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Struggling to figure out where to store AI embeddings? In this tutorial, we show how to use PostgreSQL with PGVector to store and ...

Check out Supabase: https://supabase.plug.dev/qnxeTMY ❤️ Get 40% OFF CodeCrafters: ...

An architecture session, contrasting the layout of Vespa with that of more familiar search engines like Elasticsearch. Explains how ...

Unstructured data makes up more than 80% of enterprise data and traditional search tools just can't keep up. In this episode of ...

... https://wpengine.com/smart-search/ Managed Vector Database: https://wpengine.com/managed-vector-database/ Smart Search ...

Watch tech videos https://www.usatamilan.com Artificial Intelligence - https://youtu.be/z-vBHbourKs?si=tHdeGTxxjD6OM5_F LLM ...

Breaking down Retrieval-Augmented Generation (RAG)—a powerful AI technique that enhances large language models (LLMs) ...

Learn the concept clearly in under 1 minutes, explained step-by-step with examples! About MLQs Café Welcome to MLQs Café ...

Devant offers a user-friendly way to quickly set up your knowledge base connecting a vector database and embedding model of ...

Learn from Rody Davis, Senior Developer Relations Engineer at Google, how to query and embed documents using SQLite and ...

Retrieval Augmented Generation (RAG), similar to the artistry of Remy’s Ratatouille, combines the brilliance of Large Language ...

Vector databases are a core building block of modern AI systems — from semantic search to RAG and AI agents. In this video, we ...

From R+AI 2025, hosted by R Consortium Mark Hornick, Senior Director, Oracle Machine Learning Sherry LaMonica, Consulting ...

Vector Databases: Performance and Applications The meeting focused on discussing vector databases and their applications.

AI applications are changing how we use databases, and vector data is at the center of this change. By enabling semantic search ...

... Fully local - no internet required after setup ⚡ Fast retrieval with persistent vector database ⏰ Timestamps: 00:00 Introduction ...

... gradually move into: Vector databases, Hybrid Search, RAG, LangChain, AI Agents, Memory systems, MCP, and A2A protocols.