Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping ...

Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...

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 ...

A new AI Drug Discovery tool called PDGrapher can predict more accurate drug combinations up to 25 times faster than previous ...

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 ...

Artificial digital neural network concept. Neural network software enables the implementation, deployment and training of artificial neural networks. These networks are designed to mimic the behavior ...

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of robotic arms to work together faster and smarter in busy industrial settings, ...