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