Generative Adversarial Networks (GANs) are a type of artificial intelligence algorithm which uses two neural networks, a generative network and a discriminative network, to generate new, realistic data from a given input. The generative network creates new data from the input, while the
From Wikipedia
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks compete with each other in the form of a zero-sum game, where one agent's gain is another agent's loss.