That said, these GPUs aren't just the GPUs. They are whole chassis. They are huge onboard storage arrays, TB's of RAM, 800G networking (and associated cables), racks, cooling, power distribution, backup power, etc...
None of it is easy.
I did a lot of unique optimizations to autotune each individual GPU for performance by tweaking the software knobs on them. They are all snowflakes. Same model, different batches (heck, even same batch!), can produce wildly different performance results.
Over the years, I did try to find some alternative workloads for it, but nothing could even pay for the power costs. The GPUs were very old models (rx470-rx580) and the rest of the hardware wasn't that advanced, like it is in AI, so none of it was transferred.
I'm in the process of building my own AI supercomputer now. Really looking forward to seeing how it turns out.
Nobody else on the planet was able to automate the tuning like I did, which had a direct influence on ROI. I know this because it required a very specific change to the AMD drivers to enable that functionality to happen.
That said, latest 4th gen nvlink is 900G...
https://www.nvidia.com/en-us/data-center/nvlink/
But unless you're sleeping with Jensen, you're not going to see it for 52 weeks+ after you order it.
Our lead time hasn't been horrible actually, but I work for a pretty big corp