estimation and so on so this all of this you know it pops up in unlikely ways in other fields and it sort of I'm not gonna say it originated here but definitely it was introduced into the popular deep learning world right here so they say an alternative to hierarchical softmax is noise contrastive estimation okay so in noise contrastive estimation posits that a good model should be able to differentiate data from noise by means of logistic regression you know that seems very reasonable this is similar to the hinge loss and so on yada yada