> Really though, LLM makers have only one true supplier: NVIDIA
The argument relies on the axiom that NVIDIA will have a persistent hardware advantage. Maybe they will, but even if they were always 2 years ahead of the competition, if NVIDIA-trained LLMs would 'good enough' in 2025, then non-NVIDIA-trained LLMs would be 'good enough' in 2027.
> NVIDIA will have a persistent hardware advantage
I think it probably has more to do with CUDA. The reason Python is the undisputed champion in AI and ML isn't because Python is a better, more performant programming language so much as because ecosystem of software in the AI/ML space is extremely concentrated, dense, and rich in the Python ecosystem compared to Java, Go, or C#.
Likewise, it seems like NVDAs advantage isn't even necessarily the hardware but the suite of tools and software that are built up to take advantage of that hardware.
It's definitely not CUDA advantage. If you can get Pytorch/flash attention/triton well supported in any hardware, a huge chunk of client don't care if it means cost saving. Case in point Google's TPU had extensive usage outside Google when they were cheaper for the same performance. Now that isn't the case.
It's TSMC more than NVIDIA.
And it's ASML more than TSMC.
Or maybe there's a highly profitable role for all the different parts of the value chain.