[bko]

Or, hear me out, maybe there's a compute shortage and xAI has compute and manages that well.

There are no dark GPUs. Compute translates directly to money for these frontier labs.

I think everyone is reading way too much into this. Sure there is some circular transactions that are sus, but this ain't it.

[adjejmxbdjdn]

Compute is also a rapidly depreciating asset.

I want to make a comparison with a car rental business and say that it would be like valuing Hertz entirely on the basis of the number of cars they own, as opposed to how many they rent out, but cars have a much longer depreciation period, if there are no customers they’re not costing you more money, unlike your computer which you are using for training and sucking up massive amounts of energy, and those cars do maintain decent value even after they’re of little use to the car rental company, unlike the compute here.

[nl]

> Compute is also a rapidly depreciating asset.

That's the default assumption but in the new GPU+Memory constrained age isn't true.

Time on 4 year old H100 servers costs more now than when they were new (!!)

[RealityVoid]

> That's the default assumption but in the new GPU+Memory constrained age isn't true.

Is it an age or a temporary situation?

[nl]

Memory is unlikely to drop in price before mid-2027 when new capacity starts to come online.

The GPU shortage looks to be even longer lived.

[williamdclt]

So, temporary situation then. That's a pretty short period with no paradigm shift, just a delay in capacity.

[__blockcipher__]

It’s gonna take a lot longer than mid 2027. 2029 earliest IMO. Hyperscaler spend is basically already spoken for the next 2 years.

[Seanambers]

Temporary until its not.

It's the new normal, get used to it.

The MAG7 isn't pumping all their FCF + new debt issuance into DC's just for fun.

The world is seemingly moving into a era where compute is becoming expensive and scarce.

Only thing that can possibly change this is LLMs hitting a vertical unscalable wall.

More AI compute = more CPU, memory, storage needs.

[baq]

Everything is a temporary situation on long enough timeframes, especially if it’s exponentially growing. Moore’s law which dictates that compute depreciates quickly has been slowing down a lot in the last few years, coupled with the explosion in demand we’ve found ourselves in a prolonged shortage situation. The bubble will pop, but if you predict when correctly, you will be a rich man.

[frognumber]

It's very unclear to me.

The key question is on direction of LLMs. Right now, LLMs are taking over human jobs. If the cost of silicon+power < cost of human being doing the same work, what rational reason is there to employ a human being?

If this applies to SWEs, lawyers, business analysts, many research scientists, .... this situation could persist for a long, long time. While capital costs less than the inputs of labor (nominal food, housing, etc.), there is no need for labor.

The key question is about continued progress in models, and of the tooling around them:

- Plateau: Old silicon obsoletes in due course

- Rise quickly: Old silicon maintains value for a long time

[fluidcruft]

What I don't understand is if nobody has jobs, who's paying the machines to do anything?

So okay cool you don't need people to design and build cars. Who's going to buy the cars and where exactly are they finding money?

But see also the "radiologists driving to work" meme for why I think tech in general is currently getting high off their own farts.

[saulpw]

Rich people become the only consumers.

[laichzeit0]

I think the Amish will mostly be fine. Maybe that's how the future looks like.

[ben_w]

Long term, or short term?

Short term, money physically exists and gets spent, so if you wave a magic want of oversimplification and transition all labour to AI instantly, all the money currently in bank accounts and wallets gets spend on the same businesses it was already getting spent on, a lot of which gets spent on stuff from other businesses who have in this scenario also replaced all their labour with AI.

Eventually, perhaps quickly, all this money ends up in the hands of shareholders and landlords. There's a lot of both in the economy; famously retirement funds, but smaller-scale shareholders and landlords also exist. I wouldn't want to guess what the distribution looks like, probably highly variable between countries not just social classes (the definitions of which themselves can vary between countries).

Long term, money exists as a convenient fiction to help us organise transactions of goods and services: while it may be physically possible to eat gold and banknotes, you're not getting any real nutrients out of it when you do. So in a world where goods and services come from machines, the options are too broad to forecast: humanity could be relegated to the same role and economic stature as other primates (both in and out of zoos), or we could get universal UBI denominated in machine labour credits which lets each of us live better lives than the most extravagant billionaires live today.

