The integration of neural networks into steelmaking has revolutionised process control, quality assurance and energy efficiency across primary steelmaking routes. These data-driven models are deployed ...

Continual learning refers to the capacity of neural networks to acquire knowledge from a stream of non-stationary data, preserving earlier competencies while adapting to new tasks. Unlike conventional ...

Gilead Sciences uses graph neural networks and graph databases to reveal hidden fraud networks and ensure patient's safety.

Researchers from Spain’s Valencia Polytechnic University have developed a novel method for forecasting the power generation of PV systems. Its novelty lies in developing a hyperparameter optimization ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, is exploring a federated training framework for hybrid ...

Biologically plausible learning now reaches 96.7% on MNIST and 61.7% on CIFAR-10 without backpropagation, as Sakana AI demonstrates brain-faithful training on convolutional networks for the first time ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Spread the loveImagine a future where satellites don’t just orbit our planet, but actively think, adapt, and manage ...

Image courtesy by QUE.com The Convergence of Machine Learning and Material Science The global transition toward sustainable ...