perceptron to compute the kind of conditioning on the context so instead of this kind of you know cow based method we have an MLP that looks at you know the index for reward t minus one the index forward to minus two and you know T minus let's say just a three word context so these three of these vectors can and together of you know the last three words seen we then run it through a hidden layer and then we feed it through a soft max to try to predict what the next word would be so this is a trigram language model still but we've changed