Michael I. Jordan: Machine Learning, Recommender Systems, and Future of AI | Lex Fridman Podcast #74

Lex Fridman · Beginner ·🤖 AI Agents & Automation ·6y ago
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. This episode is presented by Cash App. Download it & use code "LexPodcast": Cash App (App Store): https://apple.co/2sPrUHe Cash App (Google Play): https://bit.ly/2MlvP5w PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 EPISODE LINKS: (Blog post) Artificial Intelligence -- The Revolution Hasn’t Happened Yet: https://hdsr.mitpress.mit.edu/pub/wot7mkc1 OUTLINE: 0:00 - Introduction 3:02 - How far are we in development of AI? 8:25 - 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? CONNECT: - Subscribe to this YouTube channel - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfr
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2 Ryan Hall: Moral Victory
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3 Jimmy Pedro: Judo | Take It Uneasy Podcast
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4 Foundations of Deep Learning (Hugo Larochelle, Twitter)
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5 TensorFlow Tutorial (Sherry Moore, Google Brain)
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6 Nuts and Bolts of Applying Deep Learning (Andrew Ng)
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7 Sequence to Sequence Deep Learning (Quoc Le, Google)
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8 Torch Tutorial (Alex Wiltschko, Twitter)
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9 Theano Tutorial (Pascal Lamblin, MILA)
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10 Deep Reinforcement Learning (John Schulman, OpenAI)
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11 Deep Learning for Speech Recognition (Adam Coates, Baidu)
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12 Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
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13 Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU)
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14 Deep Learning for Computer Vision (Andrej Karpathy, OpenAI)
Deep Learning for Computer Vision (Andrej Karpathy, OpenAI)
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15 Foundations and Challenges of Deep Learning (Yoshua Bengio)
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16 MIT 6.S094: Introduction to Deep Learning and Self-Driving Cars
MIT 6.S094: Introduction to Deep Learning and Self-Driving Cars
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17 MIT 6.S094: Deep Reinforcement Learning for Motion Planning
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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
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19 MIT 6.S094: Recurrent Neural Networks for Steering Through Time
MIT 6.S094: Recurrent Neural Networks for Steering Through Time
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20 MIT 6.S094: Deep Learning for Human-Centered Semi-Autonomous Vehicles
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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
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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
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23 MIT Sloan: Intro to Machine Learning (in 360/VR)
MIT Sloan: Intro to Machine Learning (in 360/VR)
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24 MIT 6.S094: Deep Learning
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25 MIT Self-Driving Cars (2018)
MIT Self-Driving Cars (2018)
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26 MIT 6.S094: Deep Reinforcement Learning
MIT 6.S094: Deep Reinforcement Learning
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27 MIT 6.S094: Computer Vision
MIT 6.S094: Computer Vision
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28 MIT 6.S094: Deep Learning for Human Sensing
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29 MIT AGI: Artificial General Intelligence
MIT AGI: Artificial General Intelligence
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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)
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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)
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32 Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
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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)
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34 Stephen Wolfram: Computational Universe | MIT 6.S099: Artificial General Intelligence (AGI)
Stephen Wolfram: Computational Universe | MIT 6.S099: Artificial General Intelligence (AGI)
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35 Emilio Frazzoli, CTO, nuTonomy - MIT Self-Driving Cars
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36 Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars
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37 MIT AGI: Cognitive Architecture (Nate Derbinsky)
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38 MIT Advanced Vehicle Technology Study (MIT-AVT)
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39 MIT-AVT: Data Collection Device (for Large-Scale Semi-Autonomous Driving)
MIT-AVT: Data Collection Device (for Large-Scale Semi-Autonomous Driving)
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40 Geoffrey Hinton: What are you excited about in deep learning?
Geoffrey Hinton: What are you excited about in deep learning?
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41 Ilya Sutskever: OpenAI Meta-Learning and Self-Play | MIT Artificial General Intelligence (AGI)
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42 Comfortably Numb Solo | Pink Floyd Cover by Lex Fridman
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43 Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4
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44 Jeff Atwood: Stack Overflow and Coding Horror | Lex Fridman Podcast #7
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45 Eric Schmidt: Google | Lex Fridman Podcast #8
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46 Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10
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47 Deep Learning Basics: Introduction and Overview
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48 Deep Learning State of the Art (2019)
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49 MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
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50 Self-Driving Cars: State of the Art (2019)
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51 Drago Anguelov (Waymo) - MIT Self-Driving Cars
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52 Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars
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53 Karl Iagnemma & Oscar Beijbom (Aptiv Autonomous Mobility) - MIT Self-Driving Cars
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54 Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15
Leslie Kaelbling: Reinforcement Learning, Planning, and Robotics | Lex Fridman Podcast #15
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55 Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17
Greg Brockman: OpenAI and AGI | Lex Fridman Podcast #17
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56 Ian Goodfellow: Generative Adversarial Networks (GANs) | Lex Fridman Podcast #19
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57 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
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58 Chris Lattner: Compilers, LLVM, Swift, TPU, and ML Accelerators | Lex Fridman Podcast #21
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59 Rajat Monga: TensorFlow | Lex Fridman Podcast #22
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60 Gavin Miller: Adobe Research | Lex Fridman Podcast #23
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Chapters (18)

Introduction
3:02 How far are we in development of AI?
8:25 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?
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