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

00:00 - Introduction
01:42 - Math is reasoning
06:16 - Studying with the world's greatest living mathematician
10:18 - What does the math community think of AI math?
15:11 - Recursive self-improvement
18:31 - What is Lean?
21:05 - Why now?
22:46 - Synthetic data is the fuel for the model
27:29 - How fast will your model get better?
29:45 - Exploring the frontiers of human knowledge
34:11 - Lightning round