Build AI-Supercharged RAG Apps with a Vector Database
Empower your apps with AI using vector databases. Learn hands-on techniques for enhanced search, generative AI integration, and improved model capabilities through open-source tools and technologies.
Qdrant: Open Source Vector Search Engine and Vector Database
Explore Qdrant, an open-source vector search engine and database. Learn its architecture, capabilities, and applications in machine learning and information retrieval.
Building Applications with RAG and LangChain on Google Cloud
Master building AI applications with RAG and LangChain on Google Cloud. Follow a hands-on demonstration of indexing data, creating a web interface, and deploying solutions for enhanced AI response accuracy.
Optimizing ColPali for Retrieval at Scale - From Theory to Practice
Discover how to optimize ColPali's multivector document retrieval system through efficient pooling techniques, achieving 12x faster search speeds while maintaining accuracy in RAG and Vision RAG applications.
A Deep Dive into Vector Search Technology and Tools
Explore vector search technology through practical demonstrations of ClickHouse, OpenSearch, and PGVector, learning how AI models convert text to vectors for enhanced contextual search capabilities.
Improving Accuracy of GenAI Apps with Azure Database for PostgreSQL - Advanced RAG Techniques
Master advanced RAG techniques in Azure PostgreSQL to enhance GenAI app accuracy through vector search, hybrid search, semantic ranking, and GraphRAG implementation for enterprise solutions.