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[40] Lisa Lee - Learning Embodied Agents with Scalably-Supervised RL
Manage episode 322254580 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck 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://player.fm/legal.
Lisa Lee is a Research Scientist at Google Brain. Her research focuses on building AI agents that can learn and adapt like humans and animals do. Lisa's PhD thesis is titled "Learning Embodied Agents with Scalably-Supervised Reinforcement Learning", which she completed in 2021 at Carnegie Mellon University. We talk about her work in the thesis on reinforcement learning, including exploration, learning with weak supervision, and embodied agents, and cover various topics related to trends in reinforcement learning. - Episode notes: https://cs.nyu.edu/~welleck/episode40.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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47 episodes
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Manage episode 322254580 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck 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://player.fm/legal.
Lisa Lee is a Research Scientist at Google Brain. Her research focuses on building AI agents that can learn and adapt like humans and animals do. Lisa's PhD thesis is titled "Learning Embodied Agents with Scalably-Supervised Reinforcement Learning", which she completed in 2021 at Carnegie Mellon University. We talk about her work in the thesis on reinforcement learning, including exploration, learning with weak supervision, and embodied agents, and cover various topics related to trends in reinforcement learning. - Episode notes: https://cs.nyu.edu/~welleck/episode40.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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Similar to The Thesis Review
Get in-depth coverage of current and future trends in technology, and how they are shaping business, entertainment, communications, science, politics, and society.
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continue reading
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…
continue reading
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…
continue reading
DNA science. Artificial intelligence. Smartphones and 3D printers. Science and technology have transformed the world we live in. But how did we get here? It wasn’t by accident. Well, sometimes it was. It was also the result of hard work, teamwork, and competition. And incredibly surprising moments. Hosted by bestselling author Steven Johnson (“How We Got To Now”), American Innovations uses immersive scenes to tell the stories of the scientists, engineers, and ordinary people behind the great ...
…
continue reading
Come dive into one of the curiously delightful conversations overheard at National Geographic’s headquarters, as we follow explorers, photographers, and scientists to the edges of our big, weird, beautiful world. Hosted by Peter Gwin and Amy Briggs.
…
continue reading
PT Inquest is an online journal club. Hosted by Jason Tuori, Megan Graham, and Chris Juneau, the show looks at an article every week and discusses how it applies to current physical therapy practice.
…
continue reading
We humans could have a bright future ahead of us that lasts billions of years. But we have to survive the next 200 years first. Join Josh Clark of Stuff You Should Know for a 10-episode deep dive that explores the future of humanity and finds dangers we have never encountered before lurking just ahead. And if we humans are alone in the universe, if we don't survive intelligent life dies out with us too.
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