Pinecone, every mention

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Verbatim, from the transcripts: the passages where Pinecone comes up

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▶ 51:08 Sridhar Ramaswamy And so products like, uh, Pinecone, it's a great company, came along, they started providing vector indices,

▶ 9:56 Mike Freedman Uh, compared to one of the leading vector-only databases, Pinecone, a PG vector scale is 28 times faster for a high recall scenario. 4 times in the scene

▶ 36:36 Matt Turck disappeared or have accelerated dramatically in the last couple of years, uh, so the, you know, the pine cones and the quadrants and the chromas and the weviets, um, of, of the world, and I'm sure I'm, I'm forgetting LensDB, and, you know,…

▶ 19:51 Florian Douetteau Gemini, of course, Anthropic, and, ah, AI-Twenty-One Labs, ah, also with, ah, vector databases that can provide a rack for virtual elements, such as Pinecone, for instance, um, as a local, ah, as a local vendor, but also, of course, ah,… 2 times in the scene

▶ 31:11 Nancy Xu An example of this is there's the sort of pine cone, leviates chromas of the world that build vector DBs.

▶ 13:06 Milos Rusic If you want to use OpenSearch, or if you want to use Pinecone, or, um, as a database, you can simply load it in.
▶ 13:42 Milos Rusic Some of the key ones, definitely, of course, the most popular vector databases from Pinecone to Quadrant, VIAE, um, Milvus, um,

▶ 6:58 Jerry Liu And these days, you know, there's a bunch of different vector databases from Pinecone to Chroma to WeVA to a bunch of others.

▶ 5:41 George Sivulka Um, and a lot of the time, people didn't really just want a simple search index, uh, like a Chroma or Pinecone database or whatnot and, you know, some gender response over them.
▶ 20:46 George Sivulka Um, and it's not just, you know, creating some logical tree of operators in lane chain, and then having the right Pinecrum database hooked up.

▶ 0:13 Matt Turck You are the founder and CEO of, uh, Pinecone. 3 times in the scene
▶ 5:52 Matt Turck And that, um, is vector and vector embeddings, and that leads us to vector databases, so we'll talk about, you know, Pinecone in a second, but
▶ 10:18 Matt Turck Okay, so all of this is a wonderful, uh, hopefully intro into Pineco and then what Pineco does. 4 times in the scene
▶ 16:32 Matt Turck Let's talk about some of the use cases that you've seen with Pinecone.
▶ 20:13 Matt Turck I would, um, uh, put, I would use pine cone. 4 times in the scene
▶ 21:56 Edo Liberty Um, so, uh, we started Pinecone, or I started Pinecone 4 times in the scene
▶ 25:13 Edo Liberty So as, as a systems and, uh, algorithms person, Pinecone is a fascinating place to be, and I can tell you that we are far and away better in terms of efficiency of, of, uh, of running this, uh, service at scale and its stability, and we,… 2 times in the scene
▶ 28:03 unnamed speaker Like quality monitoring on embeddings, and if there are any plans in the pinecone roadmap to build that into the service.
▶ 30:16 Matt Turck I, you know, it's, it's really incredible, um, how just Pinecone has just vaulted to the forefront of, uh, just consciousness in this, um,

▶ 22:33 Matt Turck So, you know, in a world where you have, uh, you know, model producers like OpenAI and then vector databases, producers like Pinecone, which by the way is speaking at the next event, um, you know, Langchain, all those things, where, where… 3 times in the scene

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