The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
An idea about the sun’s magnetic field called the terminator model could help predict dangerous space weather more accurately ...
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
NASA’s CGS releases the MAGE model to improve space weather prediction, providing simulations of solar storms, auroras, and ...
Energy management systems (EMS) enhanced with AI are emerging as the backbone of solar-assisted greenhouse operations. These ...
NASA's PUNCH mission is photographing the Sun like never before. It can see comets that are invisible to every other ...
Meet GPT-5.2, 11x faster than human experts at under 1 percent of the cost, helping teams ship projects days sooner with fewer blockers.
Morning Overview on MSN
Parker Solar Probe pushes deeper into the Sun’s extreme atmosphere
The spacecraft that now skims through the Sun’s blistering atmosphere is not just surviving, it is turning that hostile ...
New GenCost report produces new modelling to deliver the same message: firmed renewables are lowest cost as coal and gas get ...
This is a sponsored article brought to you by . Across global electricity networks, the shift to renewable energy has ...
For decades, cold chain logistics has relied on periodic checks, manual inspections, and delayed reporting to manage ...
The marketing retainer model had its moment. Fixed fees for fixed scopes gave brands predictability, but not accountability. Agencies got paid regardless of performance. And clients paid for effort, ...
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