- cross-posted to:
- programmer_humor@programming.dev
- cross-posted to:
- programmer_humor@programming.dev
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
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Those same managers eleven seconds later when they get an ad for a new startup making the same obviously empty promises as the last startup:
They love those the most because they integrate them and then use it to justify a promotion or move so they can get out of Dodge before the inevitable explosion happens on the next guys watch. The next guy blames the previous guy and then repeats the process.
Yeah no shit. You get people dependent on your product, then Jack up the price
Corpo fell for the oldest corpo trick.
This feels predictable. AI is one of, if not the most invested in yet unprofitable industries in the history of humanity.
The last few years have been the beta and the tech demo. But that is not paying for itself yet. US companies are competing with (and falling behind) Chinese state-sponsored companies. OpenAI in particular, a company whose revenue doesn’t even cover half of their operating costs, has extended themselves into owing more than a TRILLION dollars to the entirety of big tech who are building chips and data centers on these IOUs, and will need to be paid sooner or later. The bills will come due.
Other corporations are already paying massive bills for licensing, tokens, training, and infrastructure changes to accommodate this shift to AI while laying off massove chunks of skilled workers on the idea that AI is cheap and will get cheaper over time. But that is simply not the case. This is the “first taste is free” part of this deal. Once they have companies deeply invested in AI and have destroyed the fabric of the labor economy in favor of it, that price is going to skyrocket because OF COURSE IT WILL.
Maybe at some point this will all level out. AI bubble will pop. Prices will sky rocket. Companies will try to backpedal, which will be slow and difficult, they’ll end up paying AI companies huge sums while they work to decouple themselves after just forming the bond, they’ll also end up paying stupid money to professionals who are suddenly in high demand, and many companies won’t survive the chaos. But the ones that do will settle into a new equilibrium.
AI will eventually get cheaper (but probably never this cheap again, at least not in the near future), and it will probably be a permanent fixture in our lives and work to some degree. But it’s usefulness and cost effectiveness will be limited in scope, with specialized purposes. It will not ultimately be the great labor replacement companies think/thought it would be, even as stupid and short sighted as that desire is in the first place (if 30% of the global work force is unemployed, how do you think that will effect your revenue, morons!?). But that also is assuming that the coming chaos doesn’t turn out so bad that AI is permanently legislated into oblivion after the chaos it’s about to cause.
Does AI cost more than humans primarily because of greed (i.e the AI companies demand a high profit margin now) or because of energy costs (i.e AI is so wasteful with energy, so polluting, that it costs more than human workers)
Given the ai companies are running at a loss, it’s fair to assume which of these is likely
This is a common myth, inference is not typically run at a loss, despite claims. It’s only a loss if you include staff and ongoing training costs. They could lock in their models now and be profitable if they wanted to.
Edit: I see the comment above has changed (or I misread initially) to say the companies are running at a loss rather than inference running at a loss. Yes, that’s extremely true. Now my comment doesn’t make any sense and is irrelevant so feel free to ignore my pedantry.
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
We do have numbers from comparably sized Chinese models.
Yes, every AI company is bleeding money, they’re not healthy in any way. But inference by itself is profitable, based on everything that we know.
Inference + amortizing the training costs is NOT profitable, which is what most people are talking about.
This is easily fixed by not releasing a slightly different version every month.
They fired the wrong people. Go higher!
