Lecture by Vivienne Sze in January 2020, part of the MIT Deep Learning Lecture Series.
Website: https://deeplearning.mit.edu
Slides: href=”http://bit.ly/2Rm7Gi1″ target=”_blank” rel=”nofollow”>http://bit.ly/2Rm7Gi1
Playlist: http://bit.ly/deep-learning-playlist
LECTURE LINKS:
Twitter: https://twitter.com/eems_mit
YouTube: https://www.youtube.com/channel/UC8cviSAQrtD8IpzXdE6dyug
MIT professional course: http://bit.ly/36ncGam
NeurIPS 2019 tutorial: http://bit.ly/2RhVleO
Tutorial and survey paper: https://arxiv.org/abs/1703.09039
Book coming out in Spring 2020!
OUTLINE:
0:00 – Introduction
0:43 – Talk overview
1:18 – Compute for deep learning
5:48 – Power consumption for deep learning, robotics, and AI
9:23 – Deep learning in the context of resource use
12:29 – Deep learning basics
20:28 – Hardware acceleration for deep learning
57:54 – Looking beyond the DNN accelerator for acceleration
1:03:45 – Beyond deep neural networks
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