In order to get their algorithm to produce a legitimately classical-looking portrait, Obvious’s members say they fed it a training data set of more than 15,000 portraits created between the 14th and 20th centuries. Using these images, the algorithm was able to “generate” new images similar to the ones it had been fed. These new portraits were then presented to another algorithm (the “adversarial” part of the GAN acronym) that was trained to distinguish between images produced by humans versus those by machines—a Turing-like test for artworks—until the generated portraits could fool this discriminator into thinking they were “real,” too. Since the announcement, many in the traditional art world have been losing their minds over this new movement, which Obvious has christened “GAN-ism.” But other artists making work via AI think the hype about what the technology can do on its own is premature.