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Grant Sanderson is a math educator and creator of 3Blue1Brown.

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Episode links:
3Blue1Brown: http://youtube.com/3blue1brown
Grant’s Twitter: https://twitter.com/3blue1brown

If you would like to get more information about this podcast go to https://lexfridman.com/podcast 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
05:13 – Richard Feynman
09:41 – Learning deeply vs broadly
13:56 – Telling a story with visualizations
18:43 – Topology
23:52 – Intuition about exponential growth
32:28 – Elon Musk’s exponential view of the world
40:09 – SpaceX and space exploration
45:28 – Origins of the Internet
49:50 – Does teaching on YouTube get lonely?
54:31 – Daily routine
1:00:20 – Social media
1:10:38 – Online education in a time of COVID
1:27:03 – Joe Rogan moving to Spotify
1:32:09 – Neural networks
1:38:30 – GPT-3
1:46:52 – Manim
1:51:01 – Python
1:56:21 – Theory of everything
2:03:53 – Meaning of life

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Sheldon Solomon is a social psychologist, a philosopher, co-developer of Terror Management Theory, co-author of The Worm at the Core.

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Episode links:
Sheldon’s Website: https://www.skidmore.edu/psychology/faculty/solomon.php
The Worm at the Core (book): https://amzn.to/31hQAXH
Denial of Death (book): https://amzn.to/329Zxl4

If you would like to get more information about this podcast go to https://lexfridman.com/podcast 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
05:34 – Role of death in life
22:57 – Jordan Peterson
53:02 – Humans are both selfish and cooperative
56:57 – Civilization collapse
1:10:07 – Meditating on your mortality
1:16:10 – Kierkegaard and Heidegger
1:33:25 – Elon Musk
1:36:56 – Thinking deeply about death
1:45:53 – Religion
1:56:59 – Consciousness
2:03:39 – Why is Ernest Becker not better known
2:07:09 – AI and mortality
2:21:07 – Academia should welcome renegade thinkers
2:36:33 – Book recommendations
2:43:23 – Advice for young people
2:48:17 – Meaning of life

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Sara Seager is a planetary scientist at MIT, known for her work on the search for exoplanets.

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Episode links:
Sara’s Twitter: https://twitter.com/profsaraseager
Sara’s Website: https://www.saraseager.com/
The Smallest Lights in the Universe (book): https://amzn.to/3g3LfHA

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
05:32 – Falling in love with the stars
09:55 – Are we alone in the universe?
15:27 – Seager equation for number of habitable planets
27:48 – Exoplanets
34:44 – Earth-like exoplanets
40:43 – Intelligent life
52:34 – Number of planets per star
55:09 – Space exploration
57:36 – Traveling to Proxima Centauri
1:00:52 – Starshade
1:07:34 – Using the sun as a gravitational lens
1:09:44 – Starshot
1:12:45 – Rogue planets
1:15:44 – The Smallest Lights in the Universe
1:30:15 – Book recommendations
1:37:48 – Advice for a young person
1:39:29 – Meaning of life

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Dileep George is a researcher at the intersection of neuroscience and artificial intelligence, co-founder of Vicarious, formerly co-founder of Numenta. From the early work on Hierarchical temporal memory to Recursive Cortical Networks to today, Dileep’s always sought to engineer intelligence that is closely inspired by the human brain.

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– Babbel: https://babbel.com and use code LEX
– MasterClass: https://masterclass.com/lex
– Raycon: https://buyraycon.com/lex

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:
0:00 – Introduction
4:50 – Building a model of the brain
17:11 – Visual cortex
27:50 – Probabilistic graphical models
31:35 – Encoding information in the brain
36:56 – Recursive Cortical Network
51:09 – Solving CAPTCHAs algorithmically
1:06:48 – Hype around brain-inspired AI
1:18:21 – How does the brain learn?
1:21:32 – Perception and cognition
1:25:43 – Open problems in brain-inspired AI
1:30:33 – GPT-3
1:40:41 – Memory
1:45:08 – Neuralink
1:51:32 – Consciousness
1:57:59 – Book recommendations
2:06:49 – Meaning of life

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Russ Tedrake is a roboticist and professor at MIT and vice president of robotics research at TRI. He works on control of robots in interesting, complicated, underactuated, stochastic, difficult to model situations.

