Shutterstock's reverse image search promises a gentler side of AI

For designers and photographers, selecting and laying out photos is often subjective, requiring a keen sense of color and composition. Using a computer algorithm, the stock footage site Shutterstock hopes to make that process easier. It now offers a reverse image search tool that analyzes the pixels in a photo and returns images that are similar in "look and feel" to the original without requiring a user to type in keywords to search. Dragging a photo of a stained-glass cathedral window into the search box, the company demonstrates in a video, produces a series of related images that more closely match the original in color and composition. The new search engine works by using a customized convolutional neural network, a type of machine learning tool that is modeled on how the brain's visual cortex, especially that of animals, processes images.