Why Vlad Tenev and Tudor Achim of Harmonic Think AI Is About to Change Math—and Why It Matters

Adding code to LLM training data is a known method of improving a model’s reasoning skills. But wouldn’t math, the basis of all reasoning, be even better? Up until recently, there just wasn’t enough usable data that describes mathematics to make this feasible. A few years ago, Vlad Tenev (also founder of Robinhood) and Tudor Achim noticed the rise of the community around an esoteric programming language called Lean that was gaining traction among mathematicians. The combination of that and the past decade’s rise of autoregressive models capable of fast, flexible learning made them think the time was now and they founded Harmonic. Their mission is both lofty—mathematical superintelligence—and imminently practical, verifying all safety-critical software. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital Mentioned in this episode: IMO and the Millennium Prize : Two significant global competitions Harmonic hopes to win (soon) Riemann hypothesis : One of the most difficult unsolved math conjectures (and a Millenium Prize problem) most recently in the sights of MIT mathematician Larry Guth Terry Tao : perhaps the greatest living mathematician and Vlad’s professor at UCLA Lean : an open source functional language for code verification launched by Leonardo de Moura when at Microsoft Research in 2013 that powers the Lean Theorem Prover mathlib : the largest math textbook in the world, all written in Lean Metaculus : online prediction platform that tracks and scores thousands of forecasters Minecraft Beaten in 20 Seconds : The video Vlad references as an analogy to AI math