Existing graph-based retrieval-augmented generation (RAG) systems represent knowledge with binary relations and rely primarily on semantic similarity for retrieval. This design struggles with ...

We are in an exciting era where AI advancements are transforming professional practices. Since its release, GPT-3 has “assisted” professionals in the SEM field with their content-related tasks.

The problem: Generative AI Large Language Models (LLMs) can only answer questions or complete tasks based on what they been trained on - unless they’re given access to external knowledge, like your ...

While Large Language Models (LLMs) like LLama 2 have shown remarkable prowess in understanding and generating text, they have a critical limitation: They can only answer questions based on single ...

Knowledge graph startup Diffbot Technologies Corp., which maintains one of the largest online knowledge indexes, is looking to tackle the problem of hallucinations in artificial intelligence chatbots ...

Google researchers introduce Procedural Graphs, a self-evolving framework that ranked first in 21 of 24 benchmark settings ...

unstructured data such as pdfs, text documents, YouTube videos, and web pages, into a knowledge graph stored in Neo4j, promising much better accuracy than simple RAG (Retrieval-Augmented Generation).

This article has been edited and created by AI.Today's highlights on GitHub Trending in the Python and RSS categories focus ...

With the widespread application of space traveling wave tube amplifiers (TWTAs) as core final-stage amplification devices in satellite communication ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Lily Mara explains how to avoid high-risk ...