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.
Researchers at Rice University present energy-saving designs for data-intensive computer processing with machine-learning algorithms that can improve energy efficiency.
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.
Digital transformation (DX) provides manufacturers with more flexibility and transform industrial processes and operations. See five ways metrics cover the DX solution lifecycle.
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.
Can industrial edge computing fit into the Purdue model?
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.
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.
Remote monitoring and data visualization are key to improving overall manufacturing efficiency.
Six edge computing questions to ask about data collection, networking and control systems.