Analog Devices announces general availability of AutoML for embedded
Analog Devices has introduced AutoML for Embedded, co-developed with Antmicro, which is now available as part of the Kenning framework and integrated into CodeFusion Studio.
As AI rapidly moves to the edge and demand for intelligent edge devices explodes, developers are expected to move faster. However, they are struggling to fit powerful models onto tiny microcontrollers and face a steep learning curve. Recognising this need, ADI co-developed AutoML for Embedded to make edge AI accessible, efficient and scalable for everyone.
AutoML for Embedded simplifies the process by automating the end-to-end machine learning pipeline, allowing developers without data science expertise to build high-quality and efficient models that deliver robust performance. In a recent demonstration, the tool was used to create an anomaly detection model for sensory time series data on the ADI MAX32690 MCU. The model was deployed both on physical hardware and its digital twin in Renode simulation, showcasing seamless integration and real-time performance monitoring.
