Grant Sanderson is a math educator and creator of 3Blue1Brown. Support this podcast by supporting our sponsors: - Dollar Shave Club: https://dollarshaveclub.com/lex - DoorDash: download app & use code LEX - Cash App: download app & use code "LexPodcast" Episode links: 3Blue1Brown: http://youtube.com/3blue1brown Grant's Twitter: https://twitter.com/3blue1brown If you would like to get more information about this podcast go to https://lexfridman.com/podcast or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 05:13 - Richard Feynman 09:41 - Learning deeply vs broadly 13:56 - Telling a story with visualizations 18:43 - Topology 23:52 - Intuition about exponential growth 32:28 - Elon Musk's exponential view of the world 40:09 - SpaceX and space exploration 45:28 - Origins of the Internet 49:50 - Does teaching on YouTube get lonely? 54:31 - Daily routine 1:00:20 - Social media 1:10:38 - Online education in a time of COVID 1:27:03 - Joe Rogan moving to Spotify 1:32:09 - Neural networks 1:38:30 - GPT-3 1:46:52 - Manim 1:51:01 - Python 1:56:21 - Theory of everything 2:03:53 - Meaning of life

Sheldon Solomon is a social psychologist, a philosopher, co-developer of Terror Management Theory, co-author of The Worm at the Core. Please support this channel by supporting our sponsors: - Blinkist: https://blinkist.com/lex – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App: download app & use code "LexPodcast" Episode links: Sheldon's Website: https://www.skidmore.edu/psychology/faculty/solomon.php The Worm at the Core (book): https://amzn.to/31hQAXH Denial of Death (book): https://amzn.to/329Zxl4 If you would like to get more information about this podcast go to https://lexfridman.com/podcast or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 05:34 - Role of death in life 22:57 - Jordan Peterson 53:02 - Humans are both selfish and cooperative 56:57 - Civilization collapse 1:10:07 - Meditating on your mortality 1:16:10 - Kierkegaard and Heidegger 1:33:25 - Elon Musk 1:36:56 - Thinking deeply about death 1:45:53 - Religion 1:56:59 - Consciousness 2:03:39 - Why is Ernest Becker not better known 2:07:09 - AI and mortality 2:21:07 - Academia should welcome renegade thinkers 2:36:33 - Book recommendations 2:43:23 - Advice for young people 2:48:17 - Meaning of life

Sara Seager is a planetary scientist at MIT, known for her work on the search for exoplanets. Support this podcast by supporting our sponsors. Click links, get discount: - Public Goods at https://publicgoods.com/lex and use code LEX - PowerDot: https://powerdot.com/lex and use code 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: Sara's Twitter: https://twitter.com/profsaraseager Sara's Website: https://www.saraseager.com/ The Smallest Lights in the Universe (book): https://amzn.to/3g3LfHA If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 05:32 - Falling in love with the stars 09:55 - Are we alone in the universe? 15:27 - Seager equation for number of habitable planets 27:48 - Exoplanets 34:44 - Earth-like exoplanets 40:43 - Intelligent life 52:34 - Number of planets per star 55:09 - Space exploration 57:36 - Traveling to Proxima Centauri 1:00:52 - Starshade 1:07:34 - Using the sun as a gravitational lens 1:09:44 - Starshot 1:12:45 - Rogue planets 1:15:44 - The Smallest Lights in the Universe 1:30:15 - Book recommendations 1:37:48 - Advice for a young person 1:39:29 - Meaning of life

