visualization you see how as it goes from rack 1000 to being very close to the image like the leaf beetle looks like the beetle whereas by rank 10000 16000 is not really a beetle anymore but the teacher model has given some probability to beetle when it's a predicting distribution of that image another interesting issue with this framework that's raised in the paper is the idea of inference time with model distillation so in this case we're predicting over a billion unlabeled or weekly labeled images with our teacher