Lex Fridman Podcast Archiv

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:

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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

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, 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

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, 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/

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, 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

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, 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

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, 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

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, 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

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, 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

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, 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

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, 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

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, 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/

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, 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.

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, 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.

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, 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.

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, 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