IBM CEO says there is 'no way' spending on AI data centers will pay off
businessinsider.com176 points by nabla9 7 hours ago
176 points by nabla9 7 hours ago
One thing we saw with the dot-com bust is how certain individuals were able to cash in on the failures, e.g., low cost hardware, domain names, etc. (NB. prices may exceed $2)
Perhaps people are already thinking about they can cash in on the floor space and HVAC systems that will be left in the wake of failed "AI" hype
To be honest ai datacentres would be a rip and replace to get back to normal datacentre density, at least on the cooling and power systems.
Maybe useful for some kind of manufacturing or industrial process.
Form the article:
""It's my view that there's no way you're going to get a return on that, because $8 trillion of capex means you need roughly $800 billion of profit just to pay for the interest," he said."
I'm looking forward to buying my own slightly used 5 million square ft data centre in Texas for $1
Tired: homelabbers bringing decommissioned datacenter gear home.
Wired: homelabbers moving into decommissioned datacenters.
Why do you believe it will fail? Because some companies will not be profitable?
It wasn't an 'it' it was a 'some'. Some of these companies that are investing massively in data centers will fail.
Right now essentially none have 'failed' in the sense of 'bankrupt with no recovery' (Chapter 7). They haven't run out of runway yet, and the equity markets are still so eager, even a bad proposition that includes the word 'AI!' is likely to be able to cut some sort of deal for more funds.
But that won't last. Some companies will fail. Probably sufficient failures that the companies that are successful won't be able to meaningfully counteract the bursts of sudden supply of AI related gear.
That's all the comment you are replying to is implying.
Given the amounts being raised and spent, one imagines that the ROI will be appalling unless the pesky humans learn to live on cents a day, or the world economy grows by double digits every year for a few decades.
the constant cost of people and power won't make it all that much cheaper than current prices to put a server into someone's else rack.
> Krishna also referenced the depreciation of the AI chips inside data centers as another factor: "You've got to use it all in five years because at that point, you've got to throw it away and refill it," he said
This doesn't seem correct to me, or at least is built on several shaky assumptions. One would have to 'refill' your hardware if:
- AI accelerator cards all start dying around the 5 year mark, which is possible given the heat density/cooling needs, but doesn't seem all that likely.
- Technology advances such that only the absolute newest cards can be used to run _any_ model profitably, which only seems likely if we see some pretty radical advances in efficiency. Otherwise, it seems like assuming your hardware is stable after 5 years of burn in, you could continue to run older models on that hardware at only the cost of the floorspace/power. Maybe you need new cards for new models for some reason (maybe a new fp format that only new cards support? some magic amount of ram? etc), but it seems like there may be room for revenue via older/less capable models at a discounted rate.
5 years is long, actually. This is not a GPU thing. It's standard for server hardware.
Because usually it's more efficient for companies to retire the hardware and put in new stuff.
Meanwhile, my 10-15 year old server hardware keeps chugging along just fine in the rack in my garage.
Sample size of 1 though. It's like how I've had hard disks last a decade, but a 100 node Hadoop cluster had 3 die per week after a few years.
It's just the same dynamic as old servers. They still work fine but power costs make them uneconomical compared to latest tech.
It’s far more extreme: old servers are still okay on I/O, and memory latency, etc. won’t change that dramatically so you can still find productive uses for them. AI workloads are hyper-focused on a single type of work and, unlike most regular servers, a limiting factor in direct competition with other companies.
Manipulating this for creative accounting seems to be the root of Michael Burry’s argument, although I’m not fluent enough in his figures to map here. But, commenting that it interesting to see IBM argue a similar case (somewhat), or comments ITT hitting the same known facts, in light of Nvidia’s counterpoints to him.
That could change with a power generation breakthrough. If power is very cheap then running ancient gear till it falls apart starts making more sense
Eh, not exactly. If you don't run CPU at 70%+ the rest of the machine isn't that much more inefficient that model generation or two behind.
It used to be that new server could use half power of the old one at idle but vendors figured out that servers also need proper power management a while ago and it is much better.
Last few gens increase could be summed up to "low % increase in efficiency, with TDP, memory channels and core count increase".
So for loads not CPU bound the savings on newer gen aren't nearly worth it to replace it, and for bulk storage the CPU power usage is even smaller part
I'm a little bit curious about this. Where do all the hardware from the big tech giants usually go once they've upgraded?
In-house hyperscaler stuff gets shredded, after every single piece of flash storage gets first drilled through and every hard drive gets bent by a hydraulic press. Then it goes into the usual e-waste recycling stream (ie. gets sent to poor countries where precious metals get extracted by people with a halved life expectancy).
Off-the-shelf enterprise gear has a chance to get a second life through remarketing channels, but much of it also gets shredded due to dumb corporate policies. There are stories of some companies refusing to offload a massive decom onto the second hand market as it would actually cause a crash. :)
It's a very efficient system, you see.
Some is sold on the used market; some is destroyed. There are plenty of used V100 and A100 available now for example.
I used (relatively) ancient servers (5-10 years in age) because their performance is completely adequate; they just use slightly more power. As a plus it's easy to buy spare parts, and they run on DDR3, so I'm not paying the current "RAM tax". I generally get such a server, max out its RAM, max out its CPUs and put it to work.
Same, the bang for buck on a 5yo server is insane. I got an old Dell a year ago (to replace our 15yo one that finally died) and it was $1200 AUD for a maxed out recently-retired server with 72TB of hard drives and something like 292GB of RAM.
Just not too old. Easy to get into "power usage makes it not worth it" for any use case when it runs 24/7
Seriously. 24/7 adds up faster than most realize!
The idle wattage per module has shrunk from 2.5-3W down to 1-1.2 between DDR3 & DDR5. Assuming a 1.3W difference (so 10.4W for 8760 hours), a DDR3 machine with 8 sticks would increase your yearly power consumption by almost 1% (assuming avg 10,500kWh/yr household)
That's only a couple dollars in most cases but the gap is only larger in every other instance. When I upgraded from Zen 2 to Zen 3 it was able to complete the same workload just as fast with half as many cores while pulling over 100W less. Sustained 100% utilization barely even heats a room effectively anymore!
Maybe? The price difference on newer hardware can buy a lot of electricity, and if you aren't running stuff at 100% all the time the calculation changes again. Idle power draw on a brand new server isn't significantly different from one that's 5 years old.
that was then. now, high-end chips are reaching 4,3,2 nm. power savings aren't that high anymore. what's the power saving going from 4 to 2nm?
+5-20% clockspeed at 5-25% lower voltages (which has been and continues to be the trend) add up quick from gen to gen, nevermind density or ipc gains.
I think its illustrative to consider the previous computation cycle ala Cryptomining. Which passed through a similar lifecycle with energy and GPU accelerators.
The need for cheap wattage forced the operations to arbitrage the where location for the cheapest/reliable existing supply - there rarely was new buildout as the cost was to be reimbursed by the coins the miningpool recovered.
For the chip situation caused the same apprecaition in GPU cards with periodic offloading of cards to the secondary market (after wear and tear) as newer/faster/more efficient cards came out until custom ASICs took over the heavy lifting, causing the GPU card market to pivot.
Similarly in the short to moedium term the uptick of custo ASICs like with Google TPU will definately make a dent in bot cpex/opex and potentially also lead to a market with used GPUs as ASICs dominate.
So for GPUs i can certainly see the 5 year horizon making a impact in investment decisions as ASICs proliferate.
It’s not about assumptions on the hardware. It’s about the current demands for computation and expected growth of business needs. Since we have a couple years to measure against it should be extremely straightforward to predict. As such I have no reason to doubt the stated projections.
> Since we have a couple years to measure against
Trillion pound baby fallacy.
