This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Deep learning models owe their initial success to large ...
Machine learning (ML) has progressively moved from the cloud to edge computing to reduce latency in decision-making, lower power consumption, and decrease the dependence on network connections, ...
A decade on from its debut running on high-end servers, deep learning is making its way to far more constrained systems out on the edge, though often with the help of significant amounts of pruning ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
We’ve gotten to the point where a $35 Raspberry Pi can be a reasonable alternative to a traditional desktop or laptop, and microcontrollers in the Arduino ecosystem are getting powerful enough to ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...
Arm’s ARMv8.1-M architecture specification redefines its microcontroller offerings (Fig. 1). It includes the company’s Helium technology, which addresses machine-learning (ML) applications. Arm ...
Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results