One AI works to create, say, realistic images, while a second AI analyzes the results and tries to determine whether the images are real or fake. “You can think of this like an artist and an art critic,” Goodfellow says. “The generative model wants to fool the art critic—trick the art critic into thinking the images it generates are real.” Because the second AI is working so hard to identify images as fake, the first learns to mimic the real in ways it couldn’t on its own.GANS
from Wired: Fabricating the REAL from the FAKE Pit 2 neural networks against each other to identify what makes a realistic image or realistic sound rather than one that's generated synthetically. Compare to Ross Goodwin's word.camera that demonstrates how machine learning turns a camera image into poetry.
