your training distribution and now you might make a not so good prediction make it even worse and this is an accumulation of errors over time can lead to divergence and explicitly avoided any kind of simulations to run over longer horizon need some mechanism to avoid that okay so one mechanism is to explicitly have a loss of a multi-step another mechanisms to ensure that your next state prediction comes from the correct label distribution so if you embed into my Tate unit Gaussian spins then after you do your next state