Is it possible to make a ML algorithm which has only "noise" data for training and then identifies abnormalities? It seems like that's people do that easily and it would be ideal for an application like this where you might not have much training data on all the "not noise" types of examples.

Another application would be a security camera that detects unusual events without having to train it on actual burglars.