OpenAI and Nvidia announce partnership to deploy 10GW of Nvidia systems
openai.com
openai.com
I'm not even anti-datacenter (wouldn't be here if I were), I just think there needs to be serious rebalancing of these costs because this increase in US residential electric prices in just five years (from 13¢ to 19¢, a ridiculous 46% increase) is neither fair nor sustainable.
So where is this 10GW electric supply going to come from and who is going to pay for it?
Source: https://fred.stlouisfed.org/series/APU000072610
EDIT:
To everyone arguing this is how DCs are normally sized: yes, but normally it's not the company providing the compute for the DC owner that is giving these numbers. nVidia doesn't sell empty datacenters with power distribution networks, cooling, and little else; nVidia sells the GPUs that will stock that DC. This isn't a typical PR netnewswire bulletin "OpenAI announces new 10GW datacenter", this is "nvidia is providing xx compute for OpenAI". Anyway, all this is a segue from the question of power supply, consumption, grid expansion/stability, and who is paying for all that.
Imagine Ford announced “a strategic partnership with FedEx to deploy 10 giga-gallons of ICE vehicles”
Whether they use all those gigawatts and what they use them for would be considered optional and variable from time to time.
Almost every component in a datacenter is upgradeable—in fact, the compute itself only has a lifespan of ~5 years—but the power requirements are basically locked-in. A 200MW data center will always be a 200MW data center, even though the flops it computes will increase.
The fact that we use this unit really nails the fact that AI is basically refining energy.
Raw AC comes in, then gets stepped down, filtered, converted into DC rails, gated, timed, and pulsed. That’s already an industrial refinement process. The "crude" incoming power is shaped into the precise, stable forms that CPUs, GPUs, RAM, storage, and networking can actually use.
Then those stable voltages get flipped billions of times per second into ordered states, which become instructions, models, inferences, and other high-value "product."
It sure seems like series of processes for refining something.
-- Michael Russel
A 200MW data center will always be a 200MW data center, even though the flops it computes will increase.
N2 is shaping up to be TSMC's most important node since N7.
Is it?
N2, from an energy & perf improvement seems on par with any generation node update.
N2:N3 N3:N5 N5:N7
Power ~30% ~30% ~30%
Perf ~15% ~15% ~15%
Both AMD and NVIDIA are using N4.
Refining is taking a lower quality energy source and turning it into a higher quality one.
What you could argue is that it adds value to bits. But the bits themselves, their state is what matters, not the energy that transports them.
A power plant "mines" electron, which the data center then refines into words. or whatever. The point is that energy is the raw material that flows into data centers.
A local to me ~40W datacenter used to be in really high demand, and despite having excess rack space, had no excess power. It was crazy.
But it very quickly became the best place in town for carrier interconnection. So every carrier wanted in.
Even when bigger local DC's went in, a lot of what they were doing was just landing virtual cross connects to the tiny one, because thats where everyone was.
I still have an Edison bulb that consumes more power.
Why is that? To do with the incoming power feed or something else?
Exactly. When I saw the headline I assumed it would contain some sort of ambitious green energy build-out, or at least a commitment to acquire X% of the energy from renewable sources. That's the only reason I can think to brag about energy consumption
https://subscriber.politicopro.com/article/eenews/2025/09/22...
This is probably naïve. Prices skyrocketed in Germany for similar reasons before AI data centers were a thing.
I would also like to know. It's a LOT of power to supply. Nvidia does have a ~3% stake in Applied Digital, a bitcoin miner that pivoted to AI (also a "Preferred NVIDIA Cloud Partner") with facilities in North Dakota. So they might be involved for a fraction of those 10GW, but it seems like it will be a small fraction even with all the planned expansions.
https://www.investopedia.com/applied-digital-stock-soars-on-...
https://ir.applieddigital.com/news-events/press-releases/det...
This means loads with pretty abysmal power factors (like induction motors) actually end up costing the business more money than if they ran them at home (assuming the home had a sufficient supply of power).
Further, they get these lower rates in exchange for being deprioritised -- in grid instability (e.g. an ongoing frequency decline because demand outstrips available supply), they will be the first consumers to be disconnected from the grid. Rolling blackouts affecting residential consumers are the last resort.
There are two sides to this coin.
Note that I am in no way siding with this whole AI electricity consumption disaster. I can't wait for this bubble to pop so we can get back to normality. 10GW is a third of the entire daily peak demand of my country (the United Kingdom). It's ridiculous.
Edit: Practical Engineering (YouTube channel) has a pretty decent video on the subject. https://www.youtube.com/watch?v=ZwkNTwWJP5k
Although wholesale electricity prices show double-digit average year-on-year swings, their true long-run growth is closer to ~6% per year, slightly above wages at ~4% during the same period.
So power has become somewhat less affordable, but still remains a small share of household income. In other words, wage growth has absorbed much of the real impact, and power prices are still a fraction of household income.
You can make it sound shocking with statements like “In 1999, a household’s wholesale power cost was about $150 a year, in 2022, that same household would be charged more than $1,000, even as wages only grew 2.5x”, but the real impact (on average, obviously there are outliers and low income households are disproportionately impacted in areas where gov doesn’t subsidise) isn’t major.
https://www.aer.gov.au/industry/registers/charts/annual-volu...
Especially since these sorts of corporations can get tax breaks or har means of getting regulators to allow spreading the cost. Residential shouldn’t see any increase due to data centers, but they do, and will, supplement them while seeing minimal changes to infrastructure
When people are being told to minimize air conditioning but then these big datacenters are made and aren’t told “reduce your consumption” then it doesn’t matter how big or small the electric bill is, it’s supplementing a multi billion dollar corporation’s toy
I'm sure none of the other outgoings for a household saw similar increases. /s
The bulk of cost increases come from the transition to renewable energy. You can check your local utility and see.
It’s very easy to make a huge customer like a data center directly pay the cost needed to serve them from the grid.
Generation of electricity is more complicated, the data centers pulling cheap power from Colombia river hydro are starting to compete with residential users.
Generation is a tiny fraction of electricity charges though.
- 0,1952 per kWh for uniform price.
- 0,1635 / 0,2081 for day/nigh pricing
- 0,1232 /... / 0,6468 for variable pricing
https://particulier.edf.fr/content/dam/2-Actifs/Documents/Of...
You have a very bad deal if you pay 0.97€ per kWh.
If the US petro-regime wasn't fighting against cheap energy sources this would be a rounding error in the country's solar deployment.
China deployed 277GW of solar in 2024 and is accelerating, having deployed 212GW in the first half of 2025. 10 GW could be a pebble in the road, but instead it will be a boulder.
Voters should be livid that their power bills are going up instead of plummeting.
In mid latitudes, 1 GW of solar power produces around 5.5 GWh/day. So the "real" equivalent is a 0.23 GW gas or nuclear plant (even lower when accounting for storage losses).
But "China installed 63 GW-equivalent" of solar power is a bit less interesting, so we go for the fake figures ;-)
(Things might be different if you had some sort of SiC process that let you run a GPU at 500C core temperatures, then you could start thinking of meaningful uses for that, but you'd still need a river or sea for the cool side just as you do for nuclear plants)
That's half what I pay in Italy, I'm sure the richest country in the world will do fine.
You underestimate how addicted the US is to cheap energy and how wasteful it is at the same time.
Remember how your lifestyle always expands to fill the available resources no matter how good you have it? Well if tomorrow they'd have to pay EU prices, the country would have a war.
When you lived your entire life not caring about the energy bill or about saving energy, it's crippling to suddenly have scale back and be frugal even if that price would still be less than what other countries pay.
Framing it in GW is just giving them what they want, even if it makes no sense.
> intends to invest up to xxx progressively
> preferred strategic compute and networking partner
> work together to co-optimize their roadmaps
> look forward to finalizing the details of this new phase of strategic partnership
I don't think I have seen so much meaningless corporate speak and so many outs in a public statement. "Yeah we'll maybe eventually do something cool".
In a sense, it's just an ask to public investors for added capital to do a thing, and evidently a number of investors found the pitch compelling enough.
RSU vesting is a bit like options. You have the option but not the obligation to stay in the job!
(Quick, inaccurate googling) says there will be "well over 1 million GPUs" by end of the year. With ~800 million users, that's 1 NVIDIA GPU per 800 people. If you estimate people are actively using ChatGPT 5% of the day (1.2 hours a day), you could say there's 1 GPU per 40 people in active use. Assuming consistent and even usage patterns.
That back of the envelope math isn't accurate, but interesting in the context of understanding just how much compute ChatGPT requires to operate.
Edit: I asked ChatGPT how many GPUs per user, and it spit out a bunch of calculations that estimates 1 GPU per ~3 concurrent users. Would love to see a more thorough/accurate break down.
With that kind of singularity the man-month will no longer be mythical ;)
With varying consumption/TDP, could be significantly more, could be significantly less, but at least it gives a starting figure. This doesn't account for overhead like energy losses, burst/nominal/sustained, system overhead, and heat removal.
