A new Multi-University Research Initiative (MURI) funded by the U.S. Army Research Office aims to unlock the mysteries of the brain’s hidden half. Multidisciplinary teams of scientists will investigate astrocytes and their potential as models for next-generation AI systems. The MURI is led by University of Maryland Physics Professor Wolfgang Losert, Chemistry and Biochemistry Professor John Fourkas, Electrical and Computer Engineering Assistant Professor Sahil Shah and Associate Professor Behtash Babadi; and Claremont Colleges Associate Professor of Physics Sarah Marzen.

The experimental technology, developed at an Applied Research Center at the State University of Campinas, is already accurate in over 80% of analyses. The research was presented during FAPESP Week London.

researchers at Virginia Tech have developed an “acoustic atom” — a chip-scale device that traps and controls sound waves in ways that mimic the behavior of real atoms. Long term, these advances could influence technologies connected to quantum artificial intelligence (AI), telecommunication, medical imaging, GPS, and more.

During FAPESP Week London, expert Fernando Landgraf pointed out that, beyond its mineral potential, the country must master the stages of refining and producing inputs that are globally contested by the United States and China.

SAN ANTONIO — June 3, 2026 — Southwest Research Institute (SwRI) is studying impact flashes generated by high-speed collisions. One application of understanding impact flashes is to remotely identify what materials are involved in the collisions. Advances in understanding the optical impact flashes can be highly beneficial for missile defense, making it possible to determine the composition of an intercepted missile and its payload. The work could also aid scientists in identifying the origins of meteorites or asteroids impacting surfaces, based on their composition.

A new UN University report warns that artificial intelligence is driving rapidly escalating environmental costs far beyond electricity use alone, including major impacts on water consumption, land use, carbon emissions, mineral extraction, and e-waste. The report estimates AI-related electricity demand could nearly triple by 2030, with associated emissions comparable to those of entire industrialized nations. It also highlights widening global inequities, with environmental burdens concentrated in regions supplying minerals and hosting infrastructure while benefits flow elsewhere. The authors call for urgent international action, including transparency standards, efficiency-focused design, resource limits, sustainable infrastructure planning, and stronger environmental governance across the full AI lifecycle.