Lex Fridman Podcast

Karl Friston is one of the greatest neuroscientists in history, cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including the fascinating idea of the free-energy principle for action and perception. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Karl’s Website: https://www.fil.ion.ucl.ac.uk/~karl/ Karl’s Wiki: https://en.wikipedia.org/wiki/Karl_J._Friston 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. 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 01:50 – How much of the human brain do we understand? 05:53 – Most beautiful characteristic of the human brain 10:43 – Brain imaging 20:38 – Deep structure 21:23 – History of brain imaging 32:31 – Neuralink and brain-computer interfaces 43:05 – Free energy principle 1:24:29 – Meaning of life

Sertac Karaman is a professor at MIT, co-founder of the autonomous vehicle company Optimus Ride, and is one of top roboticists in the world, including robots that drive and robots that fly. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Sertac’s Website: http://sertac.scripts.mit.edu/web/ Sertac’s Twitter: https://twitter.com/sertackaraman Optimus Ride: https://www.optimusride.com/ 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. 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 01:44 – Autonomous flying vs autonomous driving 06:37 – Flying cars 10:27 – Role of simulation in robotics 17:35 – Game theory and robotics 24:30 – Autonomous vehicle company strategies 29:46 – Optimus Ride 47:08 – Waymo, Tesla, Optimus Ride timelines 53:22 – Achieving the impossible 53:50 – Iterative learning 58:39 – Is Lidar is a crutch? 1:03:21 – Fast autonomous flight 1:18:06 – Most beautiful idea in robotics

Stephen Schwarzman is the CEO and Co-Founder of Blackstone, one of the world’s leading investment firms with over 530 billion dollars of assets under management. He is one of the most successful business leaders in history, all from humble beginnings back in Philly. I recommend his recent book called What It Takes that tells stories and lessons from this personal journey. Support this podcast by signing up with these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – MasterClass: https://masterclass.com/lex EPISODE LINKS: What It Takes (book): https://amzn.to/2WX9cZu 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. 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 04:17 – Going big in business 07:34 – How to recognize an opportunity 16:00 – Solving problems that people have 25:26 – Philanthropy 32:51 – Hope for the new College of Computing at MIT 37:32 – Unintended consequences of technological innovation 42:24 – Education systems in China and United States 50:22 – American AI Initiative 59:53 – Starting a business is a rough ride 1:04:26 – Love and family

Dawn Song is a professor of computer science at UC Berkeley with research interests in security, most recently with a focus on the intersection between computer security and machine learning. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Dawn’s Twitter: https://twitter.com/dawnsongtweets Dawn’s Website: https://people.eecs.berkeley.edu/~dawnsong/ Oasis Labs: https://www.oasislabs.com 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. 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 01:53 – Will software always have security vulnerabilities? 09:06 – Human are the weakest link in security 16:50 – Adversarial machine learning 51:27 – Adversarial attacks on Tesla Autopilot and self-driving cars 57:33 – Privacy attacks 1:05:47 – Ownership of data 1:22:13 – Blockchain and cryptocurrency 1:32:13 – Program synthesis 1:44:57 – A journey from physics to computer science 1:56:03 – US and China 1:58:19 – Transformative moment 2:00:02 – Meaning of life

Ilya Sutskever is the co-founder of OpenAI, is one of the most cited computer scientist in history with over 165,000 citations, and to me, is one of the most brilliant and insightful minds ever in the field of deep learning. There are very few people in this world who I would rather talk to and brainstorm with about deep learning, intelligence, and life than Ilya, on and off the mic. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Ilya’s Twitter: https://twitter.com/ilyasut Ilya’s Website: https://www.cs.toronto.edu/~ilya/ 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. 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 02:23 – AlexNet paper and the ImageNet moment 08:33 – Cost functions 13:39 – Recurrent neural networks 16:19 – Key ideas that led to success of deep learning 19:57 – What’s harder to solve: language or vision? 29:35 – We’re massively underestimating deep learning 36:04 – Deep double descent 41:20 – Backpropagation 42:42 – Can neural networks be made to reason? 50:35 – Long-term memory 56:37 – Language models 1:00:35 – GPT-2 1:07:14 – Active learning 1:08:52 – Staged release of AI systems 1:13:41 – How to build AGI? 1:25:00 – Question to AGI 1:32:07 – Meaning of life

Daphne Koller is a professor of computer science at Stanford University, a co-founder of Coursera with Andrew Ng and Founder and CEO of insitro, a company at the intersection of machine learning and biomedicine. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Daphne’s Twitter: https://twitter.com/daphnekoller Daphne’s Website: https://ai.stanford.edu/users/koller/index.html Insitro: http://insitro.com 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. 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 02:22 – Will we one day cure all disease? 06:31 – Longevity 10:16 – Role of machine learning in treating diseases 13:05 – A personal journey to medicine 16:25 – Insitro and disease-in-a-dish models 33:25 – What diseases can be helped with disease-in-a-dish approaches? 36:43 – Coursera and education 49:04 – Advice to people interested in AI 50:52 – Beautiful idea in deep learning 55:10 – Uncertainty in AI 58:29 – AGI and AI safety 1:06:52 – Are most people good? 1:09:04 – Meaning of life

