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