ST drives AI to edge and node embedded devices with STM32 neural-network developer toolbox
STMicroelectronics has extended the associated STM32CubeMX ecosystem for product developers, adding advanced Artificial Intelligence (AI) features.
With STM32Cube.AI, developers can now convert pre-trained neural networks into C-code that calls functions in optimized libraries that can run on STM32 MCUs.
STM32Cube.AI comes together with ready-to-use software function packs that include example code for human activity recognition and audio scene classification. These code examples are immediately usable with the ST SensorTile reference board and the ST BLE Sensor mobile app.
The STM32Cube.AI extension pack (part number: X-Cube-AI) can be downloaded inside ST’s STM32CubeMX MCU configuration and software code-generation ecosystem. It supports Caffe, Keras (with TensorFlow backend), Lasagne, ConvnetJS frameworks and IDEs including those from Keil, IAR, and System Workbench.
The comprehensive toolbox consisting of the STM32Cube.AI mapping tool, application software examples running on small-form-factor, battery-powered SensorTile hardware, together with the partner program and dedicated community support offers a fast and easy path to neural-network implementation on STM32 devices.
Additional support such as engineering services is available for developers through qualified partners inside the ST Partner Program and the dedicated AI & Machine Learning (ML) STM32 online community.