We are in geopolitically fraught times. Money alone is not capital.
We have been living in an era where financial capital has dominated.
We are entering an era where computing capital, intellectual capital, and military capital will dominate.
The people in control of those when the game changes are the ones writing the rules.
These are bullshit terms. Capital is capital. Military production, IP production and yes, AIs running in datacentres and on the grid, are all subject to economic forces. (Folks argued railroads were a different form of capital in the 19th century, too. And fibre optics. And tulips. And dot-com companies. And computer-assembled American mortgage instruments.)
We might be investing for a golden future. We might be the Soviet Union baited into unsustainable spending commitments. The answer to these questions isn't in pretending this time is different, or that economics can be suspended when it comes to certain questions of production and return.
yes, true, but it would probably be better to pour money into shipyards than data centers
I suspect that this revenue number is a vast underestimation, even today, ignoring the reality of untapped revenue streams like ChatGPT's 800M advertising eyeballs.
1. Google has stated that Gemini is processing 1.3 quadrillion tokens per month. Its hard to convert this into raw revenue; its spread across different models, much of it is likely internal usage, or usage more tied to a workspace subscription rather than per-token API billing. But to give a sense of this scale, this is what that annualized revenue looks like priced at per-token API pricing for their different models, assuming a 50/50 input/output: Gemini 2.5 Flash Lite: ~$9B/year, Gemini 2.5 Flash: ~$22.8B/year, Gemini 2.5 Pro: ~$110B/year.
2. ChatGPT has 800M weekly active users. If 10% of these users are on the paid plan, this is $19.2B/year. Adjust this value depending on what percentage of users you believe pay for ChatGPT. Sam has announced that they're processing 6B API tokens per minute, which, again depending on the model, puts their annualized API revenue between $1B-$31B.
3. Anthropic has directly stated that their annualized revenue, as of August, was $5B [2]. Given their growth, and the success of Claude 4.5, its likely this number is more around $6B-$7B right now.
So, just with these three companies, which are the three biggest involved in infrastructure rollouts, we're likely somewhere in the realm of ~$30B/year? Very fuzzy and hard, but at the very least I think its weird to guess that the number is closer to like $12B. Its possible the article is basing its estimates on numbers from earlier in 2025, but to be frank: If you're not refreshing your knowledge on this stuff every week, you're out of date. Its moving so fast.
[1] https://www.reddit.com/r/Bard/comments/1o3ex1v/gemini_is_pro...
[2] https://www.anthropic.com/news/anthropic-raises-series-f-at-...
Respectfully, the idea of sticking ads in LLMs is just copium. It's never going to work.
LLMs' unfixable inclination for hallucinations makes this an infinite lawsuit machine. Either the regulators will tear OpenAI to shreds over it, or the advertisers seeing their trademarks hijacked by scammers will do it in their stead. LLMs just cannot be controlled enough for this idea to make sense, even with RAG.
And if we step away from the idea of putting ads in the LLM response, we're left with "stick a banner ad on chatgpt dot com". The exact same scheme as the Dotcom Bubble. Worked real well that time, I hear. "Stick a banner ad on it" was a shit idea in 2000. It's not going to bail out AI in 2025.
The original content that LLMs paraphrase is itself struggling to support itself on ads. The idea that you can steal all those impressions through a service that is orders and orders of magnitude more expensive and somehow turn a profit on those very same ads is ludicrous.
OpenAI announced a few months ago that it had finally cracked $1B in monthly revenue (intriguingly, it did so twice, which makes me wonder how much fibbing there is in these statements).
I'll also say this: the fact that AI companies prefer to tout their usage numbers rather than their revenue numbers is a sign that their revenue numbers isn't stellar (especially given that several of the Big Tech companies have stopped reporting AI revenue as separate call-outs).
I believe this is incorrect; as far as I've heard, an anonymous source leaked that OpenAI had hit $12B in annualized revenue a few months ago [1]. I do not personally put any weight in leaks, and prefer to operate on data that has been officially announced.
[1] https://www.reuters.com/business/openai-hits-12-billion-annu...
[1] https://www.reuters.com/technology/openais-first-half-revenu...
Its all about citation. Everyone who read my numerology estimations above knew that they were estimations. You, on the other hand, lied about two different leaks of OpenAI's revenue numbers as being "official".
I wouldn't believe it if you told me even 1% of those users are paying. 10% is simply ridiculous.
So if the idea is to unseat Google, and make LLMs that are monetized by ads -- well that would be a lot of revenue!
