Carina Hong is CEO of Axiom Math, where they're building a self-improving superintelligent reasoner, starting with an AI mathematician. She's a Rhodes Scholar, first-gen college grad and mathematics prodigy who earned dual degrees in mathematics and physics from MIT in 3 years. And a joint JD/PhD at Stanford. They just raised a $64M seed round from B Capital, Greycroft, Madrona, and Menlo Ventures. 

Carina's favorite books: Proofs from THE BOOK (Author: Martin Aigner, Günter M. Ziegler)

(00:02 ) Intro
(00:38 ) What self-improving mathematical superintelligence means
(04:04 ) Proofs as programs: Lean and the data gap
(06:36 ) How AI proves: human-style vs. Lean-style reasoning
(10:43 ) Carina’s journey: from Olympiad problem-solver to theory-builder
(14:47 ) The engine room: data, infra, and building a math knowledge graph
(17:42 ) Verifying results: compile checks vs. LLM judges
(18:56 ) Self-improvement loops: skills libraries, memory, and conjecture↔prover curricula
(21:30 ) Synthetic data & auto-formalization strategy
(24:00 ) Benchmarks that matter: miniF2F, CombiBench, miniCTX v2
(26:24 ) Why combinatorics is uniquely hard for AI
(31:13 ) Compute footprint & scaling philosophy
(32:20 ) In-house Lean tooling and productization path
(33:57 ) Early use cases: formal verification in hardware/software
(36:19 ) Team blueprint: AI, programming languages, and math
(37:35 ) Scaling laws, efficiency, and bottlenecks
(38:26 ) If Axiom works: what becomes cheaper/faster for the world
(40:22 ) Rapid Fire Round

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Where to find Carina Hong: 

LinkedIn: https://www.linkedin.com/in/carina-hong/

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Where to find Prateek Joshi: 

Research column: https://www.infrastartups.com
Newsletter: https://prateekjoshi.substack.com 
Website: https://prateekj.com 
LinkedIn: https://www.linkedin.com/in/prateek-joshi-infinite
X: https://x.com/prateekvjoshi