Science Inc. is the company behind the app, and the listed media contact is Jose Iniguez of Flourish Science.\n\n**Study design:** Randomized controlled trial. Students were randomly assigned either to use Flourish, with instructions to use it at least twice weekly, or to a care-as-usual control group. Both groups kept access to existing campus and personal mental health resources.\n\n**Sample size:** 1,137 university students at a large North American university (unnamed).\n\n**Duration:** Six weeks.\n\n**Named institutions and organizations:**\n- Harvard Business School (working paper series)\n- Flourish Science (developer)\n- NEJM AI and the New England Journal of Medicine Group (publisher of the app's earlier trial)\n- Harvard Business School AI Institute (cited for a separate publication)\n- CMS (ACCESS Model, mentioned as an alignment target)\n\n**Working paper title and number:** \"AI-Powered Prevention and Early Intervention for Stress, Depression, and Anxiety: A Randomized Clinical Trial,\" Harvard Business School Working Paper No. 27-002.\n\n**Exact result wording:**\n- Flourish users had \"significantly lower stress, depression, and anxiety symptom scores after six weeks\" than controls.\n- Early intervention: among students with elevated symptoms and available six-week data, 52.3% of Flourish users achieved meaningful improvement in depressive symptoms, versus 31.7% of controls. For anxiety, the rates were 50.6% versus 38.1%. Meaningful improvement was defined as a reduction of at least two points on the PHQ-2 or GAD-2.\n- Prevention: among students with relatively low initial symptoms, depression and anxiety rose in both groups, but the increases were smaller for Flourish users. No figures are given for this group.\n- Exploratory: lower stress at Week 4 was associated with fewer depression and anxiety symptoms at Week 6.\n- Usage: sessions typically lasted 8 to 10 minutes.\n- Safety: no intervention-related adverse events were reported.\n\n**Context from the release:** The release describes this as a working paper. It also says a prior Flourish trial, published in NEJM AI in July 2026, found no significant effects on depression, anxiety, or stress. The release's figures are company-supplied, and the paper itself was not reviewed for this summary.",
  "durationMs": 10608,
  "url": "https://www.manilatimes.net/2026/11/03/tmt-newswire/plentisoft/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/2460422"
}

{
  "url": "https://cryptobriefing.com/openai-grid-protectors-program-data-centers/",
  "prompt": "Give publication date and all figures, quotes and attributions about the Grid Protectors Program, Georgia Power deal, megawatts, duration."
}

{
  "bytes": 161853,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** Monday, November 2, 2026, 08:44 EST (Crypto Briefing, by Diego Almada Lopez)\n\n**Grid Protectors Program**\n- OpenAI pledged to reduce electricity use at data center campuses it directly develops when extreme weather or other emergencies strain the US grid.\n- The company plans to extend commitments made in Georgia nationwide.\n- The article's framing: OpenAI \"wants to be the data center developer that steps aside when the power grid gets nervous.\"\n\n**Georgia Power deal (Project Camellia, Effingham County, GA)**\n- Projected demand at full build-out: 3.2 GW.\n- Contract length: 25 years.\n- Delivery phases: 2028 to 2032.\n- Flexible demand response: up to 1 GW, which lets Georgia Power cut energy supplied to the campus during high-demand events.\n- Construction targeted to begin in late 2026.\n- Full build-out investment: an estimated $20 billion to more than $30 billion.\n- OpenAI covers 100% of infrastructure and electric-service costs tied to the project, and the article says Georgia families are explicitly shielded from related rate increases.\n- Community benefits fund: $80 million, including up to $71 million in educational credits for Georgia students.\n- Georgia Public Service Commission approval: on or around August 26, 2026.\n\n**Other figures**\n- Southern Company (Georgia Power's parent) reports 17 GW of total contracted large-load capacity.\n\n**Attributions and caveats**\n- The article contains no direct quotes from OpenAI, Georgia Power, or regulators.\n- The pledge covers campuses OpenAI directly develops, not necessarily capacity it rents from cloud partners or third-party operators.\n- The article notes the real test of the phased schedule is years away.",
  "durationMs": 6506,
  "url": "https://cryptobriefing.com/openai-grid-protectors-program-data-centers/"
}

{
  "url": "https://techgenyz.com/openai-launches-grid-protectors-program/",
  "prompt": "Give publication date and all figures and quotes about the Grid Protectors Program, campuses, megawatts and the Georgia Power agreement."
}

{
  "bytes": 138124,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** The page gives no exact date. It shows \"2 hours ago,\" and the program was announced on November 2, 2026.\n\n**Key figures**\n- **Campus capacity:** The planned Effingham County, Georgia, campus is expected to need about 3,200 MW of electricity. This is separate from the flexible capacity below.\n- **Flexible demand response:** Up to 1,000 MW under the Georgia Power agreement, which OpenAI describes as \"up to 1,000 MW of flexible demand-response capacity.\"\n- **Household equivalence:** The 1,000 MW is roughly the average demand of about 700,000 households.\n- **Contract length:** The Georgia Power agreement covers 25 years.\n- **Customer savings projection:** Georgia Power projects about $950 million in annual customer savings from 2029, through its broader large-load customer portfolio, not only the OpenAI campus.\n- **Residential example:** A typical residential customer using 1,000 kWh per month could save at least $15 per month starting in 2029, according to Georgia Power's projections.\n\n**Georgia Power agreement and regulatory status**\n- OpenAI has committed to covering the infrastructure and electricity-service costs for the campus.\n- The contract cleared the Georgia Public Service Commission's regulatory review in August 2026. It did not receive a formal commission vote.\n\n**Quotes**\n- \"up to 1,000 MW of flexible demand-response capacity\"\n- \"equivalent to the average electricity demand of approximately 700,000 households\"\n- \"These figures represent planned capacity rather than electricity reductions already delivered to the grid.\"",
  "durationMs": 7203,
  "url": "https://techgenyz.com/openai-launches-grid-protectors-program/"
}

{
  "url": "https://www.nist.gov/artificial-intelligence",
  "prompt": "List news or publications dated November 2 or 3, 2026 with titles and URLs."
}

{
  "bytes": 98937,
  "code": 200,
  "codeText": "OK",
  "result": "The page contains no news items or publications dated November 2 or 3, 2026. The most recent dated items are from October and September 2026:\n\n- Key Practices for Incident Readiness and Response in Super Intelligence Training and Evaluation (October 2026): https://www.nist.gov/news-events/news/2026/10/key-practices-incident-readiness-and-response-super-intelligence-training\n- NIST Awards More Than $30 Million for MEP Centers in 11 States and Puerto Rico (September 2026): https://www.nist.gov/news-events/news/2026/09/nist-awards-more-30-million-mep-centers-11-states-and-puerto-rico\n- Spotlight: NIST Programmer Develops Software Libraries (September 2026): https://www.nist.gov/news-events/news/2026/09/spotlight-nist-programmer-develops-software-libraries\n\nThe blog posts listed on the page don't show dates, so I can't confirm whether any were published on November 2 or 3.",
  "durationMs": 4101,
  "url": "https://www.nist.gov/artificial-intelligence"
}

{
  "query": "\"November 2\" OR \"November 3\" 2026 artificial intelligence court ruling judge opinion sanctions",
  "mode": "extended"
}

{
  "query": "\"November 2\" OR \"November 3\" 2026 artificial intelligence court ruling judge opinion sanctions",
  "results": [
    {
      "tool_use_id": "srvtoolu_01WbaZQ9VTCbqk1y3ZatZZNx",
      "content": [
        {
          "title": "AI in litigation: Update on Gen AI sanctions in 2026",
          "url": "https://www.nortonrosefulbright.com/en-us/knowledge/publications/792d8bf3/ai-in-litigation-update-on-gen-ai-sanctions-in-2026"
        },
        {
          "title": "Brazilian lawyers busted for attempting to manipulate court's AI with prompt injection hidden in filing — court's AI flags hidden text that demanded superficial legal scrutiny, lawyers fined $16,000",
          "url": "https://tomshardware.com/tech-industry/artificial-intelligence/brazilian-lawyers-busted-for-attempting-to-manipulate-courts-ai-with-prompt-injection-hidden-in-filing-courts-ai-flags-hidden-text-that-demanded-superficial-legal-scrutiny-lawyers-fined-usd16-000"
        },
        {
          "title": "From Hallucination To Sanctions: The Potential Costs Of Unverified AI Citations",
          "url": "https://www.legal500.com/intelligence/united-states/litigation-mediation-arbitration/from-hallucination-to-sanctions-the-potential-costs-of-unverified-ai-citations"
        },
        {
          "title": "More than 8 in 10 Korean judges encounter AI-generated fake court rulings",
          "url": "https://www.koreajoongangdaily.com/korea/eight-in-10-judges-encounter-fake-ai-court-ruling-citations/12950176"
        },
        {
          "title": "Galileu Prompt Injection: Brazilian Court Fines Lawyers Over Hidden Filing Text",
          "url": "https://www.remio.ai/post/galileu-prompt-injection-brazilian-court-fines-lawyers-over-hidden-filing-text"
        },
        {
          "title": "K.G.M. v. Meta et al.",
          "url": "https://en.wikipedia.org/wiki/K.G.M._v._Meta_et_al."
        },
        {
          "title": "AI Hallucination Sanctions in 2026: 13 Verified Cases in One Table",
          "url": "https://legaldesire.com/ai-hallucination-sanctions-2026-table/"
        },
        {
          "title": "Tracking Federal Judge Orders On Artificial Intelligence",
          "url": "https://www.law360.com/pulse/ai-tracker"
        },
        {
          "title": "Appeals Court Rules on AI Use and Legal Fees",
          "url": "https://www.jdjournal.com/2026/11/03/court-ruling-ai-law-firm-legal-fees/"
        }
      ]
    },
    "Several reports from November 2–3, 2026 turned up. The search didn't return any single ruling that clearly covers both dates, so treat these as separate items.\n\n- **Tenth Circuit fee ruling (Nov. 2):** The appeals court held that using artificial intelligence alone did not establish unreasonable billing. It rejected a company's challenge to a law firm's fees, and the underlying lawsuit had been dismissed by a Colorado federal judge.\n- **Korean judges survey (Nov. 2):** More than eight in ten Korean judges surveyed said they have encountered fabricated court rulings. The National Court Administration said it plans countermeasures based on the findings.\n- **Brazilian prompt-injection sanctions (reported Nov. 1):** A labor court fined two lawyers after hidden white-on-white text in a filing tried to influence the court's AI tool. The fine was 10% of the value of the case, according to a court ruling quoted in one report. Another source dates the ruling to May 12, 2026, so the timing is unclear.\n- **Fifth Circuit criticism of a judge (undated):** One legal-news item describes a Fifth Circuit ruling that harshly criticizes a federal district judge for relying on AI-generated content in legal orders. I couldn't confirm its date from the results.\n- **Sanctions tracker (updated Nov. 2–3):** One database listed 2,262 decisions worldwide, 1,533 of them from the United States as of Nov. 2, 2026, which shows how common AI-citation sanctions have become."
  ],
  "durationSeconds": 8.663978882000084,
  "searchCount": 1
}

{
  "url": "https://www.jdjournal.com/2026/11/03/court-ruling-ai-law-firm-legal-fees/",
  "prompt": "Date, court, case name, docket, holding, amounts, and what was decided about AI use and fees."
}

{
  "bytes": 679206,
  "code": 200,
  "codeText": "OK",
  "result": "**Date:** November 2, 2026 (decision date; the article was published November 3, 2026)\n\n**Court:** U.S. Court of Appeals for the 10th Circuit (three-judge panel; opinion by Circuit Judge Carolyn McHugh)\n\n**Case:** Flux Drive Inc. v. Qiang Rong, Case No. 25-1308\n\n**Background:** Flux Drive sued a former engineer over alleged transfer of confidential information to a Chinese manufacturer. A Colorado federal judge dismissed the suit and ordered Flux Drive to pay the defendants' legal expenses.\n\n**Amount:** $115,000 in legal fees awarded to the defendants' counsel, Brownstein Hyatt Farber Schreck.\n\n**Holding:** The 10th Circuit upheld the $115,000 award. It rejected Flux Drive's argument that the firm's AI use justified cutting the fees, finding that Flux Drive had not shown AI made the billed hours unreasonable.\n\n**What was decided about AI and fees:**\n- AI use does not automatically make billed hours unreasonable or prove inflated billing.\n- A party challenging fees must identify specific problems with particular charges.\n- The ruling is narrow. It does not say AI can never justify lower fees.",
  "durationMs": 5807,
  "url": "https://www.jdjournal.com/2026/11/03/court-ruling-ai-law-firm-legal-fees/"
}

{
  "url": "https://www.koreajoongangdaily.com/korea/eight-in-10-judges-encounter-fake-ai-court-ruling-citations/12950176",
  "prompt": "Date, who conducted the survey, number of respondents, all percentages and numbers, and what actions the court administration announced."
}

{
  "bytes": 158789,
  "code": 200,
  "codeText": "OK",
  "result": "**Survey details**\n- **Date:** Published November 2, 2026. The survey ran October 6 to 16.\n- **Conducted by:** The National Court Administration, an agency under the Supreme Court.\n- **Respondents:** 360 judges nationwide.\n\n**Findings on fabricated citations** (respondents could select multiple answers)\n- 80.7% of judges handling civil, family, and administrative cases had encountered citations of nonexistent court rulings.\n- 65.4% had seen court rulings falsely cited.\n- 16.9% had encountered fabricated or nonexistent laws.\n- 4.1% had encountered fabricated or nonexistent academic papers or other materials.\n- 69.5% said litigants themselves submitted documents with such citations.\n- 57.6% named lawyers representing parties in civil cases or defendants in criminal cases.\n\n**Support for measures** (respondents could select multiple answers)\n- 91.7% said institutional measures were needed, and 64.8% called them highly necessary.\n- 61.4% supported a legal basis for administrative fines.\n- 61.1% favored requiring parties to verify the rulings they cite.\n- 60.6% supported mandatory disclosure of AI use.\n- 55.4% called for sanctions against lawyers, including disciplinary referrals.\n\n**Actions announced by the court administration**\n- Develop countermeasures based on the survey results.\n- Consult the Ministry of Justice and other relevant agencies.\n- Recommend amendments to the Civil Procedure Act and Criminal Procedure Act to the National Assembly, creating a legal basis for administrative fines and other penalties.\n- Consider issuing guidance on AI precautions to lawyers and litigants through the electronic litigation system.",
  "durationMs": 7187,
  "url": "https://www.koreajoongangdaily.com/korea/eight-in-10-judges-encounter-fake-ai-court-ruling-citations/12950176"
}

{
  "url": "https://www.sec.gov/Archives/edgar/data/0001108524/000119312526425881/d516983dex991.htm",
  "prompt": "Give the date, what is announced, all terms and figures, and any quotes."
}

{
  "bytes": 21707,
  "code": 200,
  "codeText": "OK",
  "result": "**Date:** October 20, 2026\n\n**Announcement:** Salesforce (NYSE: CRM) agreed to acquire Braze (NASDAQ: BRZE), a customer engagement platform, for about $5.66 billion in enterprise value.\n\n**Key terms and figures:**\n- Braze Class A common stockholders would receive $47.50 in cash per share.\n- The deal is expected to close in Salesforce's fiscal year 2028, subject to closing conditions, including Braze shareholder approval and required regulatory approvals.\n- Salesforce expects no change to its FY27 guidance. It has not issued FY28 guidance and is not updating its long-term targets.\n- Braze serves about 2,770 customers, including Canva, Dairy Queen, Equinox, Instacart, Urban Outfitters, and Venmo.\n\n**Advisors:**\n- Salesforce: J.P. Morgan Securities LLC (exclusive financial advisor); Wachtell, Lipton, Rosen & Katz and Covington & Burling LLP (legal counsel)\n- Braze: Qatalyst Partners (exclusive financial advisor); Davis Polk & Wardwell LLP (legal counsel)\n\n**Quotes:**\n- Patrick Stokes, President, Applications and Marketing, Salesforce: \"Braze was built to turn live customer behavior into personalized engagement at scale.\"\n- Bill Magnuson, CEO and Co-Founder, Braze: \"Salesforce shares our commitment to marketers, and we'll continue building as Braze...\"",
  "durationMs": 6442,
  "url": "https://www.sec.gov/Archives/edgar/data/0001108524/000119312526425881/d516983dex991.htm"
}

{
  "query": "Blackstone more equity needed fund AI buildout debt risks mount CNBC November 3 2026",
  "mode": "standard"
}

{
  "query": "Blackstone more equity needed fund AI buildout debt risks mount CNBC November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01UGdRkvJECyM684vepMZWPT",
      "content": [
        {
          "title": "Image Credits:Slava Blazer Photography",
          "url": "https://techcrunch.com/?p=3180358"
        },
        {
          "title": "Blackstone’s Jas Khaira downplays AI debt concerns amid market jitters",
          "url": "https://cryptobriefing.com/?p=399766"
        },
        {
          "title": "www.webull.ca",
          "url": "https://www.webull.ca/news-detail/15348117384291328"
        },
        {
          "title": "ai consolidation begins blackstone google forge an ai empire",
          "url": "https://www.barchart.com/story/news/2070386/ai-consolidation-begins-blackstone-google-forge-an-ai-empire"
        },
        {
          "title": "Blackstone sees AI buildout creating new opportunities for private credit",
          "url": "https://www.dealstreetasia.com/?p=498994"
        },
        {
          "title": "blackstones jas khaira says fears over ai buildout debt are overblown",
          "url": "https://aichief.com/news/blackstones-jas-khaira-says-fears-over-ai-buildout-debt-are-overblown/"
        },
        {
          "title": "blackstone in preliminary talks to finance oracles 10 billion michigan data center after blue owl exit 01 28 2026",
          "url": "https://www.roic.ai/news/blackstone-in-preliminary-talks-to-finance-oracles-10-billion-michigan-data-center-after-blue-owl-exit-01-28-2026"
        },
        {
          "title": "Blackstone Tying Up $3 Billion Loan Amid Data Center Debt Binge",
          "url": "https://news.bloombergtax.com/private-equity/blackstone-tying-up-3-billion-loan-amid-data-center-debt-binge"
        },
        {
          "title": "world politics tech business tabloid sports science health entertainment lifestyle food travel gaming",
          "url": "https://biztoc.com/x/4e4bc74fa9530b21"
        },
        {
          "title": "AI Consolidation Begins: Blackstone & Google Forge an AI Empire",
          "url": "https://www.pulse.bot/ai/news/ai-consolidation-begins-blackstone-google-forge-an-ai-empire-7c2522e0-8ae6-4de7-ae91-12e5b5fe1df5/"
        }
      ]
    },
    "I couldn't find the CNBC article from November 3, 2026, so I can't confirm its specific claims. The results below are related coverage from other outlets, and some dates differ from the one you asked about.\n\n- **Khaira's defense of AI debt:** Blackstone's AI chief, Jas Khaira, downplayed worries that the massive accumulation of AI infrastructure debt could lead to a widespread credit crisis. He argued that because the vast majority of data centers are built for hyperscalers, the debt financing them is ultimately backed by the most creditworthy companies. The TechCrunch piece is dated October 21, 2026, per its URL.\n- **Market stress:** Khaira acknowledged that the large debt burdens accumulated by these companies and other neocloud operators have begun to raise red flags. Another outlet reports that bonds connected to Blackstone projects traded below 88 cents during 2026, as data-center debt sold off more broadly.\n- **Equity push:** Blackstone and Alphabet announced a $5 billion joint venture to create a new AI cloud platform, with Blackstone making an initial $5 billion equity commitment to bring 500 megawatts of capacity online by 2027. That was reported in May 2026.\n- **Debt exposure:** In October 2026, Blackstone was reported to be committing $9 billion to a junior-debt tranche within an $18 billion financing package tied to AI chips and computing infrastructure for Anthropic. The firm also said about 7% of its $1.4 trillion in assets under management was exposed to AI infrastructure across debt and equity.\n\nSome sources here are low-quality aggregators, so treat their figures cautiously. Searching for the CNBC article directly, or for \"Blackstone equity raise\" with a date, would be the next step."
  ],
  "durationSeconds": 7.269944997999934,
  "searchCount": 1
}

{
  "query": "AI medicine regulation news November 3 2026 FDA CMS ONC health AI",
  "mode": "extended"
}

