Graph neural networks (GNNs) have emerged as a versatile class of machine-learning models designed to process data structured as graphs, capturing relationships among entities through iterative ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Enlaye, a holistic artificial intelligence-enabled construction risk platform, has raised $5 million to expand its predictive ...

Nvidia acquires Kumo AI for $400M, boosting enterprise predictive models with graph neural networks and automation for global ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

In our view, higher-category theory, which possesses the highest degree of abstraction, is a second-level language relative ...