[Music] let me cover something else here first so one thing that might happen is as you train the world model on your randomly collected data and then turn your policy and test it in the real world it might not always work the reason might not work is because the randomly collected data might not not have been interesting enough to maybe cover the parts of the space where you would get high reward and so what then you'd want to do is iterate this process at this point you effectively a model-based reinforcement