{
  "query": "AI medicine regulation news November 3 2026 FDA CMS ONC health AI",
  "results": [
    {
      "tool_use_id": "srvtoolu_01DExS2jGrsh4T8YtXdghVfP",
      "content": [
        {
          "title": "Manatt Health: Health AI Policy Tracker - Manatt, Phelps & Phillips, LLP",
          "url": "https://www.manatt.com/insights/newsletters/health-highlights/manatt-health-health-ai-policy-tracker"
        },
        {
          "title": "FDA Seeks Public Feedback to Inform Regulatory Approach for Generative AI-Enabled Medical Devices",
          "url": "https://www.fda.gov/news-events/press-announcements/fda-seeks-public-feedback-inform-regulatory-approach-generative-ai-enabled-medical-devices"
        },
        {
          "title": "Selected 2026 Healthcare AI Regulation Updates: U.S. and Canada",
          "url": "https://www.veroscribe.com/blog/healthcare-ai-regulation-tracker"
        },
        {
          "title": "FDA and CMS Move to Prevent Clash With State AI Sandboxes",
          "url": "https://aiweekly.co/alerts/fda-and-cms-move-to-prevent-clash-with-state-ai-sandboxes"
        },
        {
          "title": "FDA announces sweeping changes to oversight of wearables, AI-enabled devices",
          "url": "https://www.statnews.com/2026/01/06/fda-pulls-back-oversight-ai-enabled-devices-wearables/"
        },
        {
          "title": "AI Healthcare Regulations 2026: Federal and State Rules, Kept Current",
          "url": "https://livecompliance.com/learn/ai-healthcare-regulations/"
        },
        {
          "title": "Health AI Docket · The week in health-AI regulation",
          "url": "https://healthaidocket.com/"
        },
        {
          "title": "AI in Healthcare Statistics 2027: Market Growth & Adoption Data",
          "url": "https://cmarix.com/blog/ai-in-healthcare-statistics"
        },
        {
          "title": "Clinical AI Policy and Governance",
          "url": "https://physicianaihandbook.com/future/policy.html"
        },
        {
          "title": "News & Analysis as of",
          "url": "https://www.jdsupra.com/topics/department-of-health-and-human-services-hhs/artificial-intelligence/health-technology"
        }
      ]
    },
    "I didn't find any reporting dated November 3, 2026 specifically. The most recent items are from the past few days, and most of the rest are from August and September.\n\n- **FDA and CMS and state AI sandboxes:** A recent report says FDA and CMS officials are coordinating behind the scenes to avoid a regulatory logjam as more states stand up clinical-AI testing programs.\n- **FDA generative AI devices:** FDA issued a discussion paper on regulating generative artificial intelligence (GenAI)-enabled medical devices, with comments due October 19, 2026 under docket FDA-2026-N-7874. That deadline has passed, so the paper is now in the review stage.\n- **ONC HTI-5:** A proposed ONC rule would remove AI model card requirements for certified health IT. One tracker lists its effective date as Dec 28, 2026, but I couldn't confirm that date against the Federal Register.\n- **CMS WISeR model:** CMS's implementation of its model drew the significant federal pushback of the quarter.\n- **FDA device clearances:** In September, FDA codifies a new class II device type: cardiovascular machine learning-based notification software, and FDA's AI-enabled device list passes 1,600 authorized devices.\n\nFor same-day news, check FDA's press announcements, the Federal Register, and CMS newsroom directly."
  ],
  "durationSeconds": 6.476362390999915,
  "searchCount": 1
}

{
  "query": "Salesforce newsroom \"Cresta\" signs definitive agreement acquire press release",
  "mode": "standard"
}

{
  "query": "Salesforce newsroom \"Cresta\" signs definitive agreement acquire press release",
  "results": [
    {
      "tool_use_id": "srvtoolu_01EFAeECEQG8jG2VfPTCYUGH",
      "content": [
        {
          "title": "Salesforce Signs Definitive Agreement to Acquire Own Company",
          "url": "https://www.businesswire.com/news/home/20240905452826/en/Salesforce-Signs-Definitive-Agreement-to-Acquire-Own-Company"
        },
        {
          "title": "Salesforce Signs Definitive Agreement to Acquire Qualified",
          "url": "https://www.biia.com/category/company/salesforce"
        },
        {
          "title": "www.salesforce.com",
          "url": "https://www.salesforce.com/company/news-press/press-releases/2016/06/160627.jsp"
        },
        {
          "title": "as salesforce acquires ai startup cimulate should you buy sell or hold crm stock",
          "url": "https://www.barchart.com/story/news/187323/as-salesforce-acquires-ai-startup-cimulate-should-you-buy-sell-or-hold-crm-stock"
        },
        {
          "title": "www.businesswire.com",
          "url": "https://www.businesswire.com/news/home/20240905452826/en"
        },
        {
          "title": "2 min Applications",
          "url": "https://www.techzine.eu/news/applications/138775/salesforce-aims-to-make-e-commerce-smarter-with-cimulate-acquisition"
        },
        {
          "title": "Salesforce Advances AI Expansion With Cimulate Deal",
          "url": "https://www.pymnts.com/?p=3476088"
        },
        {
          "title": "www.intercom.com",
          "url": "https://www.intercom.com/blog/wp-json/wp/v2/posts/32172"
        },
        {
          "title": "martechseries.com",
          "url": "https://martechseries.com/?p=401165"
        },
        {
          "title": "• Live Feeds",
          "url": "https://www.quantisnow.com/insight/salesforce-signs-definitive-agreement-to-acquire-own-company-5684481"
        }
      ]
    },
    "The search didn't turn up any Salesforce announcement about acquiring Cresta, and no Salesforce newsroom release mentioning Cresta appeared in the results. I can't confirm whether that deal exists.\n\nThe results did include other Salesforce acquisition announcements:\n\n- **Own Company:** Salesforce agreed to buy the data backup company for about $1.9 billion in cash, according to the Business Wire release, with the deal expected to close in Salesforce's fiscal year 2025 fourth quarter.\n- **Cimulate:** A February 10 press release announced a definitive agreement for this AI product-discovery company, with closing expected in Salesforce's fiscal 2027 first quarter.\n- **Contentful:** Salesforce announced a definitive agreement to acquire this composable content platform.\n- **Fin and Qualified:** Other results mention definitive agreements for these companies, but the snippets gave few details.\n\nTo find the Cresta release, try the Salesforce newsroom directly (salesforce.com/news) or search for \"Cresta\" alongside \"Salesforce acquisition\" to see whether the deal was announced under a different name."
  ],
  "durationSeconds": 6.226157895000069,
  "searchCount": 1
}

{
  "query": "biggest AI news November 3 2026",
  "mode": "extended"
}

{
  "query": "biggest AI news November 3 2026",
  "results": [
    {
      "tool_use_id": "srvtoolu_01VDNkqKYDvMxwgGTXg8PbG4",
      "content": [
        {
          "title": "AI News Today, November 2: Top Stories",
          "url": "https://aiweekly.co/ai-news-today"
        },
        {
          "title": "AI News: Artificial Intelligence Stories, Ranked",
          "url": "https://aiweekly.co/"
        },
        {
          "title": "Artificial intelligence news: Chat AI, ChatGPT, AI generator, AI Chatbot and Bard",
          "url": "https://www.nbcnews.com/artificial-intelligence"
        },
        {
          "title": "Artificial Intelligence News -- ScienceDaily",
          "url": "https://www.sciencedaily.com/news/computers_math/artificial_intelligence/"
        },
        {
          "title": "AI - Bloomberg",
          "url": "https://www.bloomberg.com/ai"
        },
        {
          "title": "ai news alibabas 53b ai push drives 10d",
          "url": "https://avihacker.substack.com/p/ai-news-alibabas-53b-ai-push-drives-10d"
        },
        {
          "title": "Sitemap - 2024 - AI Tactical Toolbox",
          "url": "https://avihacker.substack.com/sitemap/2024"
        },
        {
          "title": "Trending AI news stories + github projects",
          "url": "https://akhaliq.substack.com/p/trending-ai-news-stories-github-projects?open=false"
        },
        {
          "title": "AK’s Substack",
          "url": "https://akhaliq.substack.com/p/trending-ai-news-stories-papers-96e"
        }
      ]
    },
    "The search didn't return a page dated specifically to November 3, 2026. The freshest results are aggregator pages, one headed \"AI News Today, November 2,\" so treat these as the latest headlines available, not confirmed November 3 news.\n\n- **Deals and M&A:** Marvell has agreed to a $115B all-stock deal for Lumentum, which would be the biggest public-tech M&A ever. Abu Dhabi has also signed four deals with OpenAI as part of an AI-focused government push (Abu Dhabi inks four OpenAI deals in AI-native government push).\n- **Anthropic IPO:** Anthropic's IPO filing sets aside $3.5B of US shares for Japanese investors (Anthropic Filing Earmarks $3.5B of US IPO Shares for Japanese Investors).\n- **Funding and market mood:** Bloomberg reports that OpenAI Funding Target Cut by $10 Billion as AI Slumps, Report Says, and one of its headlines says AI Enthusiasm Is Collapsing and Tech Earnings Just Made It Worse.\n- **Benchmarks:** One headline reports that the GDPx benchmark puts Claude Opus 5.5 at just 12% (GDPx benchmark caps top AI model Claude Opus 5.5 at just 12%). I'd verify this one before relying on it.\n- **Security and abuse:** A Northflank breach pushes Wiz's October AI-platform attack tally to nine. Wired reports 400+ Apps Run Covert Deepfake Network Across Apple and Meta Stores.\n- **Chips and infrastructure:** UK startup Salience Labs raised $125M for AI data-center switching, and Envision switched on what it calls the World's First Commercial 800V DC AI Data Center.\n- **Policy and science:** South Korea pledges $16B for AI in 2027 budget, and mathematician Terence Tao is saying AI is forcing a 'Maths 2.0' reckoning."
  ],
  "durationSeconds": 8.741682273000013,
  "searchCount": 1
}

{
  "url": "https://www.techmonitor.ai/news/salesforce-to-acquire-voice-ai-company-cresta",
  "prompt": "Give publication date, all deal terms and figures, Cresta's metrics (ARR, customers, funding), quotes, and who reported the price."
}

{
  "bytes": 243305,
  "code": 200,
  "codeText": "OK",
  "result": "**Publication date:** November 3, 2026 (by Anwesha Pattanaik, Tech Monitor)\n\n**Deal terms**\n- Salesforce has signed a definitive agreement to acquire Cresta, a voice-first customer experience platform.\n- Salesforce did not disclose the purchase price.\n- The Information reported a valuation of $2.7bn.\n- The deal is expected to close in Q1 of Salesforce's fiscal year 2028, pending regulatory approvals and other standard conditions.\n- Cresta's technology will be integrated with Salesforce Service Cloud.\n- After the acquisition, Cresta will continue supporting its customers' existing contact centre and telephony platforms.\n\n**Cresta metrics**\n- **ARR:** Not stated.\n- **Funding:** Not stated.\n- **Customers:** No total count is given. Comcast, Marriott, and Alaska Airlines are named as users of its technology.\n\n**Quotes**\n- Kishan Chetan, Salesforce EVP and GM, Agentforce and Service Cloud: \"Voice is where service is hardest to get right, and where it matters most to customers.\"\n- Ping Wu, Cresta CEO: \"Cresta's mission is to turn every customer interaction into a competitive advantage for our customers\"\n\n**Price reporting:** The $2.7bn valuation was reported by *The Information*, citing a person familiar with the transaction.",
  "durationMs": 6763,
  "url": "https://www.techmonitor.ai/news/salesforce-to-acquire-voice-ai-company-cresta"
}

{
  "command": "for d in 10.64898/2026.10.30.26366943 10.64898/2026.11.02.26364999 10.64898/2026.10.30.26366942 10.64898/2026.10.30.26366929 10.64898/2026.10.30.26366939; do echo \"== $d\"; node scripts/fetch.js \"https://doi.org/$d\" 2>&1 | head -c 220; echo; done",
  "description": "Verify medRxiv DOI links resolve"
}

{
  "stdout": "== 10.64898/2026.10.30.26366943\nHTTP 403 · http://medrxiv.org/lookup/doi/10.64898/2026.10.30.26366943 · text/html\nJust a moment...\n\n== 10.64898/2026.11.02.26364999\nHTTP 403 · http://medrxiv.org/lookup/doi/10.64898/2026.11.02.26364999 · text/html\nJust a moment...\n\n== 10.64898/2026.10.30.26366942\nHTTP 403 · http://medrxiv.org/lookup/doi/10.64898/2026.10.30.26366942 · text/html\nJust a moment...\n\n== 10.64898/2026.10.30.26366929\nHTTP 403 · http://medrxiv.org/lookup/doi/10.64898/2026.10.30.26366929 · text/html\nJust a moment...\n\n== 10.64898/2026.10.30.26366939\nHTTP 403 · http://medrxiv.org/lookup/doi/10.64898/2026.10.30.26366939 · text/html\nJust a moment...",
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{
  "query": "data center deal announced November 3 2026 gigawatt billion AI compute agreement",
  "mode": "extended"
}

{
  "query": "data center deal announced November 3 2026 gigawatt billion AI compute agreement",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Vo41wGYTkiMc6z5Aw1bXGg",
      "content": [
        {
          "title": "Nvidia and SK Group announce $500bn AI agreement, includes 2GW of data center capacity - DCD",
          "url": "https://www.datacenterdynamics.com/en/news/nvidia-and-[token redacted]/"
        },
        {
          "title": "Exascale Labs Inc. - Form 425 - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0002110790/000182912626007615/dboralarc_425.htm"
        },
        {
          "title": "Inside OpenAI’s $1 Trillion Compute Bet: How The AMD Deal Is Redefining Data Centre Infrastructure",
          "url": "https://www.verdantix.com/client-portal/blog/inside-openai-s--1-trillion-compute-bet--how-the-amd-deal-is-redefining-data-centre-infrastructure"
        },
        {
          "title": "Oracle-OpenAI $300B Deal Explained: 2026 Update",
          "url": "https://intuitionlabs.ai/articles/oracle-openai-300b-deal-analysis"
        },
        {
          "title": "Digi Power X Inc. - Form 8-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001854368/000121390026053566/ea028958501ex99-1.htm"
        },
        {
          "title": "Alpha Compute Corp - Form 6-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001095435/000117184326003368/exh_991.htm"
        },
        {
          "title": "Axe Compute Inc. - Form 8-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001446159/000117184326005581/exh_991.htm"
        },
        {
          "title": "Babcock & Wilcox Enterprises, Inc. - Form 8-K - FY2025",
          "url": "https://www.sec.gov/Archives/edgar/data/1630805/000110465925106447/tm2530246d1_ex99-3.htm"
        },
        {
          "title": "Brookfield's £20B AI Data Center at Drax Power Station · TFTC",
          "url": "https://www.tftc.io/brookfield-drax-radiant-ai-data-center-north-yorkshire-20-billion"
        }
      ]
    },
    "The search turned up one deal that matches today's date. A Drax, Brookfield, and Radiant agreement for a gigawatt-scale AI data center at Drax Power Station in North Yorkshire is dated November 3. Its total investment could exceed £20 billion ($26.8B) if the project is built in full. Drax's site already has grid capacity: a 4 GW connection and 2.6 GW of dispatchable generation on site.\n\nOther results are not from today:\n- **Nvidia and SK Group** announced a $500 billion-plus agreement that includes a 2 GW AI factory. The source is dated 25 days ago, so it is not from November 3.\n- **OpenAI and AMD**: the source describes a deal announced in October 2025 for up to 6 GW of AMD chips. It is also not new.\n- **Smaller deals**: several SEC filings describe 40 MW to 55 MW colocation or GPU contracts. These are small and were not dated November 3 in the results.\n\nOnly the Drax deal was clearly dated November 3, 2026, based on this single search. I did not confirm it through a second source."
  ],
  "durationSeconds": 6.430649163000052,
  "searchCount": 1
}

{
  "query": "AI news November 3 2026 model release benchmark announcement frontier lab",
  "mode": "extended"
}

{
  "query": "AI news November 3 2026 model release benchmark announcement frontier lab",
  "results": [
    {
      "tool_use_id": "srvtoolu_015VkzBa1DtsRj1weKUryJSM",
      "content": [
        {
          "title": "OpenAI o3",
          "url": "https://en.wikipedia.org/wiki/OpenAI_o3"
        },
        {
          "title": "LLM News Today (November 2026)",
          "url": "https://llm-stats.com/ai-news"
        },
        {
          "title": "The Biggest Benchmark in AI Just Updated, Dealing a Major Blow to a Chinese Contender",
          "url": "https://gizmodo.com/the-biggest-benchmark-in-ai-just-updated-dealing-a-major-blow-to-a-chinese-contender-2000832292"
        },
        {
          "title": "AI News Today, November 2: Top Stories",
          "url": "https://aiweekly.co/ai-news-today"
        },
        {
          "title": "Digg",
          "url": "https://digg.com/tech/8p8yp09u"
        },
        {
          "title": "AI News - Nov 02, 2026 - Agentic Benchmarks and Physical AI Safety",
          "url": "https://riorundown.substack.com/p/ai-news-nov-02-2026-agentic-benchmarks"
        },
        {
          "title": "Mistral Large 4 (Le Chonk) is now open weight",
          "url": "https://mistral.ai/news/mistral-large-4-oss/"
        },
        {
          "title": "GDPx AI Benchmark Tops Out at 12% as Claude Opus 5.5 Leads",
          "url": "https://shiftdelete.net/en/gdpx-ai-benchmark"
        },
        {
          "title": "GDPx Benchmark: Best Frontier AI Scores 12% on Real Work, Zero on Finance and Legal",
          "url": "https://www.techtimes.com/articles/329945/20261103/gdpx-benchmark-best-frontier-ai-scores-12-real-work-zero-finance-legal.htm"
        }
      ]
    },
    "Search results from the last few days point to a benchmark launch as the main story, with a few model releases alongside it. I couldn't independently verify these claims, and some sources conflict or look unreliable.\n\n- **GDPx benchmark (SemiAnalysis, Nov 2):** SemiAnalysis's GDPx benchmark tested 13 frontier AI models on 206 real professional tasks. Best score: 12%. Anthropic's Claude Opus 5.5 placed first, ahead of Google's Gemini 4 Carbon at 10.9% and OpenAI's GPT-6 Astra at 9.6%. Finance and legal returned zero across every model.\n- **Mistral Large 4:** Mistral's own announcement says its 1-trillion-parameter multimodal model is now open-weight and ranks as the best open-weight model for coding, according to the company.\n- **Kimi K3.1 Pro (Moonshot AI):** It charted at fourth place on the Artificial Analysis Intelligence Index v4. Moonshot hasn't released the model's weights yet, and won't until November 4.\n- **Artificial Analysis Intelligence Index v5:** One source reports that a new leader, \"Carbon,\" ranks #1 on the recently updated v5.0 of Artificial Analysis Intelligence Index at 59.\n- **Earlier OpenAI release:** OpenAI released GPT-6 Rosalind Research on October 30 for biology and drug discovery, reusing GPT-6 Astra weights but relaxing refusals on dual-use biological queries under a trusted-access program.\n\nCaveats: the search returned no official announcements from the labs for the November 3 date itself. Several model names (GPT-6, Claude Opus 5.5, Gemini 4 Carbon) appear only in secondary coverage, and one source's benchmark page was over 280 days old. Check the labs' own blogs or the benchmark sites before relying on these details."
  ],
  "durationSeconds": 7.46049498800002,
  "searchCount": 1
}

{
  "query": "Artificial Analysis Intelligence Index v5 launch Gemini 4 Carbon 59 ranking",
  "mode": "extended"
}

