Qeexo, developer of an automated machine learning (ML) platform that accelerates the deployment of tinyML at the edge, announced that its Qeexo AutoML platform now supports machine learning on Arm Cortex-M0 and Cortex-M0+ processors.

According to the company, the Arm Cortex-M0 processor is the smallest Arm processor available, and the Cortex-M0+ processor builds on Cortex-M0 while further reducing energy consumption and increasing performance. Per the company, Qeexo is the first company to automate adding machine learning to a processor of this size. The Cortex-M0 and Cortex-M0+ processors are designed for smart and connected embedded applications, and are ideal for use in simple, cost-sensitive devices due to the lower power-consumption and ability to extend the battery life of critical use cases such as activity trackers.  

Machine learning models built with Qeexo AutoML are optimized and have a small memory footprint. Models are designed to run locally on embedded devices, ideal for low-power, low-latency applications on MCUs and other constrained platforms. 

The list of machine learning algorithms supported on Qeexo AutoML currently include: GBM, XGBoost, Random Forest, Logistic Regression, Decision Tree, SVM, CNN, RNN, CRNN, ANN, Local Outlier Factor, and Isolation Forest. Several hardware platforms from Arduino, Renesas, and STMicroelectronics work with Qeexo AutoML out-of-the-box.

For more information, visit: https://qeexo.com/