Pod 4A
Embedded Processing
Silicon Labs
Bringing machine learning (ML) to IoT applications reduces bandwidth requirements, saves power, and increases a device’s ability to make smarter decisions. Silicon Labs supports machine learning in all Series 1 and Series 2 wireless SoCs including newly released BG24 and MG24 products with built-in AI/ML hardware accelerator.
Pod 4B
Wireless Factory Automation
Wireless MCUs with AI and ML Capabilities
Microchip
This demonstration shows off Microchip’s range of different wireless MCUs and their on the edge AI and ML capabilities.
Why ML? ML is a set of algorithmic methods that discovers patterns from seemingly unrelated data, providing you with important information to facilitate decision making.
Why on Edge? ML on edge makes the system power efficient, fast and secure. User privacy is at the forefront because personal data never leaves your device. ML on edge also saves cloud resources and compute power in storing and maintaining data pipelines.
Why Microchip? We offer 8-, 16- and 32-bit microcontrollers (MCUs), microprocessors (MPUs) and Field-Programmable Gate Arrays (FPGAs). With a simple ML design process that can bring an ML engine to each of these systems quickly and efficiently, we offer solutions for a wide spectrum of users such as embedded systems engineers and data scientists. Our AutoML-powered design process automates the steps to build the ML model and will go through multiple iterations until a satisfactory model is identified.