EurekAlert! In the Spotlight - Artificial Intelligence

Welcome to In the Spotlight, where each month we shine a light on something exciting, timely, or simply fascinating from the world of science.

This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.

Latest News Releases

Updates every hour. Last Updated: 3-Nov-2026 13:17 ET (3-Nov-2026 18:17 GMT/UTC)

13-Jul-2026

As national drought deepens, a new AI model helps balance water demands

Virginia Tech
Peer-Reviewed Publication

Virginia Tech researchers have developed an artificial intelligence (AI) model designed to help policymakers manage growing competition between agriculture and semiconductor manufacturing, as drough strains water supplies across the United States.

Journal: Journal of Water Resources Planning and Management

13-Jul-2026

Consumers perceive AI-designed products as less sustainable than human-designed alternatives

University of South Florida
Peer-Reviewed Publication

Consumers consistently perceive products designed by artificial intelligence as less sustainable than identical products designed by humans, according to new research published in the Journal of the Academy of Marketing Science. The findings suggest that consumers evaluate sustainability not only by a product's environmental performance, but also by whether they believe genuine human care went into its design.

Journal: Journal of the Academy of Marketing Science

13-Jul-2026

New method aims to keep kids safe from illegal AI-generated content

Massachusetts Institute of Technology
Reports and Proceedings

Researchers developed an evaluation procedure that tests generative AI models for harmful capabilities without generating outputs. This could enable auditors to identify open-source models that have been adapted to produce illegal content, like child sexual abuse material (CSAM).

Funder: Bridgewater AIA Labs Research Fellowship

13-Jul-2026

Study finds carbon capture and storage could help curb emissions from AI-driven data center boom

Rice University
Peer-Reviewed Publication

As artificial intelligence accelerates demand for computing power across the U.S., a new study co-authored by Hon Chung Lau, adjunct professor in the Department of Chemical and Biomolecular Engineering at Rice University and founder of Low Carbon Energies LLC, has found that carbon capture and storage could play a major role in limiting the climate impact of data centers.

Journal: Energy & Fuels

13-Jul-2026

From algorithms to outcomes: AI is rewriting healthcare in the Southeast

Medical University of South Carolina
Grant and Award Announcement

A new collaboration between the Medical University of South Carolina (MUSC) and the University of Florida (UF) is taking a cutting-edge approach to transforming healthcare research and outcomes across the Southeast. The Southeastern Health AI Consortium supports interdisciplinary teams addressing major regional health challenges by leveraging artificial intelligence (AI), large clinical datasets and combined institutional expertise. Backed by $2.5 million in funding, the projects span a broad array of focus areas that affect South Carolinians, Floridians and the broader Southeast region, including mental health, maternal health, stroke, brain health and advanced therapies.

13-Jul-2026

WVU engineers develop AI system to speed satellite tracking of wildfires

West Virginia University
Peer-Reviewed Publication

A new artificial intelligence system developed by West Virginia University engineers could help firefighters respond to wildfires sooner by enabling satellites to detect blazes and automatically adjust their positions for continued monitoring.

Journal: Journal of Aerospace Information Systems
Funder: NASA West Virginia Established Program to Stimulate Competitive Research

13-Jul-2026

[Research Article] Context-aware landmark recognition in location-based augmented reality: A switching framework with a MobileNet backbone for cultural heritage engagement

Big Earth Data
Peer-Reviewed Publication

A new study published in Big Earth Data proposes a switching-based pervasive augmented reality (AR) framework that integrates location-based AR (LBAR), deep learning (DL), and context-awareness to improve landmark recognition and cultural heritage engagement in smart cities. Through end-to-end implementation and real-world testing in Tehran, the framework significantly enhanced landmark detection accuracy compared with conventional LBAR systems, while demonstrating high user satisfaction and potential for sustainable urban planning. The dataset used in this study is not shared publicly due to copyright restrictions. However, to support reproducibility, all source code developed for data preprocessing, model training, and evaluation has been made openly available at https://github.com/mhvahidnia/tehran-img-classification-webapp/.

Journal: Big Earth Data