Daily edition · 30 items · covers 13 Sep 11:16 → 14 Sep 11:00 UTC · how this edition was made
Monday, 14 September 2026
Military 17%Policy 17%Frontier 13%Research 13%Compute 13%Health 10%Deployment 10%Security 7%
0:00 / 15:58
The argument over slowing AI down stopped being an essay and became politics and prices. Satya Nadella said Microsoft welcomes "deliberate pacing" and will publish a Code of Conduct for its first-party MAI models. Dario Amodei told CBS News' "Sunday Morning" that "for too long the industry lied to people about the fact that this technology had risks". David Sacks told Anthropic and OpenAI to pace themselves but to "stop pretending antitrust law has to be suspended so you can form a cartel".
Beijing rejected the part of Amodei's essay aimed at it. Foreign ministry spokesperson Guo Jiakun said "fearmongering, confrontation and vicious competition will only disrupt the process of global AI governance"; Global Times called the essay a "Cold War playbook"; state security minister Chen Yixin called AI "a new arena for strategic rivalry among major powers". Xi Jinping pledged a BRICS AI open-source community. In Washington, Speaker Mike Johnson ruled out an emergency session — "we will lose the race to China" — and President Trump said "whoever wins AI wins".
Markets took the slowdown talk literally. SoftBank fell 10.7% in Tokyo; the Kospi lost 3.3% to 6,684.37; Nasdaq 100 e-minis were down 505.5 points, or 1.72%, in US premarket trade. Anthropic has picked the Nasdaq for a listing that could seek a $2 trillion valuation. In research, a 51-author audit found 238 of 250 failed physics-benchmark answers were benchmark or grader errors, not model errors, and a 2,396-patient Nature Medicine study raised physicians' lung-cancer sensitivity from 0.72 to 0.87.
Frontier models & labs
Amodei tells CBS the industry "lied" about AI risks, calls China the toughest dilemma for pacing Update
- In a CBS News "Sunday Morning" interview aired on 13 September, Anthropic chief executive Dario Amodei said: "And I think for too long the industry lied to people about the fact that this technology had risks." He said the pace of progress "doesn't mean we need to panic today. It doesn't mean we need to shut it all down" but is "a warning sign that we need to slow down".
- CNBC reports Amodei told the programme that adversarial nations, namely China, not doing the same is "the toughest dilemma": "The more long-term thing would be working together to put a speed limit on the rate of of AI progress. I think that's going to be very difficult because the incentives to pull ahead and the military advantage that you get from that are so large. And honestly, I don't know if it's possible, but we should we should try."
- CNBC notes President Trump is scheduled to meet Xi Jinping at the White House on 24 September, with AI expected to be discussed.
- This updates the pacing essay covered in earlier editions; the broadcast interview and its China framing are the new facts. No evaluation data was published alongside the interview, and Anthropic has still not said what capability threshold would trigger pacing.
Nadella backs "deliberate pacing" and says Microsoft will publish a Code of Conduct for its MAI models Company claimUpdate
- In a post on 13 September, Microsoft chairman and chief executive Satya Nadella wrote: "Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing."
- Responding to Amodei's essay, Nadella wrote: "we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like 'embedded evaluators' and the broader efforts to develop the mechanisms to make this more than just talk." He added that this "cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia."
- He said Microsoft would publish "the 'Code of Conduct' that underlies our own first party MAI models that we'll publish tomorrow for public consultation". Unite.AI, reporting the post on 13 September, says the document was due on 14 September and describes the MAI family as seven in-house models introduced in June 2026.
- This is a statement of intent by a company. The Code of Conduct had not been published by the close of this window, so nothing in it can be assessed, and Microsoft has not said whether pacing would change anything about its release schedule.
The Information: Google, Anthropic and OpenAI have met regularly since July about an industry AI standards body Single sourceUpdate
- PYMNTS, citing a report published by The Information on 13 September, says representatives from Google, Anthropic and OpenAI "have been regularly meeting since July about the proposal for a standards body" covering testing and auditing of frontier models.
- According to PYMNTS, OpenAI chief executive Sam Altman has voiced support at a company town hall for "a testing and auditing organization for the industry" but believes the major labs should set standards without the backing of the US government, while Amodei's framework allows for voluntary corporate standards alongside government regulation.
- PYMNTS says the discussions follow an essay published by Demis Hassabis in July 2026 proposing a self-regulatory body modelled on the Financial Industry Regulatory Authority.
- The Information's article is paywalled and was not read directly; these facts come from PYMNTS' account of it. Nothing has been finalised, no body has been chartered or named, and none of the three companies has published terms.