Harry Cliff is a particle physicist at the University of Cambridge working on the Large Hadron Collider beauty experiment that specializes in searching for hints of new particles and forces by studying a type of particle called the “beauty quark”, or “b quark”. In this way, he is part of the group of physicists who are searching answers to some of the biggest questions in modern physics. He is also an exceptional communicator of science with some of the clearest and most captivating explanations of basic concepts in particle physics I’ve ever heard. Support this podcast by signing up with these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Harry’s Website: https://www.harrycliff.co.uk/ Harry’s Twitter: https://twitter.com/harryvcliff Beyond the Higgs Lecture: https://www.youtube.com/watch?v=edvdzh9Pggg Harry’s stand-up: https://www.youtube.com/watch?v=dnediKM_Sts 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. 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 03:51 – LHC and particle physics 13:55 – History of particle physics 38:59 – Higgs particle 57:55 – Unknowns yet to be discovered 59:48 – Beauty quarks 1:07:38 – Matter and antimatter 1:10:22 – Human side of the Large Hadron Collider 1:17:27 – Future of large particle colliders 1:24:09 – Data science with particle physics 1:27:17 – Science communication 1:33:36 – Most beautiful idea in physics

Jack Dorsey is the co-founder and CEO of Twitter and the founder and CEO of Square. Support this podcast by signing up with these sponsors: – MasterClass: https://masterclass.com/lex EPISODE LINKS: Jack’s Twitter: https://twitter.com/jack Start Small Tracker: https://bit.ly/2KxdiBL 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. 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 02:48 – Engineering at scale 08:36 – Increasing access to the economy 13:09 – Machine learning at Square 15:18 – Future of the digital economy 17:17 – Cryptocurrency 25:31 – Artificial intelligence 27:49 – Her 29:12 – Exchange with Elon Musk about bots 32:05 – Concerns about artificial intelligence 35:40 – Andrew Yang 40:57 – Eating one meal a day 45:49 – Mortality 47:50 – Meaning of life 48:59 – Simulation

Dmitry Korkin is a professor of bioinformatics and computational biology at Worcester Polytechnic Institute, where he specializes in bioinformatics of complex disease, computational genomics, systems biology, and biomedical data analytics. I came across Dmitry’s work when in February his group used the viral genome of the COVID-19 to reconstruct the 3D structure of its major viral proteins and their interactions with human proteins, in effect creating a structural genomics map of the coronavirus and making this data open and available to researchers everywhere. We talked about the biology of COVID-19, SARS, and viruses in general, and how computational methods can help us understand their structure and function in order to develop antiviral drugs and vaccines. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Dmitry’s Website: http://korkinlab.org/ Dmitry’s Twitter: https://twitter.com/dmkorkin Dmitry’s Paper that we discuss: https://bit.ly/3eKghEM 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. 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 02:33 – Viruses are terrifying and fascinating 06:02 – How hard is it to engineer a virus? 10:48 – What makes a virus contagious? 29:52 – Figuring out the function of a protein 53:27 – Functional regions of viral proteins 1:19:09 – Biology of a coronavirus treatment 1:34:46 – Is a virus alive? 1:37:05 – Epidemiological modeling 1:55:27 – Russia 2:02:31 – Science bobbleheads 2:06:31 – Meaning of life

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist who is the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram Alpha, Wolfram Language, and the new Wolfram Physics project. He is the author of several books including A New Kind of Science, which on a personal note was one of the most influential books in my journey in computer science and artificial intelligence. Support this podcast by signing up with these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Stephen’s Twitter: https://twitter.com/stephen_wolfram Stephen’s Website: https://www.stephenwolfram.com/ Wolfram Research Twitter: https://twitter.com/WolframResearch Wolfram Research YouTube: https://www.youtube.com/user/WolframResearch Wolfram Research Website: https://www.wolfram.com/ Wolfram Alpha: https://www.wolframalpha.com/ A New Kind of Science (book): https://amzn.to/34JruB2 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. 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 04:16 – Communicating with an alien intelligence 12:11 – Monolith in 2001: A Space Odyssey 29:06 – What is computation? 44:54 – Physics emerging from computation 1:14:10 – Simulation 1:19:23 – Fundamental theory of physics 1:28:01 – Richard Feynman 1:39:57 – Role of ego in science 1:47:21 – Cellular automata 2:15:08 – Wolfram language 2:55:14 – What is intelligence? 2:57:47 – Consciousness 3:02:36 – Mortality 3:05:47 – Meaning of life

