widely used because it turns out that um you know rarely do you have a data set of where all the images are either caused or motorcycles and nothing else but the only thing we're doing is just missing the label so this is kind of useful but isn't why they use where as in um what I call self-taught learning the goal is to take you know totally random images that may be caused may be old cycles may be totally other random things and to can you can use somehow use this to learn to distinguish the miles and many cycles and one weight is