#94 – Ilya Sutskever: Deep Learning
May 8, 2020
1 hr 37 min
94
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Episode 94 · May 8, 2020
#94 – Ilya Sutskever: Deep Learning
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#94 – Ilya Sutskever: Deep Learning
Summary
<p>Ilya Sutskever is the co-founder of OpenAI, is one of the most cited computer scientist in history with over 165,000 citations, and to me, is one of the most brilliant and insightful minds ever in the field of deep learning. There are very few people in this world who I would rather talk to and brainstorm with about deep learning, intelligence, and life than Ilya, on and off the mic.</p>
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<p>EPISODE LINKS:<br />
Ilya’s Twitter: <a href="https://twitter.com/ilyasut">https://twitter.com/ilyasut</a><br />
Ilya’s Website: <a href="https://www.cs.toronto.edu/~ilya/">https://www.cs.toronto.edu/~ilya/</a></p>
<p><span style="font-weight: 400;">This conversation is part of the Artificial Intelligence podcast.</span> If you would like to get more information about this podcast go to <a href="https://lexfridman.com/ai">https://lexfridman.com/ai</a> or connect with @lexfridman on <a href="https://twitter.com/lexfridman">Twitter</a>, <a href="https://www.linkedin.com/in/lexfridman/">LinkedIn</a>, <a href="https://www.facebook.com/lexfridman">Facebook</a>, <a href="https://medium.com/@lexfridman">Medium</a>, or <a href="https://www.youtube.com/lexfridman">YouTube</a> where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on <a href="https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584">Apple Podcasts</a>, follow on <a href="https://open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL">Spotify</a>, or support it on <a href="https://www.patreon.com/lexfridman">Patreon</a>.</p>
<p>Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.</p>
<p>OUTLINE:<br />
00:00 – Introduction<br />
02:23 – AlexNet paper and the ImageNet moment<br />
08:33 – Cost functions<br />
13:39 – Recurrent neural networks<br />
16:19 – Key ideas that led to success of deep learning<br />
19:57 – What’s harder to solve: language or vision?<br />
29:35 – We’re massively underestimating deep learning<br />
36:04 – Deep double descent<br />
41:20 – Backpropagation<br />
42:42 – Can neural networks be made to reason?<br />