r/MachineLearning - [D] Idea for GAN with Memory for Text QA

This is for the purpose of question answering or conversation. I found this architecture unique, because of the shared component of memory between the gen./disc., but I haven't read any GAN papers in the last year so maybe it's already been done? The model needs memory for sequences. Quick proof by example: As a human evaluator, if we give the model some new input (x) like "Who is Yann LeCun" and we know that is outside the training data, then a perfectly ok output is "I don't know.". So the correct answer requires some estimation of the model itself (which it's memory implicitly contains). So to produce a good output (y) after training, during training the model will be implicitly estimating "s", a function of it's own output and state.