181–190 of 425 posts
Almost 6 bln in sales in marketing? It looks an enormous amount given that they used to have the best models and used to give-aways tokens.
6bn seems excessive but despite GPT 5.5 arguably being better than Claude I don't see a lot of adoption of Codex yet. Some of my coworkers even use Sonnet (the default in Claude Code for the 20 USD subscription) and see no reason to change even though that model is definitely "outdated" compared to current SOTA.
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I’d easily pay multiple hundreds. Possibly a thousand a month. If I were really forced to. LLMs provide me about the same value as a car does.
Paying a thousand a month for a car is also very stupid.
I'm really curious about something: how far will you go to support AI? Clearly they'll need to monetize things further, would you still use [whatever AI you are paying for] if the price was doubled? Tripled? Where would you stop and would you stop using AI altogether or would you look at competitors?
I spend 30 - 60 bucks a year with Horizon Labs.
I spend 25 bucks a month on Cursor. Cursor replaced an OpenAI sub.
Both support hobby projects. If either cost increased I would spend some time testing local alternatives and probably drop them.
Horizon Labs especially, I know that they have been matched by open models and are mostly a convenience at this point.
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Yes if you ignore all the reasons why they’re horribly unprofitable, they’re profitable. R&D costs are hurting profit side and while you can cut that one just becomes irrelevant overnight in this space if you do, hence the problem.
> R&D costs are hurting profit That’s quite the hot take, considering it’s literally an R&D company that got to where it is by doing R&D.
”The company reports over 900 million weekly active users of ChatGPT, though only about 50 million of those are paid subscribers.” With so many free models available the ai companies are going to struggle to convert active free users to paid.
I think that AI is going to become just another utility people pay to stay relevant. Same as their internet, electricity or gas.
Napkin maths. Alphabet: ~$4.5T value / ~$403B revenue ≈ 11× revenue Microsoft: ~$2.9T value / ~$282B revenue ≈ 10× revenue OpenAI: ~$850B value / ~$13B revenue ≈ 65× revenue Can someone explains that logic?
Should these companies be valued the same?
My takeaway from this is that it's incredibly validating as a business model. Inference is _highly_ profitable. Of course, like any company that has ever tried to grow at breakneck pace, you run at a loss until you "win."
The problem is you can't just separate training costs from inference costs. If OpenAI just didn't train a new model for the next five years, sure, they'd do OK. Assuming all those dirt cheap Chinese models nipping at their heels don't make up the gap while OpenAI is resting on their laurels.
Without being a frontier model (read: continuous, incredibly expensive training), they effectively don't have much to sell. So inference and training costs are intertwined to some extent.