there's a constraint here that it's a penalty really used during learning that the the norm of the outputs of the encoder need needs to be as small as possible okay so it's l2 regularization if you want during learning now what how does that give me the information content of the code well let's say that you train without noise right so you train your two encoder is going to assign a code this is in code space it's going to assign a code vector to every training sample these are all of the training samples now I'd know as to