Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.

A new review shows how AI helps food companies predict formulation, processing, and sensory outcomes. AI does not ...

As integrated health technologies increasingly shape the future of heart failure management, this paper provides ...

AI researcher and JPMorgan Chase Software Engineer gains international recognition for research publications, reviewer ...

A team of researchers in Japan has developed an artificial intelligence tool called YORU that can identify specific animal ...

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...

Abstract: Accurate motion control in the face of disturbances within complex environments remains a major challenge in robotics. Classical model-based approaches often struggle with nonlinearities and ...

By merging telemetry data with machine learning, the advanced software platform detects issues early, reducing downtime and ...

The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...

RS offers an extensive selection of smart products optimized to support predictive maintenance strategies and improve ...

Waiting for alerts is obsolete — predictive engineering lets cloud systems see trouble coming and fix it before users ever ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...