Strike Graph, the AI-native compliance management platform, today celebrates the growing adoption of Enterprise Workspaces, a new capability that enables organizations to govern compliance across ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.

Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.

Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating ...

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 ...

This page assumes you are already familiar with the content of Introduction to visualization; in particular, you should already understand the sequence graph representation used. Right now you may be ...

Enables Real-Time, Zero-ETL Graph Queries on the Databricks Data Intelligence Platform Databricks Managed Iceberg Tables, launching in Public Preview at this year’s Data + AI Summit, offers full ...

When Daimler Truck Holding AG began the long and complex process of separating from Mercedes-Benz Group AG in 2021, it faced a daunting problem. Decades of tightly interwoven information technology ...

The cybersecurity industry loves a good quote. At every conference, buried among the slide decks littered with questionable quotes from Sun Tzu's Art of War, you will occasionally strike gold and see ...