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What are Generative Adversarial Networks (GANs)?
Generative Adversarial Networks (GANs) are a class of machine learning models composed of two neural networks: a generator and a discriminator. The generator creates fake data, while the discriminator evaluates it against real data. These networks compete with each other, improving over time as the generator gets better at creating realistic data and the discriminator becomes more skilled at detecting fakes. Generative Adversarial Networks are widely used in image generation, video synthesis, and creative AI applications, revolutionizing the way machines produce realistic content.
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