Generative adversarial networks (GANs) are a type of AI algorithm used for unsupervised learning, consisting of two competing neural networks, the generator, which creates new data, and the discriminator, which assesses its validity. This interplay allows GANs to generate realistic images, audio, and other types of content. Their applications span diverse fields such as art generation, deepfakes, and data augmentation for training other AI systems. GANs are driving innovation and creativity in both artistic and technical domains.
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