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Sean Carroll's Mindscape

Sean Carroll's Mindscape

Ever wanted to know how music affects your brain, what quantum mechanics really is, or how black holes work? In Mindscape, Sean Carroll, hosts conversations with the world’s most interesting thinkers in the world about the biggest ideas in science, society, philosophy and culture.

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1 hr, 11 min
5 Jan
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1 hr, 17 min
1 Dec 25

337 | Kevin Zollman on Game Theory, Signals, and Meaning

Game theory is a way of quantitatively describing what happens any time one thing interacts with another thing, when both things have goals and potential rewards. That's a pretty broad class of interesting events, so it is unsurprising that game theory is a useful way of thinking about everything from international relations to the evolution of peacock feathers. I talk with philosopher Kevin Zollman about what game theory is and how it gets used in biology and human interactions. We discuss how thinking in game-theoretic terms can help understand the origin of meaning and intentionality in human language.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/12/01/337-kevin-zollman-on-game-theory-signals-and-meaning/Support Mindscape on Patreon.Kevin Zollman received his Ph.D. in philosophy from the University of California, Irvine. He is currently the Herbert A. Simon Professor of Philosophy and Social and Decision Sciences in the Department of Philosophy at Carnegie Mellon University. He is also an associate fellow at the Center for Philosophy of Science at the University of Pittsburgh, and a visiting professor at the Munich Center for Mathematical Philosophy. He serves as the Director of the Institute for Complex Social Dynamics at CMU. He is the co-author, with Paul Raeburn, of The Game Theorist's Guide to Parenting.Web siteCMU web pageGoogle Scholar publicationsPhilPeople profileSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

337 | Kevin Zollman on Game Theory, Signals, and Meaning
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1 hr, 14 min
24 Nov 25

336 | Anil Ananthaswamy on the Mathematics of Neural Nets and AI

Machine learning using neural networks has led to a remarkable leap forward in artificial intelligence, and the technological and social ramifications have been discussed at great length. To understand the origin and nature of this progress, it is useful to dig at least a little bit into the mathematical and algorithmic structures underlying these techniques. Anil Ananthaswamy takes up this challenge in his book Why Machines Learn: The Elegant Math Behind Modern AI. In this conversation we give a brief overview of some of the basic ideas, including the curse of dimensionality, backpropagation, transformer architectures, and more.Blog post with transcript: https://www.preposterousuniverse.com/podcast/2025/11/24/336-anil-ananthaswamy-on-the-mathematics-of-neural-nets-and-ai/Support Mindscape on Patreon.Anil Ananthaswamy received a Masters degree in electrical engineering from the University of Washington, Seattle. He is currently a freelance science writer and feature editor for PNAS Front Matter. He was formerly the deputy news editor for New Scientist, a Knight Science Journalism Fellow at MIT, and journalist-in-residence at the Simon Institute for the Theory of Computing, University of California, Berkeley. He organizes an annual science journalism workshop at the National Centre for Biological Sciences at Bengaluru, India.Web siteAmazon author pageWikipediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

336 | Anil Ananthaswamy on the Mathematics of Neural Nets and AI
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