Machine Learning: How Did We Get Here?

Machine Learning: How Did We Get Here?

Tom Mitchell | Stanford Digital Economy Lab | Carnegie Mellon University

Episodes 14
Avg. Duration 46m
Activity Moderate
Apple Rating 4.7 (10)
Since Feb 2026
Latest Episode May 2026

Publishing Details

Schedule
Weekly
Format
Episodic
Consistency
100%
Hosting
feeds.transistor.fm

About This Podcast

Tom Mitchell literally wrote the book on machine learning. In this series of candid conversations with his fellow pioneers, Tom traces the history of the field through the people who built it. Behind the tech are stories of passion, curiosity, and humanity. Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject. This podcast is produced by the Stanford Digital Economy Lab.

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Recent Episodes

From Philosophy to Machine Learning with Bruce Buchanan

May 18, 2026 37m

Tom sits down with Bruce Buchanan, a PhD Philosopher turned machine learning researcher.  Bruce produced a key milestone for machine learning in the 1970s by creating the first program that…

AI Agents to Model Human Cognition with John Laird

May 11, 2026 32m

Tom chats with John Laird, who has spent the past 40 years trying to build an AI agent that accomplishes the full range of human cognitive abilities, beginning with his 1980s PhD research on the SOAR…

Machine Learning and Speech Recognition with Kai-Fu Lee

May 04, 2026 39m

Tom meets with Kai-Fu Lee, a pioneer in using machine learning to significantly advance speech recognition.Kai-Fu, former president of Google China and now Chairman of Sinovation Ventures and CEO of…

Machine Learning meets Cognitive Neuroscience with Jay McClelland

Apr 27, 2026 1h 3m

What is the relationship between neural network approaches in machine learning, and real neural networks in the brain? Today's guest Jay McClelland is a cognitive scientist who has spent decades…

Learning Probabilistic Models with Daphne Koller

Apr 20, 2026 39m

Tom interviews Daphne Koller, a Stanford professor turned serial entrepreneur. Daphne is widely known for her research at the intersection of machine learning and probabilistic reasoning.Daphne is a…

Self-Driving Cars in the 1980s (!) with Dean Pomerleau

Apr 13, 2026 32m

Tom meets with Dr. Dean Pomerleau, who as a CMU PhD student in the 1980s was the first person to demonstrate that a neural network could be trained to automatically steer a self-driving…

Machine Learning Meets Statistics with Michael I. Jordan

Apr 06, 2026 1h 1m

Tom sits down with Michael I. Jordan, Director of Rearch at Inria and Professor Emeritus of the Departments of EECS and Statistics, University of California, Berkeley. Michael has been a major…

Machine Learning Theory with Leslie Valiant

Mar 30, 2026 20m

What would a "theory" of machine learning tell us? In this episode Tom meets with the person who invented what is now the widely accepted definition of supervised machine learning: Turing Award…

Decision Tree Learning with Ross Quinlan

Mar 23, 2026 24m

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…

Reinforcement Learning with Rich Sutton

Mar 16, 2026 34m Transcript

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…

The Chaotic Evolution of the Field with Tom Dietterich

Mar 09, 2026 1h 5m Transcript

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…

A University and Corporate Perspective with Yann LeCun

Mar 02, 2026 1h 20m Transcript

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…

Five Decades of Neural Networks with Geoffrey Hinton

Feb 23, 2026 45m Transcript

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…

The History of Machine Learning with Tom Mitchell

Feb 23, 2026 1h 7m Transcript

Tom Mitchell, Founders University Professor at Carnegie Mellon University kicks off the podcast with this recording of his February 2026 seminar talk on “The History of Machine Learning.”He takes us…

Frequently Asked Questions

How many episodes does Machine Learning: How Did We Get Here? have?

Machine Learning: How Did We Get Here? has published 14 episodes since February 2026, covering topics in History, Technology.

Is Machine Learning: How Did We Get Here? still active?

Machine Learning: How Did We Get Here? is currently moderate with new episodes weekly. Average episode length is 46m.

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