Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Machine learning has transformed tool condition monitoring by enabling non-invasive, data-driven assessment of cutting tool health. Modern systems deploy a range of sensors—vibration, cutting force, ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Find out how this structured machine learning roadmap called I-Con could lead to breakthroughs in AI. A new “periodic table for machine learning” is reshaping how researchers explore AI, unlocking ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials ...

Apple's machine learning researchers have worked on myriad ways to improve Apple Intelligence and other generative AI systems, as its research papers accepted by a major AI conference demonstrate. The ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper and David Baker for using machine learning to tackle one of biology’s biggest challenges: predicting the 3D shape of proteins ...

A new study isolates ten saliva biomarkers that objectively detect sleep deprivation, paving the way for roadside fatigue tests.