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Local LLM setup: how to use RAG and an embedding model to stop wasting context

Local LLMs are fantastic, and they keep getting better at a staggering pace. I have non-negotiable reasons for preferring a local setup over relying on cloud giants like Claude or ChatGPT. Because of ...
Searchenginejournal.com

Introduction To Vector Databases And How To Use AI For SEO

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...
InfoWorld

Using PostgreSQL as a vector database in RAG

PostgreSQL with the pgvector extension allows tables to be used as storage for vectors, each of which is saved as a row. It also allows any number of metadata columns to be added. In an enterprise ...
VentureBeat

Google's mobile-ready EmbeddingGemma ranks highest in embedding leaderboard among small parameter models

Google’s open-source Gemma is already a small model designed to run on devices like smartphones. However, Google continues to expand the Gemma family of models and optimize these for local usage on ...
InfoWorld

Building LLM applications with vector search in Azure Cognitive Services

Tools like Semantic Kernel, TypeChat, and LangChain make it possible to build applications around generative AI technologies like Azure OpenAI. That’s because they allow you to put constraints around ...