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 Refe…

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, J…

Glen Berseth is an assistant professor at the Université de Montréal, a core academic member of the Mila - Quebec AI Institute, a Canada CIFAR AI chair, member l'Institute Courtios, and co-director of the Robotics and Embodied AI Lab (REAL). Featured Links Reinforcement Learning Conference Closing the Gap between TD Learning and Supervised Learning…

Ian Osband is a Research scientist at OpenAI (ex DeepMind, Stanford) working on decision making under uncertainty. We spoke about: - Information theory and RL - Exploration, epistemic uncertainty and joint predictions - Epistemic Neural Networks and scaling to LLMs Featured References Reinforcement Learning, Bit by Bit Xiuyuan Lu, Benjamin Van Roy,…

Sharath Chandra Raparthy on In-Context Learning for Sequential Decision Tasks, GFlowNets, and more! Sharath Chandra Raparthy is an AI Resident at FAIR at Meta, and did his Master's at Mila. Featured Reference Generalization to New Sequential Decision Making Tasks with In-Context Learning Sharath Chandra Raparthy , Eric Hambro, Robert Kirk , Mikael …

Pierluca D'Oro and Martin Klissarov on Motif and RLAIF, Noisy Neighborhoods and Return Landscapes, and more! Pierluca D'Oro is PhD student at Mila and visiting researcher at Meta. Martin Klissarov is a PhD student at Mila and McGill and research scientist intern at Meta. Featured References Motif: Intrinsic Motivation from Artificial Intelligence F…

Martin Riedmiller of Google DeepMind on controlling nuclear fusion plasma in a tokamak with RL, the original Deep Q-Network, Neural Fitted Q-Iteration, Collect and Infer, AGI for control systems, and tons more! Martin Riedmiller is a research scientist and team lead at DeepMind. Featured References Magnetic control of tokamak plasmas through deep r…

Max Schwarzer is a PhD student at Mila, with Aaron Courville and Marc Bellemare, interested in RL scaling, representation learning for RL, and RL for science. Max spent the last 1.5 years at Google Brain/DeepMind, and is now at Apple Machine Learning Research. Featured References Bigger, Better, Faster: Human-level Atari with human-level efficiency…

Julian Togelius is an Associate Professor of Computer Science and Engineering at NYU, and Cofounder and research director at modl.ai Featured References Choose Your Weapon: Survival Strategies for Depressed AI Academics Julian Togelius, Georgios N. Yannakakis Learning Controllable 3D Level Generators Zehua Jiang, Sam Earle, Michael Cerny Green, Jul…

Jakob Foerster on Multi-Agent learning, Cooperation vs Competition, Emergent Communication, Zero-shot coordination, Opponent Shaping, agents for Hanabi and Prisoner's Dilemma, and more. Jakob Foerster is an Associate Professor at University of Oxford. Featured References Learning with Opponent-Learning Awareness Jakob N. Foerster, Richard Y. Chen, …

Danijar Hafner on the DreamerV3 agent and world models, the Director agent and heirarchical RL, realtime RL on robots with DayDreamer, and his framework for unsupervised agent design! Danijar Hafner is a PhD candidate at the University of Toronto with Jimmy Ba, a visiting student at UC Berkeley with Pieter Abbeel, and an intern at DeepMind. He has …

AI Generating Algos, Learning to play Minecraft with Video PreTraining (VPT), Go-Explore for hard exploration, POET and Open Endedness, AI-GAs and ChatGPT, AGI predictions, and lots more! Professor Jeff Clune is Associate Professor of Computer Science at University of British Columbia, a Canada CIFAR AI Chair and Faculty Member at Vector Institute,…

Hear about why OpenAI cites her work in RLHF and dialog models, approaches to rewards in RLHF, ChatGPT, Industry vs Academia, PsiPhi-Learning, AGI and more! Dr Natasha Jaques is a Senior Research Scientist at Google Brain. Featured References Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog Natasha Jaques, As…

Jacob Beck and Risto Vuorio on their recent Survey of Meta-Reinforcement Learning. Jacob and Risto are Ph.D. students at Whiteson Research Lab at University of Oxford. Featured Reference A Survey of Meta-Reinforcement Learning Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa Zintgraf, Chelsea Finn, Shimon Whiteson Additional References…

John Schulman is a cofounder of OpenAI, and currently a researcher and engineer at OpenAI. Featured References WebGPT: Browser-assisted question-answering with human feedback Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, …

