this post was submitted on 30 Apr 2026
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[–] lokalhorst@feddit.org 3 points 17 hours ago (11 children)

A lot of ideas need huge investments to once become profitable. Imagine a new pharmaceutical that was found by a researcher. They have the capabilities to produce the substance in their lab in very small quantities, but it's not enough to sell it. As they don't have a lot of money by themselves, they need investments to buy a bigger lab, automate manufacturing etc. in order to scale the process. Then after a period of time, the product slowly becomes profitable and for the investors hopefully big time.

Now with AI the thought process is similar. You need huge data centers and gigantic computation facilities to train models with many billions of parameters to make a model that is even slightly useful. Their have been made huge investments into different AI companies, because this technology seems to be ground breaking and it is not clear yet, who will win the race.

Now stocks are pumped up and everybody is waiting for the breakthrough, the artificial general intelligence, called AGI. This concept is completely bullshit, but investors don't understand the technology, they are just greedy. If knowing that the token size of transformer models scale with n² was common sense, people would have already thrown the towel. Now what AI companies really need to do, is to shove AI down everyone's throat. They need to sell their models to every little business with the promise of increasing productivity largely. Companies believe the bullshitting and spend a lot of money on AI, although Harvard Business Review found out that workslop™ does in fact not increase productivity. In alignment with sunken cost fallacy, AI companies don't give up but increase their bullshitting game. They present agentic AI, - as a data scientist only writing down this term makes me cringe really hard.

As so much money has been pumped into this market, the stocks are overvalued through the roof, the GPU and storage market is broken, there is no way back. We don't know yet what the tech bros will invent in order to rescue their asses, but it is not sure at all this bubble will ever burst. So you better don't bet your ass on falling stocks.

[–] Tar_alcaran@sh.itjust.works 3 points 17 hours ago* (last edited 17 hours ago) (1 children)

Imagine a new pharmaceutical that was found by a researcher. (...)

Now with AI the thought process is similar. (...)

The two are nothing alike. The pharmaceutical has a pre-determined market, and a known effect. A researcher who finds a treatment for Somethingitis will know in advance that people with the disease will want it. They will want it because the medication has a proven effect. Nobody has to hand out the cure under cost to get people enthusiastic about it (In fact, without proper controls, the exact opposite happens. See the USA)

LLMs are pretty much the opposite. They're a solution looking for a use, and are only very marginally successful in that. Nobody can say "this product will cause that effect", pretty much by definition.

That's why they're giving their product away, and massive subsidizing the use of it. If they stopped, nobody would use it. And every month, the models get more and more expensive even as the scale increases. Actual results are few and far between, except for very niche applications which won't recover the costs before the next millennium.

The best comparison I've seen is someone selling stale bread covered in gold leaf for ten bucks. Is there a market for it? Sure, decorative bread is on display with many bakers, and I'm sure you could sell some of it for croutons and such. But nobody is buying stale bread en masse. But if you sell stale bread for 5 cents, you bet your ass people will buy it. It might not be great, but come on, for 5 cents I'm willing to eat a lot of toast.

[–] lokalhorst@feddit.org 3 points 16 hours ago

I agree with you and that is basically what I tried to say. I just used the pharmaceutical to explain the concept of investment, expectation, profit. I think both are in fact not the same, while investors think they are.

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