In the podcast, Ian Goodfellow discusses the potential applications of generative adversarial networks (GANs). He notes that while GANs have shown potential in some areas, they are still in development and may not perform as well as classifiers trained on the same data. One potential application of GANs is generating data that is differentially private, which could be used for fairness audits.
In this video, Ian Goodfellow discusses the importance of generative adversarial networks (GANs), and how they can be used to resist adversarial examples. He says that dynamic models which update their predictions will be key in this regard.