cross-posted from: https://lemmit.online/post/4242386
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The original was posted on /r/pcmasterrace by /u/trander6face on 2024-10-24 11:11:47+00:00.
I would have preferred if they had used the die space for the GPU, not this bullshit.
But then, how would ai save our future?
You can use it for blurring your background on your camera
ah that’s good
I got an Asus Vivobook with a pretty new AMD chipset that has one… running Fedora, no Idea how to make something use it either :/
Also on an Asus laptop with Fedora, after following some obscure instructions from amd I managed to get a Python script to confirm the npu exists and is technically functional… But apparently to do anything approaching useful, I need the slightly fancier npu. What a waste.
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I have heard of ollama before, is this the same thing?
I checked, ollama does not use npu
So, what? Is that only trained on ethical data?
Because i bloody doubt itIt’s not a specific model, its a harness for running models. You can find ethically trained models to run on it though iirc.
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Is it any good? Curious to hear what you’re using it for and how it compares
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I wonder if they have implemented NPU support into Folding@Home yet.
There are no plans for it, at least not for a while. Apparently F@H workloads are not suitable for the current NPUs
The only thing I can think of is AI video game upscalers. Other than that, yeah, it’s a waste of silicon.
which software exactly (that uses npu instead of gpu)?
I don’t think there is one currently, but that’s a potential use.
Co-pilot for example and other LLM types of neural network processing not tied to Nvidia.
You need a model compiled for the architecture. I saw some for the RK35xx devices when shopping for hardware. I do not think there is software made to split up or run models in general on a NPU. The models must be configured for the physical hardware topology. The stuff that runs on most devices is very small, and these either need a ton of custom fine tuning or they are barely capable of simple tasks.
On the other hand, segmentation models are small, and that makes layers, object identification, and background removal stuff work. Looking at your CPU speed, and available memory, it is unlikely to make much difference. You are also memory constrained for running models, though you could use deepspeed to load from a disk drive too.
