David Clark

Is that something that you guys are seeing internally in your portfolios?

Yeah.

So a couple of my colleagues are in China at the minute, and it's been really interesting just getting their feedback relative to what we're seeing in the U.S.

And one of the things that they were saying was the leading LLMs in China are probably six months behind where we are in the U.S.

in terms of the capability of their models, but they're 10x cheaper.

And so one of the unknowns, I think, at the minute is to what extent, what percent of the market will those type of companies capture?

How much of what we end up doing over the next decade will need to be done through the very frontier models and what can be captured by that next level down?

And it's the classic innovator's dilemma, isn't it?

That you get the next generation product that can do 80% of what the frontier product can do, but at 10% of the cost.

And over time, those capabilities extend and it's harder to be at 10%.

at that frontier.

Yeah, yeah.

How do you factor that in when you're then thinking about valuations of these companies?

Because I think one of the concerns that I would have is a bit like in 2021.

I thought 2021, the market there was kind of peak emerging manager because a lot of these managers had done the seed round, you know, established firms were coming in and writing things up.

you know, six months after the seed round had done, and there was basically a zero loss ratio.

And, you know, we know that's not how venture works.

It feels like we're in a little bit of that situation today, but with the more established firms, because it's the established firms that have been by and large capturing the early breakouts in the AI space.

But when I look at it, like, historically, when we look at our early stage funds, there's a 60% loss ratio.

So 60% of deals don't return the capital that was invested in them.