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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

#181

Post by [deleted] »

Foobar8568 wrote: post #116
toomuchtodo wrote: post #69

Earlier quoted context omitted.

My primary role is cybersecurity in a regulated entity in a regulated industry, I am highly confident it is straightforward to do so based on work accomplished in only a couple of weeks. Stand up a router, stand up a Kubernetes cluster if you don't have one, stand up the necessary VMs and compute for serving inference. Two pizza team, in my experience. Customers can switch (although we can argue the speed and pain of…

Meanwhile, in real companies, you have to wait 2 months or more to access an API endpoint in preprod. To setup a cross business kubernetes cluster will take 2 years with unknown results. On Cloud, in Switzerland, you need to call Microsoft when you need new resources, so much for agility and minute infrastructure provisioning, and I heard the same for AWS.

[deleted]

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

#182

Post by tedggh »

kurthr wrote: post #138
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…

That sounds reasonable, it's "just" $1k/yr for 2B workers (there are about 1.2B total "knowledge workers" in the world including gig drivers), or $10k/yr for 200M workers (there are 70M office and technical workers in the US). /s https://www.dpeaflcio.org/factsheets/the-professional-and-te... In 4 years it better be 10x more important to have than a cell phone is today, or 10x more important than having internet/moni…

The math looks good on paper, but in reality enterprise AI is hard, most companies are realizing they are actually not seeing ROI from AI. One of my customers took about 8 months to rollout an AI initiative that by the time it launched and people got trained on it, it was already legacy. Also if you are 10x more productive with AI that doesn’t necessarily increases your billable output. There could be some super models like Mythos aimed at very specific hard tasks like drug development, but we have not seen any of that yet, and the clock is ticking.

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

#183

Post by flyinglizard »

johndough wrote: post #164
flyinglizard wrote: post #159

Earlier quoted context omitted.

They hold value as there is insane demand. The same reason a consumer RTX4090 costs more today than bew in 2021. Once the tide drops enough for hardware lead times to shorten to weeks, they will go the way of other used DC hardware - written off after 5 years.

> Once the tide drops enough for hardware lead times to shorten to weeks Which will not be any time soon according to SK Hynix CEO: > We still forecast that customer demand will remain higher than our supply capacity even beyond 2030 https://www.reuters.com/world/asia-pacific/sk-hynix-ceo-sees...

No one knows. There's a known bullwhip effect in supply chain [0], and DRAM makers are pretty far out along the supply chain. Just like it ramped up wildly it will stop even faster.

[0] https://en.wikipedia.org/wiki/Bullwhip_effect

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

#184

Post by Noaidi »

johndough wrote: post #149
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…

> GPUs become obsolete in 5 years The GPUs are far from worthless after 5 years. E.g. the A100 80GB PCIe version cost around $15k when it was introduced in 2021 and now sells for $10k used. Things might be slightly worse for the data center servers, but I am sure they will find find buyers.

They only reason that they are retaining value is there was not so much demand for GPUs in 2021 as there is today. Once the demand drops you will find then in dumpsters across our barren, burning dystopia.

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

#185

Post by HolyLampshade »

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…

I think that's precisely what the previous commenter is saying. Sit on the side lines, and let other people bloody themselves up.

Similar in a way to dot com. It's not to say ML won't have practical application in the future, but the likelihood that it will have specifically this form is low and worth waiting until the dust settles and a more commonly accepted utility presents itself.

If AI/ML were monstrously useful in its current form the companies pushing it would not need to be hawking products; people would be bashing their doors down. I think that's why in areas where it's more directly applied to a known problem set (like Pharma research, and I'm hoping someone with Pharma expertise can pipe up here) there has been more natural pickup.

Coming from trading and markets, ML has been a part of the mix in quantitative strategies for...well, nearly 20 years (by definition I suppose). Spaces with obvious utility will see rapid adoption. Worth waiting that out, honestly.

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

#186

Post by toomuchtodo »

brazzy wrote: post #146
Foobar8568 wrote: post #116

Earlier quoted context omitted.

Meanwhile, in real companies, you have to wait 2 months or more to access an API endpoint in preprod. To setup a cross business kubernetes cluster will take 2 years with unknown results. On Cloud, in Switzerland, you need to call Microsoft when you need new resources, so much for agility and minute infrastructure provisioning, and I heard the same for AWS.

> Meanwhile, in real companies, you have to wait 2 months or more to access an API endpoint in preprod. > To setup a cross business kubernetes cluster will take 2 years with unknown results. Do you seriously believe those times will not go down 95% if the CEO pushes for it to get done yesterday because it will save the company millions in expenses?

You get it. Given sufficient incentives, processes and systems become potentially more malleable, and hard requirements can become optional. Speed is a function of appetite, will, and resources.

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

#188

Post by lardosaurusrex »

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…

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?

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

#189

Post by skywhopper »

toast0 wrote: post #173
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…

> Data centers are NOT real estate. Buildings and power lines usually last 30-50 years. GPUs become obsolete in 5 years. Data centers are real estate. One of the big players in carrier neutral data centers even calls themselves Digitial Realty. The contents of the DC is not real estate. But neither is the an office or a house or a warehouse.

The “contents” represent the majority of the cost and meaningful functionality of what we call a “datacenter”. Those contents will not last for “real estate” debt timelines.

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

#190

Post by ody4242 »

lokar wrote: post #177
ody4242 wrote: post #162

Earlier quoted context omitted.

They are building new datacenters for the AI demand, so around half of this CAPEX is not for the GPU-s, and those will not be replaced every 3-5 years. Also, TPUv2 was introduced in 2018, and still not completely retired in all regions, from accounting pov, it has been written down to 0, but they are still working.

The cost of the land, building, mechanical equipment, etc is a very small fraction of the total cost of a DC.

The upfront cost of facility is ~30%, network infra 10-15%, land/utilities is small percentage, power could be significant for an AI DC. The servers are ~50-60% only.
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