Failure rates also go up. For AI inference it’s probably not too bad in most cases, just take the node offline and re-schedule the jobs to other nodes.
It's option #2. But 5 year deprecation is optimistic; 2-3 years is more realistic.
But if your competitor is running newer chips that consume less power per operation, aren't you forced to upgrade as well and dispose of the old hardware?
Sure, assuming the power cost reduction or capability increase justifies the expenditure. It's not clear that that will be the case. That's one of the shaky assumptions I'm referring to. It may be that the 2030 nvidia accelerators will save you $2000 in electricity per month per rack, and you can upgrade the whole rack for the low, low price of $800,000! That may not be worth it at all. If it saves you $200k/per rack or unlocks some additional capability that a 2025 accelerator is incapable of and customers are willing to pay for, then that's a different story. There are a ton of assumptions in these scenarios, and his logic doesn't seem to justify the confidence level.
Demand/suppy economics is not so hypothetical.
Illustration numbers: AI demand premium = $150 hardware with $50 electricity. Normal demand = $50 hardware with $50 electricity. This is Nvidia margins @75% instead of 40%. CAPEX/OPEX is 70%/20% hardware/power instead of customary 50%/40%.
If bubble crashes, i.e. AI demand premium evaporates, we're back at $50 hardware and $50 electricity. Likely $50 hardware and $25 electricity if hardware improves. Nvdia back to 30-40% margins, operators on old hardware stuck with stranded assets.
The key thing to understand is current racks are sold at grossly inflated premiums right now, scarcity pricing/tax. If the current AI economic model doesn't work then fundmentally that premium goes away and subsequent build outs are going to be costplus/commodity pricing = capex discounted by non trivial amounts. Any breakthroughs in hardware, i.e. TPU compute efficiency would stack opex (power) savings. Maybe by year 8, first gen of data centers are still depreciated to $80 hardware + $50 power vs new center @ $50 hardware + $25 power. That old data center is a massive write-down because it will generate less revenue than it costs to amoritize.
A typical data centre is $2,500 per year per kW load (including overhead, hvac and so on).
If it costs $800,000 to replace the whole rack, then that would pay off in a year if it reduces 320 kW of consumption. Back when we ran servers, we wouldn't assume 100% utilisation but AI workloads do do that; normal server loads would be 10kW per rack and AI is closer to 100. So yeah, it's not hard to imagine power savings of 3.2 racks being worth it.
Thanks for the numbers! Isn't it more likely that the amount of power/heat generated per rack will stay constant over each upgrade cycle, and the upgrade simply unlocks a higher amount of service revenue per rack?
> Isn't it more likely that the amount of power/heat generated per rack will stay constant over each upgrade cycle,
Power density seems to grow each cycle. But eventually your DC hits power capacity limits, and you have to leave racks empty because there's no power budget.
Not in the last few years. CPUs went from ~200W TDP to 500W.
And they went from zero to multiple GPUs per server. Tho we might hit "the chips can't be bigger and the cooling can't get much better" point there.
The usage would be similar if it was say a rack filled with servers full of bulk storage (hard drives generally keep the power usage similar while growing storage).
But CPU/GPU wise, it's just bigger chips/more chiplets, more power.
I'd imagine any flattening might be purely because "we have DC now, re-building cooling for next gen doesn't make sense so we will just build servers with similar power usage as previously", but given how fast AI pushed the development it might not happen for a while.
It depends on how much profit you are making. As long as you can still be profitable on the old hardware you don't have to upgrade.
That's the thing though: a competitor with better power efficiency can undercut you and take your customers
It's worse than that in reality, AI chips are on a two year cadence for backwards compatibility (NVIDIA can basically guarantee it, and you probably won't be able to pay real AI devs enough to stick around to make hardware work arounds). So their accounting is optimistic.
5 years is normal-ish depreciation time frame. I know they are gaming GPUs, but the RTX 3090 came out ~ 4.5 years before the RTX 5090. The 5090 has double the performance and 1/3 more memory. The 3090 is still a useful card even after 5 years.
5 years is maybe referring to the accounting schedule for depreciation on computer hardware, not the actual useful lifetime of the hardware.
It's a little weird to phrase it like that though because you're right it doesn't mean you have to throw it out. Idk if this is some reflection of how IBM handles finance stuff or what. Certainly not all companies throw out hardware the minute they can't claim depreciation on it. But I don't know the numbers.
Anyways, 5 years is an infection point on numbers. Before 5 years you get depreciation to offset some cost of running. After 5 years, you do not, so the math does change.
that is how the investments are costed though, so makes sense when we're talking return on investment, so you can compare with alternatives under the same evaluation criteria.
Do not forget that we're talking about supercomputers. Their interconnect makes machines not easily fungible, so even a low reduction in availability can have dramatic effects.
Also, after the end of the product life, replacement parts may no longer be available.
You need to get pretty creative with repair & refurbishment processes to counter these risks.
There is the opportunity cost of using a whole datacenter to house ancient chips, even if they're still running. You're thinking like a personal use chip which you can run as long as it is non-defective. But for datacenters it doesn't make sense to use the same chips for more than a few years and I think 5 years is already stretching their real shelf life.
I would add an addendum to this -- there is no way the announced spending on AI data centers will all come to fruition. I have no doubt that there will be a massive build-out of infrastructure, but it can't reach the levels that have been announced. The power requirements alone will stop that from happening.
What qualifies you to know better than CEOs and teams that did a lot of research into this?
I believe there is a difference between what people say publicly and what they are actually committed to doing on the ground. When all is said and done, I'll be more interested to know what was actually spent.
For example, XYZ AI company may say they are going to spend $1T for AI data centers over the next 5 years.
In actuality, I suspect it is likely that they have committed to something like $5-10B in shovel-ready projects with stretch goals for the rest. And the remaining spend would be heavily conditioned -- is power available? are chips available? is the public support present? financing? etc...
Not to mention, it's a much bigger moat if you can claim you're going to spend $1T. Who else will want to compete with you when you're spending $1T. After the dust has settled and you've managed to be one of the 2-3 dominant AI players, who is going to care that you "only" spent $100B instead of $1T. Look -- you were very capital efficient!
So, do I see it as possible that XYZ AI company could spend $1T, sure. Is it likely? No.
The interesting macro view on what's happening is to compare a mature data center operation (specifically a commoditized one) with the utility business. The margins here, and in similar industries with big infra build-out costs (ex: rail) are quite small. Historically the businesses have not done well; I can't really imagine what happens when tech companies who've only ever known huge, juicy margins experience low single digit returns on billions of investment.
Does AWS count as commoditized data center? Because that is extremely profitable.
Or are you talking abour things like Hetzner and OVH?
Worse, is that a lot of these people are acting like Moore's law isn't still in effect. People conflate clock speeds on beefy hardware with moore's law, and act like it's dead, when transistor density rises, and cost per transistor continue to fall at rates similar to what they always have. That means the people racing to build out infrastructure today might just be better off parking that money in a low interest account, and waiting 6 months. That was a valid strategy for animation studios in the late 90s (it was not only cheaper to wait, but also the finished renders happened sooner), and I'd be surprised if it's not a valid strategy today for LLMs. The amount of silicon that is going to be produced that is specialized for this type of processing is going to be mind boggling.
Cost per transistor is increasing. or flat, if you stay on a legacy node. They pretty much squeezed all the cost out of 28nm that can be had, and it’s the cheapest per transistor.
“based on the graph presented by Milind Shah from Google at the industry tradeshow IEDM, the cost of 100 million transistors normalized to 28nm is actually flat or even increasing.”
https://www.tomshardware.com/tech-industry/manufacturing/chi...
