Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
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Content provided by Robin Ranjit Singh Chauhan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Robin Ranjit Singh Chauhan or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Similar to TalkRL: The Reinforcement Learning Podcast
Africa-focused technology, digital and innovation ecosystem insight and commentary.
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Show notes are at https://stevelitchfield.com/sshow/chat.html
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The American healthcare system is one of the most innovative in the world. But it’s also riddled with complex challenges, such as access to affordable medications, inefficiency and administrative burdens, and communication barriers between providers. There’s clearly a better way—and at Surescripts, we have a unique sightline into what that may be. In this series, host Melanie Marcus, Chief Marketing Officer of Surescripts, sits down with today’s most inspiring and innovative leaders in healt ...
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Embedded is the show for people who love gadgets. Making them, breaking them, and everything in between. Weekly interviews with engineers, educators, and enthusiasts. Find the show, blog, and more at embedded.fm.
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Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
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The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
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Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Rae Johnston and guests take a fun, deep dive into how technology is reshaping our lives.
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Big tech is transforming every aspect of our world. But how, and at what cost? This season of Land of the Giants – The Disney Dilemma – focuses on Disney’s ability to weather the ups and downs of the business cycle and changing tastes and explores what has kept it successful for over 100 years. The entertainment giant has leveraged nostalgia and its intellectual property to build a beloved brand, but after an acquisition spree that included Marvel, Lucasfilm, and 20th Century Fox, can it sus ...
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Amy Zhang
Manage episode 303248521 series 2536330
Content provided by Robin Ranjit Singh Chauhan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Robin Ranjit Singh Chauhan or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Amy Zhang is a postdoctoral scholar at UC Berkeley and a research scientist at Facebook AI Research. She will be starting as an assistant professor at UT Austin in Spring 2023.
Featured References
Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Luis Pineda, Brandon Amos, Amy Zhang, Nathan O. Lambert, Roberto Calandra
Additional References
66 episodes
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Manage episode 303248521 series 2536330
Content provided by Robin Ranjit Singh Chauhan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Robin Ranjit Singh Chauhan or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
Amy Zhang is a postdoctoral scholar at UC Berkeley and a research scientist at Facebook AI Research. She will be starting as an assistant professor at UT Austin in Spring 2023.
Featured References
Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Luis Pineda, Brandon Amos, Amy Zhang, Nathan O. Lambert, Roberto Calandra
Additional References
66 episodes
All episodes
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Posters and Hallway episodes are short interviews and poster summaries. Recorded at NeurIPS 2024 in Vancouver BC Canada. Featuring Claire Bizon Monroc from Inria: WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control Andrew Wagenmaker from UC Berkeley: Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL Harley Wiltzer from MILA: Foundations of Multivariate Distributional Reinforcement Learning Vinzenz Thoma from ETH AI Center: Contextual Bilevel Reinforcement Learning for Incentive Alignment Haozhe (Tony) Chen & Ang (Leon) Li from Columbia: QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at NeurIPS 2024 in Vancouver BC Canada. Featuring Jonathan Cook from University of Oxford: Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning Yifei Zhou from Berkeley AI Research: DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning Rory Young from University of Glasgow: Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach Glen Berseth from MILA: Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn Alexander Rutherford from University of Oxford: JaxMARL: Multi-Agent RL Environments and Algorithms in JAX…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at NeurIPS 2024 in Vancouver BC Canada. Featuring Jiaheng Hu of University of Texas: Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning Skander Moalla of EPFL: No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO Adil Zouitine of IRT Saint Exupery/Hugging Face : Time-Constrained Robust MDPs Soumyendu Sarkar of HP Labs : SustainDC: Benchmarking for Sustainable Data Center Control Matteo Bettini of Cambridge University: BenchMARL: Benchmarking Multi-Agent Reinforcement Learning Michael Bowling of U Alberta : Beyond Optimism: Exploration With Partially Observable Rewards…
