Are OpenAI and Anthropic losing money on inference?

Exactly. All of the claims that OpenAI is losing money on every request are wrong. OpenAI hasn’t even unlocked all of their possible revenue opportunities from the free tier such as ads (like Google search), affiliate links, and other services.

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.

Because Sam Altman said so?

Sam Altman also said this:

https://xcancel.com/sama/status/1876104315296968813

There is a six month gap between those statements. Inference costs have been plummeting, plans have had tweaked quotas, and usage patterns can change.

No, the argument is that Uber was going to lose money hand over fist until all of the alternatives were starved to death, then raise prices infinitely.

As someone who has been taking the largest part of Google and facebooks ad wallet share away, Let me tell you something.

Advertising is now a very very locked in market and will take over a decade to shift even a significant minority it into OpenAIs hands. This is not likely the first or even second monetization strategy imo.

But I’m happy to be wrong.

> As someone who has been taking the largest part of Google and facebooks ad wallet share away

Can you elaborate? You’ve sparked my curiosity.

Taxis sucked. Any disruptor who was willing to just... Tell people what the cost would be ahead of time without scamming them, and show up when they said they would, was going to win.

Uber (and Lyft) didn't starve the alternatives: they were already severely malnourished. Also, they found a loophole to get around the medallion system in several cities, which taxi owners used in an incredibly anticompetitive fashion to prevent new competition.

Just because Uber used a shitty business practice to deliver the killing blow doesn't mean their competition were undeserving of the loss, or that the traditional taxis weren't without a lot of shady practices.

So inference is cheap but training is expensive and getting more expensive. It seems like if they can't get training expenses down, cheap inference won't matter.

There are two companies gaining significant wallet share: Amazon and TikTok. Of those only one is taking a significant early share of both Google and Facebook.

OK, but you are a person, not a company. "You" are not taking the share away.

No. Training itself isn't that expensive compared to inference. The real expense is salary for talent.

If they're profitable, why on earth are they seeking crazy amounts of investment month after month? It seems like they'll raise 10 billion one month, and then immediately turn around and raise another 10 billion a month or two after that. If it's for training, it seems like a waste of money since GPT-5 doesn't seem like it's that much of an improvement.

"I'm digging a trench"

"No you're not, WE are digging a trench!"

Yes fine, but "I am as well".

Sheesh. Also I, personally, do and lead the work of taking the wallet share. So I will stick with "I" and would accept any of my team saying the same.

Well, at least your attitude has made it obvious who you work for now. ;)

Spoiler alert: in most of the world taxis are still there and at best Uber is just another app you can use to call them.

And lifetime profits for Uber are still at best break even which means that unless you timed the market perfectly, Uber probably lost you money as a shareholder.

Uber is just distorted in valuation by its presence in big US metro areas (which basically have no realistic transportation alternative).