Lecture on most new investigate and developments in deep studying, and hopes for 2020. This is not meant to be a record of SOTA benchmark benefits, but relatively a set of highlights of machine learning and AI improvements and development in academia, business, and culture in normal. This lecture is section of the MIT Deep Discovering Lecture Series.
Outline:
:00 – Introduction
:33 – AI in the context of human history
5:47 – Deep mastering celebrations, development, and restrictions
6:35 – Deep mastering early essential figures
9:29 – Constraints of deep learning
11:01 – Hopes for 2020: deep finding out group and exploration
12:50 – Deep discovering frameworks: TensorFlow and PyTorch
15:11 – Deep RL frameworks
16:13 – Hopes for 2020: deep understanding and deep RL frameworks
17:53 – Organic 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 up-domain dialogue
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: 6-player no-limit Texas hold’em poker
43:13 – OpenAI Rubik’s Dice
44:49 – Hopes for 2020: Deep RL and self-enjoy
45:52 – Science of deep studying
46:01 – Lottery ticket hypothesis
47:29 – Disentangled representations
48:34 – Deep double descent
49:30 – Hopes for 2020: science of deep mastering
50:56 – Autonomous vehicles and AI-assisted driving
51:50 – Waymo
52:42 – Tesla Autopilot
57:03 – Open up issue for Stage 2 and Amount 4 methods
59:55 – Hopes for 2020: autonomous vehicles and AI-assisted driving
1:01:43 – Federal government, politics, plan
1:03:03 – Advice units and coverage
1:05:36 – Hopes for 2020: Politics, plan and recommendation units
1:06:50 – Classes, Tutorials, Books
1:10:05 – General hopes for 2020
1:11:19 – Recipe for development in AI
1:14:15 – Q&A: what produced you interested in AI
1:15:21 – Q&A: Will devices ever be able to assume and come to feel?
1:18:20 – Q&A: Is RL a fantastic prospect for obtaining AGI?
1:21:31 – Q&A: Are autonomous automobiles responsive to sound?
1:22:43 – Q&A: What does the future with AGI seem like?
1:25:50 – Q&A: Will AGI techniques become our masters?
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