Near-term acquihires are certainly a likely bet I think. But given model progress on related benchmarks like kernelbench [1], I do think a set of more commoditized solutions is also inevitable.

The caveat though is that each new gen of hardware often comes with brand new constraints/features that a given generation of models haven't seen before (e.g. tcgen05 in blackwell was OOD at one point). As the models start to generalize better, this might not be a showstopper, but still an issue at least currently.

[1] https://kernelbench.com/

When you run CUDA at scale dealing with nvidia driver and library bugs takes up a disgustingly large percentage of engineer time, I don't know a lot of people who would be looking forward to rely on more nvidia libraries.

Probably not, because the specifics of the workload - exact parameters, representation of data in memory, value ranges etc - lead you to highly divergent optimization strategies.