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: 1-May-2026 11:16 ET (1-May-2026 15:16 GMT/UTC)

9-Feb-2026

ADHD symptoms predict distinct creative problem-solving styles and superior solving ability

Drexel University
Peer-Reviewed Publication

Individuals with strong attention-deficit/hyperactivity disorder (ADHD) symptoms, related to inefficient cognitive executive function, may experience a surprising benefit: a natural inclination toward a type of intuitive thinking that supports creative breakthroughs, according to a new study from Drexel University researchers.

Journal: Personality and Individual Differences

8-Feb-2026

Generating realistic 3D sound from ordinary videos using AI and visual cues

The University of Electro-Communications
Peer-Reviewed Publication

Researchers have developed an AI technique that adds realistic 3D sound to ordinary videos recorded with a single microphone. By using visual information in the video, the system makes sounds appear to come from the correct directions, even when no spatial audio was originally recorded.

6-Feb-2026

Artificial light is reshaping caracal behavior

University of Rhode Island
Peer-Reviewed Publication

A new study led by URI Ph.D. student Christopher Hickling shows that artificial light at night alters the movement and foraging behavior of caracals on South Africa’s Cape Peninsula, revealing how urban lighting impacts wildlife behavior. Hickling also studies bobcats, the caracals’ wild cat equivalent in Rhode Island, for the University’s statewide Bobcat Project.

Journal: Science of The Total Environment

6-Feb-2026

Deep learning-based discovery of tetrahydrocarbazoles as broad-spectrum antitumor agents and click-activated strategy for targeted cancer therapy

Compuscript Ltd
Peer-Reviewed Publication

https://doi.org/10.1016/j.apsb.2025.10.005

This new article publication from Acta Pharmaceutica Sinica B, discusses the deep learning-based discovery of tetrahydrocarbazoles as broad-spectrum antitumor agents and click-activated strategy for targeted cancer therapy.

6-Feb-2026

University of Phoenix research finds AI-integrated coursework strengthens student learning and career skills

University of Phoenix
Peer-Reviewed Publication

A study by University of Phoenix and published in Industry and Higher Education found that AI-integrated coursework and structured AI activities strengthens student learning and career skills.

Journal: Industry and Higher Education

6-Feb-2026

New artificial intelligence tool may help personalize ovarian cancer treatment from day one

University of Minnesota Medical School
Peer-Reviewed Publication

MINNEAPOLIS/ST. PAUL (02/09/2026) — Researchers from the University of Minnesota Medical School, in collaboration with Emory University and the Georgia Institute of Technology, have developed a new artificial intelligence (AI) biomarker tool that may help predict how ovarian cancer patients will respond to treatment at the time of diagnosis. The findings were published today in the British Journal of Cancer ReportsExternal link that opens in the same window.

Funder: Minnesota Ovarian Cancer Alliance, Randy Shaver Community Fund, American Cancer Society

6-Feb-2026

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

The Hong Kong Polytechnic University

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective at capturing relationships between nodes and edges in data, but often overlook higher-order, complex connections. To address this challenge, a research team at The Hong Kong Polytechnic University (PolyU) has developed a new heterogeneous graph attention network, revolutionising the modelling of complex relationships in graph-structured data. This innovation is poised to break through AI application limitations in fields such as neuroscience, logistics, computer vision and biology.

Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence