gk1

34 ms·

601.
Vectors as AI Data Primitives(pinecone.io)
1 points by gk1 3y ago|0 comments
602.
Choosing an Embedding Model(pinecone.io)
2 points by gk1 3y ago|0 comments
603.
Build a Wikipedia chatbot without hallucinations(pinecone.io)
1 points by gk1 3y ago|0 comments
604.
Under the hood of Pinecone's serverless vector database(pinecone.io)
1 points by gk1 3y ago|0 comments
605.
Minimize LLM Hallucinations with Pydantic Validators(blog.pydantic.dev)
2 points by gk1 3y ago|0 comments
606.
Build a Wikipedia chatbot, minus hallucinations(pinecone.io)
2 points by gk1 3y ago|0 comments
607.
Rerankers and Two-Stage Retrieval(pinecone.io)
2 points by gk1 3y ago|0 comments
608.
Foundations of Vector Retrieval(arxiv.org)
3 points by gk1 3y ago|0 comments
609.
Pinecone Serverless: New Vector Database with up to 50x lower cost(pinecone.io)
2 points by gk1 3y ago|0 comments
610.
Pinecone: Build Knowledgeable AI(pinecone.io)
1 points by gk1 3y ago|0 comments
611.
Vector search algorithms from Pinecone set new records(pinecone.io)
3 points by gk1 3y ago|0 comments
612.
by gk1 3y ago
Yes, see: https://www.pinecone.io/blog/hnsw-not-enough/
613.
by gk1 3y ago
Yes, most RAG is done with a vector database. Or something that approximates a vector database, like a traditional database with a vector-index add-on.
614.
by gk1 3y ago
This is really cool, thanks for making this and sharing with the community!
615.
What I Learned from Trying(jxnl.github.io)
4 points by gk1 3y ago|0 comments
616.
Streaming RAG Applications (video)(youtube.com)
1 points by gk1 3y ago|0 comments
617.
Generative AI and Vector Databases [video](youtube.com)
3 points by gk1 3y ago|0 comments
618.
LangChain AI Handbook(pinecone.io)
2 points by gk1 3y ago|0 comments
619.
LangChain Expression Language Explained(pinecone.io)
3 points by gk1 3y ago|1 comments
620.
Bedrock Computer Gal(bedrock.computer)
4 points by gk1 3y ago|0 comments
621.
Pinecone's CEO is on a quest to give AI something like knowledge(zdnet.com)
2 points by gk1 3y ago|0 comments
622.
Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs(arxiv.org)
1 points by gk1 3y ago|0 comments
623.
Working with Pinecone at Scale(pinecone.io)
2 points by gk1 3y ago|0 comments
624.
Getting Started with Mixtral 8X7B(pinecone.io)
3 points by gk1 3y ago|0 comments
625.
NeMo Guardrails: Prevent Unwanted Chatbot Behavior(pinecone.io)
1 points by gk1 3y ago|0 comments
626.
Awesome RAG(github.com)
2 points by gk1 3y ago|0 comments
627.
Delaying AI Regulation Won't Help Anything(aisummaries.substack.com)
1 points by gk1 3y ago|1 comments
628.
Scaling AI Applications with Kubernetes and Pinecone(pinecone.io)
1 points by gk1 3y ago|0 comments
629.
by gk1 3y ago
As another signal, check out this report by Streamlit, which shows the popularity of different vector databases among Streamlit apps: https://state-of-llm.streamlit.app/#third Faiss and Pinecone are at the top (disclosure:
630.
LangChain Expression Language Explained(pinecone.io)
2 points by gk1 3y ago|0 comments

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