those other methods just adding Gaussian noise you're usually not going to change you're not going to be able to change your input samples significantly enough and so you just end up with sort of local changes to the samples whereas with targeted augmentation you can really generate diverse diverse samples that are much more useful and in growing your training set and then as well we'll see what some of the methods they had a targeted targeted inductive bias so so yeah you can actually apply approaches that are optimized for the tasks that