Eric Weinstein is a mathematician with a bold and piercing intelligence, unafraid to explore the biggest questions in the universe and shine a light on the darkest corners of our society. He is the host of The Portal podcast, a part of which, he recently released his 2013 Oxford lecture on his theory of Geometric Unity that is at the center of his lifelong efforts in arriving at a theory of everything that unifies the fundamental laws of physics. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Eric’s Twitter: https://twitter.com/EricRWeinstein Eric’s YouTube: https://www.youtube.com/ericweinsteinphd The Portal podcast: https://podcasts.apple.com/us/podcast/the-portal/id1469999563 Graph, Wall, Tome wiki: https://theportal.wiki/wiki/Graph,_Wall,_Tome 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. 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 02:08 – World War II and the Coronavirus Pandemic 14:03 – New leaders 31:18 – Hope for our time 34:23 – WHO 44:19 – Geometric unity 1:38:55 – We need to get off this planet 1:40:47 – Elon Musk 1:46:58 – Take Back MIT 2:15:31 – The time at Harvard 2:37:01 – The Portal 2:42:58 – Legacy

Richard Dawkins is an evolutionary biologist, and author of The Selfish Gene, The Blind Watchmaker, The God Delusion, The Magic of Reality, The Greatest Show on Earth, and his latest Outgrowing God. He is the originator and popularizer of a lot of fascinating ideas in evolutionary biology and science in general, including funny enough the introduction of the word meme in his 1976 book The Selfish Gene, which in the context of a gene-centered view of evolution is an exceptionally powerful idea. He is outspoken, bold, and often fearless in his defense of science and reason, and in this way, is one of the most influential thinkers of our time. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Richard’s Website: https://www.richarddawkins.net/ Richard’s Twitter: https://twitter.com/RichardDawkins Richard’s Books: – Selfish Gene: https://amzn.to/34tpHQy – The Magic of Reality: https://amzn.to/3c0aqZQ – The Blind Watchmaker: https://amzn.to/2RqV5tH – The God Delusion: https://amzn.to/2JPrxlc – Outgrowing God: https://amzn.to/3ebFess – The Greatest Show on Earth: https://amzn.to/2Rp2j1h 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. 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 02:31 – Intelligent life in the universe 05:03 – Engineering intelligence (are there shortcuts?) 07:06 – Is the evolutionary process efficient? 10:39 – Human brain and AGI 15:31 – Memes 26:37 – Does society need religion? 33:10 – Conspiracy theories 39:10 – Where do morals come from in humans? 46:10 – AI began with the ancient wish to forge the gods 49:18 – Simulation 56:58 – Books that influenced you 1:02:53 – Meaning of life

David Silver leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo, AlphaZero and co-lead on AlphaStar, and MuZero and lot of important work in reinforcement learning. Support this podcast by signing up with these sponsors: – MasterClass: https://masterclass.com/lex – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Reinforcement learning (book): https://amzn.to/2Jwp5zG 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. 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 04:09 – First program 11:11 – AlphaGo 21:42 – Rule of the game of Go 25:37 – Reinforcement learning: personal journey 30:15 – What is reinforcement learning? 43:51 – AlphaGo (continued) 53:40 – Supervised learning and self play in AlphaGo 1:06:12 – Lee Sedol retirement from Go play 1:08:57 – Garry Kasparov 1:14:10 – Alpha Zero and self play 1:31:29 – Creativity in AlphaZero 1:35:21 – AlphaZero applications 1:37:59 – Reward functions 1:40:51 – Meaning of life

Roger Penrose is physicist, mathematician, and philosopher at University of Oxford. He has made fundamental contributions in many disciplines from the mathematical physics of general relativity and cosmology to the limitations of a computational view of consciousness. Support this podcast by signing up with these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Cycles of Time (book): https://amzn.to/39tXtpp The Emperor’s New Mind (book): https://amzn.to/2yfeVkD 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. 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 03:51 – 2001: A Space Odyssey 09:43 – Consciousness and computation 23:45 – What does it mean to “understand” 31:37 – What’s missing in quantum mechanics? 40:09 – Whatever consciousness is, it’s not a computation 44:13 – Source of consciousness in the human brain 1:02:57 – Infinite cycles of big bangs 1:22:05 – Most beautiful idea in mathematics

Nick Bostrom is a philosopher at University of Oxford and the director of the Future of Humanity Institute. He has worked on fascinating and important ideas in existential risks, simulation hypothesis, human enhancement ethics, and the risks of superintelligent AI systems, including in his book Superintelligence. I can see talking to Nick multiple times on this podcast, many hours each time, but we have to start somewhere. Support this podcast by signing up with these sponsors: – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Nick’s website: https://nickbostrom.com/ Future of Humanity Institute: – https://twitter.com/fhioxford – https://www.fhi.ox.ac.uk/ Books: – Superintelligence: https://amzn.to/2JckX83 Wikipedia: – https://en.wikipedia.org/wiki/Simulation_hypothesis – https://en.wikipedia.org/wiki/Principle_of_indifference – https://en.wikipedia.org/wiki/Doomsday_argument – https://en.wikipedia.org/wiki/Global_catastrophic_risk 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. 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 02:48 – Simulation hypothesis and simulation argument 12:17 – Technologically mature civilizations 15:30 – Case 1: if something kills all possible civilizations 19:08 – Case 2: if we lose interest in creating simulations 22:03 – Consciousness 26:27 – Immersive worlds 28:50 – Experience machine 41:10 – Intelligence and consciousness 48:58 – Weighing probabilities of the simulation argument 1:01:43 – Elaborating on Joe Rogan conversation 1:05:53 – Doomsday argument and anthropic reasoning 1:23:02 – Elon Musk 1:25:26 – What’s outside the simulation? 1:29:52 – Superintelligence 1:47:27 – AGI utopia 1:52:41 – Meaning of life