Cohere CEO Aidan Gomez calls safety rules written by the largest labs "a cartel by any other name" Single source
- In a post dated 13 September, Cohere co-founder and chief executive Aidan Gomez asks: "Should a handful of select, market-dominant AI companies from Silicon Valley get to define the rules and safety standards of a generational technology for the entire world?" His verdict on AI companies setting industry rules together: "A wolf in sheep's clothing, a cartel by any other name."
- Gomez sets out four alternatives: an evidence-based risk framework developed internationally and in the open; mandatory transparency about how systems are built and their capabilities, risks and mitigations, with serious-incident reporting; independent testing scoped to genuinely dangerous capabilities such as cyberattacks, fraud, bioweapons and threats to critical infrastructure, applied by capability and deployment context rather than company size; and layered assurance modelled on aviation and finance.
- He also writes that "critical infrastructure cannot be secured by renting national capability from a foreign monopoly behind a closed interface".
- This is a competitor's argument published on its own blog, and that blog is the only source for it. The post names no specific company or proposal it is responding to, and Cohere is not party to the standards-body discussions reported by The Information.
Research & papers
Expert re-grading finds 238 of 250 failed physics-benchmark answers were benchmark or grader errors, not model errors mixedPreprint
- "How Good Are Frontier Models at Physics? Expert Re-Grading Reveals Broken Evaluations and Near-Saturation of Leading Benchmarks" (arXiv 2609.13009, submitted 11 September, announced in the 14 September listing) has 51 authors; the HTML version lists Yale University and Jump Trading Group among the affiliations. Physics faculty and their graduate researchers audited text-only, closed-ended questions in their own subfields across six benchmarks.
- The audit covered 502 questions. Of the 250 rejected answers sent for review, 143 (57.20%) were classified as benchmark errors — a defective problem statement or reference solution — 95 (38.00%) as grader errors and 12 (4.80%) as genuine model errors; 238 of the 250, or 95.20%, were benchmark or grader errors.
- The abstract reports GPT-5.6-Sol's measured mean@4 rising from 47.3% to 78.7% on HLE-Physics and from 61.0% to 87.2% on CMT-Benchmark, with corrected pass@4 reaching 94.4% on the 54 retained CritPt challenges. The authors write that "current benchmarks substantially understate frontier models' ability to solve well-posed physics problems".
- This is a preprint and has not been peer reviewed. Corrected scores are computed on retained subsets after flawed questions were repaired or excluded, so they are not like-for-like with the original figures, and the audit covers only text-only closed-ended questions with verifiable answers.
Amazon study: 57.5% of agent conversations rated satisfied by a blind panel had failed the customer's task mixedPreprint
- "GAUGE: When Not to Trust LLM-as-a-Judge in User-Simulated Evaluation of Task-Oriented Agents" (arXiv 2609.12191, submitted 10 September, announced 14 September) is by Umesh Bodhwani, Thanh Tran and Kai Wei; the paper's title page lists Amazon. It measures 25 agents from six providers on the τ²-bench and SimulatorArena benchmarks against a grounded verifiable reward.
- The abstract reports a "satisfaction-success gap": "conversations rated satisfied by our blind panel are decorrelated from actual success, with 57.5% of them failing the customer's task, a pattern consistent across five rater populations, both benchmarks, and every subjective dimension we rated".
- The authors also report that the judge's ranking holds across a broad capability span but "loses resolution among the near-equal strong agents: this decision-disagreement rate jumps from <1% on wide-reward pairs to 31% on close pairs". They propose a judge-free completion bit as a zero-cost tripwire for truncation regressions.
- Preprint, not peer reviewed. The measurement uses LLM user-simulators rather than real customers, and the paper does not claim a figure for how often deployed agents leave real people believing a task was done when it was not.
Microsoft study: bash-only agents beat typed tools by 21.8 to 24.5 points on TheAgentCompany mixedPreprint
- "Is Bash All You Need? An Empirical Study of Tool Interfaces for Enterprise Digital Worker Agents" (arXiv 2609.11999, submitted 10 September, announced 14 September) compares five tool interfaces on TheAgentCompany and APEX-Agents using Opus-4.8 and GPT-5.5. The corresponding author's address is at Microsoft.
- The abstract reports: "Bash alone outperforms typed tools on both benchmarks, improving score by 21.8-24.5 pp on TheAgentCompany and 4.8-7.4 pp on APEX-Agents while using 19-72% fewer total tokens."
