Overview
TinyML is a subset of Edge AI that targets the smallest devices, often operating in the milliwatt power range. It enables 'always-on' intelligence in sensors and consumer electronics.
Key Concepts
- Microcontrollers (MCUs): Low-cost, low-power chips (e.g., ARM Cortex-M) that lack the resources of a full OS.
- On-device Inference: Running the model entirely on the chip without external help.
- Ultra-low Power: Devices that can run for years on a single coin-cell battery.
Applications
- Keyword spotting ('Hey Siri', 'OK Google').
- Gesture recognition in wearables.
- Predictive maintenance in industrial sensors.
- Environmental monitoring (e.g., detecting specific sounds in a forest).