| > Either CUDA will open up, if it is to survive or open API use will spread. CUDA won't die if Open APIs take over AI inferencing operations. It's still used and applied in so many niche industries that it can only be "replaced" in industries like AI where companies invest in moving digital mountains. Stuff like Microsoft's ONNX project will go a long way towards making CUDA unneccesary for AI acceleration, but it won't ever kill the demand for CUDA. Just look at how lethargic the industry's response has been in the wake of AI, and look at how other companies like AMD and Apple abandoned OpenCL before it was ready. Now Apple is banking on CoreML as an integration feature and AMD is segmenting their consumer and server hardware like crazy. > Weirdly, NVIDIA hardware only outperforms competitors on its own API. When you compare NVIDIA on a level playing field, they aren't the clear winners. That does not reflect any of the benchmarks I've seen at all, unless by "level playing field" you mean comparing old Nvidia chips to modern AMD ones. The only systems comparable to the DGX pods Nvidia sells is Apple's hardware, which lacks the networking and OS support to be competitive server side. AMD is an amazing company for being open and transparent with their approach, but nice guys always finish last. This is a race between the highest-density TSMC customers, which means it's Apple and Nvidia laughing their respective paths to the bank. |