This work uses a cutting-edge tool called a generative adversarial network, or GAN. It consists of two deep neural networks operating in tandem to learn efficiently from raw data. The GAN internalizes the properties of a particular style simply by looking at lots of examples, and it can then apply that style to an existing item of clothing. GANs, which were developed by a researcher on the Google Brain team, are a hot topic in machine learning today (see “Innovators Under 35: Ian Goodfellow”).

Both these projects were revealed at the workshop organized by Amazon. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends. The company declined to comment on the projects.

Some at the workshop showed how the techniques being developed to track fashion trends could provide broader insights into human behavior. Bala and her colleagues are using information gleaned from Instagram as a form of anthropological research. “We’re trying to understand how people live their daily lives,” she says. “It really is unprecedented in human history that we have this extent of visual records.”

Others are exploring ideas that could feed directly into people’s closets. A group from the University of Illinois in Urbana-Champaign demonstrated an algorithm for identifying fashion-focused social-network accounts. A team from the Indian clothing site Myntra showed a program that guesses a person’s correct size for a particular garment from his or her past purchases.

Tim Oates, a professor at the University of Maryland in Baltimore County, presented details of a system for transferring a particular style from one garment to another. He suggests that this approach might be used to conjure up new items of clothing from scratch. “You could train [an algorithm] on your closet, and then you could say here’s a jacket or a pair of pants, and I’d like to adapt it to my style,” Oates says.

Fashion designers probably shouldn’t fret just yet, though. Oates and other point out that it may be a long time before a machine can invent a fashion trend. “People innovate in areas like music, fashion, and cinema,” he says. “What we haven’t seen is a genuinely new music or fashion style that was generated by a computer and really resonated with people.”

That may be so, but when it comes to fashion-forward algorithms, evidently Jeff Bezos likes what he sees.