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    Technology

    Lex Fridman Podcast

    Conversations that explore technology, history, philosophy, physics, mathematics, biology, chemistry, engineering, AI, robotics, programming, music, film, art, sports, psychology, neuroscience, geopolitics, business, economics, religion, astronomy, and the human condition with people from all walks of life.

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    Latest Episodes:
    Stephen Kotkin: Stalin, Putin, and the Nature of Power Jan 03, 2020
    Show notes

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

    This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

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

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

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

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


    Donald Knuth: Algorithms, TeX, Life, and The Art of Computer Programming Dec 30, 2019
    Show notes

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

    This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

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

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

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

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


    Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI Dec 28, 2019
    Show notes

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

    This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

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

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

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

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


    Jim Gates: Supersymmetry, String Theory and Proving Einstein Right Dec 25, 2019
    Show notes

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

    This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.

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

    Episode Links:
    Proving Einstein Right (book)

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

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


    Sebastian Thrun: Flying Cars, Autonomous Vehicles, and Education Dec 21, 2019
    Show notes

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

    This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts or support it on Patreon.

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

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

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


    Michael Stevens: Vsauce Dec 17, 2019
    Show notes

    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: Amazon Alexa and Conversational AI Dec 14, 2019
    Show notes

    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: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI Dec 11, 2019
    Show notes

    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: Comedy, Robotics, Neurology, and Love Dec 05, 2019
    Show notes

    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: Principles, the Economic Machine, Artificial Intelligence & the Arc of Life Dec 02, 2019
    Show notes

    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


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