A common training technique for the creation of generative AI pits two networks with complementary learning objectives against each other. Such networks are referred to as generative adversarial networks or GANs. The objective of the generator network is to create potential outputs, while the objective of the discriminator network is to prevent poor outputs from being generated. By analogy, one can think of the generator as being tasked with brainstorming and the discriminator as being tasked with assessing which ideas are relevant and realistic. In the training phase, the generator and
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