#110 – Jitendra Malik: Computer Vision

Jitendra Malik is a professor at Berkeley and one of the seminal
figures in the field of computer vision, the kind before the deep
learning revolution, and the kind after. He has been cited over
180,000 times and has mentored many world-class researchers in
computer science. Support this podcast by supporting our sponsors:
- BetterHelp: http://betterhelp.com/lex - ExpressVPN:
https://www.expressvpn.com/lexpod 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
Apple Podcasts, follow on Spotify, or support it on Patreon. Here's
the outline of the episode. On some podcast players you should be
able to click the timestamp to jump to that time. OUTLINE: 00:00 -
Introduction 03:17 - Computer vision is hard 10:05 - Tesla
Autopilot 21:20 - Human brain vs computers 23:14 - The general
problem of computer vision 29:09 - Images vs video in computer
vision 37:47 - Benchmarks in computer vision 40:06 - Active
learning 45:34 - From pixels to semantics 52:47 - Semantic
segmentation 57:05 - The three R's of computer vision 1:02:52 -
End-to-end learning in computer vision 1:04:24 - 6 lessons we can
learn from children 1:08:36 - Vision and language 1:12:30 - Turing
test 1:16:17 - Open problems in computer vision 1:24:49 - AGI
1:35:47 - Pick the right problem