How to Find the Right Balance of Data for Your Industrial AI System
Our take Full industry article syndicated from the NIST Manufacturing Innovation Blog RSS feed: How to Find the Right Balance of Data for Your Industrial AI System. Source attributed below with a link to the original.
Article
/blogs/taking-measure/authors/michael-sharp
Michael Sharp
Michael Sharp leads the Industrial Artificial Management and Metrology Project in NIST's Communications Technology Laboratory. He currently researches methods and metrology to integrate and qualify artificial intelligence for practical use in industrial and manufacturing settings. He received his Ph.D. in nuclear engineering from the University of Tennessee in 2012 and has been an active participant in state-of-the-art research communities for data modeling, sensing capabilities and artificial intelligence. In his spare time, Michael enjoys collaborative creative endeavors, such as D&D, and exploring outdoor spaces through hikes or disc golf.
Why manufacturers might care
Read this as category context for manufacturers evaluating CAD-backed sales tools. Confirm vendor claims against primary sources and your own product family rules.
Source
How to Find the Right Balance of Data for Your Industrial AI System — via NIST Manufacturing Innovation Blog
Published in the publisher’s RSS/Atom feed (source-page). Canonical version lives on the publisher site.
Disclosure
This page is an attributed industry article on VendorCAD Reviews (published by VendorCAD). Body text comes from the publisher’s public feed for manufacturer readers evaluating CAD-backed configurators. We do not invent peer reviews or treat syndicated coverage as VendorCAD product proof. See Trust and Methodology.