STMicroelectronics Extends STM32Cube.AI Development Tool with Support for Deeply Quantized Neural Networks

By Tiera Oliver

Associate Editor

Embedded Computing Design

July 22, 2022

News

STMicroelectronics Extends STM32Cube.AI Development Tool with Support for Deeply Quantized Neural Networks

STMicroelectronics has released STM32Cube.AI version 7.2.0, the first artificial-intelligence (AI) development tool by an MCU vendor to support ultra-efficient deeply quantized neural networks. 

STM32Cube.AI converts pretrained neural networks into optimized C code for STM32 microcontrollers (MCUs). It is an essential tool for developing AI solutions that make the most of the constrained memory sizes and computing power of embedded products. Moving AI to the edge, away from the cloud, delivers substantial advantages to the application. These include privacy by design, deterministic, and real-time response, greater reliability, and lower power consumption. It also helps optimize cloud usage.

Now, with support for deep quantization input formats like qKeras or Larq, developers can even further reduce network size, memory footprint, and latency. These benefits unleash more possibilities from AI at the edge, including frugal and cost-sensitive applications. Developers can thus create edge devices, such as self-powered IoT endpoints that deliver advanced functionality and performance with longer battery runtime. ST’s STM32 familyprovides many suitable hardware platforms. The portfolio extends from ultra-low-power Arm Cortex®-M0 MCUs to high-performing devices leveraging Cortex-M7-M33, and Cortex-A7 cores.

STM32Cube.AI version 7.2.0 also adds support for TensorFlow 2.9 models, kernel performance improvements, new scikit-learn machine learning algorithms, and new Open Neural Network eXchange (ONNX) operators. 

For more information, visit www.st.com

You can also read theblogpost at https://blog.st.com/stm32cubeai-v72/.

Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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