Deep Learning State of the Art (2019)

Lex Fridman · Beginner ·📐 ML Fundamentals ·7y ago
New lecture on recent developments in deep learning that are defining the state of the art in our field (algorithms, applications, and tools). This is not a complete list, but hopefully includes a good sampling of new exciting ideas. For more lecture videos visit our website or follow code tutorials on our GitHub repo. INFO: Website: https://deeplearning.mit.edu GitHub: https://github.com/lexfridman/mit-deep-learning Slides: http://bit.ly/2HiZyvP Playlist: http://bit.ly/deep-learning-playlist OUTLINE: 0:00 - Introduction 2:00 - BERT and Natural Language Processing 14:00 - Tesla Autopilot Hardware v2+: Neural Networks at Scale 16:25 - AdaNet: AutoML with Ensembles 18:32 - AutoAugment: Deep RL Data Augmentation 22:53 - Training Deep Networks with Synthetic Data 24:37 - Segmentation Annotation with Polygon-RNN++ 26:39 - DAWNBench: Training Fast and Cheap 29:06 - BigGAN: State of the Art in Image Synthesis 30:14 - Video-to-Video Synthesis 32:12 - Semantic Segmentation 36:03 - AlphaZero & OpenAI Five 43:34 - Deep Learning Frameworks 44:40 - 2019 and beyond CONNECT: - If you enjoyed this video, please subscribe to this channel. - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Instagram: https://www.instagram.com/lexfridman
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Uploads from Lex Fridman · Lex Fridman · 48 of 60

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1 Ido Portal: Movement
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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)
Theano Tutorial (Pascal Lamblin, MILA)
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 10 Deep Reinforcement Learning (John Schulman, OpenAI)
Deep Reinforcement Learning (John Schulman, OpenAI)
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 11 Deep Learning for Speech Recognition (Adam Coates, Baidu)
Deep Learning for Speech Recognition (Adam Coates, Baidu)
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 12 Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
Deep Learning for Natural Language Processing (Richard Socher, Salesforce)
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 13 Foundations of Unsupervised Deep Learning (Ruslan Salakhutdinov, CMU)
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)
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
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
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
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
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
Emilio Frazzoli, CTO, nuTonomy - MIT Self-Driving Cars
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 36 Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars
Sterling Anderson, Co-Founder, Aurora - MIT Self-Driving Cars
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 37 MIT AGI: Cognitive Architecture (Nate Derbinsky)
MIT AGI: Cognitive Architecture (Nate Derbinsky)
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 38 MIT Advanced Vehicle Technology Study (MIT-AVT)
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)
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
Comfortably Numb Solo | Pink Floyd Cover by Lex Fridman
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 43 Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4
Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4
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 44 Jeff Atwood: Stack Overflow and Coding Horror | Lex Fridman Podcast #7
Jeff Atwood: Stack Overflow and Coding Horror | Lex Fridman Podcast #7
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 45 Eric Schmidt: Google | Lex Fridman Podcast #8
Eric Schmidt: Google | Lex Fridman Podcast #8
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 46 Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10
Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10
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 47 Deep Learning Basics: Introduction and Overview
Deep Learning Basics: Introduction and Overview
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 ▶ Deep Learning State of the Art (2019)
Deep Learning State of the Art (2019)
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 49 MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
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 50 Self-Driving Cars: State of the Art (2019)
Self-Driving Cars: State of the Art (2019)
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 51 Drago Anguelov (Waymo) - MIT Self-Driving Cars
Drago Anguelov (Waymo) - MIT Self-Driving Cars
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 52 Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars
Oliver Cameron (CEO, Voyage) - MIT Self-Driving Cars
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 53 Karl Iagnemma & Oscar Beijbom (Aptiv Autonomous Mobility) - MIT Self-Driving Cars
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
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)
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
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
Rajat Monga: TensorFlow | Lex Fridman Podcast #22
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 60 Gavin Miller: Adobe Research | Lex Fridman Podcast #23
Gavin Miller: Adobe Research | Lex Fridman Podcast #23
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Chapters (14)

Introduction
2:00 BERT and Natural Language Processing
14:00 Tesla Autopilot Hardware v2+: Neural Networks at Scale
16:25 AdaNet: AutoML with Ensembles
18:32 AutoAugment: Deep RL Data Augmentation
22:53 Training Deep Networks with Synthetic Data
24:37 Segmentation Annotation with Polygon-RNN++
26:39 DAWNBench: Training Fast and Cheap
29:06 BigGAN: State of the Art in Image Synthesis
30:14 Video-to-Video Synthesis
32:12 Semantic Segmentation
36:03 AlphaZero & OpenAI Five
43:34 Deep Learning Frameworks
44:40 2019 and beyond
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