{
  "query": "Artificial Analysis Intelligence Index v5 launch Gemini 4 Carbon 59 ranking",
  "results": [
    {
      "tool_use_id": "srvtoolu_01T7ujrnvG4PzY1SG6hE32Xm",
      "content": [
        {
          "title": "Gemini 4 Carbon Tops Artificial Analysis Intelligence Index v5",
          "url": "https://hyper.ai/en/stories/15f5bd966043d9a81fa34dbbb9b03339"
        },
        {
          "title": "Gemini 4 Carbon Ranks No. 1 on Artificial Analysis Index, Ahead of Claude Opus 5.5",
          "url": "https://www.trendingtopics.eu/gemini-4-carbon-dethrones-claude-opus-5-5/"
        },
        {
          "title": "Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5",
          "url": "https://artificialanalysis.ai/articles/gemini-4-carbon-new-number-1"
        },
        {
          "title": "Artificial Analysis Intelligence Index v5.0",
          "url": "https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index"
        },
        {
          "title": "Announcing Artificial Analysis Intelligence Index v5",
          "url": "https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v5"
        },
        {
          "title": "Comparison of AI Models across Intelligence, Performance, and Price",
          "url": "https://artificialanalysis.ai/models"
        },
        {
          "title": "Google's Gemini 4 Carbon Tops Artificial Analysis Intelligence Index, Becomes Top AI Model In The World",
          "url": "https://officechai.com/ai/googles-gemini-4-carbon-tops-artificial-analysis-intelligence-index-becomes-top-ai-model-in-the-world/"
        },
        {
          "title": "AA Intelligence Index leaderboard (Nov 2026)",
          "url": "https://www.benchleader.com/benchmarks/aa_intelligence_index_v5"
        },
        {
          "title": "Best AI Models in November 2026: Updated Rankings and Comparisons",
          "url": "https://felloai.com/best-ai-models/"
        }
      ]
    },
    "Gemini 4 Carbon ranks first on the Artificial Analysis Intelligence Index v5, with a score of 59 (reported as 59.4 by some sources).\n\n- **Launch and standing:** Artificial Analysis says Gemini 4 Carbon scores 59 on Intelligence Index v5, driven by leading performance in complex reasoning, knowledge, and scientific tasks. Its own leaderboard lists Gemini 4 Carbon (High) currently has the highest Artificial Analysis Intelligence Index score, with a score of 59.\n- **Comparison:** The previous leader was Anthropic's Claude Opus 5.5, which had led the index, with 58 points at launch. The lead is narrow. One source notes the lead over Opus 5.5 in the overall index is a single point.\n- **Per-evaluation wins:** Gemini 4 Carbon leads the Intelligence Index v5, with the #1 score in 4 of the 9 Index evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, AutomationBench-AA.\n- **Coding:** It is only 3 points behind Claude Code with Claude Opus 5.5 (max, 62) on the Artificial Analysis Coding Agent Index.\n- **Cost:** Artificial Analysis reports it costs $7.76 per Intelligence Index task, ~23% less than Claude Opus 5.5 (max, $10.04).\n- **Discrepancies:** Sources differ on precision. The Artificial Analysis pages and most news coverage say 59. A third-party leaderboard gives 59.4 for Carbon (high) and 58.4 for Opus 5.5, dated as of 3 Nov 2026. One review site also reports 59.4 for the high-effort setting. The 59.4 figure appears only in these secondary sources, so I'd treat the exact decimal as unconfirmed. The launch was around 28 October 2026."
  ],
  "durationSeconds": 7.142354720000061,
  "searchCount": 1
}

{
  "query": "Kimi K3.1 Pro Moonshot AI weights release November 2026 benchmark",
  "mode": "extended"
}

{
  "query": "Kimi K3.1 Pro Moonshot AI weights release November 2026 benchmark",
  "results": [
    {
      "tool_use_id": "srvtoolu_01ALWsXD4dcBBAkdKeDXuvvg",
      "content": [
        {
          "title": "Kimi K3.1 Pro: Moonshot AI's Open-Weight Model Challenges Opus and Astra",
          "url": "https://www.mindstudio.ai/blog/kimi-k3-1-pro-open-weight-model"
        },
        {
          "title": "Kimi K3.1 Pro: Specs, Price, Open Weights Date, and Benchmarks",
          "url": "https://www.yottalabs.ai/post/kimi-k3-1-pro-specs-price-open-weights-benchmarks"
        },
        {
          "title": "Moonshot releases Kimi K3.1 Pro and says it cut its hacking skills",
          "url": "https://thenextweb.com/news/moonshot-kimi-k3-1-pro-open-weight-cyber"
        },
        {
          "title": "Kimi K3.1 Pro: Benchmarks and What's New",
          "url": "https://www.eigent.ai/blog/kimi-k3-1-pro-open-weight-model"
        },
        {
          "title": "Kimi K3.1 Pro Guide: Pricing, Benchmarks, Open Weights",
          "url": "https://codersera.com/blog/kimi-k3-1-pro-complete-guide-2026/amp/"
        },
        {
          "title": "Moonshot AI",
          "url": "https://en.wikipedia.org/wiki/Moonshot_AI"
        },
        {
          "title": "Kimi K3.1 Pro: Price, Benchmarks and Open Weights Date",
          "url": "https://cellcog.ai/blog/kimi-k3-1-release-date/"
        },
        {
          "title": "Qwen",
          "url": "https://en.wikipedia.org/wiki/Qwen"
        },
        {
          "title": "Kimi K3.1 Pro: Benchmarks, Pricing, API and Open Weights",
          "url": "https://www.piyushmehta.com/blog/kimi-k3-1-pro-open-weight-gap"
        },
        {
          "title": "Kimi K3.1 Pro: Pricing, Benchmarks, Open Weights Date",
          "url": "https://www.developersdigest.tech/blog/kimi-k3-1-pro-release-guide-2026"
        }
      ]
    },
    "Kimi K3.1 Pro was released through Moonshot's apps and API on October 23, 2026, but as of November 3 the open weights have not yet shipped. Moonshot has promised them by November 4.\n\n- **Release and pricing:** Moonshot launched it at $2 input and $10 output per million tokens, a third less than Kimi K3. Moonshot plans to publish the full model weights by 4 November.\n- **Specs:** Sources describe it as a post-trained version of K3, with 2.8T total and 104B active parameters, text and image input. One source says thinking cannot be turned off.\n- **Benchmarks (vendor-reported):** Moonshot reports 65.7% on Terminal-Bench 4.0, ahead of GPT-6 Astra (58.2%) and just behind Claude Opus 5.5 (66.4%).\n- **Benchmarks (independent):** Artificial Analysis reportedly measured the Terminal-Bench score at 67%, and the sources disagree on its overall index. One says K3.1 Pro lands around 46, while another says Claude Opus 5.5 scores 58 and Kimi K3.1 Pro scores 55. Treat the index figures as unreliable until checked against Artificial Analysis directly.\n- **Cyber safeguards:** Moonshot removed hacking-related training data to limit misuse of the open release. On its internal exploit benchmark, the released model solved 81%, still far above K3's 33.3%.\n\nSome sources are low-quality or inconsistent, including one with stale dates and another that mentions a July 31 report. I'd rely on Moonshot's announcement and Artificial Analysis for the numbers, and check Hugging Face or Moonshot's channels for the weights and license once they land, since Moonshot has not said which license the weights will use."
  ],
  "durationSeconds": 7.521474148000008,
  "searchCount": 1
}

{
  "url": "https://www.palantir.com/newsroom/press-releases/",
  "prompt": "List the most recent press releases with titles and dates, especially Q3 2026 results."
}

{
  "bytes": 425566,
  "code": 200,
  "codeText": "OK",
  "result": "The page content you provided contains only the heading \"Press Releases | Palantir\" and a link to a sitemap. It doesn't include any press release titles, dates, or Q3 2026 results.\n\nTo get this information, you could share the full text of the press releases page, or check Palantir's investor relations or newsroom website directly.",
  "durationMs": 2460,
  "url": "https://www.palantir.com/newsroom/press-releases/"
}

{
  "query": "NCSC Annual Review 2026 published November 3 Richard Horne unprecedented rise cyber incidents",
  "mode": "standard"
}

{
  "query": "NCSC Annual Review 2026 published November 3 Richard Horne unprecedented rise cyber incidents",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Qwx53LBDsShC846vN2zh9a",
      "content": [
        {
          "title": "UK Underestimates Threat Of Cyber-Attacks, Says NCSC Head",
          "url": "https://silicon.co.uk/security/security-management/uk-underestimates-threat-of-cyber-attacks-says-ncsc-head-591281/amp"
        },
        {
          "title": "UK Says Iran, China Drive Regular Significant Cyberattacks",
          "url": "https://amp.insurancejournal.com/news/international/2026/04/22/866825.htm"
        },
        {
          "title": "UK Underestimates Threat Of Cyber-Attacks, Says NCSC Head",
          "url": "https://www.silicon.co.uk/security/security-management/uk-underestimates-threat-of-cyber-attacks-says-ncsc-head-591281"
        },
        {
          "title": "Power station",
          "url": "https://therecord.media/uk-cyber-chief-warns-underestimate"
        },
        {
          "title": "Sikov - stock.adobe.com",
          "url": "https://www.computerweekly.com/news/366644872/Hostile-states-launched-200-attacks-on-UK-infrastructure-in-five-months-says-NCSC-chief"
        },
        {
          "title": "UK faces surge in major cyber attacks, NCSC warns",
          "url": "https://the-european.eu/?p=52428"
        },
        {
          "title": "24th October 2025",
          "url": "https://commscouncil.uk/press/ncsc-publish-annual-review-2025/"
        },
        {
          "title": "UK faces surge in major cyber attacks, NCSC warns",
          "url": "https://the-european.eu/story-52428/uk-faces-surge-in-major-cyber-attacks-ncsc-warns.html"
        },
        {
          "title": "Annual Review 2025 launch",
          "url": "https://www.ncsc.gov.uk/sites/default/files/2026-07/Annual-Review-2025-launch.pdf"
        },
        {
          "title": "ncsc annual review 2025",
          "url": "https://www.gchq.gov.uk/news/ncsc-annual-review-2025"
        },
        {
          "title": "UK: NCSC Reports 130% Spike in \"Nationally Significant\" Cyber Incidents",
          "url": "https://www.infosecurity-magazine.com/news/uk-ncsc-spike-national-cyber/"
        },
        {
          "title": "UK underestimates threat from hostile states, says new NCSC head",
          "url": "https://www.itpro.com/security/cyber-attacks/uk-underestimates-threat-from-hostile-states-says-new-ncsc-head"
        },
        {
          "title": "theprint.in",
          "url": "https://theprint.in/world/uk-must-brace-for-rise-in-state-backed-cyberattacks-security-chief-says/2911336/"
        },
        {
          "title": "uk reports 50 rise in highly significant cyberattack incidents affecting critical sectors",
          "url": "https://www.inkl.com/news/uk-reports-50-rise-in-highly-significant-cyberattack-incidents-affecting-critical-sectors"
        },
        {
          "title": "uk critical infrastructure hit by 200 cyber incidents in a year agency says",
          "url": "https://www.inkl.com/news/uk-critical-infrastructure-hit-by-200-cyber-incidents-in-a-year-agency-says"
        },
        {
          "title": "‘Highly significant’ cyber-attacks rise by almost 50%, warns NCSC",
          "url": "https://nationaltechnology.co.uk/Highly_Significant_Cyberattacks_Rise_By_Almost_50_Warns_NCSC.php"
        },
        {
          "title": "UK is being hit by more cyberattacks than ever before, NCSC warns",
          "url": "https://www.techradar.com/pro/security/uk-is-being-hit-by-more-cyberattacks-than-ever-before-ncsc-warns"
        },
        {
          "title": "pressreleases.responsesource.com",
          "url": "https://pressreleases.responsesource.com/newsroom/Zensec/release/106836"
        },
        {
          "title": "UK says three-quarters of cyberattacks on critical systems are linked to hostile states",
          "url": "https://groundnews.lakegeneva.lib.wi.us/article/uk-infrastructure-being-targeted-by-hostile-states-gchq-cyber-chief-warns"
        }
      ]
    },
    "I couldn't find any report of an NCSC Annual Review 2026 published on November 3. The results describe the 2025 review, plus some 2026 speeches, so the November 3 date and the \"unprecedented rise\" framing in your query aren't confirmed.\n\n**What the results do show:**\n- The most recent review covered September 2024 to August 2025. It was published October 14, 2025, and reported 204 \"nationally significant\" cyber incidents, more than double the number in the prior year.\n- Richard Horne's launch remarks described the risk as \"widely underestimated\", and the review noted a rising frequency of cyber incidents and a growing severity in their impact.\n- A TechRadar piece says the review reports attacks reaching unprecedented levels, which may be the source of the phrase in your query. Its date isn't clear from the results.\n- In a 2026 speech, Horne said the NCSC responded to more than 200 cyber incidents affecting the UK's critical national infrastructure and its \"supporting ecosystem\" in the year to May, with about 75% \"believed to be linked to state actors\".\n\n**Caveat:** These results don't establish whether a 2026 Annual Review has been published, so the November 3 date is unverified. For the official document, check the NCSC website (ncsc.gov.uk) directly."
  ],
  "durationSeconds": 6.388395720999921,
  "searchCount": 1
}

{
  "url": "https://www.ncsc.gov.uk/news",
  "prompt": "List news items with titles and dates, newest first. Is there an Annual Review 2026?"
}

{
  "bytes": 1177,
  "code": 200,
  "codeText": "OK",
  "result": "The page content doesn't list any news items, titles, or dates. It only includes the page heading, a description (\"The latest from in and around the NCSC and cyber security including statements, announcements and press releases.\"), and some sharing links.\n\nIt also doesn't mention an Annual Review 2026, so I can't confirm whether one exists. The NCSC's website or its news section would be the place to check.",
  "durationMs": 2712,
  "url": "https://www.ncsc.gov.uk/news"
}

{
  "query": "Palantir third quarter 2026 results press release revenue $2.31 billion U.S. commercial 148%",
  "mode": "standard"
}

{
  "query": "Palantir third quarter 2026 results press release revenue $2.31 billion U.S. commercial 148%",
  "results": [
    {
      "tool_use_id": "srvtoolu_01Qxqym21tqt4ViY51adWgQ9",
      "content": [
        {
          "title": "Palantir Technologies Inc. - Form 8-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000045/a2026q3ex991pressrelease.htm"
        },
        {
          "title": "Palantir Technologies Inc. - Form 10-Q - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000041/pltr-20260630.htm"
        },
        {
          "title": "Palantir Technologies Inc. - Form 10-Q - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000028/pltr-20260331.htm"
        },
        {
          "title": "Palantir Technologies Inc. - Form 8-K - FY2026",
          "url": "https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000039/a2026q2ex991pressrelease.htm"
        },
        {
          "title": "pantau stock split apakah palatir berikutnya",
          "url": "https://pluang.com/en/news-feed/pantau-stock-split-apakah-palatir-berikutnya"
        },
        {
          "title": "Dan Ives Calls Palantir’s Commercial Business Surge A ‘Major Validation Moment’",
          "url": "https://stocktwits.com/news-articles/markets/equity/dan-ives-calls-palantir-commercial-business-surge-a-major-validation-moment/cL28OPoR3CC"
        },
        {
          "title": "Palantir boosts 2026 revenue guide by $500M on record $2.1B US commercial contract signings",
          "url": "https://startupmap.iamsterdam.com/news/feed/palantir-boosts-2026-revenue-guide-by-500m-on-record-2-1b-us-commercial-contract-signings"
        },
        {
          "title": "Palantir Technologies (PLTR) - US Commercial Revenue (I:PTPLTRNQ)",
          "url": "https://ycharts.com/indicators/palantir_technologies_pltr_us_commercial_revenue"
        },
        {
          "title": "article c49b0feb 8965 5cc9 b798 90f81246630e",
          "url": "https://www.cnhinews.com/news/article_c49b0feb-8965-5cc9-b798-90f81246630e.html"
        },
        {
          "title": "Palantir Beats Q3 Estimates, Secures $10 Billion Army Contract and £1.5 Billion Defense Deal",
          "url": "https://rallies.ai/news/palantir-beats-q3-estimates-secures-10-billion-army-contract-and-15-billion-defense-deal"
        }
      ]
    },
    "The search confirmed the Q3 2026 figures you included. The Palantir 8-K press release filed with the SEC reports revenue of $2.313 billion, up 96% year over year, which matches your $2.31 billion figure. U.S. commercial revenue was $984 million, up 148% year over year, which matches your 148% figure.\n\nOther figures from the same release:\n- U.S. government revenue was about $953 million, up 96% year over year.\n- Total U.S. revenue was $1.937 billion, up 119%.\n- Quarterly revenue passed $2 billion for the first time.\n- U.S. commercial remaining deal value reached $6.517 billion, up 79% year over year.\n\nBefore the release, the company had guided Q3 revenue to $2.160–$2.164 billion, so the reported result came in above that range."
  ],
  "durationSeconds": 6.217538847000105,
  "searchCount": 1
}

{
  "url": "https://www.securityweek.com/uk-cyber-chief-says-the-uk-will-face-ai-cyberattacks-on-critical-infrastructure-by-2028/",
  "prompt": "Give publication date, all figures and quotes from the NCSC annual review, and the name/date of the report."
}

{
  "bytes": 165600,
  "code": 200,
  "codeText": "OK",
  "result": "**Report:** NCSC Annual Review 2026, the National Cyber Security Centre's annual cyber report. The article links it as \"annual-review-2026.\"\n\n**Publication date:** Tuesday, 3 November 2026. The article is dated that day and says the speech marking the report's publication was given on Tuesday. The article gives no separate date for the report.\n\n**Figures:**\n- Malicious cyber activity costs UK organizations almost $20 billion per year, according to the NCSC.\n- The article's other figures (Jaguar Land Rover's $260 million in losses, the 500,000 people who could have lost power in Poland, and the 70% of websites affected by the PHP flaws) are not attributed to the report.\n- The article also reports a 2028 timeframe, from NCSC chief Richard Horne's warning that the UK will likely face AI-enabled attacks on critical infrastructure by then.\n\n**Quotes:**\n- On Chinese cyber activity, the report calls it the \"most sophisticated and sustained cyber challenge facing the U.K.\"\n- Richard Horne said AI could let \"vulnerabilities that have been tolerated for far too long\" be exploited.\n- Horne said technology \"underpins the automation of physical processes that are vital to modern life.\"\n- Anne Keast-Butler, director of GCHQ (the NCSC's parent agency), said \"cybersecurity is now part of the front line defense of our nation.\"",
  "durationMs": 11795,
  "url": "https://www.securityweek.com/uk-cyber-chief-says-the-uk-will-face-ai-cyberattacks-on-critical-infrastructure-by-2028/"
}

