Jim Keller is a legendary microprocessor engineer, having worked at AMD, Apple, Tesla, and now Intel. He’s known for his work on the AMD K7, K8, K12 and Zen microarchitectures, Apple A4, A5 processors, and co-author of the specifications for the x86-64 instruction set and HyperTransport interconnect. 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 02:12 – Difference between a computer and a human brain 03:43 – Computer abstraction layers and parallelism 17:53 – If you run a program multiple times, do you always get the same answer? 20:43 – Building computers and teams of people 22:41 – Start from scratch every 5 years 30:05 – Moore’s law is not dead 55:47 – Is superintelligence the next layer of abstraction? 1:00:02 – Is the universe a computer? 1:03:00 – Ray Kurzweil and exponential improvement in technology 1:04:33 – Elon Musk and Tesla Autopilot 1:20:51 – Lessons from working with Elon Musk 1:28:33 – Existential threats from AI 1:32:38 – Happiness and the meaning of life

David Chalmers is a philosopher and cognitive scientist specializing in philosophy of mind, philosophy of language, and consciousness. He is perhaps best known for formulating the hard problem of consciousness which could be stated as “why does the feeling which accompanies awareness of sensory information exist at all?” 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 02:23 – Nature of reality: Are we living in a simulation? 19:19 – Consciousness in virtual reality 27:46 – Music-color synesthesia 31:40 – What is consciousness? 51:25 – Consciousness and the meaning of life 57:33 – Philosophical zombies 1:01:38 – Creating the illusion of consciousness 1:07:03 – Conversation with a clone 1:11:35 – Free will 1:16:35 – Meta-problem of consciousness 1:18:40 – Is reality an illusion? 1:20:53 – Descartes’ evil demon 1:23:20 – Does AGI need conscioussness? 1:33:47 – Exciting future 1:35:32 – Immortality

Cristos Goodrow is VP of Engineering at Google and head of Search and Discovery at YouTube (aka YouTube Algorithm). 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 03:26 – Life-long trajectory through YouTube 07:30 – Discovering new ideas on YouTube 13:33 – Managing healthy conversation 23:02 – YouTube Algorithm 38:00 – Analyzing the content of video itself 44:38 – Clickbait thumbnails and titles 47:50 – Feeling like I’m helping the YouTube algorithm get smarter 50:14 – Personalization 51:44 – What does success look like for the algorithm? 54:32 – Effect of YouTube on society 57:24 – Creators 59:33 – Burnout 1:03:27 – YouTube algorithm: heuristics, machine learning, human behavior 1:08:36 – How to make a viral video? 1:10:27 – Veritasium: Why Are 96,000,000 Black Balls on This Reservoir? 1:13:20 – Making clips from long-form podcasts 1:18:07 – Moment-by-moment signal of viewer interest 1:20:04 – Why is video understanding such a difficult AI problem? 1:21:54 – Self-supervised learning on video 1:25:44 – What does YouTube look like 10, 20, 30 years from now?

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 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 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 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 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 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 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 (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 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