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troupo 6 hours ago

And that is revenue only. In the past 15 or so years most US companies (and especially startups) always talk about revenue only. Wheras only profit should matter.

E.g. what good is 20 billion per year when "OpenAI is targeting roughly $600 billion in total compute spending through 2030". That is $150 billion per year?

muzani 5 hours ago | parent | next [-]

The startup game is about building assets and then cashing out on them during exit.

Assets are harder to measure. Facebook used to say something silly like every user was worth $100. That sounded ridiculous for a completely free app but over a decade later, the company is worth more than that. Revenue is an easier way of measuring assets than profit.

Profit doesn't really matter. It gets taxed. But it's not about dodging taxes; it's because sitting on a pile of money is inefficient. They can hire people. They can buy hardware. They can give discounts to users with high CLTV. They can acquire instead of building. It's healthy to have profit close to $0, if not slightly negative. If revenues fall or costs increase, they can make up for the difference by just firing people or cutting unprofitable projects.

Also when they're raising money, it makes absolutely no sense to be profitable. If they were profitable, why would they raise money? Just use the profits.

aurareturn 6 hours ago | parent | prev | next [-]

It's not as much as you think. Google is spending $185b on data centers this year alone. Amazon is spending $200b this year. Total capex for big tech is ~$700b in 2026 and we're not including neo clouds, Chinese clouds, and other sovereign data centers.

Since everyone is trying to get compute from anywhere they can, including OpenAI going to Google, it's hard to tell what is used internally vs externally.

For example, it's entirely possible that Google's internal roadmap for Gemini sees it using $600b of compute through 2030 as well. In that case, OpenAI needs to match since compute is revenue.

pier25 6 hours ago | parent | prev | next [-]

Give me a billion and I'll have 500M of revenue in no time by selling dollars at 50 cents.

aurareturn 6 hours ago | parent [-]

Why are we treating OpenAI and Anthropic differently than say, Amazon or Uber? Both companies invested in growth for many years before making a profit. Most tech companies in the last 2-3 decades lost money for years before making a profit.

Why are we saying that OpenAI and Anthropic can't do the same?

hirako2000 6 hours ago | parent | next [-]

Two reasons. They somewhat broke even, and kept getting investment. The potential for quasi monopoly was obvious.

Openai can't claim either.

aurareturn 5 hours ago | parent | next [-]

How did Uber somewhat break even? They lost $34b before making a profit.

Uber was only on a path to monopoly in the US, not world wide. It’s lost to local competitors in most countries. And it can get disrupted by self driving cars soon.

OpenAI’s SOTA LLM training smells like a natural monopoly or duopoly to me. The cost to train the smartest models keep increasing. Most competitors will bow out as they do not have the revenue to keep competing. You can already see this with a few labs looking for a niche instead of competing head on with Anthropic and OpenAI.

vlovich123 5 hours ago | parent [-]

The cost of copying SOTA models though is super cheap and doesn’t take super long.

aurareturn 5 hours ago | parent [-]

How do you distill when OpenAI and Anthropic inevitably move to tasks running in the cloud? IE. Go buy this extremely hard to get concert ticket for me.

Distilling might only be effective in the chat bot dominant era. We are about to move to an agents era.

Furthermore, I’m guessing distilling will get harder and harder. Claude Code leak shows some primitive anti distilling methods already. There’s research showing that models know when it’s being benchmarked. Who’s to say Anthropic and OpenAI aren’t able to detect when their models are being distilled?

outside1234 5 hours ago | parent | prev [-]

Worse, Google can afford to outspend them in this game and basically run them both out of money.

6 hours ago | parent | prev | next [-]
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pier25 5 hours ago | parent | prev | next [-]

It's not even remotely comparable. Uber burnt some $30B over a decade or so.

6 hours ago | parent | prev | next [-]
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Forgeties79 6 hours ago | parent | prev [-]

[dead]

Swizec 6 hours ago | parent | prev | next [-]

> Wheras only profit should matter

Profit is money you couldn’t figure out how to spend. During growth, you want positive operating margins with nominal profits. When the company/market matures, you want pure profits because shareholders like money. If you can find a way to invest those profits in new areas of growth, that’s better.

aurareturn 5 hours ago | parent [-]

Not sure why you’re downvoted.

Everyone wants to treat OpenAI like a car wash business where they need to make a profit almost immediately. I don’t know why people can’t understand that the industry is in a rapid growth stage and investing the money is more important than making a profit now. The profits will come later.

nl 5 hours ago | parent | prev | next [-]

What is the point - exactly - of profit?

Profit is money you can't find a use for to grow your business, so you give some of it to the government in the form of tax.

Also there is a big difference between operational expenses and capital expenses like building data centers.

I think OpenAI is being very aggressive on the growth vs conservative financial management spectrum but just saying "only profit should matter" is just wrong.

bandrami 2 hours ago | parent [-]

> What is the point - exactly - of profit?

It's what attracts capital investment, which businesses need

nl 13 minutes ago | parent [-]

OpenAI seems to do reasonably well at attracting capital investment without profits.

