This reminds me of those "192GB is fantastic" people that bought maxed-out M2 Ultras for AI inference. It can be awesome, but you need a substantial amount of interconnect bandwidth and powerful enough local compute before it's competitive. In products where AI is an afterthought, you're fighting against much different constraints than just having a lot of high-bandwidth memory.
I've always rooted for Team Red when they made an effort to do things open-source and transparently. They're a good role-model for the rest of the industry, in a certain sense. But I have to make peace with the fact that client-side AI running on my AMD machines isn't happening. Meanwhile, I've been using CUDA, CUDNN, CUBLAS, DLSS, on my Nvidia machine for years. On Linux!
This reminds me of those "192GB is fantastic" people that bought maxed-out M2 Ultras for AI inference. It can be awesome, but you need a substantial amount of interconnect bandwidth and powerful enough local compute before it's competitive. In products where AI is an afterthought, you're fighting against much different constraints than just having a lot of high-bandwidth memory.
I've always rooted for Team Red when they made an effort to do things open-source and transparently. They're a good role-model for the rest of the industry, in a certain sense. But I have to make peace with the fact that client-side AI running on my AMD machines isn't happening. Meanwhile, I've been using CUDA, CUDNN, CUBLAS, DLSS, on my Nvidia machine for years. On Linux!