Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Data analysis is no longer a specialist skill reserved for analysts. It now supports finance, trading, ecommerce, marketing, ...

Abstract: Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. However, their application to multi-relational graph anomaly ...

The tech giant says a breakthrough in data center networking has dramatically accelerated the flow of information through its massive cloud infrastructure. The new technology hinges on a “quasi-random ...

Microsoft Sentinel adds custom graphs to visualize security data and attack relationships. Graph-based analysis helps detect threats, map attack paths, and identify anomalies. Fabric-powered ...

Got Tech, Data, AI and Media, and not afraid to use them. Gartner highlighted Data Management, Semantic Layers, and GraphRAG as Top Trends in Data and Analytics for 2026. Startups and incumbents in ...

Have you ever gone to sleep with visions of gelatin bubbles dancing in your head? What about information on 70 million financial securities and 40,000 data fields? Marvin Ward knows what both are like ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...