Silicon Labs and SensiML have partnered to deliver rapid development of TinyML smart IoT sensing applications on Silicon Labs' end-to-end machine learning (ML) development solutions for existing Silicon Labs Series 1 and Series 2 wireless SoCs and its new EFR32BG24
products, which features integrated AI/ML hardware acceleration providing up to 4x faster interferencing with up to 6x lower power consumption for ML processing.
Using Silicon Labs’ ML development solution, designers can enhance embedded applications with AI/ML capabilities, even in ultra-low-power wireless IoT devices. ML computing at the edge enables a variety of smart industrial and home applications including sensor-data processing for anomaly detection, predictive maintenance, audio pattern recognition like glass-break sensing and simple-command word recognition. The SensiML Analytics Toolkit accelerates the development of optimized AI sensor models for intelligent endpoints allowing meaningful insight to be generated locally in real-time at the embedded device.