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Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI

Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI

Lex Fridman Podcast
3 de out. de 2019 1h 25m
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Sobre este episódio

<p><span style="font-weight: 400;">Gary Marcus is a professor emeritus at NYU, founder of Robust.AI and Geometric Intelligence, the latter is a machine learning company acquired by Uber in 2016. He is the author of several books on natural and artificial intelligence, including his new book Rebooting AI: Building Machines We Can Trust. Gary has been a critical voice highlighting the limits of deep learning and discussing the challenges before the AI community that must be solved in order to achieve artificial general intelligence. This conversation is part of the Artificial Intelligence podcast.</span>&#160;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 iTunes&#160;or support it on <a href="https://www.patreon.com/lexfridman">Patreon</a>. Here&#8217;s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):</p> <p>00:00 &#8211; Introduction<br /> 01:37 &#8211; Singularity<br /> 05:48 &#8211; Physical and psychological knowledge<br /> 10:52 &#8211; Chess<br /> 14:32 &#8211; Language vs physical world<br /> 17:37 &#8211; What does AI look like 100 years from now<br /> 21:28 &#8211; Flaws of the human mind<br /> 25:27 &#8211; General intelligence<br /> 28:25 &#8211; Limits of deep learning<br /> 44:41 &#8211; Expert systems and symbol manipulation<br /> 48:37 &#8211; Knowledge representation<br /> 52:52 &#8211; Increasing compute power<br /> 56:27 &#8211; How human children learn<br /> 57:23 &#8211; Innate knowledge and learned knowledge<br /> 1:06:43 &#8211; Good test of intelligence<br /> 1:12:32 &#8211; Deep learning and symbol manipulation<br /> 1:23:35 &#8211; Guitar</p>

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