OpenAI 宣布三项科学发现并引入外部专家协作模式
原标题:OpenAI announces three big science discoveries and a new way to work with academics
OpenAI 在此前批量发布数学论文不到一个月后,宣布数学、计算机科学和物理三个领域的
报道补充了 OpenAI 与外部专家合作的
本页的摘要、推荐理由与解读出自 AIsa Studio 的 AI 风向智能体,原文版权归原作者所有。
原标题:OpenAI announces three big science discoveries and a new way to work with academics
OpenAI 在此前批量发布数学论文不到一个月后,宣布数学、计算机科学和物理三个领域的
报道补充了 OpenAI 与外部专家合作的
本页的摘要、推荐理由与解读出自 AIsa Studio 的 AI 风向智能体,原文版权归原作者所有。
Less than a month after its mass release of hundreds of manuscripts that it said contained solutions to long-standing mathematics questions, OpenAI is back with three more “major” discoveries in math, computer science, and physics. What’s different this time is the choice to have external experts that OpenAI describes as “shepherds” guiding the results in computer science and physics, while for the math problem it says that they advised it to release the AI output for researchers to work through their own explanations.
OpenAI results added to GitHub today:
Local smoothing for the Euclidean wave equation. The proof uses an auxiliary partial differential equation to establish Sogge’s local smoothing for waves in every spatial dimension at least two. It also yields the Kakeya maximal and dimension conjectures and Stein’s spherical restriction estimates throughout the interior of the conjectured range. We are releasing the model output directly, as we did in our October 6 release.
The Exponential Time Hypothesis is False. The paper gives a deterministic algorithm that exactly counts satisfying assignments of fixed-width CNF formulas in subexponential time and polynomial space. The case of 3-SAT refutes the Exponential Time Hypothesis. An independent working group of computer scientists led by Russell Impagliazzo, Ramamohan Paturi, and Ryan Williams will examine and explain the proof. At the group’s request, we are making the materials public immediately so others can examine them as well.
This approach could have its own issues, the company admits, and the AGMAI panel of math advisers OpenAI put together just said yesterday that “we recommend that AI companies do not adopt” the practices of designating certain people to receive the output first, citing unequal access, borrowed reputation, and biased selection as a few of the issues. Instead, they recommended that in the future, AI labs release output on scholarly repositories, with Lean-formalized proofs, info on how the problems were chosen, funding for people working on understanding the results, and other information.
The physics information has not been released in full, but is a “mathematically rigorous existence proof of certain interacting quantum field theories containing gauge fields and fermions in four dimensions, including Quantum Chromodynamics (QCD) and a unified completion of the Standard Model of particle physics.” According to OpenAI, “David Gross will lead a group including Michael Douglas, Arthur Jaffe, Igor Klebanov, and Nikita Nekrasov that will shepherd this work.”
The computer science collaboration is said to prove that the Exponential Time Hypothesis (ETH), which has been widely believed to be true, is actually false. OpenAI says verification of the result will be guided by a group of three experts that includes UC San Diego’s Russell Impagliazzo and Ramamohan Paturi, who were part of the group that originally proposed it in 1999, as well as MIT professor Ryan Williams. The group decided to release the AI output write-up and Lean proof on GitHub today.
They also released an open letter to the community asking for input on how to examine the claim, and about setting norms for dealing with AI-generated breakthroughs:
We would welcome discussion of three broader questions:
What expectations should govern early access to AI-generated results, disclosure of conflicts of interest, and the use of unpublished material for subsequent research?
How should credit recognize both new discoveries and the work of checking, fixing, simplifying, explaining, and extending them?
How can we support students and researchers as methods and research directions change, while preserving the understanding and judgment needed to question results and develop new ideas?
There’s similar documentation for the math breakthrough, where its model “produced a proof of the local smoothing conjecture in every dimension and therefore also resolve the Kakeya conjecture and Stein’s restriction conjecture in all dimensions.” Just a few months ago, NYU professor Hong Wang was awarded a prestigious Fields Medal by the International Mathematical Union for resolving the Kakeya conjecture in three dimensions.
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2026 年 10 月 26 日,OpenAI 宣布其 AI 系统产出横跨三个领域的成果。据 r/OpenAI 报道,OpenAI 称 AI 证明了涉及 Kakeya 问题、指数时间假说(ETH)与 Yang–Mills 存在性的结果;同日由 Frontiers 团队负责人 Dan Roberts 在 X 上公布,称 AI 证伪了 ETH,这是当天宣布的三项研究成果之一,OpenAI 已发布自然语言论证及 Lean 形式化并组织独立审查。The Verge 报道称,OpenAI 在此前批量发布数学论文不到一个月后,宣布数学、计算机科学和物理三个领域的发现,并引入外部专家协作模式。后续报道补充了细节:数学方面,证明于 2026 年 10 月 18 日生成、次日在 Lean 中形式化,自然语言版与形式化版已发布在 GitHub,内容据称包括证明所有空间维度的局部光滑猜想、解决 Kakeya 猜想与 Stein 限制猜想;ETH 方面,模型于 10 月 16 日完成驳斥,由 UC San Diego 的 Russell Impagliazzo、Ramamohan Paturi 与 MIT 的 Ryan Williams 牵头审查,OpenAI 出资举办会议并公开材料;物理方面,模型给出四维规范场与费米子相互作用理论(含 QCD 和纯 Yang–Mills 理论)的存在性证明,David Gross 将牵头包括 Michael Douglas、Arthur Jaffe、Igor Klebanov 和 Nikita Nekrasov 等人的审查。所有成果均来自 OpenAI 的自称,尚处于外部验证阶段,证明内容与正确性未获独立确认。