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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