Deep-learning approaches like transformers and GANs (generative adversarial networks) have propelled amazing progress. Transformers, as described in the previous chapter, can train on text a person has written and learn to realistically imitate their communication style. Meanwhile, a GAN entails two neural networks competing against each other. The first tries to generate an example from a target class, like a realistic image of a woman’s face. The second tries to discriminate between this image and other, real images of women’s faces. The first is rewarded (think of this as scoring points
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