Multiple-instance learning

Multiple-instance learning is a way for computers to figure out things by looking at many examples at once, instead of just one at a time. For example, if you wanted to teach a computer to recognize cats, you could show it multiple pictures of cats, instead of just one. By looking at several examples, the computer can learn what a cat looks like and be able to recognize it better.