[somenameforme]

The overwhelming majority of the labor force remains service, manual labor, and other such stuff that LLMs will have no real effect on. So the economy will be fine, but I do agree with you from a different angle. The entire goal of LLMs seems self destructive. If they're successful then the endgame is completely removing the barriers to entry to producing software and other digital tech. But if we do reach that endgame then the value of tech is going to plummet because there will be absolutely no barriers to entry to compete, or even just individuals homebrewing up what they need on demand.

Like imagine there was something you could buy where you insert some lumber, give it some passable description of furniture, and it outputs it. And you paid $20/month for access to this. And this was all being bankrolled by the furniture industry? I mean, sure guys - it's much appreciated, but I don't think I've ever seen anybody so enthusiastic about digging their own grave. I think it's already obvious that the gazillion dollars of API calls isn't going to materialize - it seems the handful of companies that trialed that are already reversing course hard. And in the future where LLMs are successful, that'd be even more true.

[paulhebert]

> what rational reason is there to employ a human being?

To maintain a functioning society and social contract?

Is wanting low unemployment in our society not rational?

[Earw0rm]

It's ethnically rational, and morally right.

However.

It's not rational relative to the short-term incentives of a typical corporation or investment vehicle. PE, VC, fund managers aren't paid to give a fuck about the social contract. Literally not in their job description.

[ben_w]

> Is wanting low unemployment in our society not rational?

Only conditionally on there being bad consequences for high unemployment.

I don't particularly trust politicians, but there's a whole host of hypothetical scenarios about futures where work is essentially optional. Unfortunately, they're all either in the sci-fi or religion sections of the book store:

Despite people occasionally investigating UBI, the efforts to research UBI seriously have the same problems that Marx had with literal Communism, in that there's an obvious difference between any partial transition as compared to a global transition, and we don't have a completely disconnected parallel world to be a petri dish for us to test the economic outcomes on.

[hackyhacky]

Correct. Unfortunately, that's not how capitalism makes decisions.

[mikepurvis]

Are current datacenter deployments structured in such a way that the memory can later be moved to newer GPU dies? Or is it all packaged together as on consumer graphics cards?

I assumed the latter and therefore that the memory is depreciating along with the GPU cores it's soldered onto PCBs with.

... or is it a different argument being made, perhaps that depreciation for GPUs has slowed because rising demand will keep them in service longer?

[nl]

The argument is that all GPUs are currently appreciating (!!)

Google is still running 10 year old Tesla T4s at full capacity.

This is way beyond the expected lifetime.

[fragmede]

Removing RAM chips off old cards is uneconomical, until it isn't. With things going the way they are, if you've got a card with soldered on RAM that could be transplanted to a newer card, I think you'll start seeing that happening.

[fer]

It has already become economic. While not exactly the same, the NVIDIA 2080 11GB cards are notorious for being upcycled with extra RAM: https://www.reddit.com/r/nvidia/comments/146us12/nvidia_gefo...

[donaldjbiden]

Chinese recyclers already do this with laptops

[adjejmxbdjdn]

> Time on 4 year old H100 servers costs more now than when they were new (!!)

There are several confounding factors.

We’ve seen massive inflation since then. So some growth in cost was expected.

More importantly, the current Tech industry almost always starts by selling things at a loss. The increased cost could simply be the industry choosing to not subsidize that particular service anymore.

But also, I don’t think that’s a realistic comparison. Rented out GPUs are likely not a similar use profile as compute used for training LLMs. The latter is likely closer to the cryptocurrency GPUs that are running at full tilt 24/7.

And those things physically burn out.

[nl]

> Rented out GPUs are likely not a similar use profile as compute used for training LLMs. The latter is likely closer to the cryptocurrency GPUs that are running at full tilt 24/7.

This is untrue.

H100's are used for training (well were, but are now outdated because B100/B200s are much faster).

Most of the reason people rent H100s is for smaller training runs.

If you are doing inference you usually buy managed capacity at Baseten or something, and that is often priced differently (although it comes down to an extra margin on longer term H100 prices basically).

Inference utilization is often actually higher than training now because so much effort has been spent on optimizing that stack.

