Pinecone

“Serverless is the fourth complete, almost complete rewrite of the entire database at Pinecon.”

“We've tested it with tens and tens of billions with live customers and live traffic.”

“Notion Q&A now runs on, on Pinecone, and they serve essentially question answering with AI to tens of thousands and probably hundreds of thousands of their own customers.”

“There's plenty of evidence that increasing the context size doesn't actually improve results unless, you know, you do this very carefully, right? So just what's called constant stuffing is not helping. You just pay more and don't actually get much for it.”

“Our research actually shows that when you do this well, we, you very rarely need keywords alongside embeddings, but getting embeddings to perform perfectly is, is actually, it could be quite intricate.”

“And you could see that if you augment all of them with RAG on, even on the internet, which is data that they were trained on, you can reduce hallucinations significantly up to 50% sometimes.”

“And in fact, if you look at statistics, even companies that are open source, 99% of the contributions are actually from the company itself. Not 99, but high nineties.”

“Those other products don't work. They don't work either because they don't scale in terms of the efficiency scale, cost, the trade-offs that they can offer, because they're not designed to do this. They're designed to do something else. They kind of thought ab…”

“And in fact, we already see, even though new players in the vector database space that, that, that basically started to try to take us down, all took the open source angle. We already see them, even young as they might be, they are already struggling, struggli…”

“Already today, we have users who use not even very large models, you know, maybe a few billion parameters, and the vector database next to the model contains trillions of parameters. And they get, you know, much better performance that way.”

“In 2019, the earthquake had already happened. Deep learning models and so on have already been grappled with. Large language models and transformer models like BERT and others started being used by the more mainstream engineering cohorts.”

“Gong does the same thing with sales calls. Again, serves all of their use cases for all of their customers, and so on.”