Nick Beim

I'm most excited about vertical AI applications.

I think the first inning of AI innovation, we've seen broad horizontal platforms, the big LLM labs achieve extraordinary things, and they're starting to shift their focus from just providing an LLM to getting into horizontal applications.

I think some of the most interesting investments are going to be in vertical AI applications.

And the reason I think vertical is so interesting is twofold.

One is more defensible.

It's very difficult for those horizontal platforms to get access to all the workflow and data in a vertical application.

And many of the vertical application incumbents and major customers are very reluctant to give their data to these AI labs.

But the second and maybe the more interesting reason is when you look what drives AI performance, it's context.

So general intelligence is interestingly getting commoditized.

But when you apply that intelligence to a particular vertical where you've got really rich idiosyncratic data,

It's a few things.

I think first, they've got a lot to do.

They've got a lot on their plate already in this sort of commoditization struggle.

They're all investing a lot to try to get incremental improvements in their core models better.

And

They can't devote all their attention to trying to win every application category they can.

They'll go after a few of them.

They'll go after the biggest ones.

I think it's very similar to what happened with Google and Microsoft as they extended their search and operating system franchises into horizontal productivity apps.

Very profitable for both companies.