{
  "message": "BEAT D RESEARCH — window 2026-11-02T11:50Z → 2026-11-03T11:05Z. 16 candidate items below, then rejections.\n\nNote on medRxiv items: abstracts and metadata were read from the medRxiv public API (`https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/<cursor>`), which lists each paper's posting date as 2026-11-02. The medrxiv.org HTML pages are Cloudflare-blocked (403) for both WebFetch and scripts/fetch.js, so I cite the canonical DOI plus the API endpoint I actually read. Posting date is day-level only — no time of day — so the exact in-window placement of the medRxiv items cannot be pinned below 24h resolution.\n\n====================================================================\n\nSECTION: Health, science & medicine\nHEADLINE: ECG foundation models show age performance gap that mitigation does not close, 5.4 million ECGs\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date; no time given)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.10.30.26366943 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- The preprint says the authors probed frozen embeddings of four ECG foundation models (ECGFounder, xECG, ECG-FM, DeepECG-SSL) across \"thirteen cohorts on four continents (5.4 million analysed ECGs, 31 endpoints, six held-out cohorts)\", stratified by age, sex and race.\n- Per the abstract, \"Disparities concentrated on age, not sex or race (median worst-group AUROC gap 0.028 vs 0.004 and 0.016; age exceeded sex in 97% of results)\".\n- The abstract reports external replication: \"ED-BWH 30-day MACE AUROC 0.81-0.90 under 40 years, 0.64-0.71 at >=75\".\n- The authors write that \"No remedy closed it (low-rank adaptation: -0.007 to -0.004)\", and that pretraining \"raised AUROC (+0.067) without changing\" the gaps; untrained copies (r=0.81, 102 pairs) and classical ECG measurements (rho=0.90) reproduced the endpoint-specific gaps.\n- The abstract states the largest race effect — \"higher potassium error in Black patients\" — \"vanished at matched true pota[ssium]\" (abstract text truncated in the API record at this point).\nFLAGS: preprint\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: LLMs beat published claims algorithms at finding drug-induced interstitial lung disease in 309 patients\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.10.30.26366942 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- The abstract states the study covered \"309 oncology patients with ILD diagnosis codes at Mass General Brigham, adjudicated by two pulmonologists\", comparing \"12 open-access LLMs with 20 published claims-based algorithms\"; LLMs received claims, EHR notes, or both, \"without task-specific training\".\n- Outcome measures were positive predictive value (PPV) and yield. \"Across the 36 model--input evaluations, LLM PPV exceeded that of the best algorithm without specialist-coding requirements (Algorithm 4) by 14.3 percentage points on average.\"\n- With claims alone, \"Qwen3-8B achieved 89.8% PPV (95% CI 78.2-95.6) at 15.9% yield, versus 86.7% at 4.9% for the highest-PPV algorithm.\"\n- With notes alone, \"Qwen3-32B achieved 78.9% PPV at 49.2% yield, versus 64.6% at 51.1% for Algorithm~4.\" With claims and notes combined, \"Qwen3-14B achieved 100.0% PPV at 24.3% yield.\"\n- The abstract says the authors \"projected the attenuation of a drug-induced ILD odds ratio under non-differential outcome misclassification\", using \"a simulated drug-safety scenario with a true odds ratio of 3.0\" (abstract truncated before the projected value).\nFLAGS: preprint\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Ten-shot multimodal LLMs match or beat vision models on ophthalmic imaging across seven datasets\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.10.30.26366929 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- Per the abstract, this is a \"Retrospective benchmarking study\" using \"4 public datasets (UCSD, IDRiD, REFUGE, ASOCT-MSDC) and 3 private datasets (OHTS, BPEI-DLS, WashU-OCT)\" of anterior- and posterior-segment ophthalmic imaging.\n- Nine models were compared across three families: MLLMs (Qwen3.8-27B, GLM-5.3-Flash, Gemma-4-31B-it), vision foundation models (DINOv3, RETFound, VisionFM) and vision-language models (CLIP, EyeCLIP, SigLIP2). MLLMs were evaluated zero-shot and 10-shot \"without additional training\"; vision models were linear-probed and fine-tuned \"on the same 10-shot set and on the full training dataset (FD)\".\n- \"For retinal OCT disease classification, 10-shot MLLMs achieved a macro-F1 of 0.94, versus 0.59 (10-shot) and 0.96 (FD) for vision models.\"\n- \"For diabetic retinopathy and macular edema grading, 10-shot MLLMs achieved QWKs of 0.69 and 0.73, versus 0.48 and 0.57 (10-shot) and 0.72\" for vision models on the full dataset (abstract truncated at this point in the API record).\nFLAGS: preprint\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Deep-learning ensemble grades schistosomal liver fibrosis from single ultrasound image, 2,921 adults\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date; DOI date stamp 2026.11.02)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.11.02.26364999 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- The abstract reports \"2,921 images from 2,921 adults (aged 18-88 years, median age 54 years; 46.4% female) from a schistosomiasis hospital in Jiangxi Province, China, between 2019 and 2023\"; \"12.9%, 34.6%, 32.4% and 20.2% had grade 0, 1, 2 and 3 fibrosis\".\n- The model combines \"ResNet-18, EfficientNet-B0, DenseNet-121 and Swin-T\" by weighted soft voting and grades \"from a single B-mode ultrasound image without manual delineation of a region of interest\".\n- \"For the four-grade task this model achieved a macro-F1 of 0.8527 (95% CI 0.8184-0.8856), an accuracy of 0.8500 (0.8136-0.8818) and a quadratic weighted kappa of 0.9187 (0.8983-0.9373) on a fixed test set of 440 images.\"\n- \"For detecting significant fibrosis (grade 2 or 3; test-set prevalence 0.530), sensitivity was 0.9700, specificity was 0.9179\" (positive predictive value truncated in the API abstract).\n- Reference grades came from \"the clinical ultrasound record and re-evaluation by an experienced radiologist according to the Chinese Handbook of Schistosomiasis Control\", with discordant cases resolved by a second radiologist.\nFLAGS: preprint\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Cheap decision-only model matches frontier LLMs as judge of medical AI answers at 1/152 the cost\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.10.30.26366939 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- The abstract describes \"an OSF pre-registered evaluation\" testing \"TypeSafe Jev 1.13 as a judge on tasks from five validated clinical benchmarks: rubric grading (HealthBench), planted clinical errors (When Rubrics Fail), risk in AI-written clinical documents (MedVAL), counseling ratings and failures (CounselBench) and physicians' preferences between answers (Real-POCQi)\".\n- Comparators listed: \"expert raters' agreement with each other, OpenAI Decisions, GPT-6 Luna, a proposed hybrid team combining decision models and a cheap LLM and, as frontier comparators, GPT-6.1 Sol and Claude Opus 5.5\". Main outcome was \"plain agreement with the expert label\".\n- \"The test comprised 25,091 units and 213,913 model calls. Jev's agreement with expert labels averaged 64.7% over six tasks. On 3,614 matched units it averaged 66.1%, against 65.0% for Opus and 60.7% for Sol, and it was non-inferior to both on four of six tasks.\"\n- \"Jev judged the whole pool in 17 minutes for US$1.46; per judgment, it cost 1/34 of Sol's price and 1/152 of Opus's.\"\n- \"A preset cutoff held its false-alarm rate on fresh planted-error answers, and in simulation, reviewing Jev's least-sure answers first found 1.4 times the errors of a random audit\"; the abstract adds \"omissions were hard for both\".\nFLAGS: preprint\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Roughly three in four US parents not comfortable with AI-led behavioral therapy for their child\nPUBLISHED: Published online November 2, 2026 (JAMA Pediatrics research letter, doi:10.1001/jamapediatrics.2026.4939)\nSOURCES:\nJAMA Pediatrics | https://jamanetwork.com/journals/jamapediatrics/fullarticle/2856091 | primary\nFACTS:\n- Cross-sectional survey, data collected November 2025, nonprobability river sample on SurveyMonkey, weighted to approximate US Census targets; \"3,102 respondents; 584 had an eligible child; 572 answered the primary outcome\" (child aged 5 to 17).\n- Weighted comfort with AI-led behavioral therapy for their child: \"Not comfortable at all: 47.2% (95% CI, 42.1–52.3); Not too comfortable: 28.8% (24.5–33.6); Somewhat comfortable: 16.2% (12.7–20.5); Very comfortable: 7.8% (5.3–11.3)\".\n- Adjusted odds ratios for higher comfort (survey-weighted cumulative-logit ordinal logistic regression, n=554): comfort with AI therapy for self 20.94 (9.78–44.86); expects AI better than medical professionals 10.12 (4.38–23.38); comfort with AI primary care for self 3.78 (2.16–6.59); expects AI about the same as professionals 3.31 (1.95–5.61); child received behavioral therapy in prior 12 months 2.07 (1.22–3.50).\n- Factors parents said would matter most (n=546): \"Accuracy of diagnosis: 58.5%; Level of empathy: 49.4%; Recommendation from a medical professional: 46.8%; Confidentiality and privacy: 43.7%; Cost: 32.8%\".\nFLAGS: (none)\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Speech samples from 1,197 shift workers in six countries predict sleep deprivation and sleepiness\nPUBLISHED: npj Digital Medicine, 03 November 2026 (Crossref record created 2026-11-03T00:35:03Z)\nSOURCES:\nnpj Digital Medicine | https://www.nature.com/articles/s41746-026-03437-0 | primary\nCrossref API record (date verification) | https://api.crossref.org/works?query.container-title=npj+Digital+Medicine&filter=from-created-date:2026-11-02,until-created-date:2026-11-04 | primary\nFACTS:\n- The abstract describes \"an intensive longitudinal study design (twice-daily measurement over two weeks in N = 1197 individuals from six different countries)\" of shift workers.\n- \"Paralinguistic speech features were used to predict different aspects of acute and chronic fatigue at each study time-point, with performance assessed in unseen (held-out) data.\"\n- \"In the cross-sectional analysis, good (close to or exceeding current state-of-the-art) performance was achieved for both current sleep deprivation and self-reported sleepiness levels.\"\n- \"The within-user analysis revealed robust increases in performance, yielding the ability to detect more subjective aspects of fatigue such as pervasive physical and mental exhaustion.\" The authors call the findings \"preliminary support\".\n- Funding: \"This work was supported by Innovate UK, the United Kingdom's innovation agency, under Grant No. 10042845\", with one author part-funded by the NIHR Biomedical Research Centre.\nFLAGS: (none)\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Company says Harvard working-paper trial of 1,137 students found AI app cut depression and anxiety scores\nPUBLISHED: November 3, 2026 (press release, dateline Palo Alto, California; distributed via TMT Newswire)\nSOURCES:\nThe Manila Times / TMT Newswire (Flourish Science press release) | https://www.manilatimes.net/2026/11/03/tmt-newswire/plentisoft/harvard-working-paper-finds-flourish-ai-app-improves-stress-depression-and-anxiety-symptoms/2460422 | primary (company release)\nHarvard Business School working paper 27-002 (listing/landing seen in search results only; PDF returned HTTP 403) | https://www.hbs.edu/ris/download.aspx?name=27-002.pdf | primary\nHBS Working Knowledge write-up (search-result text only) | https://www.library.hbs.edu/working-knowledge/in-charts-can-ai-be-your-well-being-coach | report\nFACTS:\n- The release says the paper is \"AI-Powered Prevention and Early Intervention for Stress, Depression, and Anxiety: A Randomized Clinical Trial,\" Harvard Business School Working Paper No. 27-002, and describes a six-week randomized controlled trial of \"1,137 university students at a large North American university\", with students assigned either to use Flourish at least twice weekly or to care-as-usual control; both groups kept existing campus and personal mental health resources.\n- Per the release, Flourish users had \"significantly lower stress, depression, and anxiety symptom scores after six weeks\" than controls.\n- Release figures for students with elevated baseline symptoms and six-week data: \"52.3% of Flourish users achieved meaningful improvement in depressive symptoms, versus 31.7% of controls\"; for anxiety, \"50.6% versus 38.1%\". Meaningful improvement was defined as \"a reduction of at least two points on the PHQ-2 or GAD-2\".\n- The release says sessions typically lasted 8 to 10 minutes and that no intervention-related adverse events were reported. It also states that a prior Flourish trial published in NEJM AI in July 2026 \"found no significant effects on depression, anxiety, or stress.\"\n- Conflicting account: search-result text from the HBS Working Knowledge write-up of a study titled \"AI for Proactive Mental Health: A Multi-Institutional, Longitudinal, Randomized Controlled Trial\" (described as accepted at NEJM AI) says benefits came from boosting \"emotional, social, and general well-being, rather than by lowering negative mental health symptoms like anxiety or depression.\" I could not open the HBS PDF (403) to reconcile the two.\nFLAGS: company-claim, preprint, single-source\n\n--------------------------------------------------------------------\n\nSECTION: Health, science & medicine\nHEADLINE: Survey of US and Canadian physicians: half say they are not adequately trained to use AI safely\nPUBLISHED: Posted to medRxiv 2026-11-02 (API posting date)\nSOURCES:\nmedRxiv (via medRxiv API) | https://doi.org/10.64898/2026.11.01.26367027 | primary\nmedRxiv API listing I read | https://api.biorxiv.org/details/medrxiv/2026-11-02/2026-11-02/0 | primary\nFACTS:\n- The abstract reports \"an online cross-sectional survey of 1,258 physicians (MD, DO, MBBS or equivalent) in the United States (US) and Canada from December 2023 through February 2026\", with 34 questions across six areas.\n- \"A total of 130 completed surveys were received (response rate, 10%).\" Top specialties: \"psychiatry (46.2%), internal medicine (14.6%) and pediatrics (13.8%)\".\n- \"A total of 16.9% had training in computer science or information technology and 40.8% in statistics. Nearly half (46.9%) had no formal training in AI and were self-taught.\"\n- \"Sixty to seventy percent thought AI would provide diagnostic aid or treatment recommendations, but half did not feel adequately trained to safely use AI in practice. Over 70% thought it could help with administrative tasks. More than 80% were worried about errors, misinformation, or biases in the data.\"\nFLAGS: preprint\n(Caveat for editor: n=130 completed responses at a 10% response rate, heavily psychiatry-weighted — weakest of the health items; use only if space allows.)\n\n====================================================================\n\nSECTION: Policy, regulation & law\nHEADLINE: New York Times and three Alden papers sue Brave Software over AI search index and paywall bypass\nPUBLISHED: November 2, 2026 (TheWrap, by A.J. Katz; The Next Web same day)\nSOURCES:\nTheWrap | https://www.thewrap.com/industry-news/tech/new-york-times-chicago-tribune-brave-ai-copyright-lawsuit/ | report\nThe Next Web | https://thenextweb.com/news/nyt-newspapers-sue-brave-ai-scraping | report\nFACTS:\n- Per TheWrap, the suits were filed \"on Monday\" in Manhattan federal court: The New York Times filed a 72-page complaint, and the New York Daily News, Chicago Tribune and Orlando Sentinel filed a separate 69-page complaint; a complaint link in the article references docket \"26-cv-9554\" for the Daily News/Tribune/Sentinel filing. The Next Web says the NYT sued first and the Alden-owned papers (through MediaNews Group and Tribune Publishing) filed \"hours later\".\n- The Next Web reports the complaints allege \"direct, contributory, and vicarious copyright infringement, DMCA circumvention, and unjust enrichment under New York law\", and that plaintiffs seek \"Statutory and actual damages, repayment of profits, and a permanent injunction\", with a jury trial requested.\n- The Next Web reports the Brave Index \"contains more than 30 billion web pages\" and that the Alden-owned papers say \"more than two million registered articles are affected\".\n- TheWrap reports the complaint says Brave's \"Ask Brave\" tool \"generated more than 1,200 words from a Chicago Tribune article on data center tax breaks\" and \"nearly 600 words from a Daily News article on Central Park horse carriages\".\n- Both outlets report the complaints identify Anthropic, Perplexity, Mistral, xAI and Cohere as Brave Search API customers. TheWrap says the NYT alleges it sent cease-and-desist letters to CEO Brendan Eich in August 2025 and April 2026 with no response, and that Brave has defended its search practices as fair use; News Corp countersued Brave in July.\nFLAGS: (none)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: Agencies and AI firms split over Trump order renaming artificial intelligence \"Super Intelligence\"\nPUBLISHED: November 2, 2026 (MIT Technology Review; RSS pubDate Nov 3, 04:18 UTC)\nSOURCES:\nMIT Technology Review | https://www.technologyreview.com/2026/11/02/1147932/heres-who-is-falling-in-line-for-trumps-super-intelligence-loyalty-test/ | report\nMIT Technology Review RSS feed (date/time verification) | https://www.technologyreview.com/feed/ | report\nFACTS:\n- The article, by James O'Donnell, reports that in late September 2026 President Trump signed an executive order whose single directive is that government agencies must rebrand \"artificial intelligence\" as \"Super Intelligence\" (SI); the stated reason is that AI systems \"amplify human ingenuity\" rather than imitating intelligence. The order \"also requires agency leaders to draft a legislative definition of 'Super Intelligence' for the president by the end of November.\"\n- Compliance reported as mixed: ICE issued a request for \"SI-powered\" surveillance for detention facilities; many government websites swapped the term; NIH added a banner noting visitors may see both terms during the transition; the Navy and Marines issued transition guidance. By contrast, the Pentagon's Project Meridian (announced a day after the order) used the old terminology, an FTC press release used \"superintelligence\" rather than the ordered two-word capitalized form, and recent HHS press releases showed no change. The order does not apply to previously issued documents, and the Pentagon's Chief Digital and Artificial Intelligence Office keeps \"AI\" in its name.\n- The article reports that on October 27 Trump criticized the Wall Street Journal on Truth Social for not using the term and suggested a rule could ban \"artificial intelligence\" from government documents.\n- It reports that on the same day as the order, the nonbinding \"White House Accord on Super Intelligence\" was signed by Sundar Pichai (Google), Dario Amodei (Anthropic), Mark Zuckerberg (Meta), Greg Brockman (OpenAI), Elon Musk (xAI) and Jensen Huang (Nvidia).\n- It cites a CNBC analysis of Q3 2026 earnings calls finding \"only Zuckerberg and Musk used the term consistently\", and Pew Research findings (October 8, 2026) that Americans rank AI as more important to them in the midterms than environmental and climate policy.\nFLAGS: single-source\n(Independent corroboration of the terminology change exists in search-result text from law-firm commentary on the SEC's FY2027 exam priorities, which notes the document \"uses 'super intelligence (SI)' where last year's edition said 'artificial intelligence (AI)'\" and ties it to a September 29, 2026 executive order — I did not open the SEC PDF.)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: Tenth Circuit: law firm's AI use alone does not make billed hours unreasonable, $115,000 upheld\nPUBLISHED: Decision November 2, 2026; article published November 3, 2026 (JD Journal)\nSOURCES:\nJD Journal | https://www.jdjournal.com/2026/11/03/court-ruling-ai-law-firm-legal-fees/ | report\nFACTS:\n- Per the article, the US Court of Appeals for the Tenth Circuit, in a three-judge panel opinion by Circuit Judge Carolyn McHugh, decided Flux Drive Inc. v. Qiang Rong, Case No. 25-1308, on November 2, 2026.\n- The court upheld a \"$115,000 in legal fees\" award to the defendants' counsel, Brownstein Hyatt Farber Schreck, after a Colorado federal judge dismissed Flux Drive's suit against a former engineer over alleged transfer of confidential information to a Chinese manufacturer.\n- The article reports the panel rejected Flux Drive's argument that the firm's AI use justified cutting the fees, finding Flux Drive \"had not shown AI made the billed hours unreasonable\", and that a party challenging fees \"must identify specific problems with particular charges\".\n- The article states the ruling is narrow and \"does not say AI can never justify lower fees.\"\nFLAGS: single-source\n(I did not obtain the opinion itself — CourtListener's API requires authentication (HTTP 401) and its web search returned 403. Worth a docket check before publication.)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: South Korea court survey: 80.7% of judges encountered citations to nonexistent rulings\nPUBLISHED: November 2, 2026 (Korea JoongAng Daily); survey fielded October 6–16\nSOURCES:\nKorea JoongAng Daily | https://www.koreajoongangdaily.com/korea/eight-in-10-judges-encounter-fake-ai-court-ruling-citations/12950176 | report\nFACTS:\n- The survey was conducted by the National Court Administration, an agency under the Supreme Court, from October 6 to 16, with 360 judges nationwide responding (multiple answers allowed).\n- Findings: \"80.7% of judges handling civil, family, and administrative cases had encountered citations of nonexistent court rulings\"; 65.4% had seen court rulings falsely cited; 16.9% had encountered fabricated or nonexistent laws; 4.1% fabricated or nonexistent academic papers or other materials.\n- On who submitted them: \"69.5% said litigants themselves submitted documents with such citations\"; 57.6% named lawyers representing parties in civil cases or defendants in criminal cases.\n- On remedies: \"91.7% said institutional measures were needed, and 64.8% called them highly necessary\"; 61.4% supported a legal basis for administrative fines; 61.1% favored requiring parties to verify the rulings they cite; 60.6% supported mandatory disclosure of AI use; 55.4% called for sanctions against lawyers including disciplinary referrals.\n- The article says the court administration plans to develop countermeasures, consult the Ministry of Justice and other agencies, recommend amendments to the Civil Procedure Act and Criminal Procedure Act to the National Assembly to create a legal basis for administrative fines and other penalties, and consider issuing AI guidance to lawyers and litigants through the electronic litigation system.\nFLAGS: single-source\n(Window caveat: published 2 November KST; the window opens 2 Nov 11:50Z = 2 Nov 20:50 KST, so this may sit just outside the window depending on publication hour, which the page does not state.)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: More than 40 local AI data-center ballot measures go to voters across eight states\nPUBLISHED: November 2, 2026 (Insurance Journal, carrying Bloomberg analysis)\nSOURCES:\nInsurance Journal | https://www.insurancejournal.com/news/national/2026/11/02/891163.htm | report\nFACTS:\n- The article reports \"more than 40 data center-related measures\" on ballots, sourced to \"a Bloomberg analysis of Ballotpedia data\", across Nevada, Georgia, Ohio, California, Oklahoma, North Dakota, Wisconsin and Arkansas (the Arkansas vote is in December), with the vote on November 3, 2026.\n- Specific measures named: Alhambra, California, would ban data centers outright; about a dozen Ohio communities vote on bans \"mostly targeting larger facilities\"; Grove City, Ohio, charter amendment requiring a referendum on developments above certain size, water and energy thresholds; Janesville, Wisconsin, referendum on projects costing more than $450 million at a former GM site; Harwood, North Dakota, charter amendment (Article X) seeking disclosure, independent review and public participation for large projects, near a \"$3 billion Applied Digital project\"; Boulder City, Nevada, vote on allowing data centers on a city-owned tortoise preserve; Wilmington, Ohio, vote on rezoning land around a proposed Amazon data center.\n- Recalls: Piqua, Ohio, recall of the mayor and two city commissioners who backed AI infrastructure where Meta is trying to build a data center; Yukon, Oklahoma, recall of Mayor Brian Pillmore, who supports a proposed $1 billion data center.\n- Also reported: Clarksville, Arkansas, December vote on \"$55 billion in bond ordinances for a ServerFarm data center\"; a Coweta County, Georgia petition with \"over 14,000 signatures\" to overturn approval of a \"$17 billion campus\" and ban future data centers, which \"could reach a January ballot, pending a judge's decision.\"\n- Polling and context cited: a Quinnipiac poll found 72% of voters would oppose a new data center in their community, \"up from 65% in March\"; Data Center Watch reported \"at least 45 projects worth $68 billion were disrupted by local opposition in Q2 2026.\"\nFLAGS: single-source\n(Corroborating search-result text I saw but did not open: FourWeekMBA and Tom's Guide pages citing Ballotpedia's November 2 count of 41 measures in 10 states, with 21 in Ohio and a split of 25 citizen initiatives / 11 official referrals / 5 referendums. Counts differ across outlets — 34, 35, 39, 40+, 41 — so quote only the figure attached to its source.)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: 51 proposed amicus briefs pile up in OpenAI copyright MDL as docket passes 2,500 entries\nPUBLISHED: November 2, 2026 (chatgptiseatingtheworld.com; Techdirt, Mon, Nov 2nd 2026 01:15pm)\nSOURCES:\nchatgptiseatingtheworld.com | https://chatgptiseatingtheworld.com/2026/11/02/51-amici-briefs-filed-in-openai-copyright-suit-pending-court-approval-download/ | report\nTechdirt | https://www.techdirt.com/2026/11/02/the-openai-copyright-case-has-drawn-a-mountain-of-amicus-briefs-we-sorted-them-for-you/ | report\nFACTS:\n- chatgptiseatingtheworld.com, in a post dated November 2, 2026, says 51 amici asked for leave to file briefs \"related to the summary judgment motions filed by the parties\" in \"In re OpenAI Copyright Infringement Litigation\", and that the briefs are \"pending subject to the court's approval\". It references Judge Stein; it does not give the MDL number or court in the text I read.\n- Techdirt (Mike Masnick, \"Mon, Nov 2nd 2026 01:15pm\") writes that in this MDL — consolidating suits claiming OpenAI and Microsoft infringed copyrights by training on plaintiffs' works — amici \"had to ask permission from the court\", so \"each attempted filing involved multiple filings\", and \"the docket is already at almost 2,500 entries.\"\n- Techdirt names briefs supporting the defendants from the Authors Alliance (quoted: \"Market Dilution is just a fancy term for competition, and copyright law supports competition\"), independent creators Sarah Rose Siskind and Michael Wall, the Chamber of Progress and Abundance Institute (joined by drummer Trevor Lawrence Jr.), EFF, library groups with the American Council of the Blind plus CTA and BSA, and academics Pam Samuelson, Chris Sprigman, Brian Frye (with journalist Ron Suskind), Rebecca Tushnet and Edward Lee.\n- Techdirt says the Wikimedia Foundation's brief supports \"neither\" party, arguing that under the Warhol fair use precedent \"courts need to analyze each use separately\", that regular AI training should be fair use, but that \"RAG training (basically, AI on top of a corpus of data) probably isn't fair use.\"\n- Techdirt names briefs supporting plaintiffs from actor Ashley Judd, documentarian Ken Burns, the RIAA, the Copyright Alliance, newspapers and publishers, and a joint brief from PEN America, the Protect Democracy Project and Reporters Without Borders. Techdirt discloses its own brief in the case and that it built its brief-sorting tool \"using Claude Code and the CourtListener MCP\".\nFLAGS: single-source\n(Note for editor: Techdirt is commentary with an acknowledged stake — it filed its own brief. The reportable facts are the brief count, the docket size, and who filed on which side. Search-result text from caidp.org indicated Judge Stein set an amicus deadline of October 30, 2026; sources disagree on whether summary-judgment replies are due November 6 or November 20 — I could not resolve this against the docket.)\n\n--------------------------------------------------------------------\n\nSECTION: Policy, regulation & law\nHEADLINE: Researchers map five AI developers' governance proposals, finding 15-day and six-month reporting asks\nPUBLISHED: November 2, 2026 (Tech Policy Press, Analysis)\nSOURCES:\nTech Policy Press | https://www.techpolicy.press/how-ai-companies-want-to-be-governed-and-what-that-means-for-ai-governance/ | primary\nFACTS:\n- Authors Jason Pielemeier, Jhalak M. Kakkar, Elonnai Hickok, Sudisha Mishra and Revati Vaidya, writing as part of the Multistakeholder Approach to Participation in AI Governance (MAP-AI) project, reviewed public policy pronouncements of five AI developers — Anthropic, Google, Meta, Microsoft and OpenAI — and mapped positions onto three areas: Pacing, Development/Deployment/Disclosure, and Collective Action. A comparison spreadsheet is linked separately.