Those developer quotes are tough to read. Rate limits are going to hit like a truck when the labs eventually need to make a profit.
They'd have to get the Chinese AI labs to go along with that price fixing too.
I don't pretend to have detailed domain knowledge here, I may have seen other people's GenAI output rather than reality*, but the numbers people are throwing around for this stuff sum to trillions of USD, slightly higher than other (same caveat, perhaps also GenAI output*) claims I've seen about the total supply of money in the global venture capital markets.
* I miss the days when I could make a decent guess as to which websites were reliable and which were BS
They are spending that money training ever-larger models, so they are cashflow negative, but under almost any sane GAAP treatment that does not allow one to write down all R&D upfront (capital costs of model training), they are profitable.
Should this matter to you? Only if you're making financial decisions that assume that somehow one day the "jig will be up" - i.e. please don't short these stocks when they float, or at least do so very judiciously.
Even if they quit trying to make better models today, there are a mountain of recurring costs that will never go away. Retraining the models with new data, replacing/upgrading old hardware, enormous infrastructure costs related to maintaining the actual platforms, data collection costs, payroll...
I'm not aware of a single player in the LLM space actually turning a profit, even if they're only providing inference.
Even if the bubble burst while I was writing this comment, even if every single current LLM provider goes the way of pets.com, AltaVista, and GeoCities, that can all happen without ending vibe coding.
Listen carefully to Dario’s public statements; you could just pull his most recent Dwarkesh interview for example - worth a listen in any event.
He is guilty of an engineer’s use of the word profit when he says “we never made a profit.” But he always follows up with the real story — “every model we trained has returned 2-4x in free cashflow, counting R&D and inference”
You could say “the industry is engaged in possibly ruinous competition training ever-larger models and sucking cash to do so, and in fact if anyone stops, they’ll lose forever” and those statements might be true, but to be clear the fact that these companies are posting a loss right now is a FEATURE of how R&D works, one that lets them spend more on a race. It’s not tied to the sort of financial reality accrual accounting is designed to talk about.
https://www.wheresyoured.at/costs/#how-much-did-anthropic-an...