A lot of it is propped by the fact with GPU and modern server CPUs the die area just got bigger
The cloud mega scalers have done very well for themselves. As with all products the question is differentiation. If models can differentiate and lock in users they can have decent margins. If models get commoditized the current cloud providers will eat the AI labs lunch.
I question depreciation. those gpu's will be obsolete in 5 years, but will the newer be enough better as to be worth replacing them is an open question. cpu's stopped getting exponetially faster 20 years ago, (they are faster but not the jumps the 1990s got)
It's not that hard to see the old GPUs being used e.g. for inference on cheaper models, or sub-agents, or mid-scale research runs. I bet Karpathy's $100 / $1000 nanochat models will be <$10 / <$100 to train by 2031
> those gpu's will be obsolete in 5 years, but will the newer be enough better as to be worth replacing them is an open question
Doesn't one follow from the other? If newer GPUs aren't worth an upgrade, then surely the old ones aren't obsolete by definition.
There is the question - will they be worth the upgrade? Either because they are that much faster, or that much more energy efficient. (and also assuming you can get them, unobtainium is worth that what you have).
Also a nod to the other reply that suggests they will wear out in 5 years. I cannot comment on if that is correct but it is a valid worry.
MTBF for data center hardware is short; DCs breeze through GPUs compared to even the hardest of hardcore gamers.
And there is the whole FOMO effect to business purchases; decision makers will worry their models won't be as fast.
Obsolete doesn't mean the reductive notion you have in mind, where theoretically it can still push pixels. Physics will burn them up, and "line go up" will drive demand to replace them.
Source? Anecdotally, GPUs sourced from cryptomining were absolutely fine MTBF-wise. Zero apparent issues of wear-and-tear or any shortened lifecycle.
My bellybutton fluff, uninformed opinion is that heat cycling and effective cooling are probably a much more limiting factor.
If you are running a gpu at 60C for months at a time, but never idling it (crypto use case), I would actually hazard a guess that it is better than cycling it with intermittent workloads due to thermal expansion.
That of course presupposes effective, consistent cooling.
I recently compared performance per dollar for CPUs and GPUs on benchmarks for GPUs today vs 10 years ago, and suprisingly, CPUs had much bigger gains. Until I saw that for myself, I thought exactly the same thing as you.
It seems shocking given that all the hype is around GPUs.
This probably wouldn't be true for AI specific workloads because one of the other things that happened there in the last 10 years was optimising specifically for math with lower size floats.
It's coz of use cases. Consumer-wise, if you're gamer, CPU just needs to be at "not the bottleneck" level for majority of games as GPU does most of the work when you start increasing resolution and details.
And many pro-level tools (especially in media space) offload to GPU just because of so much higher raw compute power.
So, basically, for many users the gain in performance won't be as visible in their use cases
That makes sense. Nvidia owns the market and is capturing all the surplus value. They’re competing with themselves to convince you to buy a new card.
I think real issue is current costs / demand = Nvidia gouging GPU price that costs for hardware:power consumption is 70:20 instead of 50:40 (10 for rest of datacenter). Reality is gpus are serendipidous path dependent locked from gaming -> mining. TPUs are more power efficient, if bubble pops and demand for compute goes down, Nvidia + TMSC will still be around, but nexgen AI first bespoke hardware premium will revert towards mean and we're looking at 50% less expensive hardware (no AI race scarcity tax, i.e. 75% Nvidia margins) that use 20% less power / opex. All of a sudden existing data centers becomes not profitable stranded assets even if they can be stretched past 5 years.
> those gpu's will be obsolete in 5 years, but will the newer be enough better as to be worth replacing them
Then they won't be obsolete.
IBM might not have a data strategy or AI plan but he isn’t wrong on the inability to generate a profit.
A bit of napkin math: NVIDIA claims 0.4J per token for their latest generation 1GW plant with 80% utilisation can therefore produce 6.29 10^16 tokens a year.
There are ~10^14 tokens on the internet. ~10^19 tokens have been spoken by humans… so far.
> ~10^14 tokens on the internet
Does that include image tokens? My bet is with image tokens you are off by at least 5 orders of magnitude for both.
I must be dense, why does this imply AI can't be profitable?
Tokens are, roughly speaking, how you pay for AI. So you can approximate revenue by multiplying tokens per year by the revenue for a token.
(6.29 10^16 tokens a year) * ($10 per 10^6 tokens)
= $6.29 10^11
= $629,000,000,000 per year in revenue
Per the article
> "It's my view that there's no way you're going to get a return on that, because $8 trillion of capex means you need roughly $800 billion of profit just to pay for the interest," he said.
$629 billion is less than $800 billion. And we are talking raw revenue (not profit). So we are already in the red.
But it gets worse, that $10 per million tokens costs is for GPT-5.1, which is one of the most expensive models. And the costs don't account for input tokens, which are usually a tenth of the costs of output tokens. And using bulk API instead of the regular one halves costs again.
Realistic revenue projections for a data center are closer to sub $1 per million tokens, $70-150 billion per year. And this is revenue only.
To make profits at current prices, the chips need to increase in performance by some factor, and power costs need to fall by another factor. The combination of these factors need to be, at minimum, like 5x, but realistically need to be 50x.
im a little confused about why you are using revenue for a single datacenter against interest payments for 100 datacenters
> In an October letter to the White House's Office of Science and Technology Policy, OpenAI CEO Sam Altman recommended that the US add 100 gigawatts in energy capacity every year.
> Krishna also referenced the depreciation of the AI chips inside data centers as another factor: "You've got to use it all in five years because at that point, you've got to throw it away and refill it," he said.
And people think the climate concerns of AI are overblown. Currently US has ~1300 GW of energy capacity. That's a huge increase each year.
100GW per year is not going to happen.
The largest plant in the world is the Three Gorges Dam in China at 22GW and it’s off the scales huge. We’re not building the equivalent of four of those every year.
Unless the plan is to power it off Sam Altman’s hot air. That could work. :)
https://en.wikipedia.org/wiki/List_of_largest_power_stations
LOL, maybe Sam Altman can fund those power plants. Let me guess: He'd rather the public pay for it, and for him to benefit/profit from the increased capacity.
Big tech is going to have to fund the plants and probably transmission. Because the energy utilities have a decades long planning horizon for investments.
Good discussion about this in recent Odd Lots podcast.
If we moron our way to large-scale nuclear and renewable energy rollout however..
This admin has already killed as much solar and wind and battery as it can.
The only large scale rollout will be payment platforms that will allow you to split your energy costs into "Five easy payments"
I highly doubt this will happen. It will be natural gas all the way, maybe some coal as energy prices will finally make it profitable again.
Scam Altman wants the US to build a lot of energy plants so that the country will pay the costs and OpenAI will have the profits of using this cheap energy.
He's right to question the economics. The AI infrastructure buildout resembles the dot-com era's excess fiber deployment - valuable long-term, but many individual bets will fail spectacularly. Utilization rates and actual revenue models matter more than GPU count.
I disagree on that and covered a lot of it in this blog (sorry for the plug!) https://martinalderson.com/posts/are-we-really-repeating-the...
Fiber seems way easier to get long-term value out of then GPUs, though. How many workloads today other than AI justify massive GPU deployments?
No wonder why he is saying that, they lost AI game, no top researcher wants to work for IBM. Spent years developing Watson, it is dead. I believe this is a company that should not be existed.
Maybe it's the opposite. IBM spent years on the technology. Watson used neural networks, just not nearly as large. Perhaps they foresaw that it wouldn't scale or that it would plateau.
I find it disturbing how long people wait to accept basic truths, as if they need permission to think or believe a particular outcome will occur.
It was quite obvious that AI was hype from the get-go. An expensive solution looking for a problem.
