opportunity to learn by itself how to use the potentially relevant parts of the M of the model network to solve new problems more quickly and if it wants to it can learn to ignore the M and sometimes it's a good idea to ignore the the M because it's really bad it's a bad predictor in this particular situation of life where the control is currently trying to maximize r1 however it can also allow and to address and exploit some of the sub programs that came about in the model network through compressing the data by predicting it so it now has