GAN – Why it worked?

Exploits the loss function of the discriminator to train the generator • The generator never interacts directly with the dataset, only through the discriminator. This minimizes cases where the generator “cheats” by simply copying images from the dataset. • This technique can be used with any machine learning algorithm, and not only for image generation (cheap chatbots)