{"version":"1.0","generated_at":"2026-10-11T11:14:11.366860","id":3345,"slug":"mit-openai-navier-stokes","title":"MIT 教授谈 OpenAI 模型解 Navier-Stokes 反例：人类读不懂的证明来了","summary":"MIT 工程教育副院长 Justin Solomon 在播客中表示，OpenAI 模型上个月给出了 Navier-Stokes 解失效的反例证明，但他和《Odd Lots》主持人无法读到第二页。","abstract":"MIT 教授谈 OpenAI 模型解 Navier-Stokes 反例：人类读不懂的证明来了 MIT 工程教育副院长 Justin Solomon 在播客中表示，OpenAI 模型上个月给出了 Navier-Stokes 解失效的反例证明，但他和《Odd Lots》主持人无法读到第二页。 MIT 工程教育副院长 Justin Solomon 在播客中表示，OpenAI 模型上个月给出了 Navier-Stokes 解失效的反例证明，但他和《Odd Lots》主持人无法读到第二页。 原贴提到：MIT 工程教育副院长 Justin Solomon 在播客中谈到，OpenAI 模型上个月给出 Navier-Stokes 解失效的反例证明， 来源：x.com MIT 工程教育副院长 Justin Solomon 在播客中谈到，OpenAI 模型上个月给出 Navier-Stokes 解失效的反例证明，但他和《Odd Lots》主持人读不到第二页。 这是什么信号 这不是一条普通的产品更新，而是一个来自数学与AI交叉地带的信号：一个前沿模型被指能生成针对Navier-Stokes解失效的反例证明，但人类专家在播客现场读不下去第二页。Justin Solomon的身份是MIT工程教育副院长，场景是播客，来源权威性来自专家转述，而不是论文或同行评审。 关键不是“AI又解了一道题”，而是“证明的可读性和可验证性”成为瓶颈。若连受过专业训练的数学教授都需要更长时间和更多工具才能读懂，说明AI输出的复杂度可能已经超过传统阅读式审稿的承载能力。 为什么重要 Navier-Stokes是数学与物理中的…","access_level":"public","access_label":"公开","access_mode":"full","is_preview":false,"canonical_url":"https://opc.beizhux.com/content/3345/mit-openai-navier-stokes","html_url":"https://opc.beizhux.com/content/3345/mit-openai-navier-stokes","json_url":"https://opc.beizhux.com/content/3345/mit-openai-navier-stokes.json","published_at":"2026-10-10T21:56:02","updated_at":"2026-10-11T10:25:17","category":{"slug":"hotspots","name":"全球热点解读"},"source":{"site":"x.com","author":"X：Saito 硬地骇客 (@SaitoWu)","url":"https://x.com/SaitoWu/status/2108919486581796872"},"tags":["AI 数学证明","AI可解释性","Justin 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