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    Diagnostics, Asset Management
    Artificial Chemist is an autonomous system designed to intelligently navigate through the chemical universe and develop useful materials for manufacturing applications. Courtesy: North Carolina State University
    Robotics June 17, 2020

    Automated system developed to accelerate R&D, manufacturing of materials

    North Carolina State and University of Buffalo researchers have developed Artificial Chemist, which is a technology that incorporates artificial intelligence (AI) and an automated system for performing chemical reactions to accelerate R&D and manufacturing of commercially desirable materials.

    By Matt Shipman
    Courtesy: Chris Vavra, CFE Media
    AI and Machine Learning June 12, 2020

    Engineers develop methods for AI bottlenecks with machine-learning algorithms

    Researchers at Rice University present energy-saving designs for data-intensive computer processing with machine-learning algorithms that can improve energy efficiency.

    By Mike Williams
    The new chip (top left) is patterned with tens of thousands of artificial synapses, or “memristors,” made with a silver-copper alloy. When each memristor is stimulated with a specific voltage corresponding to a pixel and shade in a gray-scale image (in this case, a Captain America shield), the new chip reproduced the same crisp image, more reliably than chips fabricated with memristors of different materials. Courtesy: Massachusetts Institute of Technology
    AI and Machine Learning June 10, 2020

    Engineers put thousands of artificial brain synapses on a single chip

    MIT engineers have designed a brain-on-a-chip made from tens of thousands of artificial brain synapses known as memristors, which could enhance the develop of portable AI devices.

    By Jennifer Chu
    Courtesy: Industrial Internet Consortium (IIC)
    Other Networks June 8, 2020

    Five ways digital transformation metrics give manufacturers more flexibility

    Digital transformation (DX) provides manufacturers with more flexibility and transform industrial processes and operations. See five ways metrics cover the DX solution lifecycle.

    By Jacques Durand
    Courtesy: Purdue University
    AI and Machine Learning June 5, 2020

    Cloud efficiency platform developed for databases

    A Purdue University data science and machine learning professor has developed OPTIMUSCLOUD, which is designed to give cloud efficiency to organizations and users for data-intensive situations like the COVID-19 pandemic.

    By Chris Adam
    Courtesy: Litmus
    IIoT, Industrie 4.0 May 7, 2020

    Data flow is no longer hierarchical

    Can industrial edge computing fit into the Purdue model?

    By Vatsal Shah
    Courtesy: Massachusetts Institute of Technology
    AI and Machine Learning April 24, 2020

    Reducing AI’s carbon footprint

    MIT researchers have developed an automated AI system for training and running certain neural networks that also cuts down the pounds of carbon emissions involved.

    By Rob Matheson
    This figure shows the model prediction of the infected case count for the United States following its current model with quarantine control and the exponential explosion in the infected case count if the quarantine measures were relaxed. On the other hand, switching to stronger quarantine measures as implemented in Wuhan, Italy, and South Korea might lead to a plateau in the infected case count sooner. Courtesy: Massachusetts Institute of Technology (MIT)
    AI and Machine Learning April 17, 2020

    Machine learning model quantifies quarantine measures on COVID-19’s spread

    A machine learning algorithm developed by MIT researchers combines data from COVID-19’s spread with a neural network to assess the impact of quarantine measures and predict when infections will slow down in each country.

    By Mary Beth Gallagher
    Remote Monitoring April 14, 2020

    Remote monitoring and data visualization

    Remote monitoring and data visualization are key to improving overall manufacturing efficiency.

    By Jack Smith
    Courtesy: MartinCSI
    virtualization, Cloud, Analytics, Edge Computing April 2, 2020

    Edge computing terms and skills

    Six edge computing questions to ask about data collection, networking and control systems.

    By Nate Kay, P.E.