Retrieval-Augmented Generation (RAG) connects large language models to external knowledge sources so they can deliver up-to-date, source-backed answers. By retrieving relevant documents at query time, ...

Vector database pioneer Pinecone recognizes this and is pivoting to meet the specific needs of agentic AI. The company today ...

AI educators on YouTube and in tech media are highlighting methods that improve ChatGPT results through context-rich prompting and organized workflows. An XDA Developers feature described moving from ...

Artificial intelligence tools like ChatGPT are increasingly being explored in cancer care, but they can sometimes produce ...

Learn how to build and deploy custom AI agents in minutes using no-code automation, voice commands, and API integrations.

AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independent AI project, ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Retrieval Augmented Generation offers a robust framework for developing reliable and evidence- aligned artificial intelligence in dentistry. By integrating external knowledge sources with the ...

Retrieval-Augmented Generation (RAG) models often suffer from reward sparsity and inefficient credit assignment when optimized with traditional outcome-based Reinforcement Learning (RL).

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Retrieval-augmented generation is ...