Simon Sinek is an author of several books including Start With Why, Leaders Eat Last, and his latest The Infinite Game. He is one of the best communicators of what it takes to be a good leader, to inspire, and to build businesses that solve big difficult challenges. Support this podcast by signing up with these sponsors: – MasterClass: https://masterclass.com/lex – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Simon twitter: https://twitter.com/simonsinek Simon facebook: https://www.facebook.com/simonsinek Simon website: https://simonsinek.com/ Books: – Infinite Game: https://amzn.to/2WxBH1i – Leaders Eat Last: https://amzn.to/2xf70Ds – Start with Why: https://amzn.to/2WxBH1i 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. 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 3:50 – Meaning of life as an infinite game 10:13 – Optimism 13:30 – Mortality 17:52 – Hard work 26:38 – Elon Musk, Steve Jobs, and leadership

Anca Dragan is a professor at Berkeley, working on human-robot interaction — algorithms that look beyond the robot’s function in isolation, and generate robot behavior that accounts for interaction and coordination with human beings. Support this podcast by supporting the sponsors and using the special code: – Download Cash App on the App Store or Google Play & use code “LexPodcast”  EPISODE LINKS: Anca’s Twitter: https://twitter.com/ancadianadragan Anca’s Website: https://people.eecs.berkeley.edu/~anca/ 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. 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 02:26 – Interest in robotics 05:32 – Computer science 07:32 – Favorite robot 13:25 – How difficult is human-robot interaction? 32:01 – HRI application domains 34:24 – Optimizing the beliefs of humans 45:59 – Difficulty of driving when humans are involved 1:05:02 – Semi-autonomous driving 1:10:39 – How do we specify good rewards? 1:17:30 – Leaked information from human behavior 1:21:59 – Three laws of robotics 1:26:31 – Book recommendation 1:29:02 – If a doctor gave you 5 years to live… 1:32:48 – Small act of kindness 1:34:31 – Meaning of life

Vitalik Buterin is co-creator of Ethereum and ether, which is a cryptocurrency that is currently the second-largest digital currency after bitcoin. Ethereum has a lot of interesting technical ideas that are defining the future of blockchain technology, and Vitalik is one of the most brilliant people innovating this space today. Support this podcast by supporting the sponsors with a special code: – Get ExpressVPN at https://www.expressvpn.com/lexpod – Sign up to MasterClass at https://masterclass.com/lex EPISODE LINKS: Vitalik blog: https://vitalik.ca Ethereum whitepaper: http://bit.ly/3cVDTpj Casper FFG (paper): http://bit.ly/2U6j7dJ Quadratic funding (paper): http://bit.ly/3aUZ8Wd Bitcoin whitepaper: https://bitcoin.org/bitcoin.pdf Mastering Ethereum (book): https://amzn.to/2xEjWmE 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. 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 04:43 – Satoshi Nakamoto 08:40 – Anonymity 11:31 – Open source project leadership 13:04 – What is money? 30:02 – Blockchain and cryptocurrency basics 46:51 – Ethereum 59:23 – Proof of work 1:02:12 – Ethereum 2.0 1:13:09 – Beautiful ideas in Ethereum 1:16:59 – Future of cryptocurrency 1:22:06 – Cryptocurrency resources and people to follow 1:24:28 – Role of governments 1:27:27 – Meeting Putin 1:29:41 – Large number of cryptocurrencies 1:32:49 – Mortality

Lee Smolin is a theoretical physicist, co-inventor of loop quantum gravity, and a contributor of many interesting ideas to cosmology, quantum field theory, the foundations of quantum mechanics, theoretical biology, and the philosophy of science. He is the author of several books including one that critiques the state of physics and string theory called The Trouble with Physics, and his latest book, Einstein’s Unfinished Revolution: The Search for What Lies Beyond the Quantum. EPISODE LINKS: Books mentioned: – Einstein’s Unfinished Revolution by Lee Smolin: https://amzn.to/2TsF5c3 – The Trouble With Physics by Lee Smolin: https://amzn.to/2v1FMzy – Against Method by Paul Feyerabend: https://amzn.to/2VOPXCD 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. OUTLINE: 00:00 – Introduction 03:03 – What is real? 05:03 – Scientific method and scientific progress 24:57 – Eric Weinstein and radical ideas in science 29:32 – Quantum mechanics and general relativity 47:24 – Sean Carroll and many-worlds interpretation of quantum mechanics 55:33 – Principles in science 57:24 – String theory