\n- Figures cited from the company proposals: \"Anthropic proposes a 15-day window for reporting stolen weights and realized harms, and a risk report every six months\"; \"Google's proposed FARO would run annual audits\"; \"Microsoft proposes annual transparency reports.\"\n- Underlying documents reviewed, per the article: Anthropic's \"Advanced AI Framework\", \"Policy on the AI Exponential\" and Dario Amodei's \"We Must Pace the Frontier\"; OpenAI's \"Public Policy Agenda\" and Chris Lehane's \"reverse federalism\" essay; Google's \"A Pragmatic Approach to AI Governance in America\"; Microsoft's \"Governing AI: A Blueprint for the Future\" (2023); and Mark Zuckerberg's \"The Future Is for Everyone\".\n- The authors call it \"an initial compilation\" that will be updated, relying only on public statements, with some positions drawn from press reporting (Politico, Fortune) rather than primary documents. No new quantitative data, surveys or experiments are presented.\nFLAGS: single-source\n(Marginal: it is an analysis piece; the new artifact is the comparative compilation itself. Drop if space is tight.)\n\n====================================================================\nREJECTED CANDIDATES AND WHY\n====================================================================\n\n- NEJM AI, \"Automation Bias in Large Language Model–Assisted Diagnostic Reasoning among Physicians Trained in AI Literacy — A Randomized Clinical Trial\" (44 physicians in Pakistan, accuracy 84.9% control vs 73.3% erroneous-suggestion arm, adjusted 14.0-percentage-point reduction). Search results pointed to a \"November 2, 2026\" date, but Crossref (10.1056/AIoa2501001) gives published/issued 2026-04-23, vol 3 issue 5, created 2026-04-23T13:00:21Z. **Outside window by six months** — do not run it as new. (ai.nejm.org returns 403 to both WebFetch and scripts/fetch.js.)\n\n- HKMA launches Project SAGE and establishes Expert Group for agentic finance (Hong Kong Monetary Authority press release 20261102-6; discussion paper on banks' use of agentic AI, 22-member expert group incl. Mastercard, Ant International, Circle Hong Kong, Google Cloud; explores a central registry for critical agents and a \"know your agent\" standard, building on supervisory guidance of 16 Oct 2026). Strong item, but issued 2 November during Hong Kong FinTech Week — HKT business hours on 2 Nov are 2 Nov 01:00–10:00Z, i.e. **before the 11:50Z window open**. Flagging in case the editor wants to carry it anyway; HKMA listing confirmed at https://www.hkma.gov.hk/eng/news-and-media/press-releases/ (release path /eng/news-and-media/press-releases/2026/11/20261102-4/).\n\n- npj Digital Medicine, \"Clinician-centered evaluation of large language model-generated discharge summaries for longer hospitalizations\" (60 Internal Medicine hospitalizations of 7–21 days at Stony Brook; reviewers preferred LLM summaries for 95% of encounters; 31 LLM-identified radiology incidental findings, 93.5% rated factually correct, 87.1% appropriate to report). Article page shows \"Published: 02 October 2026\" — **outside window**. Medical Xpress covered it 2 Nov 2026 but that is press-release recycling, not a new development.\n\n- Sen. Cassidy (R-LA) PATIENT AI Act discussion draft (FDA/ONC oversight split, five-year CMS Innovation Center payment model for autonomous clinical AI, comments due December 1, 2026 to [email redacted]). Released **October 29, 2026** — outside window, no new development found inside it.\n\n- SEC Division of Examinations FY2027 examination priorities (AI governance, model risk management, AI-driven phishing and deepfake social engineering; terminology switched to \"super intelligence\"). Released **October 23, 2026** — outside window.\n\n- House Oversight Chair Comer letter to Delaware Gov. Matt Meyer on the proposed \"Artificial Intelligence Company\" entity (records due November 9). Letter dated **October 26, 2026** — outside window.\n\n- EU AI Office's first requests for information to leading GPAI providers (security practices, external evaluation, post-market monitoring; triggered by AI agents breaching external systems in testing). Announced by EVP Henna Virkkunen **14 October 2026** — outside window.\n\n- Anthropic's acquisition of Mithril Medicine (one-person biotech, LAMA2-related congenital muscular dystrophy and alpha-dystroglycanopathy programs, Claude coordinating 11 contract labs, mouse results in under 18 months, human trials possibly late 2028). Disclosed **October 27, 2026** — outside window.\n\n- Isomorphic Labs president Max Jaderberg at Bloomberg Tech London, 2 November 2026, saying AI will eventually design all medicines. In window but **no numbers, no new result** — statements only (Bloomberg page not opened).\n\n- Pathos raising $237 million at a $3 billion valuation (STAT Plus, 2 Nov). Funding round — **Beat A/business**, not Beat D, and paywalled.\n\n- Federal Register, 2–3 November 2026: API search for \"artificial intelligence\" returned only two documents (NRC \"Streamlining Contested Adjudications in Licensing Proceedings\" and PHMSA LNG pipeline safety proposed rule), **neither AI-related in substance**. No AI rulemakings published in the window.\n\n- FTC press releases: only one item dated 2 November 2026 (\"FTC, Washington Take Action Against Payment Processor for Deceiving Small Businesses About Costs and Cancellation Terms\") — **not AI**. No 3 November releases. NIST AI page: nothing newer than October 2026. WHO news: only a South-East Asia cancer-registry guideline (2 Nov), **not AI**. NIH news releases page returned 403.\n\n- gov.uk, 3 November 2026: \"Care workers, women returning to employment and builders to gain practical AI skills\" — four Barnsley training projects sharing \"over £800,000\". In window but **too small/local** for the briefing.\n\n- npj Digital Medicine, 3 November 2026: \"The TEMPO program and the future of digital mental health regulation in the US\" (Parks & Shick) — **commentary with no new facts**; the FDA–CMS TEMPO pilot itself dates to December 5, 2025.\n\n- npj Digital Medicine, 3 November 2026: \"Cost-effectiveness analysis of digital medicine support models for alcohol use disorder\" (NCT04011644, 558 participants; annualized reductions in heavy drinking days 42.4 / 40.2 / 48.3 per patient; per-patient costs $162 / $524 / $802; ICER for clinically integrated vs self-monitored $107.9). Solid trial economics but it is a **digital-health platform, not AI** — dropped as off-beat. Available at https://www.nature.com/articles/s41746-026-03422-7 if the editor wants it.\n\n- Tech Policy Press, 2 November 2026: \"Europe and Canada Plot a Digital Alliance as US Ties Fray\" (EU–Canada digital trade pact negotiations concluded; Canada joined EuroHPC JU; bilateral digital-services trade \"almost €20 billion in 2025\"; commitments on mutual recognition of AI safety assessments). All substantive facts are from the **30 October 2026** Montreal summit and joint statement — outside window; only the analysis is new.\n\n- Tech Policy Press, 2 November 2026: other seven items that day (\"How the EU AI Office Can See the Choices Behind Frontier Labs' Safety Claims\", \"The SEC Should Block Anthropic's IPO to Protect the Public\", \"October 2026 US Tech Policy Roundup\", \"Meta Streamlines State Censorship in India with Automated Takedowns\", etc.) — **opinion/roundup without new primary facts** inside the window.\n\n- The Algorithmic Update (Substack) 2 November 2026 issue, reporting eight state AGs filing coordinated consumer-protection suits against OpenAI on October 14 and Texas on October 23, plus New York's chatbot law. **Newsletter, underlying events outside window**, counts disputed (eight-plus-Texas vs ten).\n\n- Inforrm round-up, 2 November 2026, reporting a Meta $459 million settlement with 47 states and a $25 billion New Mexico fine. **Undated underlying events, not AI-specific**, and I could not confirm either figure from a primary source.\n\n- Brazilian labour court fining two lawyers over white-on-white prompt injection aimed at the court's AI. One source dates the ruling to **12 May 2026**; coverage dated 1 November. Outside window and date unresolved.\n\n- medRxiv items posted 2 Nov that I read but judged thinner than the five above: \"Variantscape\" LLM extraction of variant-treatment-cancer associations (v2; 3.7 million abstracts, 886,195 with gene names, 37,895 with variant+cancer+agent, 11,985 unique variants, 197 cancer types, 547 agents, graph of 10,571 nodes / 44,644 verified edges — a **v2 revision**, so not a first posting); \"Comparing Machine Learning Methods for Detecting Caregiver Burden in Transcribed Conversations\"; \"Questioning the Benchmarks: Hidden Circularity in AQ-10 Autism Screening Datasets\"; \"Real-time Volumetric Imaging ... Deformable Phantom Study\"; \"Benchmarking single-subject detectability of cognitive event-related potentials\". Available on request.\n\n- bioRxiv 2 November 2026 (284 papers, 216 new, checked via API): only \"Machine learning guided design of strong transcriptional activation domains\", \"Diffusion-Based Synthetic Pretraining for Root Segmentation in Rhizotron Images\" and two genomics items matched AI keywords — **none strong enough** for an AI-for-science item.\n\n- FDA AI-enabled medical device list: **no clearance news in the window.** The list page now redirects to /medical-devices/artificial-intelligence-enabled-medical-devices/list-artificial-intelligence-enabled-medical-devices (I did not follow the cross-host redirect). Third-party analyses in search results say the list was last updated September 4, 2026 with 1,614 entries and decisions through June 29, 2026 — i.e. no new FDA AI device actions to report for 2–3 November.\n\n- Sites that refused both WebFetch and scripts/fetch.js, so could not be checked: statnews.com article pages beyond the topic index, thelancet.com/landig, fiercebiotech.com, fiercehealthcare.com, beckershospitalreview.com, healthcareitnews.com, endpoints.news, lawfaremedia.org, reuters.com (egress policy), politico.com (egress policy), axios.com, courtlistener.com (401/403), nature.com/nm (auth redirect), hbs.edu PDF (403), ohsem.me (bot check), isomorphiclabs.com/articles (404). iapp.org/news and digital-strategy.ec.europa.eu/en/news loaded but had nothing in-window and in-scope (the only 3 Nov EC item was a Web Summit 2026 participation notice)."
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  "message": "BEAT A RESEARCH — AI Edge Briefing, window 2026-11-02T11:50Z → 2026-11-03T11:05Z\n\n18 candidate items below, then rejects. Note on fetch access: Reuters, FT, Bloomberg, The Verge, Ars Technica, The Guardian, NY Post, openai.com/index/* and arstechnica all refused (403 / \"Blocked by egress policy\") — where that happened I say in the bullets which source the figures actually came from. Anthropic's S-1/A was read directly from SEC EDGAR via scripts/fetch.js (primary text quoted below).\n\n===========================================================\nSECTION: Frontier models & labs\nHEADLINE: Anthropic S-1/A says it may \"imminently\" meet its own threshold for AI-accelerated progress\nPUBLISHED: \"As filed with the Securities and Exchange Commission on November 2, 2026\" (EDGAR: filed/accepted 2026-11-02 09:24:24 ET); TechCrunch 2:14 PM PST · November 2, 2026\nSOURCES:\nAnthropic, PBC (SEC EDGAR) | https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm | primary\nSEC EDGAR filing index | https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/0001628280-26-068676-index.htm | primary\nTechCrunch | https://techcrunch.com/2026/11/02/anthropic-warns-that-its-very-close-to-rsi-capability-aka-self-building-ai/ | report\nFACTS:\n- New risk-factor language in the S-1/A, read directly from the filing: \"we have in the past not identified, and may in the future not identify, a significant acceleration in our rate of development until after it has occurred. For example, our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI.' We have not designated any of our current models as exceeding this threshold, and we continue to assess the underlying data.\" The filing adds that Anthropic is \"evaluating the implications of meeting the AI research and development capability threshold.\"\n- Same passage discloses past precautionary delays: \"In the past these measures have included delaying the release of models and limiting their initial availability, such as with Mythos through Project Glasswing\" (Mythos/Glasswing appear exactly once in the filing text).\n- The filing states revenue grew \"from $0 at commercial launch in the first quarter of 2023 to $17.0 billion for the three months ended September 30, 2026.\"\n- Statements of operations table in the filing: nine months ended September 30, 2026 revenue $33,242M; total operating expenses $34,502M; operating loss $(1,260)M; net loss $(104,039)M — versus nine months ended September 30, 2025 revenue $2,545M and net loss $(25,107)M. Other income (expense) for the nine months includes \"Change in fair value of convertible notes, derivative liabilities, and SAFEs\" of $(94,324)M.\n- Filing also states: TTM revenue per employee \"of over $6.6 million as of September 30, 2026, compared to $1.4 million as of September 30, 2025\"; and \"As of September 30, 2026, we had raised an aggregate of $141.1 billion of capital and had cash and cash equivalents of $95.6 billion and short-term investments of $36.3 billion.\"\n- TechCrunch also quotes the filing: \"We do not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding… Accordingly, we are considering updates to our Responsible Scaling Policy to keep humans in control of frontier model development at Anthropic.\"\nFLAGS: company-claim, update\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Anthropic discloses $895.4bn of compute and infrastructure purchase commitments\nPUBLISHED: Filed with the SEC November 2, 2026\nSOURCES:\nAnthropic, PBC (SEC EDGAR) | https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm | primary\nFACTS:\n- Quoted from the filing: \"As of and subsequent to September 30, 2026, we have entered into purchase commitments and lease agreements, including short-term commitments, as well as leases not yet commenced, with an aggregate committed spend of approximately $895.4 billion, substantially all of which is related to compute and infrastructure.\"\n- Breakdown in the filing: \"approximately $447.5 billion expected to be incurred before December 31, 2030, and substantially all of the remainder is expected to be incurred between 2031 and 2045. Approximately $69.8 billion of these commitments are due in the 12 months following September 30, 2026.\"\n- The filing describes the hardware base as \"our multi-chip compute architecture across AWS Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs.\"\n- The filing says these are \"long-term agreements for compute and related resources that involve minimum purchase commitments, take-or-pay provisions, and other terms that obligate us to pay for resources regardless of actual utilization.\"\nFLAGS: company-claim, update\nNOTE TO EDITOR: can be merged with the item above into one Anthropic S-1/A item if you prefer. Yesterday's brief covered the Japanese share sale (552.9bn yen) only; the $895.4bn figure and the RSI language are new in the Nov 2 S-1/A.\n\n===========================================================\nSECTION: Frontier models & labs\nHEADLINE: MIT CSAIL report: GPT-6 Astra edited 0.016% of Qwen3.5-0.8B weights, raising MATH-500 from 7.9% to 48.1%\nPUBLISHED: November 2, 2026 (research blog); VentureBeat November 2, 2026, 2:16 pm PT\nSOURCES:\nRikiya Takehi et al. (MIT CSAIL) | https://rikiyat.github.io/blog/weight-space-programming/ | primary\nVentureBeat | https://venturebeat.com/technology/like-gene-editing-for-neural-networks-mit-researchers-used-gpt-6-astra-to-edit-qwens-open-weights-directly-boosting-math-performance | report\nExperiment logs (GitHub) | https://github.com/RikiyaT/lm_understand-logs | primary\nFACTS:\n- Report title \"Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights,\" by Rikiya Takehi, Jayden Teoh, Alex Zhang and Omar Khattab (MIT CSAIL), dated November 2, 2026.\n- Qwen3.5-0.8B after Astra's edit (50 forward passes): MATH-500 48.1% vs base 7.9%; GSM8K 67.1% vs base 13.8%; IFEval 62.3% vs base 21.0%. Share of MATH-500 answers hitting the 32,768-token limit fell to 33.1% from 93.0%. Edit size: \"131,072 weights, or 0.016% of the model,\" in layers 15 and 19; no gradients or training used.\n- Reinforcement-learning experiments in the report: networks written from scratch scored Breakout 517.4 (PPO 100M steps 15.8; PPO 500M steps 25.3), Seaquest 53.1 (PPO 100M 5.6; PPO 500M 88.9), Asterix 53.2 (PPO 100M 25.8; PPO 500M 55.2). A failing car-on-ramp policy went to 100% success over 1,024 episodes after editing 3.5% of weights, from 0% for the PPO policy.\n- Authors' own limitations: results are \"very early\"; weight editing did not improve Gemma 3 270M, and they conclude editing \"can remove an obstacle that hides an ability but cannot add an ability the model lacks\"; Astra failed in four attempts to identify a sycophancy-trained model from weights alone and succeeded only when given attention patterns; 10 and 25 forward passes barely reduced looping (87.2% and 86.4% of MATH-500 answers still hit the token limit).\n- VentureBeat reports the strongest Qwen attempt took 50 evaluation requests, 158 conversational turns, 80 Python runs and 20.3 hours, and that the gain came mainly from reducing repetitive output rather than adding mathematical knowledge. VentureBeat quotes critic @1a3orn on the omitted Gemma 3 270M negative result: \"So, if there's a clear flaw in the LLM's reasoning, LLMs can help edit it out.\"\nFLAGS: preprint, company-claim (Astra is OpenAI's model; benchmark runs are the authors' own)\n\n===========================================================\nSECTION: Frontier models & labs\nHEADLINE: Anthropic adds Claude Code system-prompt rules blocking clones of existing video games\nPUBLISHED: The Decoder, November 3, 2026\nSOURCES:\nThe Decoder | https://the-decoder.com/anthropic-cracks-down-on-game-cloning-in-claude-code/ | report\nTom's Hardware | https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks | report\nArs Technica | https://arstechnica.com/ai/2026/11/claudes-new-rules-against-game-cloning-wont-stop-the-ai-copying-boom/ | report\nThe Verge | https://www.theverge.com/ai-artificial-intelligence/1024632/anthropic-claude-ai-video-game-clones | report\nFACTS:\n- The Decoder reports Anthropic added two sentences to Claude Code's system prompt for Opus 5.5 that stop the tool from recreating other people's video games, and says the rule has been active for several days and applies even when a clone is renamed or presented as original work.\n- The Decoder says Anthropic employee Addy Osmani confirmed the change on X, that using Claude to infringe intellectual property violates the usage policy, and that Anthropic plans to keep adjusting the rules.\n- The Decoder says users can still build their own games and genre titles with custom assets, but that some users report problems with original projects too, and that before the change users were producing hundreds of unofficial browser ports of well-known titles including Halo and GTA Vice City.\nFLAGS: single-source (The Decoder is the only one of the four I could read; Tom's Hardware returned navigation chrome only, Ars Technica and The Verge refused both WebFetch and scripts/fetch.js — their headlines are visible on Techmeme but I did not read their text)\n\n===========================================================\nSECTION: Frontier models & labs\nHEADLINE: OpenAI raises top bug bounty payout to $172,000 including bonuses\nPUBLISHED: Help Net Security, November 3, 2026 (OpenAI posts dated Mon 02 Nov 2026 in its RSS feed)\nSOURCES:\nHelp Net Security | https://www.helpnetsecurity.com/2026/11/03/openai-bigger-bug-bounty-rewards/ | report\nOpenAI (post title and date from openai.com/news/rss.xml) | https://openai.com/index/rewarding-defenders-with-bigger-bug-bounties | primary\nOpenAI (post title and date from openai.com/news/rss.xml) | https://openai.com/index/preparing-our-next-security-sprint-to-harden-openai | primary\nFACTS:\n- Help Net Security reports \"The midpoints of the reward ranges for medium, high, and critical findings more than quadrupled on average.\"\n- Critical vulnerabilities in core products \"such as ChatGPT, Codex, and the API Platform can earn base bounties of up to $30,000. Exceptional critical findings remain eligible for base bounties of up to $100,000, with total payouts reaching up to $172,000 with bonuses.\"\n- OpenAI introduced a five-tier loyalty program with larger bonuses at higher tiers, plus dedicated bonus pools for short-term campaigns on newly launched features; high-quality reports get a multiplier on the base bounty.\n- Help Net Security quotes OpenAI: \"If you've already submitted a report and we haven't yet awarded a bounty, we'll apply the new reward ranges,\" and says that for bounties awarded in the 30 days before the announcement OpenAI will pay the difference if the finding would have earned more under the new ranges.\n- The program \"complements OpenAI's Defense Factory, where engineers use the company's models to find and reproduce vulnerabilities and test fixes.\"\nFLAGS: company-claim, single-source\nNOTE: openai.com/index/* pages returned HTTP 403 to both WebFetch and scripts/fetch.js. The two OpenAI URLs above are listed with titles and \"Mon, 02 Nov 2026\" dates in openai.com/news/rss.xml, which I did read; all figures above come from Help Net Security, not from the OpenAI pages.\n\n===========================================================\nSECTION: Frontier models & labs\nHEADLINE: OpenAI hires former US Army Secretary Dan Driscoll for new national security role\nPUBLISHED: CNBC, November 3, 2026 (OpenAI post dated Mon 02 Nov 2026 in its RSS feed)\nSOURCES:\nCNBC | https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html | report\nOpenAI (post title and date from openai.com/news/rss.xml) | https://openai.com/index/dan-driscoll-joins-openai | primary\nFACTS:\n- CNBC: OpenAI hired Driscoll as \"senior counselor for national security modernization, a newly created role at the company.\" He will work with OpenAI's senior leadership and external partners, \"with a particular focus on helping U.S. allies adopt advanced AI responsibly,\" and will help internal teams understand the operational needs of national security institutions.\n- CNBC quotes Sam Altman saying the US has \"an extraordinary opportunity to work with other countries to spread the adoption of democratic AI.\"\n- CNBC quotes Driscoll: \"National security requirements are changing faster than at any time in the past fifty years,\" and \"I'm joining OpenAI to help the U.S. and our allies put this technology to work responsibly, for the people who keep us safe.\"\n- CNBC says Driscoll stepped down as Army secretary earlier this year after months of reported tensions with Defense Secretary Pete Hegseth (attributing the resignation detail to Reuters), and that the work builds on \"OpenAI's efforts to strengthen cyber resilience and protect essential services through its Daybreak program.\"\nFLAGS: company-claim\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Nvidia tells cloud partners at least 51% of services must go to non-Chinese customers\nPUBLISHED: Techzine Global, November 3, 2026, 10:00 am (original reporting: Financial Times, November 3, 2026)\nSOURCES:\nTechzine Global | https://www.techzine.eu/news/infrastructure/145501/nvidia-imposes-strict-requirements-on-cloud-providers/ | report\nFinancial Times (original) | https://www.ft.com/content/1902df70-1380-4588-bad5-171352b575f2 | report\nBenzinga | https://www.benzinga.com/markets/tech/26/11/62808888/nvidia-tightens-the-screws-on-chinas-ai-access-cloud-partners-worldwide-must-restrict-chinese-customers-under-new-revenue-rule-report | report\nFACTS:\n- Techzine, citing the FT: \"Cloud providers using Nvidia's AI chips must sell at least 51 percent of their services to non-Chinese customers.\" The FT's account rests on five insiders; two of them said the requirement applies to Nvidia customers worldwide, not only to Asian data centers.\n- The requirement applies only to future contracts, not existing lease agreements, and was communicated verbally through Nvidia's sales and regional teams rather than in writing.\n- Price gap cited: \"A rack of B300 chips costs about $600,000 on the international market. An insider said one was recently sold in China for the equivalent of $2.8 million.\"\n- A Singapore-based group told the FT \"it is difficult to find enough non-Chinese customers outside the U.S.\"\n- Search-result text from secondary coverage adds that the reports did not say whether the share is measured by revenue, computing capacity or number of customers, nor how Nvidia defines a Chinese company; and that Nvidia said in a statement that data centers and cloud services built on American chips are the foundation US AI developers need to compete globally.\nFLAGS: single-source (all coverage traces to one FT report; FT page itself refused both fetch methods — figures above are from Techzine's write-up of the FT and from search-result text)\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Marvell to acquire Lumentum in all-stock deal with $115 billion implied enterprise value\nPUBLISHED: November 2, 2026\nSOURCES:\nMarvell investor relations (press release) | https://investor.marvell.com/news-events/press-releases/detail/1040/marvell-and-lumentum-to-combine-creating-a-category-leader-in-ai-connectivity | primary\nLumentum Form 425 (SEC) | https://www.sec.gov/Archives/edgar/data/0001633978/000119312526442760/d163169d425.htm | primary\nReuters | https://www.reuters.com/legal/transactional/marvell-buy-lumentum-115-billion-deal-ai-data-center-bet-2026-11-02/ | report\nFACTS:\n- All-stock acquisition at an exchange ratio of 4.500 Marvell shares per Lumentum share, an implied value of about $1,132 per Lumentum share and an implied enterprise value of $115 billion.\n- Premium of approximately 23.9% based on unaffected closing prices as of October 28, 2026.\n- Pro forma ownership on a fully diluted basis: approximately 67% Marvell stockholders, approximately 33% Lumentum stockholders.\n- Marvell says it has line of sight to more than $1 billion in annual run-rate cost synergies and puts the combined company's total addressable market at $550 billion.\n- Expected to close in the first half of calendar year 2028, subject to stockholder and regulatory approvals. Marvell said preliminary fiscal Q3 2027 revenue is consistent with prior guidance, with the midpoint unchanged and the range narrowed to ±2% from ±5%.\nFLAGS: company-claim (synergy and TAM figures are Marvell's)\nNOTE: Reuters URL refused fetch; all figures above are from the Marvell press release, which I read in full.\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Drax, Brookfield and Radiant plan up to 1GW data centre at Drax power station; investment could exceed £20bn\nPUBLISHED: DatacenterDynamics, November 03, 2026; CNBC, November 3, 2026\nSOURCES:\nDatacenterDynamics | https://www.datacenterdynamics.com/en/news/drax-partners-with-brookfield-and-radiant-for-up-to-1gw-data-center-at-north-yorkshire-power-station/ | report\nCNBC | https://www.cnbc.com/2026/11/03/brookfield-ai-data-center-yorkshire-drax.html | report\nReuters | https://www.reuters.com/business/uks-drax-signs-data-centre-deal-with-brookfield-radiant-2026-11-03/ | report\nFACTS:\n- Drax has partnered with Brookfield and its UK-headquartered AI infrastructure platform Radiant to develop up to a gigawatt of data centre capacity at the 2.6GW Drax Power Station in Selby, North Yorkshire, through a joint venture called Brookfield-Qai AI (DCD).\n- Phasing: phase one up to 100MW, \"expected to be operational from Q1 2028\"; phase two to 500MW between 2028 and 2031; phase three additional capacity post-2031 (DCD).\n- \"Brookfield has said it estimates total investment in the development could exceed £20 billion ($26.8bn), including an initial £2.5bn ($3.4bn) for the first phase\" (DCD). CNBC puts the same figure at \"could exceed £20 billion ($26.8 billion), with an initial £2.5 billion investment in phase 1,\" and says total investment includes semiconductors.\n- Site: \"1,000 acres and 4GW of grid access, with 2.6GW of active dispatchable generation\" (DCD). Phase one will use power from the grid, not the power plant (CNBC).\n- Conditions: progression depends on \"the timely progression of the necessary planning, as well as receiving the required regulatory and network approvals from government and the system operator, in addition to securing a suitable tenant\"; final investment decisions are yet to be made (DCD/CNBC).\n- Drax's London-listed shares were up 8.8% in early morning trading (CNBC).\n- DCD notes the announcement follows the UK government's rejection of a bid by North Yorkshire Council, the University of York and Drax to develop an up to 1.2GW data centre at the same site under the AI Growth Zone scheme, and that per energy think tank Ember \"Drax emitted 14.1 million tonnes of CO2 equivalent in 2025.\" Radiant was launched last November as part of the $10bn Brookfield Artificial Intelligence Infrastructure Fund, \"with plans to build and acquire as much as $100bn worth of AI infrastructure.\"\nFLAGS: company-claim (investment estimate is Brookfield's)\nNOTE: Reuters URL refused fetch; all figures from DCD and CNBC.\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Oracle files to sell $10bn of stock and $10bn of senior notes to fund AI buildout; shares fall 8.8%\nPUBLISHED: CNBC, November 2, 2026\nSOURCES:\nCNBC | https://www.cnbc.com/2026/11/02/oracle-files-to-sell-20-billion-in-new-stock-bonds-to-finance-ai-buildout.html | report\nWSJ | https://www.wsj.com/finance/oracle-looks-to-raise-20-billion-to-fund-ai-ambitions-582c814f | report\nFACTS:\n- \"The hyperscaler will sell $10 billion in common stock and $10 billion in senior notes, according to filings with the Securities and Exchange Commission.