InfoQ

Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Martin Kleppmann, an associate professor at ...
techtimes

How RAG and Vector Databases Improve LLMs

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...
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 ...
Forbes

How RAG Continues To ‘Tailor’ Well-Suited AI

AI solves everything. Well, it might do one day, but for now, claims being lambasted around in this direction may be a little overblown in places, with some of the discussion perhaps only (sometimes ...
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 ...
CIO

Vector Database vs. Knowledge Graph: Making the Right Choice When Implementing RAG

Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency of a Vector DB, the goal remains clear—to harness the power of RAG systems and drive innovation, productivity, and ...
VentureBeat

Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...
Business Wire

KIOXIA AiSAQ™ Software Advances AI RAG with New Version of Vector Search Library

TOKYO--(BUSINESS WIRE)--In an ongoing effort to improve the usability of AI vector database searches within retrieval-augmented generation (RAG) systems by optimizing the use of solid-state drives ...
VentureBeat

The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

The vector database category is undergoing a shift in response to the needs of agentic AI. The retrieval-augmented generation (RAG)-to-vector database pipeline doesn't cut it anymore; agentic AI ...
InfoWorld

Using the Pinecone vector database in .NET

If you’re building generative AI applications, you need to control the data used to generate answers to user queries. Simply dropping ChatGPT into your platform isn’t going to work, especially if ...