entire space of optimum and and with with those types of problems we see that the it is actually a little bit easier to find something where you're simply one or a few gradient steps away and in fact in a minute I'll talk about the expressive power of of the Manuel algorithm and its ability to adapt even when your tasks are extremely different with regard to architectures I'll talk a bit about that but in practice we do find that it scales well to to larger larger architectures but it may require a bit more tuning than other meta