AI and Art
Adversarial training is a machine learning technique where a model learns to improve its performance by engaging in a competitive process against another model, typically involving a generator and a discriminator. This approach allows the generator to produce increasingly realistic data while the discriminator tries to distinguish between real and generated data, leading to more robust models. Through this back-and-forth process, adversarial training enhances the ability of generative models to produce high-quality outputs, which is particularly crucial in contexts like image generation and other creative AI applications.
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