Instruction: Provide a comprehensive explanation of GANs and discuss what sets them apart from other machine learning models.
Context: This question evaluates the candidate's knowledge of one of the most innovative areas of machine learning research and their ability to articulate complex concepts.
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The way I'd explain it in an interview is this: GANs are generative models built around two networks trained in opposition: a generator that tries to create realistic samples, and a discriminator that tries to tell generated samples from real ones. The generator improves by learning how to fool the...