UW News put out a Q&A about our recent work on Variational Preference Learning, a technique for personalizing Reinforcement Learning from Human Feedback (RLHF) washington.edu/news/2024/12...

Q&A: New AI training method lets systems better adjust to users’ values

University of Washington researchers created a method for training AI systems — both for large language models like ChatGPT and for robots — that can better reflect users’ diverse values. It...

washington.edu

We’ve been investigating how sim, while wrong, can be useful for real-world robotic RL! In our #NeurIPS2024 work, we theoretically showed how naive sim2real transfer can be inefficient, but if you *learn to explore* in sim, this transfers to the real world! We show this works on real robots! 🧵(1/6)

I'm excited about scaling up robot learning! We’ve been scaling up data gen with RL in realistic sims generated from crowdsourced videos. Enables data collection far more cheaply than real world teleop. Importantly, data becomes *cheaper* with more environments and transfers to real robots! 🧵 (1/N)