of space that is properly we constructed as small as you want or or larger if you want the general form is something like this where Z equals some cost function that measures the discrepancy between the data point and the decoder function applied to Z the decoder function is trainable and then you have a regularizer that limits the information content essentially of z k-means does this implicitly by restricting Z to be a discrete variable okay PCA or things similar to this implicitly do this by limiting the dimension of Z