> 1. Anthropic, OpenAI, and perhaps a couple of other frontier labs are the dominant providers of frontier AI models.
> 2. They can charge customers a lot of money for using their frontier models, and rather less money for older, no-longer-cutting-edge models.
> 3. Training a new frontier model requires ever-increasing billions of dollars of computing power.
> 4. The labs need to more or less continuously race to build new frontier models, because their competitors are all doing it, and if they don’t they will fall behind and no longer be able to charge a lot of money for their best models. (Also because they intrinsically want to build artificial superintelligence, for cancer-curing and/or killing-everyone reasons.)
> 5. If they collectively slowed down, then (1) they’d spend less on compute and (2) they’d be able to charge frontier-model prices for a longer time.
> 6. But if one of them slowed down, the others would eat its lunch.
> 7. If they got together in a room and agreed to slow down, that would look like an antitrust conspiracy: It is generally illegal for competitors to get together and agree to limit the output of their industry.
> 8. But if they publish papers about how important it is to slow down, that might have a similar coordinating function, at least among the US frontier labs if not necessarily among their Chinese competitors.
> 9. And if the government believes those papers, it might help them coordinate. Maybe the government will impose pacing by regulation that the labs could not impose by agreement. Or at least the government will let them get together and agree to slow down. Amodei’s post calls for “frontier AI companies within democratic countries [to] coordinate to establish common safety standards as well as limits on the rate of unchecked AI progress”; a footnote adds: “With government mediation or waivers of antitrust restrictions.” Just meeting in a room to establish common safety standards is legally risky; the labs can’t do it on their own unless governments affirmatively allow it.
[1] https://www.bloomberg.com/opinion/newsletters/2026-09-14/ai-...