GAN

A GAN trains two neural networks against each other: a generator that forges content and a discriminator that tries to spot the forgery, each making the other better. GANs made the first convincing deepfakes and synthetic faces. Diffusion models have taken over much of image generation, but the adversarial idea, and the deepfake problem it unleashed for fraud and identity verification, are here to stay.