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Prediction - we are going to figure out SOTA AI performance without requiring 1TB of memory within a year or so. Of course CXMT, Micron, and family will still
by fooker 3mo ago
Prediction - we are going to figure out SOTA AI performance without requiring 1TB of memory within a year or so.
Of course CXMT, Micron, and family will still be profitable, but maybe not 'surge 470% from IPO' profitable.
- yieldcrv 3mo agothat would be perfect timing Hyperscalers are screwed, data center mania couldn’t even be completed during this massive spending spree, all while the people seemingly sitting on the sidelines are working on getting these things baked into the OS and chipsets in a way consumers wouldn’t notice
- Dibby053 3mo agoWhat do you base this prediction on? It seems very unlikely, unless by SOTA you mean the current SOTA.
- oblio 3mo ago> What do you base this prediction on? Their posterior. Or worse, their interest in going to the moon (HODL style, not Artemis style).
- ImprobableTruth 3mo agoThe fundamental issue is that for these systems bigger is essentially always better (if affordable). So if we can squash something like Kimi K3 down to run on a 'normal' system, that just incentivizes devs to increase the model size until once again we're at the limit of what can be run.
- raincole 3mo agoAnd by the time the models that require 1TB memory will be better. It's like people saying mobile chips are going to be better than PC chips... until they realize PC can be made of mobile chips too if that comes true.
- fooker 3mo agoNo, it's like saying a chip that consumes 500W is going to be better than a chip that consumes 200W. This used to be true for the first several decades of microprocessors, and stopped being true in the early 2000s.
- xyzsparetimexyz 3mo agoHow would we do that? There's no historic precedent for that. Its fundamentally an information theory thing: what's the max amount of intelligence you can get out of 1 KB/MB/GB? There has to be a limit and I'm not convinced that it's far off.
- yieldcrv 3mo agoIt’s not just about small models, that’s only one part of evolution Some groups are baking models into silicone, Deepmind has an example, it gets 18,000 tokens/sec on Llama 3.1, not sure about parameter size
- intrasight 3mo agoI think this is the future - at least it will be for on-device models. Apple, for instance, will "bake silicon" once a year for their current model, and use that chip in all their devices.
- fooker 3mo ago> Some groups are baking models into silicone While some other groups are baking silicone into models :)
- yieldcrv 3mo agoThose are doctors fooker! but yes misplaced e
- londons_explore 3mo agoIt doesn't matter. However much intelligence you can squeeze into 1 GB, people will always want more. Standard Def TV was plenty for 50 years. But when more was on offer, everyone went for it, and now you can't even buy a 480p TV.
- t-sauer 3mo agoYour example also counters your point: A lot of people do not care about 4k, and even less do care about 8k or above. We reached a point where most people are completely happy with the quality they get.
- dist-epoch 3mo agoEven if we do, we are going to need a lot of RAM for the billions of agents running everywhere.
- clbrmbr 3mo agoAre you thinking of fundamental architectural changes (like the Transformer)? Or incremental (like MoE or GQA)? Are there specific neolabs or techs you are following that lead you to this prediction? Indeed it seems quite possible we are one architecture breakthrough away from existing chip stock driving us all the way to ASI. Nobody has done AFAIK the information theory to prove it’s not possible.
- greenavocado 3mo agoNOPE. The opposite will happen. CXMT will flood the market thus making 1 TB models affordable.
- whazor 3mo agoYeah, you can directly print the SOTA AI model on the chip. I also believe this can be done on older process nodes. The most important factor would be speed. How fast can you go from new model to new chip?
- tornikeo 3mo agoSoTA AI will move well past 1TB+ memory requirements in 1 year or so. Also, you will be able to play with much more competent models locally. They will still feel like children compared to the adults living in the SoTA region.
- hahahaa 3mo ago"we" being China?
- leoc 3mo agoI think the chipmakers are pretty securely set up here, the usual cyclical issues aside. Between the stubborn resistance of the data to being compressed without significant loss, and to a lesser extent the ability to do more with more memory (we’re surely at diminishing returns for LLMs already, but diminishing doesn’t mean zero) it seems like a fairly safe guess (I am not an expert on anything) that for the next decade at least you’ll still want at least 128-256GiB of video RAM to have a comfortably “SOTA-enough” experience. Then the other side of the rectangle comes from putting that VRAM in every consumer and office-worker device. Selling everything at a big premium to a few efficiency-obsessed SaaS providers is what you do when you’re temporarily supply-constrained. Sidelining the SaaS middlemen and selling to gloriously inefficient consumers who will leave their laptops closed for most of the day is the dream. This is probably not unrelated to the fact that the country which is currently making a big strategic push into memory manufacturing is also championing open models.
- petra 3mo agoAnd besides llm's memory requirements: -HBM has a lot of room to grow(bandwidth/power/density). And an HBM memory takes 3x the amount of wafers of regular DRAM. -HBM + better DRAM designs could increase random memory access speed by alot. I've seen research talking about 7x. At what point it makes sense that half of consumer GPUs and most of the server GPU/CPUs start using HBM?
- lardosaurusrex 3mo ago[dead]
- empath75 3mo agoYou can get _better_ that SOTA AI performance by burning the weights directly to silicon, the problem is you're locked into that model
- yogthos 3mo agoI'm looking forward to being able to buy CXMT chips for running SOTA models locally. :)
- cco 3mo agoIt sounds like you have strong faith that if we can do in 100GB what we can do in 1TB today, 10x-ing our model size[1] from today won't be better? [1]whether it is 10x in size, or maybe running 10x the models to have things like judges etc.