Aside: all of machine learning has this problem. It’s very trendy right now to predict video frames pixel by pixel, and as you extrapolate these predictions forward by chaining them from other predictions, the result gets blurrier and blurrier. There has been some great work that shows that if you predict in a high level abstract space and only pull out pixel predictions as a byproduct, you can get much sharper predictions that better respect the structure of how things actually move in the world. This is analogous in some ways to the HTM idea of predicting at a coarser temporal resolution.