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, <a href="https://en.wikipedia.org/wiki/Geoffrey_Hinton" rel="noopener noreferrer" target="_blank">Geoff Hinton</a>, who has fundamentally changed the focus and direction of the field. A recipient of the <a href="https://amturing.acm.org/award_winners/hinton_4791679.cfm" rel="noopener noreferrer" target="_blank">Turing Award</a>, the equivalent of the Nobel prize for computer science, he has over <a href="https://scholar.google.co.uk/citations?user=JicYPdAAAAAJ&hl=en" rel="noopener noreferrer" target="_blank">half a million citations</a> 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 <a href="https://papers.nips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html" rel="noopener noreferrer" target="_blank">ImageNet moment</a>, changed the whole AI field. Pretty much everyone dropped what they had been doing and switched to <a href="https://www.technologyreview.com/2021/04/16/1021871/geoffrey-hinton-glom-godfather-ai-neural-networks/" rel="noopener noreferrer" target="_blank">deep learning</a>.Geoff joins Pieter in our two-part season finale for a wide-ranging discussion inspired by insights gleaned from <a href="https://bit.ly/3t9xsIN" rel="noopener noreferrer" target="_blank">Hinton’s journey</a> from <a href="https://www.cs.toronto.edu/~hinton/" rel="noopener noreferrer" target="_blank">academia</a> to <a href="https://research.google/teams/brain/" rel="noopener noreferrer" target="_blank">Google Brain</a>. The episode covers how existing neural networks and <a href="https://syncedreview.com/2020/04/23/new-hinton-nature-paper-revisits-backpropagation-offers-insights-for-understanding-learning-in-the-cortex/" rel="noopener noreferrer" target="_blank">backpropagation</a> 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&nbsp;<a href="https://www.therobotbrains.ai/" rel="noopener noreferrer" target="_blank">therobotbrains.ai</a>&nbsp;and follow us on YouTube at&nbsp;<a href="https://www.youtube.com/c/TheRobotBrainsPodcast" rel="noopener noreferrer" target="_blank">TheRobotBrainsPodcast</a>, Twitter&nbsp;<a href="https://twitter.com/therobotbrains" rel="noopener noreferrer" target="_blank">@therobotbrains</a>, and Instagram&nbsp;<a href="https://www.instagram.com/therobotbrains/" rel="noopener noreferrer" target="_blank">@therobotbrains</a>.<hr> See <a style='color:grey;' target='_blank' rel='noopener noreferrer' href='https://acast.com/privacy'>acast.com/privacy</a> for privacy and opt-out information.

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Geoff Hinton on revolutionizing artificial intelligence... again

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