Deep-learning algorithm predicts photos' memorability at "near-human" levels

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have created an algorithm that can predict how memorable or forgettable an image is almost as accurately as humans -- and they plan to turn it into an app that subtly tweaks photos to make them more memorable. For each photo, the "MemNet" algorithm -- which you can try out online by uploading your own photos -- also creates a heat map that identifies exactly which parts of the image are most memorable. "Understanding memorability can help us make systems to capture the most important information, or, conversely, to store information that humans will most likely forget," says CSAIL graduate student Aditya Khosla, who was lead author on a related paper. "It's like having an instant focus group that tells you how likely it is that someone will remember a visual message." Team members picture a variety of potential applications, from improving the content of ads and social media posts, to developing more effective teaching resources, to creating your own personal "health-assistant" device to help you remember things.