So at that point a DC replaces them all with ASICs instead?
Or if they just feel like doing that any time.
To be clear, I am comparing power consumption only. In terms of mining power, all these GPUs could only mine a negligible fraction of what all specialized Bitcoin ASIC mine.
Edit: some math I did out of sheer curiosity: a modern top-of-the-line GPU would mine BTC at about 10 Ghash/s (I don't think anyone tried but I wrote GPU mining software back in the day, and that is my estimate). Nvidia is on track to sell 50 million GPUs in 2025. If they were all mining, their combined compute power would be 500 Phash/s, which is 0.05% of Bitcoin's global mining capacity.
The NVL72 is 72 chips is 120 kW total for the rack. If you throw in ~25 kW for cooling its pretty much exactly 2 kW each.
Google is pretty useful.
It uses >15 TWh per year.
Theoretically, AI could be more useful than that.
Theoretically, in the future, it could be the same amount of useful (or much more) with substantially less power usage.
It could be a short-term crunch to pull-forward (slightly) AI advancements.
Additionally, I'm extremely skeptical they'll actually turn on this many chips using that much energy globally in a reasonable time-frame.
Saying that you're going to make that kind of investment is one thing. Actually getting the power for it is easier said than done.
VC "valuations" are already a joke. They're more like minimum valuations. If OpenAI is worth anywhere near it's current "valuations", Nvidia would be criminally negligent NOT to invest at a 90% discount (the marginal profit on their chips).
30 TWh per year is equivalent to an average power consumption of 3.4 GW for everything Google does. This partnership is 3x more energy intensive.
Ultimately the difference in `real value/MWh` between these two must be many orders of magnitude.
[1] https://sustainability.google/reports/google-2025-environmen...
You over-provision so that you (almost) always have enough compute to meet your customers needs (even at planet scale, your demand is bursty), you're always doing maintenance on some section, spinning up new hardware and turning down old hardware.
So, apples to apples, this would likely not even be 2x at 30TWh for Google.
More than a "Google" of new compute is of course still a lot, but it's not many Googles' worth.
AI that could find a cure for cancer isn't the driving economic factor in LLM expansion, I don't think. I doubt cancer researchers are holding their breath on this.
All-in, you’re looking at a higher footprint maybe 4-5kw per GPU blended.
So about 2 million GPUs.
“You should expect OpenAI to spend trillions of dollars on data center construction in the not very distant future,” he told the room, according to a Verge reporter.
“We have better models, and we just can’t offer them, because we don’t have the capacity,” he said. GPUs remain in short supply, limiting the company’s ability to scale.
So why would Altman say AI is in a bubble but OpenAI wants to invest trillions? Here's my speculation:
1. OpenAI is a private company. They don't care about their own stock price.
2. OpenAI just raised $8.3b 3 weeks ago on $300b valuation ($500b valuation today). He doesn't care if the market drops until he needs to raise again.
3. OpenAI wants to buy some AI companies but they're too expensive so he's incentivized to knock the price of those companies down. For example, OpenAI's $3b deal for Windsurf fell apart when Google stepped in and hired away the co-founder.
4. He wants to retain OpenAI's talent because Meta is spending billions hiring away the top AI talent, including talent from OpenAI. By saying it's in a bubble and dropping public sentiment, the war for AI talent could cool down.
5. He wants other companies to get scared and not invest as much while OpenAI continues to invest a lot so it can stay ahead. For example, maybe investors looking to invest in Anthropic, xAI, and other private companies are more shaky after his comments and invest less. This benefits OpenAI since they just raised.
6. You should all know that Sam Altman is manipulative. This is how he operates. Just google "Sam Altman manipulative" and you'll see plenty of examples where former employees said he lies and manipulates.
in the sense that all of the positive narrative is getting priced in.
The dot com bubble saw crazy deals and valuations, followed by a crash.
some companies emerged from it and went on to be a giant company like Amazon. Let's hope this AI boom have some similar outcomes.
Like using if a datacenter is using hydroelectric power you count the evaporation from the dam reservoir as "used water".
I'm not an expert but imo correct accounting should really only consider direct consumption. It's very silly when we play games like having petro states have very high carbon footprints even if they don't actually burn the fuel.
Both of those have significantly more water impact. Both of those are significantly less useful.
Why not focus on issues that matter.
The argument is that water management policy is lacking and supplies are dwindling, shouldn’t we have better oversight of this resource before we let corporations run full speed ahead?
World is getting thirsty.
> Google is pretty useful. It uses 15 TWh per year.
15TWh per year is about 1.7GW.
Assuming the above figures, that means OpenAI and Nvidia new plan will consume about 5.8 Googles worth of power, by itself.
At that scale, there's a huge opportunity for ultra-low-power AI compute chips (compared with current GPUs), and right now there are several very promising technology pathways to it.
Sharing an example would be nice. Of how much power reduction are we talking here?
An interesting hedge in case the AI bubble pops.
I'm not sure about the GPU pow coins though
https://www.datacenterdynamics.com/en/news/new-jersey-utilit...
The data centers will naturally consolidate in areas with competitive electricity pricing.
In some cases they try to get the data centres to pay for their infrastructure costs but the argument is that customers don't pay this normally but do so through usage fees over time.
That mega dam (Site C) produces 1.1GW of energy.
In the actual shady version of this, Company B isn’t the hottest AI investment around, it’s a shell company created by your brother’s cousin that isn’t actually worth what you’re claiming on the balance sheet because it was only created for the round tripping shell game.
Every time HackerNews talks about anything in the legal or finance realm, people trip over themselves to make arguments for why something a big tech is doing is illegal. This is definitively neither illegal nor shady. If Nvidia believes, for example, that OpenAI can use their GPUs to turn a profit, then this is inherently positive sum economically for both sides: OpenAI gets capital in the form of GPUs, uses them to generate tokens which they sell above the cost of that capital and then the return some of the excess value to Nvidia. This is done via equity. It's a way for Nvidia to get access to some of the excess value of their product.
https://www.cnbc.com/2025/09/17/ai-startup-nscale-from-uk-is...
Also, investing in OpenAI means they get equity in return, which is not a worthless asset. There is actual mutually beneficial trade occurring.
It's a good time to gently remind everyone that there are a whole pile of legal things one can do to change how a security looks "by the numbers" and this isn't even close to the shadiest. Heck some sell-side research makes what companies themselves do look benign.
Two economists are walking in a forest when they come across a pile of shit.
The first economist says to the other “I’ll pay you $100 to eat that pile of shit.” The second economist takes the $100 and eats the pile of shit.
They continue walking until they come across a second pile of shit. The second economist turns to the first and says “I’ll pay you $100 to eat that pile of shit.” The first economist takes the $100 and eats a pile of shit.
Walking a little more, the first economist looks at the second and says, "You know, I gave you $100 to eat shit, then you gave me back the same $100 to eat shit. I can't help but feel like we both just ate shit for nothing."
"That's not true", responded the second economist. "We increased total revenue by $200!"
This kind of corporate behavior is bad and will end up hurting somebody. If we're lucky the fallout will only hurt Nvidia. More likely it will end up hurting most taxpayers.
[1]https://www.corpdev.org/2025/07/23/hp-awarded-945-million-in...
... and we've seen this before in previous bubbles ...
Microsoft and Google have been doing it for decades. Probably, MS started that practice.
In the end, Nvidia will have OpenAI shares, which are valuable, and OpenAI will have GPUs, which are also valuable. It is not fake revenue, the GPUs will be made, sold at market price, and used, they are not intended to be bought back and sold to another customer. And hopefully, these GPUs will be put to good use by OpenAI so that they can make a profit, which will give Nvidia some return on investment.
It doesn't look so different from a car loan, where the dealer lends you the money so that you can buy their car.
It's not necessarily manipulative but it's also not exactly an arms-length purchase of GPUs on the open market.
I say this as someone who has been holding NVDA stock since 2016 and can cash out for a large sum of money. To me its all theoretical money until I actually sell. I don't factor it into financial planning.
You don't see me being a cheerleader for NVDA. Even though I stand to gain a lot. I will still tell you that the current price is way too high and Jensen Huang has gotten high off his own supply and "celebrity status".
After all, we all can't buy NVDA stock and get rich off it. Is it truly possible for all 30,000+ NVDA employees to become multi-millionaires overnight? That's not how capitalism works.
But it goes both ways? Because AI promoters are also spreading FUD. That's how they make money. Because their livelihoods are tied to this technology and all the valuations. So is spreading FUD for you just a condition on whether or not you agree with the person?
But people are literally scared ai will destroy all the jobs after reading articles about how it will. Companies scared not to use ai whether it makes sense or not just to not miss out is where FUD is.
Execs ask their employees to return to office, because they don't know how to measure good employee output.
Now OpenAI and Nvidia measure success by gigawatt input into AI instead of successful business outcomes from AI.
