two versions of a picture come from the same picture or from different pictures and now if you simply train a linear classifier on top of these representations you're doing extremely well already so we know these representations they actually learn something about these images so that's the first part then stage 2 let's cancel all of that stage 2 is you want to do supervised fine tuning now you already see that the arrow here coming out is not this was a task agnostic big CNN the arrow is actually coming out of those