Comment by api
21 hours ago
> 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.
That hasn’t been true for anything else in computing, ever. The cost falls with scale.
Look at general compute, storage, graphics, networks, anything. Demand increases. Price goes down. There are price spikes, such as right now with RAM, but they’re transient. The trend is more faster cheaper and it won’t end until we hit actual physical limits. We are not close.
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.