A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of neurons give rise to specific human and animal behaviors. Many existing methods ...

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 ...

Designing materials that steer light is a slow kind of trial and error. Each candidate structure must be tested in computer ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining a deeper understanding of element formation in stellar events such as ...

Computational point-of-care sensors can significantly improve access to diagnostics by enabling rapid patient testing outside ...

Industrial sensing is a core technology for intelligent manufacturing. In recent years, utilizing artificial neural networks (ANNs) to improve ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

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

MCUs are opening the field for extreme edge development, unveiling a new age of possibilities and solutions — especially with ...