Varun Mohan: commitment

Transcript context

…predict monster embedding database companies? Probably Monster embedding database companies or, yeah. The model in some sense will need to talk to, Talk to these embedding databases. I'm actually not convinced that the current breed of embedding database companies are like ready for what the future sort of looks like. I think I'm just looking at their pricing, how much it costs per gigabyte and it's prohibitive at the scale we're talking about, like let's say you actually did want to host a 10 terabyte embedding database. A lot of them were created, let's say two years ago, two, three years ago, where people were like, you know, embedding databases are small and they need to make the cost economics work. But maybe, yeah, there's probably gonna be a big workload there. I will just say for us, we will probably just build this in-house to start with, and that's because I think the technology probably isn't there. And I think that the technology isn't there yet. Like waiting on point solutions to come up is a lot harder, um, than probably building it up. The way I, I like to think about this is probably the world looks on the LM space. Looks like how the early internet days were, where I think the value was accrued to probably like Google and Google needed to figure out all the crazy things to make their workload work. And the reason why they weren't able to outsource is, is no one else was feeling the pain. , they're just solving their own pain points. They're just solving their own pain points. They're so far ahead of everyone else. Yes, yes. And just wait…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.