InfoQ

Generative Search: Practical Advice for Retrieval Augmented Generation (RAG)

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
Geeky Gadgets

How to build Large Language Models (LLM) and RAG pipelines using open-source models

In the world of artificial intelligence, the ability to build Large Language Model (LLM) and Retrieval Augmented Generation (RAG) pipelines using open-source models is a skill that is increasingly in ...
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

New DeepMind study reveals a hidden bottleneck in vector search that breaks advanced RAG systems

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...
InfoWorld

What is retrieval-augmented generation? More accurate and reliable LLMs

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...
datanami.com

Couchbase Bolsters GenAI Development with Vector Search, RAG

The latest release of the Couchbase database adds support for vector search, integration with Llamaindex and LangChain, and support for retrieval-augmented generation (RAG) techniques, all of which ...
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 ...