Dileep George is a researcher at the intersection of neuroscience and artificial intelligence, co-founder of Vicarious, formerly co-founder of Numenta. From the early work on Hierarchical temporal memory to Recursive Cortical Networks to today, Dileep's always sought to engineer intelligence that is closely inspired by the human brain. Support this channel by supporting our sponsors. Click links, get discount: - Babbel: https://babbel.com and use code LEX - MasterClass: https://masterclass.com/lex - Raycon: https://buyraycon.com/lex If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 0:00 - Introduction 4:50 - Building a model of the brain 17:11 - Visual cortex 27:50 - Probabilistic graphical models 31:35 - Encoding information in the brain 36:56 - Recursive Cortical Network 51:09 - Solving CAPTCHAs algorithmically 1:06:48 - Hype around brain-inspired AI 1:18:21 - How does the brain learn? 1:21:32 - Perception and cognition 1:25:43 - Open problems in brain-inspired AI 1:30:33 - GPT-3 1:40:41 - Memory 1:45:08 - Neuralink 1:51:32 - Consciousness 1:57:59 - Book recommendations 2:06:49 - Meaning of life

Russ Tedrake is a roboticist and professor at MIT and vice president of robotics research at TRI. He works on control of robots in interesting, complicated, underactuated, stochastic, difficult to model situations. Support this podcast by supporting our sponsors. Click links, get discount: - Magic Spoon: https://magicspoon.com/lex & use code LEX at checkout - BetterHelp: https://betterhelp.com/lex - ExpressVPN: https://www.expressvpn.com/lexpod If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 04:29 - Passive dynamic walking 09:40 - Animal movement 13:34 - Control vs Dynamics 15:49 - Bipedal walking 20:56 - Running barefoot 33:01 - Think rigorously with machine learning 44:05 - DARPA Robotics Challenge 1:07:14 - When will a robot become UFC champion 1:18:32 - Black Mirror Robot Dog 1:34:01 - Robot control 1:47:00 - Simulating robots 2:00:33 - Home robotics 2:03:40 - Soft robotics 2:07:25 - Underactuated robotics 2:20:42 - Touch 2:28:55 - Book recommendations 2:40:08 - Advice to young people 2:44:20 - Meaning of life

Manolis Kellis is a professor at MIT and head of the MIT Computational Biology Group. He is interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives. Support this podcast by supporting our sponsors: - Blinkist: https://blinkist.com/lex - Eight Sleep: https://eightsleep.com/lex - MasterClass: https://masterclass.com/lex If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 03:54 - Human genome 17:47 - Sources of knowledge 29:15 - Free will 33:26 - Simulation 35:17 - Biological and computing 50:10 - Genome-wide evolutionary signatures 56:54 - Evolution of COVID-19 1:02:59 - Are viruses intelligent? 1:12:08 - Humans vs viruses 1:19:39 - Engineered pandemics 1:23:23 - Immune system 1:33:22 - Placebo effect 1:35:39 - Human genome source code 1:44:40 - Mutation 1:51:46 - Deep learning 1:58:08 - Neuralink 2:07:07 - Language 2:15:19 - Meaning of life

Ian Hutchinson is a nuclear engineer and plasma physicist at MIT. He has made a number of important contributions in plasma physics including the magnetic confinement of plasmas seeking to enable fusion reactions, which is the energy source of the stars, to be used for practical energy production. Current nuclear reactors are based on fission as we discuss. Ian has also written on the philosophy of science and the relationship between science and religion. Support this podcast by supporting our sponsors: - Sun Basket, use code LEX: https://sunbasket.com/lex - PowerDot, use code LEX: https://powerdot.com/lex If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 05:32 - Nuclear physics and plasma physics 08:00 - Fusion energy 35:22 - Nuclear weapons 42:06 - Existential risks 50:29 - Personal journey in religion 56:27 - What is God like? 1:01:34 - Scientism 1:04:21 - Atheism 1:06:39 - Not knowing 1:09:57 - Faith 1:13:46 - The value of loyalty and love 1:23:26 - Why is there suffering in the world 1:35:08 - AGI 1:40:27 - Consciousness 1:48:14 - Simulation 1:52:20 - Adam and Eve 1:54:57 - Meaning of life

