It's also kind of interesting that they don't think they can do what an economy would normally do in this situation, which is raise prices until supply matches. Shortages generally imply mispricing.

There's a lot of angles you take from that as a starting point and I'm not confident that I fully understand it, so I'll leave it to the reader.

the sales pitch is that you can keep throwing more and more tokens at a problem to solve it.

if the prices dont keep going down, the pitch falls apart, that you need a specialist to come in and make it work

Great point.

The parent's argument is that the marginal cost of inference is minimal. However, the fundamental flaw is that he's separating inference from the high cost frontier models. It's a cross-subsidy that can't be ignored.

Without any insider knowledge on the economics of these companies, I suspect it's that the amount of infrastructure you have to build is determined by peak usage rather than average usage. If peak usage is much higher for a small part of one day a week (say on Monday morning as software developers across the US get back to work) the cost of fulfilling demand at all times can be insane. That's why companies are implementing batch/standard/priority pricing for the API.

Check out this article from today [0].

It sounds like it's more of a profit maximization function (and not just demand) with GPU rental prices increasing 48% since Feb.

> Renting one of Nvidia’s most-advanced Blackwell generation of chips for one hour costs $4.08, up 48% from the $2.75 it cost two months ago, according to the Ornn Compute Price Index.

[0] https://www.wsj.com/tech/ai/ai-is-using-so-much-energy-that-...