[blensor]

I also feel that the GPU/NPU value does not lose money as fast anymore.

What I am wondering though is how long can you run such a system at basically full load without interruption before it starts to just physically degrade.

If I have a H100 and I let it run for 4 years at full throttle does it still have the same theoretical value as it had at the start or are the chips just burning out.

I think I remember that back when the cards used for crypto mining were sold en masse on ebay the advice was to stay away from them because they are more likely to fail?

[SkiFire13]

Quite the opposite, GPUs running at a stable rate degrade less than GPU that continuously hit highs and lows (like it would happen on a gaming rig).

[yobbo]

Normal use means loading data into the GPU for each batch. The load is not even, though training might be worse than "production".

[blensor]

After digging around a bit I found an unverified claim from 2024 that GPUs in datacenters have a lifespan of 1-3 years

https://www.tomshardware.com/pc-components/gpus/datacenter-g...

Others say that moderate load means a lifespan of ~5 years

Not sure what that means but I would assume that a datacenter will start replacing a node once the error rate hits a certain threshold without really investigating why it failed, so the practical lifespan may be shorter than 5 years even if it would technically still be usable enough

[RetroTechie]

https://en.wikipedia.org/wiki/Electromigration

Temperature is a big factor, as well as current density.

But there's also the # and magnitude of thermal cycles (which translate into mechanical stress, leading to metal-fatigue like effects on contact points etc), attack from chemicals in the air, cosmic radiation, ESD damage & more. Some may matter, some not.

That's why "new" > "used" in case of electronics. Especially since you don't know the (ab)use history of used parts.

[formerly_proven]

> I also feel that the GPU/NPU value does not lose money as fast anymore.

That's because the rate of improvement in silicon manufacturing has been continually declining for a few decades, which has a compounding effect. Just compare the technological improvements in successive decades. 1976->1986->1996->2006->2016->2026.

That's why "in real terms" performance has only been very slowly improving if you compare apples to apples (and not e.g. apples to oranges by reducing precision, like nvidia tends to do, or by comparing chips with x W to an MCM with x*2 W and saying the latter is much faster). The "just halve the number of bits in each generation" strategy has also run out now, there's no more bits to halve.

[almog]

Depreciating doesn't just mean it could depreciate in value relative to the performance of newer GPUs, but also that its lifespan is limited by reliability issues and failures.

[code51]

That's just inflation (yeah, the global one) and demand at play.

Let's not mix up depreciation of real value vs USD price (which is arbitrary, plus government controlled)

[scionaura]

it’s more like if you were to value Hertz as if they were a self-driving car company, only to find they’re a car rental company

[shdh]

It is depreciating, but demand has been very high.

There's a reason old 3090's went from $600 in 2022 o to over $1K in 2026.

[noosphr]

My local inference rig now costs three times what I bought it for. If I'd gotten the max ram I could at the time I would have made $10k after selling the excess to my current spec.

How someone can look at an asset class thats appreciated an order of magnitude in the last two years and say it will depreciate in value when the tailwinds are even stronger now is beyond me.

[snypher]

Yes, toilet paper and N95s were expensive and hard to buy once, which is why I stockpiled a lifetime supply of them. Suckers!

[dpark]

“Graph go up to the right. Graph stop at edge of paper. Must go up forever!”

[shdh]

Fundamentals dictate hardware is a depreciating asset, they're not wrong. They're just ignoring the reality of the current market.

[noosphr]

This was true when Moores law wasn't dead. Per watts performance has been flat since Ampere. There is a reason why undervolted 3090s are still used.

[codechicago277]

GPUs do have a life expectancy. They don’t run forever, especially at high temperatures and full utilization.

[fragmede]

Performance goes way up if you use liquid nitrogen to cool the chips. Maybe finally someone's willing to pay for that.

[DanielHB]

I have been hearing that memory suppliers are _intentionally_ not scaling up new factories like crazy because they assume the demand won't be there on the long term and they don't want to have spare unused capacity. Probably because Samsung and SK have a near duopoly on it as well...

At some point the market will be saturated with supply and prices will come down for older gen hardware. It can take years though, but it happened to fiber cable and fiber doesn't even depreciate like chips.