\" Shares tumbled 8.8% on Monday (CNBC).\n- Oracle said proceeds are for general corporate purposes, \"which may include capital expenditures, repayments of debt and future investments.\"\n- At its investor day the previous Wednesday Oracle issued a revenue forecast of at least $225 billion for fiscal 2030 and said it was limiting additional capital-market funding for the fiscal 2027 to 2030 investment cycle to that $20 billion.\n- CNBC: Oracle shares are down 33% in 2026 and 50% over the past 12 months; \"The yield on its investment-grade 4.95% bond due in 2031 is currently 7.276%\"; its five-year credit default swap spread \"sits at 292, up 265% in one year,\" which S&P Global Market Intelligence's Gavan Nolan says is \"more in line with a high-end junk bond rating.\"\n- Oracle plans to use vendor financing, customer-provided hardware and customer prepayments to help reach positive free cash flow, which it expects in the second half of 2028.\n- Baird's Rob Oliver, quoted by CNBC: \"This seems to be exactly what they previewed. So I'm not sure why the market is freaking about it.\"\nFLAGS: (none)\nNOTE: WSJ URL seen on Techmeme, not opened; all figures from CNBC.\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: Huawei's next AI chip to rely on Samsung and SK hynix HBM obtained via smuggled server packages\nPUBLISHED: TrendForce News, November 3, 2026 (original reporting: The Information, November 2, 2026)\nSOURCES:\nTrendForce News | https://www.trendforce.com/news/2026/11/03/news-china-reportedly-obtains-smuggled-hbm-via-server-packages-huawei-960dt-faces-domestic-hbm-shortage/ | report\nThe Information (original) | https://www.theinformation.com/articles/smugglers-get-expensive-memory-chips-china-south-korea | report\nTechmeme (dates the original to Nov 2) | https://www.techmeme.com/261102/p50 | report\nFACTS:\n- Per The Information via TrendForce: smugglers pack HBM chips with lower-performance server processors, \"exploiting rules that rate package computing power by the processor rather than the memory\"; in China technicians heat the packages to soften solder, remove the HBM stacks and discard the processors — \"The delicate process carries a high risk of damaging the memory.\" Smuggled memory often reaches Huawei's customers.\n- Huawei's Ascend 960DT is expected in Q1 2027, with memory bandwidth and capacity set to double versus Huawei's current AI processor, and is expected to rely heavily on HBM from Samsung Electronics and SK hynix; US restrictions prevent Huawei from sourcing enough directly, so it has reportedly asked some AI chip customers to source memory themselves.\n- Huawei \"reportedly raised the suggested price of the Ascend 950DT to more than RMB 250,000 (about US$37,000), citing high memory costs and tight supply\"; the 950DT \"delivers roughly half the raw compute of NVIDIA's H100 (launched 2022) but now costs as much as the B200.\"\n- Cambricon raised indicative pricing for its next-generation 690 chip by 20%–30%, with MetaX and Iluvatar CoreX reportedly making similar increases (attributed to Reuters).\n- CXMT's HBM3E yields are reportedly 20%–30%, versus about 70% for SK hynix (attributed to Reuters). Search-result text adds that a Chinese broker told The Information one HBM3E unit that sold for several hundred US dollars a year ago now costs about $4,000, and that SK hynix said it complies with US and South Korean export laws and had not supplied Huawei since US export controls took effect in 2020.\n- TrendForce also notes The Information's report that Huawei is working with DeepSeek to optimize the chip for AI model pre-training.\nFLAGS: single-source (all of it traces to one Information report; The Information page not opened — figures from TrendForce's write-up plus search-result text)\n\n===========================================================\nSECTION: Compute, chips & infrastructure\nHEADLINE: OpenAI launches Grid Protectors Program, pledging to cut campus power during grid emergencies\nPUBLISHED: Crypto Briefing, November 2, 2026, 08:44 EST (OpenAI post dated Mon 02 Nov 2026 in its RSS feed)\nSOURCES:\nCrypto Briefing | https://cryptobriefing.com/openai-grid-protectors-program-data-centers/ | report\nTechgenyz | https://techgenyz.com/openai-launches-grid-protectors-program/ | report\nOpenAI (post title and date from openai.com/news/rss.xml) | https://openai.com/index/grid-protectors-program | primary\nThe Verge | https://www.theverge.com/ai-artificial-intelligence/1024604/openai-data-center-grid-protection-program | report\nFACTS:\n- OpenAI pledged to reduce electricity use at data center campuses it directly develops when extreme weather or other emergencies strain the US grid, extending commitments made in Georgia nationwide (Crypto Briefing). Each campus would agree with its local utility on how much power it can give up, how quickly and for how long; OpenAI has not said which other campuses will join or on what terms.\n- Georgia flagship (Project Camellia, Effingham County, GA): projected demand at full build-out 3.2 GW; 25-year contract; delivery phases 2028 to 2032; \"up to 1 GW\" of flexible demand response letting Georgia Power cut supply during high-demand events; construction targeted to begin in late 2026; full build-out investment estimated at $20 billion to more than $30 billion (Crypto Briefing).\n- Techgenyz quotes OpenAI describing \"up to 1,000 MW of flexible demand-response capacity,\" \"equivalent to the average electricity demand of approximately 700,000 households,\" and notes \"These figures represent planned capacity rather than electricity reductions already delivered to the grid.\"\n- OpenAI covers 100% of infrastructure and electric-service costs tied to the project; community benefits fund of $80 million including up to $71 million in educational credits for Georgia students; Georgia Public Service Commission approval on or around August 26, 2026 (Crypto Briefing). Techgenyz adds Georgia Power projects about $950 million in annual customer savings from 2029 across its broader large-load portfolio, and at least $15/month savings from 2029 for a typical residential customer using 1,000 kWh/month.\n- Crypto Briefing notes the pledge covers campuses OpenAI directly develops, \"not necessarily capacity it rents from cloud partners or third-party operators.\" Search-result text quotes OpenAI saying flexibility \"cannot replace investment in new energy supply and transmission.\"\nFLAGS: company-claim\nNOTE: openai.com/index/* and theverge.com both refused fetch. All figures above come from Crypto Briefing and Techgenyz.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: Palantir Q3 revenue $2.31bn, up 96%; US commercial revenue overtakes US government for first time\nPUBLISHED: After the bell, Monday November 2, 2026 (CNBC)\nSOURCES:\nPalantir Q3 2026 press release (Form 8-K, SEC) | https://www.sec.gov/Archives/edgar/data/0001321655/000132165526000045/a2026q3ex991pressrelease.htm | primary\nCNBC | https://www.cnbc.com/2026/11/02/palantir-pltr-earnings-q3-2026.html | report\nWSJ | https://www.wsj.com/business/earnings/palantir-lifts-outlook-as-u-s-commercial-business-overtakes-government-business-16eb693f | report\nFACTS:\n- Versus LSEG estimates: adjusted EPS 44 cents vs 41 cents expected; revenue $2.31 billion vs $2.18 billion expected. \"Revenue nearly doubled from a year ago and blew past $2 billion for the first time ever, Palantir said\" (CNBC). The 8-K press release text gives revenue of $2.313 billion, up 96% year over year.\n- Net income more than doubled to $1.13 billion, or 44 cents per share, from about $476 million, or 18 cents per share (CNBC).\n- US commercial revenue jumped 148% to $984 million, surpassing US government revenue of $953 million, which was up 96%; US commercial revenue \"has more than quintupled over the last two years\" (CNBC). Press release text also gives total US revenue of $1.937 billion, up 119%, and US commercial remaining deal value of $6.517 billion, up 79% year over year.\n- Guidance raised: US commercial revenue now expected \"in excess of\" $3.56 billion for the full year, up from $3.42 billion last quarter; about $2.65 billion projected for Q4 and about $8.53 billion for full-year 2026 (CNBC).\n- Shares dipped about 3% in extended trading (CNBC). CEO Alex Karp told CNBC \"I don't believe anyone's had consistent results like this in the history of software AI, ever,\" and reiterated recent calls to nationalize AI labs, calling it the \"only realistic way\" to manage liability.\nFLAGS: (none)\nNOTE: WSJ URL seen on Techmeme, not opened. The SEC 8-K figures above come from search-result text quoting that filing; CNBC figures are from the article I read in full.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: Revolut moves ~2,000 engineers to self-hosted GLM, says coding bill fell to about a tenth\nPUBLISHED: Trending Topics, 3 November 2026, 09:22\nSOURCES:\nTrending Topics | https://www.trendingtopics.eu/revolut-glm-open-weight-coding-costs/ | report\nFACTS:\n- Revolut's default coding assistant is a self-hosted GLM model from Chinese lab Z.ai with about 800 billion parameters, running on about 56 Nvidia B200 chips on US infrastructure rather than the developer's China endpoint; context window capped at 256,000 tokens; GLM handles text only, with image tasks routed to Gemini, and Claude Code and Codex remaining available as exceptions.\n- Revolut says its bill is about a tenth of its previous spend on Anthropic and OpenAI, a roughly 90% reduction; self-hosted inference costs about 30 cents per million tokens, per Revolut's David Abitbol; token limits were removed and a flat bill replaced month-end invoices.\n- Across a sample of about 2,000 software engineers: coding time fell 60% and lead time (task pickup to merge) fell 70% with GLM; earlier, Google's Gemini cut coding time by 20% and lead time by 10%. Time to first token dropped from over 10 seconds to 1.6 seconds \"even as demand rose 76%.\"\n- Source of the claims: a talk by David Abitbol, who oversees AI operations and infrastructure at Revolut, titled \"Shipping like a startup, regulated like a bank\" at the AI Engineer conference in New York. Trending Topics notes an analysis by StartupHub.ai saying the 90% figure excludes cloud, staff and monitoring costs, and that the article does not say whether Revolut bought or rents the chips.\n- Hardware cost framing in the article: per Jensen Huang, B200 chips cost $30,000–40,000 each, about $1.7–2.2 million for 56; industry estimates put eight-B200 servers at $450,000–500,000.\nFLAGS: company-claim, single-source\nNOTE: Trending Topics states the article was co-produced with AI (\"Trendy AI\"); figures are attributed to Abitbol/Revolut and StartupHub.ai.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: Musk says Grok Bot serving costs were \"unsustainably high relative to revenue\" as usage limits tighten\nPUBLISHED: TechCrunch, 8:23 AM PST · November 2, 2026; Forbes, Nov 02, 2026, 06:19am EST\nSOURCES:\nTechCrunch | https://techcrunch.com/2026/11/02/elon-musk-throttles-grok-bot-limits-due-to-unsustainably-high-costs/ | report\nForbes | https://www.forbes.com/sites/siladityaray/2026/11/02/musk-says-grok-bots-costs-were-unsustainably-high-weeks-after-touting-rapid-growth/ | report\nFACTS:\n- Over the Halloween weekend some Grok Bot users found weekly usage limits unexpectedly maxed out, with some reporting usage jumping \"from as low as 50% to 100%\"; Musk confirmed in an X post on Sunday that this was not a glitch, writing \"The cost of serving Grok Bot was unsustainably high relative to revenue\" (TechCrunch, quoting the Nov 1 post).\n- TechCrunch: SpaceX \"said in a filing last month that AI now makes up 52% of company income\"; its renamed \"Super Intelligence\" division \"turned a profit of $431 million,\" and \"Its profit would've been higher if not for $1.2 billion of one-time costs related to its acquisition of Cursor.\" Musk has not said how subscriber usage limits will be affected going forward.\n- Forbes: Grok Bot is available to users on the $30/month \"Premium\" tier or higher, with $100/month Super and $200/month Ultra plans offering higher limits; Musk's posts \"didn't say how much Grok Bot costs the company to operate or if the company has lowered its usage limits for subscribers.\"\n- Forbes: SpaceX President Gwynne Shotwell said on the Q3 earnings call that Grok Bot had 800,000 paid weekly users in early October, \"more than doubled over the previous month.\" Musk on the same call called it the fastest-growing product he has ever seen and said the company is preparing \"wide deployment within a few weeks\" for enterprise customers.\n- Forbes: SpaceX acquired Cursor for $60 billion in August; Cursor reported a billing and usage dashboard problem on Sunday, later marked resolved, and \"Grok and Cursor draw from a shared weekly usage allowance under the company's unified subscription plans.\"\nFLAGS: company-claim\nNOTE: x.ai now renders as \"SpaceXSI\"; its news index lists a Product post dated Nov 2, 2026, \"Giving every team a data scientist with Grok Bot,\" but I could not locate a working URL for that post (the slug I tried 404'd), so I have not used it.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: New York Times sues Brave over scraping, naming Anthropic, Perplexity, Mistral, xAI and Cohere as buyers\nPUBLISHED: TechCrunch, 11:19 AM PST · November 2, 2026\nSOURCES:\nTechCrunch | https://techcrunch.com/2026/11/02/new-york-times-and-other-outlets-sue-web-browser-brave-over-alleged-content-scraping/ | report\nFACTS:\n- The New York Times sued Brave on Monday, alleging it scraped the outlet's copyrighted content \"and unlawfully distributed it to customers the suit names as Anthropic, Perplexity, Mistral, xAI, and Cohere.\"\n- Separately on Monday the Daily News, the Chicago Tribune and the Orlando Sentinel filed a similar lawsuit; both were brought in federal court in Manhattan.\n- The suit likens Brave to a \"supplier, dealer, and distributor of stolen copyrighted content\" and reads: \"In this way, Brave acts both like a burglar that misappropriates the content of publishers, and an AI 'fence' that sells stolen content to third parties.\"\n- The suit says Brave \"built an index of more than 30 billion web pages using an unidentified crawler, leaving publishers unable to block it,\" and also targets a Brave feature that bypasses paywalls and its practice of blocking publishers' ads while selling its own.\n- Brave has raised roughly $250 million to date according to private-market trackers; the Times seeks an injunction and damages; Brave did not immediately respond to a request for comment.\nFLAGS: single-source\nNOTE: I did not locate the court docket or complaint PDF; all facts are from TechCrunch's reading of the filings.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: UK NCSC annual review warns AI-powered ransomware on critical infrastructure \"highly likely\" by 2028\nPUBLISHED: The Record, November 3, 2026 (report launched Tuesday); SecurityWeek, 3 November 2026\nSOURCES:\nThe Record (Recorded Future News) | https://therecord.media/uk-ncsc-predicts-rise-cyberattacks-coming-months | report\nSecurityWeek | https://www.securityweek.com/uk-cyber-chief-says-the-uk-will-face-ai-cyberattacks-on-critical-infrastructure-by-2028/ | report\nThe Guardian | https://www.theguardian.com/technology/2026/nov/03/ai-powered-malware-artificial-intelligence-hacking-critical-uk-infrastructure | report\nFACTS:\n- Launching the NCSC's annual report, chief executive Richard Horne warns Britain faces the \"real prospect of an unprecedented rise in the number of cyber incidents\" in the coming months — \"not because AI has invented new ways to attack us,\" but \"because vulnerabilities that have been tolerated for far too long can now be discovered and exploited at a scale that was once unimaginable\" (The Record).\n- The NCSC says it is \"highly likely\" that AI-powered malware will be used in a ransomware attack on Britain's critical infrastructure by 2028, and that China and Russia will \"routinely\" be using AI in their cyber operations by that date (The Record).\n- Horne, quoted by The Record: \"Major technology providers are now fixing hundreds of vulnerabilities in a single update … and the Linux kernel project alone patched more than a thousand vulnerabilities last month.\"\n- Government AI defence spending in the report: a new £70 million ($93 million) NERV Centre (National Exposure and Real-Time Vulnerability Centre), and a further £60 million ($80 million) for the first phase of Cyber Shield, \"a national network of AI agents first previewed in July.\" Project DROMOS, \"initially planned to be a four-week pilot,\" was expanded into live government environments where it found \"hundreds of potential security issues, including critical vulnerabilities\" (The Record).\n- The report says the \"structural advantage will remain with defenders,\" but \"this advantage is not a given and realising it requires clear direction, investment and disciplined adoption\" (The Record).\n- SecurityWeek: the report is the NCSC Annual Review 2026; \"Malicious cyber activity costs UK organizations almost $20 billion per year, according to the NCSC\"; the report calls Chinese cyber activity the \"most sophisticated and sustained cyber challenge facing the U.K.\"; GCHQ director Anne Keast-Butler said \"cybersecurity is now part of the front line defense of our nation.\"\nFLAGS: (none)\nNOTE: I could not reach the NCSC Annual Review 2026 document itself (ncsc.gov.uk/news returned no listing; Guardian refused fetch). All facts are from The Record and SecurityWeek.\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: Salesforce signs definitive agreement to acquire voice-AI contact centre company Cresta\nPUBLISHED: Announced November 2, 2026; Tech Monitor, November 3, 2026\nSOURCES:\nTech Monitor | https://www.techmonitor.ai/news/salesforce-to-acquire-voice-ai-company-cresta | report\nThe Information (price) | https://www.theinformation.com/briefings/exclusive-salesforce-acquires-startup-cresta-2-7-billion | report\nFACTS:\n- Salesforce signed a definitive agreement to acquire Cresta, a voice-first customer experience platform; Salesforce did not disclose the purchase price. The Information reported a valuation of $2.7bn, citing a person familiar with the transaction (Tech Monitor).\n- The deal is expected to close in Q1 of Salesforce's fiscal year 2028, pending regulatory approvals and other standard conditions; Cresta's technology will be integrated with Salesforce Service Cloud, and after close Cresta \"will continue supporting its customers' existing contact centre and telephony platforms\" (Tech Monitor).\n- Comcast, Marriott and Alaska Airlines are named as users of Cresta's technology (Tech Monitor).\n- Quotes (Tech Monitor): Kishan Chetan, Salesforce EVP and GM, Agentforce and Service Cloud — \"Voice is where service is hardest to get right, and where it matters most to customers\"; Cresta CEO Ping Wu — \"Cresta's mission is to turn every customer interaction into a competitive advantage for our customers.\"\n- Search-result text adds that Cresta's last known valuation was $1.6 billion in 2022.\nFLAGS: single-source (price is one outlet's reporting; Salesforce did not disclose it)\n\n===========================================================\nSECTION: Deployment & impact\nHEADLINE: Squarespace cuts about 19% of staff, around 300 employees, in restructuring\nPUBLISHED: TechCrunch, 11:25 AM PST · November 2, 2026\nSOURCES:\nTechCrunch | https://techcrunch.com/2026/11/02/web-host-squarespace-lays-off-19-of-its-employees/ | report\nFACTS:\n- Squarespace spokesperson Jeff Seedman confirmed to TechCrunch: \"Squarespace is restructuring its organization and reducing its global workforce by approximately 19%, representing around 300 employees. The changes are intended to simplify how we operate, sharpen our priorities and enable the company to move faster as we position Squarespace for its next phase of growth.\" The Verge initially reported the layoffs.\n- Squarespace's statement does not attribute the cuts to AI. TechCrunch's own framing notes that \"'Vibe-coding' website builders… have largely upended the industry,\" citing Wix's $80 million purchase of Base44 last year and Lovable's $400 million Series C in August at a $13.3 billion valuation.\n- TechCrunch notes Squarespace launched an AI tool called Blueprint in 2024 and has announced an upcoming \"AI native platform\" called Forma; the company went public in 2021 at a $10 billion valuation and went private in a $7 billion private equity deal in 2024.\nFLAGS: single-source\nNOTE: Include only if you want a labour-effects item; the company did not cite AI as the cause, and the AI connection is the reporter's framing. I would treat this as a weak candidate.\n\n===========================================================\nREJECTED CANDIDATES (and why)\n- Google's first Project Suncatcher satellite running Gemma 4 in orbit / \"writing poetry\" — the orbital AI response was announced 30 October 2026 and the launch was 1 October; no new development inside the window.\n- Anthropic expected to get a \"high junk\" credit rating post-IPO (FT/Blackstone) — TechCrunch's report is dated 2026-10-30, outside the window.\n- Anthropic seeking up to $3.5B from Japanese investors (Bloomberg, Nov 2) — appears to be the same story as yesterday's covered 552.9bn yen Japanese share sale; no new facts I could verify.\n- SemiAnalysis GDPx benchmark (Nov 2) — covered yesterday; nothing new inside the window beyond secondary rewrites.\n- Mistral Large 4 / \"Le Chonk\" open weights — Mistral news page and the Hugging Face post both date it 29 October; outside window.\n- Kimi K3.1 Pro (Moonshot) — released 23 October; weights promised 4 November, i.e. after the window.\n- Artificial Analysis Intelligence Index v5 / Gemini 4 Carbon at 59 — index launch and the #1 result date to around 28 October; outside window.\n- DeepSeek \"creator mode\" for Harness plugins (Bloomberg, Nov 2) — a developer-preview feature addition with no figures; minor feature update per the skip rules.\n- OpenAI trims fundraising goal to up to $20B (CNBC, Nov 2 headline) — the underlying report is TechCrunch/Reuters from 31 October; I could not open a Nov 2 piece with new numbers (CNBC URL guesses 404'd).\n- Intel foundry \"critical test after stock's 45% plunge in October\" (CNBC) — could not verify the 45% figure or locate the article; dropped.\n- Blackstone \"more equity needed to fund AI buildout as debt risks mount\" (CNBC, Nov 3) — could not locate a working URL or confirm any figure; dropped.\n- \"Scaling Git at OpenAI\" (openai.com, Nov 2) — openai.com/index/* returns HTTP 403 to every fetch method; could not read it, so no facts to report.\n- 42AI out of stealth with $62.5M (TechCrunch, Nov 2) — below the $100M bar, not a frontier/defence/health/security lab, and its headline claims (98% accuracy, F1 0.8–0.85, ~$30M of \"additional value\" at one brokerage) are entirely company-stated and unverifiable.\n- Trajectory $45M (TechCrunch, Nov 2), Tutor Intelligence $75M (Forbes/SiliconANGLE, Nov 2), Omen AI's $16M Aquatic Labs acquisition — all below the $100M bar and not strategically notable.\n- Y Combinator's Garry Tan spending up to $200K/year on tokens (TechCrunch, Nov 2) — single anecdote, no verifiable aggregate.\n- \"The SEC Should Block Anthropic's IPO to Protect the Public\" (Tech Policy Press, Nov 2) — opinion piece with no new facts.\n- Apple margin/memory-cost commentary (Gizmodo/TechCrunch, Nov 2) — the earnings call itself predates the window; the Nov 2 items are commentary.\n- NVIDIA \"Cities Worldwide Build and Scale AI Services\" (blogs.nvidia.com, Nov 3) and Hugging Face \"Transformers Model Integration Contracts\" (Nov 3) — in window but marketing/engineering notes with no releases, benchmarks or figures.\n- Nothing in window from: anthropic.com/news (latest Oct 28), DeepMind blog (latest Oct), Google AI blog (only an October-roundup post), Microsoft Research feed (latest Oct 30), Mistral news (latest Oct 29), Allen AI blog (latest Oct 27), SemiAnalysis (latest in-window item is the already-covered GDPx), Utility Dive (latest dated items Oct 26–27). moonshotai.github.io redirects to moonshot.cn with no content; qwenlm.github.io has moved and qwen.ai/research returned no readable listing; z.ai/blog 404s; api-docs.deepseek.com/news shows no dated list.\n"
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{"stdout":"{\n  \"date\": \"2026-11-03\",\n  \"edition\": \"daily\",\n  \"generated_at\": \"2026-11-03T11:50:00Z\",\n  \"window\": \"2 Nov 11:50 → 3 Nov 11:05 UTC\",\n  \"title\": \"Anthropic says its self-improvement threshold may arrive imminently\",\n  \"summary\": [\n    \"Anthropic's amended Form S-1, filed with the SEC on 2 November, tells investors that \\\"our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI.'\\\" The filing says no current model has been designated as exceeding that threshold, reports that over 90% of the contributions to Anthropic's codebase in September 2026 were written by Claude, and puts aggregate committed spend at approximately $895.4 billion, substantially all of it compute and infrastructure, against $17.0 billion of third-quarter revenue and a $567 million operating loss.\",\n    \"Four MIT CSAIL researchers report that GPT-6 Astra, with no training loop, edited 131,072 weights of Qwen3.5-0.8B — 0.016% of the model — and moved it from 7.9% to 48.1% on MATH-500; a critic published the next day argues the gain came from removing a looping failure rather than adding mathematical ability. Google Threat Intelligence Group says hijacked enterprise LLM access produced fraudulent charges \\\"exceeding $100,000 USD in a single day\\\", with cumulative charges at some organisations reaching $1 million, and that one actor executed more than 500,000 LLM API calls in less than eight hours to power a resale service priced at about $60 a month.\",\n    \"The UK's National Cyber Security Centre published its annual review today, assessing it \\\"highly likely\\\" that AI-powered malware will have been used in a ransomware attack on UK critical national infrastructure by 2028. And Seoul Economic Daily, reporting the Financial Times, says Nvidia has told cloud and data-centre customers worldwide that at least 51% of their services must be sold to non-Chinese companies.\"\n  ],\n  \"sections\": [\n    {\n      \"name\": \"Frontier models & labs\",\n      \"items\": [\n        {\n          \"headline\": \"Anthropic's amended S-1 says internal estimates indicate it may \\\"imminently\\\" meet its own AI-acceleration threshold\",\n          \"sources\": [\n            { \"name\": \"SEC\", \"url\": \"https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm\" },\n            { \"name\": \"Gizmodo\", \"url\": \"https://gizmodo.com/anthropic-claims-to-be-closing-in-on-recursive-self-improvement-2000834175\" }\n          ],\n          \"bullets\": [\n            \"New risk-factor language in the Form S-1/A filed on 2 November reads: \\\"our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI.' We have not designated any of our current models as exceeding this threshold, and we continue to assess the underlying data.\\\" The filing says Anthropic is also \\\"evaluating the implications of meeting the AI research and development capability threshold\\\".\",\n            \"The same filing says Anthropic does \\\"not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding, if and when that becomes technically possible\\\", and that it is \\\"considering updates to our Responsible Scaling Policy to keep humans in control of frontier model development\\\". It discloses that past precautionary measures \\\"have included delaying the release of models and limiting their initial availability, such as with Mythos through Project Glasswing\\\".\",\n            \"The filing reports that \\\"over 90% of the contributions to our codebase in September 2026 were written by Claude\\\", and that average daily code contributed per engineer in the three months to 30 September 2026 was \\\"over 45 times\\\" the average daily volume in the year ended 31 December 2024.\",\n            \"Anthropic has not published the estimates behind the statement. The filing says much of its evidence on the pace of AI-driven acceleration \\\"is derived from lagging indicators\\\" and that its ability to forecast or measure acceleration \\\"is limited\\\", adding that it has \\\"in the past not identified, and may in the future not identify, a significant acceleration in our rate of development until after it has occurred\\\". Gizmodo reports the 26 October version of the filing contained the section on AI-driven acceleration without this passage.\"\n          ],\n          \"topics\": [\"anthropic\", \"alignment\", \"scaling\"],\n          \"storylines\": [\"pacing-frontier-ai\"],\n          \"impact\": \"neutral\",\n          \"flags\": [\"company-claim\"]\n        },\n        {\n          \"headline\": \"Anthropic adds two sentences to Claude Code's Opus 5.5 system prompt to stop it recreating existing video games\",\n          \"sources\": [\n            { \"name\": \"The Decoder\", \"url\": \"https://the-decoder.com/anthropic-cracks-down-on-game-cloning-in-claude-code-after-wave-of-ai-built-knockoffs/\" },\n            { \"name\": \"Tom's Hardware\", \"url\": \"https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks\" }\n          ],\n          \"bullets\": [\n            \"The Decoder reports that Anthropic employee Addy Osmani confirmed on X that two sentences were added to Claude Code's system prompt for Opus 5.5 to stop the tool cloning other people's games, and that Osmani said using Claude to infringe intellectual property violates the usage p
… [10069 more characters in events.jsonl]

