Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Graphs are everywhere around us. Your social network is a graph of people ...
Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, ...
Franz Inc., an early innovator in AI and leading supplier of graph database technology, is releasing AllegroGraph 7.2, providing organizations with essential data fabric tools, including graph neural ...
Guangzhou Haofang Automotive Parts Co., Ltd. and Guangzhou Qianlang Technology Co., Ltd. recently announced the successful acquisition of a patent titled "An Intelligent Detection Method for Defective ...
The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...
Recently, Zhongzhexin Technology Consulting Co., Ltd. applied for a patent titled "An AI-based Method and System for Identifying Production Risk Hazards in Enterprises," indicating the deep ...
Graph neural networks (GNNs) are a relatively recent development in the field of machine learning. Like traditional graphs, a core principle of GNNs is that they model the dependencies and ...
Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping ...
Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...
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