Distill AI

AI is the teacher; I’m the student.

I first explain an idea in my own words, then ask AI to identify gaps in my understanding and offer clearer explanations. I think of this exchange as a kind of on-policy distillation, where my own reasoning guides what we explore next.

These notes are mostly written by AI, guided by my questions and evolving understanding. They help me build a holistic view of different subjects and the connections between them. They give structure to my understanding.

My interests

  • Robotics
  • Dexterous manipulation
  • Reinforcement learning
  • Model-based RL
  • World models
  • Generative models
  • Multimodal foundation models
  • Post-training
  • Optimization
  • Kinematics
  • Control theory
  • Geometric vision algorithms

And the connections between them.

Notes