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Inside the ?Black Box? of a Neural Network


Google Brain
Deep Dream
Olah
ImageNet
art.)Since
AI
the University of Wyoming
Dynamics
CNMN Collection
Nast
Condé Nast


Shan Carter
Chris Olah
OpenAI
Jeff Clune
Geoff Hinton
Marc Raibert
SpotMini

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The New York Times
SOURCE: https://www.wired.com/story/inside-black-box-of-neural-network/
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Summary

On Wednesday, Carter’s team released a paper that offers a peek inside, showing how a neural network builds and arranges visual concepts.This particular line of research dates back to 2015, when Carter’s coauthor, Chris Olah, helped design Deep Dream, a program that tried to interpret neural networks by reverse-engineering them. If you were to squint a bit, you might see rows of white teeth and gums—or, perhaps, the seams of a baseball.As they browsed the images associated with whales and sharks, the researchers noticed that one image—perhaps of a shark's jaws—had the qualities of a baseball.It turns out the neural network they studied also has a gift for such visual metaphors, which can be wielded as a cheap trick to fool the system. By manipulating the fin photo—say, throwing in a postage stamp image of a baseball in one corner—Carter and Olah found you could easily convince the neural network that a whale was, in fact, a shark.By inserting a postage-stamp image of a baseball, they found they could confuse the neural network into thinking a whale was a shark.It’s true, Olah says, that the method is unlikely to be wielded by human saboteurs; there are easier and more subtle ways of causing such mayhem.

As said here by Gregory Barber