I know watts but I really can’t quantify this. How much of Nvidia is there in the amount of servers that consume 10GW? Do they all use the same chip? What if there is newer chip that consumes less, does the deal imply more servers? Did GPT write this post?
Also, the idea of a newer Nvidia card using less power is très amusant.
So this investment is somewhat structured like the Microsoft investment where equity was traded for Azure compute.
I'm confused because if I assume each rack takes up 1 square meter I get a much smaller footprint: around 12 hectares or 17 football fields.
And that assumes that the installation is one floor. I don't know much about data centers but I would have thought they'd stack them a bit.
Am I the only person who had to look up how big Monaco was?
[1]: https://en.wikipedia.org/wiki/Monaco
[2]: https://www.wolframalpha.com/input?i=10+GW+%2F+%2880kw+%2F+m...
Adding 10GW of offtake to any grid is going to cause significant problems and likely require CAPEX intensive upgrades (try buy 525kV dc cable from an established player and you are waiting until 2030+), as well as new generation for the power!
Don’t datacenters want to run at their rated capacity 24/7?
The xAI Colossus 2 1GW data centers seem to be located about ~20 miles from the power generation utility (https://semianalysis.com/2025/09/16/xais-colossus-2-first-gi...)
How many atrophic,xAi,google,Microsoft would be????
having around 5% entire country infrastructure on AI hardware seems excessive no???
5% to 10% of US electricity going to AI in 10 years is consistent with the current valuations of AI companies.
The platant disregard of global warming by AI investors is truly repulsive.
So there are other factors to weigh besides how much contributes to CO2 emissions.
The reasonable (cost effective, can be done quickly) thing to do is put this wherever you can generate solar + wind the most reliably, build out a giant battery bank, and use the grid as a backup generator. Over time build a better and better connection to the grid to sell excess energy.
He wants coal and gas.
If each human brain consumes ~20W then 10 GW is like 500 M people, that sounds like a lot of thinking. Maybe LLMs are moving in the complete opposite direction and at some point something else will appear that vaporizes this inefficiency making all of this worthless.
I don’t know, just looking at insects like flies and all the information they manage to process with what I assume is a ridiculous amount of energy suggests to me there must be a more efficient way to ‘think’, lol.
Unless the optimization relies in part on a different hardware architecture, and is no more efficient than current techniques on existing hardware.
> there's not a reason for it to make it meaningless any more than more efficient cars didn't obsolete roads
Rail cars are pretty darned efficient, but they don’t really work on roads made for the other kind.
I imagine this as a subtractive process starting with the maximum energy window.
Because if some card with more FLOPS comes available, and the market will buy all your FLOPS regardless, you just swap it in at constant y / for no appreciable change in how much you're spending to operate.
(I have no idea if y is actually much larger than x)
Therefore, they are listing in terms of the critical limit: power.
Personally, I expect this to blow up first in the faces of normal people who find they can no longer keep their phones charged or their apartments lit at night, and only then will the current AI investment bubble pop.
https://en.m.wikipedia.org/wiki/List_of_countries_by_electri...
> to invest up to
i.e. 0 to something something
https://bsky.app/profile/anthonycr.bsky.social/post/3lz7qtjy...
(pencil in another loop between Nvidia and OpenAI now)
It does seem like Satya believes models will get commoditized, so no need to hitch themselves with OpenAI that strongly.
https://www.reuters.com/business/microsoft-use-some-ai-anthr...
500 is insane.
"Good news everybody, your power bills are going up and your creaking, chronically underfunded infrastructure is even closer to collapse!"
https://www.newstarget.com/2025-08-02-texas-ai-data-centers-...
I think the eventual AI bust will lead to the same thing, as the costs for developing a domain-specific model have cratered over the past couple years.
AI/ML (and the infra around it) is overvalued at their current multiples, but the value created it real, and as the market grows to understand the limitations but also the opportunities, a more realistic and permanent boo' will occur.
It appears that the answer is "more likely yes than not".
Counting some examples:
- self driving / autonomous vehicles (seeing real deployments now with Waymo, but 99% deployment still ahead; meanwhile, $$$ billions of value destroyed in the last 10-15 years with so many startups running out of money, getting acquihired, etc)
- Humanoid robots... (potential bubble?? I don't know of a single commercial deployment today that is worth any solid revenues, but companies keep getting funded left / right)
I think you make a very interesting observation about these bubbles potentially being an inherent part of new technology expansion.
It makes sense too from a human behavior perspective. Whenever there are massive wins to be had, speculation will run rampant. Everyone wants to be the winner, but only a small fraction will actually win.
And the data center-class hardware doesn't do well in a home environment. It's not good for gaming. It runs hot and uses a ton of energy. Not to mention, silicon that is running hot 24/7 for years probably isn't the best thing to own second hand.
If this was such a great business, money would be coming from outside and Nvidia would be using its profits to scale production. But they know it's not and once the bubble pops, they profit margin evaporates in months. So they keep the ball rolling - this is pretty much equivalent to buying the cards from ... themselves.
And before you think that's nonsense, let's not forget these people are accelerationists. Destroying the fabric of society is their goal.
I generally like what’s been happening with AI but man this is gonna crash hard when reality sets in. We’re reaching the scary stage of a bubble where folks are forced to throw more and more cash on the fire to keep it going with no clear path to ever get that cash back. If anyone slows down, even just a bit, the whole thing goes critical and implodes.
The current SOTA is going to pale in comparison to what we have 10 years from now.
What advancements?
We have done a fabulous job at lowering power consumption while exponentially increasing density of cores and to a lesser extent transistors.
Delivering power to data centers was becoming a problem 20 ish years ago. Today Power density and heat generation are off the charts. Most data center owners are lowering per rack system density to deal with the "problem".
There are literal projects pushing not only water cooling but refrigerant in the rack systems, in an attempt to get cooling to keep up with everything else.
The dot com boom and then Web 2.0 were fueled by Mores law, by Clock doubling and then the initial wave of core density. We have run out of all of those tricks. The new steps that were putting out have increased core densities but not lowered costs (because yields have been abysmal). Look at Nvidia's latests cores, They simply are not that much better in terms of real performance when compared to previous generations. If the 60 series shows the same slack gains then hardware isnt going to come along to bail out AI --- that continues to demand MORE compute cycles (tokens on thinking anyone) rather than less with each generation.
Collapse might look a little like the dot com bubble (stock crashes, bankruptcies, layoffs, etc)
These hype cycles aren't even bad per se. There is lots of capital to test out lots of useful ideas. But only a fraction of those will turn out to be both useful and currently viable, and the readjustment will be painful
Bubble collapsing looks like enshittification of OpenAI tools as they try to raise revenues. It’ll ripple all throughout tech as everyone is tied into LLMs, and capital will be harder to come by.
This is totally False, NVDA has not done any stock offerings. The money is coming from the ungodly amount of GPUs they are selling. In fact they are doing the opposite, they are buying back their stock because they have more money that they know what to do with.
Buybacks are the preferred method of RETURNING CASH to shareholders, because dividends historically have been sticky. Buybacks are flexible.
Buybacks are also done to optimise the debt ratio, to minimise the firms cost of capital and thereby maximizing firm value.
Meanwhile NVDA stock is mildly up on this news, so the current owners of NVDA seem to like this investment. Or at least not hate it.
Agreed that we’ll see ad-enabled ChatGPT in about five minutes. What’s not clear is how easily we’ll be able to identify the ads.
Then consider we are about to lower interest rates and kick off the growth cycle again. The only way these valuations are going is way up for the foreseeable future
Why does monetizing OpenAI tools lead to bubble collapse? People are clearly willing to pay for LLMs
This isn't a bubble. This is the collapse of 300 years of modern capitalism into corporate techno feudalism.
This won't crash and lead to a recession or depression. We are at the end game. Look around you. Capital is going scorched earth on labor. They are winning. Cost of living in metropolitan areas is exploding, and most of us will end up begging for scraps in peripheral areas.
This is the result of everything the elites have been working towards for the past few decades. Climate catastrophe is the cherry on the cake: they will shock therapy us into the last few bits. There will be corporate citizenship that enables one to live as a demi-god at the behest of the owners, and survival in the wastelands for the rest of us.
[0] dyson spheres are a joke / Angela Collier https://youtu.be/fLzEX1TPBFM
How much investment and prioritization in scaling laws is justified?
What is the source of the cash in steps 3, 4, and 7?
Disclaimer: I also have a small amount of money in vanguard IRA
The flywheel metaphor is pretty apt.
I’m not saying there isn’t a bubble, but I am saying if the researchers and strategists absolutely closest to the “metal” of realtime frontier models are correct that AGI is in reach, then this isn’t a bubble, it’s a highly rational race. One that large players seem to be winning right now.
Inference services are wildly profitable. Currently companies believe it’s economically sensible to plow that money into R&D / Investment in new models through training.
For reference, oAI’s monthly revs are reportedly between $1b and $2b right now. Monthly. I think if you do a little napkin math you’ll see that they could be cashflow positive any time they wanted to.
