take a soft max you just optimize for the dot products of the averaging words from the neighboring words and the possible product of you are sent over and that's what this loss amounts to and oh and this way the parameters of your loss function end up being your word embedding matrices and all you need to do is take lots of different chunks of text pick particular sent over to pick some respondent neighboring words embed them average neighboring words try to maximize the dot product of the actual central word relatively all the other