me I can use that to inform my learning of the classifier boundary because the this tribution of the unlabeled data suggests that there's actually some clusters inside this data set and I can I can use that to you know come up with a a classifier boundary that's better than the one that I would have come up with if I only have those labeled examples so that's the distinction between few shot and semi-supervised all right so the first method which is a method for semi-supervised learning that went into this paper is so-called pseudo labeling