Foundation of Compound AI Meetup Kicking Off, More LanceDB Integrations Community contributions 💡Dspy now works with LanceDB. LanceDB helps DSPy by quickly storing and retrieving information. This lets DSPy find relevant details faster, making prompts
Implement contextual retrieval and prompt caching with LanceDB Decrease chunk retrieval failure rate by 35% to 50% Have you ever worked on a task where your users search in one language and the
Late interaction & efficient Multi-modal retrievers need more than a vector index A lot has happened in the last few months in AI. Let's look at what's new with document retrieval. Try this
New Lance v0.16.1 Release, Random Access I/O, Hybrid Search+Reranking Report 🔥New release of Lance v0.16.1🔥 Lance v0.16.1 brings new features to help manage versions and Lance file format editions, a new
Training a Variational AutoEncoder from scratch with Lance file format Autoencoders encode an input into a latent space and decode the latent representation into an output. The output is often referred to as the reconstruction,
Multi document agentic RAG: A walkthrough 💡This is a community post by Vipul Maheshwari Agentic RAG (Retrieval-Augmented Generation) brings a notable improvement in how information is managed. While traditional RAG systems
Lance v0.16.1 Feature Roundup In Lance v0.16.1 we introduced several new features, implemented by a combination of LanceDB engineers and community contributors. Lance is an OSS project
Improve (almost) every retriever with LanceDB hybrid search and Reranking Retrieval is a key component of any type of recommender system, including RAG. The quality of responses generated by chatbot can only be as good
GraphRAG: Hierarchical approach to Retrieval Augmented Generation 💡This is a community blog by Akash Desai What is RAG? Retrieval-Augmented Generation (RAG) is an architecture that combines traditional information retrieval systems with large
The case for random access I/O One of the reasons we started the Lance file format and have been investigating new encodings is because we wanted a format with better support
My summer internship experience at LanceDB I'm Raunak, a master's student at the University of Illinois, Urbana-Champaign. This summer, I had the opportunity to intern as a
GraphRAG, Full-Text Search, LanceDB+Character.AI 🔥LanceDB as the Local Vector Database of Choice of GraphRAG🔥 Microsoft Research open sourced their GraphRAG project last week, and we are excited that the
