Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission that could reshape how ...
AZoSensors on MSN
Low-Power Sensor Node Brings Machine Learning to the Edge of Environmental Monitoring
A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time ...
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...
AI is driving record power demand in data centers, with rack densities hitting 150 kW. C&D Technologies helps operators ...
MaC Venture Capital’s Marlon Nichols explores how the rapid growth of A.I. data centers is straining America’s power grid. As ...
This valuable study presents a technically sophisticated intravital two-photon calcium imaging approach to characterize Ca²⁺ dynamics in distinct populations of meningeal macrophages in awake, freely ...
South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.
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