you have a different way of obtaining the positive and the negative samples in this case positive samples are everything that's in the context negative samples are just randomly sampled from the data set and that you know works of course that works much much much faster and you can see that this this turns out to give you vectors that are pretty good and you can train with higher vectors sorry with higher dimensional vectors you can train with bigger vocabularies with this this has turned out to be very very influential