This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

With exploitation of vulnerabilities taking just days, preemptive security must be the new model for defenders.

Abstract: Nonlinear model predictive control (NMPC) algorithms have been widely used in autonomous vehicle trajectory tracking, yet their performance is primarily limited by the accuracy of the ...

Researchers at Pacific Northwest National Laboratory used artificial intelligence to analyze protein nanoribbons, pointing to potential design rules tied to peptide length and secondary structure. The ...

Abstract: The high performance of conventional model predictive control (CMPC) for electric drives depends on the fidelity of the machine’s parametric model. However, the parameters of the interior ...

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

H2O.ai, a pioneer in sovereign AI and the world’s leading agentic, highly accurate predictive AI company, today announced its openly available H2OVL Mississippi visual-language multimodal models has ...

Executive Summary - Artificial intelligence has moved from research laboratories into deployed defense systems: autonomous ISR platforms, ...

Entrepreneur Frank Giaoui has spent decades at the intersection of law, technology and economics, and discusses the benefits and risks of using AI in the industry.

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

Researchers at Mass General Brigham have developed a series of artificial intelligence (AI) tools that uses machine learning ...

“Industrial AI must start with trusted data,” said Steve Mason, COO of Canary Labs. “Our historian has long been the foundation for operational visibility. By natively integrating with SORBA.ai’ SORBA ...