A new “periodic table for machine learning,” is reshaping how researchers explore AI, unlocking fresh pathways for discovery. The framework, Information-Contrastive Learning (I-Con), connects diverse ...

Infrared optoelectronic functional materials are essential for applications in lasers, photodetectors, and infrared imaging, ...

Windows machine learning is one of the highlights of this year’s Microsoft annual developer event. The company is also paving ...

Mortgage servicing is a serious challenge for institutions striving for operational efficiency, regulatory compliance, ...

The core problem tackled by this research is the opaque nature of many high-performing AI models used in fraud detection.

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies ...

Researchers at Northwestern Engineering have developed a scientific machine learning framework that predicts and inversely designs the mechanical behavior of spinodal metamaterials – specially ...

Eric D. Boyd of responsiveX previews his VSLive! 2025 session at Microsoft HQ in August where he explains how Azure ML ...

The answer to 'What customer needs requires an AI solution?' isn’t always 'Yes.' LLMs are still expensive and not always accurate.

Adusupalli’s proposed framework applies continuous integration ... to inconsistencies and lags in updates. By leveraging machine learning and AI models, Adusupalli's framework identifies ...

With such an explosion of e-commerce ecosystem today, fraud detection and risk management have grown beyond a mere necessity. Online marketplaces that link buye ...