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Blog posts tagged "RAG"

Hybrid search and reranking: a deeper look at RAG

Hybrid search and reranking: a deeper look at RAG

Many of us are familiar with the retrieval augmented generative AI (RAG) pattern for building agentic AI applications – like digital concierges, frontline support chatbots and agents that can help with basic self-service troubleshooting.  At a high level, the flow for RAG is fairly clear – the user’s prompt is augmented with some relevant

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Building an end-to-end Retrieval- Augmented Generation (RAG) workflow

Building an end-to-end Retrieval- Augmented Generation (RAG) workflow 

In this guide, we will take you through setting up a RAG pipeline. We will utilize open source tools such as Charmed OpenSearch for efficient search retrieval and KServe for machine learning inference, specifically in Azure and Ubuntu environments while leveraging silicons.

AI
Building optimized LLM chatbots with Canonical and NVIDIA

Building optimized LLM chatbots with Canonical and NVIDIA

The landscape of generative AI is rapidly evolving, and building robust, scalable large language model (LLM) applications is becoming a critical need for many organizations. Canonical, in collaboration with NVIDIA, is excited to introduce a reference architecture designed to streamline and optimize the creation of powerful LLM chatbots. T

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Building RAG with enterprise open source AI infrastructure

Building RAG with enterprise open source AI infrastructure

How to create a robust enterprise AI infrastructure for RAG systems using open source tooling?A highlight on how open source can help

Data Platform
What is RAG?

What is RAG?

RAG explained: is a technique that enhances generative AI models by utilizing external knowledge sources such as documents and extensive databases.

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