TinyML Edge AI

TinyML is machine learning on edge devices—microcontrollers, IoT sensors, mobile phones—without relying on cloud compute. You train neural networks in the cloud, convert them to compact models using quantization and pruning, then deploy them to devices with limited memory (KBs-MBs) and compute power. Inference happens on-device, enabling offline, real-time, privacy-preserving AI. Use cases range from wake-word detection in smart speakers, motion detection in security cameras, pose estimation on mobile, to anomaly detection in industrial sensors. TinyML is the foundation of modern edge intelligence.