AMD's best option is a greenfield GPU architecture that puts CUDA in the crosshairs, which is what they already did for datacenter customers with AMD Instinct.
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.
And while compatibility layers aren't illegal, they ordinarily have to be a cleanroom design. If AMD knew that the ZLUDA dev was decompiling CUDA drivers to reverse-engineer a translation layer, then legally they would be on very thin ice.
Those billions are much better-off being spent on new hardware designs, and ROCm integrations with preexisting projects that make sense. Translating CUDA to AMD hardware would only advertise why Nvidia is worth so much.
> it would be genuinely transformative and commercially valuable.
Bullshit. If I had a dime for every time someone told me "my favorite raster GPU will annihilate CUDA eventually!" then I could fund the next Nvidia competitor out of pocket. Apple didn't do it, Intel didn't do it, and AMD has tried three separate times and failed. This time isn't any different, there's no genuine transformation or commercial value to unlock with outdated raster-focused designs.
...but that requires buy-in from the rest of the industry, and it's doubtful FAANG is willing to thread that needle together. Nvidia's hedged bet against industry-wide cooperation is making Jensen the 21st century Mansa Musa.