Lex Fridman Podcast

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
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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
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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
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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
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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
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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
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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