High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

The technology enables ApplyBoard to implement a "traffic light" system that prioritizes applications for human review based on confidence scores. High-confide ...

Some of the most consequential breakthroughs in American healthcare are not new drugs or devices. They are quieter ...

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

Machine learning reveals widespread integrity concerns in cancer studies, highlighting paper mill risks and why publishers must strengthen research oversight.

This repository contains the code and data associated with the research paper: "Automated Regression Workflow for Interpretable Deflection Prediction in Bio-Inspired Laminated Composite Plates" Shakti ...

A new machine learning tool has identified more than 250,000 cancer research papers that may have been produced by so-called "paper mills." Developed by QUT researcher Professor Adrian Barnett, from ...

What is the one thing common across all PC brands today? The promise of AI which can lead to faster workflows, smarter software, and machines that can “think locally”. Almost every brand is busy ...