Generative Adversarial Networks

What happened

Ian Goodfellow and colleagues introduced Generative Adversarial Networks (GANs), in which two neural networks — a generator and a discriminator — are trained against each other, one trying to create realistic data and the other trying to spot fakes.

Why it matters

GANs made it possible for machines to generate startlingly realistic images and helped launch the field of generative AI.

Sources

• Goodfellow et al., arXiv. Generative Adversarial Networks (2014) · Peer-reviewed