Researchers affiliated with universities in China and Singapore have devised a technique to make stolen knowledge graph data ...

As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large.

GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM prompting and summarization into a ...

Coding prowess took center stage in the Davis Center’s grand Maple ballroom as the annual Computer Science Fair returned with over 90 unique projects competing for top honors in 4 different categories ...

When I first wrote “Vector databases: Shiny object syndrome and the case of a missing unicorn” in March 2024, the industry was awash in hype. Vector databases were positioned as the next big thing — a ...

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 ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive ...