not going to scale with the size of the dataset you're not gonna be able to maintain a separate moving average embedding for every sample if you have if it is that is so big enough like a million or billion images so mean teacher basically amortize that and said that hey if you want to keep an exponential moving average for n bearings why not just keep an expansion moving average for parameters so that you used to take two different views but make sure that the embeddings match that of the moving average versions rather