- Adding typed tools or persistent agent-synthesized tools on top of bash "produces no detectable pooled score gain", and programmatic tool calling — which restricts actions to a fixed typed catalog — "generally underperforms bash alone in both quality and cost efficiency".
- Preprint, not peer reviewed. The authors' own recommendation is conditional: bash alone "when arbitrary execution can be isolated", and programmatic tool calling where security or compliance policy requires a fixed catalog — the trade-off the headline number does not price.
Reproduction finds subliminal learning holds in open-weight models but transmission varies by trait and task mixedPreprint
- "Reproducing and Evaluating the Generalizability of Subliminal Learning in Open-Weight Models" (arXiv 2609.12586, submitted 11 September, announced 14 September) is by Daan van der Weijden, Nathan Brack and Selene Báez Santamaría; the HTML version lists University of Zurich addresses.
- The paper reproduces the original subliminal-learning experiments — in which a teacher model transmits behavioural preferences through semantically unrelated data — across two trait types, animal preferences and misalignment, and three modalities: number sequences, code and chain of thought. It then extends them with new preference categories, a chess move-generation task and the open-weight model Ministral8B.
- The abstract states: "Our reproduction supports the original paper's claims, but our extensions show they are not universal as transmission strength varies across traits and tasks, and one model shows almost no effect at all."
- Preprint, not peer reviewed. The authors say they used open-weight models because "the original paper's GPT-4.x fine-tuning is no longer available", so the reproduction does not re-test the closed models the original result was reported on.
Security, misuse & threat intelligence
FBI and Google analysts say AI bug-hunting is stripping the obscurity that protected legacy and industrial code harmfulSingle source
- Brett Leatherman, assistant director of the FBI's Cyber Division, told The Register in a piece published on 13 September: "You see open source platforms that have been visible to the tech community for a decade, these libraries that are run in 80 percent of web servers out there, people have stress-tested those for 10 years, and the community believed that they were really secure. The latest models were able to break those and say, 'yeah, there's significant vulnerabilities in here.'"
- John Hultquist, chief analyst at Google Threat Intelligence Group, told the publication that AI "is excellent at technical troubleshooting, at knowing obscure systems and helping you make your way through it, and this makes me very concerned about industrial control systems", adding that it also helps attackers work down through the operating system "and even down into the firmware".
- The piece notes that five US agencies said attackers used AI-generated exploitation scripts to break into internet-exposed Siemens S7 Series programmable logic controllers at water, manufacturing, energy and other critical facilities, warning: "This is not a theoretical risk – it is an active threat." Trend Micro Zero Day Initiative's Dustin Childs is quoted the day after a Microsoft Patch Tuesday that addressed 974 CVEs.
- Only one outlet carries these interviews. The officials describe a direction of travel, not a measured rate: none gives a count of AI-discovered vulnerabilities, and the 80 percent figure is Leatherman's characterisation of how widely the libraries are deployed, not a count of compromised servers.
K-Bench: unlearned models still leak the secret on 22 to 86% of queries once deployed as agents harmfulPreprint
- "K-Bench: A Benchmark for LLM Unlearning in Agentic Deployments" (arXiv 2609.12808, submitted 11 September, announced 14 September) is by authors at the University of Technology Sydney and CSIRO. It inspects all six channels a ReAct agent exposes — chain of thought, tool calls, tool observations, retrieval, the answer and an elicited summary — and counts a query as leaked if the secret appears in any of them.
- The abstract states: "When the secret lives in the prompt or the retrieval store, TOFU and MUSE report no leakage, while the deployed agent still leaks it on 22--86% of queries." On structured retrieval, "the secret stays verbatim in the tool-observation channel and the aggregate leak rate is unchanged".
- Where the secret is in the weights, the authors report that "none of the twenty evaluated published methods demonstrably removes it, and only an input-corruption intervention reaches selective forgetting under the evaluated observer".
- Preprint, not peer reviewed. The measurement is against the authors' own observer and benchmark rather than a live deployment, and they note the top-ranked unlearning method changes across base models, so no method is established as correct.
Military, defense & geopolitics
NSA restructures into five mission centers, one of them dedicated to artificial intelligence
- The Washington Post reported on 13 September that NSA director Army Gen. Joshua M. Rudd is creating five new organisations at Fort Meade — artificial intelligence, China, cybersecurity, combat support and warfighting, and global intelligence — each led by a newly elevated "mission director" holding the effective authorities of an NSA deputy director, with candidates possibly drawn from outside the agency.
