Comment by dannyw
3 hours ago
NVIDIA is one of the most open labs.
They even share many of their pre-training and even post-training datasets for Nemotron on HuggingFace; for example: https://huggingface.co/datasets/nvidia/Nemotron-Post-Trainin...
Which other lab shares this?
Yes, there is no question NVIDIA wants to lock you into CUDA and their hardware. But also, they’ve consistently demonstrated the most openness when it comes to model training, datasets, and research; even before the LLM era (e.g. StyleGAN).
There’s also modelscope.cn (china’s huggingface) which is worth checking out. I would not be surprised if one day, we have to use China VPNs to download open weight models.
> NVIDIA is one of the most open labs.
Of course they are. They're commoditizing their complement.
I want to own the hardware, not play around in an nvidia fiefdom full of nvidia rules.
You do own the hardware. Nvidia GPUs have FOSS driver alternatives (Nouveau, NOVA) and have supported OpenCL on the proprietary drivers since 2009.
If you don't want to use CUDA, they expose the PTX bindings to write your own CUDA alternative too: https://docs.nvidia.com/cuda/parallel-thread-execution/index...
When last looked at it, NVIDIA was not supporting OpenCL beyond 1.0.
Also, when running OpenCL, NVIDIA hardware disables multiple DMA engines, and allows only one memory transfer at a time to prevent OpenCL running as fast CUDA.
Did NVIDIA finally allow open source drivers to access all parts and features of the card to allow feature parity? Last time I checked they were considering a plan for planning a solution to that.
I wish OpenCL was usable today like your implying...
nothing stopping you from doing that
Are you joking? They just bought HF for $13bill and didn’t break a sweat. They are dominant and spreading.
Can't buy a decent modern Intel gpu to run AI on because of nividias "donation"
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I'm with Torvalds here, fuck you Nvidia.
"The proprietary shovel seller has some excellent tutorials on how to dig gold. Nobody else has such good step by step guides. Therefore them buying a shovel-agnostic tutorials and techniques method (that has a lot of info on using other shovels effectively) is justified."
They are sharing stuff that makes you consume their stuff. Their position with big ai companies is always vulnerable (asics/direct tsmc relations)
> They are sharing stuff that makes you consume their stuff
No shit Sherlock. Name one company that shared their code to make you NOT to consume their stuff?
NVIDIA is a lot more than a “lab”.
lol “Everything you said is correct but you’re wrong because I’m thinking about something other than what you were talking about”
CUDA is proprietary for a pretty understandable reason. There's no good way for Nvidia to standardize it.
They supported OpenCL when Khronos floated the idea of a GPGPU standard to manufacturers, but OEMs didn't want to design scalable hardware or sponsor the software.