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The Race to Buy the Human Brains Behind Deep Learning Machines

Any aspiring science fiction writer looking for a good protagonist could do worse than ripping off the Wikipedia page for Demis Hassabis: He grew up in England as a chess prodigy and built absurdly sophisticated video games before getting a degree in computer science from Cambridge, started studying neuroscience and publishing respected papers on amnesia and other topics, and then proceeded to co-found one of the hottest artificial-intelligence startups. Now that his company, DeepMind, has been snapped up by Google for a reported $400 million to $500 million (depending on your tech blog of choice), exactly how this latest twist will change his story remains to be seen—but there’s a decent chance Hassabis will ultimately become commander of an army of humanoid Googlebots.

Google’s acquisition of Hassabis and the rest of the DeepMind team points to the surging interest in the field of deep learning, a funky part of computer science seen as key to building truly intelligent machines. It centers on having computers learn to do tasks and find patterns on their own. Google, for example, received attention a couple of years ago, when its network of self-learning computers were able to understand the concept of a cat and find cats in YouTube videos. (There’s obviously way more complexity to deep learning than cat videos, and you’re welcome to expand your horizons on the subject here.)