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.

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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

#110 – Jitendra Malik: Computer Vision

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