out over X T and keep working your way forward all the way till XT plus K and the XT will just still be in the air because she never some doubt over it what is the common smoother the common smoother is exactly what we just covered applied to the situation where these probability distributions are conditional gaussians where conditional of XT plus 1 given X T is a linear Gaussian and a conditional of ZT given XT is a linear Gaussian and then their concrete they're not just like these abstract distributions but in that