Jan 2022 - Casual Robotics

  • Host: Kevin Zakka
  • Guests: Pete Florence and myself
  • Summary: We discuss progress in robotics in the last 50 years, and the roles software and hardware have played in this development. On the algorithmic side, we discuss how much of imitation learning and reinforcement learning is needed to obtain general purpose robots and why policy evaluation is hard in the real-world.
  • Links: Spotify

Jan 2022 - The Gradient Podcast

  • Host: Andrey Kurenkov
  • Summary: We cover how I got into AI research (starting from neuroscience!) and the hard-won lessons I learned from my first few projects at Google. This is a summary of what I have learned about robotic deep learning in the last 5-6 years. Hopefully folks who are curious about what a “5-year growth trajectory, starting from 0 experience” find this useful.
  • Links: Substack, Apple Podcasts, Spotify

Dec 2021 - Bits of Deep Learning Podcast

  • Host: Andrea Lonza
  • Summary: I discuss my opinions on “the most important problem in robotics”, Reinforcement Learning vs. Imitation Learning vs. Self-Supervised Learning”, & “Just ask for Generalization”.
  • Links: YouTube

Dec 2021 - Stitch Fix Algo Hour

  • Host: Stitch Fix
  • Summary: I give a talk version of the ideas behind my blog posts “Just ask for Generalization” and “To Understand Language is to Understand Generalization”.
  • Links: YouTube

Jun 2019 - Tutorial on Normalizing Flows

  • Host: ICML 2019 Workshop on Invertible Generative Models
  • Links: slideslive.com

Jan 2019 - Deep Learning for Robotics and Robotics for Deep Learning