Get the latest updates on the Coronavirus impact on engineers.Click Here

Manufacturing IT, MES

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.
Courtesy: CFE Media and Technology
Discrete Manufacturing March 17, 2020

Coronavirus reveals weaknesses, potential opportunities in supply chain

Even in the wake of COVID-19 (coronavirus), manufacturers still need human workers to manage the supply chain. The need for more automation and information is an opportunity for manufacturers.

By ABI Research
MIT computer scientist Aleksander Madry. Courtesy: Ian MacLellan, MIT
AI and Machine Learning March 15, 2020

Doing machine learning the right way

MIT Professor Aleksander Madry strives to build machine-learning models that are more reliable, understandable and robust.

By Rob Matheson