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I think we're in NVIDIA world for a while, right? You know, you have AMD out there, but AMD doesn't have a performant training fabric, right? Like that's something that's proprietary with an NVIDIA is in fit and band, right? So you can build this, a comparatively performant training fabric with AMD infrastructure, right? So you can kind of only use it then for inference and it's sort of, well, if you've, if you've already trained your model on NVIDIA, it's, it's a tough leap to want to move your
I think that's why you're seeing entities like Microsoft, Meta, et cetera, who are focused on building their own Silicon, right? They're not trying to replace the GPU. They're just trying to solve for different models that they're running internally.
we're building at, I think it's 28 data centers this year across North America. We're one of the largest operators of this infrastructure in the world. And we are unable to keep up with demand. And we really don't see that subsiding for years to come.