It's like witnessing a rocket using the most powerful engine on Earth then once it escaped orbit turn off the engine and said "It is flying without power!".

Yes, sure, right now it is ... but that's NOT how it got here.

There are trillions invested to recoup and at most billions in sales. It doesn't add up to tokens making a profit any time soon.

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StevenWaterman 5 hours ago | parent | next [-]

The problem is, people see "they're not profitable once you account for training" and equate that to "AI will go away soon"

But if all the AI companies stopped training new models, they would all instantly become profitable (and stick around)

The thing that makes them unprofitable, is having to compete (which means training models). If / when enough companies exit the market, the cost to compete goes down and you end up in an equilibrium

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notahacker 4 hours ago | parent | next [-]

Sure, but if companies don't exit the market and FOSS alternatives don't end up being unable to get near them in quality, they have to keep spending on training. And conversely, if the market becomes uncompetitive and FOSS sucks, the winners of the AI arms race are very strongly incentivised to stick their prices up anyway...

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JumpCrisscross 4 hours ago | parent [-]

> if companies don't exit the market and FOSS alternatives don't end up being unable to get near them in quality, they have to keep spending on training

Eh, the AI companies still have lots of datacentres. For the guys who funded with equity, they could collapse down to just running those as utilities. (For the guys who funded with debt, they'd have to restructure.)

From the customer's perspective, this situation shouldn't result in a cost spike. (Consolidation, on the other hand, would. But that's a separate argument from the one the article attemptes to make.)

	▲	notahacker an hour ago \| parent [-]
		How often do VC funded unicorns collectively decide to stop scaling up, shut down all their departments targeting growth and reach breakeven point by becoming low margin utilities that will never justify their valuation?

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InsideOutSanta 4 hours ago | parent | prev [-]

That's all true, but that ends badly for us either way. If there's competition, training must continue, which must eventually be reflected in pricing.

But if there's no more competition, there's no more incentive to keep prices low, which will also be reflected in pricing.

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JumpCrisscross 4 hours ago | parent | prev | next [-]

> There are trillions invested to recoup and at most billions in sales. It doesn't add up to tokens making a profit any time soon

But this isn't "a ticking time bomb for enterprise." It's an issue for the AI companies' investors.

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shimman 4 hours ago | parent | next [-]

Good thing the entire nation's economic growth outlook isn't tied to these companies then. For a second I thought we had a potentially dangerous situation on how we misappropriated trillions of capital.

	▲	airstrike 4 hours ago \| parent [-]
		For anyone doubting this, total private investments in the US grew 2% in 2025 relative to the prior year, adjusted for inflation. But within that big pie, the "IT-related" investments grew 15.7% whereas non-IT actually shrank 2.0%.

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alkyon 4 hours ago | parent | prev [-]

Not really, because investors will sooner or later want to see real returns on what they invested. Tokens are suddenly not dirt cheap and enterprises are screwed.

It's like selling dope, once they're addicted, a dealer could turn the screw on them

	▲	mpyne 4 hours ago \| parent \| next [-]
		That's why it's an issue for investors. Their investment may not payout. But the things that were built will still have been built and available to sell for related purposes, the models that were trained will still be trained, and so on. If things don't end up working out a lot of people have already been (and in the future will be) paid. It's the investors that will lose out, not the subscriber.
	▲	airstrike 4 hours ago \| parent \| prev [-]
		Not if they IPO and some other sucker buys the stock.

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manmal 3 hours ago | parent | prev [-]

Certainly not trillions. The models costing tens of billions to train are a very new development.