Everyone has a dream. But sometimes there’s a gap between where we are and where we want to be. True, there are some people who can bridge that gap easily, on their own, but all of us need a little help at some point. A little boost. An accountability partner. A Snooze Squad. In each episode, the Snooze Squad will strategize an action plan for people to face their fears. Guests will transform their own perception of their potential and walk away a few inches closer to who they want to become ...
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AI Agents That Do What We Want
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Content provided by UCTV. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UCTV 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://ro.player.fm/legal.
Researchers used to define objectives for artificial intelligence (AI) agents by hand, but with progress in optimization and reinforcement learning, it became obvious that it's too difficult to think of everything ahead of time and write it down. Instead, these days the objective is viewed as a hidden part of the state on which researchers can receive feedback or observations from humans — how they act and react, how they compare options, what they say. In this talk, Anca Dragan, Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, discusses what this transition has achieved, what open challenges researchers still face and ideas for mitigating them. Dragan discusses applications in robotics and how the lessons there apply to virtual agents like large language models. Series: "Data Science Channel" [Science] [Show ID: 39350]
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114 episoade
MP4•Pagina episodului
Manage episode 390431377 series 2578515
Content provided by UCTV. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UCTV 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://ro.player.fm/legal.
Researchers used to define objectives for artificial intelligence (AI) agents by hand, but with progress in optimization and reinforcement learning, it became obvious that it's too difficult to think of everything ahead of time and write it down. Instead, these days the objective is viewed as a hidden part of the state on which researchers can receive feedback or observations from humans — how they act and react, how they compare options, what they say. In this talk, Anca Dragan, Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, discusses what this transition has achieved, what open challenges researchers still face and ideas for mitigating them. Dragan discusses applications in robotics and how the lessons there apply to virtual agents like large language models. Series: "Data Science Channel" [Science] [Show ID: 39350]
…
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114 episoade
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