After selling the first artificial intelligence generated artwork earlier this year, deep learning algorithms are now tackling portraits -- of made-up people that don't exist. In a research paper, Nvidia recently shared the results of a generative adversarial network (GAN) trained to generate images of people while unsupervised. The concept is based in part on style transfer technology, which transfers the style of one image onto another in order to do anything from building a photo app like Prisma to creating realistic deep fakes. Nvidia researchers redesigned the GAN to use a style transfer, while adjusting that style on each layer of code. The change, the researchers say, allows the software to generate high-level attributes like subtle differences in poses as well as random variation in features.