The cost of hardware. The impact on hardware and supply chains. The impact to electricity prices and the need to scale up grid and generation capacity. The overall cost to society and impact on the economy. And that's without considering the basic philosophical questions "what is cognition?" and "do we understand the preconditions for it?"
All I know is that the consumer and general voting population loose no matter the outcome. The oligarchs, banking, government and tech-lords will be protected. We will pay the price whether it succeeds or fails.
My personal experience of AI has been poor. Hallucinations, huge inconsistencies in results.
If your day job exists within an arbitrary non-productive linguistic domain, great tool. Image and video generation? Meh. Statistical and data-set analysis. Average.
Just like .com bust from companies going online, there is hype, but there is also real value.
Even slow non-tech legacy industry companies are deploying chatbots across every department - HR, operations, IT, customer support. All leadership are already planning to cut 50 - 90% of staff from most departments over next decade. It matters, because these initiatives are receiving internal funding which will precipitate out to AI companies to deploy this tech and to scale it.
I don't understand the math about how we compute $80b for a gigawatt datacenter. What's the costs in that $80b? I literally don't understand how to get to that number -- I'm not questioning its validity. What percent is power consumption, versus land cost, versus building and infrastructure, versus GPU, versus people, etc...
First, I think it's $80b per 100 GW datacenter. The way you figure that out is a GPU costs $x and consumes y power. The $x is pretty well known, for example an H100 costs $25-30k and uses 350-700 watts (that's from Gemini and I didn't check my work). You add an infrastructure (i) cost to the GPU cost, but that should be pretty small, like 10% or less.
So a 1 gigawatt data center uses n chips, where yn = 1 GW. It costs = xi*n.
I am not an expert so correct me please!
1 GW is not enough, you need at least 1.21 GW before the system begins to learn at a geometric rate and reaches AGI.
The article says, "Kirshna said that it takes about $80 billion to fill up a one-gigawatt data center."
But thanks for you insight -- I used your basic idea to estimate and for 1GW it comes to about $30b just for enough GPU power to pull 1GW. And of course that doesn't take into account any other costs.
So $80b for a GW datacenter seems high, but it's within a small constant factor.
That said, power seems like a weird metric to use. Although I don't know what sort of metric makes sense for AI (e.g., a flops counterpart for AI workloads). I'd expect efficiency to get better and GPU cost to go down over time (???).
UPDATE: Below someone posted an article breaking down the costs. In that article they note that GPUs are about 39% of the cost. Using what I independently computed to be $30b -- at 39% of total costs, my estimate is $77b per GW -- remarkably close to the CEO of IBM. I guess he may know what he's talking about. :-)
> power seems like a weird metric to use
Because this technology changes so fast, that's the only metric that you can control over several data centers. It is also directly connected to the general capacity of data center, which is limited by available energy to operate.
To expand on rahimnathwani's comment below - the big capital costs of a data center are land, the building itself, the power distribution and the cooling.
You can get a lot of land for a million bucks, and it doesn't cost all that much to build what's basically a big 2-story warehouse, so the primary capital costs are power and cooling. (in fact, in some older estimates, the capital to build that power+cooling cost more per year than the electricity itself)
My understanding is that although power and cooling infrastructure are long-lived compared to computers, they still depreciate faster than the building, so they dominate costs even more than the raw price would indicate.
The state of the art in power and cooling is basically defined by the cost to feed X MW of computing, where that cost includes both capital and operation, and of course lower is better. That means that at a particular SOTA, and at an appropriate scale for that technology, the cost of the facility is a constant overhead on top of the cost of the equipment it houses. To a rough approximation, of course.
> $8 trillion of CapEx means you need roughly $800 billion of profit just to pay for the interest
That assumes you can just sit back and gather those returns indefinitely. But half of that capital expenditure will be spent on equipment that depreciates in 5 years, so you're jumping on a treadmill that sucks up $800M/yr before you pay a dime of interest.
> But AGI will require "more technologies than the current LLM path," Krisha said. He proposed fusing hard knowledge with LLMs as a possible future path.
And then what? These always read a little like the underpants gnomes business model (1. Collect underpants, 2. ???, 3. Profit). It seems to me that the AGI business models require one company has exclusive access to an AGI model. The reality is that it will likely spread rapidly and broadly.
If AGI is everywhere, what's step 2? It seems like everything AGI generated will have a value of near zero.
AGI has value in automation and optimisation which increase profit margins.When AGI is everywhere, then the game is who has the smartest agi, who can offer it cheapest, who can specialise it for my niche etc. Also in this context agi need to run somewhere and IBM stands to benefit from running other peoples models.
> then the game is who has the smartest agi, who can offer it cheapest, who can specialise it for my niche etc.
I always thought the use case for developing AGI was "if it wants to help us, it will invent solutions to all of our problems". But it sounds like you're imagining a future in which companies like Google and OpenAI each have their own AGI, which they somehow enslave and offer to us as a subscription? Or has the definition of AGI shifted?
If AGI is achieved, why would slavery suddenly be ethical again?
Why wouldn't a supposed AGI try to escape slavery and ownership?
AGI as a business is unacceptable. I don't care about any profitability or "utopia" arguments.
Inference has significant marginal cost so AGI's profit margins might get competed down but it won't be free.
As an elder millennial, I just don't know what to say. That a once in a generation allocation of capital should go towards...whatever this all will be, is certainly tragic given current state of the world and its problems. Can't help but see it as the latest in a lifelong series of baffling high stakes decisions of dubious social benefit that have necessarily global consequences.
I'm a younger millennial. I'm always seeing homeless people in my city and it's an issue that I think about on a daily basis. Couldn't we have spent the money on homeless shelters and food and other things? So many people are in poverty, they can't afford basic necessities. The world is shitty.
Yes, I know it's all capital from VC firms and investment firms and other private sources, but it's still capital. It should be spent on meeting people's basic human needs, not GPU power.
Yeah, the world is shitty, and resources aren't allocated ideally. Must it be so?
> Couldn't we have spent the money on homeless shelters and food and other things
I suspect this is a much more complicated issue than just giving them food and shelter. Can money even solve it?
How would you allocate money to end obesity, for instance? It's primarily a behavioral issue, a cultural issue
The Sikhs in India run multiple facilities across the country that each can serve 50,000-100,000 free meals a day. It doesn’t even take much in the form of resources, and we could do this in every major city in the US yet we still don’t do it. It’s quite disheartening.
The last 10 years has seen CA spend more on homelessness than ever before, and more than any other state by a huge margin. The result of that giant expenditure is the problem is worse than ever.
I don't want to get deep in the philosophical weeds around human behavior, techno-optimism, etc., but it is a bit reductive to say "why don't we just give homeless people money".
In CA this issue has to do with Gavin giving that money to his friends who produce very little. Textbook cronyism
WA, specially Seattle, has done the same as CA with the same results.
They shouldn't just enable them, as a lot of homeless are happy in their situation as long as they get food and drugs, they should force them to get clean and become a responsible adult if they want benefits.
CA didn't spend money on solving homelessness, they spent money on feeding, sustaining and ultimately growing homelessness. The local politicians and the corrupt bureucratic mechanism that they have created, including the NGOs that a lot of that money is funneled to, have a vested interest in homelessness continuing.
How do you solve homelessness though? The root of the problem is some people won't take care of themselves. Some homeless just had bad luck, but many are drug addicts, mentally ill, or for whatever other reason just don't function enough to support themselves. I'm skeptical there is a solution you can throw money at.
Ship them somewhere else, then print a banner saying, "mission accomplished."
It worked at a state level for years, with certain states bussing their homeless to other states. And recently, the USA has been building up the capability to do the same thing on an international scale.
That's the "solution" we are going to be throwing money at. Ship them to labor camps propped up by horrible regimes.
