Genius Makers: The Mavericks Who Brought A.I. to Google, Facebook, and the World

by Cade Metz

He offered a radically different solution. What they should do, he explained, was build a neural network that learned from another neural network. The first neural network would create an image and try to fool the second into thinking it was real. The second would pinpoint where the first went wrong. The first would try again. And so on. If these dueling neural networks dueled long enough, he said, they could build an image that looked like the real thing. Goodfellow’s colleagues were unimpressed. His idea, they said, was even worse than theirs. And if he hadn’t been slightly drunk, Goodfellow would have come to the same conclusion. “It’s hard enough to train one neural net,” a sober Goodfellow would have said. “You can’t train one neural net inside the learning algorithm of another.” But in the moment, he was convinced it would work.