Silicon Labs looks to brings AI/ML to the Edge with Matter-ready platform

2 min read

Silicon Labs has introduced the BG24 and MG24 families of 2.4 GHz wireless SoCs for Bluetooth and Multiple-protocol operations, respectively, along with a new software toolkit.

This co-optimised hardware and software platform is intended to help bring AI/ML applications and wireless high performance to battery-powered edge devices. Matter-ready, the ultra-low-power BG24 and MG24 families support multiple wireless protocols and incorporate PSA Level 3 Secure Vault protection for a diverse range of smart home, medical and industrial applications.

The SoC and software solution for the Internet of Things (IoT) includes:

● Two new families of 2.4 GHz wireless SoCs, which feature the industry’s first integrated AI/ML accelerators, support for Matter, Zigbee, OpenThread, Bluetooth Low Energy, Bluetooth mesh, proprietary and multi-protocol operation, the highest level of industry security certification, ultra-low power capabilities and the largest memory and flash capacity in the Silicon Labs portfolio.
● A new software toolkit designed to allow developers to quickly build and deploy AI and machine learning algorithms using some of the most popular tool suites like TensorFlow.

“The BG24 and MG24 wireless SoCs represent a combination of industry capabilities including broad wireless multiprotocol support, battery life, machine learning, and security for IoT Edge applications,” said Matt Johnson, CEO of Silicon Labs.

For many engineers considering deploying AI or machine learning at the edge they are faced with steep penalties in terms of both performance and energy use that may outweigh the benefits.

To address these issues the BG24 and MG24 are the first ultra-low powered devices with dedicated AI/ML accelerators built-in. This specialised hardware is designed to handle complex calculations quickly and efficiently, with internal testing showing up to a 4x improvement in performance along with up to a 6x improvement in energy efficiency. Because the ML calculations are happening on the local device rather than in the cloud, network latency is eliminated for faster decision-making and actions.

Both device families also have the largest Flash and random access memory (RAM) capacities in the Silicon Labs portfolio. This means that the device can evolve for multi-protocol support, Matter, and trained ML algorithms for large datasets.

PSA Level 3-Certified Secure Vault, the highest level of security certification for IoT devices, provides the security needed in products like door locks, medical equipment, and other sensitive deployments where hardening the device from external threats is paramount.

In addition to natively supporting TensorFlow, Silicon Labs has partnered with some of the leading AI and ML tools providers, like SensiML and Edge Impulse, to ensure that developers have an end-to-end toolchain that simplifies the development of machine learning models optimized for embedded deployments of wireless applications.

Using this AI/ML toolchain with Silicon Labs’s Simplicity Studio and the BG24 and MG24 families of SoCs, developers will be able to create applications that draw information from various connected devices, all communicating with each other using Matter to then make intelligent machine learning-driven decisions.