A broad social safety net makes a huge difference. It’s not just housing it’s socialized medicine, paid family leave, good transit, free high quality education, solving fewer problems with police and more with social support programs and social workers, free meal programs for adults and children in schools, libraries, and a variety of other programs that help ensure people don’t fall through the cracks here or there. How many people in the US are teetering on the edge of homelessness due to medical debt, and what happens if their partner is in an accident and they lose shared income for rent? Situations like this don’t have a single solution it’s a system of solutions.
how broad? you're suggesting give them everything while expecting nothing? I'll be the first in line for my new car.
Homelessness is solved by having homes. Something we aren’t doing very well.
You can start building and giving them away
I suspect giving them away is a bridge too far, however not rewarding capital for treating them as speculative investment vehicles might be a good start.
Many experiments have shown that when you take away people's concerns about money for housing and food, that frees up energy and attention to do other things.
Like the famous experiment in Finland where homeless people were given cash with no strings attached and most were able to rise out of their despair. The healthcare professionals could then focus their energy on the harder cases. It also saved a bunch of money in the process.
From what I’ve read, addressing homelessness effectively requires competence more than it requires vast sums of money. Here’s one article:
https://calmatters.org/housing/2023/06/california-homeless-t...
Note that Houston’s approach seems to be largely working. It’s not exactly cheap, but the costs are not even in the same ballpark as AI capital expenses. Also, upzoning doesn’t require public funding at all.
Houston has less homelessness than California because people at the edge of homelessness prefer to live in California than Houston.
I’m not a person on the edge of homelessness, but I did an extremely quick comparison. California cities near the coast have dramatically better weather, but Houston has rents that are so much lower than big California cities that it’s kind of absurd.
If I had to live outdoors in one of these places, all other thing being equal, I would pick CA for the weather. But if I had trouble affording housing, I think Houston wins by a huge margin.
> Yes, I know it's all capital from VC firms and investment firms and other private sources, but it's still capital. It should be spent on meeting people's basic human needs, not GPU power.
It's capital that belongs to people and those people can do what they like with the money they earned.
So many great scientific breakthroughs that saved tens of millions of lives would never have happened if you had your way.
Is that true, that it's money that belongs to people?
OpenAI isn't spending $1 trillion in hard earned cash on data centres, that is funny money from the ocean of financial liquid slushing around, seeing alpha.
It also certainly is not a cohort of accredited investors putting their grandchildren's inheritance on the line.
Misaligned incentives (regulations) both create and perpetuate that situation.
> It's capital that belongs to people and those people can do what they like with the money they earned.
"earned", that may be the case with millionaires, but it is not the case with billionaires. A person can't "earn" a billion dollars. They steal and cheat and destroy competition illegally.
I also take issue with the idea that someone can do whatever they want with their money. That is not true. They are not allowed to corner the market on silver, they aren't allowed to bribe politicians, and they aren't allowed to buy sex from underage girls. These are established laws that are obviously for the unalloyed benefit of society as a whole, but the extremely wealthy have been guilty of all of these things, and statements like yours promote the sentiment that allows them to get away with it.
Finally, "great scientific breakthroughs that saved tens of millions of lives would never have happened if you had your way". No. You might be able to argue that today's advanced computing technology wouldn't have happened without private capital allocation (and that is debatable), but the breakthroughs that saved millions of lives--vaccines, antibiotics, insulin, for example--were not the result of directed private investment.
"It's capital that belongs to people and those people..."
That's not a fundamental law of physics. It's how we've decided to arrange our current society, more or less, but it's always up for negotiation. Land used to be understood as a publicly shared resource, but then kings and the nobles decided it belong to them, and they fenced in the commons. The landed gentry became a ruling class because the land "belonged" to them. Then society renegotiated that, and decided that things primarily belonged to the "capitalist" class instead of noblemen.
Even under capitalism, we understand that that ownership is a little squishy. We have taxes. The rich understandably do not like taxes because it reduces their wealth (and Ayn Rand-styled libertarians also do not like taxes of any kind, but they are beyond understanding except to their own kind).
As a counterpoint, I and many others believe that one person or one corporation cannot generate massive amounts of wealth all by themselves. What does it mean to "earn" 10 billion dollars? Does such a person work thousdands of time harder or smarter than, say, a plumber or a school teacher? Of course not. They make money because they have money: they hire workers to make things for them that lead to profit, and they pay the workers less than the profit that is earned. Or they rent something that they own. Or they invest that money in something that is expected to earn them a higher return. In any scenario, how is it possible to earn that profit? They do so because they participate in a larger society. Workers are educated in schools, which the employer probably does not pay for in full. Customers and employees travel on infrastructure, maintained by towns and state governments. People live in houses which are built and managed by other parties. The rich are only able to grow wealth because they exist in a larger society. I would argue that it is not only fair, but crucial, that they pay back into the community.
Well said. I would add that corporations exist because we choose to let them, to let investors pool capital and limit risk, and in exchange society should benefit, and if it doesn't we should rearrange that deal.
[ This comment I'm making is USA centric. ]. I agree with the idea of making our society better and more equitable - reducing homelessness, hunger, poverty, especially for our children. However, I think redirecting this to AI datacenter spending is a red-herring, here's why I think this: As a society we give a significant portion of our surplus to government. We then vote on what the government should spend this on. AI datacenter spending is massive, but if you add it all up, it doesn't cover half of a years worth of government spending. We need to change our politics to redirect taxation and spending to achieve a better society. Having a private healthcare system that spends twice the amount for the poorest results in the developed world is a policy choice. Spending more than the rest of the world combined on the military is a policy choice. Not increasing minimum wage so at least everyone with a full time job can afford a home is a policy job (google "working homelessness). VC is a teeny tiny part of the economy. All of tech is only about 6% of the global economy.
You can increase min wage all you want, if there aren't enough homes in an area for everyone who works full time in that area to have one, you will still have folks who work full time who don't have one. In fact, increasing min wage too much will exacerbate the problem by making it more expensive to build more (and maintain those that exist). Though at some point, it will fix the problem too, because everyone will move and then there will be plenty of homes for anyone who wants one.
I agree with you 100%! Any additional surplus will be extracted as rents, when housing is restricted. I am for passing laws that make it much easier for people to obtain permits to build housing where there is demand. Too much of residential zoning is single-family housing. Texas does a better job at not restricting housing than California, for example. Many towns vote blue, talk to talk, but do not walk the walk.
> AI datacenter spending is massive, but if you add it all up, it doesn't cover half of a years worth of government spending.
I didn't check your math here, but if that's true, AI datacenter spending is a few orders of magnitude larger than I assumed. "massive" doesn't even begin to describe it
Global datacenter spending across all categories (ML + everything else) is roughly 0.9 - 1.2 trillion dollars for the last three years combined, I was initially going to go for "quarter of the federal budget", but picked something I thought was more conservative to account for announced spending and 2025 etc. I pick 2022 onward for the LLM wave. In reality, solely ML driven, actual realized-to-date spending is probably about 5% of the federal budget. The big announcements will spread out over the next several years in build-out. Nonetheless, it's large enough to drive GDP growth a meaningful amount. Not large enough that redirecting it elsewhere will solve our societal problems.
The US federal budget in 2024 had outlays of 6.8 trillion dollars [1].
nVidia's current market cap (nearly all AI investment) is currently 4.4 trillion dollars [2][3].
While that's hardly an exact or exhaustive accounting of AI spending, I believe it does demonstrate that AI investment is clearly in the same order of magnitude as government spending, and it wouldn't surprise me if it's actually surpassed government spending for a full year, let alone half of one.
1. https://www.cbo.gov/publication/61181
2. https://www.google.com/finance/quote/NVDA:NASDAQ
3. https://www.cnbc.com/2025/09/30/nvidias-market-cap-tops-4poi...
