> OpenAI is profitable if they stop training their next generation models. Their unit economics are extremely favorable.

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...

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theptip 3 days ago | parent | next [-]

I agree the market dynamics are weird now, I disagree that says much about the existence of other equilibria.

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.

	▲	mgh95 3 days ago \| parent [-]
		> 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. 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.

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Workaccount2 4 days ago | parent | prev [-]

That's why we are seeing these insane numbers. The competition is "do or die" right now.

Zuckerberg said in an interview last week he doesn't mind spending $100B on AI, because not investing carries more risk.

	▲	mgh95 4 days ago \| parent [-]
		This only applies if you think one of two things; First, that it is guaranteed that this specific line of inquiry will lead to development of a form of superintelligence or otherwise broadly applicable development; or second, the form of machine learning technologies that unlocks or otherwise enables a market which would otherwise be inaccsesible that justifies this investment. To date, no evidence of either even exists. See Zuckerbergs recent live demo of Facebooks Ray Bans technology, for example.