auxilary objective or tasks or you know hand design some method that allows you to improve performance once you flip the switch and go to a supervised learning on the standard machine learning great data or in the limit as we'll talk later get rid of the need entirely to have a classic supervised learning data side and potentially begin to learn tasks in a purely unsupervised way and evaluate them in a like zero shot setting so there's a variety of methods this lecture is going to focus primarily on auto regressive maximum-likelihood