Why do we need 10 bits to represent the 1000 classes in AlexNet? I'm reading the AlexNet paper. In section 4, where the authors explain how they prevent overfitting, they mention 


  Although the 1000 classes of ILSVRC make each training example impose 10 bits of constraint on the mapping from image to label". 


What does this mean?
You need 10-bits ($2^{10} = 1024$) to represent 1000 classes.