1 Abhishek Naik on Continuing RL & Average Reward 1:21:40
1:21:40 
Play Later 
Play Later 
Lists 
Like 
Liked1:21:40
Play Later Play Later Lists Like LikedAbhishek Naik was a student at University of Alberta and Alberta Machine Intelligence Institute, and he just finished his PhD in reinforcement learning, working with Rich Sutton. Now he is a postdoc fellow at the National Research Council of Canada, where he does AI research on Space applications. Featured References Reinforcement Learning for Continuing Problems Using Average Reward Abhishek Naik Ph.D. dissertation 2024 Reward Centering Abhishek Naik, Yi Wan, Manan Tomar, Richard S. Sutton 2024 Learning and Planning in Average-Reward Markov Decision Processes Yi Wan, Abhishek Naik, Richard S. Sutton 2020 Discounted Reinforcement Learning Is Not an Optimization Problem Abhishek Naik, Roshan Shariff, Niko Yasui, Hengshuai Yao, Richard S. Sutton 2019 Additional References Explaining dopamine through prediction errors and beyond , Gershman et al 2024 (proposes Differential-TD-like learning mechanism in the brain around Box 4)…
1 Neurips 2024 RL meetup Hot takes: What sucks about RL? 17:45
17:45 Play Later Play Later Lists Like Liked17:45
Play Later Play Later Lists Like LikedWhat do RL researchers complain about after hours at the bar? In this "Hot takes" episode, we find out! Recorded at The Pearl in downtown Vancouver, during the RL meetup after a day of Neurips 2024. Special thanks to "David Beckham" for the inspiration :)
Posters and Hallway episodes are short interviews and poster summaries. Recorded at RLC 2024 in Amherst MA. Featuring: 0:01 David Radke of the Chicago Blackhawks NHL on RL for professional sports 0:56 Abhishek Naik from the National Research Council on Continuing RL and Average Reward 2:42 Daphne Cornelisse from NYU on Autonomous Driving and Multi-Agent RL 08:58 Shray Bansal from Georgia Tech on Cognitive Bias for Human AI Ad hoc Teamwork 10:21 Claas Voelcker from University of Toronto on Can we hop in general? 11:23 Brent Venable from The Institute for Human & Machine Cognition on Cooperative information dissemination…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at RLC 2024 in Amherst MA. Featuring: 0:01 David Abel from DeepMind on 3 Dogmas of RL 0:55 Kevin Wang from Brown on learning variable depth search for MCTS 2:17 Ashwin Kumar from Washington University in St Louis on fairness in resource allocation 3:36 Prabhat Nagarajan from UAlberta on Value overestimation…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at RLC 2024 in Amherst MA. Featuring: 0:01 Kris De Asis from Openmind on Time Discretization 2:23 Anna Hakhverdyan from U of Alberta on Online Hyperparameters 3:59 Dilip Arumugam from Princeton on Information Theory and Exploration 5:04 Micah Carroll from UC Berkeley on Changing preferences and AI alignment…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at RLC 2024 in Amherst MA. Featuring: 0:01 Hector Kohler from Centre Inria de l'Université de Lille with " Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning " 2:29 Quentin Delfosse from TU Darmstadt on " Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents " 4:15 Sonja Johnson-Yu from Harvard on " Understanding biological active sensing behaviors by interpreting learned artificial agent policies " 6:42 Jannis Blüml from TU Darmstadt on " OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments " 8:20 Cameron Allen from UC Berkeley on " Resolving Partial Observability in Decision Processes via the Lambda Discrepancy " 9:48 James Staley from Tufts on " Agent-Centric Human Demonstrations Train World Models " 14:54 Jonathan Li from Rensselaer Polytechnic Institute…
Posters and Hallway episodes are short interviews and poster summaries. Recorded at RLC 2024 in Amherst MA. Featuring: 0:01 Ann Huang from Harvard on Learning Dynamics and the Geometry of Neural Dynamics in Recurrent Neural Controllers 1:37 Jannis Blüml from TU Darmstadt on HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning 3:13 Benjamin Fuhrer from NVIDIA on Gradient Boosting Reinforcement Learning 3:54 Paul Festor from Imperial College London on Evaluating the impact of explainable RL on physician decision-making in high-fidelity simulations: insights from eye-tracking metrics…
1 Finale Doshi-Velez on RL for Healthcare @ RCL 2024 7:35
7:35 Play Later Play Later Lists Like Liked7:35
