Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

Hitachi expanded its HMAX industrial AI platform on September 3, 2026, adding HMAX Data Fabric -- a knowledge-graph system ...

In recent years, knowledge graphs have become an important tool for organizing and accessing large volumes of enterprise data in diverse industries — from healthcare to industrial, to banking and ...

Our past columns have emphasized repeatedly that modeling is the single most important activity in mechatronics, which is becoming the design process of choice for successful multidisciplinary systems ...

Jedify, the autonomous context graph for data-intensive agentic applications and workflows, today announced the findings of a new benchmark study on context graph architectures, which pre-encode ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way ...

Pretreatment CT-based radiomics and machine learning models for predicting treatment response in lung cancer: A diagnostic test accuracy meta-analysis. This is an ASCO Meeting Abstract from the 2026 ...