Last fall, Carina Hong, a PhD student at Stanford University, spent her weekends poring over mathematical research papers at a Verve Coffee Roasters near campus.
At one of the cafe’s communal tables, she struck up a conversation with Shubho Sengupta, an AI researcher at Meta who worked on large language models that wrote software tests.
They talked for hours about the intersection of their respective fields and the possibility of developing an AI that could solve the world’s toughest math problems— and discover new ones.
Hong dropped out of Stanford soon after to start Axiom Math, an early stage startup that aims to build a so-called “AI mathematician”— a model that can solve complex mathematical questions, generate detailed proofs of the different steps it took to get to the answer and check its own work.
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