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OpenAI used its AI systems to help produce a formal proof related to the Navier-Stokes equations, but the model mistranslated parts of the mathematics into code during the formalization process.
A commentary discussing the mathematician backlash against OpenAI's released AI-generated mathematical proofs, arguing the real issue is not lack of human credit but the lack of comprehensibility — models only close proofs without conveying understanding needed to advance mathematics.
OpenAI 一次性发布了近 400 条 AI 生成的数学结果，涵盖 700 多篇手稿，令数学界既震惊又焦虑；但仅约 42% 的成果完成了 Lean 形式化验证，数学家们表示可能需要数年才能消化这批成果。
Thomas Hales writes a guest post for Terence Tao's blog explaining what mathematicians should know about the Lean theorem prover, covering formal proof reliability, the growth of the mathlib library, and how AI-driven autoformalization has become a practical reality in 2026.
Tristan Buckmaster, a mathematics professor at New York University, has publicly accused OpenAI of obtaining and copying their work while their research was nearing completion, rushing to publish a solution to the Navier-Stokes equations, and allegedly using user research data stored on OpenAI's servers. OpenAI denies that the relevant prompts influenced its system, but its claim of a 'one-shot' solution has been retracted.
A discussion post on Lobsters about "Two Futures for LLMs in Mathematics," exploring potential directions for how large language models will relate to mathematical research and practice.
OpenAI发布了700多篇由AI智能体生成的论文，声称在理论数学、计算机科学和物理领域解决了372个公开问题，其中包括关于黎曼假设的重大进展，尽管部分证明已被发现错误并撤回，专家仍称这些成果令人震惊。
Fields Medalist Hugo Duminil-Copin reacts to OpenAI's claimed resolution of 350 major mathematical problems, comparing the impact to being run over by trucks, as every research problem he used to cite in his talks and grant applications has reportedly been solved.
A collection of 100+ short reactions from mathematicians to OpenAI's October 6 announcement that its models solved over 100 open mathematical problems, ranging from astonishment at results like the Quasi-Riemann hypothesis to reflections on the future role of human mathematicians.
OpenProblemBench introduces a benchmark of 82 unresolved problems from mathematics and theoretical physics, evaluating AI models' ability to make progress on open scientific questions, with GPT-6-Astra achieving the highest mean solve rate of 14.0%.
Guest post on Terence Tao's blog by Álvaro Lozano-Robledo addressing students worried that LLM advances may upend mathematical research careers, urging them to keep studying math while examining whether AI will surpass human researchers and shrink academic math.
评论文章指出，AI 在数学领域造成的影响远比编程或设计等其他领域更为彻底和剧烈——数学问题非解即未解，没有模糊空间，这使得多年培养的数学家技能可能迅速贬值。
Mathematician Asaf Karagila critiques OpenAI's preprint claiming the Partition Principle does not imply the Axiom of Choice, arguing the paper is unclear, poorly structured, and would merit desk rejection for quality.
OpenAI released hundreds of AI-generated solutions to hard math problems, but they fall short of the Advisory Group on Mathematics and Artificial Intelligence's standards, with gaps in formalization, chain-of-thought disclosure, and human understanding, as highlighted by a Cambridge and King's College paper on discrepancies between natural language proofs and Lean code.
一篇科学美国人（Scientific American）的报道，讲述 OpenAI 的 AI 代理通过单一提示产出大量数学研究成果，令数学界震动。
继AI模型接连攻克长期悬而未决的数学难题之后，业内专家Scott Aaronson透露，各AI实验室正悄然测试其最新内部模型能否攻破主要密码学协议。
OpenAI 发布了一个包含由其未公开内部模型产出的 719 篇数学手稿（372 个结果族）的仓库，并附带部分 Lean 形式化证明与推理摘要，同时据标题消息撤回了其中 3 篇论文。
OpenAI 更新其数学仓库，新增 6 个 Lean 形式化证明、19 项修改，并撤回三项数学结果；仓库约 42% 的核心结果已完成形式化验证，且大部分成果由未发布的内部模型经大量思考计算生成。
评论文章探讨“Math 2.0”应如何更整体地评估数学研究进展，呼吁改变当前以论文为中心的评价体系。
The Association for Human Mathematics published a statement — reposted on Terence Tao's blog — condemning OpenAI's October 6 release of purported solutions to open math problems, accusing the company of ignoring the Advisory Group on Mathematics and AI's guidance, and urging mathematicians to stop working with OpenAI.