Play Later Play Later Lists Like LikedFinale Doshi-Velez is a Professor at the Harvard Paulson School of Engineering and Applied Sciences. This off-the-cuff interview was recorded at UMass Amherst during the workshop day of RL Conference on August 9th 2024. Host notes: I've been a fan of some of Prof Doshi-Velez' past work on clinical RL and hoped to feature her for some time now, so I jumped at the chance to get a few minutes of her thoughts -- even though you can tell I was not prepared and a bit flustered tbh. Thanks to Prof Doshi-Velez for taking a moment for this, and I hope to cross paths in future for a more in depth interview. References Finale Doshi-Velez Homepage @ Harvard Finale Doshi-Velez on Google Scholar…
1 David Silver 2 - Discussion after Keynote @ RCL 2024 16:17
16:17 Play Later Play Later Lists Like Liked16:17
Play Later Play Later Lists Like LikedThanks to Professor Silver for permission to record this discussion after his RLC 2024 keynote lecture. Recorded at UMass Amherst during RCL 2024. Due to the live recording environment, audio quality varies. We publish this audio in its raw form to preserve the authenticity and immediacy of the discussion. References AlphaProof announcement on DeepMind's blog Discovering Reinforcement Learning Algorithms , Oh et al -- His keynote at RLC 2024 referred to more recent update to this work, yet to be published Reinforcement Learning Conference 2024 David Silver on Google Scholar…
David Silver is a principal research scientist at DeepMind and a professor at University College London. This interview was recorded at UMass Amherst during RLC 2024. References Discovering Reinforcement Learning Algorithms , Oh et al -- His keynote at RLC 2024 referred to more recent update to this work, yet to be published Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm , Silver et al 2017 -- the AlphaZero algo was used in his recent work on AlphaProof AlphaProof on the DeepMind blog AlphaFold on the DeepMind blog Reinforcement Learning Conference 2024 David Silver on Google Scholar…
Dr. Vincent Moens is an Applied Machine Learning Research Scientist at Meta, and an author of TorchRL and TensorDict in pytorch. Featured References TorchRL: A data-driven decision-making library for PyTorch Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens Additional References TorchRL on github TensorDict Documentation…
Arash Ahmadian is a Researcher at Cohere and Cohere For AI focussed on Preference Training of large language models. He’s also a researcher at the Vector Institute of AI. Featured Reference Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker Additional References Self-Rewarding Language Models , Yuan et al 2024 Reinforcement Learning: An Introduction , Sutton and Barto 1992 Learning from Delayed Rewards , Chris Watkins 1989 Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , Williams 1992…
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Similar to TalkRL: The Reinforcement Learning Podcast
Redefining AI is the 2024 New York Digital Award winning tech podcast! Discover a whole new take on Artificial Intelligence in joining host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and ...
…
continue reading
Africa-focused technology, digital and innovation ecosystem insight and commentary.
…
continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
…
continue reading
The American healthcare system is one of the most innovative in the world. But it’s also riddled with complex challenges, such as access to affordable medications, inefficiency and administrative burdens, and communication barriers between providers. There’s clearly a better way—and at Surescripts, we have a unique sightline into what that may be. In this series, host Melanie Marcus, Chief Marketing Officer of Surescripts, sits down with today’s most inspiring and innovative leaders in healt ...
…
continue reading
Embedded is the show for people who love gadgets. Making them, breaking them, and everything in between. Weekly interviews with engineers, educators, and enthusiasts. Find the show, blog, and more at embedded.fm.
…
continue reading
Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
…
continue reading
The power of Data is undeniable. And unharnessed - it’s nothing but chaos. Making data your ally. Using it to lead with confidence and clarity. Host Jess Carter is solving problems in real-time to reveal what’s possible. Helping communities and people thrive. This is Data Driven Leadership, a show brought to you by Resultant.
…
continue reading
Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Rae Johnston and guests take a fun, deep dive into how technology is reshaping our lives.
…
continue reading
Big tech is transforming every aspect of our world. But how, and at what cost? This season of Land of the Giants – The Disney Dilemma – focuses on Disney’s ability to weather the ups and downs of the business cycle and changing tastes and explores what has kept it successful for over 100 years. The entertainment giant has leveraged nostalgia and its intellectual property to build a beloved brand, but after an acquisition spree that included Marvel, Lucasfilm, and 20th Century Fox, can it sus ...
…
continue reading
This is the audio podcast version of Troy Hunt's weekly update video published here: https://www.troyhunt.com/tag/weekly-update/
…
continue reading
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