Rob Wiblin

So like I said earlier, in AI 2027 and a lot of stories of the intelligence explosion, you get to a point where one company has pulled far enough ahead of its competitors that it –

keeps its internal best systems to itself and only releases systems that are considerably worse than its internal frontier that are just good enough to be ahead of its competitors' released products.

And there can be a growing gap in how intelligent the best internal systems are and how intelligent the best externally accessible systems are.

And the AI company may deliberately choose not to sell to willing customers because they want to keep their secrets to themselves.

Another possibility is they might be willing to sell to you but the price just might be way too steep because the opportunity cost of using that compute to like sell to you to do whatever you want to do with it is training further more powerful AIs and they might be willing to pay quite a lot for that.

So I think both are challenges.

The second one is in some sense more straightforward to address which is you try to like

hedge against this possibility, um, by having some portion of your portfolio, like really exposed to compute prices, um, and hope that, you know, maybe that looks like in the extreme case, just, just having GPUs yourself, um, that, uh, you know, in peacetime, you just rent out to other people doing commercial activity with it.

But then during crunch time, um, you redirect to, um,

doing AI labor, although in that case, you'll have to furthermore figure out how to get the latest AI models onto those chips that you own.

So you might have to cut deals to make that happen.

But also in less extreme cases, you might just purchase a bunch of NVIDIA or purchase a bunch of liquid public stocks that are exposed to AI to make it more likely that you can afford AI capabilities at the time.

Yeah, I think that at least at the beginning part of crunch time, like when the AIs are just starting to automate a lot of AI R&D, my bet is that things will at that point be relatively commercial, relatively open.

The leading few companies are within a month of each other in their capability frontier.

Or maybe it's hard to say who's in the lead because one company specializes in one

like, you know, their model is like a little spiky on like pre-training and another company's model is a little spiky on software engineering or something like that.

And I think that the reason I think that is basically just because it's kind of what like a naive econ 101 model would predict would happen.

It seems like these companies don't have big moats.

And it also seems like what we've seen happen over the last few years, like,

It describes the present day.