Raza Habib: observation

Transcript context

…trying to get some insight from there. I don't know. Yeah. So I can tell you the trajectory we've seen, right? So really early on. The like killer use case was some form of writing assistant, whether it was like a marketing writing assistant. The Jaspers. Right. Jasper, Copy AI. We had like seven of them at one time, right? And then you had like specialist writing assistants. Some, some I think have gone on to be really successful products like Sudowrite or Type AI is another one, but they're still fundamentally like helping people write better. And then I think increasingly we've seen more diversification. There was a wave of chat to documents in one form or another. Yeah, chat PDF, still doing well. Yeah, chat PDF doing super well. Once RAG started working, like retrieval augmented generation, there was that. But since then, as people are more problem driven. And they're like trying to say, okay, how can we use this? We see a much broader range. So even within like, take Duolingo as an example, they've got Duolingo Max. So that's like a conversational experience, but they're also using large language models within the evaluation of that. They're all choosing it for content creation. And each of these companies sort of, you start with one use case and I feel like it expands because you just discover more and more things you can do the model with, do with the models. Yeah, yeah. Do you see much code generation?…

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