Vector databases, so hot right now. I haven't really looked into them, I'm just wondering when or if postgres will do it better?
Pinecone raises $100M Series B
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Re: Pinecone raises $100M Series B
#22Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).
Maybe I am fundamentally missing something, but a "cloud database company" seems like the most boring tech? No one is calling Planetscale or Yugabyte nonsense because there are free alternatives like Postgres.
Re: Pinecone raises $100M Series B
#23I was using pinecone before installing pgvector in Postgres. Pinecone works and all but having the vectors in Postgres resulted in an explosion of use for us. Full relational queries with where clauses and order by etc AND vector embeddings is wicked.
Re: Pinecone raises $100M Series B
#24Vector databases, so hot right now. I haven't really looked into them, I'm just wondering when or if postgres will do it better?
Postgres has pgvector. It’s awesome.
Re: Pinecone raises $100M Series B
#25My alarm bells are going off given the Andreessen participation—what am I missing?
Re: Pinecone raises $100M Series B
#26I’ve wanted to ask this question but I don’t know who to ask. Can someone explain what the use case is for vector DBs like pinecone, milvus etc. vs a fully featured search engine like Vespa, ElasticSearch etc. which also support vector search features? Is there something about running this type of index operationally that is particularly difficult?
I’ve been playing around here a bit. One feature is that documents have embeddings stored at index time which means that query performance is quite good. Another is that the model you’re using to embed and query can be changed and configured based on specific use cases. A pretty cool feature of Marqo is multi-statement queries that let you search for multiple positive queries and even include negative queries to filter out results.
Overall I’m really enjoying the tech.
Re: Pinecone raises $100M Series B
#27Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).
You're telling me the VC that went hog-wild on NFTs and Crypto is fomo'ing into AI without any DD?
I'm shocked.
Re: Pinecone raises $100M Series B
#28Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).
Most demos shared by people can use numpy arrays similar to this https://twitter.com/karpathy/status/1647374645316968449
It’s true, but I also wouldn’t want any developer beside Karpathy to implement a production service using numpy arrays (I use Faiss).
Re: Pinecone raises $100M Series B
#29Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).
You're telling me the VC that went hog-wild on NFTs and Crypto is fomo'ing into AI without any DD? I'm shocked.
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Re: Pinecone raises $100M Series B
#30Perfect example of AI gold rush nonsense. Pinecone has zero moat and quite a few free alternatives (Faiss, Weviate, pg-vector). Their biggest selling point is that AI hype train people don’t Google “alternatives to pinecone” when cloning the newest trending repo (or I guess, ask ChatGPT).
Spot on. There is zero moat and the self-hosted alternatives are rapidly improving (if not better) than Pinecone. There are good open-source contributions coming from bigcorp beyond Meta too, e.g., DiskANN ( https://github.com/microsoft/DiskANN ).
why use this instead of something like pgvector?