[mlyle]

Will it continue to appreciate to infinity? Maintain its value forever? Or will something else happen?

The same argument you’ve made would work for tulip bulbs, dotcom prices, or whatever. Prices go up until they don’t. Exponentials don’t last forever and the intrinsics of technology assets depreciate: things wear out and are also replaced with better things.

[iririririr]

everything* is 3x more expensive in the same amount of time though. that's inflation mostly.

* except ram

[jubilanti]

Car rentals are a great comparison, but not for the reason you think. Cars depreciate value similarly to GPUs. The depriciation lifecycle timeframe is actually similar between hyperscaler GPUs and mainstream corporate car rental companies ike Hertz. They sell their cars after 2-3 years or 20-40k miles. There is a huge market for used cars. Hertz runs their used car sales out of their rental retail offices and a lot of overhead is shared. So take the difference in cost to buy new in bulk from the manufacturer from the retail sales price for a 2-3 year old car. As long as Hertz can make more money renting it out in that time, that's revenue positive.

Same with GPUs. There is also a huge market for used GPUs from 1-2 generations ago. The A100 is a six year old chip at this point and is still running strong, especially for inference. Like cars, chips can be refurbished and repaired. A hyperscaler or even mid level player here isn't going to hold onto chips for their entire usable lifespan.

[rolisz]

> if there are no customers they’re not costing you more money, unlike your computer which you are using for training

So are you using the computers or not? I'd argue that if you're using them for training, then it's not wasted capacity. And if you're not using them, then you can turn them off, so you're not sucking up energy.

[eecc]

Compute is also a rapidly depreciating asset.

I don’t know but this dude at my son’s school has a 32GB RTX 5090 and it’s worth more than what he paid for; and he did the same trick with the RTX 4090 before that.

Until shortages are the rule, these assets are appreciating

[latchkey]

"depreciating" is not being used in the right sense.

There is depreciation, which is taking the purchase price and dividing it across N number of years (typically 5). That's the D in EBITDA and is mostly used as a profitability calculation.

The depreciation of a GPU also gets mucked up in the current GPU financed market as well. DDTL loans. The people running the GPUs often don't even own the GPU, they lease it, so there is nothing for them to depreciate (D).

The analogy that a GPU is like a used car makes zero sense. There is no oil or tires to change on a GPU. They don't wear out in the same way that a rental car would. They are housed in climate controlled locations with clean power. They just don't fail the way that is portrayed in the press.

Useful life of a GPU is based on profitability. When does opex cost more than profitability?

Some companies, like mine, also have support contracts. Anything goes wrong with the GPU (or any part of the system), Dell comes and fixes it at no extra charge. We just migrate customers and workloads to hot spares while the parts are replaced.

As for compute going down in value... the 122TB of enterprise nvme and 2GB of ram in each server that I bought 2 years ago is now worth vastly more than I paid for it. I'm also renting my GPUs out for more money now due to supply being so tight and demand being so high.

[BoorishBears]

Compute is about to come an appreciating asset in the near-term, and it some ways it already is.

The frontier labs are shifting from pricing grounded in the price of compute, to pricing grounded in the intelligence provided, or more specifically the economic value of that intelligence downstream.

The margins on that allow them to pay a hefty premium on compute and still come out ahead.

As they buy more compute at high prices, they're also pricing out competition from cheaper models. It's already become materially more difficult to get compute to run open weight models at competitive prices as a result of frontier labs in the last year.

[enos_feedler]

There is zero evidence of this shift in pricing occurring. It’s still a dream which seems unlikely

[BoorishBears]

News to me?

Opus 4.7 has all the signs of a smaller model distilled from a newer pretraining run... except a smaller price.

Flash 3.5 raised in price pretty meaningfully over Flash 3

GPT 5.4 got a small price bump over gpt-5.3-Codex/gpt-5.2, then gpt-5.5 doubled pricing over gpt-5.4

Even open weights isn't immune: Kimi K2.6 was originally priced higher despite openly being 2.5 + more post-training, same with GLM 5.1 vs 5

-

All while rental prices are spiking month over month, and NVIDIA Inception discounted prices for buying are higher than undiscounted prices for buying 6 months ago...

