As artificial intelligence grows more powerful, its energy demands are rising rapidly—driven by massive data centers that many experts say are unsustainable. To address this challenge, UT San Antonio is launching a national initiative through its MATRIX AI Consortium to rethink how AI computing works.

Backed by funding from the National Science Foundation, the initiative—called THOR: The Neuromorphic Commons—will establish a publicly accessible national hub for neuromorphic computing. This brain-inspired approach mimics how human neurons process information, activating only when needed and using far less energy than traditional computers.

THOR will provide researchers nationwide with open access to the largest full-stack neuromorphic computing platform of its kind, accelerating experimentation while advancing more energy-efficient and sustainable AI technologies.

Korean researchers have developed key technology to ensure pedestrian safety at intersections, laying the foundation for a paradigm shift in traffic safety. This technology is expected to significantly reduce pedestrian accidents after being tested by local governments and commercialized in the future. ETRI announced that since October 8 in 2025, it has been conducting a demonstration of Korea’s first “predictive pedestrian safety AI service” at four major intersections in Cheonan. This service can predict pedestrian trajectories to prevent traffic accidents in advance.

Spatial skills develop early in life. We catch balls, pour drinks, ride escalators, and perform countless activities that require spatial awareness. What would happen if machines could emulate this 3D understanding of the world? University of Virginia assistant professor Lei Li is exploring this new frontier of AI at the University of Virginia's Spatial AI Lab.

Researchers from the Indian Institute of Technology Gandhinagar presented a scalable, automated framework for pollen identification using scanning electron microscopy images and machine learning. The team developed an open-access web-based application that organises pollen images and associated data. The computer vision framework provides a reproducible, adaptable solution for pollen analysis, improving speed and accuracy while minimising reliance on manual annotation. The study involves an interdisciplinary methodology with broad applications in domains ranging from plant taxonomy and biodiversity monitoring to agriculture, pollen allergies, and paleoecology.

OncoPRO is a next-gen symptom monitoring program designed to detect problems earlier, strengthen cancer patient safety and deliver data-driven care. The program demonstrates how digital infrastructure can bridge research and clinical operations and align oncology, survivorship and clinical trials.

An international team featuring faculty at Binghamton University, State University of New York has drilled the longest ever sediment core from under an ice sheet, providing a record stretching back millions of years that will help climate scientists forecast the fate of the ice sheet in our warming world.

Professor Jon Hathaway, a UT civil and environmental engineering professor, studies urban hydrology and how green infrastructure improves cities by reducing flooding and pollution. With a $2.6 million USFS grant, his interdisciplinary team built four low-cost gravel-tree stormwater systems in underserved Knoxville areas, pairing education, workforce training, and scalable designs.

University of Victoria researchers are shaping Canada’s quantum future