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.
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