replaced that MLP with a recurrent neural network and that allows for handling potentially unbounded context now it handles that context in a learn fashion so you'll get an input word vector at one time step and you'll have this context buffer which is a learned memory state that the RNN kind of modifies and updates and you'll use that to kind of represent a running summary of everything you've seen that's important for predicting the next potential word this has potentially unbounded context but in practice we'll