STMicroelectronics, a global semiconductor leader serving customers across the spectrum of electronics applications, today announced the availability of ST Edge AI Suite, bringing together tools, software and knowledge to simplify and accelerate building edge-AI applications.
The ST Edge AI Suite is an integrated collection of software tools, designed to facilitate the development and deployment of embedded AI applications. This comprehensive suite supports both optimization and deployment of machine-learning algorithms, starting from data collection to final deployment on hardware, streamlining the workflow for different types of users.
The tools from the suite are covering a broad range of ST products, from smart sensors to microcontrollers and microprocessors including upcoming STM32N6 neural-processing microcontrollers.
While working across multiple hardware platforms, ST Edge AI Suite meets the needs of different types of users such as data scientists, embedded software developers, and hardware system engineers.
There is seamless access to online tools such as the ST Edge AI Model Zoo and Developer Cloud, as well as desktop tools for data tuning and model optimization on the chosen hardware platform. These include NanoEdge AI Studio for generating machine learning libraries automatically, and STM32Cube.AI, MEMS Studio, and Stellar Studio, for model optimization on STM32 devices, MEMS inertial sensors, and Stellar processors. All are ready to use free of charge.
The release of this suite is also an opportunity to introduce world-first innovations for AI applications in the MEMS Studio tool: the 'ISPU NN model optimizer' and 'automatic selection of MLC features and filters.'
Lead customers’ experiences:
Honeywell, Soxai, and HPE Group explain how tools such as MEMS Studio and Stellar Studio in the ST Edge AI Suite help simplify and accelerate edge-AI development.
Alessandro Cremonesi, EVP, Chief Innovation Officer and General Manager of STMicroelectronics’ System Research and Applications Group
ST Edge AI Suite is the new starting point on st.com for embedded AI development. Here, today’s innovators, driven by imagination, can find help to realize tomorrow’s smart things that sense, infer, and respond intelligently, autonomously, and efficiently to the world around. This environment brings developers simplicity through an easy choice of models and data sources, finding the right tools quickly and easily, optimizing and benchmarking, then automatically generating code and libraries - all within one unified framework.
Israel Herrera, Firmware Architect & Embedded Systems Engineer, Honeywell Fire
We recognize the innovative strides ST has made in the realm of edge computing with their sensors. MEMS Studio, as featured in the ST Edge AI Suite, has proved to be a great software development tool to help us perform quick tests using multiple MEMS sensor modules from ST. It enables us to create proof of concepts easily through its code generation feature. MEMS Studio is also very useful in testing different and independent Machine Learning and Data Analysis algorithms.
Tatsuhiko Watanabe, CEO & Founder of SOXAI, which is using ST’s edge-AI sensors
While we were developing SOXAI RING 1, ST introduced the world's first sensor with edge AI, and we quickly adopted it to boost our product's performance. The machine-learning core software tool featured in the ST Edge AI Suite helped us quickly integrate this new technology and allowed our developers to harness the full potential of the sensor with minimal effort. Compared to the first generation, our new SOXAI RING 1 now boasts an extended battery life of at least 10 hours, a game-changer in the world of wearable technology.
Andrea Bozzoli, CEO of HPE Group
HPE is at the forefront of transforming the automotive sector through our collaboration with STMicroelectronics and their Stellar MCU and Stellar Studio software, which is part of the ST Edge AI Suite. Our Prometeo Joint Innovation Lab efforts are set to deliver a proof-of-concept for next-generation vehicle powertrains, leveraging AI to enhance predictive maintenance and control systems. This synergy will not only elevate electric vehicle performance but also enrich the digital cockpit experience, setting a new standard for smart, sustainable mobility.
