Author Archives: Lex Fridman

Paul Krugman: Economics of Innovation, Automation, Safety Nets & Universal Basic Income

Paul Krugman is a Nobel Prize winner in economics, professor at CUNY, and columnist at the New York Times. His academic work centers around international economics, economic geography, liquidity traps, and currency crises.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:44 – Utopia from an economics perspective
04:51 – Competition
06:33 – Well-informed citizen
07:52 – Disagreements in economics
09:57 – Metrics of outcomes
13:00 – Safety nets
15:54 – Invisible hand of the market
21:43 – Regulation of tech sector
22:48 – Automation
25:51 – Metric of productivity
30:35 – Interaction of the economy and politics
33:48 – Universal basic income
36:40 – Divisiveness of political discourse
42:53 – Economic theories
52:25 – Starting a system on Mars from scratch
55:11 – International trade
59:08 – Writing in a time of radicalization and Twitter mobs

Ayanna Howard: Human-Robot Interaction and Ethics of Safety-Critical Systems

Ayanna Howard is a roboticist and professor at Georgia Tech, director of Human-Automation Systems lab, with research interests in human-robot interaction, assistive robots in the home, therapy gaming apps, and remote robotic exploration of extreme environments.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:09 – Favorite robot
05:05 – Autonomous vehicles
08:43 – Tesla Autopilot
20:03 – Ethical responsibility of safety-critical algorithms
28:11 – Bias in robotics
38:20 – AI in politics and law
40:35 – Solutions to bias in algorithms
47:44 – HAL 9000
49:57 – Memories from working at NASA
51:53 – SpotMini and Bionic Woman
54:27 – Future of robots in space
57:11 – Human-robot interaction
1:02:38 – Trust
1:09:26 – AI in education
1:15:06 – Andrew Yang, automation, and job loss
1:17:17 – Love, AI, and the movie Her
1:25:01 – Why do so many robotics companies fail?
1:32:22 – Fear of robots
1:34:17 – Existential threats of AI
1:35:57 – Matrix
1:37:37 – Hang out for a day with a robot

Daniel Kahneman: Thinking Fast and Slow, Deep Learning, and AI

Daniel Kahneman is winner of the Nobel Prize in economics for his integration of economic science with the psychology of human behavior, judgment and decision-making. He is the author of the popular book “Thinking, Fast and Slow” that summarizes in an accessible way his research of several decades, often in collaboration with Amos Tversky, on cognitive biases, prospect theory, and happiness. The central thesis of this work is a dichotomy between two modes of thought: “System 1” is fast, instinctive and emotional; “System 2” is slower, more deliberative, and more logical. The book delineates cognitive biases associated with each type of thinking.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:36 – Lessons about human behavior from WWII
08:19 – System 1 and system 2: thinking fast and slow
15:17 – Deep learning
30:01 – How hard is autonomous driving?
35:59 – Explainability in AI and humans
40:08 – Experiencing self and the remembering self
51:58 – Man’s Search for Meaning by Viktor Frankl
54:46 – How much of human behavior can we study in the lab?
57:57 – Collaboration
1:01:09 – Replication crisis in psychology
1:09:28 – Disagreements and controversies in psychology
1:13:01 – Test for AGI
1:16:17 – Meaning of life

Grant Sanderson: 3Blue1Brown and the Beauty of Mathematics

Grant Sanderson is a math educator and creator of 3Blue1Brown, a popular YouTube channel that uses programmatically-animated visualizations to explain concepts in linear algebra, calculus, and other fields of mathematics.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
01:56 – What kind of math would aliens have?
03:48 – Euler’s identity and the least favorite piece of notation
10:31 – Is math discovered or invented?
14:30 – Difference between physics and math
17:24 – Why is reality compressible into simple equations?
21:44 – Are we living in a simulation?
26:27 – Infinity and abstractions
35:48 – Most beautiful idea in mathematics
41:32 – Favorite video to create
45:04 – Video creation process
50:04 – Euler identity
51:47 – Mortality and meaning
55:16 – How do you know when a video is done?
56:18 – What is the best way to learn math for beginners?
59:17 – Happy moment

Stephen Kotkin: Stalin, Putin, and the Nature of Power

Stephen Kotkin is a professor of history at Princeton university and one of the great historians of our time, specializing in Russian and Soviet history. He has written many books on Stalin and the Soviet Union including the first 2 of a 3 volume work on Stalin, and he is currently working on volume 3.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
Stalin (book, vol 1): https://amzn.to/2FjdLF2
Stalin (book, vol 2): https://amzn.to/2tqyjc3

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:10 – Do all human beings crave power?
11:29 – Russian people and authoritarian power
15:06 – Putin and the Russian people
23:23 – Corruption in Russia
31:30 – Russia’s future
41:07 – Individuals and institutions
44:42 – Stalin’s rise to power
1:05:20 – What is the ideal political system?
1:21:10 – Questions for Putin
1:29:41 – Questions for Stalin
1:33:25 – Will there always be evil in the world?

