Through edge computing and machine learning, we can actually significantly reduce the amount of time—and hence, power—data centers need to use to process data.

American Tower president and CEO Steven Vondran has admitted that Edge computing hasn't taken off as the company had ...

Wastewater treatment plants (WWTPs) are inherently complex, with nonlinear processes that are challenging to analyze and ...

Edge computing is witnessing a significant interest with new use cases, especially after the introduction of 5G. The 2021 State of the Edge report by the Linux Foundation predicts that the global ...

Being able to deploy machine learning applications at the edge bears the promise of unlocking a multi-billion dollar market. For that to happen, hardware and software must work in tandem. Arm's ...

Machine learning inherently involves a lot of data. You would want to do as much of that inferencing either on the end node or on the edge, as opposed to trying to send information back and forth ...

Before getting started with training the machine learning algorithm, we will need to install Jupyter. To do so, we will use a platform known as Anaconda. Anaconda is a free and open-source ...

Integrating machine learning into the edge data center solves latency problems, distributes the computing load and reduces costs. It simplifies and speeds up decision-making and delivers better ...