These companies are unprofitable (as all companies at this stage and ambition should be) but I increasingly don't see any justification for the idea that it is fundamentally unprofitable.
Inference alone is certainly profitable. I'm running models at home that are comparable to performance of paid models a year or so ago for free. Even for much larger models the cost around inference serving are clearly manageable.
Training is where the costs are, but I'm increasingly convinced those too could have costs dramatically reduced if necessary. Chinese companies like Moonshot.ai are doing fantastic work training frontier models for a fraction of the cost we're seeing from Anthropic/OpenAI.
This isn't like Uber or Doordash where the economics fundamentally don't make sense (referring to the early days of these services where rates were very cheap).
It's a compelling story that "current AI is unsustainable", but it doesn't pan out in practice for a multitude of reasons (not the least of which is that we can always fall back to what models did last year for basically free).
And if you can run those strong models at home for free, why would hosting them be a successful business for any of these providers?
Profitable maybe, in terms of having low costs, but why pay Google or whoever when you can do it yourself for cheaper/"free"?
For free == with a huge upfront cost of getting a good enough box and running costs of maintaining it and just keeping it powered. By the time it pays off the frontier labs are three generations ahead at least.
Compare with on-demand billing per token and it just doesn’t make sense to own the hardware if you aren’t using it productively or renting it out for 95% of the time.
If you can run your server at home for free why would hosting it be a successful business for any of these propviders?
Arguably nothing even has to change with training for this to be sustainable. Dario has claimed that Anthropic is profitable on a per training run basis. They aren't profitable because they choose to keep investing in increasingly large training runs.
Cut the crap.
The value of the firm's operating assets = EBIT(1-t) - Reinvestment
You (Anthropic) want that sky-high valuation? Accept reinvestment is part of the equation.
If they decide to stop reinvesting, then they are as good as dead.
Moreover, they clearly are not re-investing cash flows from operations. Why do you think they are continually raising money? Lmao.
If it's profitable, why haven't they reported any profits? People like Ed Zitron have done the math and it just doesn't add up. I mean he just published this piece today: https://www.wheresyoured.at/ai-is-too-expensive/
Amazon was unprofitable for over a decade, and they were public. Theres no incentive to be profitable as a private company if you can continue to raise money.
Ed Zitron and Gary Marcus are... confused.
> Amazon was unprofitable for over a decade, and they were public.
Amazon was unprofitable because they poured their revenue into growth. On paper, they were in the red, but everyone - especially investors - saw what was going to happen, given their trajectory.
Is it the case that any of these AI companies are actually making a ton of money and growing accordingly? AFAICT, we've just got [a] big players like Google that can subsidize AI in the hopes of waiting everyone else out and [b] private companies raising capital in the hopes that when the market returns to rationality, they may be solvent.
> On paper, they were in the red, but everyone - especially investors - saw what was going to happen, given their trajectory.
As I recall, no, Wall Street and public shareholders were getting pretty antsy over AMZN earnings, which is why Bezos famously said "We are willing to be misunderstood for long periods of time."
The same thing is playing out today: insiders and early investors (presumably privy to information we don't have) see the trajectory of the frontier AI labs, but Wall Street and public shareholders see only the losses. This is why at every earnings report the hyperscalers simultaneously 1) post record revenues and earnings, 2) announce even greater CapEx spending and AI investments, and hence 3) get punished by the stock market.
Clearly all the AI players are willing to be misunderstood for long periods of time.
Yes that is exactly what is happening. OpenAI and Anthropic are the fastest growing companies by revenue ever and their gross profit margins are healthy.
According to this article[0]:
> HSBC Global Investment Research projects that OpenAI still won’t be profitable by 2030, even though its consumer base will grow by that point to comprise some 44% of the world’s adult population (up from 10% in 2025). Beyond that, it will need at least another $207 billion of compute to keep up with its growth plans.
This article is from six months ago. Was HSBC wrong; did something dramatically change in the last six months; is OpenAI not, in fact, profitable?, or are they in fact doing well but doing a huge investment (as was the case with Amazon 25ish years ago)?
I genuinely do not know, but my impression is that they're burning investment capital trying to compete with others' investment capital and Google's bottomless pockets.
[0] https://fortune.com/2025/11/26/is-openai-profitable-forecast...
Also OpenAI somehow having 44% of the world’s population as its customer base is a plainly absurd goal and will never happen, not in 5 years
and to make matters worse, they are massively over-valued.
Whoever buys the stock at a richly priced 1tn at ipo is a bozo lmao. I know I know, index funds will be forced to hold it bypassing the 1 year rule. Disaster already.
Then why do they constantly need more and more funding from VC and Google and MS and NVIDIA? Why is it all circular dealing? Why aren’t there smaller AI startups running these smaller, “profitable” models?
But I've been told here -- over and over again -- that the cost of inference was going to go down as the technology matured.
The trend lines are going in the opposite direction.
His entire brand is that the AI bubble will burst. By his account it was supposed to have several times by now. Like the doomers, it's not if it's when and they have to keep pushing back their predictions. Funny how both camps can be so confident. Alas, that's how they get eyes, ears and dollars.
That's not to say they will be or are wrong, it's just that they aren't exactly unbiased, or humble, sources.
Yeah, at this point I think the worst-case scenario for OpenAI/Anthropic/etc is to slow down frontier model development and focus on tooling and services, as opposed to imploding completely and bursting the economic bubble. I hope?