the unlabeled data you have but you only collect label data for that corresponding percentage you can see how much gain it's giving you especially in the low data regime so you basically just need eighty percent fewer labels to match the same amount or accuracy that supervised learning gets so with just ten images per class you're almost close to 80 percent top five accuracy on image classification which is the standard set by alx not and and and you can also see that the supervised state of the art is matched with around like twenty twenty