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Comment by chasd00 | Hacker News Reader

To me CoreWeave is the one to watch. They have to actually bring all these promised datacenters online, operational, and profitable. They basically got a $2B bailout from Nividia a week or so ago but they're back to sinking.

https://ts2.tech/en/coreweave-stock-slips-as-class-action-no...

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I think ARM is the one to watch. Softbank only has a 10% float of their stock.

90% of their stock is being used as collateral against 33 banks for 18 billion stargate loan to OpenAI.

Given Japanese bond markets right now, 30% circular financing, if the AI narrative falls, ARM is gonna blow up.

Consumer can eat all the GPUs they have and more if we stop trying to force B2B

Right we have a loop where AI is so expensive (because it's priced to feast on B2B margins) that the best consumer experiences aren't affordable, and they're not affordable so they don't go mainstream, and they're not mainstream so no one is willing to take less money and bank on the incredible volume that would emerge if it went mainstream.

If we can get model pricing cheaper AI entertainment alone will probably carry things (I'm 99% sure NovelAI is already one of their largest customers outside of major AI labs)

> Consumer can eat all the GPUs they have and more if we stop trying to force B2B

You should really crunch the numbers on buying and then running enough compute to run a leading edge model. The economics of buying it (never mind running it) just dont add up.

You still haven't factored in "training", the major problem right now that every one remains head in sand about.

I dont need a model to know who Tom Cruise is or how to write SQL if I am asking it "set up my amazon refund" or "cancel xyz service". The moment someone figures out how to build targeted and small it will take off.

And as for training, well having to make ongoing investment into re-training is what killed expert systems, it's what killed all past AI efforts. Just because it's much more "automated" doesn't mean it isnt the same "problem". Till a model learns (and can become a useful digital twin) the consumer market is going to remain "out of reach".

That doesn't mean we dont have an amazing tool at hand, because we do. But the way it's being sold is only going to lead to confusion and disappointment.

Consumer, as in B2C, not consumers buying directly. B2C companies will happily buy (or rent from people who are buying today) GPUs, because a huge part of the game is managing margins to a degree B2B typically doesn't need to concern itself with.

> I dont need a model to know who Tom Cruise is or how to write SQL if I am asking it "set up my amazon refund" or "cancel xyz service". The moment someone figures out how to build targeted and small it will take off.

I think people got a lot of ideas when dense models were in vogue that don't hold up today. Kimi K2.5 maybe be a "1T parameter model" but it only has 32B active parameters and still easily trounces any prior dense model, including Llama 405B...

Small models need to make sense in terms of actual UX since beating these higher sparsity MoEs on raw efficiency is harder than people realize.

Even if consumer can eat all the gpus, it cannot have the margins (as you say), and thus won’t sustain the current valuations all these companies have and which fuel the (necessary) investments.

NVIDIA is sitting on 74% gross margin. If we reach a place where "all" these companies have to do to unlock nearly unbounded demand is take lower margins, they will find capital.

If anything I'm more worried about the consumers than the companies.

It is not nvidia who has problems here, but the ai companies which depend on huge valuations for their continuous funding and survival, thus also those who invest on those valuations. I am not worried about them though, I hope they all burn to the ground, but alas it will not be them who pay for it in the end.

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