lex ai – Frank's World of Data Science & AI

Developer Future
0
1 min read

Chris Lattner on the Future of Computing and Programming Languages

Lex Fridman interviews Chris Lattner, a world-class software & hardware engineer, leading projects at Apple, Tesla, Google, and SiFive.

OUTLINE:

0:00 – Introduction
2:25 – Working with Elon Musk, Steve Jobs, Jeff Dean
7:55 – Why do programming languages matter?
13:55 – Python vs Swift
24:48 – Design decisions
30:06 – Types
33:54 – Programming languages are a bicycle for the mind
36:26 – Picking what language to learn
42:25 – Most beautiful feature of a programming language
51:50 – Walrus operator
1:01:16 – LLVM
1:06:28 – MLIR compiler framework
1:10:35 – SiFive semiconductor design
1:23:09 – Moore’s Law
1:26:22 – Parallelization
1:30:50 – Swift concurrency manifesto
1:41:39 – Running a neural network fast
1:47:16 – Is the universe a quantum computer?
1:52:57 – Effects of the pandemic on society
2:10:09 – GPT-3
2:14:28 – Software 2.0
2:27:54 – Advice for young people
2:32:37 – Meaning of life

AI Quantum Computing
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25 sec read

Scott Aaronson on Computational Complexity and Consciousness

Lex Fridman interviews Scott Aaronson, a quantum computer scientist.

Time index:

0:00 – Introduction
3:31 – Simulation
8:22 – Theories of everything
14:02 – Consciousness
36:16 – Roger Penrose on consciousness
46:28 – Turing test
50:16 – GPT-3
58:46 – Universality of computation
1:05:17 – Complexity
1:11:23 – P vs NP
1:23:41 – Complexity of quantum computation
1:35:48 – Pandemic
1:49:33 – Love

Quantum Computing Science
Closed
6 sec read

Quantum Mechanics Emerges from the Multiway Causal Graph

Here’s a selection from Lex Fridman’s conversation with Stepham Wolfram.

AI
Closed
37 sec read

François Chollet on Measures of Intelligence

Lex Fridman interviewed François Chollet, an AI researcher at Google and creator of Keras, for a second time on his podcast.\

OUTLINE:

0:00 – Introduction
5:04 – Early influence
6:23 – Language
12:50 – Thinking with mind maps
23:42 – Definition of intelligence
42:24 – GPT-3
53:07 – Semantic web
57:22 – Autonomous driving
1:09:30 – Tests of intelligence
1:13:59 – Tests of human intelligence
1:27:18 – IQ tests
1:35:59 – ARC Challenge
1:59:11 – Generalization
2:09:50 – Turing Test
2:20:44 – Hutter prize
2:27:44 – Meaning of life

AI Robotics
Closed
1 min read

Russ Tedrake on Underactuated Robotics, Control, Dynamics and Touch

Lex Fridman talks to Russ Tedrake in the latest episode of his AI podcast.

Russ Tedrake is a roboticist and professor at MIT and vice president of robotics research at TRI. He works on control of robots in interesting, complicated, underactuated, stochastic, difficult to model situations. This conversation is part of the Artificial Intelligence podcast.

Outline:

0:00 – Introduction
4:29 – Passive dynamic walking
9:40 – Animal movement
13:34 – Control vs Dynamics
15:49 – Bipedal walking
20:56 – Running barefoot
33:01 – Think rigorously with machine learning
44:05 – DARPA Robotics Challenge
1:07:14 – When will a robot become UFC champion
1:18:32 – Black Mirror Robot Dog
1:34:01 – Robot control
1:47:00 – Simulating robots
2:00:33 – Home robotics
2:03:40 – Soft robotics
2:07:25 – Underactuated robotics
2:20:42 – Touch
2:28:55 – Book recommendations
2:40:08 – Advice to young people
2:44:20 – Meaning of life

AI Bioinformatics
Closed
53 sec read

Manolis Kellis on Human Genome and Evolutionary Dynamics

Lex Fridman interviews Manolis Kellis,a professor at MIT and head of the MIT Computational Biology Group.

He is interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives.

This conversation is part of the Artificial Intelligence podcast.

