近期，OpenAI对外公布其内部研发的AI模型在破解数学界知名的"纳维-斯托克斯存在性与光滑性难题"方面取得成功，此消息一经传出便引发各界的高度关注与激烈讨论。该难题是克莱数学研究所于2000年提出的七大"千禧年大奖难题"之一，多年来一直是全球数学家难以攻克的学术高地。
根据OpenAI披露的信息，研究团队通过调度约10,000个AI智能体协同工作，仅用88小时便完成了整个证明流程。证明结论显示，在有限时间范围内，处于初始平滑且静止状态的流体有可能演化出"奇点"，也就是流速呈现无限增长趋势的现象。为保障研究结论的可靠性，OpenAI采用Lean编程语言实施了形式化验证，此项验证任务由其最新推出的GPT-6Astra模型在17小时内执行完毕。
然而，该声明很快陷入争议漩涡。纽约大学数学教授特里斯坦·巴克马斯特与Anthropic研究员莱文特·阿尔珀格联合指出，其团队在OpenAI公布的前一天刚刚发表了关于相关流体方程的研究论文。巴克马斯特对OpenAI提出质疑，认为对方可能在获知其研究动态后调整了技术路线，改用"外力驱动"方法进行攻关，同时他还提及存储于OpenAICodex模型中的研究数据或许已被用于模型训练或作为参考依据。
面对上述质疑，OpenAI研究员塞巴斯蒂安·布贝克态度坚决地否认了研究人员或AI智能体曾获取具体用户数据，但公司在官方声明中坦承，所使用的匿名化数据可能在一定程度上间接促进了模型性能的提升。这一事件同时引发了对AI技术发展边界的深入反思。知名数学家陶哲轩发出警示，倘若AI能够独立解决最为复杂的数学难题，恐怕将削弱人类对数学本质的深层认知与理解。
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Recently, OpenAI made headlines by announcing that its internal AI model had successfully cracked the "Navier-Stokes Existence and Smoothness Problem," a renowned challenge in the mathematical world. This news quickly sparked widespread attention and heated debate. The problem is one of the seven "Millennium Prize Problems" posed by the Clay Mathematics Institute in 2000, which have long been considered academic heights difficult for global mathematicians to conquer.
According to OpenAI's disclosure, the research team orchestrated approximately 10,000 AI agents to collaborate, completing the entire proof process within 88 hours. The proof concludes that within a finite time frame, a fluid initially in a smooth and static state can evolve to a "singularity," where the flow velocity exhibits an infinite growth trend. To ensure the reliability of the research, OpenAI employed the Lean programming language for formal verification, a task performed by its newly launched GPT-6Astra model over a 17-hour period.
However, the announcement was soon mired in controversy. Tristan Buckmaster, a mathematics professor at New York University, and Levent Alpager, a researcher at Anthropic, jointly pointed out that their team had just published a paper on the relevant fluid equations the day before OpenAI's announcement. Buckmaster questioned OpenAI, suggesting that the company may have shifted its technical approach to use "external force driving" after becoming aware of his research progress, and also mentioned that data stored in the OpenAI Codex model might have been used for training or as a reference.
In response to these accusations, OpenAI researcher Sebastian Bubeck firmly denied that the researchers or AI agents accessed specific user data. However, the company acknowledged in an official statement that the anonymized data used likely indirectly contributed to the model's performance improvement. This event simultaneously prompted deep reflection on the boundaries of AI technology development. Renowned mathematician Terence Tao issued a warning that if AI could independently solve the most complex mathematical problems, it would likely diminish humanity's profound cognition and understanding of the essence of mathematics.
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