Then my selling 2 dollars for 1 dollar is a wildly profitable business as well! Can't sell them fast enough!
Why does it seem like so many people have ceased to think critically?
The company overall is still not profitable because these proceeds are being used to fund training the next GPT generation.
Say the first model cost $2 to make. On metered sales, they’ve made $10 on it.
They then decide to make a $20 model, raising more money. It turns out, that model made $100.
They then decide to make a $1,000 model. That model made $5,000.
There are two possible paths for their shiny new $10,000 model: either it will be a better market fit than the 1k model, or it will not.
If it is a better market fit than the 1k model, then it seems very likely that at some point it will make more than $10,000 (2x the prior model’s utility).
If it does not provide better value, then you can scrub that model, and keep selling the $1k model. Eventually it will likely provide the additional $5k of investor capital back through profits.
What we have seen is this above scenario, with a couple twists: first, the training (capital investment) decisions overlay the useful life of the prior model, so you have to tease out the profitability when you think strategy. Second, it turns out there’s quite a lot of money to be made distilling models the market likes into models that give like 90% better profit.
So, these businesses paying billions of dollars to train frontier models are absolutely rational actors. They are aggressive actors, engaged in an arms race, and not all of them will survive. But right now, with current inference demand, if all the global training capital dried up, (and therefore we are stuck with current models for some time), they would become highly, highly profitable companies during the period where fast followers tried to come in and compete on price.
You can choose to have a Claude API portal to the future where you pay 2025 prices for token inference, or you can skip it, and use 1995 devs to build your competitor.
Which do you do?
Even if we assume this is true, the downstream customers paying for that inference also need it to pay for itself on average in order for the upstream model training to be sustainable, otherwise the demand for inference will dry up when the music stops. There won't always be a parade of over-funded AI startups burning $10 worth of tokens to bring in $1 of revenue.
I can maybe digest the fact that it helped prototype and ship a bit more code in a shorter time frame... but does that warrant in enough new customers or a higher value product that would justify $100k a month?!
The 20% spent on dev tooling seems well-spent. About 10 devs on the team, and all at least 2x (hard to measure exactly, but 2x seems conservative) more productive with these tools.
Right now, I assume more the former than the latter. But if you're an optimistic investor, I can see why one might think a few hundred billion dollars more might get us an AI that's close enough to the latter to be worth it.
Me, I'm mostly hoping that the bubble pops soon in a way I can catch up with what the existing models can already provide real help with (which is well short of an entire project, but still cool and significant).
* e.g. the tokens are bad financial advice that might as well be a repeat of SBF
** how many tokens would get you the next Minecraft?
I propose software creation, and therefore demand for software creation are subject to Jevon’s Paradox.
It's less "will it happen" now, and more "whether it hits in a few decades or in a few years".
The real question is what are we gonna do with all this cheap GPU compute when the bubble pops! Will high def game streaming finally have its time to shine? Will VFX outsource all of its render to the cloud? Will it meet the VR/AR hardware improvements in time to finally push the tech mainstream? Will it all just get re-routed back to crypto? Will someone come up with a more useful application of GPU compute?
Right now I kind of land on the side of "Where is all the shovelware?". If AI is such a huge productivity boost for developers, where is all the software those developers are supposedly writing[3]? But this is just a microcosm of a bigger question. Almost all the economic growth since the AI boom started has been in AI companies. If AI is revolutionizing multiple fields, why aren't relevant companies those fields also growing at above-expected rates? Where's all this productivity that AI is supposedly unlocking?
[1] https://hms.harvard.edu/news/does-ai-help-or-hurt-human-radi...
[2] https://www.ajronline.org/doi/10.2214/AJR.24.31493
[3] https://mikelovesrobots.substack.com/p/wheres-the-shovelware...
Of course i agree ML has already helped in many other areas and has a bright future. But the thing everyone is talking about here are LLM's
Even if AI somehow bucks the trend and stops advancing in leaps? It's still on track to be the most impactful technology since smartphones, if not since the Internet itself. And the likes of Nvidia? They're the Cisco of AI infrastructure.
AI is here to stay, but the question is whether the players can accurately forecast the growth rate, or get too far ahead of it and get financially burnt.
Is there some (tax?) efficiency where OpenAI could take money from another source, then pay it to Nvidia, and receive GPUs. But instead taking investment from Nvidia acts as a discount in some way.
(In addition to Nvidia being realistically the efficient/sole supplier of an input OpenAI currently needs. So this gives
1. Nvidia an incentive to prioritize OpenAI and induces a win/win pricing component on Nvidia's GPU profit margin so OpenAI can bet on more GPUs now
2. OpenAI some hedge on GPU pricing's effect on their valuations as the cost/margin fluctuates with new entrantsBut now that there is a new SEC, they are doing a bunch of these deals. There is this one, which is huge. They also invested in Lambda, who is deploying Gigawatt scale datacenters of NVIDIA GPUs. And they are doing smaller deals too.
https://nvidianews.nvidia.com/news/nvidia-announces-financia...
This also explains why NVIDIA will not sell high VRAM consumer GPUs: it would cannibalize on their exorbitant data-center profits.
I'm asking because its not just OpenAI that they are apparently doing this with, instead its with multiple other major GPU providers, like Coreweave.
And its just being done all out in the open? How?
I'm just surprised that nobody is yelling to the rooftops about practices that are just so out in the open right now.
As an investor you may decide that round-tripping is dumb but in that case your recourse is to sell the stock.
Textbook round tripping is like: OpenAI buys GPUs from Nvidia. And the only reason it buys these GPUs is to resell it back to Nvidia, or just do nothing. It doesn't make it round tripping just because OpenAI is taking investment and buying stuff from Nvidia at the same time.
Unless you really believe OpenAI has no intention to use these GPUs for other purposes (like training GPT-6. I know, a crazy idea: OpenAI will train and release a model), it's not round tripping.
> OpenAI buys GPUs from Nvidia. And the only reason it buys these GPUs is to resell it back to Nvidia
Funny you should say this. Nvidia having those GPUs be rented back to them is also something thats happening.
https://www.kerrisdalecap.com/wp-content/uploads/2025/09/Ker...
"As detailed by The Information, in early 2023 Nvidia invested $100 million in equity and signed a $1.3 billion rental agreement through 2027, under which it rents back GPUs from CoreWeave to support internal R&D and its DGX cloud offering."
"CoreWeave is not the only neocloud to benefit from Nvidia’s strategic support. Nvidia has actively supported an ecosystem of emerging AI infrastructure providers – including Lambda, Nebius, and Applied Digital –"
They are quite literally buying GPUs only to rent them right back to Nvidia.
And these are just the public deals. Is Nvidia systematically selling GPUs and having them be rented back to, by every major GPU cloud providers?
https://www.investing.com/analysis/coreweave-nvidia-partners...
"This deep alliance culminates in the new $6.3 billion agreement. The deal’s most critical component is a strategic commitment from NVIDIA to purchase any of CoreWeave’s unsold cloud computing capacity through April 2032"
I (as a uninformed rando) think that there are a lot of research ideas that have not been fully explored because doing a small training run takes 100k. If that drops to 1000, then there is a lot more opportunities to try new techniques.
That's where the belief that we are in a bubble comes from.
Inference has extremely different unit economics from a typical SaaS like Salesforce or adtech like google or facebook.
This market dynamic begets a low margin race to the bottom, where no party appears able to secure the highly attractive (think the >70% service margin we see in typical tech) unit economics typical of tech.
Inference is a very tough business. It is my opinion (and likely the opinion of many others) that the margins will not sustain a typical "tech" business without continual investment to attempt to develop increasingly complex and expensive models, which itself is unprofitable.
In the absence of typical software margins, they will be eroded by providers of "good enough" margins (AWS, Azure, GCP, etc.) who gain more profit from the bundled services than OpenAI does from the primary services. This has happened multiple times in history, either resulting in smaller businesses below IPO price (such as Elastic, Hashicorp, etc.) or outright bankruptcy.
Second, the distilling happens on the outputs of the model. Model distillation refers to the usage of a models outputs to train a secondary smaller model. Do not mistake distillation for training (or retraining) to sparse models. You can absolutely distill proprietary models. In fact, that is how DeekSeek-R1-Distill-Qwen and the DeepSeek-R1-Distill-Llama are trained. This also happens with Chinese startups distilling OpenAI models to resell [2].
The worst part is OpenAI is already having to provide APIs to do this [1]. This is not ideal, as OpenAI wants to lock people into (as much as possible) a single platform.
I really don't like OpenAIs market position here. I don't think it's long term profitable.
[1] https://openai.com/index/api-model-distillation/
[2] https://www.theguardian.com/technology/2025/jan/29/openai-ch...
Indeed. And even if that revenue is net profitable right now (and analysts differ sharply on whether it really is), is there a sustainable moat that'll keep fast-followers from replicating most of OpenAI's product value at lower cost? History is littered with first-movers who planted the crop only to see new competitors feast on the fruit.
The classic story of the shoeshine boy giving out stock tips...and all that.
