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Geoff Hinton

Prominent figure in AI, 2024 Nobel Prize recipient, and former Vice President and Engineering Fellow at Google. Known for his work on the foundational algorithms of AI systems and his concerns about rapid AI advancements.

Top 5 podcasts with Geoff Hinton

Ranked by the Snipd community
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78 snips
Jan 18, 2025 • 1h 19min

Why the Godfather of AI Now Fears His Creation (ft. Geoffrey Hinton)

Geoffrey Hinton, the 'Godfather of AI' and a 2024 Nobel Prize recipient, shares his urgent concerns about the rapid development of artificial intelligence. He discusses the existential threats posed by AI, questioning the nature of consciousness and the differences between human and machine perceptions. Hinton emphasizes the need for careful regulation to mitigate job displacement and ethical issues. He also reflects on his transition from tech leadership to philosophy, urging a deeper understanding of AI's societal impacts.
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59 snips
May 10, 2023 • 57min

Geoff Hinton Returns: the Godfather of AI on quitting Google to warn of AI risks

Geoff Hinton, the "Godfather of AI" returns to the Robot Brains with Pieter Abeel to discuss quitting Google to warn of AI risks. Geoff and Peter discuss whether AI is smarter than people, the role of regulation, fusing human and artificial intelligence, and what Geoff's next steps will be. Subscribe to the Robot Brains Podcast today | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast and Twitter @therobotbrains. Hosted on Acast. See acast.com/privacy for more information.
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28 snips
Jun 1, 2022 • 1h 23min

Geoff Hinton on revolutionizing artificial intelligence... again

Over the past ten years, AI has experienced breakthrough after breakthrough in everything from computer vision to speech recognition, protein folding prediction, and so much more.Many of these advancements hinge on the deep learning work conducted by our guest, Geoff Hinton, who has fundamentally changed the focus and direction of the field. A recipient of the Turing Award, the equivalent of the Nobel prize for computer science, he has over half a million citations of his work. Hinton has spent about half a century on deep learning, most of the time researching in relative obscurity. But that all changed in 2012 when Hinton and his students showed deep learning is better at image recognition than any other approaches to computer vision, and by a very large margin. That result, that moment, known as the ImageNet moment, changed the whole AI field. Pretty much everyone dropped what they had been doing and switched to deep learning.Geoff joins Pieter in our two-part season finale for a wide-ranging discussion inspired by insights gleaned from Hinton’s journey from academia to Google Brain. The episode covers how existing neural networks and backpropagation models operate differently than how the brain actually works; the purpose of sleep; and why it’s better to grow our computers than manufacture them.SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast, Twitter @therobotbrains, and Instagram @therobotbrains. Hosted on Acast. See acast.com/privacy for more information.
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5 snips
Dec 4, 2024 • 24min

Machine Consciousness - with Nicholas Thompson and Geoffrey Hinton

In this engaging discussion, Geoffrey Hinton, a 2024 Nobel Prize winner and a trailblazer in AI, delves into the intriguing concept of machine consciousness. He explores the potential for AI to replicate human emotions and cognitive processes, raising profound philosophical questions. The conversation takes a fascinating turn as they connect dreams with neural networks, shedding light on how our sleeping minds might influence AI learning. Hinton also addresses the ethical implications of these advancements and the importance of regulation as AI evolves.
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Jan 10, 2025 • 47min

The ‘Godfather of AI’ says we can’t afford to get it wrong

Geoffrey Hinton, a pioneering figure in artificial intelligence and the 2024 Nobel Prize recipient in Physics, delves into the future of AI and its inherent risks. He recounts the humble beginnings of neural networks, once dismissed by experts, and reflects on how his childhood curiosity for nature shaped his career. Hinton emphasizes the critical need to guide AI safely, discussing the alignment problem and the existential threats that AI could pose if misaligned. This riveting dialogue blends personal anecdotes with profound insights into cognition and technology.