Machine Learning: How Did We Get Here?
Tom Mitchell | Stanford Digital Economy Lab | Carnegie Mellon UniversityTom 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... more
| Publishes | Weekly | Episodes | 10 | Founded | 2 months ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | HistoryTechnology | |||
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Latest Episodes
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 member of the U.S. National Academy of Engineerin... more
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 vehicle.
Dean's results shocked the research community, and pav... more
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 contributor to machine learning, especially at the inters... more
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 recipient and Harvard Professor Leslie Valiant.
Leslie ... more
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- How Refreshing
Almost all podcasts have been overrun by LLM discussions for years now; so it's incredibly refreshing to listen to a review on the wider world of machine learning from the experts involved in the world building.
Apple Podcasts5jhy1101
United Kingdom2 months ago - Pretty amazing lineup
Judging from the first episode, there will be a great set of guests on this show
Apple Podcasts5c(e)m
United States2 months ago
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Apple Podcasts | #75 |  Brazil/Technology |
Apple Podcasts | #177 |  Mexico/Technology |
Apple Podcasts | #200 |  South Korea/Technology |
Apple Podcasts | #223 |  Finland/Technology |
Apple Podcasts | #241 |  India/Technology |
Apple Podcasts | #248 |  Israel/Technology |
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Frequently Asked Questions About Machine Learning: How Did We Get Here?
What is Machine Learning: How Did We Get Here? about and what kind of topics does it cover?
This series curates candid conversations with early pioneers and current leaders in machine learning, tracing the field's evolution from symbolic and rule-based ideas to data-driven approaches. Episodes thread together foundational concepts, key breakthroughs, and the sociotechnical shifts that shaped modern AI—covering neural networks, reinforcement learning, kernel methods, and the transformer era—while weaving in personal stories, collaborations, and interdisciplinary influences. Notable throughlines include the tension between theory and practice, the role of large-scale experimentation and industry labs, and thoughtful discussions on AI safety, governance, and societal impact. The format tends to blend historical context with technical... more
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Machine Learning: How Did We Get Here? launched 2 months ago and published 10 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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What guests have appeared on Machine Learning: How Did We Get Here??
Recent guests on Machine Learning: How Did We Get Here? include:
1. Dean Pomerleau
2. Michael Jordan
3. Leslie Valiant
4. Ross Quinlan
5. Rich Sutton
6. Tom Dietterich
7. Yann LeCun
8. Geoffrey Hinton
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