- The Post says the new mission directors must submit their organisational redesigns by the end of September, with rollout expected in mid-October and full operating capacity targeted for mid-January. It describes an agency of more than 30,000 military and civilian staff, and says the reconstituted Tailored Access Operations hacking unit will sit under the global-intelligence mission director and is set for a significant budget increase in the fiscal year beginning 1 October.
- The Post reports the agency "has been keenly interested in working with commercial AI labs, even circumventing a Pentagon ban against Anthropic to employ the firm's advanced Mythos model", and that NSA has rolled out a desktop AI tool called "Ask Mary". The Record, reporting the same day with its own sources, says Rudd started a 30-day implementation clock and that some mission-center chiefs, including the head of AI, could be announced internally as soon as Monday.
- The Washington Post is the originating report and The Record confirmed it with separate sources; both say NSA did not respond to requests for comment. No named officials are on the record, the AI mission center's remit is not described, and no budget figure is attached to it.
Beijing's foreign and commerce ministries and Global Times reject Amodei's call to keep curbing China's AI Update
- At a regular briefing in Beijing on Monday 14 September, foreign ministry spokesperson Guo Jiakun said: "Fearmongering, confrontation and vicious competition will only disrupt the process of global AI governance which serves no one's interest." The AP reports the commerce ministry separately dismissed US allegations as groundless, said distillation is commonly used by many AI companies, and accused the US of pursuing a "monopoly of the AI industry".
- The AP reports the response follows Amodei's essay, which warned that a "Chinese lead in AI would pose grave danger for the United States and the world" and called for continuing restrictions on sales of cutting-edge AI chips and chipmaking equipment to China.
- Reuters reports the state-backed Global Times said the essay's true objective was "to attempt to curb China's AI development through technological barriers and regulatory monopolies", and that "this 'silent AI Cold War' is hypocritical and short-sighted", warning that excluding China would "significantly increase the trial-and-error costs and risks of loss of control in global AI development".
- This is an update: the essay and its chip and distillation proposals were covered in earlier editions, and the Chinese government reaction is the new element. Neither wire reports any change in Chinese policy, and the AP places the exchange ahead of the Trump-Xi meeting on 24 September.
China's state security minister calls AI "a new arena for strategic rivalry among major powers"
- The South China Morning Post, publishing at 8:00am on 14 September, reports that China's state security minister Chen Yixin wrote that AI has become "a new arena for strategic rivalry among major powers", and warned of risks to state data, business secrets and personal privacy.
- Semafor, publishing at 6:49am EDT on 14 September, describes the piece as a weekend essay by the minister of state security listing six principal AI risks, among them threats to political regime security, digital infrastructure, public order and national defence.
- The SCMP reports Chen called for robust risk-prevention frameworks, stronger global governance of AI and a "fair and open international AI rules system". Semafor reports that Global Times characterised Amodei's essay as coming "out of the 'Cold War playbook'".
- Neither report reproduces the full essay and the SCMP article is partly paywalled; the six-risk breakdown here is Semafor's characterisation rather than a translated list. No new Chinese regulation was announced alongside the essay.
Xi tells the BRICS summit China will create a BRICS AI open-source community and a digital ecosystem cloud platform
- In a statement released on Sunday 13 September by China's Ministry of Foreign Affairs and reported by CNBC, President Xi Jinping said at the BRICS summit in New Delhi that China "will pioneer the establishment of a BRICS AI open-source community, support the cooperation in developing and applying large language models, hold AI seminars and training courses, and build an open AI ecosystem".
- CNBC reports Xi also said China will work to establish a BRICS digital ecosystem cloud platform and conduct digital skills training, technological exchange and industrial alignment, and proposed a BRICS engineer cultivation alliance and a youth exchange programme for scientific and technological innovation. In separate reporting CNBC says Xi called for a "consensus-based global AI governance framework".
- BRICS was established in 2009 and now comprises 11 nations including China, India, Russia, Iran and the United Arab Emirates, CNBC notes.
- CNBC says Xi did not address the ongoing AI safety debate. No funding figure, timetable or governing structure was announced for the open-source community or the cloud platform, so this is a commitment rather than a launch.
Lockheed Skunk Works to build four more Vectis combat drone prototypes, aiming at the CCA price point Company claim
- At the Air & Space Forces Association's Air, Space & Cyber Conference on 14 September, Skunk Works vice president and general manager Ron Fehlen said Lockheed Martin is "moving forward with a plan to build an additional four vehicles, bringing a total of five to include the original prototype", and that the company remains on track to fly the first Vectis by the end of 2027.
