train it with method methods like truncated back prop where we only update for and compute you know how to modify the the transition function of the state for up to like maybe 32 words or 64 words so it might be biased in that way but it's kind of just still can potentially learn to encode a lot of information into a learned memory system instead of kind of using like hard coded methods of just like keeping the explicit input presentations so here we get again like probably one of the first real language models where on that