I do not misunderstand.

Let's say you put 50-100 seasoned devs on the problem, and within 2-3 years, probably get ZLUDA to the point where most mainstream CUDA applications — ML training/inference, scientific computing, rendering — run correctly on AMD hardware at 70-80% of the performance you'd get from a native ROCm port. Even if its not optimal due to hardware differences, it would be genuinely transformative and commercially valuable.

This would give them runway for their parallel effort to build native greenfield libraries and toolkits and get adoption, and perhaps make some tweaks to future hardware iterations that make compatibility easier.