Geeky Gadgets

Llama 2 Retrieval Augmented Generation (RAG) tutorial

If you are interested in learning more about how to use Llama 2, a large language model (LLM), for a simplified version of retrieval augmented generation (RAG). This guide will help you utilize the ...
dbta

Beyond RAG basics: Strategies and best practices for implementing RAG

Join DBTA and Elastic as we explore advanced techniques in retrieval augmented generation (RAG). This talk provides developers, data scientists, and AI enthusiasts with essential insights to elevate ...

Most RAG systems don’t understand sophisticated documents — they shred them

Standard RAG pipelines treat documents as flat strings of text. They use "fixed-size chunking" (cutting a document every 500 ...
ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
InfoWorld

How to run RAG projects for better data analytics results

RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid. The arrival of generative AI-enhanced business intelligence (GenBI) for enterprise ...
Geeky Gadgets

Build advanced AI agents and assistants using Python

The guide provides a tutorial on building an advanced artificial intelligence (AI) agent using Python and Retrieval Augmented Generation (RAG). The AI agent is capable of utilizing various tools and ...
VentureBeat

Vectorize debuts agentic RAG platform for real time enterprise data

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now While vector databases are now increasingly ...