# What is the principial difference between zero-shot learning and k-NN and clusterization based methods?

One can consider clustering and k-NN to be a zero-shot, too?

I think there is no much principal difference, except using some neural network architecture (usually it is a transformer) which is used to build embedding space, i.e. simplify nearest neighbours search.

Am I wrong? What am I missing?