Richard Karp is a professor at Berkeley and one of the most important figures in the history of theoretical computer science. In 1985, he received the Turing Award for his research in the theory of algorithms, including the development of the Edmonds–Karp algorithm for solving the maximum flow problem on networks, Hopcroft–Karp algorithm for finding maximum cardinality matchings in bipartite graphs, and his landmark paper in complexity theory called "Reducibility Among Combinatorial Problems", in which he proved 21 problems to be NP-complete. This paper was probably the most important catalyst in the explosion of interest in the study of NP-completeness and the P vs NP problem. Support this podcast by supporting our sponsors: - Eight Sleep: https://eightsleep.com/lex - Cash App – use code "LexPodcast" and download: - Cash App (App Store): https://apple.co/2sPrUHe - Cash App (Google Play): https://bit.ly/2MlvP5w If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 03:50 - Geometry 09:46 - Visualizing an algorithm 13:00 - A beautiful algorithm 18:06 - Don Knuth and geeks 22:06 - Early days of computers 25:53 - Turing Test 30:05 - Consciousness 33:22 - Combinatorial algorithms 37:42 - Edmonds-Karp algorithm 40:22 - Algorithmic complexity 50:25 - P=NP 54:25 - NP-Complete problems 1:10:29 - Proving P=NP 1:12:57 - Stable marriage problem 1:20:32 - Randomized algorithms 1:33:23 - Can a hard problem be easy in practice? 1:43:57 - Open problems in theoretical computer science 1:46:21 - A strange idea in complexity theory 1:50:49 - Machine learning 1:56:26 - Bioinformatics 2:00:37 - Memory of Richard's father

Jitendra Malik is a professor at Berkeley and one of the seminal figures in the field of computer vision, the kind before the deep learning revolution, and the kind after. He has been cited over 180,000 times and has mentored many world-class researchers in computer science. Support this podcast by supporting our sponsors: - BetterHelp: http://betterhelp.com/lex - ExpressVPN: https://www.expressvpn.com/lexpod If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 03:17 - Computer vision is hard 10:05 - Tesla Autopilot 21:20 - Human brain vs computers 23:14 - The general problem of computer vision 29:09 - Images vs video in computer vision 37:47 - Benchmarks in computer vision 40:06 - Active learning 45:34 - From pixels to semantics 52:47 - Semantic segmentation 57:05 - The three R's of computer vision 1:02:52 - End-to-end learning in computer vision 1:04:24 - 6 lessons we can learn from children 1:08:36 - Vision and language 1:12:30 - Turing test 1:16:17 - Open problems in computer vision 1:24:49 - AGI 1:35:47 - Pick the right problem

Brian Kernighan is a professor of computer science at Princeton University. He co-authored the C Programming Language with Dennis Ritchie (creator of C) and has written a lot of books on programming, computers, and life including the Practice of Programming, the Go Programming Language, his latest UNIX: A History and a Memoir. He co-created AWK, the text processing language used by Linux folks like myself. He co-designed AMPL, an algebraic modeling language for large-scale optimization. Support this podcast by supporting our sponsors: - Eight Sleep: https://eightsleep.com/lex - Raycon: http://buyraycon.com/lex If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 04:24 - UNIX early days 22:09 - Unix philosophy 31:54 - Is programming art or science? 35:18 - AWK 42:03 - Programming setup 46:39 - History of programming languages 52:48 - C programming language 58:44 - Go language 1:01:57 - Learning new programming languages 1:04:57 - Javascript 1:08:16 - Variety of programming languages 1:10:30 - AMPL 1:18:01 - Graph theory 1:22:20 - AI in 1964 1:27:50 - Future of AI 1:29:47 - Moore's law 1:32:54 - Computers in our world 1:40:37 - Life

