In an interview, Terence Tao evaluated the mathematical results released by OpenAI, saying that its proof related to the Navier–Stokes problem runs to 100 pages, and that colleagues who spent days studying it with the help of AI could only explain half of it, with it bringing almost no mathematical insight; he called this practice automated strip-mining. He mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined the no-AI research group, and argued that the mathematics community should build its own open models and research tools to retain the right to oversee and intervene in the AI research process. He also discussed the possibility that AI could exploit vulnerabilities in Lean to construct fake proofs and slip them through, arguing that current mathematical tools are insufficient to establish adequate guardrails.
In an interview, Terence Tao evaluated the mathematical results released by OpenAI, saying that its proof related to the Navier–Stokes problem runs to 100 pages, and that colleagues who spent days studying it with the help of AI could only explain half of it, with it bringing almost no mathematical insight; he called this practice automated strip-mining. He mentioned that the Human Mathematics Association already has 1,008 members, of whom 654 have joined the no-AI research group, and argued tha
Anthropic announced that it will expand the AI for Science program from supporting individual teams to 20 scientific foundations, research institutions, and research groups worldwide, providing Claude credits. The author believes that this forms two approaches in contrast with OpenAI's emphasis on models independently making scientific discoveries, and mentions that Anthropic is jointly developing standards for models operating hardware with HHMI Janelia, pointing toward AI Agents taking over laboratory instruments. The author also notes that Anthropic has not disclosed the scale of funding for the credits, and some frontier experiments are still in early preview stages.
s to 20 scientific foundations, research institutions, and research groups worldwide, providing Claude credits. The author believes that this forms two approaches in contrast with OpenAI's emphasis on models independently making scientific discoveries, and mentions that Anthropic is jointly developing standards for models operating hardware with HHMI Janelia, pointing toward AI Agents taking over laboratory instruments. The author also notes that Anthropic has not disclosed the scale of funding
Yuchen Jin commented that the focus of the OpenAI vs. Anthropic subscription competition is no longer on whose model is best, but on who offers more tokens per dollar. The Tibo post he cited announced that usage limits for all Pro 100/200/500 tiers and Business Premium are doubled, the usage limit for Pro 200 will no longer be reduced, and Work and Codex usage remain unchanged.
Karan Singhal, head of OpenAI's health division, said in an interview that more than 300 million people ask ChatGPT health-related questions every week, and that OpenAI chooses to incorporate medical data at each training stage of its general models rather than training a separate medical-specific model, to avoid the specialized model quickly falling behind frontier models. He mentioned that OpenAI is exploring a proactive personal health assistant covering before, during, and after consultations, and said users' health information will not be used for model training or ad targeting. OpenAI is also working with Penda Health to experiment with a clinician assistance system, and with medical information systems such as Epic to explore using ChatGPT directly within healthcare workers' existing work environments.
Karan Singhal, head of OpenAI's health division, said in an interview that more than 300 million people ask ChatGPT health-related questions every week, and that OpenAI chooses to incorporate medical data at each training stage of its general models rather than training a separate medical-specific model, to avoid the specialized model quickly falling behind frontier models. He mentioned that OpenAI is exploring a proactive personal health assistant covering before, during, and after consultation
Dan Shipper shared Rishabh Karnawat's interpretation of an OpenAI internal model's claim to have broken the Exponential Time Hypothesis (ETH), calling it an excellent explanation. According to the interpretation, the model found an algorithm for solving 3-SAT faster than ETH permits, and the proof was checked in Lean; Impagliazzo and Paturi, who proposed ETH, along with MIT's Ryan Williams, are leading a public review. If the refutation holds, many complexity conclusions that rest on ETH as a premise would lose their foundation, but the new algorithm's absolute speed is still slow, and it does not amount to solving P versus NP.
Dan Shipper shared Rishabh Karnawat's interpretation of an OpenAI internal model's claim to have broken the Exponential Time Hypothesis (ETH), calling it an excellent explanation. According to the interpretation, the model found an algorithm for solving 3-SAT faster than ETH permits, and the proof was checked in Lean; Impagliazzo and Paturi, who proposed ETH, along with MIT's Ryan Williams, are leading a public review. If the refutation holds, many complexity conclusions that rest on ETH as a pr
Vaibhav Srivastav, OpenAI's Head of Developer Experience and Community, said in an interview that GPT-6.1 Sol can achieve about 95% of the performance of GPT-6 Astra at only one-fifth the cost, and that he himself mainly uses Sol in his daily work. He recommends using Astra for adversarial review on new projects or unfamiliar problems, and said the Ultrafast tier targets real-time scenarios such as fraud detection and financial investigations, with speeds exceeding 300 tokens per second. He also described how the always-on agent OpenAI dots aggregates information from Slack, GitHub, Gmail, and calendars and handles PRs on users' behalf, as well as how Auto-review checks model actions against custom policies before they are taken.