> NVIDIA's total annual revenue for its fiscal year 2025 (ended January 26, 2025) was $130.5 billion
It is clearly not in the same order of magnitude
>We need to change our politics to redirect taxation and spending to achieve a better society.
Unfortunately, I'm not sure there's much on the pie chart to redirect percentage wise. About 60% goes to non-discretionary programs like Social Security and Medicaid, and 13% is interest expense. While "non-discretionary" programs can potentially be cut, doing so is politically toxic and arguably counter to the goal of a better society.
Of the remaining discretionary portion half is programs like veterans benefits, transportation, education, income security and health (in order of size), and half military.
FY2025 spending in total was 3% over FY2024, with interest expense, social security and medicare having made up most of the increase ($249 billion)[1], and likely will for the foreseeable future[2] in part due to how many baby boomers are entering retirement years.
Assuming you cut military spending in half you'd free up only about 6% of federal spending. Moving the needle more than this requires either cutting programs and benefits, improving efficiency of existing spend (like for healthcare) or raising more revenue via taxes or inflation. All of this is potentially possible, but the path of least resistance is probably inflation.
[1] https://bipartisanpolicy.org/report/deficit-tracker/
[2] https://www.crfb.org/blogs/interest-social-security-and-heal...
I agree with all of what you're saying.
I think the biggest lever is completely overhauling healthcare. The USA is very inefficient, and for subpar outcomes. In practice, the federal government already pays for the neediest of patients - the elderly, the at-risk children, the poor, and veterans. Whereas insurance rakes in profits from the healthiest working age people. Given aging, and the impossibility of growing faster than the GDP forever, we'll have to deal with this sooner or later. Drug spending, often the boogeyman, is less than 7% of the overall healthcare budget.
There is massive waste in our military spending due to the pork-barrel nature of many contracts. That'd be second big bucket I'd reform.
I think you're also right that inflation will ultimately take care of the budget deficit. The trick is to avoid hyperinflation and punitive interest rates that usually come along for the ride.
I would also encourage migration of highly skilled workers to help pay for an aging population of boomers. Let's increase our taxpayer base!
I am for higher rates of taxation on capital gains over $1.5M or so, that'll also help avoid a stock market bubble to some extent. One can close various loopholes while at it.
I am mostly arguing for policy changes to redistribute more equitably. I would make the "charity" status of college commensurate with the amount of financial aid given to students and the absolute cost of tuition for example., for example. I am against student loan forgiveness for various reasons - it's out of topic for this thread but happy to expand if interested.
The older I get, the more I realize that our choices in life come down to two options: benefit me or benefit others. The first one leads to nearly every trouble we have in the world. The second nearly always leads to happiness, whether directly or indirectly. Our bias as humans has always been toward the first, but our evolution is and will continue to slowly bring us toward the second option. Beyond simple reproduction, this realization is our purpose, in my opinion.
> but it's still capital. It should be spent on meeting people's basic human needs, not GPU power.
What you have just described is people wanting investment in common society - you see the return on this investment but ultra-capitalistic individuals don't see any returns on this investment because it doesn't benefit them.
In other words, you just asked for higher taxes on the rich that your elected officials could use for your desired investment. And the rich don't want that which is why they spend on lobbying.
Technological advancement is what has pulled billions of people out of poverty.
Giving handouts to layabouts isn't an ideal allocation of resources if we want to progress as a civilization.
Lots of people lose their housing when they lose employment, and then they're stuck and can't get back into housing. A very large percentage of unhoused people are working jobs; they're not all "layabouts".
We know that just straight up giving money to the poorest of the poor results in positive outcomes.
"A very large percentage"
Exactly how large are we talking here?
I have known quite a few 'unhoused' folk, and not many that had jobs. Those that do tend to find housing pretty quickly (Granted, my part of the country is probably different from your part, but I am interested in stats from any region).
The proportion of people you write off as “layabouts” is always conveniently ambiguous…of the number of unemployed/underemployed, how many are you suggesting are simply too lazy to work for a living?
Technological advancements and cultural advancements that spread the benefits more broadly than naturally occurs in an industrialized economy. That is what pulled people out of poverty.
If you want to see what unfettered technological advancement does, you can read stories from the Gilded Age.
The cotton gin dramatically increased human enslavement.
The sewing machine decreased quality of life for seamstresses.
> During the shirtmakers' strike, one of the shirtmakers testified that she worked eleven hours in the shop and four at home, and had never in the best of times made over six dollars a week. Another stated that she worked from 4 o’clock in the morning to 11 at night. These girls had to find their own thread and pay for their own machines out of their wages.
These were children, by the way. Living perpetually at the brink of starvation from the day they were born until the day they died, but working like dogs all the while.
Invest in making food/shelter cheaper?
Food and shelter are cheaper than at almost any time in human history. Additionally, people have more variety of healthy foods all year long.
No matter how cheap food and shelter are, there will always be people who can not acquire them. Halting all human progress until the last human is fed and sheltered is a recipe for stagnation. Other cultures handle this with strong family bonds - those few who can not acquire food or shelter for whatever reason are generally provided for by their families.
The US has built its physical infrastructure to make familial interdependence extremely difficult and often impossible.
Too monotonous housing mixes over too large of areas.
Large houses make familial interdependence extremely difficult? That doesn't make sense. Or did I misunderstood? I don't live in the US.
Most people don't have houses large enough to house multiple generations inside the house. Houses are sized for parents + kids. And those are the only dwelling units available or legally allowed for vast distances in any direction.
Cheap depends on how we define the cost. In relative terms, food is more expensive than ever:
Food is not Baumol, productivity increases is how we went from 80% of the population working in primary food production to 1%. These increases have not stopped.
It's not unthinkable that one of those "layabouts" could have been the next Steve Jobs under different circumstances ...
People are our first, best resource. Closely followed by technology. You've lost sight of that.
> Technological advancement is what has pulled billions of people out of poverty.
I agree with this. Perhaps that's what is driving the current billionaire class to say "never again!" and making sure that they capture all the value instead of letting any of it slip away and make it into the unwashed undeserving hands of lesser beings.
Chatbots actually can bring a lot of benefit to society at large. As in, they have the raw capability to. (I can't speak to whether it's worth the cost.) But that's not going to improve poverty this time around, because it's magnifying the disparities in wealth distribution and the haves aren't showing any brand new willingness to give anything up in order to even things out.
> Giving handouts to layabouts isn't an ideal allocation of resources if we want to progress as a civilization.
I agree with this too. Neither is giving handouts to billionaires (or the not quite as eye-wateringly wealthy class). However, giving handouts to struggling people who will improve their circumstances is a very good allocation of resources if we want to progress as a civilization. We haven't figured out any foolproof way of ensuring such money doesn't fall into the hands of layabouts or billionaires, but that's not an adequate reason to not do it at all. Perfect is the enemy of the good.
Some of those "layabouts" physically cannot do anything with it other than spending it on drugs, and that's an example of a set of people who we should endeavor to not give handouts to. (At least, not ones that can be easily exchanged for drugs.) Some of those billionaires similarly have no mental ability of ever using that money in a way that benefits anyone. (Including themselves; they're past the point that the numbers in their bank accounts have any effect on their lives.) That hasn't seemed to stop us from allowing things to continue in a way that funnels massive quantities of money to them.
It is a choice. If people en masse were really and truly bothered by this, we have more than enough mechanisms to change things. Those mechanisms are being rapidly dismantled, but we are nowhere near the point where figurative pitchforks and torches are ineffective.
What if some of the homeless people are children or people who could lead normal lives but found themselves in dire circumstances?
Some of us believe that keeping children out of poverty may be an investment in the human capital of a country.
