Built to handle 500,000 collisions per second, the Electron-Ion Collider is integrating AI into everything from beam tuning ...

Abstract: The major objective of our research is to retrieve wave parameters from synthetic aperture radar (SAR) images during a tropical cyclone (TC) based on a machine learning method. In this study ...

A central challenge in recommendation systems is incentivizing exploration, encouraging users to select options that help the platform learn the information needed for better future decisions. In some ...

About You can be found in the Amazon Shopping app, mobile web, and desktop. On mobile, navigate to the Me tab, click on your ...

The promise of smart test is a data-chain problem before it is an algorithm problem. A device can pass every checkpoint and ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

This article was co-authored with Emma Myer, a student at Washington and Lee University who studies Cognitive/Behavioral Science and Strategic Communication. In today’s digital age, social media has ...

The leap between experimentation and scalable operationalization is where most organizations find that progress stops.

In a novel attempt to improve how large language models learn and make them more capable and energy-efficient, Stevens Institute of Technology researchers have devised an algorithm that improves AI ...

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — boosting MMLU scores by 18 points over human baselines.

For centuries, humans looked to seers and astrologers to determine fate. Today, we look to algorithms, and the loss of agency is the same.

Pushing against years of scepticism, an analysis suggests quantum computers may offer real advantages for running machine learning and similar algorithms in the near future ...