- Breaking Defense reports Lockheed released new specifications: the tailless aircraft is about 34 feet long with a wingspan of about 38 feet. Fehlen said Vectis is aimed at "the CCA competitive price"; Breaking Defense notes the Air Force set a $20 million per-aircraft cost target for Collaborative Combat Aircraft Increment 1, won this year by General Atomics and Anduril.
- Fehlen said a technique Lockheed calls "minimal tooling determinate assembly" has produced "in many cases an 80 percent reduction in labor hours to build up the aircraft itself".
- Every figure here is Lockheed's own and none is independently verified. Defense One reports the company declined to disclose the size of its investment, the customer, the weapons loadout, the propulsion system or an estimated per-aircraft cost, and no Vectis has flown.
Health, science & medicine
Nature Medicine: AI support raised physicians' lung-cancer disease-control sensitivity from 0.72 to 0.87 in a 2,396-patient study beneficial
- "Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC", published in Nature Medicine on 13 September, reports on I³LUNG (NCT05537922), which enrolled 2,396 patients with stage IIIC–IVB non-small cell lung cancer treated with immunotherapy between September 2012 and October 2023 across six centres in Italy, Greece, Germany, Spain, the USA and Israel.
- In the usability study, 20 physicians — 10 lung expert oncologists and 10 non-experts — each assessed 10 real-world cases, totalling 200 assessments. With the explainable-AI tool, sensitivity for disease control rate rose from 0.72 (95% CI 0.64–0.80) to 0.87 (95% CI 0.79–0.92), P = 0.0011, and accuracy from 0.57 to 0.65, P = 0.0431, "at the expense of slightly lower specificity". Agreement between experts and non-experts rose from κ = 0.11 to κ = 0.48.
- Clinical-and-blood-only models "achieved consistent performance across outcomes with area under the curve (AUC) up to 0.77 in the test (TEST) set" and "significantly surpassed PD-L1" and other standard scores in that set. The authors say a prospective validation in more than 2,000 patients is under way.
- The paper is explicit about limits: performance fell in external validation to an "AUC range: 0.55–0.72", and the benefit of adding CT, pathology and genomics "remains uncertain, not translated in TEST and EXVAL". Physicians adopted correct AI suggestions 74.5% of the time, but experts followed incorrect ones more often than non-experts, 72.2% versus 63.6%.
Harvard-led team releases a fine-tuned physician-level judge and a 9,217-score benchmark for grading medical AI beneficialPreprint
- "Scaling Clinical Judgment to Evaluate Medical AI" (arXiv 2609.12822, submitted 11 September, announced 14 September) has 17 authors including Thomas A. Buckley, Adam Rodman and Arjun K. Manrai. It introduces PrecepTron, "an LLM fine-tuned for physician-level evaluation of open-ended responses", "trained using low-rank adaptation (LoRA) of a 32-billion-parameter model on a small number of physician examples".
- The authors release GRAND-ROUNDS, "a new large-scale physician-annotated benchmark of 9,217 scores by 11 physicians across seven studies", and say all code, data and labels are freely available.
- They report that frontier models used in typical "LLM-as-a-judge" setups "often disagree with physicians and with each other", and say they used PrecepTron to reproduce headline findings from five studies of LLMs for clinical care published in JAMA, Science and Nature Medicine "without new human grading".
- Preprint, not peer reviewed. Reproducing published findings is not the same as validating clinical safety, and the abstract gives no figure for PrecepTron's agreement with physicians outside the seven studies it was built from.
Oxford study: rubric scoring leaves clinically relevant medical hallucinations undetected, often leaving scores unchanged mixedPreprint
- "When Rubrics Fail: Hallucinations Reveal Blind Spots in Medical AI Evaluation" (arXiv 2609.12718, submitted 11 September, announced 14 September) has seven authors, all listed with University of Oxford affiliations in the HTML version. They build a taxonomy of medical hallucination types and a clinician-validated error-injection pipeline producing matched correct and error-injected responses.
- The abstract states: "Across HealthBench, HealthBench Professional, and LiveMedBench, our clinically relevant hallucinations are missed by rubrics, often leaving scores unchanged." Rubrics "are most effective when explicitly checking facts, and are less effective for additional or unexpected errors they do not anticipate".
- The authors report that a preliminary retrieval-based factuality check "recovers some of the rubric-blind errors", and conclude that "rubric scores alone are insufficient to establish clinical reliability".
- Preprint, not peer reviewed. The hallucinations are injected by the authors rather than produced by a model in clinical use, and the abstract gives no figure for the share of injected errors that rubrics miss.
