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 ...
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 ...
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 ...
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 ...
Business Wire

Qdrant Launches Groundbreaking Pure Vector-Based Hybrid Search, Setting Higher Standards for RAG and AI Applications

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the leading high-performance open-source vector database, today announced the launch of BM42, a pure vector-based hybrid search approach that delivers more ...
InfoWorld

Qdrant unveils vector-based hybrid search for RAG

Open-source vector database provider Qdrant has launched BM42, a vector-based hybrid search algorithm intended to provide more accurate and efficient retrieval for retrieval-augmented generation (RAG) ...
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 ...
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 ...
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 ...