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 ...
Business Wire

New Vector Database in Salesforce Data Cloud Will Power AI, Analytics, and Automation Using LLMs with Business Data for Use Across the Einstein 1 Platform

Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot, ...
Risk.net

Regulatory impact analysis using LLMs, generative AI and vector databases

Learn how to safely and effectively integrate GenAI to transform regulatory analysis through practical application ...
InfoWorld

LlamaIndex review: Easy context-augmented LLM applications

“Turn your enterprise data into production-ready LLM applications,” blares the LlamaIndex home page in 60 point type. OK, then. The subhead for that is “LlamaIndex is the leading data framework for ...
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 ...
Communications of the ACM

Teaching LLMs to Give Better Answers

As a result, researchers are exploring ways to embed better logic into AI. The goal isn’t so much to make LLMs smarter; it’s ...