Judea Pearl: Correlation and Causation | AI Podcast Clips

Lex Fridman · Beginner ·🛡️ AI Safety & Ethics ·6y ago
Full episode with Judea Pearl (Dec 2019): https://www.youtube.com/watch?v=pEBI0vF45ic Clips channel (Lex Clips): https://www.youtube.com/lexclips Main channel (Lex Fridman): https://www.youtube.com/lexfridman (more links below) Podcast full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Podcasts clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 Podcast website: https://lexfridman.com/ai Podcast on Apple Podcasts (iTunes): https://apple.co/2lwqZIr Podcast on Spotify: https://spoti.fi/2nEwCF8 Podcast RSS: https://lexfridman.com/category/ai/feed/ 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. Subscribe to this YouTube channel or connect on: - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - Medium: https://medium.com/@lexfridman - Support on Patreon: https://www.patreon.com/lexfridman
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from Lex Fridman · Lex Fridman · 0 of 60

← Previous Next →
1 Ido Portal: Movement
Ido Portal: Movement
Lex Fridman
2 Ryan Hall: Moral Victory
Ryan Hall: Moral Victory
Lex Fridman
3 Jimmy Pedro: Judo | Take It Uneasy Podcast
Jimmy Pedro: Judo | Take It Uneasy Podcast
Lex Fridman
4 Foundations of Deep Learning (Hugo Larochelle, Twitter)
Foundations of Deep Learning (Hugo Larochelle, Twitter)
Lex Fridman
5 TensorFlow Tutorial (Sherry Moore, Google Brain)
TensorFlow Tutorial (Sherry Moore, Google Brain)
Lex Fridman
6 Nuts and Bolts of Applying Deep Learning (Andrew Ng)
Nuts and Bolts of Applying Deep Learning (Andrew Ng)
Lex Fridman
7 Sequence to Sequence Deep Learning (Quoc Le, Google)
Sequence to Sequence Deep Learning (Quoc Le, Google)
Lex Fridman
8 Torch Tutorial (Alex Wiltschko, Twitter)
Torch Tutorial (Alex Wiltschko, Twitter)
Lex Fridman
9 Theano Tutorial (Pascal Lamblin, MILA)
Theano Tutorial (Pascal Lamblin, MILA)
Lex Fridman
10 Deep Reinforcement Learning (John Schulman, OpenAI)
Deep Reinforcement Learning (John Schulman, OpenAI)
Lex Fridman
11 Deep Learning for Speech Recognition (Adam Coates, Baidu)
Deep Learning for Speech Recognition (Adam Coates, Baidu)
Lex Fridman
12 Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
Lex Fridman
13 Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU)
Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU)
Lex Fridman
14 Deep Learning for Computer Vision (Andrej Karpathy, OpenAI)
Deep Learning for Computer Vision (Andrej Karpathy, OpenAI)
Lex Fridman
15 Foundations and Challenges of Deep Learning (Yoshua Bengio)
Foundations and Challenges of Deep Learning (Yoshua Bengio)
Lex Fridman
16 MIT 6.S094: Introduction to Deep Learning and Self-Driving Cars
MIT 6.S094: Introduction to Deep Learning and Self-Driving Cars
Lex Fridman
17 MIT 6.S094: Deep Reinforcement Learning for Motion Planning
MIT 6.S094: Deep Reinforcement Learning for Motion Planning
Lex Fridman
18 MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task
MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task
Lex Fridman
19 MIT 6.S094: Recurrent Neural Networks for Steering Through Time
MIT 6.S094: Recurrent Neural Networks for Steering Through Time
Lex Fridman
20 MIT 6.S094: Deep Learning for Human-Centered Semi-Autonomous Vehicles
MIT 6.S094: Deep Learning for Human-Centered Semi-Autonomous Vehicles
Lex Fridman
21 Chris Gerdes (Stanford) on Technology, Policy and Vehicle Safety - MIT Self-Driving Cars
Chris Gerdes (Stanford) on Technology, Policy and Vehicle Safety - MIT Self-Driving Cars
Lex Fridman
22 Sertac Karaman (MIT) on Motion Planning in a Complex World - MIT Self-Driving Cars
Sertac Karaman (MIT) on Motion Planning in a Complex World - MIT Self-Driving Cars
Lex Fridman
23 MIT Sloan: Intro to Machine Learning (in 360/VR)
MIT Sloan: Intro to Machine Learning (in 360/VR)
Lex Fridman
24 MIT 6.S094: Deep Learning
MIT 6.S094: Deep Learning
Lex Fridman
25 MIT Self-Driving Cars (2018)
MIT Self-Driving Cars (2018)
Lex Fridman
26 MIT 6.S094: Deep Reinforcement Learning
MIT 6.S094: Deep Reinforcement Learning
Lex Fridman
27 MIT 6.S094: Computer Vision
MIT 6.S094: Computer Vision
Lex Fridman
28 MIT 6.S094: Deep Learning for Human Sensing
MIT 6.S094: Deep Learning for Human Sensing
Lex Fridman
29 MIT AGI: Artificial General Intelligence
MIT AGI: Artificial General Intelligence
Lex Fridman
30 MIT AGI: Building machines that see, learn, and think like people (Josh Tenenbaum)
MIT AGI: Building machines that see, learn, and think like people (Josh Tenenbaum)
Lex Fridman
31 Ray Kurzweil: Future of Intelligence | MIT 6.S099: Artificial General Intelligence (AGI)
Ray Kurzweil: Future of Intelligence | MIT 6.S099: Artificial General Intelligence (AGI)
Lex Fridman
32 Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
Lex Fridman
33 Lisa Feldman Barrett: How the Brain Creates Emotions |  MIT Artificial General Intelligence (AGI)
