Sarah Wang: belief

Transcript context

…Does that make sense? Like, I mean, it could be, it could be the case that the only reason this is working is ‘cause they can raise that next round and they can train that next model. ‘cause these models have such a short. Life. And so at some point in time, like, you know, they won’t be able to [00:31:00] raise that next round for the next model and then things will kind of converge and fragment again. But right now it’s not. Totally. I think the other, by the way, just, um, a meta point. I think the other lesson from the last three years is, and we talk about this all the time ‘cause we’re on this. Twitter X bubble. Um, cool. But, you know, if you go back to, let’s say March, 2024, that period, it felt like a, I think an open source model with an, like a, you know, benchmark leading capability was sort of launching on a daily basis at that point. And, um, and so that, you know, that’s one period. Suddenly it’s sort of like open source takes over the world. There’s gonna be a plethora. It’s not an oligopoly, you know, if you fast, you know, if you, if you rewind time even before that GPT-4 was number one for. Nine months, 10 months. It’s a long time. Right. Um, and of course now we’re in this era where it feels like an oligopoly, um, maybe some very steady state shifts and, and you know, it could look like this in the future too, but it just, it’s so hard to call. And I think the thing that keeps, you know, us up at night in, in a good way and bad way, is that the capability progress is actually not slowing down. And so until that happens, right, like you don’t know what’s gonna look like. But I, I would, I would say for sure it’s not converged, like for sure, like the systemic capital flows have not converged, meaning right now it’s still borrowing against the future to subsidize growth currently, which you can do that for a period of time. But, but you know, at the end, at some point the market will rationalize that and just nobody knows what that will look like.…

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