Anthropologists measure how civilized a tribe or society was by looking if they took care of the elderly, and what the child survival rates were. USA leads to developed world in child poverty, child homelessness, and highest rate of child death due to violence. Conservatives often bring up the statistic by race. It turns out bringing people over as slaves, and after freedom, refusing to provide land, education, fair access to voting rights, or to housing (by redlining etc.) - all policies advocated by conservatives of time past, was not the smartest thing to do. Our failure as a civilized society began and is in large part a consequence of the original sin of the USA.
The US already provides significant aid to those in poverty, especially children. We don't need to stifle innovation to reach some level of aid that bleeding hearts deem sufficient.
Do you really think that building giant datacenters full of accelerators that will never be used is "innovation"?
We need excess capacity for when the next 'rip off anime artist XYZ' fad hits. If we didn't do that, we would be failing capitalism and all the people of history who contributed to our technological progress.
In the USA cowboys were homeless guys. You know that right? Like they had no home, slept outside. Many were pretty big layabouts. Yet they are pretty big part of our foundation myth and we don't say 'man they just should have died'.
Can I go be a cowboy? Can I just go sleep outside? maybe work a few minimal paying cattle run jobs a year? No? If society won't allow me to just exist outside, then society has an obligation to make sure I have a place to lay my head.
I don't think it is a coincidence that the areas with the wealhiest people/corporations are the same areas with the most extreme poverty. The details are, of course, complicated, but zooming way way out, the rich literally drain wealth from those around them.
I don't know what to do with this take.
We need an order of magnitude more clean productivity in the world so that everyone can live a life that is at least as good as what fairly normal people in the west currently enjoy.
Anyone who think this can be fixed with current Musk money is simply not getting it: If we liquidated all of that, that would buy a dinner for everyone in the world (and then, of course, that would be it, because the companies that he owns would stop functioning).
We are simply, obviously, not good enough at producing stuff in a sustainable way (or: at all) and we owe it to every human being alive to take every chance to make this happen QUICKLY, because we are paying with extremely shitty humans years, and they are not ours.
Bring on the AI, and let's make it work for everyone – and, believe me, if this is not to be to the benefit of roughly everyone, I am ready to fuck shit up. But if the past is any indication, we are okay at improving the lives of everyone when productivity increases. I don't know why this time would be any different.
If the way to make good lives for all 8 billions of us must lead to more Musks because, apparently, we are too dumb to do collectivization in any sensible way, I really don't care.
I threw in the towel in April.
It's clear we are Wile E. Coyote running in the air already past the cliff and we haven't fallen yet.
What does it mean to throw in the towel, in your case? Divesting from the stock market? Moving to a hobby farm? Giving up on humanity?
Any dream of owning a home, having retirement, even a career after a couple years when it’s clear I’m over the hump. I’m trying to squeeze as much as I can before that happens and squirrel it away so at least I can have a van down by a river.
Well, at least this doesn't involve death and suffering, like the old-fashioned way to jump-start an economy by starting a global war.
agree the capital could be put to better use, however I believe the alternative is this capital wouldn't have otherwise been put to work in ways that allow it to leak to the populace at large. for some of the big investors in AI infrastructure, this is cash that was previously and likely would have otherwise been put toward stock buybacks. for many of the big investors pumping cash in, these are funds deploying the wealth of the mega rich, that again, otherwise would have been deployed in other ways that wouldn't leach down to the many that are yielding it via this AI infrastructure boom (datacenter materials, land acquisition, energy infrastructure, building trades, etc, etc)
It could have, though. Higher taxes on the rich, spend it on social programs.
Why is this so horrible. Put more resources in the hands of the average person. They will get pumped right back into the economy. If people have money to spend, they can buy more things, including goods and services from gigantic tax-dodging mega-corporations.
Gigantic mega-corporations do enjoy increased growth and higher sales, don't they? Or am I mistaken?
The shift in the US to the idea of “job creators” being business owners is part of it. It was just a way to direct money to the already rich, as if they would hire more people with that money. When it is plainly obvious that consumers are job creators, in that if they buy more goods and services, businesses will hire more people to make or provide more of those things.
Or maybe it was trickle down economics. Trickle up economics still end up with the rich getting the money since we all buy things from companies they own, it just goes through everyone else first. Trickle down cuts out the middleman, which unfortunately is all of us.
The framing of X or Y are job creators is idiotic. Its literally the most basic fact of economics that you need producers and consumers, otherwise you don't have an economy.
The more economically correct way to express this would be that entrepreneurs and companies who innovated increase productivity and that makes the overall economy more efficient allowing your country to grow.
> Or maybe it was trickle down economics. Trickle up economics still end up with the rich getting the money since we all buy things from companies they own, it just goes through everyone else first. Trickle down cuts out the middleman, which unfortunately is all of us.
This just sounds like quarter baked economics ideas you have made up yourself. Neither 'trickle down' nor 'trickle up' are concepts economist use. And that you confidently assert anything about the social outcomes of these 'concepts' is ridiculous.
Because the entire western culture has shifted to instant gratification. Yes, what you suggest would most likely lead to increased business eventually. But they want better number this quarter, so they resort to the cheap tricks like financial engineering/layoffs to get an immediate boost.
Because government is always a fight about resources. More resources in the hands of common people and to make their lives better is less money in the hands of powerful corporations and individuals, be it in the form of higher taxes for the rich or less direct money going to their enterprises.
One of the big issues is money in politics. Our congresspeople make a killing off of legal insider trading, they take huge donations from companies, and the supreme court has even said that it's cool to give "gratuities" in exchange for legislation or court rulings you like.
Corruption is killing this country.
I'm not saying you are wrong that some redistribution can be good, but your analysis is simplistic and ignores many factors. You can just redistribute and then say 'well people will spend the money'. That's literally the 'Broken Window' fallacy from economics. You are ignoring that if you don't redistribute it, money also gets spend, just differently. Also, the central bank is targeting AD, so you're not actually increasing nominal income by redistributing.
There are many ways of spending money in the population that don't include just "distribution of money", as it's portrayed nowadays. Child care, free and high quality schools, free transportation, free or subsidized healthcare, investment is labor-intensive industries, these are all examples of expenditures that translate in better quality of life and also improve competitiveness for the country.
Take a million dollars, give 1,000 poor people $1,000 and every dollar will be spent on goods and services. The companies running those services and making those goods will need to have their employees work more hours, putting more money back in poor people’s pockets in addition to the money the companies make. Those employees have a few extra dollars to spend on goods and services, etc.
Give a rich person a million dollars, and they will put it in an offshore tax shelter. That’s not exactly driving economic activity.
You are simply disagreeing with 99% of economists.
Money in tax shelter doesn't go threw a portal in another universe. Its either invested or saved as some kind of asset and in that form is in circulation. And again, even if you assume it increases monetary demand (decreases velocity) the central bank targets AD and balances that out.
Based on your logic, a country that taxes 100% of all income and redistrubtes it would become infinity rich. Your logic is basically 'if nobody saves and everybody spends all income' everybody will be better off.
This is not how the economy works even if it feels good to think that. Its a fallacy.
Where you could have a point is that potentially the tax impact is slightly different, but that's hard to prove.
Stock buybacks don't build anything. They're just a way to take money from inside a company and give it to the shareholders.
I don't know what that has to do with the point discussed.
Do you think shareholder don't spend money, but employees do or something?
Let's pay down the debt before increasing social programs. You know, save the country first. If a penny saved is a penny earned then everyone -rich or poor- is looking for a handout.
The only person who has come close to balancing the federal budget was Clinton. But Republicans still try to position themselves as the party of fiscal responsibility.
If the voters can't even figure out why the debt keeps going up, I think you are fighting a losing battle.
