going to be pulled together so not only does the let work learn about these augmentations which again for this idea the augmentations aren't even necessary the network there learns a representation space where images of the same class are close together which again is going to make the task of later linear classifiers that needs to separate this class from other classes very very easy and again the other images aren't just going to be pushed away but if they're from the same class let's say this and this image are from