The tremendous growth in the artificial intelligence (AI) sector over the last several years may be attributed in large part to the proliferation of so-called big data. But even today, data sets of sufficient size and quality are not always available for certain applications. That’s where a technology called generative adversarial networks (GANs) comes in. GANs, which are neural networks comprising two separate networks (a generator and a discriminator network that face off against each another), are useful for creating new (“synthetic” or “fake”) data samples. As a result, one of the hottest areas for AI research today involves GANs,…