Geoff Hinton on revolutionizing artificial intelligence... again
Publisher |
Pieter Abbeel
Media Type |
audio
Categories Via RSS |
Education
Science
Technology
Publication Date |
Jun 01, 2022
Episode Duration |
01:23:08

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 Abstract.html">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.

This episode currently has no reviews.

Submit Review
This episode could use a review!

This episode could use a review! Have anything to say about it? Share your thoughts using the button below.

Submit Review