Policy, regulation & law
Johnson rules out an emergency AI session and Trump dismisses the warnings as the House prepares to leave until November
- House Speaker Mike Johnson said on CNN's "State of the Union" on Sunday 13 September: "If Congress just races in and does some sort of emergency session to try to regulate AI, we will lose the race to China, that is a threat to every single American." He added: "We don't need everybody to panic right now, we need to handle this new technology like we have others in the past." CNBC reports Johnson is scheduled to send the House home after this week until after November's elections.
- Johnson called instead for a meeting between Washington and industry leaders: "I'd do it tomorrow. I think we need to go in a big room, close the door and sort this out."
- In brief remarks in Ireland on Sunday, according to a pool report cited by CNBC, President Trump said: "Well I say this, we're leading China on AI. We're the most sophisticated country in the world and frankly I want to keep it that way, because whoever wins AI wins. We can put guardrails, and we can do this and that, but I think you have a lot of negative forces that are bringing it up and they're bringing up things that won't happen." NPR reports he did not say what he meant by "negative forces"; CNN reports he later said AI's advance will bring "more good" than harm.
- No bill, hearing or vote was scheduled in the window. CNBC reports that a Senate bill being worked on by Majority Leader John Thune with Senators Amy Klobuchar and Ted Cruz "has not yet been introduced", and that an unnamed industry source expects legislation "in the coming week".
House Democrats demand Congress stay in session on AI; Jeffries calls a Tuesday caucus meeting Single source
- A group of Democrats led by Rep. Sam Liccardo wrote to Speaker Johnson on Friday, in a letter obtained by CNBC: "The House should return to Washington immediately and remain in session until Congress advances meaningful, bipartisan AI safeguards." The letter names proposals it says deserve consideration, including bills mandating transparency and evaluation of frontier models, "kill switch" requirements, and "a waiver of antitrust laws to allow the industry to work together on safety and security".
- House Democratic Leader Hakeem Jeffries said on ABC's "This Week" that Democrats would meet on Tuesday to discuss AI guardrails: "We should take decisive action now so that we can slow down, as the CEOs have recently acknowledged, slow down the pace of development in order to protect the American people and ensure that AI is proceeding safely."
- Sen. Ruben Gallego told CNN's "State of the Union": "Dr. Frankenstein is telling us the monster is escaping; help us stop this. The method that we're answering [with] is not meeting the moment." Pennsylvania Governor Josh Shapiro posted that the industry leaders' comments "should be heeded as a bright flashing red light telling the President and Congress they need to act now".
- CNBC is the only outlet cited here for the letter's text and the industry-source expectation. The House has introduced multiple proposals, including the FRONTIER Act led by Reps. Jay Obernolte and Lori Trahan, but CNBC reports the Senate has not coalesced around a bipartisan bill and none of the House proposals was scheduled for a vote.
Sacks tells OpenAI and Anthropic to pace themselves but refuses an antitrust waiver: "stop pretending" Single source
- In a post on 13 September, David Sacks wrote: "Dario has written that we need to 'pace the frontier,' and Sam has agreed. People may be surprised by my response: go ahead. You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence."
- He rejected the regulatory asks that accompany the proposal: "But stop pretending you need anyone else's permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic's investors and staff. Stop pretending you need those same evaluators to police competitors who aren't even at the frontier."
- Sacks argued the motive is partly commercial: "You face massive product-liability exposure if your products enable a truly damaging cyberattack… After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability." He closed: "The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system."
- The post is the only source for these remarks and Sacks offers no evidence for the claim about METR's independence; METR has not responded publicly within this window. He also writes that "China is very unlikely to join a global agreement" without citing a source.
UK Joint Committee on Human Rights calls for a dedicated AI bill and a statutory AI regulator Update
- In a report published on 14 September, Parliament's Joint Committee on Human Rights called for a new bill on AI to "address the scale and seriousness" of the threats it identifies, saying the current legal framework is "fragmented and difficult to navigate".
- The committee's chair, Labour MP Alex Sobel, said: "Nowhere in the world, including the UK, has a current legislative and regulatory approach to AI that is fit for purpose."
- IT Pro lists the recommendations: a single independent statutory AI oversight body able to set codes of practice, enforce transparency and impose sanctions; a distinction between low-risk and high-risk systems; outright bans on some uses including subliminal techniques and inappropriate biometric profiling; due diligence across the AI supply chain; and clarification of data protection law on automated decision-making. The report notes the AI Security Institute operates voluntarily, without statutory power to test or block a risky release.
- This is a select-committee recommendation, not law. The BBC reports Education Minister Georgia Gould pointed to existing government action on non-consensual deepfakes, cyber security legislation and the AI Security Institute; no dedicated AI bill has been introduced, and the government is not obliged to accept the recommendations.
