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, OpenAI, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute.
Hosted by Robin Ranjit Singh Chauhan.
TalkRL: The Reinforcement Learning Podcast
Claim This Podcastby Robin Ranjit Singh Chauhan
5.0(84 reviews)
75 episodes
Updated Weekly
Accepts GuestsHas SponsorsLocation 🇨🇦
62
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality86
Social0
YouTube0
Engagement92
Podcast Overview
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, OpenAI, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute. Hosted by Robin Ranjit Singh Chauhan.
Language
🇺🇲
Publishing Since
8/1/2019
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62
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality86
Social0
YouTube0
Engagement92
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excellent
Episode Length
29 minutes
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Every 31 days
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Recent Episodes
January 3, 2026
Joseph Modayil of Openmind Research Institute @ RLC 2025
<p>Joseph Modayil is the Founder, President & Research Director of Openmind Research Institute.</p><p><strong>Featured References </strong></p><p><a href="https://www.openmindresearch.org/">Openmind Research Institute</a> <strong></strong></p><p><a href="https://arxiv.org/abs/2208.11173">The Alberta Plan for AI Research</a> <br>Richard S. Sutton, Michael Bowling, Patrick M. Pilarski </p><p><br><strong>Additional References </strong></p><ul><li><a href="https://scholar.google.co.in/citations?user=G3pvUNEAAAAJ&hl=ja">Joseph Modayil on Google Scholar</a> </li><li><a href="https://josephmodayil.com/">Joseph Modayil Homepage</a> </li></ul>
November 10, 2025
Danijar Hafner on Dreamer v4
<p>Danijar Hafner was a Research Scientist at Google DeepMind until recently.</p><p><br><strong>Featured References </strong></p><p><a href="https://arxiv.org/abs/2509.24527">Training Agents Inside of Scalable World Models</a> [ <a href="https://danijar.com/project/dreamer4/">blog</a> ] <br>Danijar Hafner, Wilson Yan, Timothy Lillicrap</p><p><a href="https://arxiv.org/abs/2410.12557">One Step Diffusion via Shortcut Models</a><br>Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel</p><p><a href="https://arxiv.org/abs/2009.01791">Action and Perception as Divergence Minimization</a> [ <a href="https://danijar.com/project/apd/">blog</a> ] <br>Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl Friston, Nicolas Heess </p><p><br><strong>Additional References </strong></p><ul><li><a href="https://arxiv.org/abs/2301.04104v1">Mastering Diverse Domains through World Models</a> [ <a href="https://danijar.com/project/dreamerv3/">blog</a> ] DreaverV3l Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy Lillicrap </li><li><a href="https://arxiv.org/abs/2010.02193">Mastering Atari with Discrete World Models</a> [ <a href="https://danijar.com/project/dreamerv2/">blog</a> ] DreaverV2 ; Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba </li><li><a href="https://arxiv.org/abs/1912.01603">Dream to Control: Learning Behaviors by Latent Imagination</a> [ <a href="https://danijar.com/project/dreamer/">blog</a> ] Dreamer ; Danijar Hafner, Timothy Lillicrap, Jimmy Ba, Mohammad Norouzi </li><li><a href="https://arxiv.org/abs/2206.11795">Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos</a> [ <a href="https://openai.com/research/vpt">Blog Post</a> ], Baker et al</li></ul>
September 8, 2025
David Abel on the Science of Agency @ RLDM 2025
<p>David Abel is a Senior Research Scientist at DeepMind on the Agency team, and an Honorary Fellow at the University of Edinburgh. His research blends computer science and philosophy, exploring foundational questions about reinforcement learning, definitions, and the nature of agency. </p><p><br><strong>Featured References </strong></p><p><br><a href="https://arxiv.org/pdf/2505.10361">Plasticity as the Mirror of Empowerment</a> <br> David Abel, Michael Bowling, André Barreto, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh </p><p><br><a href="https://arxiv.org/pdf/2307.11046">A Definition of Continual RL</a> <br> David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado van Hasselt, Satinder Singh </p><p><br><a href="https://arxiv.org/pdf/2502.04403">Agency is Frame-Dependent</a> <br> David Abel, André Barreto, Michael Bowling, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh </p><p><br><a href="https://arxiv.org/abs/2111.00876">On the Expressivity of Markov Reward</a> <br> David Abel, Will Dabney, Anna Harutyunyan, Mark Ho, Michael Littman, Doina Precup, Satinder Singh — Outstanding Paper Award, NeurIPS 2021 </p><p><br><strong>Additional References </strong></p><ul><li><a href="https://ieeexplore.ieee.org/abstract/document/1091610/similar#similar">Bidirectional Communication Theory</a> — Marko 1973 </li><li><a href="https://www.isiweb.ee.ethz.ch/archive/massey_pub/pdf/BI532.pdf">Causality, Feedback and Directed Information</a> — Massey 1990 </li><li><a href="https://openreview.net/forum?id=Sv7DazuCn8">The Big World Hypothesis</a> — Javed et al. 2024 </li><li><a href="https://www.nature.com/articles/s41586-024-07711-7">Loss of plasticity in deep continual learning</a> — Dohare et al. 2024 </li><li><a href="https://david-abel.github.io/tdorl.pdf">Three Dogmas of Reinforcement Learning</a> — Abel 2024 </li><li><a href="https://pubmed.ncbi.nlm.nih.gov/39054370/">Explaining dopamine through prediction errors and beyond</a> — Gershman et al. 2024 </li><li><a href="https://scholar.google.com/citations?user=lvBJlmwAAAAJ&hl=en">David Abel Google Scholar</a> </li><li><a href="https://david-abel.github.io/">David Abel personal website</a> </li></ul>
75 total episodes available with 8 transcripts
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Satinder Singh
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Frequently asked questions
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- What is TalkRL: The Reinforcement Learning Podcast?
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This podcast updates weekly.
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This podcast is available on 10 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
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