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2019 | OriginalPaper | Chapter

4. Deep Learning

The Revolution in AI

Author : Tom Taulli

Published in: Artificial Intelligence Basics

Publisher: Apress

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Abstract

Fei-Fei Li, who got a BA degree in physics from Princeton in 1999 with high honors and a PhD in electrical engineering from Caltech in 2005, focused her brilliance on developing AI models. But she had a major challenge: finding quality datasets. At first, she looked at creating them by hand, such as with graduate students who downloaded images from the Internet. But the process was too slow and tedious.

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Footnotes
1
Siddhartha Mukherjee, “The Algorithm Will See You Now,” The New Yorker, April 3, 2017, https://www.newyorker.com/magazine/2017/04/03/ai-versus-md .
 
3
https://medium.com/@GabriellaLeone/the-best-explanation-machine-learning-vs-deep-learning-d5c123405b11
 
4
David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams, “Learning Representations by Back-propagating Errors,” Nature 323 (1986): 533–536.
 
6
Sepp Hochreiter and Jürgen Schmidhuber, “Long Short-Term Memory,” Neural Computation 9, no. 8 (1997): 1735-80.
 
11
Yann LeCun et al., “Gradient-Based Learning Applied to Document Recognition,” Proceedings of the IEEE 86 no. 11 (1998): 2278-2324.
 
12
Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning (Cambridge, MA: The MIT Press, 2016).
 
32
This is from the author’s interview with Sheldon Fernandez, the CEO of DarwinAI.
 
34
This is from the author’s interview with Sheldon Fernandez, the CEO of DarwinAI.
 
35
Gary Marcus, “Deep Learning: A Critical Appraisal,” arXiv, 1801.00631v1 [cs.AI]:1–27, 2018.
 
37
Gary Marcus, Kluge: The Haphazard Construction of the Human Mind (Houghton Mifflin, 2008).
 
Metadata
Title
Deep Learning
Author
Tom Taulli
Copyright Year
2019
Publisher
Apress
DOI
https://doi.org/10.1007/978-1-4842-5028-0_4

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