LocalLLaMA

3125 readers

38 users here now

Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.

Get support from the community! Ask questions, share prompts, discuss benchmarks, get hyped at the latest and greatest model releases! Enjoy talking about our awesome hobby.

As ambassadors of the self-hosting machine learning community, we strive to support each other and share our enthusiasm in a positive constructive way.

Rules:

No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.

No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.

No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.

No implying that models are devoid of purpose or potential for enriching peoples lives.

founded 2 years ago

MODERATORS

AMD’s Untether AI Deal - Bad Signs for GPU-Driven AI training (semiconductorsinsight.com)

submitted 2 days ago by [email protected] to c/localllama

15 comments fedilink hide all child comments

It looks like AI has followed Crypto chip wise in going CPU > GPU > ASIC

GPUs, while dominant in training large models, are often too power-hungry and costly for efficient inference at scale. This is opening new opportunities for specialized inference hardware, a market where startups like Untether AI were early pioneers.

In April, then-CEO Chris Walker had highlighted rising demand for Untether’s chips as enterprises sought alternatives to high-power GPUs. “There’s a strong appetite for processors that don’t consume as much energy as Nvidia’s energy-hungry GPUs that are pushing racks to 120 kilowatts,” Walker told CRN. Walker left Untether AI in May.

Hopefully the training part of AI goes to ASIC's to reduce costs and energy use but GPU's continue to improve inference and increase VRAM sizes to the point that AI requires nothing special to run it locally

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 3 points 1 day ago* (last edited 1 day ago)

That’s a premade 8x 7900 XTX PC. All standard and off the shelf.

I dunno anything about Geohot, all I know is people have been telling me how cool Tinygrad is for years with seemingly nothing to show for it other than social media hype, while other, sometimes newer, PyTorch alternatives like TVM, GGML, the MLIR efforts and such are running real workloads.