Tag: RAG retrieval-augmented generation
Build Performant RAG Applications Using Couchbase Vector Search and Amazon Bedrock
Enhance generative AI with Retrieval-Augmented Generation using Couchbase Capella and Amazon Bedrock for scalable, accurate results.
A Step-by-Step Guide to Preparing Data for Retrieval-Augmented Generation (RAG)
MData gathering, chunking & embedding techniques for efficient Retrieval-Augmented Generation (RAG) with Scrapy, Python, and BAAI model.
Enhancing GenAI for Privacy and Performance: The Future of Personalized AI with Edge Vector Databases
This article focuses on the Centralized vs. Edge Compute paradigm, exploring why a cloud to edge database with vector capability will best address challenges on data privacy, performance, and cost-effectiveness
Develop Performant RAG Apps With Couchbase and Vectorize
The teams at Couchbase and Vectorize have been working hard to bring the power of Vectorize experiments to Couchbase Capella.
What are Foundation Models? (Plus Types and Use Cases)
This blog post will explain what foundation models are and how they work, along with providing information on types of models and how to train them.
An Overview of Retrieval-Augmented Generation (RAG)
This blog post provides an overview of retrieval-augmented generation, explaining how it's used, how to implement it, and more. Read now at Couchbase.
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