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[This is a guest post by Sophie Huiberts , being an expanded version of a post on her own blog . This blog post was initially written in a different file format and converted using AI. — T.] When you prove a theorem, you are imparted a responsibility to the field of mathematics. At minimum you need to explain what you did, including which steps required new ideas and which steps are already well-known. More substanti
By Melissa Lee , Monash University In August, artificial intelligence company OpenAI announced ten advances in mathematics and computer science made with their as-yet unreleased model Astra. The discoveries cover a wide range of mathematical fields, including geometry, cryptography and coding theory. These ten are just the latest in a rapidly growing list of mathematical breakthroughs made by generative artificial in
Why is Anthropic running a biology lab? Anthropic is best known for Claude, the artificial intelligence chatbot that competes with OpenAI’s ChatGPT and Google’s Gemini. But the AI company now employs molecular biologists, studies DNA, and operates a laboratory where scientists conduct physical experiments. The San Francisco Bay Area facility is what researchers call a “wet lab”: a laboratory where scientists work dir
As AI agents’ ability to do science autonomously continues to improve, scientists are facing a once-unthinkable question: will I get scooped by a bot? At least twice in the past five weeks, researchers have said that they had been working for an extended period on a particular research question, only to learn that artificial-intelligence companies had either answered the question before them or announced results befo
A few days ago OpenAI released a paper generated by "an internal frontier model" of Navier-Stokes fame titled A Coulomb ground-state density without Kohn-Sham ensemble representation . The model considers a system with 2 nuclei and 3 electrons. It then spends 40 pages (seemingly) proving that for "sufficiently large" internuclear distance, restricted open-shell ensemble KS-DFT cannot describe the ground-state density
The Mathocalypse Last night my 9-year-old son was taunting my wife, complexity theorist Dana Moshkovitz, as follows: “mommy, I heard you got cooked! I heard that a robot solved the math problem you worked on for your whole career! OOF!” While my son was being a brat, he also wasn’t wrong. Whether you’re thrilled, depressed, angry, or whatever else about it, yesterday was surely one of the biggest days in mathematical
OpenAI’s massive new math drop: [This essay was written in extreme haste before a very long wifi-less flight; please forgive typos.] Part One: My take The real news here isn’t the result; it’s not what we were told. 1. AI once tried to be a science. Now we get stuff like the completely vague report from OpenAI below: “Same procedure”? “Using an unreleased model”? This would never pass peer review. We don’t know what
OpenAI releases 722 AI-generated mathematics papers as researchers weigh what comes next OpenAI has published hundreds of mathematical manuscripts produced by an unreleased AI model, opening a much bigger debate over how AI-generated research should be checked, understood and incorporated into mathematics OpenAI has released a collection of 722 mathematical manuscripts generated by an internal frontier AI model, cove
OpenAI has released 722 mathematics manuscripts produced by a single unreleased internal model, grouped into 372 results across 17 areas. According to the company, the model tried roughly 4,000 research problems, with each result consuming compute equal to about three hours of ChatGPT Pro thinking. Papers, source code and some Lean proofs were posted to GitHub, along with 10 model reasoning summaries. Headline claims
AI Models & Platforms OpenAI Releases 722 Math Manuscripts From an Unreleased AI Model Add Unite.AI to your preferred sources on Google In a research post published October 6, 2026, OpenAI said it is releasing a broad range of new mathematical results produced by an unreleased internal frontier model, publishing 722 manuscripts organized into 372 families in a public GitHub repository alongside Lean proof formalizati
The floodgates are open. Right on the heels of OpenAI’s new large language model producing the biggest math breakthrough in two decades, the company just released no less than 372 results from the same model. Each resolves or makes substantial progress on a major open question in mathematics or theoretical computer science, the company says. OpenAI revealed the results in a GitHub repository at 6 P.M. EDT. The deluge
