In this presentation, Superlinked explored the challenges of building vector search systems tailored for complex data. They emphasize the importance of effectively managing various data types beyond simple text, such as numbers and structured information commonly found in databases. The session highlights practical solutions for creating custom embedding models that enhance data ingestion and querying. Attendees can access valuable resources, including an open-source database comparison table and GitHub repository for hands-on experimentation. The talk aims to equip community members with insights and tools to harness vector search technology for real-world applications.
More info: "Superlinked is a framework and soon a cloud service that helps AI & Data teams build vector embedding-powered software across RAG, Search, Recommendation Systems and Analytics. It is specifically focused on constructing custom data & query embedding models from pre-trained components, cutting down on time-to-market and the amount of compute required for evaluation and for production."
