I wonder how their neural network structures informed the hardware design, such as the dimensions of tensor products. Or is Dojo trying for as general purpose

I wonder how their neural network structures informed the hardware design, such as the dimensions of tensor products. Or is Dojo trying for as general purpose ML as possible? I imagine there is a tension between software and hardware teams where Karpathy's team is always changing things while the hardware team wants specs/reqs. The "tiles of tiles" chip architecture seems like an Elon-obvious, let's just scale what we have approach. Do their neural networks map to that multiscale tiling well?