内容来源：https://www.theverge.com/ai-artificial-intelligence/991710/openai-navier-stokes-solution

内容总结：

据《纽约时报》和《连线》杂志报道，OpenAI近日宣布，其内部AI模型攻克了一道困扰数学界约90年的重大难题——纳维-斯托克斯问题。该问题关乎液体与气体的流动规律，属于七大“千禧年大奖难题”之一，每道题的破解者将获得100万美元奖金。OpenAI在5月20日的博客文章中表示，他们利用一个比最新发布的GPT-6 Astra更强大的内部AI模型，并调动了1万个并发智能体协同工作，最终得出了解决方案。

然而，这一里程碑式的突破迅速引发争议。就在OpenAI官宣的前一天，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·阿尔波格合作，发布了一项与纳维-斯托克斯问题相关的研究成果。巴克马斯特称，他在得知OpenAI获知他们的研究进展后主动联系了对方，却发现OpenAI已通过一条他们曾用OpenAI Codex和Anthropic Claude推进的路径，先行得出了纳维-斯托克斯方程的证明。

巴克马斯特在声明中质疑，OpenAI是否通过访问他们在Codex上的会话数据而接近了答案。他写道：“我询问模型是否基于或访问过我们在Codex中的会话记录——整个项目期间我们的所有草稿都存放于此。对方告知模型并未查阅用户数据。我再次追问训练数据相关问题时，未获正面回应。”

为平息外界疑虑，OpenAI在同日的公告中强调：“解决该问题未访问任何特定用户数据。”但同时承认：“尽管可能性不大，我们无法完全排除产品使用过程中产生的去标识化数据对模型训练有所助益的可能性。”OpenAI在X平台上的声明与博客内容一致，并指向该帖作为官方回应。

OpenAI技术团队成员塞巴斯蒂安·布贝克补充称：“在他们昨晚公开成果之前，我们从未看到过巴克马斯特和阿尔波格的任何工作。事后看来，我们的证明路径与他们存在显著差异，连最终证得的具体结论也各不相同。”

对此，巴克马斯特在Mastodon上发文反击，称OpenAI“公开承认使用了在我们得出结果之后一段时间内的训练数据”。此外，OpenAI表示不打算领取那笔100万美元的奖金。

中文翻译：

OpenAI表示，它找到了一个困扰数学界约90年的重大难题的解法，这一点此前由《纽约时报》和《连线》杂志报道。在周二的一篇博客文章中，OpenAI宣布，它利用一个比新发布的GPT-6 Astra更强大的内部AI模型，并配合一万个并发智能体，发现了纳维-斯托克斯问题的解法——该问题与液体和气体的流动有关。纳维-斯托克斯问题是七个千禧年大奖难题之一，每个难题的解决都能获得100万美元的奖金。

关于OpenAI这一传奇性数学里程碑的争议四起

OpenAI对90年难题的突破遭到研究者的质疑，后者在前一天解决了一个相关问题。

OpenAI对90年难题的突破遭到研究者的质疑，后者在前一天解决了一个相关问题。

OpenAI表示，它于8月28日开始训练这一内部AI模型，该模型“在我们的基准测试中展现出了前所未有的表现，包括数学领域。”这一解法对数学界而言是一个重大突破，但它并非没有争议。

就在OpenAI发布公告的前一天，纽约大学数学教授特里斯坦·巴克马斯特与Anthropic的研究员莱文特·阿尔波格合作，发布了一项相关问题的研究结果。在公布这些发现时，巴克马斯特声称，他在得知OpenAI听说他们的进展后联系了OpenAI。然而，巴克马斯特发现，OpenAI对纳维-斯托克斯方程提出了一种证明，其路径正是他和阿尔波格一直在用OpenAI的Codex和Anthropic的Claude所推进的方向。

在他的声明中，巴克马斯特对OpenAI是否访问了他们的Codex数据以更接近纳维-斯托克斯解法表示担忧。“我问该模型是否经过训练，或是否可以访问我们在Codex中的会话记录——我们在这整个项目中把所有草稿都放在那里，”巴克马斯特写道。“我得到的答复是，该模型不会查看用户数据。我再次询问关于训练的问题，但没有得到回答。”

OpenAI现在正试图通过其周二的公告来打消这些疑虑，称“在解决这一问题时，没有访问任何特定用户数据。”它补充说，“虽然不太可能，但我们无法排除从用户使用我们产品中获得的去标识化数据帮助改进了我们的模型。”在被要求置评时，OpenAI将The Verge的提问指向了其X平台上的声明，该声明与其博客文章内容一致。

OpenAI的技术人员塞巴斯蒂安·布贝克也说道：“在他们昨晚公开发布之前，我们并没有看到他们的（巴克马斯特和阿尔波格的）任何工作。事后回顾，可以看出我们的证明有很大不同，甚至所证明的具体结果也是不同的。”

与此同时，巴克马斯特在Mastodon上发帖回应，声称OpenAI“公开承认他们使用了在我们得出结果之后一段时间的训练数据。”

OpenAI表示，它不打算领取那100万美元的奖金。

英文来源：

OpenAI says it found a solution to a major math problem that has remained unsolved for around 90 years, as reported earlier by The New York Times and Wired. In a blog post on Tuesday, OpenAI announced that it discovered a solution to the Navier-Stokes problem — which relates to the flow of liquid and gas — using an internal AI model more powerful than the newly released GPT-6 Astra alongside 10,000 concurrent agents. The Navier-Stokes problem is one of seven Millennium Prize Problems, each of which comes with a $1 million reward for solving.
Drama swirls around OpenAI’s legendary mathematical milestone
OpenAI’s breakthrough with a 90-year-old problem is challenged by researchers who solved a related problem the day before.
OpenAI’s breakthrough with a 90-year-old problem is challenged by researchers who solved a related problem the day before.
OpenAI says it started training the internal AI model on August 28th, which has “exhibited unprecedented performance in our benchmarks, including mathematics.” The solution is a big breakthrough for the mathematics community, but it doesn’t come without controversy.
Just one day before OpenAI’s announcement, New York University mathematics professor Tristan Buckmaster published findings on a related problem in partnership with Levent Alpöge, a researcher at Anthropic. When announcing these findings, Buckmaster claims he contacted OpenAI after learning the company had heard about their progress. However, Buckmaster found that OpenAI had produced a proof for the Navier-Stokes equation using a route he and Alpöge had been working on with OpenAI’s Codex and Anthropic’s Claude.
In his statement, Buckmaster raises concerns about whether OpenAI had accessed their Codex data to get closer to the Navier-Stokes solution. “I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project,” Buckmaster writes. “I was told the model did not look up user data. I asked again, about training, and I did not get an answer.”
OpenAI is now attempting to squash these suspicions with its Tuesday announcement, saying “no specific user data was accessed in order to solve this problem.” It adds that “while unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.” When reached for comment, OpenAI pointed The Verge to its statement on X, which echoes its blog post.
Sebastien Bubeck, a member of technical staff at OpenAI, similarly said: “We did not see any of their [Buckmaster and Alpöge’s] work until they released it publicly last night. One can in hindsight see that our proofs differ significantly and even the precise results proved are different.”
Meanwhile, Buckmaster responded to this in a post on Mastodon, claiming that OpenAI is “openly admitting they used training data from a period after we found our result.”
OpenAI says it doesn’t plan on taking the $1 million prize.