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 ...

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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 ...

*** All content in this blog provided by Davis Sawyer, Co-founder & CPO at Deeplite.ai *** The emergence of AI and deep learning on embedded devices and platforms has created opportunities for ...

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, ...

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 ...