but somehow structurally similar and typically these would come from your prior data now we could simply stop right there and treat meta learning as a nonparametric learning problem so you want to basically use D and D meta train together but oftentimes we want to use high capacity models we don't want to store all of our data and keep it around forever we'd like to somehow to SIL it into a model into a parametric model with learn model parameters so in meta learning we don't want to keep D meta train around forever what we'd like to