[dylan604]

It feels like this is the line people are using to justify the expense of compute capex

[BoorishBears]

I run a consumer AI product and the current reality of trying to get compute vs what it was 6-12 months ago is enough to justify it to anyone who has the money.

I think OpenClaw created a mania that was completely unfounded (Apple Silicon is worth dirt compared to literally anything from NVIDIA including consumer GPUs), but the prediction of compute becoming scarce was correct

[otterley]

The fact that you can sell or lease out something for more than you bought it for is justification in and of itself.

[adgjlsfhk1]

Not necessarily. The GPU leases Spacex has made are month to month, so they are taking on all of the risk. If demand goes down, they're the ones stuck with the assets.

[koolala]

Dream? It is a nightmare that computers aren't getting significantly more efficient anymore.

[leoedin]

In the short term, compute becomes an appreciating asset.

In the medium term, everyone ramps up production. Huawei and other Chinese companies work really hard to develop in-house alternatives. At some point, the hype cycle will peak and less money will flow into datacentres (yes, this will happen. It always does. Even for technologies that change society. The bubble always bursts).

The question is not if this will happen. It will happen. It's just a question of when it happens and how big the magnitude of the cycle is.

[iririririr]

no need for a car analogy.

the comment you replied to is word-by-word what people hyping canadian telecoms were saying before the dotcom crash!

[jklinger410]

> I think everyone is reading way too much into this. Sure there is some circular transactions that are sus, but this ain't it.

Let us pin this comment and see how it ages

[fragmede]

Let's say it does all collapse. How would we know it's the 5-6% stake (which in my mind doesn't make them a "major shareholder") that was a circular deal that was the fall of the house of cards vs some other segment?

[bastawhiz]

It doesn't even have to be circular. One company is juicing another company's valuation to make their stake worth more. Down the road they'll sell their stake, end the deal, and leave everyone else holding the bag.

Nothing about this deal is about better technology or talent. It's about an opportunity that's too juicy for Google to pass up on.

[senordevnyc]

When has that kind of nuance ever stopped an angry mob with an axe to grind?

[jhallenworld]

>There are no dark GPUs

This might not be true. Someone was comparing Nvidia's production rate with known data center capacity, and they do not match. Their conclusion was that people (possibly even Nvidia) were hoarding GPUs- in the very short term this might be a good strategy, but GPUs go EOL fast. There are other stories about paused datacenter builds that match with this.

TSMC is definitely fully allocated, based on current 40 wk lead times for FPGAs..

[Dig1t]

All that means is that there's a bottleneck at the data center layer. When he says "dark GPUs" he's saying that there are no dark DEPLOYED GPUs.

This is a reference to the 1990's dot com bubble where internet infrastructure companies overbuilt network capacity, leading to the term "dark fiber". That was an indicator of a bubble because it showed that capacity was larger than demand. OP is saying that this is specifically NOT happening in the case of GPUs yet, indicating that demand still outstrips supply of compute.

>GPUs go EOL fast

We are seeing the opposite of what was expected, GPUs are actually getting more valuable because demand is so great, something that basically never happens. Even older chips have become more valuable.

>paused datacenter builds

It doesn't seem that datacenters have been paused because of lack of demand for AI, it seems mostly that there is a lot of pushback by cities to build these things and also there is a shortage of power to run them.

IMO none of these things point to a AI being a bubble (over-hyped, demand does not match the stated value). It mostly points to the opposite, there is massive demand for AI and every layer of the supply chain is struggling to keep up with that demand.

[hadlock]

Adding to this, a lot of fiber installed in the 1990s is still dark. Multi-wavelength XYZ and other improvements mean the same fiber from 35 years ago can carry 100 or 1000x what it was originally designed for. Also, like Solar, all the cost is in labor. When they designed the Seattle/King County fiber network, they knew they would never have access/permits to go back and add more, so instead of running a single 12 fiber bundle the size of your pinkie, they ran 3 x 1024 bundles the size of your arm through the hollow bridges that span I-5 freeway and snakes through Seattle underground. Almost all of that sits dark today despite being in a very busy area, simply because fiber technology keeps getting better.

