Researchers at the Nara Institute of Science and Technology and Osaka University have developed a computational model of how human emotions are formed. This system integrates body signals, sensory input, and language, forming emotional concepts that match the self-reported human emotional judgment with 75% accuracy. The findings highlight new ways of building emotionally aware artificial intelligence, with potential applications in mental health care, interactive robots, and assistive technologies.

A speech study by a research team from The University of Texas at El Paso has identified an underappreciated aspect of speech in English and Spanish speakers that could lead to improvements in artificial intelligence spoken dialogue systems.

The SETI Institute announced that alliant Global CEO, Dhaval Jadav, joined its Board of Directors. Dhaval brings a deep lifelong passion for space science, a strong commitment to STEM education, and a shared belief in the SETI Institute’s mission to explore one of humanity’s most profound questions: Are we alone in the universe?

This marks the beginning of a strategic partnership that gives the SETI Institute the ability to leverage alliant’s resources and AI capabilities in the search for extraterrestrial life.

“As a kid nothing got me more excited to learn about space than the thought of extraterrestrials being out there,” said Dhaval. “I think we’ve lost some of that sense of wonder, the curiosity that drives people to look beyond their screens and ask big questions about the universe. I wholeheartedly believe in the SETI Institute’s mission, and I hope alliant can help the SETI Institute be a beacon that rekindles that curiosity and inspires people to seek answers to life’s biggest mysteries.”

One of the primary challenges with prosthetic hands is the ability to properly tune the appropriate grip based on the object being handled. In Nanotechnology and Precision Engineering, researchers in China have developed an object identification system for prosthetic hands to guide appropriate grip strength decisions in real time. Their system uses an electromyography sensor at the user’s forearm to determine what the user intends to do with the object at hand.