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.
GPUs are basically halfway to ASICs already. Probably about half of a lot of modern GPU die area is dedicated to or needed to support specialized AI hardware.
I think the next steps are integrated memory and compute, and ternary operations. Integrated memory and compute would probably need specialized hardware, I doubt it would make sense to include anything other than matrix operations and some common AI functions in that sort of processor.
Also, isn't that just an NPU?
They aren't specialized though!
There are a lot of directions "AI" could go:
There's all sorts of wild directions the sector could go. Having the flexibility of an ASIC die would be a huge benefit for AMD, as they don't have to 'commit' to any particular direction like Nvidia's monolithic dies. If a new trend takes off, they can take an existing die and swap out the ASIC relatively quickly, without taping out a whole new GPU.
What about an asic makes it more flexible or easy to swap out? I thought it was just a general term for any application specific chip.
I think NVIDIA's strategy is to have high throughout and compute for fp4,8,16,32,bf8,sparsity,etc and not really commit to much. I guess if the application is very well known there's a bit of overhead in that.
I'm not in industry or anything so I'm not very confident in this but I don't really see how an ASIC would be that different overall
Because it’s a separate physical die.
Taping out, aka simply designing a large GPU chip for production is at least a 9 figure cost. Hence Nvidia/AMD offer a relatively small selection of physical dies in products, as each die has a huge fixed cost. But AMD has specifically taken the approach of splitting up chips into smaller sections, and linking them together by placing them right next to each other, stacking them, and so on.
Hence, if AMD, say, acquire a niche ASIC company, theoretically they can slap a variant of their design next to existing GPUs, or even next to existing CPUs, and have it share the memory bus, general compute, and other functions, without paying the full 9 figures for a massive new chip. There’s still testing costs, but it’s not so prohibitive.
The ASICs will come as soon as the architecture stabilizes. The problem with building specialized hardware today is it won't necessarily be capable of running models that come out tomorrow.
With AMD’s IP, they could make a hybrid chip, eg a (for example) bitnet ASIC hanging off a GPU for flexible, cuda-compatible compute where needed.
Nvidia sorta does this now (with tensor cores being a separate part of the die), but with their history of MCM designs, AMD could take it to an extreme.
Tinygrad is (so far) software only, ostensibly sort of a lightweight PyTorch replacement.
Tinygrad is (so far) not really used for much, not even research or tinkering.
Between that and the lead dev's YouTube antics, it kinda seems like hot air to me.
Ready for pickup in 2-4 days. https://tinycorp.myshopify.com/products/tinybox-red
You're right to be skeptical, but on the other hand, Geohot has done some incredibly impressive things in the past. Like that time he livestreamed buying a new model of Corolla and updating the software on for the comma.ai self-driving hardware to work for it and immediately took it onto the highway.
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.
It’s like bitcoin mining all over again. And providing roughly an equal amount of value.
If you think AI provides the same value as bitcoin you are brain dead
Consider the perspective of the average person: who is gaining value from AI in its current form? It sure as hell isn't us.
It could be if it’s run locally.
If you agents run on your hardware, navigate crappy apps and websites and such for you, what do you need the corporate cloud for? How can they show ads or monetize you through that?
That’s the war raging right now, open-weights vs closed weights.
Consider the perspective of the average person: who is gaining value from AI in its current form? It sure as hell isn’t us.
Ah yeah, the millions of people using it to generate images, generate summaries, translate documents, clean up photos etcetcetc are getting no value from it at all 🙄
Perplexity received 780 million queries in May, CEO Aravind Srinivas shared onstage at Bloomberg’s Tech Summit on Thursday. Srinivas said that the AI search engine is seeing more than 20% growth month-over-month.
edit: why am I having this discussion, if you don't like AI feel free to go literally anywhere else on Lemmy