Lex Fridman Podcast Archiv

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.

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 or support it on Patreon.

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

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

00:00 – Introduction

03:59 – Common language with an alience species

05:46 – Structure of language

07:18 – Roots of language in our brain

08:51 – Language and thought

09:44 – The limit of human cognition

16:48 – Neuralink

19:32 – Deepest property of language

22:13 – Limits of deep learning

28:01 – Good and evil

29:52 – Memorable experiences

33:29 – Mortality

34:23 – Meaning of life

Gilbert Strang is a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times.

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 or support it on Patreon.

This episode is presented by Cash App. Download it, use code LexPodcast. 

And it is supported by ZipRecruiter. Try it: http://ziprecruiter.com/lexpod

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

00:00 – Introduction

03:45 – Math rockstar

05:10 – MIT OpenCourseWare

07:29 – Four Fundamental Subspaces of Linear Algebra

13:11 – Linear Algebra vs Calculus

15:03 – Singular value decomposition

19:47 – Why people like math

23:38 – Teaching by example

25:04 – Andrew Yang

26:46 – Society for Industrial and Applied Mathematics

29:21 – Deep learning

37:28 – Theory vs application

38:54 – Open problems in mathematics

39:00 – Linear algebra as a subfield of mathematics

41:52 – Favorite matrix

46:19 – Advice for students on their journey through math

47:37 – Looking back

Dava Newman is the Apollo Program professor of AeroAstro at MIT and the former Deputy Administrator of NASA and has been a principal investigator on four spaceflight missions. Her research interests are in aerospace biomedical engineering, investigating human performance in varying gravity environments. She has developed a space activity suit, namely the BioSuit, which would provide pressure through compression directly on the skin via the suit’s textile weave, patterning, and materials rather than with pressurized gas.

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 or support it on Patreon.

This episode is presented by Cash App. Download it, use code LexPodcast. You get $10 and $10 is donated to FIRST, one of my favorite nonprofit organizations that inspires young minds through robotics and STEM education.

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

00:00 – Introduction

03:11 – Circumnavigating the globe by boat

05:11 – Exploration

07:17 – Life on Mars

11:07 – Intelligent life in the universe

12:25 – Advanced propulsion technology

13:32 – The Moon and NASA’s Artemis program

19:17 – SpaceX

21:45 – Science on a CubeSat

23:45 – Reusable rockets

25:23 – Spacesuit of the future

32:01 – AI in Space

35:31 – Interplanetary species

36:57 – Future of space exploration

Michael Kearns is a professor at University of Pennsylvania and a co-author of the new book Ethical Algorithm that is the focus of much of our conversation, including algorithmic fairness, bias, privacy, and ethics in general. But, that is just one of many fields that Michael is a world-class researcher in, some of which we touch on quickly including learning theory or theoretical foundations of machine learning, game theory, algorithmic trading, quantitative finance, computational social science, and more.

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 or support it on Patreon. This episode is sponsored by Pessimists Archive podcast. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

02:45 – Influence from literature and journalism

07:39 – Are most people good?

13:05 – Ethical algorithm

24:28 – Algorithmic fairness of groups vs individuals

33:36 – Fairness tradeoffs

46:29 – Facebook, social networks, and algorithmic ethics

58:04 – Machine learning

58:05 – Machine learning

59:19 – Algorithm that determines what is fair

1:01:25 – Computer scientists should think about ethics

1:05:59 – Algorithmic privacy

1:11:50 – Differential privacy

1:19:10 – Privacy by misinformation

1:22:31 – Privacy of data in society

1:27:49 – Game theory

1:29:40 – Nash equilibrium

1:30:35 – Machine learning and game theory

1:34:52 – Mutual assured destruction

1:36:56 – Algorithmic trading

1:44:09 – Pivotal moment in graduate school

Elon Musk is the CEO of Tesla, SpaceX, Neuralink, and a co-founder of several other companies. This is the second time Elon has been on the podcast. You can watch the first time on YouTube or listen to the first time on its episode page. You can read the transcript (PDF) here. 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 or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:57 – Consciousness

