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A class of Artificial Intelligence algorithms used in Unsupervised Machine Learning, where two Neural Networks (a generator and a discriminator) compete with each other in a zero-sum game framework. The generator creates data samples, while the discriminator attempts to distinguish between real and generated data, leading to the generation of highly realistic data over time.