[db48x]

Yea, fiber is great. They can do hundreds of terabits/s per fiber today, and petabits/s is not far away. Bandwidth is fundamentally cheap enough that my ISP offers 50Gbps residential service!

[podocarp]

Can I ask where do you stay? Korea? 50G is insane, is it on qsfp? Also what's the pricing on that?

[db48x]

I live in Oregon. The price was $900/month last time I checked. I believe they do provide a QSFP+ module to plug into your equipment. They also allow residential customers, at any tier of service, to announce their own IP blocks via BGP.

https://ziplyfiber.com/internet/multigig

[LearnYouALisp]

> ...GPUs are actually getting more valuable because demand is so great, something that basically never happens. Even older chips have become more valuable.

Huh, anybody want to buy a GTX 680? Or even a formerly-SLI'd pair?

[userbinator]

The retrocomputing community is driving up prices at that end of the market.

[snypher]

Don't you think that under excess demand, production will ramp, competition will become available etc? These posts read like we're all out of fresh silicon or something.

[elictronic]

Supply will catch up, it will just take 3-5 years, with the price rising the whole time. Basically a worse version of the Covid supply disruption where I sold my car for more than I bought it for years later.

The physical world can’t be patched overnight, and cutting edge manufacturing takes a long time. Fortunately we are in a very peaceful low tension world right now and no one would try burning down or blowing up one of those extremely important, irreplaceable fabs.

[aprdm]

No. Because the investment to get into the game is too big and takes too long. The ones who can create the silicon are already oversubscribed.

[dan00]

> IMO none of these things point to a AI being a bubble (over-hyped, demand does not match the stated value). It mostly points to the opposite, there is massive demand for AI and every layer of the supply chain is struggling to keep up with that demand.

Yes, the demand is there for the currently unsustainable price. Lets see what happens when the dumping of money into AI stops and the companies are forced to increase prices a lot.

[baq]

> IMO none of these things point to a AI being a bubble (over-hyped, demand does not match the stated value).

I agree the demand is there, but hyperscaler capex is what now? 3% GDP? This is an absurd amount of money and people who question whether the ROI is there have a point just because of the order of magnitude of this spend number.

[b112]

Indeed, that hardware was bought on old RAM, SSD, etc pricing. These are now 5x the price.

To reap massive profits before depreciation is just plain smart. LLM space, model generation is just plain crowded now too. And everyone thinks a crash is coming.

They could also build out their own end-user infra, but letting someone else which already sells direct to the public do so, is sensible.

I know of the desire to show profit for the IPO, but my point is, this is a good move on its own.

[tootie]

Compute is presently in shortage but generally it's a commodity. It also depreciates.

[JumpCrisscross]

> generally it's a commodity

The NVIDIA GPUs, HBM, land-use permits and power-supply agreements xAI nailed down are absolutely not commodities.

I think xAI is a mess. But let’s call a spade a spade, they speculated on AI compute and they are currently right.

[grogers]

My read is that xAI built a lot of compute for their own use, but they didn't get any adoption so they are reselling the unused capacity to recoup at least some of the costs. So calling it a good bet is kind of misleading

[mirekrusin]

"Some" of the cost? More like 120%-200% recovery during shortage and it's still going to be an asset after that period.

[fc417fc802]

> and power-supply agreements

Don't you mean gas turbine purchases and questionably legal operation? But yeah I feel exactly the same way. The AI part of xAI looks like a mess but it seems that they still managed to score a massive win.

[JumpCrisscross]

> Don't you mean gas turbine purchases and questionably legal operation?

The point is it’s running. They built fast before the backlash got organized. Now everyone has to deal with delays and thoughtful permitting processes.

[XorNot]

The point is they're in a business no one would claim is particularly profitable but claiming a valuation like they're in a totally different business - one where they're not even top 3.

Its not that there isn't value in that business, but it's not the AI business either. Its the one where Oracle is laying off staff to try and avoid a revenue crash on future commitments.

Both Google and Anthropic would be trying to can this sort of rental arrangement as fast as possible since it's a mind bogglingly expensive way to get something you already do in house.

[fc417fc802]

It isn't normally particularly profitable but given their lucky timing they appear to temporarily be doing quite well. When their tenants eventually vacate either they make a move to reenter the race for the cutting edge and get lucky or else they revert to a "boring" cloud rental business with near cutting edge hardware. That seems like an extremely favorable mode of failure to me.

