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

reuters.com

211–220 of 306 posts

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

#211
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…

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

#212
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.

The per token costs plummet with more concurrents. A box that can do 100 tps at request depth 1 might be able to do 3000 tps at request depth 64. Less per thread, but massively more per GPU/joule/etc. That’s the economy of scale of running in a DC rather than locally that they were referring to.

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

#214
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?

> If everyone's running local

Who's running local? Image generation can make sense to run locally, but frontier LLM make no sense to run on your own hardware.

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

#215
post #178
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…

>H100 is nearing five years and costs more to buy a used one now than a new one when it was released :) Because everyone is buying as they want to run their own models and not pay for a cloud service?

Because demand for inference tokens is above supply

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

#217
post #84

Looking at cash burn is looking at the wrong end of the horse. Some companies, like Meta, have burned huge piles of cash in pursuit of, for example, the Metaverse and they've got nothing to show for it, not even a slight increment in ad tech, and yet they earned enough to shrug it off. There's a big difference between Google spending tens of billions on AI infrastructure and what Oracle is doing. Oracle is spending t…

Meta glasses are a direct result of this investment, and they're selling like hotcakes

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

#218
post #175

Earlier quoted context omitted.

What costs are 1/100th?

Of serving a (approximately) gpt4 sized model.

So the number is irrelevant. No one wants yesterdays newspaper.

The only relevant number is the price to serve a frontier or near-frontier model.

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

#219

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…

> Their strategy to let Siri stagnate for 15 years and let everyone else take that market?

What have they lost by doing this? Did anyone switch from iPhones to something else?

Google's Assistant was and is better than Siri's. How many switched to Android because of it?

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

#220
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…

I just don’t understand this view. This is the most significant technology ever developed. The uncertainty currently is whether it 1) has massive impact, completely altering society and the making world significantly significantly better or 2) if we go into a fast takeoff/rsi loop. Personally I’ve always been highly skeptical of the later, but that seems like a genuine possibility now. It’s not ‘are we going to be able to generate 10% roic on compute’ the answer to that is yes.
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