What is Generative Adversarial Networks (GANs)?

Generative Adversarial Networks (GANs) are a type of artificial intelligence algorithm used for unsupervised learning. GANs are composed of two neural networks, a generative network and a discriminative network, which compete against each other in a zero-sum game. The generative network generates data from a given input, while the discriminative network attempts to distinguish between real data and generated data. The two networks continuously improve as they learn from each other, eventually converging on a solution that produces realistic data. GANs have been used to generate realistic images, audio, and text, and can be used for a variety of applications, such as data augmentation, image synthesis, and text-to-image translation.