Edge Computing, Embedded Systems

Edge Computing, Embedded Systems November 18, 2022

Machine learning facilitates turbulence tracking in fusion reactors

MIT researchers have developed a machine learning approach that can affect the energy generated during fusion reactions, with implications for reactor design.

By Adam Zewe
Edge Computing, Embedded Systems November 7, 2022

Improving deep learning with light photonics

A new method uses optics to accelerate machine-learning computations on smart speakers and other low-power connected devices.

By Adam Zewe
Edge Computing, Embedded Systems November 5, 2022

How AI and machine learning can drive sustainable 5G

Future networks have the potential to reduce the environmental impact of industries that consume high levels of energy, but the industry needs a holistic energy saving solution to maximize the benefits and create real impact.

By Subhankar Pal
Courtesy: Brett Sayles
Edge Computing, Embedded Systems November 4, 2022

AI is driving digital transformation in engineering

Artificial intelligence (AI) is driving digitalization when it comes to transforming the engineering sector.

By Sonali Singh and Sandeep Mohan
Edge Computing, Embedded Systems November 2, 2022

Network pruning can skew deep learning models

North Carolina State University researchers learn that network pruning can adversely affect the performance of the model at identifying certain groups.

By Matt Shipman
Edge Computing, Embedded Systems October 18, 2022

Machine, device learning on the edge

MIT researchers have developed a technique that enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.

By David L. Chandler
Image courtesy: Brett Sayles
Edge Computing, Embedded Systems October 11, 2022

Formula tackles complex moral decision-making for AI

A blueprint for creating algorithms that more effectively incorporate ethical guidelines into artificial intelligence (AI) decision-making programs has been developed.

By Matt Shipman
Edge Computing, Embedded Systems October 7, 2022

Is control theory better than AI for improving plant performance?

Understand the strengths and weaknesses of artificial intelligence (AI) and machine learning (ML) versus control theory, particularly model predictive control (MPC) for improving process and manufacturing applications and operations.

By John F. Carrier
Edge Computing, Embedded Systems October 5, 2022

Smarter energy measurements, faster, using AI

Engineers use artificial intelligence (AI) to magnify domain expertise and significantly cut time to end user.

By Dr. Bas Kastelein and Dr. Richard Ahlfeld
Edge Computing, Embedded Systems October 4, 2022

Using edge machine learning for anomaly detection, predictive maintenance

More powerful and cost-effective computing combined with advancements in artificial intelligence (AI) are helping predictive maintenance to detect anomalies, which predicate a maintenance action when needed. Edge computing brings decision-making and intelligence as close to the process as possible.

By Matt Dentino and Mitsuo Baba