Scanning photographs can be time consuming, especially if you’re looking for things depicted in thousands of satellite images of Earth.
With that in mind, a geospatial data firm in New Mexico developed an A.I.-powered search engine that can rapidly search through billions of aerial and satellite images to find specific landmark features that are alike. Stanford University developed a similar system to track poverty levels in African villages over time, though their algorithm looks for changes to housing, lighting, agriculture, and roads to assess each tracked village’s economic health.
Little doubt that such A.I. capabilities will soon be advanced enough to find the proverbial needle in a haystack.