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Artificial Neural Networks Decode Brain Activity during performed and imagined Movements

In order to achieve better brain signal transmission quality, the researchers apply contact gel. Credit: Michael Veit

In order to achieve better brain signal transmission quality, the researchers apply contact gel. Credit: Michael Veit

Several groups from the Freiburg excellence cluster BrainLinks-BrainTools led by neuroscientist Dr. Tonio Ball are showing how ideas from computer science could revolutionize brain research. They illustrate how a self-learning algorithm decodes human brain signals that were measured by an electroencephalogram (EEG). It included performed movements, but also hand and foot movements that were merely thought of, or an imaginary rotation of objects...

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No more Burning Batteries? Scientists turn to AI to create safer Lithium-ion batteries

No more burning batteries? Stanford scientists turn to AI to create safer lithium-ion batteries

Evan Reed, assistant professor of Materials Science & Engineering at Stanford, and graduate student Austin Sendek are using artificial intelligence to develop safer batteries. Credit: L.A. Cicero/Stanford News Service

Scientists have spent decades searching for a safe alternative to the flammable liquid electrolytes used in lithium-ion batteries. Stanford University researchers have identified nearly 2-dozen solid electrolytes that could someday replace the volatile liquids used in smartphones, laptops and other electronic devices. The results, based on techniques adapted from artificial intelligence (AI) and machine learning, are published in the journal Energy & Environmental Science.

“Electrolytes shuttle lithium ions back and forth between the battery’s positive and negative electrodes...

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Researchers’ Discovery of new Verbal Working Memory architecture has implications for AI

The neural structure we use to store and process information in verbal working memory is more complex than previously understood, finds a new study by NYU researchers—a discovery that has implications for the creation of artificial intelligence (AI) systems, such as speech translation tools. (c)iStock/NicoElNino

The neural structure we use to store and process information in verbal working memory is more complex than previously understood, finds a new study by NYU researchers—a discovery that has implications for the creation of artificial intelligence (AI) systems, such as speech translation tools. (c)iStock/NicoElNino

The neural structure we use to store and process information in verbal working memory is more complex than previously understood, finds a new study by New York University researchers. It shows that processing information in working memory involves 2 different networks in the brain rather than one—a discovery that has implications for the creation of artificial intelligence (AI) systems, such as speech translation tools.

“Our results show there are at least two brain networks th...

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