Math is one of the clearest ways to see how far AI has come in a short span. OpenAI researchers Sébastien Bubeck and Ernest Ryu join host Andrew Mayne to explain what changed and what it could mean for the future of research. They reflect on how Ernest used ChatGPT to help solve a 42-year-old open problem, the difference between deep literature search and original mathematical discovery, and what changes when AI can work over longer timelines. 

Chapters

01:27 The surprising progress of AI’s math capabilities 

03:01 Solving an open problem with ChatGPT

06:57 How models went from basic math to research level

11:32 Why math matters for AGI

14:26 AI and the Erdős problems

21:26 Building an automated researcher

28:19 The role of humans as models improve

33:52 Verifying proofs with AI

36:00 The risk of shallow understanding

41:19 Advice for learning math with ChatGPT

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