What was once experimental research is now becoming operational backbone across modern energy systems. In the editorial ...

Read more about Artificial intelligence boosts financial forecasting accuracy in banking sector on Devdiscourse ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Choosing the right method for multimodal AI—systems that combine text, images, and more—has long been trial and error. Emory ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

Scientists develop a forecasting system that predicts high-risk windows and regions for solar superflares, using 50 years of X-ray data and machine learning techniques.

A team of scientists from around the world has created the first system that can predict when and where extremely powerful ...

A growing body of peer-reviewed research is giving scientists new tools to isolate the distinct climate signals left behind by volcanic mega-eruptions and extreme wildfires, two forces that can alter ...

Inflation, labor shortages, and rising operating costs have become persistent challenges for businesses and communities across the United States. Yet many of the decisions that shape these ...

We present a knowledge‐guided machine learning framework for operational hydrologic forecasting at the catchment scale. Our approach, a Factorized Hierarchical Neural Network (FHNN), has two main ...

The polynomial regression model enables counterfactual analysis by projecting what costs would have been without FinOps interventions, allowing rigorous attribution of savings. finops-ev-telematics/ ...