[BoorishBears]

You're taking an odd tone here.

The "backlash" is the poorest residents one of the poorest large cities in America trying to fight for their right to clean air.

Your point might end at "it's running", but holistic thinkers have no problem considering the how they arrived there, given what it's doing to these folks for marginal benefit.

It's not like xAI would go under if they had chosen a less populated location and waited to get permanent power.

[JumpCrisscross]

> "backlash" is the poorest residents one of the poorest large cities in America trying to fight for their right to clean air

Sorry, I'm referring to the national pushback against datacenters being built in peoples' backyards. xAI didn't face backlash. At least not organised enough to stop them. Their competitors, today, are facing backlash sufficiently powerful to stop new datacenters from being put down.

[hn_acc1]

Sure, they brought in artillery and a small freelance militia to shoot at the unionized workers, but the point is, the survivors are back working the mines...

[BoorishBears]

This feels highly revisionist: they bet on becoming a frontier lab and were aiming for AGI.

If they were speculating on compute, it seems highly unlikely they'd have spent the operating costs for the last 3 years of model development and deployment instead of just getting even more compute.

[Earw0rm]

And while there's no challenging the underlying proposition "AI has value", right now 95% of corporate users are still at the "throw everything at the wall and see what sticks" level in terms of model usage compute.

It's sheer brute force, tons of waste, seems like very little thought going in to fitting the implementation to the problem.

The value of compute can drop significantly in the event of users figuring out how to optimise for their particular need. And yep, there are wasteful applications that can burn whatever compute is available, but how much demand for that is there when it's properly priced?

Extreme example. Generating novel 4K VR video on demand. I'm certain there's a market for it, at $10/hour probably quite a healthy one, at $100/hour not so much.

[killerstorm]

Presumably from internal all-hands presentation in Google: “Now we must double every 6 months… the next 1000x in 4–5 years.” reported by CNBC in November 2025, attributed to Amin Vahdat, Google Cloud VP / AI infrastructure lead.

Sundar Pichai at Q4 2025 earnings call: “We’ve been supply-constrained".

Satya Nadella, 2026: Microsoft would increase total AI capacity by over 80% in the year and roughly double total datacenter footprint over two years.

Microsoft CFO, 2026 earnings call: “We’ve been short now for many quarters. I thought we were going to catch up. We are not. Demand is increasing.”

So yeah, either top management of hyperscalers are doing a 'bit' for the last few years, or Aschenbrenner 'Situational Awareness' is going roughly as predicted and hyperscalers are desperate to acquire compute even at higher cost.

[baq]

> There are no dark GPUs.

There are actually lots of GPUs in storage somewhere waiting for data center megawatts to put them in.

[AtlasBarfed]

There is a compute shortage.

In fact, for all these companies to do what they're going to do, they need a massive, massive massive amount of data centers, a highly improbable number of data centers that need to be built in an highly improbably short amount of time.

And the capitals about to dry off in about a year. So it's a race between these improbable timelines on data center construction, with capital evaporating.

[podocarp]

Source for capital drying up in one year? Not trying to be snarky but that's super big if true.

[AtlasBarfed]

- iran destabilization will shift middle east capital to military spending and infrastructure repair

- Ukraine war similarly is triggering an EU buildup and reduction in us dependency

- all the IPOs indicate the companies themselves know the private investment is coming to an end so they need the retail investors to keep the boondoggle moving

[oblio]

> I think everyone is reading way too much into this. Sure there is some circular transactions that are sus, but this ain't it.

Alphabet/Google profits:

Q1 2025: $34.54 billion

Q2 2025: $28.20 billion

Q3 2025: $34.98 billion

Q4 2025: $34.46 billion

<<Q1 2026: $62.58 billion>>

Amazon profits:

Q1 2025: $17.1 billion

Q2 2025: $18.16 billion

Q3 2025: $21.2 billion

Q4 2025: $21.19 billion

<<Q1 2026: $30.3 billion>>

Both Alphabet/Google and Amazon have invested recently into Anthropic and are doing all sorts of financial chicanery.

https://www.youtube.com/watch?v=-bjNrGFiAI4

Nah, man, it's all fine, they're just going to take down the entire global financial system doing this crap, and by global, I mean <<everyone's>> pensions are going to take a hit, even "fully funded" pension systems.