Sven Mika is the Reinforcement Learning Team Lead at Anyscale, and lead committer of RLlib. He holds a PhD in biomathematics, bioinformatics, and computational biology from Witten/Herdecke University. Featured References RLlib Documentation: RLlib: Industry-Grade Reinforcement Learning Ray: Documentation RLlib: Abstractions for Distributed Reinforc…

Karol Hausman is a Senior Research Scientist at Google Brain and an Adjunct Professor at Stanford working on robotics and machine learning. Karol is interested in enabling robots to acquire general-purpose skills with minimal supervision in real-world environments. Fei Xia is a Research Scientist with Google Research. Fei Xia is mostly interested i…

Saikrishna Gottipati is an RL Researcher at AI Redefined, working on RL, MARL, human in the loop learning. Featured References Cogment: Open Source Framework For Distributed Multi-actor Training, Deployment & Operations AI Redefined, Sai Krishna Gottipati, Sagar Kurandwad, Clodéric Mars, Gregory Szriftgiser, François Chabot Do As You Teach: A Multi…

The Midseason Madness 2022 Recap (before I go vacay) - Positive Reinforcement by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

Aravind Srinivas is back! He is now a research Scientist at OpenAI. Featured References Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch VideoGPT: Video Generation using VQ-VAE and Transformers Wilson Y…

Dr. Rohin Shah is a Research Scientist at DeepMind, and the editor and main contributor of the Alignment Newsletter. Featured References The MineRL BASALT Competition on Learning from Human Feedback Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, …

Jordan Terry is a PhD candidate at University of Maryland, the maintainer of Gym, the maintainer and creator of PettingZoo and the founder of Swarm Labs. Featured References PettingZoo: Gym for Multi-Agent Reinforcement Learning J. K. Terry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari, Ryan Sullivan, Luis Santos, Rodrigo Perez, …

Robert Tjarko Lange is a PhD student working at the Technical University Berlin. Featured References Learning not to learn: Nature versus nurture in silico Lange, R. T., & Sprekeler, H. (2020) On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning Vischer, M. A., Lange, R. T., & Sprekeler, H. (2021). Semantic RL with Act…

We hear about the idea of PERLS and why its important to talk about. Political Economy of Reinforcement Learning (PERLS) Workshop at NeurIPS 2021 on Tues Dec 14th NeurIPS 2021Robin Ranjit Singh Chauhan による

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 Precu…

Xianyuan Zhan is currently a research assistant professor at the Institute for AI Industry Research (AIR), Tsinghua University. He received his Ph.D. degree at Purdue University. Before joining Tsinghua University, Dr. Zhan worked as a researcher at Microsoft Research Asia (MSRA) and a data scientist at JD Technology. At JD Technology, he led the r…

Eugene Vinitsky is a PhD student at UC Berkeley advised by Alexandre Bayen. He has interned at Tesla and Deepmind. Featured References A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings Eugene Vinitsky, Raphael Köster, John P. Agapiou, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets, Joel Z. Leib…

Hey everyone, so today's podcast is a little bit lengthier than usual and that is because I am discussing why everyone needs to take their children out of these public hell holes they call schools. So pretty much I am giving information about different homeschooling methods that many people may not even be aware of. These methods include but are no…

Dr. Jess Whittlestone is a Senior Research Fellow at the Centre for the Study of Existential Risk and the Leverhulme Centre for the Future of Intelligence, both at the University of Cambridge. Featured References The Societal Implications of Deep Reinforcement Learning Jess Whittlestone, Kai Arulkumaran, Matthew Crosby Artificial Canaries: Early Wa…

Often times we let outsiders influence the way we want to live our lives and that is just not okay. How does one truly expect to live in their divinity if they continue to look outside of themselves for answers that they already have?--- Support this podcast: https://podcasters.spotify.com/pod/show/crsmith/support…

Dr Aleksandra Faust is a Staff Research Scientist and Reinforcement Learning research team co-founder at Google Brain Research. Featured References Reinforcement Learning and Planning for Preference Balancing Tasks Faust 2014 Learning Navigation Behaviors End-to-End with AutoRL Hao-Tien Lewis Chiang, Aleksandra Faust, Marek Fiser, Anthony Francis E…

