The nation’s energy infrastructure is in dire need of change. Electricity demands are rising, but aging infrastructure, understaffed energy organizations, and shifting trends make it challenging to ...

Data centers use an estimated 200 terawatt hours (TWh) of electricity annually, equal to roughly 50% of all electricity currently used for all global transport, and a worse-case-scenario model ...

Data processing these days is exhibiting a split personality. ‘Cloud’ computing grabs the headlines for sheer scale and computing power, while ‘edge’ computing puts the processing at the ‘coal face’ ...

Artificial intelligence (AI) and machine learning (ML) are becoming synonymous with the operation of power generation facilities. The increased digitization of power plants, from equipment to software ...

Intelligent organizations prioritize investments in machine learning and real-time data to improve decision making, accelerate revenue generation efforts, reduce operational expenses and protect ...

Predicting the power or energy required to run an AI/ML algorithm is a complex task that requires accurate power models, none of which exist today. AI and machine learning are being designed into just ...

The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the ...

Artificial intelligence (AI) holds promising potential for advancing nuclear energy production. These sophisticated computer systems mimic human logic in problem solving and decision making. With its ...