Deep Learning State of the Art (2020)
Lecture on most recent research and developments in deep learning, and hopes for 2020. This is not intended to be a list of SOTA benchmark results, but rather a set of highlights of machine learning and AI innovations and progress in academia, industry, and society in general. This lecture is part of the MIT Deep Learning Lecture Series.
Website: https://deeplearning.mit.edu
Slides: http://bit.ly/2QEfbAm
References: http://bit.ly/deeplearn-sota-2020
Playlist: http://bit.ly/deep-learning-playlist
OUTLINE:
0:00 - Introduction
0:33 - AI in the context of human history
5:47 - Deep learning celeb…
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Chapters (37)
Introduction
0:33
AI in the context of human history
5:47
Deep learning celebrations, growth, and limitations
6:35
Deep learning early key figures
9:29
Limitations of deep learning
11:01
Hopes for 2020: deep learning community and research
12:50
Deep learning frameworks: TensorFlow and PyTorch
15:11
Deep RL frameworks
16:13
Hopes for 2020: deep learning and deep RL frameworks
17:53
Natural language processing
19:42
Megatron, XLNet, ALBERT
21:21
Write with transformer examples
24:28
GPT-2 release strategies report
26:25
Multi-domain dialogue
27:13
Commonsense reasoning
28:26
Alexa prize and open-domain conversation
33:44
Hopes for 2020: natural language processing
35:11
Deep RL and self-play
35:30
OpenAI Five and Dota 2
37:04
DeepMind Quake III Arena
39:07
DeepMind AlphaStar
41:09
Pluribus: six-player no-limit Texas hold'em poker
43:13
OpenAI Rubik's Cube
44:49
Hopes for 2020: Deep RL and self-play
45:52
Science of deep learning
46:01
Lottery ticket hypothesis
47:29
Disentangled representations
48:34
Deep double descent
49:30
Hopes for 2020: science of deep learning
50:56
Autonomous vehicles and AI-assisted driving
51:50
Waymo
52:42
Tesla Autopilot
57:03
Open question for Level 2 and Level 4 approaches
59:55
Hopes for 2020: autonomous vehicles and AI-assisted driving
1:01:43
Government, politics, policy
1:03:03
Recommendation systems and policy
1:05:36
Hopes for 2020: Politics, policy an
Playlist
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