We all know how that turned out.
I am fundamentally skeptical of "scaling inference". Margins are not defensible in the market segment OpenAI is in.
I'm also pretty skeptical, and could imagine this whole thing blowing up, but it's not like this a big grift that's going to end up like the GFC either.
It's already happening in China that datacenters are at GPU overcapacity. I wouldn't be surprised if it occurs here.
I do buy that they are extremely over-valued if they have to slow down on model training.
For cloud providers, the analysis is a bit more complex; presumably if training demand craters then the existing inference demand would be met at a lower price, and maybe you’d see some consolidation as margins got compressed.
But OpenAI can't stop training their next generation models. OpenAI already spends over 50% of their revenue on inference cost [1] with some vendors spending over 100% of their revenue on inference.
The real cash cow for them is in the business segment. The problem here is models are rapidly cloned, and the companies adjacent to model providers actively seek to provide consumers the ability to rapidly and seamlessly switch between model providers [2][3].
Model providers are in the situation you imagine cloud providers to be in; a non-differentiated, commodity product with high fixed costs, and poor margins.
[1] https://www.wheresyoured.at/why-everybody-is-losing-money-on...
[2] https://www.jetbrains.com/help/ai-assistant/use-custom-model...
[3] https://code.visualstudio.com/docs/copilot/customization/lan...
Zuckerberg said in an interview last week he doesn't mind spending $100B on AI, because not investing carries more risk.
To date, no evidence of either even exists. See Zuckerbergs recent live demo of Facebooks Ray Bans technology, for example.
For example, inference on older GPUs is actually more profitable than bleeding-edge right now; the shops that are selling hosted inference have options to broaden their portfolio the advancement of the frontier slows.
Cloud providers are currently “un-differentiated”, but there are three huge ones making profits and some small ones too. Hosting is an economy-of-scale business and so is inference.
And all of these startups you quote like Cursor that are not free-cash-flow positive are simply playing the VC land grab game. Costs will rise for consumers if VCs stop funding, sure. That says nothing about how much TAM there is at the new higher price point.
The idea that OAI is un-differentiated is just weird. They have a massively popular consumer offering, a huge bankroll, and can continue to innovate on features. Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.
And generally speaking there are huge opportunities to do enterprise integrations and build out the retooling of $10T of economic activities, just with the models we have now; a Salesforce play would be a natural pivot for them.
Anybody who has worked in a compliance heavy segment (PCI-DSS, HIPAA, etc.) will tell you the big 3 clouds have very significant differences from the smaller players. The differentiation is not on compute itself, but on the product. It's partially why products like AWS Bedrock exist and are actively placing model providers both in competition with eachother and AWS itself which is exactly the market dynamic they should seek to avoid.
> The idea that OAI is un-differentiated is just weird. They have a massively popular consumer offering, a huge bankroll, and can continue to innovate on features. Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.
This is exactly where this line of reasoning goes off the rails. The consumer market is problematic (see the recent post about the segment its growing in; basically young women of limited spend in low income countries); a huge bankroll is also a huge liability, model providers are on a clock to get huge or die, and the innovation we are seeing is effectively attempting to "scale-up" models, not provide novel features.
> Their consumer offering has remained sticky even though Claude and Gemini have both had periods of being the best model to those in the know.
This isn't a good thing with current market mix.
> And generally speaking there are huge opportunities to do enterprise integrations and build out the retooling of $10T of economic activities, just with the models we have now; a Salesforce play would be a natural pivot for them.
Do you have any indication these are achieving buy in or profitable? Most significantly, we have seen a recent study by MIT that 95% of generative AI pilots fail. The honeymoon period is rapidly coming to a close. Tangible results are necessary.
It just turns out they were a server farm subsidizing a gift shop.
Ultimately the marketplace was just an investment that had embedded within it a real option for AWS. Magical really.
I guess that’s why they would be gaming their numbers: to convince the next greater fools.
Well, yes. Which again is how venture capitalism has worked for ... is it decades or centuries? There is always an element of risk. With pretty solidly established ways to handle: expected value, risk mitigation etc.
I haven't lived through the dot com bubble (too young) but i've read about it. The absolutely insane ways they were throwing money at startups were... just insane. The potential of the technology is the same now and then: AI vs Internet. It wasn't the tech that failed the last time, it was the way the money was allocated.
The math is actually quite mathing this time around. Most AI companies have solid revenues and business models. They aren't turning a profit because (like any tech startup) they chose to invest all their revenue plus investments into growth, which in this case is research and training new models. They aren't pivoting every 6 months, aren't burning through cash reserves just to pay salaries, and they've already gone through train/deploy cycles several times each, successfully.
Are they overvalued? shrug that's between them and their investors, and we'll find that out eventually. But this is not a bubble that can burst as easily as last time, because we're all actually using and paying for their products.
At this moment they could as well be called bitcoin or tulips....No different from Chinese ghost towns. Real houses being planned and built... And let's not talk to accountants about the depreciation rates on GPU Hardware that is out in 8 to 12 months...
Infrastructure tends to have much longer lifetimes. A lot of the telco infrastructure "overbuilt" during that boom is still used today - you can always blow new fibre, replace endpoints and all that without digging everything up again, which was the largest cost in the first place. Sure, in the above example you'll still the datacentre itself (and things like electricity connections and cooling) that can be reused, but that's a relatively small fraction of the total cost comparitively.
But the "round tripping" kind of makes sense. OpenAI is not listed, but if it was, some of the AI investment money would flow to it. So now, if you are an AI believer, NVidia is allocating some of that money for you.
By many different measures, we are at record valuations (though must be said, not P/E however). Tends not to end well. And housing prices are based on when mortgages were at 3% and have not reset accordingly. We are in everything bubble territory and have been.
Always keep in mind the old saying: pesimists get to be right and optimists get to be rich.
Optimists go bankrupt or something and you blame them on their work ethic or something and you discard any of those optimists who didn't really succeed and cherry pick those optimists which went right...
Its a classic survivorship bias.
I am pessimistic in US stocks because they are so concentrated on AI for returns and its definitely a bubble or approaches its territory, there is somewhat no denying about it from what I observe.
Your comment really is just off putting to me because I feel like its just a copium which is going to be inhaled by the new generation and then if we fail which lets be honest failure is a natural part of life, we are gonna blame ourselves and that's just really depressing.
I'd better be right than rich. Maybe my rich definition is something that I can get out of hard work while maybe being pessimist (just enough money to have freedom lol)
I don't want to make billions or hundreds of millions, i don't want to build a vc funded disaster for humanity in the name of shareholders whether its an Ad dystopia or an AI nightmare fuel, I'd rather make a imprint on humanity other than my bank account number but maybe that's me being "optimistic"
Sorry but your comment truly ragebaited me... I have very strong opinions in this regards.
The russel 2000 index just made an all time high. The bull market is diverse and global. Indexes of many countries are also at all time highs.
I also didn't know that the other world's stocks are doing fine actually. but maybe there is a difference in economy and stocks at this point...
I believe that we can all surely agree on the legendary john bogle's philosophy and in the current day and age realize that us s&p stocks are too centralized on ai and world stocks can be better...
Regarding russel 2000 index. I feel like a lot of money trickles down from the AI hype but its honestly great that russel is doing great.
The point I am trying to make is that atleast for US right now, its political system is so shaky that I can't trust its economical system and there is no denying that if the AI bubble bursts, then it would bleed the whole economy at this point including russel.
There was a great hank green video which I recommend about this concept https://www.youtube.com/watch?v=VZMFp-mEWoM
Also, A lot of countries are definitely in turmoil right now so I am actually surprised by your statements that world economy is doing quite high, maybe stock markets are just another asset class which have gotten so inflated that they are out of touch from the ground reality... (Something I heard in an atrioc video)
I am definitely a bit surprised to hear that the world stocks are doing fine from all the bloodbath of tarrifs and some political issues the world is facing right now...
The stock market has so much money going into it that it is in a bull market. Because people have nowhere else to put their money into (real estate is dead atm).
You are letting your political biases poison your financial decisions.
And I feel like its in a bull market because of AI Hype which was the main comment of the original parent to which you responded I think...
If this AI hype fails to deliver. Literally the magnificient 7 will have a huge loss of money which would then make the stockholders feel less wealthy which will spend less and it would have a drastic impact in the WHOLE economy.
Yes its in a bull market but I feel like I don't want to find out if I am in the peak of a bull market for an AI craze y'know?
And I am not advocating against stocks omg, I am just saying that world stocks are better in current landscape and I doubt if its poisoning my financial decisions.
NO I Don't want all of my saved money to go into an index which is going to be heavily dictated by the future of AI which I and many presume to be a bubble. I would much rather invest in index funds that target the world, heck maybe even index funds that target every country ex usa
My point is that the bubble will burst and then atleast S&P / nasdaq will definitely bleed.
Either we can talk about if you think its a bubble or not, since I am not comfortable investing in a bubbly situation no matter how lucrative it becomes y'know?
