The cuda happy path is very polished and works reliably. The amdgpu happy path fights you a little but basically works. I think the amd libraries starting to be packaged under Linux is a big deal.
If you don't want to follow the happy path, on Nvidia you get to beg them to maybe support your use case in future. On amdgpu, you get the option to build it yourself, where almost all the pieces are open source and pliable. The driver ships in Linux. The userspace is on GitHub. It's only GPU firmware which is an opaque blob at present, and that's arguably equivalent to not being able to easily modify the silicon.
AMD GPUs work great, the issue is that people don't want to mess with ROCm/HIP when CUDA is kind of the documented workflow. Along with the fact that ROCm was stagnant for a long time. AMD missed the first AI wave, but are now committed to making ROCm into the best it can be.
The other problem is that there aren't any places to rent the high end AMD AI/ML GPUs, like the MI250's and soon to be released MI300's. They are only available on things like the Frontier super computer, which few developers have access to. "regular" developers are stuck without easy access to this equipment.
I'm working on the later problem. I'd like to create more of a flywheel effect. Get more developers interested in AMD by enabling them to inexpensively rent and do development on them, which will create more demand. @gmail if you'd like to be an early adopter.
If you don't want to follow the happy path, on Nvidia you get to beg them to maybe support your use case in future. On amdgpu, you get the option to build it yourself, where almost all the pieces are open source and pliable. The driver ships in Linux. The userspace is on GitHub. It's only GPU firmware which is an opaque blob at present, and that's arguably equivalent to not being able to easily modify the silicon.