Hi

I don’t get the reason of this correction. I see what Prof. Andrew mentioned in the course the correct. because when encoding is independent of input image, then the output is always zero.

*"Another way for the neural network to give a trivial output is if the encoding for every image was identical to the encoding to every other image, in which case, you again get zero minus zero ",*

He means that you get " **N minus N"** , which is zero.