The paper, authored by six of Apple’s researchers, doesn’t focus on AI that someone with an iPhone might interact with, but rather how to create enough data to effectively train it. Specifically, the research focuses on making realistic fake images—mostly of humans—to train facial recognition AI. It addresses a core problem: training a machine takes a huge amount of data. Moreover, training a machine on matters like faces and body language can take a ton of personal data. The ability to manufacture this kind of training data and still achieve high results could allow Apple to build AI that understand how humans function (the way we move our hands or look around a screen) without needing to use any user data while building the software.