12.1 GANs and their quantum counterparts
Quantum GANs are generative models that can be trained in a perfectly unsupervised manner. By the fact that they are generative models we mean that quantum GANs will be useful for generating data that can mimic a training dataset; for instance, if you had a large dataset with pictures of people, a good generative model would be able to generate new pictures of people that would be indiscernible from those coming from the original distribution. The fact that QGANs can be trained in an unsupervised fashion simply means that our datasets will not have to be labeled; we won’t have to tell the generator whether its output is good or bad, the model will figure that out on its own. How exactly? Stay tuned!
That’s the big picture of GANs, but, before we can explore all their details, there’s something we need to talk about. Let’s talk about how to counterfeit money.
