Drama swirls around OpenAI’s legendary mathematical milestone
Drama swirls around OpenAI’s legendary mathematical milestone
OpenAI 传奇数学里程碑引发争议
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.
据《纽约时报》和《连线》杂志早先报道，OpenAI 称其已找到一个困扰数学界约 90 年的重大难题的解决方案。周二，OpenAI 在一篇博客文章中宣布，他们利用一个比刚发布的 GPT-6 Astra 更强大的内部 AI 模型，配合 10,000 个并发智能体，成功破解了纳维-斯托克斯（Navier-Stokes）方程——该问题涉及液体和气体的流动。纳维-斯托克斯问题是七大“千禧年大奖难题”之一，每道题的奖金高达 100 万美元。
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.
OpenAI 表示，他们于 8 月 28 日开始训练该内部 AI 模型，该模型“在包括数学在内的各项基准测试中展现出了前所未有的性能”。这一解决方案对数学界来说是一项重大突破，但同时也伴随着争议。
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.
就在 OpenAI 发布公告的前一天，纽约大学数学教授 Tristan Buckmaster 与 Anthropic 的研究员 Levent Alpöge 合作发表了关于相关问题的研究成果。Buckmaster 声称，在得知 OpenAI 获悉他们的进展后，他曾联系过该公司。然而，Buckmaster 发现 OpenAI 竟利用他与 Alpöge 在 OpenAI 的 Codex 和 Anthropic 的 Claude 上共同研究的路径，推导出了纳维-斯托克斯方程的证明。
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.”
在声明中，Buckmaster 对 OpenAI 是否通过访问他们的 Codex 数据来获取纳维-斯托克斯方程的解表示担忧。Buckmaster 写道：“我询问该模型是否在我们的 Codex 会话上进行过训练或访问过这些会话，因为我们将整个项目的草稿都放在了里面。我得到的答复是模型没有查看用户数据。我再次追问关于训练的问题时，却没有得到回答。”
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.
OpenAI 现正试图通过周二的公告平息这些质疑，称“在解决此问题的过程中，没有访问任何特定的用户数据”。该公司补充道：“虽然可能性不大，但我们不能排除从他们使用我们产品中得出的去标识化数据有助于改进我们模型的情况。”当《The Verge》寻求置评时，OpenAI 指向了其在 X 平台上的声明，该声明与博客文章内容一致。
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.”
OpenAI 技术人员 Sebastien Bubeck 也表示：“在他们昨晚公开成果之前，我们没有看到过他们的任何工作。事后看来，我们的证明方式有显著差异，甚至所证明的精确结果也不尽相同。”
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.”
与此同时，Buckmaster 在 Mastodon 上发帖回应称，OpenAI 这是“公开承认他们使用了我们得出结果之后一段时间内的训练数据”。
OpenAI says it doesn’t plan on taking the $1 million prize.
OpenAI 表示，他们不打算领取那 100 万美元的奖金。