The problem is obviously that Google knows this, and they made huge investments in AI before anyone else
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I guess someone wants to do to Google what Apple did to Microsoft in the mobile era -- take over the operating system that matters by building something new (mobile), not by directly trying to unseat Microsoft
The problem seems to be that no one has figured out what the network effect in LLMs is. Google has a few network effects, but the bidder / ad buyer network is very strong -- they can afford to pay out a bigger rev share than anybody else
Google also had very few competitors early on -- Yahoo was the most credible competitor for a long time. And employees didn't leave to start competitors. Whereas OpenAI has splintered into 5 or more companies, fairly early in its life
[1] at least according to the Acquired podcast, which is reputable
edit: oops, it was profit, not revenue
https://www.acquired.fm/episodes/google
Google with this business model makes more profits than any other company, ergo tautologically, is the most magical business model ever discovered.
By yearly revenue, the highest revenue company is Walmart, followed by Amazon, which make somewhere near twice the revenue of Alphabet (around 11th place, per https://en.wikipedia.org/wiki/List_of_largest_companies_by_r...). Especially if you account the inflation, the total lifetime revenues of the major oil companies will easily dwarf Google.
Google is nowhere close to earning the most revenue of any business ever.
OP said revenue, not profit. And neither of those numbers are relevant to Google, which runs a 32% (28%) operating (net) margin [1].
That said, yes, Google is the most profitable company in the world [2]. But its $116bn is not in a different league from Microsoft's $102bn, Apple's $99bn or Saudi Aramco's $96bn.
[1] https://s206.q4cdn.com/479360582/files/doc_financials/2025/q...
Neither revenue nor profit is the full story, though.
Accrual accounting gives lots of room for revenue-recognition fuckery [1].
[1] https://www.investopedia.com/terms/r/revenuerecognition.asp
Of course, even you go by most profit, Saudi Aramco still has Google beat, because it turns out that being able to charge highest market price for oil that costs you $5/barrel to make and being around for decades gives you an astounding lifetime net profit.
Google is very large, and I’m sure Acquired framed the statement is such a way that it’s true, but this statement as you presented it is false.
Other publicly traded companies have reported more lifetime revenue. Other product categories besides internet search have generated more revenue.
At the very least, the exact same network effects with respect to advertising that search has. The vast majority of frequent ChatGPT users I know mostly use it like a search engine.
That said, those network effects will be massive. Ads in LLMs are going to be unprecedentedly lucrative, irrespective of the platform. Google/Meta currently charge so much for ads because they have such enormous proprietary profiles on users based on their search/communication history that they can offer advertisers the ability to target users with extraordinary granularity. But at the end of the day, the ad itself is static and obviously an ad. LLMs will make these ads dynamic and insidious, subtly injected into chats in the way a real-life conversation might happen to discuss products. LLMs will become the ultimate word-of-mouth advertisers, the final form of astroturfing.
As people pointed, this is wrong.
But anyway, Google's revenue last year was enough to satisfy the smallest point of the interval the article points out. And barely so.
So if everything goes perfectly for the next 5 years capital-wise, and AI manages to capture Google's revenue, at the most optimist conditions, they will be able to break even with depreciation.
Honestly, that is better than what I was expecting. But it completely different from the picture you will see in any media.
Companies like Uber and Amazon operated at a loss, true. But they had an actual product. And they didn't come close to the money Google, Meta, OpenAI and Microsoft are losing.
That about sums it up.
I don’t know if it’s that surreal or unexpected. There’s a reason “The Emperors Clothes” is such a classic, enduring, fable. It’s happened before. It’ll happen again.
Not shading the article. All good points, just was surprised the author threw this bit in.
Buy more tulips.
Railroads and fibre are better examples. Tulips are actually fucking useless as a productive asset. Railroads, fibre-optic cables, power production and datacentres are not.
That's called a "bubble". Obviously, this time it is different until it isn't.
I own several books of trig and other tables, three slide rules and a couple of calculators, a working Commodore 64 and an IT consultancy company.
We are fiddling with LLMs as yet another tool. We are getting some great results but not earth shattering.
Tulips are very pretty flowers. I have several dozen in my garden. I have some plants that are way more valuable than tulips in my garden too.
Oh, AI.
It is artificial but it is not intelligent. A LLM (int al) is a marvelous thing. I find sheer joy in conversing with a "gpt-oss-20b F16" that runs on a £600 GPU and a slack handful of CPU and RAM because so little gives so much.
They think they are building an AI god.
If you think of it in religious terms it suddenly makes sense. Expected rate of return? One scenario has has infinite expected return (some kind of pascals wager/mugging)!
Of course there will be no AGI. Just a planet we'll have to live on where those deluded idiots wasted our resources on some boondoggle. Maybe this kind of concentration of power is a bad thing? I think we are going to get to those kind of questions once the party is over.
The people investing in AI companies (and the big players spending in AI) are seeking Artificial General Intelligence (AGI). It's the only way they get a return on their capital.
They are investing so they can get there first. Money basically becomes meaningless at that point, whoever owns the AGI owns the world. That's the only way to get a return on that investment.
Then why fuck around with ads?
How would you test the hypothesis that they're running these like regular businsses versus on a crusade?