What are your thoughts on it?
Mag7 are some of the most profitable and well run companies in history investing their insane profits.
No other country has public markets as developed, regulated and liquid as the US. Likely you are just investing into the unknown with a ton of risk factors you are not aware of. In places outside of the US politics actually is a significant factor in investing.
I can be wrong, I usually am.
That being said, My question to you is:
Do you believe that it is an excuse if I don't invest in mag7 while they are most profitable and well run because I believe that their stock price is highly overflated and past performances aren't indicative of future performances unless we are talking over an aggregate time which the general markets do have.
Now the question is, Do you think its an excuse if I don't want to invest in mag7 because I am worried that its an AI bubble and that worry is backed up by the fact of this AI craze.
If AI doesn't deliver on its prices, can you wager that MAG7 would actually do good? Of course it wouldn't.
What do you mean to think that AI would deliver to its prices as it seems to be either only hyper applicable in tech and all other AI tech is seemingly run at a loss and I can see no way how they might force normal users when there is so much foss ai to actually pay for ai...
What is the monetization plan? Is it to churn the money that you get from stocks into AI to get a higher evaluation of stocks and do some passing around the circle from one company to other and repeat?
Well run is another questionable term given how Magnificient7 includes tesla but maybe we can talk about it later.
I believe that time in the markets beats timing in the markets, so your experiences shouldn't be with a market that feels bubbly y'know? Otherwise, you might just stop it alltogether and I feel like that things might fall down quicker than we think as AI is kinda scrambling through, A lot of people felt disappointed in gpt-5. Reality is settling in, but is reality settling in those magnificient 7 stocks?
I consider myself to be an average investor in the sense that being a superior investor is insanely insanely difficult and its much easier to think you are a superior investor because you might get lucky and then lose more money than you could've made over a long term of time and you try to recoup previous money and previous money.... I definitely don't want to experience it in first place to keep my experiences somewhat moderate y'know?
This is HN so I presume you don't get bored with this response as I love this talk & trying to understand your point in good faith!
You are confusing a popular, cover my ass legal statement with market truth. Past performances absolutely are indicative of future performance the vast majority of the time. They are of course not a guarantee. Inflated price is also not a particularly good indicator of future performance. A stock generally has a high valuation for a reason.
> What do you mean to think that AI would deliver to its prices as it seems to be either only hyper applicable in tech and all other AI tech is seemingly run at a loss and I can see no way how they might force normal users when there is so much foss ai to actually pay for ai...
Google, Microsoft and others run real world AI and I doubt it is at a loss. They make a ton on money on infrastructure. OpenAI operates at a loss, but it is a private company.
> I feel like that things might fall down quicker than we think as AI is kinda scrambling through, A lot of people felt disappointed in gpt-5. Reality is settling in, but is reality settling in those magnificient 7 stocks?
You consider yourself to be an average investor, yet you disagree with the market, thus you think you are smarter than the market. This is cognitive dissonance. The market is a public consensus of the future. Stocks that are more valued have a higher price, because people are willing to bet money they will do better in the future.
This is not toolip mania, or even the dotcom bubble. Bull markets are always caused by investment cycles. Before AI it was mobile and cloud. Those were not bubbles. Neither is AI, because the real world usage is undeniable. The user growth trajectory of ChatGPT was unprecedented. Google deepmind founders got a nobel prize for their work, for something that happened just a few year prior, but was so groundbreaking it deserved it.
Also I am not some investing guru, I just listen to some great investment podcasts. The Real Eisman Playbook (Steve Eisman is the person portrayed by Steve Carell in The Big Short) and Compound and friends.
It seems that we aren't agreeing on if the market is in a somewhat bubble or not.
You say that real usage is undeniable. But to me its undeniable because its being spoon fed to you for free for SOTA models from all fronts including open source chinese models.
They are running at a loss because they are having these insane growth cycles but they have no moat to a somewhat degree.
Tell me how OPENAI or any AI company plans to be profitable and actually return great profits on what the investment is.
The thing is, that they have to constantly train and retrain the models to reach SOTA and people are realizing that they are being benchmaxxed.
Open source models are coming to a somewhat close degree and I doubt that it would be thaaat noticable for most consumers y'know?
There is no moat. Sure, maybe there is some moat in coding as I feel like that is the only thing that wasn't touched by Open source models.
Open source has sort of SOTA image models, SOTA-ish video models and what not & so anybody can try to compete with these on things like open router which is where half the api uses become because of how convoluted other apis are and how openrouter just sorta works...
I can provide you sources as well but there is a long consensus that AI doesn't really help in research thaat much.
The point is, that sure there is this great tech but its just unprofitable at the scale if you consider providing free access to the masses too.
Tell me how these companies are gonna make a consistent profit on AI without being crunched by each other's SOTA benchmaxxing and kill throat competition from China's open source models.
I genuinely wonder what "real world AI" to you is & how its turning up at a profit.
Like, okay, maybe I can agree that sure maybe inference could be made profitable if done to somewhat degree like how deepseek did but there is no way that it was worth the return in investment...
And do you know what happened? Nvidia selling the shovels, "infrastructure" got to be the most valuable company. If this isn't a bubble then why did Nvidia lose so many billions of $'s just because China released deepseek model.
Sure nvidia has regrown but are you really not going to take the past into account?
Regarding past performance quote, I think that I had also agreed in my original quote but I had mentioned past performance of something like 100 years. Computer stocks have been less time than that and this AI hype is quite new.
These companies like google etc. are integrating everything AI not because they want to but because their stock rises up when they mention AI for the most part.
I will repeat this again, my friend, but if you can tell me how the average investor is investing into a business which is going to make a profit...
How are they going to make a profit given the amount that they have invested in with degrees of no moat, it seems that entreprise is the most clear moat they have but https://www.forbes.com/sites/jaimecatmull/2025/08/22/mit-say...
Coding models might be the most profitable imo given that people want absolute best in it and they don't mind paying the price (claude code) but that is a niche of niche and that alone can't justify the amount of investment and stock prices made I suppose, not unless you believe in some sort of AGI.
How are these companies going to make a profit dude, the only way they have been for now is by their stock prices but I know that you know that it isn't sustainable, thus it becomes a sort of bubble situation.
I am an average investor, yet I am cautious of the times here, because I believe that AI just kinda came out of no where and became a mainstream word and VC's were funding things like devin which was literal BS LMAO but the amount of fear mongering there was, was crazy. So like, there was a fomo of more VC's which invested in more AI's which then made people jump into the trend to then have a scene where anything labelled with AI gets stock price to
Am I false in the above statement?
How is this not a bubble? The tech is cool but people aren't paying in stock markets to support a tech or smth, they want returns now... And once those returns stop coming in the sense that people realize this... Oops, looks like nobody want those Ai stocks anymore.
I have read the intelligent investor to a somewhat degree to then pick up on John bogle's index fund related book to realize that benjamin graham, the creator of intelligent investor would've also preferred index funds and thus my whole sentiment shifted towards realizing diversification and to maybe preventing bubbles I suppose.
Honestly, so funny because your statements could be shown in history as what people believed before the bubble burst and it would still be accurate and mine tbh can also be taken in that intepretation from the other way...
I hope you are still interested as I still love this discussion!
But that is an entirely different game compared to what AI is being used for now. Two random examples I came across:
https://x.com/LinusEkenstam/status/1965014479760204118
https://longevity.technology/news/new-ai-tool-demonstrates-p...
This is AI as it is capable now, solving real life problems and making industries more efficient. This is happening throughout practically every field of human endeavor, which is why ChatGPT is used so much. Medicine, biomedicine, law, translations, coding, investing, learning and so on.
nVidia is the most valuable company in the world right now, because they are powering practically all of it.
Worrying about profits right now is an entirely wrong thing to concentrate on. Analogous to the previous investment cycle: Youtube is one of the most valuable pieces of the tech industry. It was a money loser for a damn long time and would have gone broke if google had not bought them, not to mention being sued out of existence (a real threat in the early days). When it was made in 2006 it was a bet everyone thought was insane, because of the infrastructure costs and legal risks. Right now it is very profitable, because they had time to optimize and develop their business model.
Here's the thing though:
Youtube has a moat. It is a social media and the networking effect runs wild on it and tbh there were a lot of other things too like (vines?) which fall.
But, can you say the same for Ai given open models?
China couldn't create an alternative to social media (in some sense?) because it requires a network effect.
But it sure can use gpu's, maybe even build their in house gpus so that they can then train on the data just as how america did and effectively price dump with no restrictions :/
Honestly, I can agree if you believe that AI Has a moat similar to social media, then sure, but I just don't believe it has a moat.
Youtube turned profit because of moat, Is there any moat in LLM's?
And if we are talking general purpose robotics/ automation, then I agree that yes its good.
But for an average investor whose investing, they are investing thinking that its sort of inevitable actual general AI when that's not the case.
From what I know, the optimizations of LLM's don't really apply to robotics, so all this funding of billions going into LLM only to pivot into robotics is a bit :/ for the investors.