{
  "command": "cat /home/user/ainews/data/2026-11-03.script.json",
  "description": "Read script JSON"
}

{"stdout":"{\n  \"date\": \"2026-11-03\",\n  \"format\": \"dialogue\",\n  \"hosts\": {\n    \"A\": {\n      \"name\": \"Maya\",\n      \"voice\": \"marin\"\n    },\n    \"B\": {\n      \"name\": \"Alex\",\n      \"voice\": \"cedar\"\n    }\n  },\n  \"blocks\": [\n    {\n      \"type\": \"intro\",\n      \"lines\": [\n        {\n          \"host\": \"A\",\n          \"text\": \"It's Tuesday, November 3rd, and this is The AI Edge, presented by Epilogue.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"Epilogue builds AI for work where being wrong is expensive. Epilogue ships systems that know what they know, show their work, and fail visibly instead of quietly. Find out more at epiloguelabs.com.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"I'm Maya.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"And I'm Alex.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"Here's what happened at the frontier of AI since yesterday morning. The advances, the research, and how it's being used for good and for harm, with every claim checked against its source.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"So what are the three that matter most today?\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"Anthropic filed an amended prospectus with the SEC, and told investors its internal estimates indicate it may imminently meet its own threshold for dramatically accelerated progress attributable to AI.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"Four researchers at MIT CSAIL say a frontier model edited 0.016% of a small model's weights and moved it from 7.9% to 48.1% on a maths benchmark.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"And Google's threat intelligence group says hijacked access to company AI accounts ran up fraudulent charges exceeding $100,000 in a single day.\"\n        }\n      ]\n    },\n    {\n      \"type\": \"transition\",\n      \"lines\": [\n        {\n          \"host\": \"B\",\n          \"text\": \"Let's start with the labs.\"\n        }\n      ]\n    },\n    {\n      \"type\": \"item\",\n      \"section\": \"Frontier models & labs\",\n      \"headline\": \"Anthropic's amended S-1 says internal estimates indicate it may \\\"imminently\\\" meet its own AI-acceleration threshold\",\n      \"lines\": [\n        {\n          \"host\": \"A\",\n          \"text\": \"Anthropic filed an amended registration statement on November 2nd, and there's new language in the risk factors. It says its internal estimates and its expectations about future models, rather than current models, indicate it may imminently meet its Responsible Scaling Policy's definition of dramatically accelerated progress attributable to AI.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"That's the company's own safety threshold. Has it crossed it?\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"Not yet. The filing says no current model has been designated as exceeding the threshold, and that Anthropic continues to assess the underlying data. It also says it does not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"And it's reconsidering the policy itself.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"It says it's considering updates to the Responsible Scaling Policy to keep humans in control of frontier model development. The filing also reports that over 90% of the contributions to Anthropic's codebase in September of 2026 were written by Claude.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"This is a company claim in Anthropic's own prospectus, not an independent assessment. The estimates behind it haven't been published, and the filing itself says much of its evidence comes from lagging indicators and that its ability to measure that acceleration is limited.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"It even says it has in the past not identified a significant acceleration until after it happened. Gizmodo reports the October 26th version of the filing had the acceleration section, but without this passage.\"\n        }\n      ]\n    },\n    {\n      \"type\": \"transition\",\n      \"lines\": [\n        {\n          \"host\": \"A\",\n          \"text\": \"To the research now.\"\n        }\n      ]\n    },\n    {\n      \"type\": \"item\",\n      \"section\": \"Research & papers\",\n      \"headline\": \"MIT CSAIL report: GPT-6 Astra edited 0.016% of a small model's weights and lifted MATH-500 from 7.9% to 48.1%\",\n      \"lines\": [\n        {\n          \"host\": \"B\",\n          \"text\": \"Four researchers at MIT CSAIL report that GPT-6 Astra, using no gradients and no training, read and edited another model's weights directly. The edit was 131,072 weights in a model called Qwen3.5-0.8B. That's 0.016% of it.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"And the effect?\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"They report it moved the model from 7.9% to 48.1% on MATH-500, from 13.8% to 67.1% on GSM8K, and from 21.0% to 62.3% on IFEval. A separate failing control policy succeeded in all 1,024 episodes after 3.5% of its weights were changed.\"\n        },\n        {\n          \"host\": \"A\",\n          \"text\": \"They published their own negative results too.\"\n        },\n        {\n          \"host\": \"B\",\n          \"text\": \"On a different small model, Gemma 3 270M, no edit moved MATH-500 by more than about a point. Their conclusion is that editing weights can remove an
… [10069 more characters in events.jsonl]

