AI Consolidation, Biotech Opportunities, and World Models with Sarah and Elad

**Sarah** (0:05)
Elad, what's going on?

**Elad** (0:06)
How are you doing, Sarah?

**Sarah** (0:08)
I'm good. I can't tell if it is a very stable time in the market, like it's crystallizing into known businesses and models, or it's as fluid. What's your take?

**Elad** (0:18)
You know, it's interesting. AI is the one market in my career where I've sort of consistently said, the more I learn, the less I know, right? Every other market, you kind of learn more, you know more, you keep advancing. And I actually feel like that's shifted in the last couple of months, where I feel for a subset of areas, despite the rapid pace of innovation, all the really exciting new models and research findings and everything else, I actually feel like a bunch of markets have sort of consolidated. And it's kind of clear now who are the likely players or winners in like two or three big areas. And that may change, right? In three years, another new startup may launch and displace everybody, or an incumbent may make a bold move or whatever it may be. But I feel like in the foundation model market, at least for LLMs, there is a clear view of sort of what's important and what isn't. At the application level, I think it's kind of clear who the winners are going to be in sort of at least the first set of services for health care related, things like medical scribing or other flows. Encoding, it seems like it's consolidated into two or three players.
You know, maybe that's Cursor, Codium, Cognition, and then Microsoft's Copilot, right? But there aren't probably like two dozen companies that are all still competing there. In customer success, it seems like things are kind of consolidating against Sierra and Dekagon. So you kind of go through market by market and you're like, okay, there's a bunch of markets where it's kind of clear who we think some of the winners may end up being, or at least the ones who are going to be important for the next two, three years. And then I think there's a set of markets where it's still wide open, right? So you look at sales productivity tooling, there's going to be something really important there. There's going to be some financial analyst thing that's going to be really important. There's going to be an accounting company that's really important. And the question is, has that not consolidated yet because of nobody yet doing the exact right product approach? Is it because the models aren't good enough and the capabilities have to get better? So it feels like there's a bunch of stuff that is still unknown, but it's way clearer than I think it was a year ago. I feel like for the first time in like two years or something, when I first started investing in generative AI, you just went and you backed the things that the people seemed really good and the market seemed interesting because there wasn't a lot of competition, right? So that's when I led the seed run for Perplexity or Invested in Character or Harvey or some of these other things. That was, you know, pre-Chat GPT or pre-Mid-Journey.

**Sarah** (2:35)
Oh, the good old days, yeah.

**Elad** (2:36)
The good old days when nobody cared. When GPT-3 was out and everybody was like, this is kind of crappy. But the scaling law was clear, right? So I thought a handful of people, you know, you being included kind of, I think we collectively saw that this stuff was going to be important. But then there was like a period of like uncertainty for two years or something like that, maybe three years, where there was just so much innovation and so much change and so much rapid growth. And I think now finally we're hitting a period where at least a subset of things are consolidating back down. And again, these may not be the winners five years from now, but they definitely seem to be emerging as the winners for the next two years. So I think it's kind of a nice breather in terms of uncertainty and kind of having a bit more clarity in what's going to happen. What do you think?

**Sarah** (3:18)
I feel a little bit like I understand some temporary physics of the market a little bit better. It's like a race to find the verticals of relevance and then get something to work in a way that users actually want. Maybe you have to go get proprietary data sources that you can retrieve against and get distribution. And then ideally have users that can create or derive or extend knowledge from that. Like the companies you just named, and I don't think you explicitly said it, but I put like a bridge and open evidence. I think they fit into that shape. And then one thing you and I have talked about is, I'm actually quite unsure about sales. I like don't know how to think about how something wins there. Like you could go at it from a data perspective or adoption perspective, but it's been a very fragmented market to date. But I agree with you on finance and accounting. I'd add pharma to that. Like there are some industries that are really document driven where you can see something just becoming really important.