Lex Fridman shared this lecture by Vivienne Sze in January 2020 as part of the MIT Deep Learning Lecture Series.

Website: https://deeplearning.mit.edu

Slides: 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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