Category Archives: ai

Jim Keller: Moore’s Law, Microprocessors, Abstractions, and First Principles

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: The Hard Problem of Consciousness

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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 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: YouTube Algorithm

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Cristos Goodrow is VP of Engineering at Google and head of Search and Discovery at YouTube (aka YouTube Algorithm).

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: Economics of Innovation, Automation, Safety Nets & Universal Basic Income

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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 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: Human-Robot Interaction and Ethics of Safety-Critical Systems

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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 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: Thinking Fast and Slow, Deep Learning, and AI

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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 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: 3Blue1Brown and the Beauty of Mathematics

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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 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: Stalin, Putin, and the Nature of Power

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

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

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

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

Donald Knuth: Algorithms, TeX, Life, and The Art of Computer Programming

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

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

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

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

Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI

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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 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

Lex Fridman

Research Scientist at MIT. Host of Lex Fridman Podcast.

Category Archives: ai

Jim Keller: Moore’s Law, Microprocessors, Abstractions, and First Principles

David Chalmers: The Hard Problem of Consciousness

Cristos Goodrow: YouTube Algorithm

Paul Krugman: Economics of Innovation, Automation, Safety Nets & Universal Basic Income

Ayanna Howard: Human-Robot Interaction and Ethics of Safety-Critical Systems

Daniel Kahneman: Thinking Fast and Slow, Deep Learning, and AI

Grant Sanderson: 3Blue1Brown and the Beauty of Mathematics

Stephen Kotkin: Stalin, Putin, and the Nature of Power

Donald Knuth: Algorithms, TeX, Life, and The Art of Computer Programming

Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI