The intersection of large language models and graph databases is one that’s rich with possibilities. The folks at property graph database maker Neo4j today took a first step in realizing those ...

Graph neural networks (GNNs) have rapidly emerged as a central methodology for analysing complex datasets presented as graphs, where entities are interconnected through diverse relationships. By ...

There’s been a debate of sorts in AI circles about which database is more important in finding truthful information in generative AI applications: graph or vector databases. AWS decided to leave the ...

The metric dimension is a key invariant in graph theory that encapsulates the minimal number of reference points, or “resolving sets”, required to uniquely determine the position of each vertex within ...

(MENAFN- GetNews) NebulaGraph v5.2 unlocks AI-ready graph intelligence: 100x faster path queries, native hybrid search (graph + vector + text), and real-time subgraph compute for smarter, faster AI.

TigerGraph, the enterprise AI infrastructure and graph database leader, is releasing its next generation graph and vector hybrid search, delivering the industry's “most advanced” solution for ...