Manon Revel: Is Democracy a Comma in History? - 74th Conversation
Computing Up
Manon Revel (, , ), an Employee Fellow at the Berkman Klein Center for Internet & Society at Harvard University, joins Michael and Dave for a conversation about the past, present, and future of democracy, and ways to understand it in both computational and practical terms. [Thumbnail based on image provided courtesy of Manon Revel]
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Martha White: Sparse is Rich - 73rd Conversation
Computing Up
Martha White, associate professor of Computing Science at University of Alberta (, ) joins Michael and Dave in a conversation about AI, system prediction and control, the power of sparse representations, and many aspects of machine learning from new mathematical theory to the absolutely practical control of a real water treatment plant. [Thumbnail based on image used courtesy of Martha White]
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Rich Sutton Brings Reinforcements - 72nd Conversation
Computing Up
Computer scientist Rich Sutton, FRS (, , ), a quiet giant of machine learning, joins Michael and Dave in a sprawling conversation touching on reinforcement learning, a hopeful view of AI, the importance of ideas, and a host of other topics. [Thumbnail image used courtesy of Rich Sutton]
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The Living Computation Theory of Everything - 71st Conversation
Computing Up
Michael interviews Dave about his recent video () on a 'theory of everything'. The conversation begins with Michael praising Dave for finally doing some theory, and descends from there.
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Oren Etzioni All Over - 70th Conversation
Computing Up
Oren Etzioni, founding CEO of the Allen Institute for Artificial Intelligence and Professor Emeritus of Computer Science at University of Washington, (, , ) joins Michael and Dave in a conversation that ranges all over, from AI hype and language models to alignment and existential risk and ethics and morality to information pollution and cryptography and politics and more. [Thumbnail based on image licensed CC BY-SA 4.0 by Carissapod ]
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Beautiful Messiness with Jonathan Frankle - 69th Conversation
Computing Up
Jonathan Frankle, the new Chief Scientist - Neural Networks at Databricks (, , ), joins Michael and Dave in a fast conversation about topics ranging from AI risks and fairness to the problems of Computer Science education to the beautiful messiness of modern deep learning. [Thumbnail based on image courtesy of Jonathan Frankle]
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Love Hate Writing - 68th Conversation
Computing Up
Michael and Dave talk about their love and hate relationships with writing, in the context of Dave's foray into publishing and Michael's upcoming MIT Press book . (This conversation is Part 2 of Where The Hell Have Michael & Dave Been?)
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Busy Busy / Let's Blame AI - 67th Conversation
Computing Up
Michael and Dave catch up on where the hell they've been for the last couple months. (Mostly it's about busy, but Dave wants to blame everything on AI.)
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Michael Levin TAMEs Life - 66th Conversation
Computing Up
Michael Levin (, , ) is the director of the Allen Discovery Center at Tufts University, and Distinguished Professor of Biology and Vannevar Bush Chair, among several other roles. In this episode he talks with Michael and Dave about computing writ very large indeed, with topics ranging from the meaning of life and agency to the problems of computability theory to the ways Levin's TAME model - Technological Approach to Mind Everywhere () - envisions a reality full of adaptive machines made of adaptive parts adapting to each other with everything they've got.
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The Understandable Cynthia Rudin - 65th Conversation
Computing Up
Cynthia Rudin, the Earl D. McLean, Jr. Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics,and Biostatistics & Bioinformatics at Duke University (, , ), joins Michael and Dave for a fast and feisty conversation about how to make machines we can understand and control, with high-stakes examples like predicting power failures in New York City.
info_outlineCynthia Rudin, the Earl D. McLean, Jr. Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics,and Biostatistics & Bioinformatics at Duke University (🔗, 🔗, 🔗), joins Michael and Dave for a fast and feisty
conversation about how to make machines we can understand and control, with high-stakes examples like predicting power failures in New York City.