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From https://www.theverge.com/command-line-newsletter/759897/sam-... , Sam Altman said: > “If we didn’t pay for training, we’d be a very profitable company.”
From https://www.theverge.com/command-line-newsletter/759897/sam-... , Sam Altman said: > “If we didn’t pay for training, we’d be a very profitable company.”
They have a service which understands a users question/needs 100x better than a traditional Google search does.
Once they tap into that for PPC/paid ads, their profit/query should jump into the green. In fact, there's a decent chance a lot of these models will go 100% free once that PPC pipeline is implemented and shown to be profitable.
From https://www.theverge.com/command-line-newsletter/759897/sam-... , Sam Altman said: > “If we didn’t pay for training, we’d be a very profitable company.”
There’s also a lot of comments in this thread who want LLM companies to fail for different reasons, so they’re projecting that wish on to imagined unit economics.
I’m having flashbacks to all of the conversations about Uber and claims that it was going to collapse as soon as the investment money ran out. Then Uber gradually transitioned to profitability and the critics moved to using the same shtick on AI companies.
These articles (of which there are many) all make the same basic accounting mistakes. You have to include all the costs associated with the model, not just inference compute. This article is like saying an apartment complex isn’t “losing money” because the monthly rents cover operating costs but ignoring the cost of the building. Most real estate developments go bust because the developers can’t pay the mortgage paym…
> if you have healthy positive cash flow you have much better mechanisms available to fund capital investment other than selling shares. Eg issue a bond against that healthy cash flow. Is that actually true in 2025? Presumably you have to make coupon payments on a bond(?), but shares are free. Companies like Meta have shown you can issue shares that don't come with voting rights and people will buy them, and meme sto…
These companies are behaving the same way. Folks are willing to throw endless money into the present pit so on the one hand I can’t blame them for taking it.
Reality is though that when the hype wears off it’s only throwing more gasoline on the fire and building a bigger pool of investors that’s will become increasingly desperate to salvage returns. History says time and time again that story doesn’t end well and that’s why the voices mumbling “bubble” under their breath are getting louder every day.
Earlier quoted context omitted.
Unit economics needs to include the cost of the thing being sold, not just the direct cost of selling it. Unit economics is mostly a manufacturing concept and the only reason it looks OK here is because of not really factoring in the cost of building the thing into the cost of the thing. Someone might say I don’t understand “unit economics” but I’d simply argue applying a unit economics argument saying it’s good with…
There is no marginal cost for training, just like there's no marginal cost for software. This is why you don't generally use unit economics for analyzing software company breakeven.
Compare the cost of tweeting to the cost of submitting a question to ChatGPT. The fact that ChatGPT rate limits (and now sells additional credits to keep using it after you hit the limit) indicates there are serious unit economic considerations.
We can't think of OpenAI/Anthropic as software businesses. At least from a financial perspective, it's more similar to a company selling compute (e.g. AWS) than a company selling software (e.g. Twitter/X).
Earlier quoted context omitted.
But what about running Deepseek R1 or (insert other open weights model here)? There is no training cost for that.
1. Someone is still paying for that cost. 2. “Open source” is great but then it’s just a commodity. It would be very hard to build a sustainable business purely on the back of commoditized models. Adding a feature to an actual product that does something else though? Sure.
These articles (of which there are many) all make the same basic accounting mistakes. You have to include all the costs associated with the model, not just inference compute. This article is like saying an apartment complex isn’t “losing money” because the monthly rents cover operating costs but ignoring the cost of the building. Most real estate developments go bust because the developers can’t pay the mortgage paym…
Think of the model as an investment.
These numbers are off. > $20/month ChatGPT Pro user: Heavy daily usage but token-limited ChatGPT Pro is $200/month and Sam Altman already admitted that OpenAI is losing money from Pro subscriptions in January 2025: "insane thing: we are currently losing money on openai pro subscriptions! people use it much more than we expected." - Sam Altman, January 6, 2025 https://xcancel.com/sama/status/1876104315296968813
With the heat turning up on AI companies to explain how they will land on a viable business model some of this is starting to look like WeWork’s “Community Adjusted EBITA” arguments of “hey if you ignore where we’re losing money, we’re not losing money!” that they made right before imploding. I think most folks understand that pure inference in a vacuum is likely cash flow positive, but that’s not why folks are askin…
A fast growing venture backed startup doing frontier R&D should be losing money overall. If they weren’t losing money, they wouldn’t be spending enough on R&D. This isn’t some gotcha. It’s what the investors want right now.
WeWork’s investors didn’t want them to focus on business fundamentals either and kept pumping money elsewhere. That didn’t turn out so well.