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Understanding the Elegant Math Behind Modern Machine Learning 1:14:43

4天之前1:14:43

1:14:43

Artificial intelligence is evolving at an unprecedented pace—what does that mean for the future of technology, venture capital, business, and even our understanding of ourselves? Award-winning journalist and writer Anil Ananthaswamy joins us for our latest episode to discuss his latest book Why Machines Learn: The Elegant Math Behind Modern AI . Anil helps us explore the journey and many breakthroughs that have propelled machine learning from simple perceptrons to the sophisticated algorithms shaping today’s AI revolution, powering GPT and other models. The discussion aims to demystify some of the underlying math that powers modern machine learning to help everyone grasp this technology impacting our lives, even if your last math class was in high school. Anil walks us through the power of scaling laws, the shift from training to inference optimization, and the debate among AI’s pioneers about the road to AGI—should we be concerned, or are we still missing key pieces of the puzzle? The conversation also delves into AI’s philosophical implications—could understanding how machines learn help us better understand ourselves? And what challenges remain before AI systems can truly operate with agency? If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform. Sign up for our newsletter at techsurgepodcast.com for exclusive insights and updates on upcoming TechSurge Live Summits. Links: Read Why Machines Learn, Anil’s latest book on the math behind AI https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Learn more about Anil Ananthaswamy’s work and writing https://anilananthaswamy.com/ Watch Anil Ananthaswamy’s TED Talk on AI and intelligence https://www.ted.com/speakers/anil_ananthaswamy Discover the MIT Knight Science Journalism Fellowship that shaped Anil’s AI research https://ksj.mit.edu/ Understand the Perceptron, the foundation of neural networks https://en.wikipedia.org/wiki/Perceptron Read about the Perceptron Convergence Theorem and its significance https://www.nature.com/articles/323533a0…

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Extra: The Wallace Line

大约1年之前 13:17

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Guest: Ian McFadden, Lecturer in Computational Ecology, Queen Mary University of London

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Extra: The Wallace Line

Futureproof with Jonathan McCrea

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published 大约1年之前

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内容由Newstalk提供。所有播客内容（包括剧集、图形和播客描述）均由 Newstalk 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品，您可以按照此处概述的流程进行操作https://zh.player.fm/legal。

Guest: Ian McFadden, Lecturer in Computational Ecology, Queen Mary University of London

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1
Should we reintroduce wolves to Ireland? 32:00

1 day之前32:00

32:00

Guests: Dr Jonny Hanson QUB Dr Annie Curtis Dr Shane Bergin

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Extra: How our Brains Handle Aggression 11:32

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Guest: Dayu Lin, Neuroscientist and Professor of Psychiatry, Neuroscience and Physiology at the New York University Grossman School of Medicine.

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Understanding More About the Sun & The Science of Risk 42:32

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Guests: Dr Laura Hayes, Solar Physicist. Don Ross, Professor of Philosophy and Behavioural Economist.

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Futureproof Extra: Bioprinted Hearts 18:10

27天之前18:10

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Guest: Professor Andrew Daly, Associate Professor in Biomedical Engineering at the University of Galway.

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When Mega-Icebergs Melt 29:35

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How New Memories Are Formed 30:52

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Extra: Carbon Dioxide's Secrets 15:49

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How Decontamination Happens in Space 28:41

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Guest: Dr Lokesh Joshi, Stokes Professor of Glycosciences at the Infectious Diseases Section of the School of Biological and Chemical Sciences at the University of Galway.

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Extra: The Wallace Line 13:17

7 weeks之前13:17

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Guest: Ian McFadden, Lecturer in Computational Ecology, Queen Mary University of London

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