Ventali Tan

Physics, philosophy, and the machines that learn the world.

I studied physics, philosophy, and computer science at Duke, with detours into archaeology. I am currently interested in automating reinforcement learning systems and developing intelligence systems for scientific discovery.

My work focuses on structuring scientific knowledge (e.g., Paperbase) and exploring hybrid architectures that combine language models with formal or symbolic methods to enable more rigorous reasoning and abstraction discovery. Previously, I built several agentic systems and Valida, a custom instruction set and compiler architecture for zero-knowledge virtual machines.

I run an AI & Science reading group in San Francisco and angel invest through Delendum.