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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
04:29 – Passive dynamic walking
09:40 – Animal movement
13:34 – Control vs Dynamics
15:49 – Bipedal walking
20:56 – Running barefoot
33:01 – Think rigorously with machine learning
44:05 – DARPA Robotics Challenge
1:07:14 – When will a robot become UFC champion
1:18:32 – Black Mirror Robot Dog
1:34:01 – Robot control
1:47:00 – Simulating robots
2:00:33 – Home robotics
2:03:40 – Soft robotics
2:07:25 – Underactuated robotics
2:20:42 – Touch
2:28:55 – Book recommendations
2:40:08 – Advice to young people
2:44:20 – Meaning of life

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Manolis Kellis is a professor at MIT and head of the MIT Computational Biology Group. He is interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives.

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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
03:54 – Human genome
17:47 – Sources of knowledge
29:15 – Free will
33:26 – Simulation
35:17 – Biological and computing
50:10 – Genome-wide evolutionary signatures
56:54 – Evolution of COVID-19
1:02:59 – Are viruses intelligent?
1:12:08 – Humans vs viruses
1:19:39 – Engineered pandemics
1:23:23 – Immune system
1:33:22 – Placebo effect
1:35:39 – Human genome source code
1:44:40 – Mutation
1:51:46 – Deep learning
1:58:08 – Neuralink
2:07:07 – Language
2:15:19 – Meaning of life

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Ian Hutchinson is a nuclear engineer and plasma physicist at MIT. He has made a number of important contributions in plasma physics including the magnetic confinement of plasmas seeking to enable fusion reactions, which is the energy source of the stars, to be used for practical energy production. Current nuclear reactors are based on fission as we discuss. Ian has also written on the philosophy of science and the relationship between science and religion.

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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
05:32 – Nuclear physics and plasma physics
08:00 – Fusion energy
35:22 – Nuclear weapons
42:06 – Existential risks
50:29 – Personal journey in religion
56:27 – What is God like?
1:01:34 – Scientism
1:04:21 – Atheism
1:06:39 – Not knowing
1:09:57 – Faith
1:13:46 – The value of loyalty and love
1:23:26 – Why is there suffering in the world
1:35:08 – AGI
1:40:27 – Consciousness
1:48:14 – Simulation
1:52:20 – Adam and Eve
1:54:57 – Meaning of life

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Richard Karp is a professor at Berkeley and one of the most important figures in the history of theoretical computer science. In 1985, he received the Turing Award for his research in the theory of algorithms, including the development of the Edmonds–Karp algorithm for solving the maximum flow problem on networks, Hopcroft–Karp algorithm for finding maximum cardinality matchings in bipartite graphs, and his landmark paper in complexity theory called “Reducibility Among Combinatorial Problems”, in which he proved 21 problems to be NP-complete. This paper was probably the most important catalyst in the explosion of interest in the study of NP-completeness and the P vs NP problem.

Support this podcast by supporting our sponsors:
– Eight Sleep: https://eightsleep.com/lex
– Cash App – use code “LexPodcast” and download:
– Cash App (App Store): https://apple.co/2sPrUHe
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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
03:50 – Geometry
09:46 – Visualizing an algorithm
13:00 – A beautiful algorithm
18:06 – Don Knuth and geeks
22:06 – Early days of computers
25:53 – Turing Test
30:05 – Consciousness
33:22 – Combinatorial algorithms
37:42 – Edmonds-Karp algorithm
40:22 – Algorithmic complexity
50:25 – P=NP
54:25 – NP-Complete problems
1:10:29 – Proving P=NP
1:12:57 – Stable marriage problem
1:20:32 – Randomized algorithms
1:33:23 – Can a hard problem be easy in practice?
1:43:57 – Open problems in theoretical computer science
1:46:21 – A strange idea in complexity theory
1:50:49 – Machine learning
1:56:26 – Bioinformatics
2:00:37 – Memory of Richard’s father

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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
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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

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Brian Kernighan is a professor of computer science at Princeton University. He co-authored the C Programming Language with Dennis Ritchie (creator of C) and has written a lot of books on programming, computers, and life including the Practice of Programming, the Go Programming Language, his latest UNIX: A History and a Memoir. He co-created AWK, the text processing language used by Linux folks like myself. He co-designed AMPL, an algebraic modeling language for large-scale optimization.

Support this podcast by supporting our sponsors:
– Eight Sleep: https://eightsleep.com/lex
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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
04:24 – UNIX early days
22:09 – Unix philosophy
31:54 – Is programming art or science?
35:18 – AWK
42:03 – Programming setup
46:39 – History of programming languages
52:48 – C programming language
58:44 – Go language
1:01:57 – Learning new programming languages
1:04:57 – Javascript
1:08:16 – Variety of programming languages
1:10:30 – AMPL
1:18:01 – Graph theory
1:22:20 – AI in 1964
1:27:50 – Future of AI
1:29:47 – Moore’s law
1:32:54 – Computers in our world
1:40:37 – Life