STM32 Summit | Tech dive
Explore computer vision use cases
Hear from our ST Partners on how they used the STM32N6 MCU with AI acceleration in their applications.
Vincent Richard
AI solutions Product Marketing Manager
All the tools available in the ST Edge AI Suite
X-LINUX-AI
HAND POSTURE TOF
HIGH SPEED DATALOG
MEMS STUDIO
NANOEDGE AI STUDIO
ST EDGE AI CORE
ST EDGE AI DEVELOPER CLOUD
MODEL ZOO
STELLAR STUDIO
STM32CUBE.AI
ST AIoT CRAFT
All frameworks compatible with ST edge AI solutions
All authorized partners
The ST Edge AI Suite is supported by a growing ecosystem of partners, expanding the available resources and expertise for your project.
STM32 microcontrollers with AI acceleration
The first high-performance STM32 MCUs with the ST Neural-ART Accelerator, a proprietary neural processing unit, drive innovation in industrial and consumer applications.
Feature overview
 | ||||
| Architecture | Core Arm® Cortex®-M55 | Operating frequency 800 MHz | CoreMark 3.360 | RAM 4.2 Mbytes contiguous RAM |
| Edge AI and multimedia | ST Neural-ART Accelerator 600 GOPS | Computer vision pipeline Parallel and MIPI CSI-2 camera I/F Image signal processor (ISP) | Graphic accelerators Chrom-ART: 2D GPU Chrom-GRC for non-square displays NeoChrom: 2.5D GPU | Multimedia accelerators H.264 encoder 1080p15 and 720p30 JPEG encoder and decoder |
| Security | Target certifications SESIP Assurance Level 3 PSA Certified Level 3 | TrustZone® YES | Resource isolation framework YES | Secure secret provisioning YES |
FAQ
Quickly find clear, concise answers to the most common questions.
Frequently asked questions on how to deploy edge AI in embedded projects.
- For all ST devices: the ST Edge AI Core CLI version and the ST Edge AI Developer Cloud allow users to optimize and evaluate AI model performance on any ST hardware.
- For STM32 MCUs: STM32Cube.AI (X-CUBE-AI) enables neural network optimization. NanoEdge AI Studio is an AutoML tool.
- For STM32 MPUs: developers can use AI for OpenSTLinux (X-LINUX-AI) and the STM32MP2 offline compiler for Linux AI frameworks.
- For Stellar MCUs: StellarStudioAI is a software package for neural network optimization and deployment.
- For MEMS sensors with a machine learning core: the online tool ST AIoT Craft and the desktop tool MEMS Studio can be used for data analysis, algorithm design, and model optimization. The MLC model zoo provides pre-optimized models.
- For MEMS sensors with an ISPU: the MEMS Studio enables data analysis and model optimization. The ISPU model zoo provides pre-optimized models."
The ST Edge AI Suite facilitates the deployment of AI models by allowing users to easily find the right tool for their project:
- Data logging: capturing the sensor data necessary for AI model training.
- Auto ML: automatically generating optimized machine learning algorithms.
- Model optimization: optimizing AI models and generating associated code for target devices.
- Validation and testing: ensuring model performance meets deployment criteria.
- Online benchmarking: testing model performance on ST hardware using the cloud.
Embedded developers can also benefit from:
- The model zoo: simplifying the deployment of AI models on supported devices.
- Documentation for more guidance through the deployment process.
The tools featured in the ST Edge AI Suite are free of charge, including for commercial use, which contributes to reducing the costs of running AI on embedded devices.
The ST Edge AI Suite is a set of tools for integrating AI features in embedded systems. It supports STM32 microcontrollers and microprocessors, Stellar automotive microcontrollers, and MEMS smart sensors, and includes resources for data handling and AI model optimization and deployment. Users will also find educational insights and real-world case studies to simplify their design journey.
The ST Edge AI Suite is compatible with a wide range of sensors as shown in the breakdown:
- Time series sensors: accelerometers, gyroscopes, magnetometers, temperature sensors, ToF ranging sensors and other sensors that output data over time.
- Audio sensors: microphones are the primary sensors for capturing audio data.
- Vision sensors: cameras (RGB, B&W, IR), Time of Light sensors, radar, lidar, and more.
The ST Edge AI Suite is optimized for ST sensors, including MEMS devices with an MLC and the ISPU. It supports any sensor as long as the data provided is compatible with the tool requirements.
The tools in the ST Edge AI Suite can support different types of data:
- High Speed Datalog:
- Time Series Data
- NanoEdge AI Studio:
- Time Series Data
- STM32Cube.AI (X-CUBE-AI):
- Time Series Data
- Audio Data
- Vision Data
- MEMS Studio:
- Time Series Data (from the MEMS sensor)
- StellarStudioAI:
- Time Series Data
- Audio Data
- AI for OpenSTLinux (X-LINUX-AI):
- Time Series Data
- Audio Data
- Vision Data
- ST AIoT Craft:
- Time Series Data (from the MEMS sensor)