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Tom sits down with Geoffrey Hinton, University Professor Emeritus at the University of Toronto, and co-winner of the ACM Turing Award and of the 2024 Nobel Prize in Physics. Geoffrey explains how he got into the field, from his days as an aspiring carpenter to his conversion to a neural network res…
Tom interviews Rich Sutton, Research Scientist at Keen Technologies, Professor of Computing Science at the University of Alberta and co-winner of the 2024 ACM Turing Award for his foundational research on reinforcement learning. Rich discusses why the common framing of machine learning as 'supervis…
Tom sits down with Yann LeCun, the Jacob T. Schwartz Professor of Computer Science at NYU, and Executive Chairman of Advanced Machine Intelligence Labs. Yann is co-winner of the 2018 ACM Turing Award for his research in neural network learning. Yann takes us from his days as a postdoc working with …
Tom speaks with Ross Quinlan, whose algorithms C4.5 and ID3 helped establish decision trees as one of the most popular approaches in machine learning, and who founded RuleQuest Research, which accelerated the commercial adoption of machine learning. Ross (published as "JR Quinlan") describes a sabb…
Tom discusses the chaotic evolution of the field of machine learning with Tom Dietterich, Distinguished Professor Emeritus at Oregon State University. Tom has made numerous research contributions to the field, and has served in professional roles from Executive Editor of the journal Machine Learnin…
Dichiarazione di non responsabilità: Il podcast e la grafica incorporati in questa pagina provengono da Tom Mitchell | Stanford Digital Economy Lab | Carnegie Mellon University, che è di proprietà del suo proprietario e non è affiliato o approvato da Listen Notes, Inc.