Machine learning is at its best when there’s way too much information for any human to comb through manually, like making high-volume stock trades or surfacing the best posts from hundreds of friends on Facebook.

Now one Estonia-based startup, Teleport, is using this idea, coupled with images from Google Street View, to automatically look around cities and see if people will like them based on their lifestyle preferences.

In a Medium post, Teleport co-founder Silver Keskkula walks through an example of the process. First, he plots 10,000 randomized points throughout a city, and grabs images taken by Google Street View. Then those images are run through computer-vision algorithms that identify objects, people, and buildings, and describes them in a short sentence. Words are a lot easier to search than images, and the final step is calculating which phrases or words are most common, like “a country road” or “a man riding a skateboard up the side of the road.”

Keskkula’s example focuses on motorcycles: He owns two and is interested in a city that welcomes them. If the AI sees a lot of motorcycles around, it’s able to predict that the city has a culture of motorcyclists, and then rank it higher as a potential place to move. (Of course, this doesn’t take into account pending laws and regulations or the temperament of drivers towards motorcyclists.) Teleport currently allows you to select whether you want to live around parks, safe streets, trees, and other visible markers.

The idea of extracting information from Google Street View was inspired by MIT Media Lab’s StreetScore project, Keskkula writes, where machine learning was used to rank the safety of 3,000 streets in New York and Boston.