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Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

reuters.com

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Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#201

Post by kingleopold »

fooker wrote: post #195
lardosaurusrex wrote: post #188

Earlier quoted context omitted.

You just stated yourself that it costs more now used than when they were new. If everyone's running local then why are these larger companies dumping cash into data centres?

Economies of scale. You need a cluster of 8-12 H100s to run the largest models locally. It doesn't make sense to run these locally yet unless your use case also involves making it available for several dozen concurrent users.

not to miss, future models will be more compute hungry too. Current hardware prices are still goin up and no it's not cheaper to run your AI for like %99 of the people because of lots of costs, it's not just hardware.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#203

Post by dundarious »

fullshark wrote: post #142
epistasis wrote: post #59

I'm thinking Apple has been really smart in their AI strategy here. It seems a mistake to make unprecedentedly large capital expenditures, in a very very crowded space, without much evidence of a moat. Presumably people thought the moat would be singularity-like self-improvement of AI, but the singularity is merely a religious concept, and nobody should take religious myth as fact, it's merely narrative for orientati…

Their strategy to let Siri stagnate for 15 years and let everyone else take that market? Their strategy to put a bunch of not ready for consumer use AI features on their devices and then roll them back? They just have such a strong hardware + os ecosystem that they can sit on the sidelines. They'll be able to negotiate with some LLM provider at a good discount when the time is right and put harnesses around it for ac…

The point was that one rational approach is that it's OK to not be top ranked in a market that has significant medium-term profitability issues. Apple has no problem creating new markets, but not if being top ranked requires years and years and years without return on investment after launch, and large subsidies. Not to say Apple hasn't failed at creating new markets either, or anything like that.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#204

Post by tsoukase »

tedggh wrote: post #113

The current commitment by hyperscalers is around 1.7T USD, reported liabilities 1.3T and this year global debt related to AI is 570B. So that’s around 3T total. For this to make sense AI must generate 2T in new revenue per year by the end of the decade. And that would be only a 10% ROIC. For context ROIC for big tech is around 35% so at 10% they will be barely breaking even. The SP500 gives 10-12%. With 10% ROIC from…

Everyone that has invested even a dollar to AI believes the revenue will easily surpass the most optimistic predictions. Ask them.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#205

Post by Imustaskforhelp »

fooker wrote: post #158
tedggh wrote: post #113

The current commitment by hyperscalers is around 1.7T USD, reported liabilities 1.3T and this year global debt related to AI is 570B. So that’s around 3T total. For this to make sense AI must generate 2T in new revenue per year by the end of the decade. And that would be only a 10% ROIC. For context ROIC for big tech is around 35% so at 10% they will be barely breaking even. The SP500 gives 10-12%. With 10% ROIC from…

H100 is nearing five years and costs more to buy a used one now than a new one when it was released :) You are completely missing the bet these companies are making. They think can outlast their competitors and capture a larger portion of the pie while the cost of inference keeps going down dramatically. If you haven't been paying attention, the cost is about 1/100th of what it was in 2024. This is the trajectory pre…

> They think can outlast their competitors and capture a larger portion of the pie while the cost of inference keeps going down dramatically.

We are also within an arms race of training newer larger models with more speed while discontinuing older models.

Gemini/Chatgpt have already discontinued their models from 2024 (iirc) because they are using all their compute in serving/training newer models. Being quite frank, nobody is serving a model from 2024 as the intended use-case while having very little moat as open source models are catching up.

> Of course there will be market crashes and corrections and things like that and most companies won't survive, but the bet is that whoever survives ends up doing pretty well.

How so, by raising the prices? because the current prices aren't sustainable and I feel as if there would certainly be companies which will try for one reason or other to be cheaper to capture the market share because of the larger promise of whoever is able to get as market share. I had once thought about it and I don't think that even in an ideal world, they would end up doing pretty well given no moat.

Also even if a company survives and ends up being one of the survivors and makes profit in the ideal scenario you mention, then within some years other companies will try again and construct more datacenters and end up driving the prices down for everyone, so nobody knows how things might look down for 2-3 years let alone a decade, so I remain a bit skeptic currently so.

