The researchers at PNNL, which has a world-class team modernizing the grid, took a closer look at one machine-learning algorithm applied to power systems.

Machine learning (ML) can be applied at the ‘edge’ where data processing functions are tightly targeted and power consumption must be low.

The machine-learning model from Qiu’s team showed that this calculation can be done 12 times faster than is possible without AI, reducing the time required from nearly 10 minutes to 60 seconds.

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 ...

By 2030, it’s expected that the market for streaming data will eclipse $73 billion, growing nearly 20% each year until then. More impressively, the machine learning market—which brought in $15 ...

Meanwhile, between 2010 and 2020, global data usage increased from 1.2 trillion gigabytes to almost 60 trillion gigabytes. At some point, quantum systems will more easily handle the ongoing ...