stars i just show to the studio network as traditionally the set of samples x and y and i will have n samples each sample will live in dimension p so before p was the order of the tensor now p will be the dimension till the end of the talk and then the student may or may not not know the architecture of the teacher network i will actually be telling you about both cases in this talk and the question is what is the generalization error that the gradient descent is reaching depending on the number of samples that