• OpenAI CEO Sam Altman and mathematicians have a complicated relationship.
• OpenAI has taken credit for solving hundreds of math problems, irking many mathematicians.
• At a recent talk at Stanford, Altman said mathematicians have already gone from anger to acceptance.

Like someone in mourning, Sam Altman said mathematicians went through phases after OpenAI began its blitz into the field.

First, there was disbelief. Then, there was pain.

"The day one reaction was like, 'We're cooked, and our field is over,'" OpenAI's CEO said. "'We're telling our grad students to switch majors.'"

After that, there was anger.

"The day three reaction was maybe like: 'It's horrible that OpenAI did this,'" Altman said at a recent talk at Stanford, before hundreds of students jittery about the viability of their future careers.

Come day five, though, in Altman's telling, mathematicians began to come around to what he described as AI's now-inalienable role in the study of numbers and proofs.

"We've now seen a lot of people say, actually, I'm going to have a different but hopefully better kind of career as a mathematician," Altman said.

Altman's buoyant assessment contrasts sharply with what some in the math community have described as an existential transformation.

After OpenAI abruptly broke into the field's prerogatives in September, announcing its models had solved the Navier-Stokes equations — a famously challenging math puzzle that stumped the industry's brightest since the 19th Century — preeminent mathematicians erupted in fury.

A pair of academics, one at New York University and another at Anthropic, accused OpenAI of using data from their chat logs to help crack the problem. Mathematicians also complained that while an AI model might have solved the problem, it didn't show its work, leaving them with the less celebratory task of verifying it.

And in the wake of all that controversy, there was more controversy.

A group of undergrads at Caltech, wary of how rapidly AI was disrupting their field and wanting to stay relevant, advertised a "mathathon" where participants were encouraged to use AI to solve long-standing problems.

OpenAI dropped out of sponsoring the event after more than 700 academics signed an open letter denouncing the competition for promoting AI "slop." (Organizers have since made adjustments to the rules, and the competition is set for November.)

More recently, Terence Tao, a math prodigy at UCLA who earned his doctorate at 20, said math's "romantic era" is over, as top academics like him adjust to a workflow that involves verifying AI's work rather than solving problems individually.

"Some things are being lost," Tao said after OpenAI this month said it solved over 700 more problems.

Meanwhile, Altman, sitting on the opposite side of the debate, has adopted the optimism of the disrupter.

"I don't think there's going to be like a job apocalypse," Altman said of AI causing companies to restructure their workforces. In the field of math, however, Altman said the disruptions came more quickly than in other disciplines and industries.

"That was the fastest that I think we've all gotten to watch a field go through this cycle," he said.

• Terence Tao, now a UCLA professor, earned his doctorate in mathematics at 20.
• The prodigy said his work is changing in the age of AI.
• With AI tools doing the legwork, math is no longer "heroic," Tao said.

AI is upending mathematics. For one top professor, the issue is just as spiritual as it is practical.

Terence Tao, a renowned professor at UCLA, said in a recent podcast appearance that the "romantic era" of math is over, thanks to AI tools capable of solving hundreds of problems with some simple prompting.

Now, he said, even leading scholars like him are reduced to sorting through reams of AI-generated proofs, instead of doing the "heroic" solving themselves.

"We are moving to an industrial era where math will become much more large-scale," Tao said in an interview this week on Numberphile, a YouTube channel dedicated to math.

"We are entering an era where exciting new things are possible, but some things are being lost," he added.

OpenAI began its brusque push into the field by solving the Navier-Stokes equation in early September, one of math's millennium problems.

The revelation that AI had cracked it caused consternation from many a math geek. Some mathematicians also expressed frustration that while the AI model might have solved the problem, it didn't show its work, leaving them with the less celebratory task of verifying it.

Then, earlier this month, OpenAI said it cracked another 700 outstanding problems. A math professor at New York University told CNBC that the company's release had derailed work by early-career mathematicians.

"We've had whole research programs wiped out on Tuesday by their dump," the professor, Tristan Buckmaster, said at the time.

In a separate brouhaha in September, OpenAI backed out of a sponsorship for a so-called AI "mathathon" — an event organized by undergraduates at Caltech, where participants were encouraged to use AI to solve equations — after complaints from a group of more senior academics.

Event organizers told Business Insider at the time that their professors were sorely out of touch with the field's trajectory.

"We look to the future, and we don't even know if there's going to be grad school open positions by the time we get to Ph.D," one organizer, Caiman Moreno-Earle, said.

Though OpenAI has said it is taking steps to ensure human academics retain their role in this new era, some researchers and professors are already forecasting their possible obsolescence.

Tao isn't as much of a doomer as some of his colleagues in the field. However, he did say in the interview that the stories math nerds tell themselves may not mean so much in the future.

"We have these sort of mythological stories," he said in reference to the tale of Sir Andrew Wiles, who famously spent seven years isolated in his attic solving a single difficult equation.

"There was something romantic about sort of the heroic age," Tao said.