Silicon Labs SiWx917 Wi-Fi 6 Solution Features AI/ML Accelerator with Guided Developer Journey
The Silicon Labs SiWx917 ultra-low-power Wi-Fi 6 product family has reached general availability (GA) for its AI/ML hardware accelerator. Accompanied with a guided machine learning (ML) development journey and other tools, the SiWx917 makes artificial intelligence (AI) on IoT (AIoT) accessible for everyone and speeds up edge AI transformation for Wi-Fi IoT device makers.
Edge AI Transformation
The world has become AI-driven. With smarter algorithms that go far beyond what traditional rule-based programming can ever achieve, AI improves accuracy, enhances functionalities, and enables new use-cases on almost any imaginable thing, function, and system. Anything that benefits from the advantages of AI is being enhanced with that capability as we speak. However, behind the scenes of this profound technological revolution, a significant transformation is taking place. While cloud computing has dominated the AI/ML landscape for years, the centralized model is now challenged with a distributed architecture that also operates at the network edges as well as on the IoT devices. Edge AI is a fundamental transformation driven by clear, quantifiable benefits.
The Benefits of Edge AI
While cloud computing has proven effective in making AI ubiquitous, it has faced significant challenges. The latency of sending data to the cloud and back does not scale for real-time applications. Processing and storing sensitive data on cloud servers raises privacy and security concerns. Vast amounts of data are causing constant network congestion, flooding cloud storage, and increasing energy consumption and CO2 emissions.
Edge AI distributes computing to billions of nodes. ML models run directly on IoT devices, close to where the data is generated, avoiding the need to send every bit of data to the cloud. The proliferation of IoT connectivity, rapid advancements in AI/ML hardware acceleration on wireless microcontrollers like the SiWx917, combined with easy ML development tools have made it possible to perform sophisticated ML computations directly on compact, resource-constrained devices.
With on-device AI/ML execution, billions of smart home appliances, IoT sensors, smart cameras, industrial equipment, and many other smart devices can now process data and make decisions autonomously, without relying on the cloud. The result is faster processing, real-time response, resilient applications, and reduced load on networks and data storage. Data stays where it was generated, improving privacy and security.
SiWG917 AI/ML Accelerator and Development Tools
The SiWG917 (part of the SiWx917 product family) is an ultra-low-power Wi-Fi 6 and Bluetooth Low Energy wireless MCU for energy-efficient and battery-powered IoT devices. The comprehensive Edge AI-capable system features Matter protocol support, a dual-processor architecture with a powerful application microcontroller, network wireless processor (NWP), and large SRAM, PSRAM, and flash memory capacity. Its rich set of peripherals and high GPIO count make SiWG917 a versatile wireless MCU solution for any smart IoT application.
The dedicated AI/ML hardware accelerator on SiWG917 is optimized for energy-efficient ML inference, offloading the Arm Cortex-M4 application MCU. The on-device optimized AI/ML inference capabilities include executing time series data processing ML models such as predictive maintenance, environmental monitoring, anomaly detection, voice and audio detection, and low-resolution vision use-cases.
The dedicated AI/ML hardware block on the SiWG917 is optimized for energy-efficient TinyML workloads. It can perform 320 MOPs on the dedicated accelerator, offloading this load from the Cortex-M4 microcontroller, and allowing it to process the application. This makes the SiWG917 a game-changer for energy-efficient, battery-powered Edge AI devices.
Edge AI is Now Accessible to IoT Developers
To make AIoT accessible to every developer, the SiWG917 AI/ML accelerator comes with an AI/ML Extension for Simplicity SDK that ensures a seamless use of the accelerator through a standard CMSIS-NN interface. The ML SDK includes TensorFlow Lite Micro (LiteRT) optimization for microcontrollers, running compact, efficient ML models on the IoT device.
Our online AI/ML developer journey guides you through the end-to-end development flow with sample apps, tooling, and a partner list, further lowering the bar for Edge AI innovation. Whether you're a seasoned embedded engineer or a data scientist exploring the edge, the SiWG917 offers a seamless path from ML model training to deployment.
Learn More About AI/ML on SiWx917
