"needs work" is an understatement. ROCM only just came out for windows(!) and so far everyone in the LLM and SD scene says that ROCM on linux is a pain in the ass to get working, requires a lot of hackery and override environment variables, is buggy, and also only supports a small handful of cards - whereas CUDA runs on nearly everything NVIDIA makes, from laptop GPUs to datacenter compute cards. And there's very little support on the third party software side at the moment.

That "no consumer hardware support" sounds stupid, but people getting into ML/AI, grad students, etc want to be able to mess around and develop/prototype on local hardware they already own.

You cannot do that with ROCM, because they only support a very, very small number of consumer-level cards - and very oddly, it's a mix of the very high end and low end, nothing in the middle.

AMD is also massively behind hardware-wise with only the current 7xxx series cards that just came out having AI-specific hardware, whereas NVIDIA has had tensor cores for three generations of their cards.

But of course AMD can't do anything right, so they nerfed the GPU's graphics processing cores when they added the AI stuff, making the cards a worse deal from a pure gaming standpoint. The 7000 series cars are basically a tiny bump at best, and in many games worse, than the 6000 series equivalents. Their only advantage is better hardware video encoding support and somewhat better power consumption.