Webinar
Deliver everyday practicality to your IoT market with edge AI
Learn how to run tiny neural networks directly on an smartsensor with an intelligent sensor processing unit (ISPU) for unmatched performance and efficiency.
Denise Sanfilippo
Application Development Engineer
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
STM32 MPUs with edge AI acceleration
The latest generation of 64-bit STM32 microprocessors enables advanced, secure edge AI applications.
Feature overview
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| Architecture | Core Dual Arm® Cortex®-A35 | Operating frequency 1.5 GHz | Coprocessor Arm® Cortex®-M33 | Coprocessor frequency 400 MHz | DRAM support DDR3(L)/ DDR4/ LPDDR4 16/32-bit | ||
| Edge AI and multimedia | NPU 1.35 TOPS | 3D GPU 1080p60 with RGB, LVDS, DSI outputs | Video encoding H.264 encode/decode | PCIe Gen2 | Ethernet 3 ports with switch (TSN support) | USB 3 | Display interface LVDS/DSI |
| Security | Target certifications SESIP Level 3 PSA Certified Level 1 | TrustZone® YES | Resource isolation framework YES | Secure provisioning ecosystem YES |
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FAQ
Quickly find clear, concise answers to the most common questions.
Frequently asked questions on how to deploy edge AI in embedded projects.
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)
- 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.
