10% of the of the images labeled and they do that essentially using a clustering algorithm where the discriminator learns to assign the objects to groups and then this understanding that objects can be grouped into you know similar types helps it to form more realistic ideas of what should be appearing in the image because it knows that every image it creates has to come from one of these archetypal groups rather than just being some arbitrary image if you train again with no class labels you tend to get things that look sort of like grass or