This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

Study authors Hunter Schweiger (left) and Ash Robbins. Imagine balancing a ruler vertically in the palm of your hand: you have to constantly pay attention to the angle of the ruler and make many small ...

Gambling addiction, which affects many service members and veterans, has been approved for Department of War research funding. The Fiscal 2026 Consolidated Appropriations Act, signed into law by ...

Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that ...

All the telltale clues a top Supreme Court justice is considering an exit Eden Hazard has become a taxi driver! Lisa Phillips was in her twenties when she went to Jeffrey Epstein’s island - now in her ...

The Kadena Air Base game room in Japan features more than 80 entertainment slot machines. (Senior Airman Omari Bernard/U.S. Air Force) Gambling addiction is now a topic that researchers can study ...

Benefits-eligible employees can earn an additional $150 wellness incentive by completing the optional online learning module in 2026. This course, “Your Path to Prescription Drug Benefits,” is ...

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...

As the fall semester came to a close, Andrew Heiss, an assistant professor in the Department of Public Management and Policy at the Andrew Young School of Policy Studies at Georgia State University, ...

Niral Shah does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...