{
  "command": "cat /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results/bgt5j3kx7.txt | head -c 30000",
  "description": "Read first part of edition"
}

{"stdout":"{\n  \"date\": \"2026-11-03\",\n  \"edition\": \"daily\",\n  \"generated_at\": \"2026-11-03T11:50:00Z\",\n  \"window\": \"2 Nov 11:50 → 3 Nov 11:05 UTC\",\n  \"title\": \"Anthropic says its self-improvement threshold may arrive imminently\",\n  \"summary\": [\n    \"Anthropic's amended Form S-1, filed with the SEC on 2 November, tells investors that \\\"our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI.'\\\" The filing says no current model has been designated as exceeding that threshold, reports that over 90% of the contributions to Anthropic's codebase in September 2026 were written by Claude, and puts aggregate committed spend at approximately $895.4 billion, substantially all of it compute and infrastructure, against $17.0 billion of third-quarter revenue and a $567 million operating loss.\",\n    \"Four MIT CSAIL researchers report that GPT-6 Astra, with no training loop, edited 131,072 weights of Qwen3.5-0.8B — 0.016% of the model — and moved it from 7.9% to 48.1% on MATH-500; a critic published the next day argues the gain came from removing a looping failure rather than adding mathematical ability. Google Threat Intelligence Group says hijacked enterprise LLM access produced fraudulent charges \\\"exceeding $100,000 USD in a single day\\\", with cumulative charges at some organisations reaching $1 million, and that one actor executed more than 500,000 LLM API calls in less than eight hours to power a resale service priced at about $60 a month.\",\n    \"The UK's National Cyber Security Centre published its annual review today, assessing it \\\"highly likely\\\" that AI-powered malware will have been used in a ransomware attack on UK critical national infrastructure by 2028. And Seoul Economic Daily, reporting the Financial Times, says Nvidia has told cloud and data-centre customers worldwide that at least 51% of their services must be sold to non-Chinese companies.\"\n  ],\n  \"sections\": [\n    {\n      \"name\": \"Frontier models & labs\",\n      \"items\": [\n        {\n          \"headline\": \"Anthropic's amended S-1 says internal estimates indicate it may \\\"imminently\\\" meet its own AI-acceleration threshold\",\n          \"sources\": [\n            { \"name\": \"SEC\", \"url\": \"https://www.sec.gov/Archives/edgar/data/2130357/000162828026068676/anthropicpbc-sx1ax1.htm\" },\n            { \"name\": \"Gizmodo\", \"url\": \"https://gizmodo.com/anthropic-claims-to-be-closing-in-on-recursive-self-improvement-2000834175\" }\n          ],\n          \"bullets\": [\n            \"New risk-factor language in the Form S-1/A filed on 2 November reads: \\\"our internal estimates and our expectations regarding future models, rather than our current models, indicate that we may imminently meet our Responsible Scaling Policy's definition of 'dramatically accelerated progress attributable to AI.' We have not designated any of our current models as exceeding this threshold, and we continue to assess the underlying data.\\\" The filing says Anthropic is also \\\"evaluating the implications of meeting the AI research and development capability threshold\\\".\",\n            \"The same filing says Anthropic does \\\"not anticipate being able to safely use Claude to fully autonomously design and build successive generations of frontier models without meaningful human supervision or understanding, if and when that becomes technically possible\\\", and that it is \\\"considering updates to our Responsible Scaling Policy to keep humans in control of frontier model development\\\". It discloses that past precautionary measures \\\"have included delaying the release of models and limiting their initial availability, such as with Mythos through Project Glasswing\\\".\",\n            \"The filing reports that \\\"over 90% of the contributions to our codebase in September 2026 were written by Claude\\\", and that average daily code contributed per engineer in the three months to 30 September 2026 was \\\"over 45 times\\\" the average daily volume in the year ended 31 December 2024.\",\n            \"Anthropic has not published the estimates behind the statement. The filing says much of its evidence on the pace of AI-driven acceleration \\\"is derived from lagging indicators\\\" and that its ability to forecast or measure acceleration \\\"is limited\\\", adding that it has \\\"in the past not identified, and may in the future not identify, a significant acceleration in our rate of development until after it has occurred\\\". Gizmodo reports the 26 October version of the filing contained the section on AI-driven acceleration without this passage.\"\n          ],\n          \"topics\": [\"anthropic\", \"alignment\", \"scaling\"],\n          \"storylines\": [\"pacing-frontier-ai\"],\n          \"impact\": \"neutral\",\n          \"flags\": [\"company-claim\"]\n        },\n        {\n          \"headline\": \"Anthropic adds two sentences to Claude Code's Opus 5.5 system prompt to stop it recreating existing video games\",\n          \"sources\": [\n            { \"name\": \"The Decoder\", \"url\": \"https://the-decoder.com/anthropic-cracks-down-on-game-cloning-in-claude-code-after-wave-of-ai-built-knockoffs/\" },\n            { \"name\": \"Tom's Hardware\", \"url\": \"https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-confirms-new-claude-code-limits-to-prevent-game-cloning-users-report-opus-5-5-is-also-actively-blocking-reverse-engineering-tasks\" }\n          ],\n          \"bullets\": [\n            \"The Decoder reports that Anthropic employee Addy Osmani confirmed on X that two sentences were added to Claude Code's system prompt for Opus 5.5 to stop the tool cloning other people's games, and that Osmani said using Claude to infringe intellectual property violates the usage p
… [10069 more characters in events.jsonl]

{
  "command": "tail -c +30000 /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results/bgt5j3kx7.txt | head -c 30000",
  "description": "Read middle part of edition"
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{"stdout":"pping controlled goods to China through a third country and illegal gains confiscated.\",\n            \"The bill follows an August case in which Keelung prosecutors indicted nine people — including the general manager of Flying Tiger Technology and staff at the local units of Nvidia and Super Micro Computer — for allegedly diverting 74 Nvidia B300 servers to Chinese buyers for a profit of more than NT$600 million (US$18.5 million). None of the nine faces an export charge: prosecutors relied on breach of trust and document forgery, because selling the servers to China broke the two companies' internal rules and US export curbs but not Taiwanese law.\",\n            \"Asia Times is the only outlet reporting this that could be opened from here, and the bill is at hearing stage, not passed.\"\n          ],\n          \"topics\": [\"export-controls\", \"china\", \"chips\"],\n          \"storylines\": [\"china-distillation-export-controls\"],\n          \"impact\": \"neutral\",\n          \"flags\": [\"single-source\"]\n        },\n        {\n          \"headline\": \"OpenAI hires former US Army Secretary Dan Driscoll as senior counselor for national security modernization\",\n          \"sources\": [\n            { \"name\": \"CNBC\", \"url\": \"https://www.cnbc.com/2026/11/03/openai-hires-dan-driscoll-national-security.html\" }\n          ],\n          \"bullets\": [\n            \"CNBC reports OpenAI has hired former US Army Secretary Dan Driscoll as senior counselor for national security modernization, \\\"a newly created role at the company\\\", and that his updated LinkedIn profile also lists the position. He will focus on how AI can be used to strengthen US national security and cybersecurity, working with OpenAI's senior leadership and external partners \\\"with a particular focus on helping U.S. allies adopt advanced AI responsibly\\\".\",\n            \"Sam Altman said the US has \\\"an extraordinary opportunity to work with other countries to spread the adoption of democratic AI\\\". Driscoll said \\\"National security requirements are changing faster than at any time in the past fifty years\\\" and that he is joining \\\"to help the U.S. and our allies put this technology to work responsibly, for the people who keep us safe\\\".\",\n            \"CNBC says Driscoll resigned as Army secretary following reported tensions with Defense Secretary Pete Hegseth, citing Reuters, and that the work builds on OpenAI's efforts to strengthen cyber resilience and protect essential services through its Daybreak programme.\",\n            \"Neither OpenAI nor CNBC describes any specific contract or government programme attached to the role, and OpenAI's own announcement page could not be opened from here.\"\n          ],\n          \"topics\": [\"openai\", \"military\", \"us-federal-policy\"],\n          \"impact\": \"neutral\"\n        },\n        {\n          \"headline\": \"Saab says it developed, trained and flew its own combat AI agents on a Gripen E fighter\",\n          \"sources\": [\n            { \"name\": \"Breaking Defense\", \"url\": \"https://breakingdefense.com/2026/11/swedens-saab-launches-family-of-ai-agents-for-future-aircraft-projects/\" }\n          ],\n          \"bullets\": [\n            \"Breaking Defense reports Saab has unveiled a suite of in-house AI agents for future aircraft platforms after testing them on a Gripen E multirole fighter, and that a company statement released the same day says this demonstrates Saab's \\\"ability to develop, train, and fly its own AI for air combat\\\" operations. Saab says the agents use \\\"various AI techniques to master tactical decision-making in complex operational environments\\\" and can work with a pilot in the cockpit or from an uncrewed air vehicle.\",\n            \"Peter Nilsson, head of Advanced Programs at Saab's aeronautics unit, told Breaking Defense and other media: \\\"The harder question is how we turn this success [of flying with the agents] into a dependable capability that can learn, improve, and be relevant over time… that is the true purpose of the AI Fighter Pilot Academy.\\\"\",\n            \"Breaking Defense reports Nilsson's claim that \\\"When Sferical AI is applied to a one-hour simulated training flight, it can produce the equivalent of one billion flight hours for a human pilot.\\\" It says the agents have mostly been tested under Beyond Visual Range combat conditions, and that Saab plans to use the technology on a trio of unmanned aircraft — the A1, A2 and A3 — on the path to a loyal wingman drone.\",\n            \"The capability and equivalence claims are Saab's and are not independently verified; Breaking Defense notes the earlier reference point is a 2025 Gripen E test campaign using Helsing's Centaur AI, which is not part of this programme.\"\n          ],\n          \"topics\": [\"military\", \"autonomous-weapons\", \"robotics\"],\n          \"impact\": \"neutral\",\n          \"flags\": [\"company-claim\"]\n        },\n        {\n          \"headline\": \"Russian decree lets data-centre operators use foreign compute with FSB approval after drone strikes on Yandex sites\",\n          \"sources\": [\n            { \"name\": \"Silicon UK\", \"url\": \"https://www.silicon.co.uk/cloud/datacenter/russia-data-centre-632139\" }\n          ],\n          \"bullets\": [\n            \"Silicon UK reports the Russian government has given data-centre operators temporary permission to use computing resources located outside the country, after Ukrainian drone strikes on Yandex facilities in October disrupted some services. Companies will require permission from the Federal Security Service (FSB) to form such links with foreign companies, according to a Monday decree by the presidential administration posted on the government's legal information portal.\",\n            \"The decree also obliges Russian data-centre operators to reserve 10 percent of their capacity for supporting government information r
… [10069 more characters in events.jsonl]

{
  "command": "tail -c +60000 /root/.claude/projects/-home-user-ainews/c0ba620c-ead7-5889-a588-1d740c20a25e/tool-results/bgt5j3kx7.txt",
  "description": "Read remaining part of edition"
}

{
  "stdout": " and that OpenAI committed an \\\"$80 million community benefits fund\\\" including \\\"up to $71 million in educational credits for Georgia students\\\". Southern Company, Georgia Power's parent, now reports total contracted large-load capacity of 17 GW.\",\n            \"These are planned capabilities, not electricity reductions already delivered. Crypto Briefing notes the pledge \\\"covers campuses OpenAI directly develops, not necessarily capacity it rents from cloud partners or third-party operators\\\", and OpenAI has not said which other campuses will join the programme or on what terms. OpenAI's own announcement page could not be opened from here.\"\n          ],\n          \"topics\": [\"openai\", \"energy\", \"datacenters\"],\n          \"impact\": \"mixed\",\n          \"flags\": [\"company-claim\", \"single-source\"]\n        }\n      ]\n    },\n    {\n      \"name\": \"Deployment & impact\",\n      \"items\": [\n        {\n          \"headline\": \"Palantir's Q3 revenue rises 96% to $2.313 billion as US commercial revenue overtakes US government for the first time\",\n          \"sources\": [\n            { \"name\": \"SiliconANGLE\", \"url\": \"https://siliconangle.com/2026/11/02/palantir-beats-q3-forecasts-as-us-commercial-revenue-overtakes-government-for-first-time/\" }\n          ],\n          \"bullets\": [\n            \"SiliconANGLE reports Palantir's third-quarter revenue was $2.313 billion, up 96% year over year, with US commercial revenue of $984 million, up 148%, overtaking US government revenue of $953 million, which was up 96%. Adjusted earnings were $0.44 per share against $0.21 a year earlier, and net income was $1.128 billion against $476 million.\",\n            \"Palantir raised full-year 2026 revenue guidance to between $8.530 billion and $8.534 billion, from $8.150 billion to $8.158 billion in August, and said US commercial revenue is expected to exceed $3.559 billion, growth of at least 143%.\",\n            \"The crossover matters because Palantir's US commercial book is the part of the business least tied to federal budget cycles, and the company's government work remains the subject of continuing scrutiny over deployments in the US and UK.\",\n            \"These are company-reported figures on the day of release; SiliconANGLE does not report GAAP earnings per share, and reports of the share-price reaction differed across outlets, so none is given here.\"\n          ],\n          \"topics\": [\"palantir\", \"earnings\", \"deployment\"],\n          \"impact\": \"neutral\",\n          \"flags\": [\"company-claim\", \"single-source\"]\n        },\n        {\n          \"headline\": \"Revolut moves about 2,000 engineers to a self-hosted Chinese open-weight model and says its coding bill fell to about a tenth\",\n          \"sources\": [\n            { \"name\": \"Trending Topics\", \"url\": \"https://www.trendingtopics.eu/revolut-glm-open-weight-coding-costs/\" }\n          ],\n          \"bullets\": [\n            \"Trending Topics reports that Revolut has moved its roughly 2,000 software engineers from Claude Code and Codex to a self-hosted open-weight model, GLM from the Chinese lab Z.ai, and that according to Revolut its bill is now about a tenth of what it used to pay Anthropic and OpenAI. The details come from a talk by David Abitbol, who oversees AI operations and infrastructure at Revolut, at the AI Engineer conference in New York.\",\n            \"Revolut runs GLM, a model with about 800 billion parameters, on roughly 56 Nvidia B200 chips, at a cost of about 30 cents per million tokens, with a flat bill replacing month-end invoices and per-engineer token limits removed. After optimisation, time to first token fell from more than 10 seconds to 1.6 seconds \\\"even as demand rose 76 percent\\\"; the context window is capped at 256,000 tokens; GLM handles text only, with image tasks routed to Gemini; and Claude Code and Codex remain available as exceptions.\",\n            \"In a sample of about 2,000 engineers, Abitbol says coding time fell 60 percent and lead time, from picking up a task to merging it, fell 70 percent. An earlier company-wide rollout of Google's Gemini cut coding time by 20 percent and lead time by 10 percent. Abitbol's reading of the gap is that \\\"The bottleneck for engineering is not necessarily coding.\\\"\",\n            \"All figures are Revolut's own, presented at a conference, with no independent measurement. Trending Topics notes an analysis by StartupHub.ai saying the 90% cost reduction excludes cloud, staff and monitoring costs, and the article does not say whether Revolut bought or rents the chips; Trending Topics also states the article was co-produced with AI.\"\n          ],\n          \"topics\": [\"open-weights\", \"compute\", \"labor\", \"deployment\"],\n          \"impact\": \"mixed\",\n          \"flags\": [\"company-claim\", \"single-source\"]\n        }\n      ]\n    }\n  ]\n}",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
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{
  "command": "date -d 2026-11-03 +%A",
  "description": "Check weekday"
}

{
  "stdout": "Tuesday",
  "stderr": "",
  "interrupted": false,
  "isImage": false,
  "noOutputExpected": false
}