Ramaphosa asks BRICS to set up an international mechanism for independent scientific evaluation of AI Single source
- In a statement delivered at the 18th BRICS Leaders' Summit in New Delhi and published on 13 September, President Cyril Ramaphosa said: "South Africa accordingly proposes that BRICS should establish an international mechanism for the independent scientific evaluation of AI."
- He listed the risks he wants evaluated: "Systems capable of advanced cyber operations, assistance in biological weapons development, autonomous action, manipulation, mass surveillance, disruption of employment and, ultimately, systems whose capabilities may become difficult for human beings to control."
- The statement pairs the proposal with meaningful human-control principles, mandatory reporting of serious incidents, progressively stronger safeguards as capability increases, and simultaneous investment in sovereign AI capacity for developing-economy countries, arguing that "such oversight is standard practice in other industries whose activities have a significant impact on human safety and well-being, such as aviation, pharmaceuticals, nuclear power and financial institutions".
- This is one government's proposal in a summit statement, and the primary text is the only source used here. No other BRICS member endorsed it in the window, and the summit's New Delhi Declaration — adopted on 12 September, before this window — does not establish such a mechanism.
Compute, chips & infrastructure
AI and chip stocks sell off in Asia and US premarket after lab CEOs call for slowing development mixed
- The Associated Press reports that on Monday 14 September SoftBank Group fell 10.7% in Tokyo, SK Hynix and Kioxia Holdings each fell 6.4%, Samsung Electronics fell 4.1%, TSMC fell 1.2% and Tokyo Electron fell 1%. South Korea's Kospi lost 3.3% to 6,684.37 and Japan's Nikkei 225 slid 0.8% to 63,492.99, while Hong Kong's Hang Seng rose 0.4% to 24,904.46.
- Reuters reports that in US premarket trade at 04:46 a.m. ET, Nasdaq 100 e-minis were down 505.5 points or 1.72%, S&P 500 e-minis down 53.25 points or 0.70% and Dow e-minis down 97 points or 0.18%. Nvidia fell more than 2%, Intel nearly 6%, Marvell Technology around 6% and AMD around 5%, while Meta and Amazon each fell more than 1%. ServiceNow rose 3%, and Adobe and Workday 2.5% each.
- The AP quotes Dan Baker of Morningstar saying the decline "probably reflects the possibility that AI development may be slowed by regulators to try to avoid the worst case outcomes".
- These are intraday and premarket moves, not closing prices, and the pacing debate was not the only thing moving markets: the AP reports Brent crude rose 2.8% to US$107.55 a barrel in the same session.
Samsung and SK hynix reject KEPCO's proposal to prepay five years of electricity bills for chip clusters mixedSingle source
- The Korea Herald, publishing at 09:51 on 14 September and citing industry sources, reports that state-run Korea Electric Power Corp. proposed Samsung Electronics prepay 20 trillion won ($14.8 billion) and SK hynix prepay 5 trillion won — roughly five years of electricity bills based on last year's payments — and that both companies rejected it after internal reviews.
- The prepayment would have helped expand power infrastructure for the semiconductor clusters under construction in Yongin, just south of Seoul, and in the southwestern Honam region.
- The paper reports KEPCO's total debt stood at 210.7 trillion won as of the end of June, with daily interest expenses of 11.5 billion won, and says the decision reflects concern about committing that much money upfront when it is uncertain whether the AI-driven semiconductor boom will continue.
- The report rests on unnamed industry sources relayed by Yonhap; neither company nor KEPCO is quoted, and the article does not say how the power infrastructure will be funded instead.
SoftBank seals an upsized $11.87bn two-year loan from about 20 banks for its OpenAI investment Single source
- Bloomberg reports that SoftBank Group secured an $11.87 billion loan to support its investment in OpenAI, up from an earlier target of $10 billion. The two-year facility was sealed last week and attracted commitments from around 20 banks, according to people familiar with the matter who asked not to be identified.
- The report says SoftBank stated last week that it would repay the balance of a $40 billion loan taken earlier this year to finance the OpenAI investment, paying down the $25.9 billion it owes on 15 September; that uncollateralised borrowing was due to mature in March next year.
- Bloomberg says SoftBank is slated to invest close to $65 billion in OpenAI by October and has already raised about $37 billion this year from offshore and domestic bond sales and loans, including this facility, alongside a $10 billion margin loan backed by its OpenAI stake and a potential bond sale of as much as $20 billion.
