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Small-Scale Question Sunday for September 13, 2026

Do you have a dumb question that you're kind of embarrassed to ask in the main thread? Is there something you're just not sure about?

This is your opportunity to ask questions. No question too simple or too silly.

Culture war topics are accepted, and proposals for a better intro post are appreciated.

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Is it not inevitable that these 'frontier AI labs' calling for regulation are going to get eaten alive by the half dozen big tech companies that have accountants overseeing the nerds? The business case will prevent AI risk, the market won't stay solvent long enough to present X risk.

I may not be educated, but I can sanity check. This stuff is really expensive and when the bill comes due someone who has the revenue to pay it gets the assets.

They are operating on the idea that one of the frontier companies will make a major breakthrough that creates an insurmountable lead. Using customer data and a superhuman AGI they'll be able to immediately move into multiple high profit industries and take over.

The problem they are having is that so far training better models seems to be able to suck up an unlimited amount of money. That was unexpected.

Also the open models have been better at keeping up than they expected. You can fine tune the open models for specific tasks and get "good enough" results.

So they are in a weird spot since there are so man unknown unknowns. There are potentially massive returns. The huge costs are all in training models, so if they cut that back and just run inference with existing models then they can immediately become profitable. They can get to work doing low level speed optimizations on existing models and build out more capacity that way.

Right now they're going for a moon shot, but they can scale back training without being forced to sell of the companies at the risk of losing their leads.

Don't they need to service their debt as well?

They do, but the race is less about debt and more about the capability growth and its effects on revenue. OAI and Anthropic are both printing money. But the 50-100B a year they can theoretically print will vanish in a single year if a competitor leapfrogs them. Their revenue is only sustainable while they remain the only game in town, if open or big tech model competitors like gemini get capability parity, they go from serving inference at 80% margins to serving inference at 2% margins as competition intensifies (At least on API usage billing, consumers are probably more locked in, but still very willing to move on if someone else has a better model for their 20 dollars). Their debt is nothing if they keep leading the pack, everything if others catch up to their leads.

So they can't service their debt if they stop and they can't finance continuing (much longer) either?

They can't service their debt if their revenue falls off a cliff. Anthropic's debt is in the vicinity of 70 billion. Their revenue this year is projected to be a whopping 65 billion (If each quarter is as good as their last one). Their revenue last year was just under 10 billion. See the issue? Those are some very different numbers. OpenAI's debt is probably in the vicinity of 100 billion, but their revenue this year is on track to hit 40 billion. I don't know their rates, but the issue is those revenue numbers could theoretically as easily go to tens of billions as they could hundreds of millions, and those are revenue numbers, not profit. If the industry ends up with mostly comparable models, a race to the bottom on cost could destroy companies. But if the big names manage to hold their decisive advantage for as little as five years, they could well print over a trillion dollars before anyone catches up and begins to drive price down.

But to answer your question, they can service their debt unless revenue falls below well last year's numbers and remains that way. And the only realistic way that happens is serious competition on cost.