Abstract: Tiny machine learning (TinyML) is a promising approach to enable intelligent applications relying on Human Activity Recognition (HAR) on resource-limited and low-power Internet of Things ...

Artificial intelligence (AI) is expanding rapidly to the edge. This generalization conceals many more specific advances—many kinds of applications, with different processing and memory requirements, ...

TinyML can run on standard microcontrollers, but ones with hardware acceleration or AI/ML-enhanced instruction sets can implement AI/ML models more efficiently. They can also make applications ...

If you’re completely new to Microsoft Word, you’re probably wondering where to begin. You’ve come to the right place because we’ll get you started. From what you see in the Word window to how to save ...

Neural Architecture Search (NAS) has emerged as a powerful tool for automating the design of neural network architectures, providing a clear advantage over manual design methods. It significantly ...

Ceva, Inc. has extended its Ceva-NeuPro family of edge AI NPUs with the launch of Ceva-NeuPro-Nano. These highly-efficient NPUs claim the power, performance and cost efficiencies needed to integrate ...

These highly-efficient, self-sufficient NPUs deliver the power, performance, and cost efficiencies needed for semiconductor companies and OEMs to integrate TinyML models into their SoCs for consumer, ...