The team then used that information to train a generative adversarial network (GAN), a type of artificial intelligence that is especially proficient when it comes to generating realistic images. A GAN works by having two networks train on the same data. One of the networks generates fake images based on that data set, while the other network uses the same data to determine whether an image is real. This method lets the network improve its results. For this research, the GAN created multiple images of items for each user.

GANs, which were created by Ian Goodfellow, one of MIT Technology Review’s 35 Innovators Under 35 for 2017, have been in the news recently: after a different research team trained them on real images of Hollywood stars, the networks were able to create eerily believable fake celebrity faces. The faces weren’t all perfect, though—some had blurred areas or were missing features like eyebrows. There were fewer such problems with the fashion project, largely because the images used to train the networks were all shot from the same angle on white backgrounds, which makes generating convincing images much easier—something that would be essential if they were ever to be used to sell clothing.

Adding GANs to recommender systems could help online retailers figure out what customers want beyond the items that already exist. Still, researchers would need to figure out quite a few things before that could happen, including how to turn the two-dimensional computer-generated images into 3-D renderings that could be used to produce a piece of clothing.

“It’s not like we are generating a sewing pattern,” says Julian McAuley, a computer scientist at UC San Diego and one of the paper’s authors.

The team’s GAN also has a way to go before it can replace a stylist or even suggest a new outfit. At the moment, for a shopper who liked blue shirts, the GAN creates more blue shirts—hardly a revelation. Preference for black pants did feed into the GAN to create khakis, but the system can’t create a set of shoes that would go well with a certain pair of pants yet.