Content outline:

0:00 – Introduction
3:54 – Human genome
17:47 – Sources of knowledge
29:15 – Free will
33:26 – Simulation
35:17 – Biological and computing
50:10 – Genome-wide evolutionary signatures
56:54 – Evolution of COVID-19
1:02:59 – Are viruses intelligent?
1:12:08 – Humans vs viruses
1:19:39 – Engineered pandemics
1:23:23 – Immune system
1:33:22 – Placebo effect
1:35:39 – Human genome source code
1:44:40 – Mutation
1:51:46 – Deep learning
1:58:08 – Neuralink
2:07:07 – Language
2:15:19 – Meaning of life

Computer Vision
Closed
1 min read

Jitendra Malik on Computer Vision

Lex Fridman interviews Jitendra Malik, a professor at Berkeley and one of the seminal figures in the field of computer vision, the kind before the deep learning revolution, and the kind after.

He has been cited over 180,000 times and has mentored many world-class researchers in computer science. This conversation is part of the Artificial Intelligence podcast.

Content index:

0:00 – Introduction
3:17 – Computer vision is hard
10:05 – Tesla Autopilot
21:20 – Human brain vs computers
23:14 – The general problem of computer vision
29:09 – Images vs video in computer vision
37:47 – Benchmarks in computer vision
40:06 – Active learning
45:34 – From pixels to semantics
52:47 – Semantic segmentation
57:05 – The three R’s of computer vision
1:02:52 – End-to-end learning in computer vision
1:04:24 – 6 lessons we can learn from children
1:08:36 – Vision and language
1:12:30 – Turing test
1:16:17 – Open problems in computer vision
1:24:49 – AGI
1:35:47 – Pick the right problem

AI Developer Linux
Closed
1 min read

Brian Kernighan on UNIX, C, AWK, AMPL, and Go Programming

Lex Fridman interviews Brian Kernighan in the latest episode of his podcast.

Brian Kernighan is a professor of computer science at Princeton University. He co-authored the C Programming Language with Dennis Ritchie (creator of C) and has written a lot of books on programming, computers, and life including the Practice of Programming, the Go Programming Language, his latest UNIX: A History and a Memoir. He co-created AWK, the text processing language used by Linux folks like myself. He co-designed AMPL, an algebraic modeling language for large-scale optimization. This conversation is part of the Artificial Intelligence podcast.

Outline:

0:00 – Introduction
4:24 – UNIX early days
22:09 – Unix philosophy
31:54 – Is programming art or science?
35:18 – AWK
42:03 – Programming setup
46:39 – History of programming languages
52:48 – C programming language
58:44 – Go language
1:01:57 – Learning new programming languages
1:04:57 – Javascript
1:08:16 – Variety of programming languages
1:10:30 – AMPL
1:18:01 – Graph theory
1:22:20 – AI in 1964
1:27:50 – Future of AI
1:29:47 – Moore’s law
1:32:54 – Computers in our world
1:40:37 – Life

Machine Learning Robotics
Closed
1 min read

Sergey Levine on Robotics and Machine Learning

Lex Fridman interviews Sergey Levine in episode 108 of his podcast.

Sergey Levine is a professor at Berkeley and a world-class researcher in deep learning, reinforcement learning, robotics, and computer vision, including the development of algorithms for end-to-end training of neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep RL algorithms. This conversation is part of the Artificial Intelligence podcast.

Episode outline:

0:00 – Introduction
3:05 – State-of-the-art robots vs humans
16:13 – Robotics may help us understand intelligence
22:49 – End-to-end learning in robotics
27:01 – Canonical problem in robotics
31:44 – Commonsense reasoning in robotics
34:41 – Can we solve robotics through learning?
44:55 – What is reinforcement learning?
1:06:36 – Tesla Autopilot
1:08:15 – Simulation in reinforcement learning
1:13:46 – Can we learn gravity from data?
1:16:03 – Self-play
1:17:39 – Reward functions
1:27:01 – Bitter lesson by Rich Sutton
1:32:13 – Advice for students interesting in AI
1:33:55 – Meaning of life

AI Ethics
Closed
1 min read

Peter Singer on Suffering in Humans, Animals, and AI

Lex Fridman interviews Peter Singer in this enlightening episode of his podcast.

Peter Singer is a professor of bioethics at Princeton, best known for his 1975 book Animal Liberation, that makes an ethical case against eating meat. He has written brilliantly from an ethical perspective on extreme poverty, euthanasia, human genetic selection, sports doping, the sale of kidneys, and happiness including in his books Ethics in the Real World and The Life You Can Save. He was a key popularizer of the effective altruism movement and is generally considered one of the most influential philosophers in the world. This conversation is part of the Artificial Intelligence podcast.