Pete Warden discusses why Deep Learning is a great fit for tiny, cheap devices, what can be built with it, and how to get started. Pete Warden is technical lead on the mobile and embedded side of ...

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 ...

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 ...

One exciting avenue in the world of AI research and development is finding ways to shrink AI algorithms to run on smaller devices closer to sensors, motors and people. Developing embedded AI ...

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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 ...

STMicroelectronics (NYSE:STM) is ready to launch its new series of microcontrollers with machine learning capabilities in high volumes. The Switzerland-based company said the STM32N6 microcontroller, ...

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 ...

One exciting avenue in the world of AI research and development is finding ways to shrink AI algorithms to run on smaller devices closer to sensors, motors and people. Developing embedded AI ...

CMSIS-NN is an open-source library of optimized software kernels that maximize NN performance on Cortex-M cores with minimal memory footprint overhead. Machine learning (ML) algorithms are moving to ...