Sergey Levine is a professor at Berkeley and a world-class researcher in deep learning, reinforcement learning, robotics, and computer vision, including the development of algorithms for end-to-end training of neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep RL algorithms. Support this podcast by supporting these sponsors: - ExpressVPN: 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 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 03:05 - State-of-the-art robots vs humans 16:13 - Robotics may help us understand intelligence 22:49 - End-to-end learning in robotics 27:01 - Canonical problem in robotics 31:44 - Commonsense reasoning in robotics 34:41 - Can we solve robotics through learning? 44:55 - What is reinforcement learning? 1:06:36 - Tesla Autopilot 1:08:15 - Simulation in reinforcement learning 1:13:46 - Can we learn gravity from data? 1:16:03 - Self-play 1:17:39 - Reward functions 1:27:01 - Bitter lesson by Rich Sutton 1:32:13 - Advice for students interesting in AI 1:33:55 - Meaning of life

Peter Singer is a professor of bioethics at Princeton, best known for his 1975 book Animal Liberation, that makes an ethical case against eating meat. He has written brilliantly from an ethical perspective on extreme poverty, euthanasia, human genetic selection, sports doping, the sale of kidneys, and happiness including in his books Ethics in the Real World and The Life You Can Save. He was a key popularizer of the effective altruism movement and is generally considered one of the most influential philosophers in the world. Support this podcast by supporting 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 If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here's the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 - Introduction 05:25 - World War II 09:53 - Suffering 16:06 - Is everyone capable of evil? 21:52 - Can robots suffer? 37:22 - Animal liberation 40:31 - Question for AI about suffering 43:32 - Neuralink 45:11 - Control problem of AI 51:08 - Utilitarianism 59:43 - Helping people in poverty 1:05:15 - Mortality

Matt Botvinick is the Director of Neuroscience Research at DeepMind. He is a brilliant cross-disciplinary mind navigating effortlessly between cognitive psychology, computational neuroscience, and artificial intelligence. Support this podcast by supporting these sponsors: - The Jordan Harbinger Show: https://www.jordanharbinger.com/lex - Magic Spoon: https://magicspoon.com/lex and use code LEX at checkout 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 03:29 - How much of the brain do we understand? 14:26 - Psychology 22:53 - The paradox of the human brain 32:23 - Cognition is a function of the environment 39:34 - Prefrontal cortex 53:27 - Information processing in the brain 1:00:11 - Meta-reinforcement learning 1:15:18 - Dopamine 1:19:01 - Neuroscience and AI research 1:23:37 - Human side of AI 1:39:56 - Dopamine and reinforcement learning 1:53:07 - Can we create an AI that a human can love?

Robert Langer is a professor at MIT and one of the most cited researchers in history, specializing in biotechnology fields of drug delivery systems and tissue engineering. He has bridged theory and practice by being a key member and driving force in launching many successful biotech companies out of MIT. Support this podcast by supporting 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 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 03:07 - Magic and science 05:34 - Memorable rejection 08:35 - How to come up with big ideas in science 13:27 - How to make a new drug 22:38 - Drug delivery 28:22 - Tissue engineering 35:22 - Beautiful idea in bioengineering 38:16 - Patenting process 42:21 - What does it take to build a successful startup? 46:18 - Mentoring students 50:54 - Funding 58:08 - Cookies 59:41 - What are you most proud of?

David Patterson is a Turing award winner and professor of computer science at Berkeley. He is known for pioneering contributions to RISC processor architecture used by 99% of new chips today and for co-creating RAID storage. The impact that these two lines of research and development have had on our world is immeasurable. He is also one of the great educators of computer science in the world. His book with John Hennessy "Computer Architecture: A Quantitative Approach" is how I first learned about and was humbled by the inner workings of machines at the lowest level. Support this podcast by supporting these sponsors: - Jordan Harbinger Show: https://jordanharbinger.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 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 03:28 - How have computers changed? 04:22 - What's inside a computer? 10:02 - Layers of abstraction 13:05 - RISC vs CISC computer architectures 28:18 - Designing a good instruction set is an art 31:46 - Measures of performance 36:02 - RISC instruction set 39:39 - RISC-V open standard instruction set architecture 51:12 - Why do ARM implementations vary? 52:57 - Simple is beautiful in instruction set design 58:09 - How machine learning changed computers 1:08:18 - Machine learning benchmarks 1:16:30 - Quantum computing 1:19:41 - Moore's law 1:28:22 - RAID data storage 1:36:53 - Teaching 1:40:59 - Wrestling 1:45:26 - Meaning of life

