little bit confusing right there what is this model that we are learning and how is it different from the generator well it turns out that for noise contrastive estimation the generator is used as a source of reference noise and the model learns to tell samples apart from noise by assigning higher density to the data so noise contrastive estimation might consist of generating samples from a Gaussian distribution and then training this discriminator function to tell whether a given input comes from the gaussian distribution or it comes from