And Hynek , when I wa told him about this , he had an interesting point , and that was th um  the  the final models that they end up training up have I think probably something on the order of six Gaussians per state. So they 're fairly , you know , hefty models. And Hynek was saying that well , probably in a real application ,  you wouldn't have enough compute to handle models that are very big or complicated. So in fact what we may want are simpler models.
Could be.
And compare how they perform to that. But  you know , it depends on what the actual application is and it 's really hard to know what your limits are in terms of how many Gaussians you can have.
Right. And that , I mean , at the moment that 's not the limitation , so.