This could also be (at least partly) a reaction to Microsoft threatening to pull OpenAI's cloud credits last year. OpenAI wants to maintain independence and with compute accounting for 25–50% of their expenses (currently) [2], this strategy may actually be prudent.
[1] https://www.cnbc.com/2025/01/03/microsoft-expects-to-spend-8...
But to answer your question, no they aren’t even profitable by themselves.
Depends on your definition of profitability, They are not recovering R&D and training costs, but they (and MS) are recouping inference costs from user subscription and API revenue with a healthy operating margin.
Today they will not survive if they stop investing in R&D, but they do have to slow down at some point. It looks like they and other big players are betting on a moat they hope to build with the $100B DCs and ASICs that open weight models or others cannot compete with.
This will be either because training will be too expensive (few entities have the budget for $10B+ on training and no need to monetize it) and even those kind of models where available may be impossible to run inference with off the shelf GPUs, i.e. these models can only run on ASICS, which only large players will have access to[1].
In this scenario corporations will have to pay them the money for the best models, when that happens OpenAI can slow down R&D and become profitable with capex considered.
[1] This is natural progression in a compute bottle-necked sector, we saw a similar evolution from CPU to ASICS and GPU in the crypto few years ago. It is slightly distorted comparison due to the switch from PoW to PoS and intentional design for GPU for some coins, even then you needed DC scale operations in a cheap power location to be profitable.
If the frontier models generate huge revenue from big government and intelligence and corporate contracts, then I can see a dynamo kicking off with the business model. The missing link is probably that there need to be continual breakthroughs that massively increase the power of AI rather than it tapering off with diminishing returns for bigger training/inference capital outlay. Obviously, openAI is leveraging against that view as well.
Maybe the most important part is that all of these huge names are involved in the project to some degree. Well, they're all cross-linked in the entire AI enterprise, really, like OpenAI Microsoft, so once all the players give preference to each other, it sort of creates a moat in and of itself, unless foreign sovereign wealth funds start spinning up massive stargate initiatives as well.
We'll see. Europe has been behind the ball in tech developments like this historically, and China, although this might be a bit of a stretch to claim, does seem to be held back by their need for control and censorship when it comes to what these models can do. They want them to be focused tools that help society, but the American companies want much more, and they want power in their own hands and power in their user's hands. So much like the first round where American big tech took over the world, maybe it's prime to happen again as the AI industry continues to scale.
If you don't believe US has elections then straighten up your tinfoil hat:)
Maybe you'll say next the earth is flat, if you think people have nothing better to do but to find ways to lie to you.
I was explaining why it is more harmful and thought you were arguing it is not harmful?
Censorship in the west and china are both done by unelected people