Logan Kilpatrick: belief

Transcript context

…Can can I ask a follow up question on that? Cuz I am just learning about embeddings myself. What makes OpenAI’s embeddings different from other embeddings? If, if there's like, It's okay if you don't have the, the numbers at hand, but I'm just like, why should I use open AI emitting versus others? I don't understand. Yeah, that's a really good question. So I'm still ramping up on my understanding of embeddings as well. So the two things that come to my mind, one, going back to the 50 million to embed the whole internet example, it's actually just super cheap. I, I don't know the comparisons of like other prices, but at least from what I've seen people talking about on Twitter, like the embeddings that that we have in the API is just like significantly cheaper than a lot of other c. Embeddings. Also the accuracy of some of the benchmarks that are like, Sort of academic benchmarks to use in embeddings. I know at least I was just looking back through the blog post from when we announced the new text embedding model, which is what Powers embeddings and it's, yeah, the, on those metrics, our API is just better. So those are the those. I'll go read it up. Yeah, those are the two things. It's a good. It's a good blog post to read. I think the most recent one that came out, but, and also the original one from when we first announced the Embeddings api, I think also was a, it had, that one has a little bit more like context around if you're trying to wrap your head around embeddings, how they work. That one has the context, the new one just has like the fancy new stuff and the metrics and all that kind of stuff. I would shout a hugging face for having really good content around what these things like foundational concepts are. Because I was familiar with, so, you know, in Python you have like text tove, my first embedding as as a, as someone getting into nlp. But then developing the concept of sentence embeddings is, is as opposed to words I think is, is super important. But yeah, it's an interesting form of lock in as a business because yes, I'm gonna embed all my source data, but then every inference needs an embedding as. . And I think that is a risk to some people, because I've seen some builders should try and build on open ai, call that out as, as a cost, as as like, you know, it starts to add a cost to every single query that you, that you…

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