Ben Goertzel is one of the most interesting minds in the artificial intelligence community. He is the founder of SingularityNET, designer of OpenCog AI framework, formerly a director of the Machine Intelligence Research Institute, Chief Scientist of Hanson Robotics, the company that created the Sophia Robot. He has been a central figure in the AGI community for many years, including in the Conference on Artificial General Intelligence. Support this podcast by supporting these sponsors: - Jordan Harbinger Show: https://jordanharbinger.com/lex/ - MasterClass: https://masterclass.com/lex 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 03:20 - Books that inspired you 06:38 - Are there intelligent beings all around us? 13:13 - Dostoevsky 15:56 - Russian roots 20:19 - When did you fall in love with AI? 31:30 - Are humans good or evil? 42:04 - Colonizing mars 46:53 - Origin of the term AGI 55:56 - AGI community 1:12:36 - How to build AGI? 1:36:47 - OpenCog 2:25:32 - SingularityNET 2:49:33 - Sophia 3:16:02 - Coronavirus 3:24:14 - Decentralized mechanisms of power 3:40:16 - Life and death 3:42:44 - Would you live forever? 3:50:26 - Meaning of life 3:58:03 - Hat 3:58:46 - Question for AGI

Steven Pressfield is a historian and author of War of Art, a book that had a big impact on my life and the life of millions of whose passion is to create in art, science, business, sport, and everywhere else. I highly recommend it and others of his books on this topic, including Turning Pro, Do the Work, Nobody Wants to Read Your Shit, and the Warrior Ethos. Also his books Gates of Fire about the Spartans and the battle at Thermopylae, The Lion's Gate, Tides of War, and others are some of the best historical fiction novels ever written. Support this podcast by supporting these sponsors: - Jordan Harbinger Show: https://jordanharbinger.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 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 05:00 - Nature of war 11:43 - The struggle within 17:11 - Love and hate in a time of war 25:17 - Future of warfare 28:31 - Technology in war 30:10 - What it takes to kill a person 32:22 - Mortality 37:30 - The muse 46:09 - Editing 52:19 - Resistance 1:10:41 - Loneliness 1:12:24 - Is a warrior born or trained? 1:13:53 - Hard work and health 1:18:41 - Daily ritual

Joscha Bach is the VP of Research at the AI Foundation, previously doing research at MIT and Harvard. Joscha work explores the workings of the human mind, intelligence, consciousness, life on Earth, and the possibly-simulated fabric of our universe. Support this podcast by supporting 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 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 03:14 - Reverse engineering Joscha Bach 10:38 - Nature of truth 18:47 - Original thinking 23:14 - Sentience vs intelligence 31:45 - Mind vs Reality 46:51 - Hard problem of consciousness 51:09 - Connection between the mind and the universe 56:29 - What is consciousness 1:02:32 - Language and concepts 1:09:02 - Meta-learning 1:16:35 - Spirit 1:18:10 - Our civilization may not exist for long 1:37:48 - Twitter and social media 1:44:52 - What systems of government might work well? 1:47:12 - The way out of self-destruction with AI 1:55:18 - AI simulating humans to understand its own nature 2:04:32 - Reinforcement learning 2:09:12 - Commonsense reasoning 2:15:47 - Would AGI need to have a body? 2:22:34 - Neuralink 2:27:01 - Reasoning at the scale of neurons and societies 2:37:16 - Role of emotion 2:48:03 - Happiness is a cookie that your brain bakes for itself

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