Terence Tao used a SAIR talk to criticize AI model companies for accelerating mathematics without knowing what comes next, saying, "We must slow down." He described a normal proof lifecycle—proposing a solution, mechanical verification, exposition, peer review, and textbook incorporation—and said AI is racing through generation and Lean formalization while the later stages stall, creating "proof indigestion": proofs
On 13 September, leading luminaries and up-and-coming talents in mathematics and computer science congregated at the annual Heidelberg Laureate Forum in Germany for a week of discussion, networking, and—naturally—wurst. Having attended several of these events in the past, the mathematicians normally focus their chatter on which famed researchers are present, or what interesting problems they have been working on. But
Noam Brown, an OpenAI researcher and core author of o1, discussed his current focus, multi-agent systems, in a recent podcast. He said OpenAI previously used 10,000 agents over 88 hours and 130 billion tokens to solve a Millennium Prize mathematics problem. Brown was explicit that the result came from having a general, powerful model, and that he would not even attribute 10% of the credit to multi-agent methods, whic
[This is a guest post by Tapio Schneider . This blog post was initially written in a different file format and converted using AI. — T.] [This will be cross-posted on the CliMA blog .] The apparent proof of finite-time blow-up of the forced Navier-Stokes equation, announced by OpenAI on September 8, has brought into focus a debate about the role of AI in mathematics. The proof was produced with a system of some 10,00
Radical Numerics co-founder Eric Nguyen discusses genomic language models and biosecurity. He helped develop Evo and Evo 2; a separate Arc/Stanford team later used those models to generate and synthesize functional bacteriophage genomes. The interview distinguishes three sequence scales: an average human gene is about 60K, long genes can reach 2.3M, and the whole human genome is around 3B. Nguyen argues that models w
Two weeks ago OpenAI claimed a solution to one of the biggest open problems in math—the Navier-Stokes problem—an achievement worth a $1-million prize from the Clay Mathematics Institute. The proof ignited a powder keg of concern over artificial intelligence companies’ race to disrupt the subject. But with the dust still far from settled, a different controversy is emerging: Did OpenAI even solve the right Navier-Stok
AI Models & Platforms Insilico Medicine Releases Open Longevity AI Toolkit in Cell Study Add Unite.AI to your preferred sources on Google Insilico Medicine on September 17, 2026 announced the publication of a study in Cell introducing an openly released AI toolkit for aging biology: the LongevityBench benchmark, a family of five compact Longevity-LLMs, and the Longevity Claw agentic research platform. Publication in
OpenAI’s announcement that it used an artificial-intelligence model to solve a major puzzle in fluid dynamics — the Navier–Stokes problem — is likely to change how mathematics is done forever. The claim, made by the AI company in San Francisco, California, on 8 September, has also sparked controversy about whether OpenAI tools have learnt information from human mathematicians who were also racing to solve the problem
Understanding why people age — and how to slow that process down — is an obsession that has stretched across millennia, from mythic quests for immortality to modern science’s hunt for drugs that lengthen lifespan. Now, that quest has entered the AI era. A report1 published today in Cell unveils a bespoke artificial-intelligence system that aims to turbocharge longevity research. The system introduces large language m
On September 8, OpenAI said 10,000 of its agents, running for 88 hours, had produced a 166-page proof regarding the Navier-Stokes equations — which describe fluid movement and have remained an open question since 1934. It's one of the seven Millennium Prize Problems established by the Clay Mathematics Institute in 2000, each carrying a $1 million prize; only one has ever been awarded. OpenAI has said it won't be clai
A statement signed by 25 Fields medalists, posted by Terence Tao on September 11 under the title 《人工智能在数学中的严重错位》, argues that AI companies' focus on solving famous mathematical problems seriously diverges from the community's goals of conceptual understanding, method development, and knowledge transmission. Former OpenAI VP of post-training Liam Fedus responds that today's AI limits should not frame future possibilit
The report says the Chinese company DeepCybo released the physical foundation model PhysBrain 1.5 on September 9, 2026. It scored 72.5 on 28 public benchmarks, ranking first among participating open-source models, with 14 first-place and 10 second-place open-source results. Its score is within 1 point of GPT-6 Astra (73.3) and Gemini 3.6 Flash (73.0), and above Hy-Embodied-VLM-1.0 (66.0) by about 6.5 points and RynnB