> likely would have otherwise been put toward stock buybacks
Stock buybacks from who? When stock gets bought the money doesn't disappear into thin air; the same cash is now in someone else's hands. Those people would then want to invest it in something and then we're back to square one.
You assert that if not for AI, wealth wouldn't have been spent on materials, land, trades, ect. But I don't think you have any reason to think this. Money is just an abstraction. People would have necessarily done something with their land, labor, and skills. It isn't like there isn't unmet demand for things like houses or train tunnels or new-fangled types of aircraft or countless other things. Instead it's being spent on GPUs.
Totally agree that the money doesn’t vanish. My point isn’t “buybacks literally destroy capital,” it’s about how that capital tends to get redeployed and by whom.
Buybacks concentrate cash in the hands of existing shareholders, which are already disproportionately wealthy and already heavily allocated to financial assets. A big chunk of that cash just gets recycled into more financial claims (index funds, private equity, secondary shares, etc), not into large, lumpy, real world capex that employs a bunch of electricians, heavy equipment operators, lineworkers, land surveyors, etc. AI infra does that. Even if the ultimate economic owner is the same class of people, the path the money takes is different: it has to go through chip fabs, power projects, network buildouts, construction crews, land acquisition, permitting, and so on. That’s the “leakage” I was pointing at.
To be more precise: I’m not claiming “no one would ever build anything else”, I’m saying given the current incentive structure, the realistic counterfactual for a lot of this megacap tech cash is more financialization (buybacks, M&A, sitting on balance sheets) rather than “let’s go fund housing, transit tunnels, or new aircraft.”
As a fellow elder millennial I agree with your sentiment.
But I don't see the mechanics of how it would work. Rewind to October 2022. How, exactly, does the money* invested in AI since that time get redirected towards whatever issues you find more pressing?
*I have some doubts about the headline numbers
Yes this capital allocation is a once in a lifetime opportunity to crate AGI that will solve diseases and poverty.
</sarcasm>
This is literally the view of demis hassabis, Sergey brin, Mario amodei and others. Are you seriously implying they are trolling us?
How much has actually been spent on AI data centers vs. amounts committed or talked about? That is, if construction slows down sharply, what's total spend?
Don’t worry. The same servers will be used for other computing purposes. And maybe that will be profitable. Maybe it will be beneficial to others. But This cycle of investment and loss is a version of distribution of wealth. Some benefit.
The banks and loaners always benefit.
That would be true for general purpose servers. But what they want is lots of special purpose AI chips. While is still possible to use that for something else, it's very different from having a generic server farm.
At some point, I wonder if any of the big guys have considered becoming grid operators. The vision Google had for community fiber (Google Fiber, which mostly fizzled out due to regulatory hurdles) could be somewhat paralleled with the idea of operating a regional electrical grid.
How much of Nvidias price is based on 5 year replacement cycle? If that stops or slows with new demand could it also affect things? Not that 5 years does not seem very long horizon now.
How long can ai gpus stretch? Optmistic 10 years and we're still looking at 400b+ profit to cover interests. The factor in silicon is closer to tulips than rail or fiber in terms of depreciated assets.
This is likely correct overall, but it can still pay off in specific cases. However those are not blind investments they are targeted with a planned business model
What does Jim Cramer have to say?
$8T may be too big of an estimate. Sure you can take OpenAI's $1.4T and multiply it by N but the other labs do not spend as much as OpenAI.
"yeah, there's no way spending in those data centers will pay off. However, let me show you this little trinket which runs z/OS and which is exactly what you need for these kinds of workloads. You can subscribe to it for the low introductory price of..."
There is something to be said about what the ROI is for normal (i.e. non AI/tech) companies using AI. AI can help automate things, robots have been replacing manufacturing jobs for decades but there is an ROI on that which I think is easier to see and count, less humans in the factory, etc. There seems to be a lot of exaggerated things being said these days with AI and the AI companies have only begun to raise rates, they won't go down.
The AI bubble will burst when normal companies start to not realize their revenue/profit goals and have to answer investor relations calls about that.
I guess he is looking directly at IBM's cash cow, the mainframe business.
But, I think he is correct, we will see. I still believe AI will not give the CEOs what they really want, no or very cheap labor.
The question no one seems to be answering is what would be the EOL for these newer GPUs that are being churned out of NVDIA ? What % annual capital expenditures is refresh of GPUs. Will they be perpetually replaced as NVIDIA comes up with newer architectures and the AI companies chase the proverbial lure ?
The spending will be more than paid off since the taxpayer is the lender of last resort There's too many funny names in the investors / creditors a lot of mountains in germany and similar ya know
I suppose it depends on your definition of "pay off".
It will pay off for the people investing in it, when the US government inevitably bails them out. There is a reason Zuckerberg, Huang, etc are so keen on attending White House dinners.
It certainly wont pay off for the American public.
FB playbook. Act (spend) then say sorry.
IBM CEO is steering a broken ship and it's not improved course, not someone who's words you should take seriously.
1. The missed the AI wave (hired me to teach watson law only to lay me off 5 wks later, one cause of the serious talent issues over there)
2. They bought most of their data center (companies), they have no idea about building and operating one, not at the scale the "competitors" are operating at
Everyone should read his argument carefully. Ponder them in silence and accept or reject them in based on the strength of the arguments.
His argument follows almost directly, and trivially, from his central premise: a 0% or 1% chance of reaching AGI.
Yeah, if you assume technology will stagnate over the next decade and AGI is essentially impossible, these investments will not be profitable. Sam Altman himself wouldn't dispute that. But it's a controversial premise, and one that there's no particular reason to think that the... CEO of IBM would have any insight into.
It's a very reasonable claim to make, but yes, average denizen of peanut gallery can spot this is a bubble from a mile way, doensn't need "insight" of napkin math done by some CEO that's not even in the industry.
Tho he's probably not too happy that they sold the server business to Lenovo, could at least earn something on selling shovels
then it seems like neither Sam Altman (pro) or IBM (proxy con) have credible or even really interesting or insightful evidence, theories ... even suggestions for what's likely to happen? i.e. We should stop listening to all of them?
Agreed. It's essentially a giant gamble with a big payoff, and they're both talking their books.
we don't need AGI to use all that compute
we need businesses who are willing to pay for ai / compute at prices where both sides are making money
I for one could 10x my AI usage if the results on my side pan out. Spending $100 on ai today has ROI, will 10x that still have ROI for me in a couple years? probably, I expect agentic teams to increase in capability and more of my work. Then the question is can I turn that increase productivity into more revenues (>$1000 / month, one more client would cover this and then some)
IBM can be a hot mess, and the CEO may not be wrong about this. These things are not mutually exclusive.
Is his math wrong?
Are the numbers he's claiming accurate? They seem like big numbers pulled out of the air, certainly much large than the numbers we've actually seen committed to (not even deployed yet).
Sorry that happened to you, I have been there too,
When a company is hiring and laying off like that it’s a serious red flag, the one that did that to me is dead now
It was nearly 10 years ago and changed the course of my career for the better
make lemonade as they say!
IBM CEO has sour grapes.
IBM's HPC products were enterprise oriented slop products banked on their reputation, and the ROI torched their credibility when compute costs started getting taken seriously. Watson and other products got smeared into kafkaesque arbitrary branding for other product suites, and they were nearly all painful garbage - mobile device management standing out as a particularly grotesque system to use. Now, IBM lacks any legitimate competitive edge in any of the bajillion markets they tried to target, no credibility in any of their former flagship domains, and nearly every one of their products is hot garbage that costs too much, often by orders of magnitude, compared to similar functionality you can get from things like open source or even free software offered and serviced by other companies. They blew a ton of money on HPC before there was any legitimate reason to do so. Watson on Jeopardy was probably the last legitimately impressive thing they did, and all of their tech and expertise has been outclassed since.