https://www.axios.com/2026/04/26/ai-cost-human-workers Uber's chief technology officer already blew through his full 2026 AI budget due to token costs, according to The Information.
Lol. Lmao even
this post was submitted on 21 May 2026
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Yes, and let’s also not count all the investments in infrastructure because you know… like training and staff it’s not a real cost that’s essential to the business.
Anyways, you wouldn’t happened to have heard that from Anthropic or OpenAI?
Somehow we don’t have any actual indisputable numbers (I wonder why) but it is actually quite controversial and some of those who have done deep research on the subject are saying inference IS run at a loss and it might not get profitable ever.
https://www.ft.com/content/fce77ba4-6231-4920-9e99-693a6c38e7d5?syn-25a6b1a6=1
Those people disagree with me and what I want are therefore wrong
"Inference is not typically run at a loss"
Bro thats called cherry picking
Businesses work on cash in cash out
Right now AI companies make way less cash than they spend overall when you dont include investments
Furthermore, most people use a free version of AI and would stop using it if it cost them anything
Explain how to pivot to profit when the investments dry up, were all waiting
Do companies tend to use the free version too?
Do rhetorical questions add anything of value, beyond a gotcha moment, to the conversation?
It's not a rhetorical question or a "gotcha" moment. I'm simply asking you to clarify your point. Could AI companies survive on their subscription model alone if they increased their prices?
You know that wouldn't happen. Which AI company wants to be the one that says, "we're happy with where the model is at right now" and stops throwing cash into the boiler of the investor hype train and let their competitors exceed them in real or imagined metrics? Clearly firms like Anthropic have to rely on circus marketing tricks like "This model is too dangerous for the general public to see! Ooooh scary! Coming Soon!", and they can't do that without continuous training.
For you and I, the offline models aren't too bad for getting little side projects started, but for major AI firms, the ongoing training cost for the next model and the one after that has become ingrained into the operating model.