Artificial Intelligence (AI) is no longer confined to data centers. Today, AI is widely used and implemented in edge devices, smartphones, and embedded systems. This has been made possible through hardware and software acceleration methods that work together within embedded systems. It’s now feasible to run small machine-learning models on low-power, resource-constrained microcontroller units without…
What are the top machine-learning frameworks for microcontrollers
Machine learning (ML) is becoming increasingly important for microcontrollers because it enables smart and autonomous decision-making in embedded systems. The many Internet of Things (IoT) applications — often called “smart devices” — only become intelligent thanks to ML. Microcontrollers are commonly used in edge computing devices where data is processed locally rather than being sent…