Comment by ItsMattyG
1 day ago
To me it seems the opposite. There's a few companies in the world that have enough compute to train and serve frontier models.
As the frontier gets smarter and more useful prices will only go up, as they are set to replace jobs being paid six or seven figures a year - the demand for as much inference on these models for as long as possible will be astronomical, but compute starting in 2030 will not be keeping up.
Eventually prices will fall for assistants but the frontier will be the most profitable thing in the world, and the top companies basically already have oligopolies due to their ridiculously expensive compute investments.
> There's a few companies in the world that have enough compute to train and serve frontier models.
Train: yes, for now.
Host: depends on the scale. At a small scale a wealthy individual could easily build a rig in their basement to host one of these things. At larger scale any cloud company could do it, and many already have the compute on site. At large scale this is true... again, for now.
What you say only holds (in the absence of a state oligopoly) if two conditions are met: (1) AI performance does not asymptote any time soon due to running out of training data or other scaling limitations, and (2) these companies are able to stay at the frontier.
There's little to no moat, so staying at the frontier will be a game of investing massively in compute, talent, and R&D, and they can never stop.
Again, there is a moat based on compute. If the thesis is right, cost of compute will only rise... As it is as you say someone will have it be quite wealthy to host something like Astra with trillions of parameters, but that cost will only rise with demand for serving these frontier models.
what suggests that we will hit an asymptote any time soon? Agree with you on the second part. The ever elusive frontier will probably always be changing hands after some point.