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Part of the problem is that MRIs involve a series of pictures that act like “slices” of the human body, that are assembled to create a 3D model, a time-consuming process.

“What we’re looking at with our technology is, what if you don’t need to look at all the slices to build up a full 3D image?” she said. “We take a few slices and based on the information in those slices, we decide what slices to get next. So now we have an adaptive acquisition procedure.”

The idea is that if an algorithm can make guesses at how to fill in the missing parts of a 3D image, and then test those guesses to improve accuracy, there could be all sorts of applications beyond medical imaging.

This kind of research matters to Facebook in a big way, because the company is relying heavily on artificial intelligence to hold their social networking empire together.

When Facebook CEO Mark Zuckerberg testified to the U.S. Congress in the wake of the Cambridge Analytica privacy scandal, he repeatedly talked about artificial intelligence tools as a key tool for the social media platform.

Already, Facebook uses AI to detect terrorist propaganda and block bad actors from setting up fake accounts. Zuckerberg said other problems are more difficult for AI tools, such as the persistent problem with hate speech.

“Artificial intelligence” can be a nebulous term, but for the most part it involves using machine learning algorithms, and in particular deep learning neural networks.