In August, OpenAI convened around 40 mathematicians to discuss what to do if AI outpaces human capabilities in the field. The company hinted that its powerful models had solved hundreds of longstanding math problems, say people who were in attendance, but company representatives assured attendees it would not release the solutions all at once—an assurance OpenAI spokesperson Lindsay McCallum says the company is “not aware of”—and, worried by how the community might react, sought advice on how to publish the findings.
Attendees responded with “a mixture of excitement and dread,” but the meeting was a promising first step, recalls Northwestern University mathematician Bryna Kra. The group, she tells WIRED, asked the firm not to just publish them in a blog or tweet, like they had done with 10 problems earlier that month. Instead, it would be important for OpenAI to publish papers explaining the work so that mathematicians could absorb, digest, and use the results, according to Kra. “Apparently, that input was ignored,” she says.
OpenAI has told people it plans to dump hundreds of the results it referenced in the August meeting on GitHub on Tuesday, people familiar with the plans tell WIRED. The release would be the latest of tens of thousands of mathematical solutions generated by AI this year, as frontier models become increasingly capable.
“On August 28, we began training a new internal model. In addition to resolving the Navier—Stokes Millennium Prize problem, this model has now resolved more than 100 long-standing open problems across most areas of mathematics,” says McCallum. “We are working to responsibly release the next math results from our model, drawing on advice and public recommendations from the Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study to inform how we release these results. We have not set a release time.”
But for several leading mathematicians, the impending output is also a sign that the company has learned little from the controversies over previous releases.
In conversations with WIRED, the academics say they feel the field has become a playground for OpenAI and its rival Anthropic to show off their models as both prepare for blockbuster initial public offerings. In their rush to outdo each other, mathematicians say, traditional scientific processes for releasing and attributing results have been cast aside.
The most striking case so far came in September. OpenAI deployed thousands of agents to solve a legendary million-dollar Millennium Prize problem after hearing “rumors” that others were closing in on solutions. Tristan Buckmaster, a mathematician and professor at New York University, accused the company of front-running the work he had done toward solving an element of the problem in a personal collaboration with Anthropic employee Levent Alpöge. The pair hadn’t published their work, but had been using OpenAI’s tools to help them.