Ann Druyan is the writer, producer, director, and one of the most important and impactful communicators of science in our time. She co-wrote the 1980 science documentary series Cosmos hosted by Carl Sagan, whom she married in 1981, and her love for whom, with the help of NASA, was recorded as brain waves on a golden record along with other things our civilization has to offer and launched into space on the Voyager 1 and Voyager 2 spacecraft that are now, 42 years later, still active, reaching out farther into deep space than any human-made object ever has. This was a profound and beautiful decision she made as a Creative Director of NASA’s Voyager Interstellar Message Project. In 2014, she went on to create the second season of Cosmos, called Cosmos: A Spacetime Odyssey, and in 2020, the new third season called Cosmos: Possible Worlds, which is being released this upcoming Monday, March 9. It is hosted, once again, by the fun and brilliant Neil deGrasse Tyson. EPISODE LINKS: Cosmos Twitter: https://twitter.com/COSMOSonTV Cosmos Website: https://fox.tv/CosmosOnTV 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. OUTLINE: 00:00 – Introduction 03:24 – Role of science in society 07:04 – Love and science 09:07 – Skepticism in science 14:15 – Voyager, Carl Sagan, and the Golden Record 36:41 – Cosmos 53:22 – Existential threats 1:00:36 – Origin of life 1:04:22 – Mortality

Alex Garland is a writer and director of many imaginative and philosophical films from the dreamlike exploration of human self-destruction in the movie Annihilation to the deep questions of consciousness and intelligence raised in the movie Ex Machina, which to me is one of the greatest movies on artificial intelligence ever made. I’m releasing this podcast to coincide with the release of his new series called Devs that will premiere this Thursday, March 5, on Hulu. EPISODE LINKS: Devs: https://hulu.tv/2x35HaH Annihilation: https://hulu.tv/3ai9Eqk Ex Machina: https://www.netflix.com/title/80023689 Alex IMDb: https://www.imdb.com/name/nm0307497/ Alex Wiki: https://en.wikipedia.org/wiki/Alex_Garland 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. OUTLINE: 00:00 – Introduction 03:42 – Are we living in a dream? 07:15 – Aliens 12:34 – Science fiction: imagination becoming reality 17:29 – Artificial intelligence 22:40 – The new “Devs” series and the veneer of virtue in Silicon Valley 31:50 – Ex Machina and 2001: A Space Odyssey 44:58 – Lone genius 49:34 – Drawing inpiration from Elon Musk 51:24 – Space travel 54:03 – Free will 57:35 – Devs and the poetry of science 1:06:38 – What will you be remembered for?

John Hopfield is professor at Princeton, whose life’s work weaved beautifully through biology, chemistry, neuroscience, and physics. Most crucially, he saw the messy world of biology through the piercing eyes of a physicist. He is perhaps best known for his work on associate neural networks, now known as Hopfield networks that were one of the early ideas that catalyzed the development of the modern field of deep learning. EPISODE LINKS: Now What? article: http://bit.ly/3843LeU John wikipedia: https://en.wikipedia.org/wiki/John_Hopfield Books mentioned: – Einstein’s Dreams: https://amzn.to/2PBa96X – Mind is Flat: https://amzn.to/2I3YB84 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. OUTLINE: 00:00 – Introduction 02:35 – Difference between biological and artificial neural networks 08:49 – Adaptation 13:45 – Physics view of the mind 23:03 – Hopfield networks and associative memory 35:22 – Boltzmann machines 37:29 – Learning 39:53 – Consciousness 48:45 – Attractor networks and dynamical systems 53:14 – How do we build intelligent systems? 57:11 – Deep thinking as the way to arrive at breakthroughs 59:12 – Brain-computer interfaces 1:06:10 – Mortality 1:08:12 – Meaning of life

Marcus Hutter is a senior research scientist at DeepMind and professor at Australian National University. Throughout his career of research, including with Jürgen Schmidhuber and Shane Legg, he has proposed a lot of interesting ideas in and around the field of artificial general intelligence, including the development of the AIXI model which is a mathematical approach to AGI that incorporates ideas of Kolmogorov complexity, Solomonoff induction, and reinforcement learning. EPISODE LINKS: Hutter Prize: http://prize.hutter1.net Marcus web: http://www.hutter1.net Books mentioned: – Universal AI: https://amzn.to/2waIAuw – AI: A Modern Approach: https://amzn.to/3camxnY – Reinforcement Learning: https://amzn.to/2PoANj9 – Theory of Knowledge: https://amzn.to/3a6Vp7x 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. OUTLINE: 00:00 – Introduction 03:32 – Universe as a computer 05:48 – Occam’s razor 09:26 – Solomonoff induction 15:05 – Kolmogorov complexity 20:06 – Cellular automata 26:03 – What is intelligence? 35:26 – AIXI – Universal Artificial Intelligence 1:05:24 – Where do rewards come from? 1:12:14 – Reward function for human existence 1:13:32 – Bounded rationality 1:16:07 – Approximation in AIXI 1:18:01 – Godel machines 1:21:51 – Consciousness 1:27:15 – AGI community 1:32:36 – Book recommendations 1:36:07 – Two moments to relive (past and future)