I had actually thought some on the economics of datacenters and I found it to be very related to power. The only ones which seems to be making money might be the power generators actually because power is the actual bottleneck rather than GPU's in datacenters from my understanding.

Though the power is raised at the cost of electricity bill increases for everybody including people living in houses. The job prospects are minimal as well, as a nation, aside from just getting investment just for the sake of it because AI's trendy right now, I feel like its a net negative deal for people living there.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#206

Post by spwa4 »

lardosaurusrex wrote: post #188
fooker wrote: post #158

Earlier quoted context omitted.

H100 is nearing five years and costs more to buy a used one now than a new one when it was released :) You are completely missing the bet these companies are making. They think can outlast their competitors and capture a larger portion of the pie while the cost of inference keeps going down dramatically. If you haven't been paying attention, the cost is about 1/100th of what it was in 2024. This is the trajectory pre…

You just stated yourself that it costs more now used than when they were new. If everyone's running local then why are these larger companies dumping cash into data centres?

Google's doing a attempt to answer that (while still firmly hiding who their customers are) here: https://blog.google/innovation-and-ai/technology/research/un...

They promise updates.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#207

Post by postflopclarity »

kingleopold wrote: post #202
postflopclarity wrote: post #170

Earlier quoted context omitted.

real

historical did not have free money printer this big

there's always something. technology has come a long way. AI is disruptive, but so were railways, electricity, the transistor, etc...

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#208

Post by Imustaskforhelp »

gavin_gee wrote: post #108

i dont understand the concern. they are putting up great financials. you have to invest ahead of the outcome. this is just classic quarterly public company earnings BS, where public markets dont reward innovation investment. they just want crank the handle financials. The bigger issue is on the model front, can Google compete; Gemini doesnt seem to be able to compete on the heavy expert end; they are doing well on li…

> you have to invest ahead of the outcome

> this is just classic quarterly public company earnings BS, where public markets dont reward innovation investment

Genuine question; but aren't these treating stocks as speculative and on vibes? One can say that these comments could be true for the first signs of cracking of dot com bubble. Sure, Web eventually succeeded but many tech giants from dot com era (AOL/Yahoo and so many more) eventually went to dust for spending too much time on the innovative bandwagon.

During the Dot-com bubble really tried to give this example but IIRC there were companies like pets.com who lost 2$ for every 1$ of sale so how a company treats its financials do matter a lot.

The market doesn't seem to reward innovation sometimes because there have been times the first persons to innovative have actually really failed to capitalize on that innovation and many extremely innovative businesses like Airlines (We can literally fly speak of innovation!) have been terrible businesses investment-wise generally speaking.

Re: Alphabet's cash burn raises alarm for Big Tech as AI spending climbs

#209

Post by lardosaurusrex »

kingleopold wrote: post #201
fooker wrote: post #195

Earlier quoted context omitted.

Economies of scale. You need a cluster of 8-12 H100s to run the largest models locally. It doesn't make sense to run these locally yet unless your use case also involves making it available for several dozen concurrent users.

not to miss, future models will be more compute hungry too. Current hardware prices are still goin up and no it's not cheaper to run your AI for like %99 of the people because of lots of costs, it's not just hardware.

I think this fails to take into account how many people are fine with "fast enough" vs "fastest".

I've seen people happily use AI that takes several minutes to generate text or edit an image because to them they already aren't using their computer when they tell it to start; they just grab their phone and walk away and come back only to check in on it.

I feel like people here and on other technology discussions -- although it's worse here -- don't seem to parse what being the minority means.

They know they're one of the few to have access to such incredible hardware -- whether it be rented or purchased for way too much cash -- but they only see their own kin; their own ilk. They only compare themselves to the best.

The reality is that nobody expects data centre speed nor power in their own home and are satisfied to just go "haha its thinking" and let their computer quietly tick in the background as opposed to paying outragious prices for subscriptions or hardware.

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