A guide to implementing semantic search for static websites using Amazon S3 Vector Buckets and Microsoft's Semantic Kernel for embedding generation.
A guide on preparing data for Generative AI using RAG, covering data embedding, chunking, and building effective data pipelines.
Argues that building a good search engine is more critical for effective RAG than just using a vector database, as poor retrieval misleads AI.
A guide on using Azure Database for PostgreSQL with the vector extension as a vector store for LLM applications, including setup and integration with LangChain.
Interview with Weaviate CEO Bob Van Luijt on building an open-source vector database, the rise of vector search, and the business of AI-first software.
A tutorial on building a Streamlit web UI for a semantic search application using Pinecone vector database and OpenAI embeddings.
A guide on using Redis as a vector database to store and query embeddings for semantic search, replacing Pinecone in a tech stack.
