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- Mathematicians say OpenAI's Navier-Stokes proof took a different route than claimed
On September 8, 2026, OpenAI said its internal AI system produced a 166-page Navier-Stokes proof in about 88 hours using roughly 10,000 agents, published a Lean formalization, and attributed the approach to Spanish mathematicians Diego Córdoba and Luis Martínez-Zoroa. Several expert groups told Scientific American that the details instead show a different method, with EPFL mathematician Gonzalo Cao-Labora saying the similarities are only surface-level. OpenAI researcher Noam Brown estimates the multi-agent setup contributed under 10% of the success; NYU mathematician Tristan Buckmaster has accused OpenAI of building on work he did with Anthropic's Levent Alpöge, which OpenAI denies, and the Clay Mathematics Institute has been reviewing the proof.
36氪 人工智能 · 🔥 3 - MIT professor says OpenAI's math proofs are beyond human reading
According to a 36Kr repost of a New Zhiyuan article, OpenAI published 722 math papers at once, said to include a counterexample showing failure of solutions to the Navier-Stokes equations and other claimed results on well-known open problems; the report also notes the papers still await verification. On Bloomberg's Odd Lots podcast, MIT associate dean of engineering education Justin Solomon said the proof is dense with technical detail, counterintuitive inequalities and extreme bounds, and that he stalled after two pages, able only to say it is "probably right." Fields Medalist Terence Tao, in a Caltech "Math 2.0" talk, offered a thought experiment about an AI-designed cancer therapy that passes formal verification and trials but whose mechanism no human understands, raising questions of interpretability and alignment.
36氪 人工智能 · 🔥 0 - OpenAI posts 722 AI-written math preprints, drawing math community backlash
On Oct 6 (US Eastern time), OpenAI published 722 math research manuscripts on GitHub written by an unreleased internal model, grouped into 372 result categories across 17 fields, with 162 carrying Lean formalizations of their main results; the company said each successful result cost roughly the equivalent of ChatGPT Pro thinking for three hours, and listed targets such as the four-dimensional Kakeya conjecture, the Unique Games conjecture and Mahler's conjecture. The release drew heavy skepticism, coming after OpenAI's Sept 8 claim to have solved the Navier–Stokes Millennium Prize problem; a Milan-Bicocca researcher says a recent paper finds at least two inconsistencies between the paper and its Lean code, making the formalized result weaker. OpenAI has released only average compute times, not the model, prompts or full computation traces, and has withdrawn 3 manuscripts and revised 14 after finding a symbol error, leaving 719 listed.
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