a new algorithm consistently outperformed humans at a variation of the task in which users are shown 2 photos and asked which scene is closer to a McDonald’s. To create the algorithm, the team trained a computer on a set of 8m Google images from 8 major US cities that were embedded with GPS data on crime rates and McDonald’s locations. They then used deep-learning techniques to help the program teach itself how different qualities of the photos correlate. For example, the algorithm independently discovered that some things you often find near McDonald’s franchises include taxis, police vans, and prisons.

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