IMO When I mentioned S&P AI stocks, that's exactly things like Google,microsoft,amazon which are still similar to OpenAi and anthropic, don't you think?
S&P's growth is heavily based on the calculated return that Google,microsoft,amazon are gonna be the winners of the Ai "wars", that's what I meant!!
If google says a line similar to yours that LLM's aren't the future, then you can naturally expect how the market would react.
The funny thing is, is that between your comment, I got recommended a video about AI bubble... which is accused in comments to be created by AI
https://www.youtube.com/watch?v=37aUuoRyMhM
The tech is cool but 95% are focused on the wrong thing or smth and there is no advantage/moat and uh its still literally something like. bubble. Even in a bubble, google/amazon survived.
You can say that I should still invest because stock prices grew even after bubble bust, but they were in a deep awakening, and I feel like as an average investor I'd rather prefer some more stability knowing that there is still a condition of a bubble formation in S&P and US tech stocks atleast
These companies are using AI as a magic word. Vercel's keynote had AI esque words 42 times... LET ME REPEAT, 42 times. Vercel isn't even that AI based lol, its a react next app thingy for most people.
Still hoping you can comment! I was thinking of creating a hackernews post about involving other people in this discussion since at the day our discussion boils down to: is this a bubble?
I thought that it was common knowledge to everybody but maybe not, I can create a ASK HN: Do you think that S&P 500 / Magnificient 7 is an AI bubble right now? or smth!
Looking forward to your feedback and I had a blast in this conversation! Wish to discuss more lol!! Have a nice day, (waiting for your comment)
AI wave is more than just LLMs. Movement autonomy for cars/robots, image/video generation, protein folding, etc. Those are not LLM based AI applications. They are all downstream from the transformer architecture. Autonomy AI development is the missing piece of robotics, which is why so many billions are being invested now.
The lack of moat regarding LLMs is a problem only to those playing in that field, but their actual goals are not just running LLMs, they are like I said aiming for actual general intelligence.
In the mean time, companies are training or optimizing their own models for their use cases, like the ones I listed in the previous reply. They do have a moat, because they require specialized knowledge to play in that field. Even the abel police guys, their competitors were just an interface to ChatGPT and it worked abysmally.
> IMO When I mentioned S&P AI stocks, that's exactly things like Google,microsoft,amazon which are still similar to OpenAi and anthropic, don't you think?
Absolutely not. OpenAI is a private company spending insane billions for a moonshot project. The public S&P500 companies are investing their insane profits and making a return on those investments. Their infrastructure and scale is a moat.
I agree with all the aspects of protein folding / general purpose automation due to "AI" and not LLMs but that was happening before the "AI" hype thanks to OpenAI / chatgpt where so much money was flowing into it...
And I have no issues with them if their prices were baked into realism that they were baked into pre 2022's / whenever chatgpt got launched
My biggest issue which is the crust of this discussion might be that I believe that tech stock prices are roaring so high mostly because of the AI hype that they bring which raises their prices.
Oracle made larry Ellison the richest person for some time due to the stargate project / due to their deal with OpenAI / then larry invested into openai for some hundred billion $ which openai paid back to oracle and oracle's stock price increased more... rinse and repeat?
The thing is, why is oracle which I think is S&P company raising because of their deals in LLM's at an unastronomical rate/ unprecedented rates.
Google/meta/microsoft/amazon are also all integrating AI into their every project / mentiniong AI as much as possible which lets be honest again, is mostly LLM's for the most part.
Yes I know, google has some really interesting non LLM AI projects which I know and love but they were pre 2022 and google's price wasn't as much dictated by those projects as they are doing now y'know?
My conclusion is that A lot of people can't / couldn't invest into OpenAI / thus flowed their money into anything LLM / AI related in the markets... & the companies are loving this and mentioning AI as much as possible
Can we agree on this or not?
I can agree if you think that these companies are investing into infrastructure but that infrastucture is now mostly GPU's which are only really useful for LLM related tasks and becomes redundant for general purpose stuff like running servers for the most part.
Do we agree on this or not?
Also regarding infrastructure, The thing is, That most of them are just packing Nvidia Gpu's which is something that Nvidia also offers and others could do too but yeah, I can get that part but is it an "investment" is questionable...
Its an investment only if LLM's turn out to be profitable.
Firstly the cut throat competition means that literally everyone is competing in it so it cuts each other profits.
Secondly, there are some recent models which are kinda small and could run to a somewhat degree on modern hardware if need be which could satisfy some users needs without having to need that infrastucture
Then again, even if there are some people that might not have that and they search on things like chatgpt. They do it out of freebies that its not gonna cost them that much. And they can switch out if those AI providers do charge them first... with open source models while they themselves ride this end of AI hype.
If you believe that AGI is near, whatever that means, then literally everything I said gets out of the equation but I am assuming you aren't believing that.
Now sure there are gonna be returns but they aren't gonna be nearly as expected. In fact I think that most S&P companies are gonna be in a loss with all of these training of models / building infrastructure. Also, training of models is a recurring cost for the most part if they have to stay SOTA iirc with higher developer's cost working in AI/ML (100 million$ income is provided by the people investing into S&P dude)
So with all of these things, I believe that there is a legitimate concern that the investment isn't worth the return.
Then why are companies investing?
Because of fomo. When the AI hype started thanks to chatgpt. every private equity rushed for similars and that kinda leaked into S&P companies which are doing the same thing with AI hype mentioning it so much.
Do you agree?
If you can agree with all 3 of these statements to a reasonable degree, then I believe that we can agree that we are in an agreement and that it isn't much of an investment as its a way to somehow increase their stock prices by essentially mentioning the word AI and that's all that matters to them in the end, but its all on a proposition that someone is gonna buy the stocks thinking that its gonna go up and so on and so on.. when fundamentally the business model is kinda messed up when you think about it y'know? This is a bubble to me in my definition of it when people are investing into things without caring about things for the most part / logically I suppose...
If we have any disagreements, do let me know so that I can maybe lighten up on some other points as I love talking lol. I am loving it although I feel like I write realllly long sentences but hey, I am writing this to really explore why I believe the things the way I do and if you can convince me then sure, I can be wrong, I usually am.
Have a nice day and looking forward to your next comment!
They are not that high at all, at least nowhere near bubble territory according at least to the financial analysts I follow. A better metric than simply p/e is looking at forward p/e because the current price reflects their forward guidance.
> My conclusion is that A lot of people can't / couldn't invest into OpenAI / thus flowed their money into anything LLM / AI related in the markets... & the companies are loving this and mentioning AI as much as possible
I guess, but that in itself does not mean it is a bubble.
> I can agree if you think that these companies are investing into infrastructure but that infrastucture is now mostly GPU's which are only really useful for LLM related tasks and becomes redundant for general purpose stuff like running servers for the most part.
Recommendation algorithms run on GPUs, which is a huge part of any social network (like meta and tiktok). Like I said there is more than LLMs and those need to run on GPUs as well. They also provide a service to rent out GPUs to other companies to run their own models and make a very good business of it.
> when fundamentally the business model is kinda messed up when you think about it y'know?
You are alone in that opinion. These are some of the most profitable companies in history, which is why they make such a huge part of the S&P. You are talking about a feedback loop of investing, which is normal in any investment bull cycle. It can turn into a bubble and we may be at the start of one, but being an AI skeptic investor just means not participating and having poor returns. The future is uncertain and it sounds to me like you are looking for reasons not to invest.
These companies have sort of saturated their markets and thus joined into LLM etc. to try to catch the new shiny thing.
>You are alone in that opinion. These are some of the most profitable companies in history, which is why they make such a huge part of the S&P. You are talking about a feedback loop of investing, which is normal in any investment bull cycle. It can turn into a bubble and we may be at the start of one, but being an AI skeptic investor just means not participating and having poor returns. The future is uncertain and it sounds to me like you are looking for reasons not to invest.
Please try to change the word Ai in this sentence to crypto to see how relevant it might be :>
Also, this line kinda means "It may be a bubble but it pays right now" in the sense that you are basing your returns STILL on the fact of some predicted PE.
I am just saying that people shouldn't consider S&P 500 "safe enough" then I suppose due to this AI hype if there is even a sheer possiblity of bubble formation.
Higher profits generally mean higher risks and there is no free lunch. So S&P 500's higher profits does have a higher risk and people should know that risk before investing and my risk appetite doesn't support it and I am wondering how yours could.
Superior returns aren't easy and if someone's saying them without giving you the underlying reason ie. realized productivity gains in an underlying trade (think a house builder built a house which was productive to the family and they are gonna pay for it) (compare it to how messy AI is, and how we haven't really still discussed on why there is so much hype in the market when the economy is doing kinda bad)
> it sounds to me like you are looking for reasons not to invest.
