Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

New research shows Americans' economic circumstances shape their democratic values more than political ideology when forced ...

AI has evolved significantly, shifting from narrow, task-specific automation to advanced Cognitive Intelligence Platforms ...

The paper addresses the AI shutdown problem, a long-standing challenge in AI safety. The shutdown problem asks how to design AI systems that will shut down when instructed, will not try to prevent ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their applications in improving industrial efficiency and flexibility. It also ...

Road networks are critical public assets that must be monitored, modeled, and maintained with rigor and efficiency. As agencies face heavier traffic, ...

Combining microscopy and machine-learning techniques leads to faster, more precise analyses of critical coating materials ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

The U.S. Army created a new AI and machine learning officer career field, launching initial selections through VTIP in 2026.