assumptions that you made the quality of the models that you built in okay let's step through Bayes filters so what builds up step-by-step is the probably the key thing for the second part of lecture so we want to believe which is a distribution over X D given everything from the past including also the current observation of time T now remember it's going to be a recursive thing we're going to already have this presumably for time T minus one and we're going to see if we already had it for t minus one how do we get it for time T what's the