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ABI Research thinks TinyML will catch up next year

Experts from the analytical company ABI Research tried to assess the prospects of TinyML technology, the implementation of which has slowed down due to the pandemic, and came to the conclusion that this technology will catch up next year.

As a reminder, TinyML (from Tiny Machine Learning) brings together lightweight and optimized machine learning tools capable of performing analytics at the edge of the cloud. In essence, TinyML is machine learning with minimal resource consumption (this applies to both the cost of equipment and energy costs) and without accessing the network.

TinyML is said to have tremendous potential already and is on track to become the largest segment of the edge machine learning (ML) market in terms of shipments. ABI Research predicts that the total shipments of TinyML devices in 2022 will reach 1.2 billion pieces. That’s more than Edge ML devices. In addition, the proliferation of ultra-low power machine learning applications means that more legacy devices will also be equipped with machine learning models for abnormality detection, health monitoring, and predictive maintenance.

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