> Models are getting 99% more efficient every 3 years - to get the same amount of output, combined with hardware and (mostly) software upgrades - you can use 99% less power.
Even if true, this still doesn't bend the curve when paying for the next model.
> If AI stopped progressing today, it would take probably a decade or longer for us to take full advantage of it. So there is tons of forward looking revenue that isn't counted yet.
If this is true, it's true for the technology overall, and not necessarily OpenAI since inference would get commoditized quickly at that point. OpenAI could continue to have a capital advantage as a public stock, but I don't think it would if the music stopped.
I would actually like to see the real math currently.
The market adoption has increased a lot. The cost to serve has come down a lot per token.
Model sizes have not increased exponentially recently (The high point being the aborted GPT-4.5), most refinement recently seems to be extending training on relatively smaller models.
When you take this into account together, the relative training to inference income/cost ratio likely has actually changed dramatically.