Most of the big OSS AI codebases (LLM and Diffusion, at least) have code to work on any GPU, not just nVidia GPUs, now. There's a slight performance benefit to sticking with nVidia, but once you need to split work across multiple GPUs, you can do a cost-benefit analysis and decide that, say, 12 AMD GPUs is faster than 8 nVidia GPUs and cheaper, as well.
Then nVidia's moat begins to shrink because they need to offer their GPUs at a somewhat reduced price to try to keep their majority share.
UTF-16 is also just as complicated as UTF-8 requiring multibyte characters to cover the entirety of Unicode, so it doesn't avoid the issue you're complaining about for the newest languages added, and it has the added complexity of a BOM being required to be sure you have the pairs of bytes in the right order, so you are more vulnerable to truncated data being unrecoverable versus UTF-8.
UTF-32 would be a fair comparison, but it is 4 bytes per character and I don't know what, if anything, uses it.
Then nVidia's moat begins to shrink because they need to offer their GPUs at a somewhat reduced price to try to keep their majority share.