Generative Adversarial Nets

Generative Adversarial Networks (GANs) are a framework for training generative models. Two networks, a generator and a discriminator, are trained simultaneously. The generator creates new data instances, while the discriminator evaluates them for authenticity. Through this adversarial process, the generator learns to produce increasingly realistic data, and this technology is often used in AI logo generation to create diverse design options based on user inputs.