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

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. If you would like to get more
information about this podcast go to https://lexfridman.com/ai or
connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium,
or YouTube where you can watch the video versions of these
conversations. If you enjoy the podcast, please rate it 5 stars
on iTunes or support it on Patreon. Here’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):


00:00 – Introduction
01:37 – Singularity
05:48 – Physical and psychological knowledge
10:52 – Chess
14:32 – Language vs physical world
17:37 – What does AI look like 100 years from now
21:28 – Flaws of the human mind
25:27 – General intelligence
28:25 – Limits of deep learning
44:41 – Expert systems and symbol manipulation
48:37 – Knowledge representation
52:52 – Increasing compute power
56:27 – How human children learn
57:23 – Innate knowledge and learned knowledge
1:06:43 – Good test of intelligence
1:12:32 – Deep learning and symbol manipulation
1:23:35 – Guitar