Mindscape 336 | Anil Ananthaswamy on Neural Nets & AI 🤖
Anil Ananthaswamy discusses the mathematics behind neural networks and AI in this episode. Listen with show notes and transcript.

Sean Carroll
11.7K views • Nov 24, 2025

About this video
Patreon: https://www.patreon.com/seanmcarroll
Blog post with audio player, show notes, and transcript: https://www.preposterousuniverse.com/podcast/2025/11/24/336-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.
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 site
Amazon author page
Wikipedia
Mindscape Podcast playlist: https://www.youtube.com/playlist?list=PLrxfgDEc2NxY_fRExpDXr87tzRbPCaA5x
Sean Carroll channel: https://www.youtube.com/c/seancarroll
#podcast #ideas #science #philosophy #culture
Blog post with audio player, show notes, and transcript: https://www.preposterousuniverse.com/podcast/2025/11/24/336-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.
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 site
Amazon author page
Wikipedia
Mindscape Podcast playlist: https://www.youtube.com/playlist?list=PLrxfgDEc2NxY_fRExpDXr87tzRbPCaA5x
Sean Carroll channel: https://www.youtube.com/c/seancarroll
#podcast #ideas #science #philosophy #culture
Video Information
Views
11.7K
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Duration
01:14:12
Published
Nov 24, 2025
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