embeddings

“So I think for the next couple years, yeah, we will see a whole bunch of new embeddings maybe of different sites, and much, much faster than today.”

“Embeddings really is kind of like the lowest hanging fruit, and using something like Instructor can really help produce a data structure, and then you can just use your computer science to reason about this data structure.”

“For a lot of the systems, we do believe embeddings work, but for complex questions, we don't believe embeddings can encapsulate all the granularity of a particular query. Like imagine, imagine I have a question on a codebase of find me all quadratic time algor…”

“I don't think that like embeddings are going to be able to scale to, I think they work well for some of this as like kind of the MVP version of the experience, but I think you're going to need a different experience and it's Probably something like really smar…”

“They're much more discoverable. You can kind of see it. There's observability to it versus kind of embeddings, which you can't really do much with as a human. You know, once they're in there, you can't pull stuff back out”

“But I think as a tool to understand how these AI platforms are consuming your content, embeddings aren't that relevant. You're better off focusing on, like, just, again, having a good structured set of content that makes sense, like, to a human with, like, cle…”