Generative Adversarial Nets

Generative Adversarial Networks (GANs) are a framework for training generative models. Two networks, a generator and a discriminator, are trained in adversarial competition. The generator creates synthetic data, while the discriminator tries to distinguish between real and generated data. This process pushes the generator to produce increasingly realistic outputs, which can be used for creating visually consistent social media posts and marketing materials.