this post was submitted on 04 Apr 2024
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Intresting. But I'm curious about the performance.
A bigger LLM (mixtral) already struggles to run on my mid-range gaming PC. Trying to run an LLM that isn't terrible on a standard laptop wouldn't be a good experience.
I have no idea how this is set up to work technically, but most of the heavy lifting is gonna be on the GPU. I'm not sure that it matters much whether the browser is what's pushing data to the GPU or some other package.
The thought that internet becomes shitty enough that you need a GPU to browse it is really frightening me. If we really reach that point that may be to run an AI which filters out AI generated spam which would really depress me 😭
I mean, there was a point where an FPU was a separate chip and wasn't the norm; now it's built into the CPU.
I think that it's probably safe to say that, in the future, there will be broader use of parallel processing, as we've fundamental limits on what we know we can do there with existing laws of physics with serial processing. That could wind up being part of the CPU. It could live on a separate piece of hardware -- which may not necessarily be a "GPU" -- parallel processing hardware entered the PC because the most-immediate need was to do 3d graphics rendering, but as you can see from the LLMs that people are running on GPUs today, that's not the only application. The parallel compute accelerator cards that Nvidia is selling today for an arm and a leg on servers aren't aimed at doing 3d graphics.
It may not be 3d graphics rendering or running LLMs that becomes the primary application. But I'd be reasonably comfortable saying that down the line, relative to today, there will be more parallel-processing hardware in computers than is present today.
For a lot of newer processors, it already is. Intel, Apple, Samsung, and Qualcomm like to brag about their processors having some sort of neural contraption meant to assist with AI processing.
If it stays around, it might be good enough that you don't need a GPU to do it, since the CPU has an onboard chip that can handle that work instead, since tensor processors like that are a bit more efficient than GPUs, but are also more specialised.