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TinyML
(Tiny Machine Learning)
tinyml refers to ML techniques optimized to run on resource-constrained devices like microcontrollers and edge devices. This emerging field enables AI applications in low-power scenarios where traditional GPU or cloud-based solutions aren't feasible.
By employing model compression, quantization, and efficient architectures, tinyml brings intelligent capabilities to devices with limited memory and processing power. Applications include always-on voice interfaces, predictive maintenance sensors, and smart agriculture devices. The global edge AI market, powered by tinyml innovations, is projected to reach $107.4 billion by 2029, driven by demand for decentralized, privacy-preserving AI solutions.
By employing model compression, quantization, and efficient architectures, tinyml brings intelligent capabilities to devices with limited memory and processing power. Applications include always-on voice interfaces, predictive maintenance sensors, and smart agriculture devices. The global edge AI market, powered by tinyml innovations, is projected to reach $107.4 billion by 2029, driven by demand for decentralized, privacy-preserving AI solutions.