As did Amazon, Google, Meta etc etc.

bandrami 8 minutes ago | parent [-]

OpenAI is great at attracting people who say "yeah, sure, I'll give you capital at some point in the future" who then never actually give them the capital (or at least haven't yet).

merlindru 6 hours ago | parent | prev [-]

why should only profits matter? if i had a killer product today that i just need to sell tomorrow, wouldn't you still invest today knowing i'll probably only start to make money tomorrow (or perhaps next week)?

the expectation is that they'll eventually make money. they can't raise forever. only startups are not profitable for a few years. but most companies that have existed for a long while have been profitable

and since they're expected to make a LOT of money, everyone wants a piece of that future pie, pushing up the valuation and amount raised to admittedly somewhat delusional levels like here

bandrami 6 hours ago | parent | next [-]

> why should only profits matter?

In this case because it's not clear that anybody has actually figured out how to sell inference for more than it costs

nl 5 hours ago | parent [-]

It's well know everyone is making great money on inference. The cost is training.

Whether GPT-5 was profitable to run depends on which profit margin you’re talking about. If we subtract the cost of compute from revenue to calculate the gross margin (on an accounting basis),2 it seems to be about 30% — lower than the norm for software companies (where 60-80% is typical) but still higher than many industries.

(They go on to point out that there are other costs that might mean they didn't break even on other costs - although I suspect these costs should be partially amortized over the whole GPT 5.x series, not just 5.0)

https://epochai.substack.com/p/can-ai-companies-become-profi...

https://martinalderson.com/posts/are-openai-and-anthropic-re... (with math working backwards from GPU capacity)

"Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company"

https://simonwillison.net/2025/Aug/17/sam-altman/

"There’s a bright spot, however. OpenAI has gotten more efficient at serving paying users: Its compute margin—the revenue left after subtracting the cost of running AI models for those customers—was roughly 70% in October, an increase from about 52% at the end of last year and roughly 35% in January 2024."

https://archive.is/OqIny#selection-1279.0-1279.305 (Note this is after having to pay higher spot rates for compute because of higher than expected demand)

bandrami 4 hours ago | parent [-]

> It's well know everyone is making great money on inference.

That is not, in fact, "well known", but based entirely on the announcements of the inference providers themselves who also get very cagey when asked to show their work and at least look like they're soliciting a constant firehose of investment money simply to keep the lights on. In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.

nl 16 minutes ago | parent [-]

> based entirely on the announcements of the inference providers themselves who also get very cagey when asked to show their work

I mean sure, it's self reported.

But the inference prices somewhere like Fireworks or TogetherAI charges is comparable to what Google/AWS/Azure charge for the same model an we know they aren't losing money - they have public accounts that show it, eg:

https://au.finance.yahoo.com/news/wall-street-resets-amazon-...

Fireworks’ gross margin—gross profit as a percentage of revenue—is roughly 50%, according to the same person

https://archive.is/Y26lA#selection-1249.65-1249.173

> In particular there's a troubling tendency to call revenue "recurring" before it actually, you know, recurs.

If someone has a subscription then yes that is pretty normal.

Barrin92 6 hours ago | parent | prev [-]

not if your product is selling two dollars for one dollar and as soon as you'll start to charge more I'll switch to one of your twenty competitors

profit isn't a function of having a killer product, it's a function of having no competition

aurareturn 6 hours ago | parent | next [-]

And why do you think twenty competitors can stay competitive for years to come?

Industries always consolidate and winners emerge. SOTA LLMs look like a natural monopoly or duopoly to me because the cost to train the next model keeps going up such that it won't make sense for 20 competitors to compete at the very high end.

TSMC is a perfect example of this. Fab costs double every 4 years (Rock’s Law). It's almost impossible to compete against TSMC because no one has the customer base to generate enough revenue to build the next generation of fabs - except those who are propped up by governments such as Intel and Rapidus. Samsung is basically the SK government.

I don’t see how companies can catch OpenAI or Anthropic without the strong revenue growth.

outside1234 5 hours ago | parent | next [-]

Google has completely caught OpenAI. Anthropic has a better coding model, but I'm sure Google is working on that too.

komali2 2 hours ago | parent | prev | next [-]

The barrier to replicating TSMC isn't just cost, it's supply chain, geopolitics, and talent.

Only one company on Earth can make the UV lithography machines TSMC buys for their highest end fabs, and they're not selling to anyone else.

The PRC tried to brute force this supply chain backed by the full might of the Party's blank check, all red tape cut, literally the best possible duplication scenario, and they failed.

Barrin92 4 hours ago | parent | prev [-]

>Industries always consolidate and winners emerge.

no, most industries just sell boring generic products, a few industries favor monopolists. Semiconductors are one of them but LLMs are also as far removed from that business as is physically possible.

TSMC makes the most complicated machines humans have ever built, a LLM requires a few dozen nerds, a power plant, a few thousand lines of python and chips. That's why if you're Elon Musk you could buy all of the above and train yourself an LLM in a month.

LLMs are comically simple pieces of software, they're just big. But anyone with a billion dollars can have one, they're all going to be commoditized and free in due time, like search. Copying a lithography machine is difficult, copying software is easy. that's why Google burrowed itself into email, and browsers, and your phone's OS. Problem for openai is they don't have any of that, there's already half a dozen companies that, for 99% of people, do what they do.

ds2df 6 hours ago | parent | prev [-]

no competition is a bit extreme. Limited competition yes due to competitive advantages.