learning has contributed a lot to the overall quality of this current state of the art model so in conclusion I guess I'd hope that everyone remembers that generative adversarial networks are models that use supervised learning to approximate in intractable costs by estimating ratios and that they can simulate many different cost functions including the one that's used for maximum likelihood the most important research frontier in generative adversarial networks is figuring out how to find Nash equilibria in high