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.
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Slides:
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OUTLINE:
0:00 - 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, XL
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