[JumpCrisscross]

> Both Alphabet/Google and Amazon have invested recently into Anthropic and are doing all sorts of financial chicanery

bko didn’t say there isn’t circular financing going on. They’re just saying this isn’t an example of it. They’re right.

It’s a potential conflict of interest. And if the agreement is fake—if Google cancels without paying the cash—it could be market manipulation. But the influencer space likes to latch onto jargon, and the one it’s overapplying right now is circular financing.

[oblio]

Did I say it was circular financing? I said "financial chicanery". I even included a link to a video explaining said financial chicanery.

What are you even going on about?

[JumpCrisscross]

The comment you’re responding to and the comment above it are about circular financing. It’s reasonably to assume that’s the same chicanery you’re talking about; expecting everyone to watch a random video to understand your comment is unreasonable.

[oblio]

I listed a bunch of data points that make no sense (profits spiking 50% in a non-Christmas quarter for companies) and weren't directly tied[1] to the circular financing.

[1] They're indirectly tied to it.

[JumpCrisscross]

> that make no sense (profits spiking 50%

They were unrealized gains on non-marketable equities. It’s clearly disclosed and done according to GAAP. It’s put under other income precisely so analysts can strip it out when modelling long-term trends.

Like, yes, if SpaceX goes to zero Google would have to realize losses and probably lose a quarter or two of GAAP profits. (But not cash flows. Cash-flow wise, it may wind up being positive due to tax effects.) It’s a risk factor, of course, but far from making no sense.

None of which is particularly relevant to the deal at hand other than in raising a potential conflict of interest among related parties.

[Spooky23]

xAI lets companies like Google move fast and hurt people at arms length.

Google itself has a good reputation as a facilities operator. SpaceXAI is operating gas turbines emitting exhaust at ground level.

[seltzered_]

Google has also tried to hide things like water consumption data, see:

- https://cloud.sustainability.watch/explore-issues/example-go...

- https://www.sfgate.com/national-parks/article/mount-hood-wat...

They also seemingly dropped their net-zero climate goal:

https://www.tomshardware.com/tech-industry/google-quietly-re...

[0xbadcafebee]

The compute is useless if nobody is left to pay for the compute, once all the AI companies die, from all that debt getting called in, once everyone realizes it's a scam. (AI isn't a scam, but the financial deals and promises of unrealistic recoupment are)

[ViscountPenguin]

The thing I've never understood about the ai investment model is the upside. What's the point of valuations that only make sense if you've built a digital god, when at that point you've literally got a digital god. I can't imagine the tangible value of money being high in that scenario

[0xbadcafebee]

Money is imaginary, it's just a placeholder, doesn't need to be tangible. In the case of AI it's the promise that you can replace humans with cheap fast robots, to do more things and cheaper. That's valuable. But the wealthy aren't considering that our economy depends on people (replacing all the people too fast would tank the economy from unemployment, and cause a revolt). So you might wonder, why don't they just move at a slower, sustainable pace? The answer is greed. Make as much as you can, as fast as you can, before the next guy does.

All this investment is completely driven by the companies leading the pack. OpenAI and Anthropic have been telling everyone they need to spend hundreds of billions in a few years. Of course they don't, they could do this over 10-15 years and still be profitable. But they're terrified they won't be able to dominate the market. So to dominate the market, they've estimated they need this growth to beat China (and each other). And the US technically has the capital to make this happen, but there's only so much money available to spend. By growing too fast, they spend money faster than they can make it, and the bills are so big that the investors go bankrupt.

That's what happened in the panic of 1873 (railroads instead of AI). That's what's going to happen here in the next 2-4 years.

[epsteingpt]

correct

but it's really bad news for the industry capacity if your best option is unproven space datacenters.

[danielmarkbruce]

But this doesn't sound exciting to folks who like a good conspiracy theory. The google/xai deal is the least interesting thing at spacex.

"you have compute, i need compute, i'll pay you for some compute.".