TalkRL podcast is All Reinforcement Learning, All the Time.
In-depth interviews with brilliant people at the forefront of RL research and practice.
Guests from places like MILA, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute.
Hosted by Robin Ranjit Singh Chauhan. Technical content.
Robert Lange on learning vs hard-coding, meta-RL, Lottery Tickets and Minimal Task Representations, Action Grammars and more!
NeurIPS 2021 Political Economy of Reinforcement Learning Systems (PERLS) Workshop
Dr. Thomas Gilbert and Dr. Mark Nitzberg on the upcoming PERLS Workshop @ NeurIPS 2021
Amy Zhang shares her work on Invariant Causal Prediction for Block MDPs, Multi-Task Reinforcement Learning with Context-based Representations, MBRL-Lib, shares insight on generalization on RL, and more!
Xianyuan Zhan on DeepThermal for controlling thermal power plants, the MORE algorithm for Model-based Offline RL, comparing AI in China and the US, and more!
Eugene Vinitsky of UC Berkeley on social norms and sanctions, traffic simulation, mixed-autonomy traffic, and more!
Jess Whittlestone on societal implications of deep reinforcement Learning, AI policy, warning signs of transformative progress in AI, and more!
Exposes a wide array of topics
I am a first-year PhD student and I love this podcast. It helps me to be exposed to so many idea and find fellow RL researchers. Thank you Robin for putting this together.
If you are looking for a podcast to help you advance in the field and become a better RL researcher than this is the podcast for you!5
Unexpected gem to learn deeply about RL
I had the pleasure of finding this podcast as a listener and then being on it within a month or two. Robin does a great job and is here to help improve the experience for the community.
Will help listeners rapidly get up to date with the happenings in reinforcement learning.
Love the pod cast!
Great to have a podcast that digs into the technical detail of RL!!