Donald Knuth: Algorithms, TeX, Life, and The Art of Computer Programming

Donald Knuth is one of the greatest and most impactful computer scientists and mathematicians ever. He is the recipient in 1974 of the Turing Award, considered the Nobel Prize of computing. He is the author of the multi-volume work, the magnum opus, The Art of Computer Programming. He made several key contributions to the rigorous analysis of the computational complexity of algorithms. He popularized asymptotic notation, that we all affectionately know as the big-O notation. He also created the TeX typesetting which most computer scientists, physicists, mathematicians, and scientists and engineers use to write technical papers and make them look beautiful.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
The Art of Computer Programming (book set)

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:45 – IBM 650
07:51 – Geeks
12:29 – Alan Turing
14:26 – My life is a convex combination of english and mathematics
24:00 – Japanese arrow puzzle example
25:42 – Neural networks and machine learning
27:59 – The Art of Computer Programming
36:49 – Combinatorics
39:16 – Writing process
42:10 – Are some days harder than others?
48:36 – What’s the “Art” in the Art of Computer Programming
50:21 – Binary (boolean) decision diagram
55:06 – Big-O notation
58:02 – P=NP
1:10:05 – Artificial intelligence
1:13:26 – Ant colonies and human cognition
1:17:11 – God and the Bible
1:24:28 – Reflection on life
1:28:25 – Facing mortality
1:33:40 – TeX and beautiful typography
1:39:23 – How much of the world do we understand?
1:44:17 – Question for God

Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI

Melanie Mitchell is a professor of computer science at Portland State University and an external professor at Santa Fe Institute. She has worked on and written about artificial intelligence from fascinating perspectives including adaptive complex systems, genetic algorithms, and the Copycat cognitive architecture which places the process of analogy making at the core of human cognition. From her doctoral work with her advisors Douglas Hofstadter and John Holland to today, she has contributed a lot of important ideas to the field of AI, including her recent book, simply called Artificial Intelligence: A Guide for Thinking Humans.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
AI: A Guide for Thinking Humans (book)

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:33 – The term “artificial intelligence”
06:30 – Line between weak and strong AI
12:46 – Why have people dreamed of creating AI?
15:24 – Complex systems and intelligence
18:38 – Why are we bad at predicting the future with regard to AI?
22:05 – Are fundamental breakthroughs in AI needed?
25:13 – Different AI communities
31:28 – Copycat cognitive architecture
36:51 – Concepts and analogies
55:33 – Deep learning and the formation of concepts
1:09:07 – Autonomous vehicles
1:20:21 – Embodied AI and emotion
1:25:01 – Fear of superintelligent AI
1:36:14 – Good test for intelligence
1:38:09 – What is complexity?
1:43:09 – Santa Fe Institute
1:47:34 – Douglas Hofstadter
1:49:42 – Proudest moment

Jim Gates: Supersymmetry, String Theory and Proving Einstein Right

Jim Gates (S James Gates Jr.) is a theoretical physicist and professor at Brown University working on supersymmetry, supergravity, and superstring theory. He served on former President Obama’s Council of Advisors on Science and Technology. He is the co-author of a new book titled Proving Einstein Right about the scientists who set out to prove Einstein’s theory of relativity.

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 Apple Podcasts, follow on Spotify, or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode Links:
Proving Einstein Right (book)

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:13 – Will we ever venture outside our solar system?
05:16 – When will the first human step foot on Mars?
11:14 – Are we alone in the universe?
13:55 – Most beautiful idea in physics
16:29 – Can the mind be digitized?
21:15 – Does the possibility of superintelligence excite you?
22:25 – Role of dreaming in creativity and mathematical thinking
30:51 – Existential threats
31:46 – Basic particles underlying our universe
41:28 – What is supersymmetry?
52:19 – Adinkra symbols
1:00:24 – String theory
1:07:02 – Proving Einstein right and experimental validation of general relativity
1:19:07 – Richard Feynman
1:22:01 – Barack Obama’s Council of Advisors on Science and Technology
1:30:20 – Exciting problems in physics that are just within our reach
1:31:26 – Mortality

Sebastian Thrun: Flying Cars, Autonomous Vehicles, and Education

Sebastian Thrun is one of the greatest roboticists, computer scientists, and educators of our time. He led development of the autonomous vehicles at Stanford that won the 2005 DARPA Grand Challenge and placed second in the 2007 DARPA Urban Challenge. He then led the Google self-driving car program which launched the self-driving revolution. He taught the popular Stanford course on Artificial Intelligence in 2011 which was one of the first MOOCs. That experience led him to co-found Udacity, an online education platform. He is also the CEO of Kitty Hawk, a company working on building flying cars or more technically eVTOLS which stands for electric vertical take-off and landing aircraft.

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 Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
03:24 – The Matrix
04:39 – Predicting the future 30+ years ago
06:14 – Machine learning and expert systems
09:18 – How to pick what ideas to work on
11:27 – DARPA Grand Challenges
17:33 – What does it take to be a good leader?
23:44 – Autonomous vehicles
38:42 – Waymo and Tesla Autopilot
42:11 – Self-Driving Car Nanodegree
47:29 – Machine learning
51:10 – AI in medical applications
54:06 – AI-related job loss and education
57:51 – Teaching soft skills
1:00:13 – Kitty Hawk and flying cars
1:08:22 – Love and AI
1:13:12 – Life

Michael Stevens: Vsauce

Michael Stevens is the creator of Vsauce, one of the most popular educational YouTube channel in the world, with over 15 million subscribers and over 1.7 billion views. His videos often ask and answer questions that are both profound and entertaining, spanning topics from physics to psychology. As part of his channel he created 3 seasons of Mind Field, a series that explored human behavior.

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 Apple Podcasts or support it on Patreon.

This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”. 

Episode links:
Vsauce YouTube: https://www.youtube.com/Vsauce
Vsauce Twitter: https://twitter.com/tweetsauce
Vsauce Instagram: https://www.instagram.com/electricpants/

Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.

00:00 – Introduction
02:26 – Psychology
03:59 – Consciousness
06:55 – Free will
07:55 – Perception vs reality
09:59 – Simulation
11:32 – Science
16:24 – Flat earth
27:04 – Artificial Intelligence
30:14 – Existential threats
38:03 – Elon Musk and the responsibility of having a large following
43:05 – YouTube algorithm
52:41 – Mortality and the meaning of life