Michael I. Jordan is a professor at Berkeley, and one of the most influential people in the history of machine learning, statistics, and artificial intelligence. He has been cited over 170,000 times and has mentored many of the world-class researchers defining the field of AI today, including Andrew Ng, Zoubin Ghahramani, Ben Taskar, and Yoshua Bengio. EPISODE LINKS: (Blog post) Artificial Intelligence—The Revolution Hasn’t Happened Yet 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. OUTLINE: 00:00 – Introduction 03:02 – How far are we in development of AI? 08:25 – Neuralink and brain-computer interfaces 14:49 – The term “artificial intelligence” 19:00 – Does science progress by ideas or personalities? 19:55 – Disagreement with Yann LeCun 23:53 – Recommender systems and distributed decision-making at scale 43:34 – Facebook, privacy, and trust 1:01:11 – Are human beings fundamentally good? 1:02:32 – Can a human life and society be modeled as an optimization problem? 1:04:27 – Is the world deterministic? 1:04:59 – Role of optimization in multi-agent systems 1:09:52 – Optimization of neural networks 1:16:08 – Beautiful idea in optimization: Nesterov acceleration 1:19:02 – What is statistics? 1:29:21 – What is intelligence? 1:37:01 – Advice for students 1:39:57 – Which language is more beautiful: English or French?

Andrew Ng is one of the most impactful educators, researchers, innovators, and leaders in artificial intelligence and technology space in general. He co-founded Coursera and Google Brain, launched deeplearning.ai, Landing.ai, and the AI fund, and was the Chief Scientist at Baidu. As a Stanford professor, and with Coursera and deeplearning.ai, he has helped educate and inspire millions of students including me. EPISODE LINKS: Andrew Twitter: https://twitter.com/AndrewYNg Andrew Facebook: https://www.facebook.com/andrew.ng.96 Andrew LinkedIn: https://www.linkedin.com/in/andrewyng/ deeplearning.ai: https://www.deeplearning.ai landing.ai: https://landing.ai AI Fund: https://aifund.ai/ AI for Everyone: https://www.coursera.org/learn/ai-for-everyone The Batch newsletter: https://www.deeplearning.ai/thebatch/ 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”.  This episode is also supported by the Techmeme Ride Home podcast. Get it on Apple Podcasts, on its website, or find it by searching “Ride Home” in your podcast app. 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 02:23 – First few steps in AI 05:05 – Early days of online education 16:07 – Teaching on a whiteboard 17:46 – Pieter Abbeel and early research at Stanford 23:17 – Early days of deep learning 32:55 – Quick preview: deeplearning.ai, landing.ai, and AI fund 33:23 – deeplearning.ai: how to get started in deep learning 45:55 – Unsupervised learning 49:40 – deeplearning.ai (continued) 56:12 – Career in deep learning 58:56 – Should you get a PhD? 1:03:28 – AI fund – building startups 1:11:14 – Landing.ai – growing AI efforts in established companies 1:20:44 – Artificial general intelligence

Scott Aaronson is a professor at UT Austin, director of its Quantum Information Center, and previously a professor at MIT. His research interests center around the capabilities and limits of quantum computers and computational complexity theory more generally. 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”.  This episode is also supported by the Techmeme Ride Home podcast. Get it on Apple Podcasts, on its website, or find it by searching “Ride Home” in your podcast app. 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 05:07 – Role of philosophy in science 29:27 – What is a quantum computer? 41:12 – Quantum decoherence (noise in quantum information) 49:22 – Quantum computer engineering challenges 51:00 – Moore’s Law 56:33 – Quantum supremacy 1:12:18 – Using quantum computers to break cryptography 1:17:11 – Practical application of quantum computers 1:22:18 – Quantum machine learning, questionable claims, and cautious optimism 1:30:53 – Meaning of life

Vladimir Vapnik is the co-inventor of support vector machines, support vector clustering, VC theory, and many foundational ideas in statistical learning. He was born in the Soviet Union, worked at the Institute of Control Sciences in Moscow, then in the US, worked at AT&T, NEC Labs, Facebook AI Research, and now is a professor at Columbia University. His work has been cited over 200,000 times. 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 02:55 – Alan Turing: science and engineering of intelligence 09:09 – What is a predicate? 14:22 – Plato’s world of ideas and world of things 21:06 – Strong and weak convergence 28:37 – Deep learning and the essence of intelligence 50:36 – Symbolic AI and logic-based systems 54:31 – How hard is 2D image understanding? 1:00:23 – Data 1:06:39 – Language 1:14:54 – Beautiful idea in statistical theory of learning 1:19:28 – Intelligence and heuristics 1:22:23 – Reasoning 1:25:11 – Role of philosophy in learning theory 1:31:40 – Music (speaking in Russian) 1:35:08 – Mortality