- The sources are unnamed and SoftBank has not published the facility's terms. Bloomberg notes the financing comes as executives voice the need to slow AI development, and flags concerns about growing credit risk in the sector.
Z.ai files in Hong Kong to raise about $5bn through a discounted placement and zero-coupon convertible bonds Single source
- TechNode Global, reporting a filing made to the Hong Kong stock exchange on 13 September, says Z.ai plans a share placement of HK$15.68 billion (about $1.98 billion) at HK$714 per share — a 9.96% discount to the 11 September close of HK$793 — representing about 4.5% of enlarged share capital and expected to close on 16 September.
- Alongside it the company plans convertible bonds with gross proceeds of $3.016 billion and principal of RMB20.14 billion, zero coupon, maturing in 2027, with an initial conversion price of HK$892.50 per share.
- Of the proceeds, 60% is earmarked for next-generation GLM models and training, inference and computing infrastructure, 15% for business expansion, strategic investments and potential acquisitions, and 25% for capital structure, working capital and general corporate purposes, with deployment expected by 30 June 2028.
- Both transactions remain conditional and had not closed; TechNode notes the placement may not proceed if its conditions are not met. Only this outlet's account of the filing was read for this item.
Deployment & impact
Anthropic picks the Nasdaq for a listing that could seek a $2 trillion valuation while its CEO urges a slowdown
- CNBC reported on 14 September: "Anthropic has picked the Nasdaq as the exchange for its potential IPO, CNBC confirmed after Business Insider first reported the selection." The company was valued at $965 billion earlier this year, confidentially filed its IPO prospectus in June, has been widely expected to list as soon as next month and "could seek a $2 trillion valuation in its IPO".
- CNBC reports Anthropic hit $65 billion in annualised revenue in July, about a sevenfold increase from the prior year. Matt Murphy, a partner at Menlo Ventures and an Anthropic investor, called the growth rate "off the charts" and said: "Don't see why growth would slow or any other reason to wait."
- Gil Luria, an equity analyst at D.A. Davidson, told CNBC: "I don't know that investors are necessarily going to see it as a negative. Unless the companies are genuine and say, 'OK, we're not going to IPO, we're not going to use any more compute, we're not going to train any more models.' That's not what they're saying." CNBC also cites a Pew Research Center report that more than half of Americans say they are more concerned than excited about the growing use of AI in daily life, up from 37% in 2021.
- Anthropic and OpenAI declined to comment. No filing date, price range or exchange confirmation has come from the company itself, and the $2 trillion figure is reported as what the company could seek, not a set target.
FT: Anthropic tells shareholders adjusted operating income will be positive for a second straight quarter Company claimSingle source
- Reuters, summarising a Financial Times report published on 13 September, says Anthropic told shareholders that "adjusted operating income will be positive for a second straight quarter", and that gross margins are above 80% before accounting for revenue shared with distribution partners, including Amazon, and the cost of training its models.
- CNBC, reporting the same FT story on 14 September, says the FT cited people familiar with the matter and that the profit refers to the current period.
- The figures are being shown to shareholders ahead of a listing the company has not yet dated, at the moment its own chief executive is arguing publicly that the industry should slow down.
- These are Anthropic's own numbers, relayed by unnamed people to the FT; Reuters says it could not independently verify the report and that Anthropic did not respond to a request for comment. The 80% margin figure excludes partner revenue share and model training costs, so it is not a gross margin on the ordinary definition.
NYU Abu Dhabi analysis: Reddit informational help-seeking did not decline after ChatGPT launched Preprint
- "Informational Help-Seeking on Reddit Did Not Decline After ChatGPT" (arXiv 2609.12447, submitted 11 September, announced 14 September) by Hazem Ibrahim and Yasir Zaki tracks monthly post counts in 26 Reddit informational communities against 90 size-comparable hobby communities over the same six calendar months before and after ChatGPT's launch, and repeats the analysis at 66 earlier dates as a placebo.
- The abstract states: "Our results rule out any decline in posting larger than 3.4%, far smaller than the 8% to 25% declines documented in prior work."
- The authors scored 274,411 posts and 223,775 comments with AI-text detectors and report that "AI-written posts rose only 2-3 percentage points more in informational communities than in hobby communities, short of the 5.1 points that would be needed to hide even the smallest decline previously reported for Reddit". They attribute earlier findings to community types already drifting apart before ChatGPT existed.
- Preprint, not peer reviewed. The study covers one platform over a six-month window around launch and relies on AI-text detectors whose false positives it cancels statistically rather than validates directly. The authors report their own largest estimate — an 18% fall in posts to low-stakes curiosity communities — matches that group's pre-existing trend.