Episode

OpenAI Researchers on the Future of Mathematical Reasoning

Podcast
The a16z Show
Published
Sep 8, 2026
Duration seconds
3915
Processing state
not_requested
Canonical source
https://a16z.simplecast.com/episodes/openai-researchers-on-the-future-of-mathematical-reasoning-Jn50EkyR
Audio
https://mgln.ai/e/1344/afp-848985-injected.calisto.simplecastaudio.com/3f86df7b-51c6-4101-88a2-550dba782de8/episodes/0936ea4f-0124-43ff-b2b1-641cc247a0c3/audio/128/default.mp3?aid=rss_feed&awCollectionId=3f86df7b-51c6-4101-88a2-550dba782de8&awEpisodeId=0936ea4f-0124-43ff-b2b1-641cc247a0c3&feed=JGE3yC0V
JSON
/v1/public/podcasts/the-a16z-show-436525/episodes/openai-researchers-on-the-future-of-mathematical-reasoning
Markdown
/podcast/the-a16z-show-436525/openai-researchers-on-the-future-of-mathematical-reasoning.md

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Summary

a16z Infra Partner Lisha Li sits down with OpenAI mathematicians Mehtaab Sawhney and Mark Sellke to discuss how quickly AI’s mathematical capabilities are advancing, what recent results reveal about model reasoning, and what happens when AI begins making progress on problems mathematicians have struggled with for decades. Mehtaab and Mark unpack several recent results from OpenAI’s models, including advances in sphere packing and the construction of a non-sofic group. They explain why the surprising part isn’t simply that models can search more possibilities or work longer than humans: in many cases, the reasoning traces look remarkably similar to the work of an expert mathematician, including choosing promising approaches, backtracking when they fail, and combining ideas from across the literature. They also explore what this means for mathematics itself: how the role of human taste and judgment may change, whether AI could produce far more mathematics than humans can absorb, and why models that accelerate discovery may also make sophisticated results easier to understand.