Yes, I naturally took the discussion from this side in investing in S&P markets and It's wild how you think so when I really agreed to you on a lot of things and your last line sort of sums it except when you look at the true gravitas of the situation, there is almost very little uncertainty about that (so no need for maybe)
Sam Altman, CEO of OpenAI, has expressed concerns that the AI market may be experiencing a bubble, similar to the dot-com bubble of the late 1990s
This is my opinion too.
I was thinking of someone who wants to have a long time in the market as I think I said but time in the market beats the timing in teh market and so these "maybe" lines do frighten me. Do I want to mess around and find out if things are in a bubble with my money!? On a company which is massively enshittening itself in the names of AI (youtube auto dub comes to mind)
This was a good faith discussion and I appreciate it but I don't agree on how it means not participating in bubble-ish maybe activities means you aren't getting returns, its like saying that I am not getting returns on crypto because I am not participating... because the whole thing is bubblish & those returns aren't magical...
S&P should be considered a safe enough investment not something that is on the whims of a maybe, I suppose?
I really like your last line I must admit, and it can take both an AI skeptic (AI skeptic in the sense that the tech is cool but its not gonna generate much profit given the investment) and pro AI person...
> You are alone in this opinion ..
I;d genuinely love to know if that's the case and I really wish to create an Ask HN, linking to this discussion as I don't think that my take is unreasonable?
Do you have any way that I can contact ya tbh as I really find our discussion a bit fascinating and something that I agree on which sort of makes me believe even more that it might be a bubble yet at the same time, maybe its not thaaat harsh at the same time y'know. Like its partially a bubble, definitely something to be cautious but still
Would love to get a way to contact ya, msg me on my mail please, I have also added my signal information just for this in my hn bio i guess.
I'm no financial guru but this time around the boom/bust cycle, there's a new, additional factor that's concerning. Even though I sold my individual tech company shares a few years ago and diversified all my equity holdings in broad market ETFs like VTI, the so-called "Magnificent 7" tech companies have inflated so much, they now occupy a disproportionate percentage of even broad market ETFs which hold ~5,000 stocks based on their market caps. The obvious issue being their share prices all having a significant component elevated by the same thing - unrealistic AI growth expectations.
Where do you think your 401K money is going...right into the S&P 500...and who gets the lion's share of allocation out of that? The Mag7 et al.
If you chart the last 25 years, Gold (yes, that one...the useless metal) has outperformed the S&P (and it's making new highs even today). What does that say about hard assets vs these companies?
Nice metaphor! Huge bubbles usually get a historical name like "Tulip Craze" or "Dot Com Crash" and when this bubble bursts "House of Cards" is a good candidate.
The biggest difference here though is that most of these moves seem to to involve direct investment and the movement of equity, not debt. I think this is an important distinction, because if things take a downturn debt is highly explosive (see GE during the GFC) whereas equity is not.
Not to say anyone wants to take a huge markdown on their equity, and there are real costs associated with designing, building, and powering GPUs which needs to be paid for, but Nvidia is also generating real revenue which likely covers that, I don't think they're funding much through debt? Tech tends to be very high margin so there's a lot of room to play if you're willing to just reduce your revenue (as opposed to taking on debt) in the short term.
Of course this means asset prices in the industry are going to get really tightly coupled, so if one starts to deflate it's likely that the market is going to wipe out a lot of value quickly and while there isn't an obvious debt bomb that will explode, I'm sure there's a landmine lying around somewhere...
Not as explosive as debt but I'd venture to say that nowadays equity is a lot more "inflamable" compared to 2008-2010, as in a lot more debt-like (which I think partly explains the current equity bubble in the US).
As in, there are lots and lots of investment funds/pension funds/other such like financial entities which are very heavily tied to the "performance" of equity, and I'm talking about trillions (at this point) of dollars, and if that equity were to get a, let's say, 20 or 30% hair-cut in a matter of two-three months (at most), then we'll for sure be back in October 2008 mode.
Just curious, can you detail how it would fail exactly?
It might not be the catastrophic cascading failure of the GFC, but someone somewhere in the pile will get exposed.
1. Selling equity (probably good).
2. Financed with actual profits over time showing up as lower margins on the income statement (probably good).
3. Issuing debt backed by their equity (possibly a dumpster fire).
would these equity investments only impact the balance-sheet as financial investments - why would they show up as lower margins on income statement ?
Nvidia makes money by selling to OpenAI. OpenAI makes money by selling a service to users that uses Nvidia. So Nvidia invests in the build out and expansion of the infrastructure that will use Nvidia.
This is a classic positive sum loop.
It's not that different than a company reinvesting revenue in growing the company.
Of course the strategy of taking a loss and reinvesting - but I don't see how OpenAI is making enough money to pay for all this, now or in the future.
That's literally hundreds of billions worth of revenue.
Just look at the options OpenAI has to generate revenue beyond subscriptions.
Given the amount of money invested and the expectations, the crash will be of cataclysmic proportions
Nvidia is transforming into a venture GPU company. X GPUs for Y percent.
It's like selling steel by the average fractional number of mining deaths that went into producing it. Sure, at a given moment there will be some ratio between average deaths and steel, but that's a number that you want to be as low as possible.
It's just a different abstraction level.
More degenerate "privatizing of the profits, socializing the profits" behavior. American public continues to get bent by billionaires and continue to elect folks that will gladly lube them up in preparation of that event.
The electric bills are getting out of hand.
If you're actually interested, the reason it's important to build out the grid even more instead of "subsidizing" is because the current grid can't handle renewables well which we need to improve if we want to use sustainable energy.
However at least AI is doing _something_ with the energy. Cryptocurrency is such a fucking useless waste of energy I'd take anything over it.
You essentially have Nvidia propping up its own valuation here by being its own customer. If they sold a bunch of H100's to themselves and then put it as revenue on their books they'd be accused of fraud. Doing it this way is only slightly better.
I think even Byrne Hobart would agree (from his interview with Ben): -- Bubbles are this weird financial phenomenon where asset prices move in a way that does not seem justified by economic fundamentals. A lot of money pours into some industry, a lot of stuff gets built, and usually too much of it gets built and a bunch of people lose their shirts and a lot of very smart, sophisticated people are involved with the beginning, a lot of those people are selling at the peak, and a lot of people who are buying at the peak are less smart, less sophisticated, but they’ve been kind of taken in by the vibe and they’re buying at the wrong time and they lose their shirts, and that’s really bad. --
This is a classic bubble. It starts, builds, and ends the same way. The technology is valuable, but it gets overbought/overproduced. Still no telling when it may pop, but remember asset values across many categories are rich right now and this could hurt.
Seriously, is there anyone in the media keeping unbiased tabs on how much we're spending on summarizing emails and making creatives starve a little more?
What is a credible indication? Who is credible? Its all subjective. Its possible to fool yourself endlessly when financial incentives are involved. The banks did it with mortgages.
If you add up all of the contracts that OpenAI is signing, it's buying something like $1 trillion/year worth of compute. To merely break even, it would have to make more money than literally every other company on the planet, fairly close to twice the current highest revenue company (Walmart, a retailer, which, yeah, there's a reason that has high revenue).
But no, let's build us a slightly better code generator.
Strange times we live in...
Solar does compete economically with methane already, and it's only going to improve even more.
Firstly, there is no such thing as an infinitely scaling system.
Secondly, because power transmission isn't moving freight. The infrastructure to move electricity long distances is extremely complicated. Even moving past basic challenges like transmission line resistance and voltage drop, power grids have to be synchronized in both phase and frequency. Phase instability is a real problem for transmission within hundreds of miles, let alone thousands upon thousands.
Also that infrastructure is quite a bit more expensive to build than rail or even roads, and it's very maintenance hungry. An express built piece of power transmission that goes direct from a desert solar farm to one of the coasts is just fragile centralization. You have a long chain of high-maintenance infrastructure, a single point of failure makes the whole thing useless. So instead you go through the national grid, and end up with nothing, because all of that power is getting sucked up by everyone between you and the solar farm. It probably doesn't even make it out of the state it's being generated in.
BTW the vast majority of the cost of electricity is in the infrastructure, not its generation. Even a nuclear reactor is cheap compared to a large grid. New York city's collection of transmission lines, transformers, etc. (not even any energy generation infrastructure, just transmission) ballparks a couple hundred billion dollars. Maintenance is complex and extremely dangerous, which means the labor is $$$$. That's what you're paying for. That's why as we continue to move towards renewables price/watt will continue to go up, even though we're not paying for the expensive fuel anymore. The actual ~$60 million worth of fuel an average natural gas plant burns in a year pales in comparison to the billions a city spends making sure the electrons are happy.
If the coast-to-coast railways hadn't been built in the past, I don't think the US could build them today. There are too many parties who can now block big projects altogether or force the project to spend another 18 months proving that it should be allowed to move forward.
67% of new grid capacity in the US was solar in 2024 (a further 18% was batteries, 9% wind, and 6% for everything else). In the first half of 2025 that dropped to 56% solar, 26% batteries, 10% wind, and 8% everything else (gas). Source for numbers: https://seia.org/research-resources/solar-market-insight-rep...