[This is a guest post by Silvia De Toffoli and Eamon Duede . This blog post was initially written in a different file format and converted using AI. — T.] Silvia De Toffoli (University School for Advanced Studies IUSS Pavia) Eamon Duede (Princeton University and Purdue University) On September 8th, 2026, OpenAI announced that it had produced an AI-generated solution to the Navier–Stokes existence and smoothness probl
It was a week that left mathematicians reeling. Hot on the heels of a flurry of cases of artificial intelligence furthering the field, OpenAI declared a major scalp: its latest AI model had cracked a Millennium Prize Problem, a puzzle with a $1m reward that had defied human brains for decades. The achievement bore little resemblance to how mathematical problems normally fall. A near-trillion dollar private company ha
Epoch AI says FrontierMath Tier 4 is now "saturated": by its accounting, when attempts across different models and different time periods are accumulated, every Tier 4 problem has been correctly solved by an AI at least once. OpenAI reports a score of 97.6% for GPT-6 Astra, which solved the one problem that had never been cracked before. When Tier 4 launched on July 11, 2025, the top score on the board was only about
Twenty-five Fields Medalists, with Terence Tao and Deng Yu among the first signers, issued an urgent public statement arguing that the way AI companies are pursuing mathematics is now in "severe misalignment" with the goals of the mathematical community. The statement explicitly does not call for stopping AI or deny its achievements. It raises three concerns: AI is solving problems faster than the community can diges
The controversy over OpenAI's maths miracle ‘Historic’ mathematical breakthrough by the tech company has been overshadowed by data privacy concerns of human researchers This year has been one of “unthinkable” progress for maths, said The Wall Street Journal. But OpenAI’s proof of the Navier-Stokes problem – one of the seven esteemed Millennium Prize Problems accepted as maths’ “deepest and most difficult unresolved q
[This is a guest post by Anima Anandkumar . This blog post was initially written in a different file format and converted using AI. — T.] The last few days have been a flurry of activity. After months of sleepless nights and diving deep into different mathematical and computational tools to tackle the open problem of singularity in fluid dynamics, we were finally ready to send our work on Euler equations (without for
Today was a tough news cycle to launch anything; we ordinarily promise to cover any new decacorn fundraises so Cognition’s $48B round and Mistral’s $24B round would normally have made it; we love imagegen so GPT Image 2.5 would have been its own headline; we covered the Dreamer story closely so their relaunch as Meta’s Muse agent should have made it; but.. yknow… the bar is higher these days. The summaries below capt
Fields Medalist Jacob Tsimerman announced at the award ceremony that he will soon join OpenAI to conduct AI safety research. Author and source: The Washington Post Jacob Tsimerman, who just won the Fields Medal last month, announced at the award ceremony that he will soon join OpenAI to work on AI safety research. In early August, he convened around 40 mathematicians at OpenAI’s headquarters in San Francisco with res
According to Latent Space, since 2022, components of the AI pipeline have been shifting from human-made to model-made, each flip starting with a 'patient zero' at a frontier lab. This trend is characterized as simulation: slightly worse (10%), but 100x cheaper and 10,000x faster. Stage 1 (2022): Reward signal went synthetic with InstructGPT's reward model, followed by Constitutional AI and RLAIF, where AI critiques i
New Nvidia research highlights that for long-horizon tasks, the software harness—the tools, memory management, and rules around a model—matters more than the model itself. Using a custom harness with improved memory handling and a supervisor component, researchers achieved a 100% score on the interactive reasoning benchmark ARC-AGI-3 with Claude Opus 5, compared to 30% without the harness, which was still the best am
On this episode of Decoder, The Verge's London-based AI reporter Robert Hart discusses the impact of AI on the field of mathematics and the existential crisis many leading mathematicians are experiencing. OpenAI's recent release of solutions to longstanding math problems has caused a stir in the math community, sparking intense debate. While AI systems still struggle with elementary arithmetic, they are becoming incr
AINews reports on a new paper demonstrating how encrypted reasoning traces from frontier models can be decoded and replayed to other models, sessions, or users, leading to dramatic improvements in open models. Since the release of o1, reasoning models have obscured their traces with cryptographic signatures to prevent distillation, but this study shows that these encrypted blocks can be replayed to weaker models and