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

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

Rohit Prasad is the vice president and head scientist of Amazon Alexa and one of its original creators. 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”.  The episode is also supported by ZipRecruiter. Try it: http://ziprecruiter.com/lexpod 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 04:34 – Her 06:31 – Human-like aspects of smart assistants 08:39 – Test of intelligence 13:04 – Alexa prize 21:35 – What does it take to win the Alexa prize? 27:24 – Embodiment and the essence of Alexa 34:35 – Personality 36:23 – Personalization 38:49 – Alexa’s backstory from her perspective 40:35 – Trust in Human-AI relations 44:00 – Privacy 47:45 – Is Alexa listening? 53:51 – How Alexa started 54:51 – Solving far-field speech recognition and intent understanding 1:11:51 – Alexa main categories of skills 1:13:19 – Conversation intent modeling 1:17:47 – Alexa memory and long-term learning 1:22:50 – Making Alexa sound more natural 1:27:16 – Open problems for Alexa and conversational AI 1:29:26 – Emotion recognition from audio and video 1:30:53 – Deep learning and reasoning 1:36:26 – Future of Alexa 1:41:47 – The big picture of conversational AI

Judea Pearl is a professor at UCLA and a winner of the Turing Award, that’s generally recognized as the Nobel Prize of computing. He is one of the seminal figures in the field of artificial intelligence, computer science, and statistics. He has developed and championed probabilistic approaches to AI, including Bayesian Networks and profound ideas in causality in general. These ideas are important not just for AI, but to our understanding and practice of science. But in the field of AI, the idea of causality, cause and effect, to many, lies at the core of what is currently missing and what must be developed in order to build truly intelligent systems. For this reason, and many others, his work is worth returning to often. 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 03:18 – Descartes and analytic geometry 06:25 – Good way to teach math 07:10 – From math to engineering 09:14 – Does God play dice? 10:47 – Free will 11:59 – Probability 22:21 – Machine learning 23:13 – Causal Networks 27:48 – Intelligent systems that reason with causation 29:29 – Do(x) operator 36:57 – Counterfactuals 44:12 – Reasoning by Metaphor 51:15 – Machine learning and causal reasoning 53:28 – Temporal aspect of causation 56:21 – Machine learning (continued) 59:15 – Human-level artificial intelligence 1:04:08 – Consciousness 1:04:31 – Concerns about AGI 1:09:53 – Religion and robotics 1:12:07 – Daniel Pearl 1:19:09 – Advice for students 1:21:00 – Legacy

Whitney Cummings is a stand-up comedian, actor, producer, writer, director, and the host of a new podcast called Good for You. Her most recent Netflix special called “Can I Touch It?” features in part a robot, she affectionately named Bearclaw, that is designed to be visually a replica of Whitney. It’s exciting for me to see one of my favorite comedians explore the social aspects of robotics and AI in our society. She also has some fascinating ideas about human behavior, psychology, and neurology, some of which she explores in her book called “I’m Fine…And Other Lies.” 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”.  The episode is also supported by ZipRecruiter. Try it: http://ziprecruiter.com/lexpod 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 03:51 – Eye contact 04:42 – Robot gender 08:49 – Whitney’s robot (Bearclaw) 12:17 – Human reaction to robots 14:09 – Fear of robots 25:15 – Surveillance 29:35 – Animals 35:01 – Compassion from people who own robots 37:55 – Passion 44:57 – Neurology 56:38 – Social media 1:04:35 – Love 1:13:40 – Mortality

Ray Dalio is the founder, Co-Chairman and Co-Chief Investment Officer of Bridgewater Associates, one of the world’s largest and most successful investment firms that is famous for the principles of radical truth and transparency that underlie its culture. Ray is one of the wealthiest people in the world, with ideas that extend far beyond the specifics of how he made that wealth. His ideas, applicable to everyone, are brilliantly summarized in his book Principles. 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 02:56 – Doing something that’s never been done before 08:39 – Shapers 13:28 – A Players 15:09 – Confidence and disagreement 17:10 – Don’t confuse dilusion with not knowing 24:38 – Idea meritocracy 27:39 – Is credit good for society? 32:59 – What is money? 37:13 – Bitcoin and digital currency 41:01 – The economic machine is amazing 46:24 – Principle for using AI 58:55 – Human irrationality 1:01:31 – Call for adventure at the edge of principles 1:03:26 – The line between madness and genius 1:04:30 – Automation 1:07:28 – American dream 1:14:02 – Can money buy happiness? 1:19:48 – Work-life balance and the arc of life 1:28:01 – Meaning of life

Noam Chomsky is one of the greatest minds of our time and is one of the most cited scholars in history. He is a linguist, philosopher, cognitive scientist, historian, social critic, and political activist. He has spent over 60 years at MIT and recently also joined the University of Arizona. 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 03:59 – Common language with an alience species 05:46 – Structure of language 07:18 – Roots of language in our brain 08:51 – Language and thought 09:44 – The limit of human cognition 16:48 – Neuralink 19:32 – Deepest property of language 22:13 – Limits of deep learning 28:01 – Good and evil 29:52 – Memorable experiences 33:29 – Mortality 34:23 – Meaning of life

