of them as we've done in previous lectures the big high level ideas are that we attain a neural network and beep reinforcement learning your mind is looking at auxilary losses and if those losses are related to your task well it might help you to learn more quickly than if you did not have those exact losses and of course the most economical paper there was the Unreal paper under the hood a lot of disguise to state representation if we have high dimensional image inputs well hopefully under the hood in this task often there