Episode

Building an AI Mathematician with Carina Hong - #754

Podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Published
Nov 4, 2025
Duration seconds
3352
Processing state
processed
Canonical source
https://twimlai.com/podcast/twimlai/building-an-ai-mathematician/
Audio
https://pscrb.fm/rss/p/traffic.megaphone.fm/MLN1309151606.mp3?updated=1762355698
JSON
/v1/public/podcasts/twiml-ai-podcast/episodes/building-an-ai-mathematician-with-carina-hong-754
Markdown
/podcast/twiml-ai-podcast/building-an-ai-mathematician-with-carina-hong-754.md

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Summary

In this episode, Carina Hong, founder and CEO of Axiom, joins us to discuss her work building an "AI Mathematician." Carina explains why this is a pivotal moment for AI in mathematics, citing a convergence of three key areas: the advanced reasoning capabilities of modern LLMs, the rise of formal proof languages like Lean, and breakthroughs in code generation. We explore the core technical challenges, including the massive data gap between general-purpose code and formal math code, and the difficult problem of "autoformalization," or translating natural language proofs into a machine-verifiable format. Carina also shares Axiom's vision for a self-improving system that uses a self-play loop of conjecturing and proving to discover new mathematical knowledge. Finally, we discuss the broader applications of this technology in areas like formal verification for high-stakes software and hardware. The complete show notes for this episode can be found at https://twimlai.com/go/754.