I'm just giving the view from an investors point of view -- you don't expect these to eventually run like a normal business where their revenue exceeds their cost. You expect them to make as much revenue as they can while they spend more than the make to get to AGI.
We are not seeing that (currently) with GPUs. Perf/watt has basically completely stalled out recently while tokens per user has easily increased in many use cases has went up 100x+ (take Claude code usage vs normal chat usage). It's very very unlikely we will get breakthroughs in compute efficiency in the same way we did in the late 90s/2000s for fiber optic capacity.
Secondly, I'm not convinced the capex has increased that much. From some brief research the major tech firms (hyperscalers + meta) were spending something like $10-15bn a month in capex in 2019. Now if we assume that spend has all been rebadged AI, and adjust for inflation it's a big ramp but not quite as big as it seems, especially when you consider construction inflation has been horrendous virtually everywhere post covid.
What I really think is going on is some sort of prisoners dilemma with capex. If you don't build then you are at serious risk of shortages assuming demand does continue in even the short and medium term. This then potentially means you start churning major non AI workloads along with the AI work from eg AWS. So everyone is booking up all the capacity they can get, and let's keep in mind a small fraction of these giant trillion dollar numbers being thrown around from especially OpenAI are actually hard commitments.
To be honest if it wasn't for Claude code I would be extremely skeptical of the demand story but given I now get through millions of tokens a day, if even a small percentage of knowledge workers globally adopt similar tooling it's sort of a given we are in for a very large shortage of compute. I'm sure there will be various market corrections along the way, but I do think we are going to require a shedload more data centres.
A few thoughts:
1. The comparison to previous tech bubbles is apt - we're seeing massive capex without clear paths to profitability for many use cases.
2. The "build it and they will come" mentality might work for foundational models, but the application layer needs more concrete business cases.
3. Enterprise adoption is happening, but at a much slower pace than the investment would suggest. Most companies are still in pilot phases.
4. The real value might come from productivity gains rather than direct revenue - harder to measure but potentially more impactful long-term.
What's your take on which AI applications will actually generate enough value to justify the current spending levels?
At least for gaming, GPU performance per dollar has gotten a lot better in the last decade. It hasn't gotten much better in the past couple of years specifically, but I assume a lot of that is due to the increased demand for AI use driving up the price for consumers.
Why wouldn't Moore's Law continue?
Also ads only make sense for the use case of direct chatting with a user, any type of automation (the big promise of AI) ads don't matter.
Imagine at the start of the electrification era people went "We'd need to build loads of cables and power plants and stuff that's expensive, lets just stick to steam power".
It's not a bet on this making sense via pedestrian business economics but rather that it'll be a game changer.
...whether that pans out is a technological and societal question, not an economic one in my mind
False dichotomy. There are literally infinite options between ignoring AI and spending a quarter of a trillion on it annually.
Fibre and railroads, again, are really good comparisons. Both involved busineasses built on advancing technology. If you built your network before signalling, your costs were immediately higher than a competitor who rolled out more slowly. Similarly, do we really think Nvidia has had its last say in GPUs?
gyomu•1h ago
1) the labor angle: it’s been stated plainly by many execs that the goal is to replace double percent digits of their workforce with AI of some sort. Human wages being what they are, the savings there are meaningful and seemingly worth the gamble.
2) the military angle: the future of warfare seems to be autonomous weapons/vehicles of all sorts. Given the winner takes all nature of warfare, any edge you can get there is worth it. If not investing enough in AI means the US gets steamrolled by China in the Pacific (and other countries getting steamrolled by whomever China wants to sell/lend its tech to), then it seems to justify most any investment, no matter how ridiculous the current returns seem.
Analemma_•1h ago
Even if we grant that this is possible, have any of these execs actually thought through what happens when their competitors also replace large chunks of their workforce with AI and then begin undercutting them on price? The idea that "our prices will stay exactly the same, but our salary costs will go to zero and become pure profit instead!" is delusional even if AI can actually replace large numbers of people, which itself is quite doubtful.
nothercastle•1h ago
JumpCrisscross•1h ago
Has anyone said this?
The point is such a shift would transfer spending from labour to these AI companies. That satisfies their investors' thesis requirement.
bitmasher9•53m ago
JumpCrisscross•45m ago
You're describing elasticity. None of this is particularly novel. If there is sufficient demand, the thesis is met: returns may not be astronomical, but they'll be positive for at least some of the major players. (Those with the most efficient operations or ability to command a price premium.)
the_bear•27m ago
Unless you're a monopoly, I don't see how AI will lead to these massive cost savings everyone is hoping for.
nothercastle•1h ago
aswanson•38m ago
MontyCarloHall•28m ago
marcosdumay•25m ago
If those companies replace a low 2-digits percentages of the developers, and capture their entire salary, it's still not enough to reach the depreciation numbers on the article.
On 2, that could justify it... Except that we are talking about fucking LLMs. What do anybody expect LLMs to do in a war that will completely obliterate some country?