I am currently a researcher at Thinking Machines.

I was previously at OpenAI, Hudson River Trading, and Meta. I graduated from UC Berkeley, where I was fortunate to be advised by Pieter Abbeel and Igor Mordatch.

Email: matches my arxiv papers

Blog

• Mar 2024 — Spending Inference Time
  How should we structure inference compute to maximize performance?
  
• Feb 2024 — LoRAs as Composable Programs
  How can we design LLMs to be future-proof operating systems?
  
• Jan 2024 — Unifying RLHF Objectives
  What are different RL algorithms actually optimizing?
  

Papers

• Jun 2021 — Decision Transformer
  How can we perform reinforcement learning with autoregressive sequence models?
  
• Mar 2021 — Pretrained Transformers as Universal Computation Engines
  What are the limits of transfer of large pretrained language models?
  
• Summary — Towards a Universal Decision Making Paradigm
  How can we design a universal learning method for sequential decision making?