Between 2021 and 2026, IoT connections will nearly triple to 23.6 billion. Each new connection represents an opportunity to use artificial intelligence and machine learning, and TinyML technology will be critical to harness this opportunity.
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.
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In fact, TinyML is machine learning with minimal resource consumption (this applies to both the cost of equipment and energy costs) and without accessing the network. According to consulting company ABI Research, shipments of TinyML devices will grow from 15.2 million units in 2020 to 2.5 billion units in 2030.
Chipsets for TinyML devices are designed to address cost and energy efficiency issues. TinyML conducts data analytics on low-power hardware with modest processing power and low memory, aided by software designed for small inference workloads.
This approach could revolutionize the future of the Internet of Things, as the proliferation of TinyML is expected to expand the scope of edge AI beyond traditional core markets.
(Via)
