As Machine Learning (ML) becomes increasingly integral to embedded design across various industries, Microchip Technology (Nasdaq: MCHP) has introduced the MPLAB Machine Learning Development Suite. This comprehensive software toolkit offers a streamlined workflow for ML model development and can be seamlessly integrated across Microchip’s extensive portfolio of microcontrollers (MCUs) and microprocessors (MPUs), marking a significant advancement in the field.
Rodger Richey, VP of Microchip’s Development Systems business unit, emphasized the importance of ML in the embedded controller domain, stating, “Machine Learning is the new normal for embedded controllers, and utilizing it at the edge allows a product to be efficient, more secure and use less power than systems that rely on cloud communication for processing.” He added that Microchip’s unique solution sets itself apart by supporting not only 32-bit MCUs and MPUs but also 8- and 16-bit devices, thus facilitating efficient product development.
Machine Learning involves using algorithmic methods to analyze large datasets, enabling more rapid, accurate, and easily updatable decision-making processes compared to manual methods. One of its key applications is predictive maintenance, allowing industries such as manufacturing, automotive, consumer electronics, and more to forecast potential equipment issues accurately.
The MPLAB Machine Learning Development Suite aids engineers in constructing efficient, compact ML models. Fueled by AutoML, this toolkit simplifies repetitive and time-consuming tasks such as data extraction, training, validation, and testing, while also optimizing models to respect the memory constraints of MCUs and MPUs.
When combined with the MPLAB X Integrated Development Environment (IDE), the toolkit offers a complete solution suitable for individuals with limited ML programming knowledge, potentially reducing the need to hire data scientists. Simultaneously, it caters to experienced ML designers seeking greater control.
Microchip provides an option to import models from TensorFlow Lite for use in MPLAB Harmony v3 projects. This integrated software development framework offers flexibility and interoperability for streamlined product development. Additionally, the VectorBlox Accelerator Software Development Kit (SDK) enhances Convolutional Neural Network (CNN)-based Artificial Intelligence/Machine Learning (AI/ML) inference with PolarFire FPGAs, optimizing power efficiency.
The MPLAB Machine Learning Development Suite empowers the design and optimization of edge products with ML inference capabilities. For those seeking to expedite development while controlling costs, Microchip’s intuitive ML tools offer an efficient solution.
Pricing for the MPLAB Machine Learning Development Suite varies based on licensing, with a free evaluation version available.
