points and so what we can do is we can take this take this architecture instead of outputting Phi we can output something like H where H is representing a low dimensional vector and then and this will be essentially representing information about the task everything that's needed about the task in order to make predictions and then you can combine this sufficient statistic H with another set of parameters theta G that are also metal learned along with the parameters of F such that with these with both H and theta we can make