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