05:58 – Regulation of AI Safety

09:39 – Neuralink – understanding the human brain

11:53 – Neuralink – expanding the capacity of the human mind

17:51 – Neuralink – future challenges, solutions, and impact

24:59 – Smart Summon

27:18 – Tesla Autopilot and Full Self-Driving

31:16 – Carl Sagan and the Pale Blue Dot

Bjarne Stroustrup is the creator of C++, a programming language that after 40 years is still one of the most popular and powerful languages in the world. Its focus on fast, stable, robust code underlies many of the biggest systems in the world that we have come to rely on as a society. If you’re watching this on YouTube, many of the critical back-end component of YouTube are written in C++. Same goes for Google, Facebook, Amazon, Twitter, most Microsoft applications, Adobe applications, most database systems, and most physical systems that operate in the real-world like cars, robots, rockets that launch us into space and one day will land us on Mars.

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 or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:40 – First program

02:18 – Journey to C++

16:45 – Learning multiple languages

23:20 – Javascript

25:08 – Efficiency and reliability in C++

31:53 – What does good code look like?

36:45 – Static checkers

41:16 – Zero-overhead principle in C++

50:00 – Different implementation of C++

54:46 – Key features of C++

1:08:02 – C++ Concepts

1:18:06 – C++ Standards Process

1:28:05 – Constructors and destructors

1:31:52 – Unified theory of programming

1:44:20 – Proudest moment

Sean Carroll is a theoretical physicist at Caltech and Santa Fe Institute specializing in quantum mechanics, arrow of time, cosmology, and gravitation. He is the author of Something Deeply Hidden and several popular books and he is the host of a great podcast called Mindscape. This is the second time Sean has been on the podcast. You can watch the first time on YouTube or listen to the first time on its episode page. 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 or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:23 – Capacity of human mind to understand physics

10:49 – Perception vs reality

12:29 – Conservation of momentum

17:20 – Difference between math and physics

20:10 – Why is our world so compressable

22:53 – What would Newton think of quantum mechanics

25:44 – What is quantum mechanics?

27:54 – What is an atom?

30:34 – What is the wave function?

32:30 – What is quantum entanglement?

35:19 – What is Hilbert space?

37:32 – What is entropy?

39:31 – Infinity

42:43 – Many-worlds interpretation of quantum mechanics

1:01:13 – Quantum gravity and the emergence of spacetime

1:08:34 – Our branch of reality in many-worlds interpretation

1:10:40 – Time travel

1:12:54 – Arrow of time

1:16:18 – What is fundamental in physics

1:16:58 – Quantum computers

1:17:42 – Experimental validation of many-worlds and emergent spacetime

1:19:53 – Quantum mechanics and the human mind

1:21:51 – Mindscape podcast

Garry Kasparov is considered by many to be the greatest chess player of all time. From 1986 until his retirement in 2005, he dominated the chess world, ranking world number 1 for most of those 19 years. While he has many historic matches against human chess players, in the long arc of history he may be remembered for his match again a machine, IBM’s Deep Blue. His initial victories and eventual loss to Deep Blue captivated the imagination of the world of what role Artificial Intelligence systems may play in our civilization’s future. That excitement inspired an entire generation of AI researchers, including myself, to get into the field. Garry is also a pro-democracy political thinker and leader, a fearless human-rights activist, and author of several books including How Life Imitates Chess which is a book on strategy and decision-making, Winter Is Coming which is a book articulating his opposition to the Putin regime, and Deep Thinking which is a book the role of both artificial intelligence and human intelligence in defining our future. 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 or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:33 – Love of winning and hatred of losing

04:54 – Psychological elements

09:03 – Favorite games

16:48 – Magnus Carlsen

23:06 – IBM Deep Blue

37:39 – Morality

38:59 – Autonomous vehicles

42:03 – Fall of the Soviet Union

45:50 – Putin

52:25 – Life

Michio Kaku is a theoretical physicist, futurist, and professor at the City College of New York. He is the author of many fascinating books on the nature of our reality and the future of our civilization. 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 or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:14 – Contact with Aliens in the 21st century

06:36 – Multiverse and Nirvana

09:46 – String Theory

11:07 – Einstein’s God

15:01 – Would aliens hurt us?

17:34 – What would aliens look like?

22:13 – Brain-machine interfaces

27:35 – Existential risk from AI

30:22 – Digital immortality

34:02 – Biological immortality

37:42 – Does mortality give meaning?

