Generative Adversarial Networks

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Sofia Clark 20 Nov 2024

This adversarial approach leads to the continuous improvement of both networks, allowing GANs to generate realistic images, videos, and even music.

Generative adversarial networks (GANs) are reshaping the landscape of artificial intelligence by enabling machines to generate new content autonomously. By using a generator to create synthetic data and a discriminator to evaluate it, GANs refine their outputs through iterative learning. This technology has applications across various sectors, including video game design, digital art, and image editing. GANs are increasingly being employed to create content, enhance training datasets, and develop realistic simulations.