Sam Ritter is a Research Scientist on the neuroscience team at DeepMind. Featured References Unsupervised Predictive Memory in a Goal-Directed Agent (MERLIN) Greg Wayne, Chia-Chun Hung, David Amos, Mehdi Mirza, Arun Ahuja, Agnieszka Grabska-Barwinska, Jack Rae, Piotr Mirowski, Joel Z. Leibo, Adam Santoro, Mevlana Gemici, Malcolm Reynolds, Tim Harle…

Week 1 June Joust PREDICTIONS! (what could go wrong) — Positive Reinforcement S2 E10 by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

June Joust APAC Preview! Rapid fire analysis! — Positive Reinforcement S2 E9 by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

Thomas Krendl Gilbert is a PhD student at UC Berkeley’s Center for Human-Compatible AI, specializing in Machine Ethics and Epistemology. Featured References Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz Mapping the Political Economy of Re…

New Map Pool for JUNE JOUST! — Positive Reinforcement S2 E8 by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

Breaking down the JUNE JOUST Overwatch patch! — Positive Reinforcement S2 E7 by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

CARPE is the most interesting player in the Overwatch League! — Positive Reinforcement S2 E6 by Jonathan @Reinforce LarssonJonathan @Reinforce Larsson による

SLEEPY MORNING EDITIONJonathan @Reinforce Larsson による

Professor Marc G. Bellemare is a Research Scientist at Google Research (Brain team), An Adjunct Professor at McGill University, and a Canada CIFAR AI Chair. Featured References The Arcade Learning Environment: An Evaluation Platform for General Agents Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling Human-level control through deep rei…

Robert Osazuwa Ness is an adjunct professor of computer science at Northeastern University, an ML Research Engineer at Gamalon, and the founder of AltDeep School of AI. He holds a PhD in statistics. He studied at Johns Hopkins SAIS and then Purdue University. References Altdeep School of AI, Altdeep on Twitch, Substack, Robert Ness Altdeep Causal G…

Dr. Marlos C. Machado is a research scientist at DeepMind and an adjunct professor at the University of Alberta. He holds a PhD from the University of Alberta and a MSc and BSc from UFMG, in Brazil. Featured References Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents Marlos C. Machado, Marc G. Be…

Often times we are targeted for having our mind right, people will project their insecurities on to you just because they lack basic common sense. Don't let them get too you because when it's all said and done the joke is will be on them.--- Support this podcast: https://podcasters.spotify.com/pod/show/crsmith/support…

Nathan Lambert is a PhD Candidate at UC Berkeley. Featured References Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning Nathan O. Lambert, Albert Wilcox, Howard Zhang, Kristofer S. J. Pister, Roberto Calandra Objective Mismatch in Model-based Reinforcement Learning Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra…

Kai Arulkumaran is a researcher at Araya in Tokyo. Featured References AlphaStar: An Evolutionary Computation Perspective Kai Arulkumaran, Antoine Cully, Julian Togelius Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation Tianhong Dai, Kai Arulkumaran, Tamara Gerbert, Samyakh Tukra, Feryal Behbahani, Anil Anthony Bharath …

Michael Dennis is a PhD student at the Center for Human-Compatible AI at UC Berkeley, supervised by Professor Stuart Russell. I'm interested in robustness in RL and multi-agent RL, specifically as it applies to making the interaction between AI systems and society at large to be more beneficial. --Michael Dennis Featured References Emergent Complex…

Roman Ring is a Research Engineer at DeepMind. Featured References Grandmaster level in StarCraft II using multi-agent reinforcement learning Vinyals et al, 2019 Replicating DeepMind StarCraft II Reinforcement Learning Benchmark with Actor-Critic Methods Roman Ring, 2018 Additional References Relational Deep Reinforcement Learning, Zambaldi et al 2…

Shimon Whiteson is a Professor of Computer Science at Oxford University, the head of WhiRL, the Whiteson Research Lab at Oxford, and Head of Research at Waymo UK. Featured References VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann…

Hey y’all, I just tried to upload my spiritual journey podcast by itself but for some reason it combined with my previous podcast, so if you already listened to the pandemic podcast you can just skip like the first six minutes lol , I am gonna be touching on spirituality and learning who I am. Maybe y’all can relate. Thanks for listening --- Suppor…

Aravind Srinivas is a 3rd year PhD student at UC Berkeley advised by Prof. Abbeel. He co-created and co-taught a grad course on Deep Unsupervised Learning at Berkeley. Featured References Data-Efficient Image Recognition with Contrastive Predictive Coding Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Esla…