Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...

A fundamental challenge in advancing AI research lies in developing systems that can autonomously perform structured reasoning and dynamically expand domain knowledge. Traditional AI models often rely ...

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Graph neural networks (GNNs) have emerged as powerful tools for capturing complex interactions in real-world entities and finding applications across various business domains. These networks excel at ...

Identity management for cybersecurity is inherently a complex graph problem due to the vast, dynamic, and interconnected nature of modern IT environments. The Fast Company Executive Board is a private ...

A paper posted online in March 2023 has presented the first substantial progress in a half-century on one of the fundamental questions in the overlap between mathematics and computer science: how to ...