As anybody who has Netflix or has used Amazon knows, these types of services use complex recommendation algorithms to promote similar content that you might like, whether movies or music or mousetraps. A new paper shows how these recommendation algorithms might be improved, however, by taking a cue from biology and thermodynamics. The results are impressive, improving accuracy both for things you are expected to like but also for novel things other people like you like.