I think the analysis of (2) is too simplistic because it ignores network effects. A community of developers and users around a specific toolset (e.g. CUDA) is hard to just "buy". Imagine trying to build a better programming language than python -- you could do it for a trillion dollars, but good luck getting the world to use it. For a real example, see Meta and Threads, or any other Twitter competitor.
You have a trillion dollars in incentive. You can use it for more than just creating the software, you can offer incentives to use it or directly contribute patches to the tools people are already using so they support your system. Moreover, third parties already have a large motivation to use any viable replacement because they'd avoid the premium Nvidia charges for hardware.
You could apply this analysis to any of the other big tech innovations like operating systems, search, social media, ...
MS threw a lot of money after Windows Phone. I worked for a company that not only got access to great resources, but also plain money, just to port our app. We took the money and made the port. Needless to say, it still didn't work out for MS.
Those markets have a much stronger network effect (especially social media), or were/are propped up by aggressive antitrust violations, or both.
To use your example, the problem with entering the phone market is that customers expect to buy one phone and then use it for everything. So then it needs to support everything out of the gate in order to get the first satisfied customer, meanwhile there are millions of third party apps.
Enterprise GPUs aren't like that. If one GPU supports 100% of code and another one supports 10% of code, but you're a research group where that 10% includes the thing you're doing (or you're in a position to port your own code), you can switch 100% of your GPUs. If you're a cloud provider buying a thousand GPUs to run the full gamut of applications, you can switch what proportion of your GPUs that run supported applications, instead of needing 100% coverage to switch a single one. Then lots of competing GPUs get made and fund the competition and soon put the competition's GPUs into the used market where they become obtainium and people start porting even more applications to them etc.
It also allows the competition to capture the head of the distribution first and go after the long tail after. There might be a million small projects that are tied to CUDA, but if you get the most popular models running on competing hardware, by volume that's most of the market. And once they're shipping in volume the small projects start to add support on their own.
Why can’t you just build something that’s CUDA-compatible? You won’t have to move anyone over then. Or is the actual CUDA api patented? And will Chinese companies care about that?
AFAIK, CUDA is protected. There are patents, and the terms of use of the compiler forbids using it on other devices.
Of course, most countries will stump over the terms of use thing (or worse, use it as evidence to go after Nvidia), and will probably ignore the patents because they are anticompetitive. It's not only China that will ignore them.
