Sam Altman 同情数学家,但称 OpenAI 的 AI 数学成果攻势不会停止
Sam Altman sympathizes with mathematicians, but says OpenAI’s math onslaught won’t stop
- 1OpenAI CEO Sam Altman 在播客中称同情数学家,但认为世界有权了解宇宙如何运作,OpenAI 不会停止发布
- 2本月 OpenAI 已发布数百项数学成果,多为简短难读的说明,受访数学家批评归因不足、缺乏背景和验证
- 3Altman 确认公司还握有更多未公开的数学发现;Yang-Mills 理论成果细节以受邀专家建议为由未公开
- 4Altman 估计 OpenAI 在数学问题上已投入约数亿美元,其中 Navier-Stokes 解法花费约 1000 万美元
OpenAI 的立场是基础科学发现不应被捂住,真正与数学界冲突的是发布节奏和验证方式,而非是否发布。
- 影响:前沿实验室正以数亿美元级投入切入基础科研,学术研究者的发现空间可能被资金门槛挤压;成果发布缺乏验证流程也显示,头部 AI 公司的科研产出同样需要第三方复核。
- 参考:若考虑用前沿模型辅助研发,可先把独立验证所需的人力和预算单独算出来;值得参照此争议为自家 AI 产出的对外披露制定归因与复核规则。
- 依据:表态来自 Altman 在 Cheeky Pint 播客的访谈;投入数亿美元与 Navier-Stokes 约 1000 万美元为其个人口径,暂无独立验证;数学家批评来自 The Verge 采访。
After months of bombarding mathematicians with a relentless stream of AI-generated results, OpenAI CEO Sam Altman says he sympathizes with researchers struggling to make sense of it all. But he has no intention of stopping — and hints there could be much more to come from the company’s stockpile of discoveries.
“I think, on net, the world deserves to understand how the universe works,” Altman said during an episode of the Cheeky Pint podcast released Thursday. “But I do have empathy for the method.”
His comments mark one of the first times the OpenAI chief has directly acknowledged the company’s impact on mathematicians, following a string of genuinely impressive AI-generated results whose chaotic, poorly communicated rollouts have left researchers bewildered and struggling to keep up, even amid widespread excitement about AI’s potential as a tool for discovery.
Altman argued that the public’s right to new scientific knowledge “outweighs” the disruption caused by OpenAI’s releases, though he acknowledged the company needs to improve how it communicates its findings. “I feel unequivocal on this point: Humanity deserves fundamental knowledge, and we should not be sitting on a major fundamental science discovery,” he said. “The world deserves that.”
Mathematicians speaking to The Verge have repeatedly criticized OpenAI for how it announces its results, citing inadequate attribution, little context, and insufficient verification. Researchers say this has left them doing the painstaking work of checking and making sense of their findings even as the company presses ahead with more. This month alone, OpenAI has released hundreds of mathematical results, often with little more than brief writeups that researchers have described as poorly written and hard to follow.
Yet OpenAI is now facing criticism for doing precisely what Altman says it should not be: sitting on potentially significant findings: Mathematicians and scientists speaking to The Verge this week said are frustrated by what they see as OpenAI’s gatekeeping of research, following the announcement of three major breakthroughs in mathematics, physics, and computer science. Details for one of the claimed results — involving Yang-Mills theory, the mathematical foundations of modern particle physics — have not been released publicly. OpenAI says it is due to the recommendations of a hand-picked group of experts it consulted on how best to release it. The practice runs directly counter to the advice of a previous group of mathematicians the company consulted, but forms part of what the company says is a new approach to communicating its findings.
On the podcast, Altman hints that OpenAI is sitting on many more mathematical discoveries than it has made public, too. Asked whether the company has more than the hundreds of proofs they have already released, Altman replied: “We do. Of course.”
Altman also acknowledged that OpenAI’s pursuit of mathematical problems did “get out of control” for a short period of time, but said that was deliberate and necessary to probe the limits of its AI models. He described an internal Slack channel called “Model Name-Hold My Beer,” where employees “were just throwing that at the hardest problems they could” to see how the models would perform.
Altman also estimated that OpenAI has spent in the order of hundreds of millions of dollars tackling mathematical problems, including around $10 million — “maybe a little more” — on its Navier-Stokes solution, one of mathematics’ legendary Millennium Prize problems. The spending offers a glimpse of the vast resources AI labs are bringing to bear on scientific problems, raising concerns among researchers that they may be priced out of their own fields.
It looks like mathematicians and other researchers hoping for a breather may be out of luck.
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- Robert Hart
来源:The Verge · AI · theverge.com