43:42 – String theory

47:16 – Universe as a computer and a simulation

53:16 – First human on Mars

David Ferrucci led the team that built Watson, the IBM question-answering system that beat the top humans in the world at the game of Jeopardy. He is also the Founder, CEO, and Chief Scientist of Elemental Cognition, a company working engineer AI systems that understand the world the way people do. 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 iTunes or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:06 – Biological vs computer systems

08:03 – What is intelligence?

31:49 – Knowledge frameworks

52:02 – IBM Watson winning Jeopardy

1:24:21 – Watson vs human difference in approach

1:27:52 – Q&A vs dialogue

1:35:22 – Humor

1:41:33 – Good test of intelligence

1:46:36 – AlphaZero, AlphaStar accomplishments

1:51:29 – Explainability, induction, deduction in medical diagnosis

1:59:34 – Grand challenges

2:04:03 – Consciousness

2:08:26 – Timeline for AGI

2:13:55 – Embodied AI

2:17:07 – Love and companionship

2:18:06 – Concerns about AI

2:21:56 – Discussion with AGI

Gary Marcus is a professor emeritus at NYU, founder of Robust.AI and Geometric Intelligence, the latter is a machine learning company acquired by Uber in 2016. He is the author of several books on natural and artificial intelligence, including his new book Rebooting AI: Building Machines We Can Trust. Gary has been a critical voice highlighting the limits of deep learning and discussing the challenges before the AI community that must be solved in order to achieve artificial general intelligence. 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 iTunes or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:37 – Singularity

05:48 – Physical and psychological knowledge

10:52 – Chess

14:32 – Language vs physical world

17:37 – What does AI look like 100 years from now

21:28 – Flaws of the human mind

25:27 – General intelligence

28:25 – Limits of deep learning

44:41 – Expert systems and symbol manipulation

48:37 – Knowledge representation

52:52 – Increasing compute power

56:27 – How human children learn

57:23 – Innate knowledge and learned knowledge

1:06:43 – Good test of intelligence

1:12:32 – Deep learning and symbol manipulation

1:23:35 – Guitar

Peter Norvig is a research director at Google and the co-author with Stuart Russell of the book Artificial Intelligence: A Modern Approach that educated and inspired a whole generation of researchers including myself to get into the field. 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 iTunes or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

00:37 – Artificial Intelligence: A Modern Approach

09:11 – Covering the entire field of AI

15:42 – Expert systems and knowledge representation

18:31 – Explainable AI

23:15 – Trust

25:47 – Education – Intro to AI – MOOC

32:43 – Learning to program in 10 years

37:12 – Changing nature of mastery

40:01 – Code review

41:17 – How have you changed as a programmer

43:05 – LISP

47:41 – Python

48:32 – Early days of Google Search

53:24 – What does it take to build human-level intelligence

55:14 – Her

57:00 – Test of intelligence

58:41 – Future threats from AI

1:00:58 – Exciting open problems in AI

Leonard Susskind is a professor of theoretical physics at Stanford University, and founding director of the Stanford Institute for Theoretical Physics. He is widely regarded as one of the fathers of string theory and in general as one of the greatest physicists of our time both as a researcher and an educator. 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 iTunes or support it on Patreon. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode):

00:00 – Introduction

01:02 – Richard Feynman

02:09 – Visualization and intuition

06:45 – Ego in Science

09:27 – Academia

11:18 – Developing ideas

12:12 – Quantum computers

21:37 – Universe as an information processing system

26:35 – Machine learning

29:47 – Predicting the future

30:48 – String theory

37:03 – Free will

39:26 – Arrow of time

46:39 – Universe as a computer

49:45 – Big bang

50:50 – Infinity

51:35 – First image of a black hole

54:08 – Questions within the reach of science

55:55 – Questions out of reach of science

Regina Barzilay is a professor at MIT and a world-class researcher in natural language processing and applications of deep learning to chemistry and oncology, or the use of deep learning for early diagnosis, prevention and treatment of cancer. She has also been recognized for her teaching of several successful AI-related courses at MIT, including the popular Introduction to Machine Learning course. 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 iTunes or support it on Patreon.