Gilbert Strang is a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times. 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, use code LexPodcast.  And it is supported by ZipRecruiter. Try it: http://ziprecruiter.com/lexpod 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 – Math rockstar 05:10 – MIT OpenCourseWare 07:29 – Four Fundamental Subspaces of Linear Algebra 13:11 – Linear Algebra vs Calculus 15:03 – Singular value decomposition 19:47 – Why people like math 23:38 – Teaching by example 25:04 – Andrew Yang 26:46 – Society for Industrial and Applied Mathematics 29:21 – Deep learning 37:28 – Theory vs application 38:54 – Open problems in mathematics 39:00 – Linear algebra as a subfield of mathematics 41:52 – Favorite matrix 46:19 – Advice for students on their journey through math 47:37 – Looking back

Dava Newman is the Apollo Program professor of AeroAstro at MIT and the former Deputy Administrator of NASA and has been a principal investigator on four spaceflight missions. Her research interests are in aerospace biomedical engineering, investigating human performance in varying gravity environments. She has developed a space activity suit, namely the BioSuit, which would provide pressure through compression directly on the skin via the suit’s textile weave, patterning, and materials rather than with pressurized gas. 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, use code LexPodcast. You get $10 and $10 is donated to FIRST, one of my favorite nonprofit organizations that inspires young minds through robotics and STEM education. 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 03:11 – Circumnavigating the globe by boat 05:11 – Exploration 07:17 – Life on Mars 11:07 – Intelligent life in the universe 12:25 – Advanced propulsion technology 13:32 – The Moon and NASA’s Artemis program 19:17 – SpaceX 21:45 – Science on a CubeSat 23:45 – Reusable rockets 25:23 – Spacesuit of the future 32:01 – AI in Space 35:31 – Interplanetary species 36:57 – Future of space exploration

Michael Kearns is a professor at University of Pennsylvania and a co-author of the new book Ethical Algorithm that is the focus of much of our conversation, including algorithmic fairness, bias, privacy, and ethics in general. But, that is just one of many fields that Michael is a world-class researcher in, some of which we touch on quickly including learning theory or theoretical foundations of machine learning, game theory, algorithmic trading, quantitative finance, computational social science, and more. 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 sponsored by Pessimists Archive podcast. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode): 00:00 – Introduction 02:45 – Influence from literature and journalism 07:39 – Are most people good? 13:05 – Ethical algorithm 24:28 – Algorithmic fairness of groups vs individuals 33:36 – Fairness tradeoffs 46:29 – Facebook, social networks, and algorithmic ethics 58:04 – Machine learning 58:05 – Machine learning 59:19 – Algorithm that determines what is fair 1:01:25 – Computer scientists should think about ethics 1:05:59 – Algorithmic privacy 1:11:50 – Differential privacy 1:19:10 – Privacy by misinformation 1:22:31 – Privacy of data in society 1:27:49 – Game theory 1:29:40 – Nash equilibrium 1:30:35 – Machine learning and game theory 1:34:52 – Mutual assured destruction 1:36:56 – Algorithmic trading 1:44:09 – Pivotal moment in graduate school

Elon Musk is the CEO of Tesla, SpaceX, Neuralink, and a co-founder of several other companies. This is the second time Elon has been on the podcast. You can watch the first time on YouTube or listen to the first time on its episode page. You can read the transcript (PDF) here. 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. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode): 00:00 – Introduction 01:57 – Consciousness 05:58 – Regulation of AI Safety 09:39 – Neuralink – understanding the human brain 11:53 – Neuralink – expanding the capacity of the human mind 17:51 – Neuralink – future challenges, solutions, and impact 24:59 – Smart Summon 27:18 – Tesla Autopilot and Full Self-Driving 31:16 – Carl Sagan and the Pale Blue Dot

Bjarne Stroustrup is the creator of C++, a programming language that after 40 years is still one of the most popular and powerful languages in the world. Its focus on fast, stable, robust code underlies many of the biggest systems in the world that we have come to rely on as a society. If you’re watching this on YouTube, many of the critical back-end component of YouTube are written in C++. Same goes for Google, Facebook, Amazon, Twitter, most Microsoft applications, Adobe applications, most database systems, and most physical systems that operate in the real-world like cars, robots, rockets that launch us into space and one day will land us on Mars. 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. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode): 00:00 – Introduction 01:40 – First program 02:18 – Journey to C++ 16:45 – Learning multiple languages 23:20 – Javascript 25:08 – Efficiency and reliability in C++ 31:53 – What does good code look like? 36:45 – Static checkers 41:16 – Zero-overhead principle in C++ 50:00 – Different implementation of C++ 54:46 – Key features of C++ 1:08:02 – C++ Concepts 1:18:06 – C++ Standards Process 1:28:05 – Constructors and destructors 1:31:52 – Unified theory of programming 1:44:20 – Proudest moment