OpenAICEO Sam Altman 称同情那些在挣扎着去理解这一切的研究人员。 但是，他并不打算停止——从公司发现的库存中可以得出更多的暗示。
Sam Altman同情数学家
Altman 称 OpenAI在数学上花费了上亿美金——并且其袖子上还有更多的发现。
“我认为，从网络上看，世界应该了解宇宙是如何运作的，”阿尔特曼·称在"Cheeky Pint播音员"(发布)星期四的一集中，“但我确实同情这个方法。”
他的评论标志着OpenAI首席首次直接承认了公司对数学家的影响，紧接着一系列真正令人印象深刻的AI产生的结果
Altman认为，公众获得新科学知识的权利 " 超越 " OpenAI的发布造成的干扰，尽管他承认该公司需要改进如何传播其调查结果。 “在这一点上我感到毫不含糊：人类应该得到基本知识，我们不应坐以待毙，“世界理应如此。”
数学家们在"The Verge"上多次批评了OpenAI如何得到它的结果，并引用了归属不充分，上下文很少，以及核查不充分。 研究者说，这让他们做了艰苦的工作，检查和理解他们的发现，即便公司以更多的压力前进。 仅这个月，OpenAI就有了发布的上百个数学结果，往往只有简短的写作，被研究者描述为写作不好，难以遵循。
然而，OpenAI现在正面临批评，因为它做了阿尔特曼·称不应该做的事：坐视潜在的重大调查结果。 数学家和科学家本周在The Verge(英语：The Verge)演讲称时，其中一项声称的结果的细节——涉及现代粒子物理的数学基础杨-米尔斯理论——并没有公开发布。 OpenAI 称是由于一个亲身挑选的专家组的建议，该小组就如何最好地发布它进行了咨询。 这种做法直接违背了公司所咨询的前一组数学家的建议，但构成了称公司传播其调查结果的新方法的一部分。
在播客上，阿尔特曼暗示OpenAI坐落在比它公开的更多数学发现上。 在被问及该公司是否有超过他们已有的上百个发布的证据时，Altman回答说：“我们有。 当然。”
Altman还承认，OpenAI对数学问题的追求确实在很短的时间内"失控了"，但称是深思熟虑的，是探究其AI模型极限所必需的。 他描述了一个名为“Model Name-Hold My Beer”的内部的Slack频道，其中雇员“只是在面对他们可能面临的最困难的问题而扔出这种东西”，看看这些模型将如何运作。
阿尔特曼还估计OpenAI已经花费了约上亿美元解决数学问题，包括大约1000万美元——"可能更多一些"——用于它的纳维耶-斯托克斯解决方案，这是数学传奇的千年奖问题之一。 这笔开支可以一窥AI实验室给科学问题带来的巨大资源，引起研究人员的担心，认为它们可能从自己的领域定价。
它看起来像数学家和其他研究者希望呼吸器可能不走运。
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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.
Sam Altman sympathizes with mathematicians, but says OpenAI’s math onslaught won’t stop
Altman says OpenAI has spent hundreds of millions on math — and has more discoveries up its sleeve.
“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 they 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’s 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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