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AI is supposed to do anything human or traditional computer can do, that is what we expect AI to be. Technically you would need AGI (Artifical General Intelligence) to do anything a human can do. This is not a technology that exists, but a goal of some AI research to perform more and more general tasks. So 'generating random value' is also a task ...


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In general, you should train both discriminator D and generator G simultaneously. Depending on the metric that you use as the target for your model, you may encounter a Vanishing gradient problem. It can happen when you implement original loss (i.e. JS-divergence). In that case D can become overconfident regarding fake samples and won't provide any useful ...


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