In this crosspost from AI Matters, a publication of ACM SIGAI, Ella Scallan interviews Akari Asai, winner of the 2025 AAAI Doctoral Dissertation Award. Asai's doctoral research focused on retrieval-augmented language models (LMs), arguing for moving beyond monolithic LMs to augmented LMs that are designed, trained, and deployed with complementary modules. She pioneered retrieval-augmented LMs, which retrieve relevant
How OpenAI Announced Its Next Frontier Model 'Astra' The US AI firm OpenAI, led by CEO Sam Altman, has announced its latest model, Astra. In a shocking introduction to the AI model, the company shared a selection of 10 results, each of which resolves or makes substantial progress on a long-standing open problem. The problems span high-dimensional geometry, coding theory, arithmetic circuit complexity, group theory, o
OpenAI says an internal version of its next major artificial intelligence model has produced new results on 10 longstanding problems in mathematics and theoretical computer science, highlighting the growing role of AI systems in advanced scientific research. The company said the results were generated by an internal version of Astra, described as its next major model. The issues had remained open with no progress on
OpenAI released ten results on long-standing problems together with human-prepared manuscripts and Lean certificates.
The author recounts attending a workshop on mathematics and AI, which produced the Leiden Declaration, now signed by over 3000 people. Although he did not sign, he clarifies it is not due to disagreement but rather uncertainty about some confident assertions and recommendations. He appreciates the declaration's role in focusing attention on pressing issues, and quotes its passage on characteristic values of mathemati
“The future of biology is programmable.” To give you a sense of how important this topic is, Patrick Hsu is the first guest we’ve had back to Ground Truths since the podcast began a few years ago. Nearly 2 years ago we spoke about digital biology but so much has happened since to help unravel the complexities in the language of life. Patrick is a co-founder and core investigator at the Arc Institute . His work is at
Large language models (LLMs) are increasingly used as synthetic survey respondents, but their individual answers may look plausible while failing to preserve the joint distribution, latent structure, reliability, mediation pathways, and demographic effects of real human data. This study introduces a Lithuanian organizational-psychology dataset (n=263 employees; 68 items, 12 subscales) and evaluates 37 LLMs from OpenA
LifeSciBench evaluates models on research tasks designed with life scientists rather than relying on generic knowledge questions.
Astrophysicist Chi-kwan Chan used Codex to derive, implement and test candidate algorithms for Event Horizon Telescope simulations.
Last week, OpenAI announced that an internal AI model had disproved the Erdős unit distance conjecture, a famous problem in discrete geometry that had stumped human mathematicians for the last 80 years. OpenAI gave several mathematicians early access to the result and published their reactions. Tim Gowers — who won the Fields Medal, the most prestigious prize in mathematics — wrote that “there is no doubt that the so
OpenAI scored a big result yesterday, with respect to an Erdos problem: Clearly impressive. But as with so much else, it should be viewed with skepticism. In an email to me this morning, Cal Newport made a number of good points that he said I could share, summarizing both what was found and some limitations: OpenAI used a new reasoning model (not yet released) to help identify a counterexample that disproved a conjec
OpenAI’s GPT can summarize research papers and make predictions—but can it do science? Can it generate hypotheses, design experiments, interpret results and iterate? Last summer researchers at OpenAI and Ginkgo Bioworks, a company that designs and installs autonomous, robot-run labs, decided to find out. Though artificial intelligence systems have posted high scores in math, physics and computer science, biology is h
"AI Has Overwhelmed Human Exam Questions," A Conversation Between Terence Tao and Mark Chen: Large Language Models Are No Longer "Math Underachievers" Recently, at a seminar hosted by the Institute for Pure and Applied Mathematics (IPAM), Fields Medalist Terence Tao and Mark Chen, the Chief Researcher at OpenAI, participated in a "fireside chat." The two discussed the leap - forward progress of AI in the past year an
Fourteen researchers report eleven case studies across mathematics, physics, astronomy, biology and materials, documenting both concrete advances and failure modes.