look at that legs back coding solves a scheme on the previous slide we sample I from PR given X the cost descendant is log of 1 over PI then we send X cost is log 1 over P of X given are all the same as in the previous line base back idea with exact difference between approximate inference later what will it do the recipient decodes I and X but knows the distribution for a given X because they have the corresponding model on their side so what that means is that there see piant actually can recover the random seed that you used to