NIST Improves Flagship Device for Measuring Mass
In a brightly lit subterranean lab at the National Institute of Standards and Technology (NIST) sits a room-sized electromechanical machine called the NIST-4 Kibble balance.
In a brightly lit subterranean lab at the National Institute of Standards and Technology (NIST) sits a room-sized electromechanical machine called the NIST-4 Kibble balance.
With 2022 firmly in the rearview mirror and the new year now underway, it’s clear many of the opportunities and challenges affecting equipment manufacturers today will remain as relevant as ever in the weeks and months ahead.
Every engineer dreams of having a virtual personal assistant like Jarvis, the disembodied voice that carries out Iron Man’s orders.
A not-so-surprising fact, according to HubSpot: 65 percent of consumers state that the experience they encounter on a website is a “very important” factor in recommending a brand.
When deep-learning models are deployed in the real world—perhaps to detect financial fraud from credit card activity or identify cancer in medical images—they are often able to outperform humans.
Credit: DeepMind on Unsplash
Ever since deep learning burst into the mainstream in 2012, the hype around AI research has often outpaced
I’m sure you’ve heard the buzz around the German apprenticeship system—but does it really live up to the hype?
The worldwide pandemic presented unique challenges for every manufacturer in the United States. Hexagon’s Manufacturing Intelligence division was no exception.
As 2022 draws to a close, we ask NIST’s senior researchers to look ahead to the new year and beyond. They research topics that affect all of us, from indoor air quality to cybersecurity.
There’s a growing movement to increase competency and skills-based education and hiring practices in both the public and private sectors.
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