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 ...

A tandem neural network capable of inferring key physical parameters of semiconductor materials from simple transistor measurements has been developed, as reported by researchers from the Institute of ...

Neurologists use millisecond-level M/EEG tracking to prove the human brain and AI language models organize and predict language using parallel processing principles.

Computational point-of-care sensors can significantly improve access to diagnostics by enabling rapid patient testing outside centralized medical facilities. These tests rely on machine learning ...

“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 ...

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has ...

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 ...

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 ...

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 ...

Baseten Inc., a startup with a platform for running artificial intelligence inference workloads, is raising $1.5 billion in ...