Lisa Feldman Barrett: How the Brain Creates Emotions | MIT Artificial General Intelligence (AGI)
Lex Fridman
34 Stephen Wolfram: Computational Universe | MIT 6.S099: Artificial General Intelligence (AGI)
Stephen Wolfram: Computational Universe | MIT 6.S099: Artificial General Intelligence (AGI)
Lex Fridman
35 Emilio Frazzoli, CTO, nuTonomy - MIT Self-Driving Cars
Emilio Frazzoli, CTO, nuTonomy - MIT Self-Driving Cars
Lex Fridman
36 Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars
Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars
Lex Fridman
37 MIT AGI: Cognitive Architecture (Nate Derbinsky)
MIT AGI: Cognitive Architecture (Nate Derbinsky)
Lex Fridman
38 MIT Advanced Vehicle Technology Study (MIT-AVT)
MIT Advanced Vehicle Technology Study (MIT-AVT)
Lex Fridman
39 MIT-AVT: Data Collection Device (for Large-Scale Semi-Autonomous Driving)
MIT-AVT: Data Collection Device (for Large-Scale Semi-Autonomous Driving)
Lex Fridman
40 Geoffrey Hinton: What are you excited about in deep learning?
Geoffrey Hinton: What are you excited about in deep learning?
Lex Fridman
41 Ilya Sutskever: OpenAI Meta-Learning and Self-Play | MIT Artificial General Intelligence (AGI)
Ilya Sutskever: OpenAI Meta-Learning and Self-Play | MIT Artificial General Intelligence (AGI)
Lex Fridman
42 Comfortably Numb Solo | Pink Floyd Cover by Lex Fridman
Comfortably Numb Solo | Pink Floyd Cover by Lex Fridman
Lex Fridman
43 Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4
Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4
Lex Fridman
44 Jeff Atwood: Stack Overflow and Coding Horror | Lex Fridman Podcast #7
Jeff Atwood: Stack Overflow and Coding Horror | Lex Fridman Podcast #7
Lex Fridman
45 Eric Schmidt: Google | Lex Fridman Podcast #8
Eric Schmidt: Google | Lex Fridman Podcast #8
Lex Fridman
46 Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10
Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10
Lex Fridman
47 Deep Learning Basics: Introduction and Overview
Deep Learning Basics: Introduction and Overview
Lex Fridman
48 Deep Learning State of the Art (2019)
Deep Learning State of the Art (2019)
Lex Fridman
49 MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
Lex Fridman
50 Self-Driving Cars: State of the Art (2019)
Self-Driving Cars: State of the Art (2019)
Lex Fridman
51 Drago Anguelov (Waymo) - MIT Self-Driving Cars
Drago Anguelov (Waymo) - MIT Self-Driving Cars
Lex Fridman
52 Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars
Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars
Lex Fridman
53 Karl Iagnemma & Oscar Beijbom (Aptiv Autonomous Mobility) - MIT Self-Driving Cars
Karl Iagnemma & Oscar Beijbom (Aptiv Autonomous Mobility) - MIT Self-Driving Cars
Lex Fridman
54 Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15
Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15
Lex Fridman
55 Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17
Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17
Lex Fridman
56 Ian Goodfellow: Generative Adversarial Networks (GANs) | Lex Fridman Podcast #19
Ian Goodfellow: Generative Adversarial Networks (GANs) | Lex Fridman Podcast #19
Lex Fridman
57 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
Lex Fridman
58 Chris Lattner: Compilers, LLVM, Swift, TPU, and ML Accelerators | Lex Fridman Podcast #21
Chris Lattner: Compilers, LLVM, Swift, TPU, and ML Accelerators | Lex Fridman Podcast #21
Lex Fridman
59 Rajat Monga: TensorFlow | Lex Fridman Podcast #22
Rajat Monga: TensorFlow | Lex Fridman Podcast #22
Lex Fridman
60 Gavin Miller: Adobe Research | Lex Fridman Podcast #23
Gavin Miller: Adobe Research | Lex Fridman Podcast #23
Lex Fridman

Related AI Lessons

Latest Metrics Show AI Models Surpassing Humans
AI models are surpassing humans in many technical fields, with serious implications for cybersecurity, and professionals must adapt to leverage these models effectively
Medium · Cybersecurity
Big Tech firms are accelerating AI investments and integration, while regulators and companies focus on safety and responsible adoption.
Big Tech firms are accelerating AI investments while focusing on safety and responsible adoption, and you can apply these principles to your own projects by prioritizing ethics and transparency
Dev.to AI
Big Tech firms are accelerating AI investments and integration, while regulators and companies focus on safety and responsible adoption.
Big Tech firms are accelerating AI investments while focusing on safety and responsible adoption, and you can apply these principles to your own AI projects
Dev.to AI
The April 18, 2026 AI Security Awakening: 7 Undiscovered Wealth Engines From the OWASP & MCP…
Learn about the AI security crisis on April 18, 2026, and discover 7 undiscovered wealth engines from OWASP and MCP
Medium · AI
Up next
The AI, Climate, and Energy Connection
Coursera
Watch →