Machine learning takes hold in nuclear physics
By Chris Patrick, contributing writer for Phys.org
Scientists have begun turning to new tools offered by machine learning to help save time and money. In the past several years, nuclear physics has seen a flurry of machine learning projects come online, with many papers published on the subject. Now, 18 authors from 11 institutions summarize this explosion of artificial intelligence-aided work in “Machine Learning in Nuclear Physics,” a paper recently published in Reviews of Modern Physics.
Machine Learning accelerates development of advanced manufacturing techniques
By Pacific Northwest National Laboratory, contributing writers for Newswise.com
Despite the remarkable technological advances that fill our lives today, the ways we work with the metals that underlie these developments haven’t changed significantly in thousands of years. This is true of everything from the metal rods, tubes, and cubes that provide cars and trucks with their shape, strength, and fuel economy, to wires that move electrical energy in everything from motors to undersea cables.
How digital transformation is greening the power sector
By Om Gupta, contributing writer for Timestech.in
Digital solutions are delivering environmental benefits across the power and utility sector in different ways, whether by improving asset efficiency, increasing overall business value, or strengthening ESG reporting says David Thomason, Industry Principal – Power Generation at AVEVA.
What are graph neural networks?
By Rick Merritt, contributing writer for Blogs.nvidia.com
When two technologies converge, they can create something new and wonderful — like cellphones and browsers were fused to forge smartphones.
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