I don't think there's much use currently. But I kinda like the direction of the paper anyway. Most mathematical objects in ML have geometric or topological structure, implicitly defined. By making that structure explicit, we at worst have a fresh new perspective on some ML thing. Like how viewing the complex numbers on a 2d cartesian plane often clicks more for students compared to the dry algebraic perspective. So even in the worst case I think there's some pedagogical clarity here.