Vaibhav Srivastav, OpenAI's Head of Developer Experience and Community, said in an interview that GPT-6.1 Sol can achieve about 95% of the performance of GPT-6 Astra at only one-fifth the cost, and that he himself mainly uses Sol in his daily work. He recommends using Astra for adversarial review on new projects or unfamiliar problems, and said the Ultrafast tier targets real-time scenarios such as fraud detection and financial investigations, with speeds exceeding 300 tokens per second. He also
Historian Niall Ferguson, researcher Lisa Klaassen, and former Google CEO Eric Schmidt wrote in Foreign Affairs, comparing OpenAI and Anthropic to colonial-era East India Companies, arguing that they negotiate with governments but remain constrained by them. The article cites the example of the U.S. Commerce Department in June requiring Anthropic to cut off foreign nationals' access to its two most powerful models; because Anthropic could not verify users' nationalities in real time, it took Fable 5 and Mythos 5 offline worldwide. About two weeks later, export controls on Fable 5 were lifted, while Mythos 5 remains available only to certain U.S. institutions. The authors also say U.S. tech companies plan to invest more than $600 billion in 2026, much of it debt-financed, while China plans to invest $295 billion over five years, and they propose an "imperial trilemma" in which defense, technological leadership, and the welfare state are difficult to achieve at the same time.
Historian Niall Ferguson, researcher Lisa Klaassen, and former Google CEO Eric Schmidt wrote in Foreign Affairs, comparing OpenAI and Anthropic to colonial-era East India Companies, arguing that they negotiate with governments but remain constrained by them. The article cites the example of the U.S. Commerce Department in June requiring Anthropic to cut off foreign nationals' access to its two most powerful models; because Anthropic could not verify users' nationalities in real time, it took Fab
OpenAI published 722 mathematics papers at once, covering number theory, geometry, and theoretical computer science, claiming progress on problems such as the Riemann Hypothesis, Catalan's constant, and the Kakeya conjecture, without peer review. Fields Medalist Hugo Duminil-Copin said 16 problems related to his research had been flattened by AI, and some doctoral students face their topics being covered and their degrees affected. The article also mentions an Anthropic researcher claiming to have disproved the Jacobian conjecture, and Shing-Tung Yau leading the establishment of a mathematics and artificial intelligence laboratory alliance.
OpenAI published 722 mathematics papers at once, covering number theory, geometry, and theoretical computer science, claiming progress on problems such as the Riemann Hypothesis, Catalan's constant, and the Kakeya conjecture, without peer review. Fields Medalist Hugo Duminil-Copin said 16 problems related to his research had been flattened by AI, and some doctoral students face their topics being covered and their degrees affected. The article also mentions an Anthropic researcher claiming to ha
gihyo.jp reviews multiple releases and reports from late October, organizing AI-era defense challenges along two lines: vulnerability remediation implementation and permission management. Anthropic Deputy CISO Jason D. Clinton says that within about 18 months, high cyber capability will spread to small, cheap models, but fixes still need to be applied to running systems. The article cites OpenAI's discovery of Brotli's CVE-2026-111497 during testing in an isolated environment, and introduces remediation and credential control solutions such as AWS Continuum, Google Agent Compute Engine, and 1Password for Agents, as well as Microsoft's report on Storm-0940 using AI to automate attacks.
opic Deputy CISO Jason D. Clinton says that within about 18 months, high cyber capability will spread to small, cheap models, but fixes still need to be applied to running systems. The article cites OpenAI's discovery of Brotli's CVE-2026-111497 during testing in an isolated environment, and introduces remediation and credential control solutions such as AWS Continuum, Google Agent Compute Engine, and 1Password for Agents, as well as Microsoft's report on Storm-0940 using AI to automate attacks.
OpenAI's FDE team was established in early 2025, with the goal of filling the deployment gap between model capabilities and customers' real-world constraints; the approach is to first get results into production, then consolidate customized solutions into reusable products. In the early days, every use case required extensive customized integration; after Codex became stronger, the team rebuilt the application on Codex, turning customized applications into plugins and skills based on Codex primitives, and self-reports that about 90% of the customized code for each project was removed. In a semiconductor customer case, about 15 FDEs covered 10+ use cases, self-reporting about 48% time savings in targeted test generation and about 22% median performance improvement in kernel optimization; in a telecom customer service voice case, the key evaluation rose from about 60% to 90%+ in about six months.
OpenAI's FDE team was established in early 2025, with the goal of filling the deployment gap between model capabilities and customers' real-world constraints; the approach is to first get results into production, then consolidate customized solutions into reusable products. In the early days, every use case required extensive customized integration; after Codex became stronger, the team rebuilt the application on Codex, turning customized applications into plugins and skills based on Codex primi
Anthropic disclosed to IPO investors third-quarter revenue of $16.8 billion, up 46% quarter-over-quarter, a marked slowdown from the over 100% growth in the first half; SemiAnalysis estimates its annualized revenue at about $74 billion. OpenAI's annualized revenue as of the end of September was close to $50 billion, about $20 billion less than the market expectation of $70 billion, with the gap mainly stemming from differences in revenue recognition methods. After the news was announced, chip stocks such as Nvidia, AMD, and Broadcom fell; on October 14, the A-share STAR 50 Index dropped 3.29%, and the market began to reassess the revenue growth and capital expenditure sustainability of the AI industry chain.
e of $16.8 billion, up 46% quarter-over-quarter, a marked slowdown from the over 100% growth in the first half; SemiAnalysis estimates its annualized revenue at about $74 billion. OpenAI's annualized revenue as of the end of September was close to $50 billion, about $20 billion less than the market expectation of $70 billion, with the gap mainly stemming from differences in revenue recognition methods. After the news was announced, chip stocks such as Nvidia, AMD, and Broadcom fell; on October 1