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Eta Compute MCU Puts AI in IoT

October 30, 2018

Author: Bob Wheeler

Riding the AI-in-IoT wave, Eta Compute has developed an SoC that combines an MCU with a DSP for machine learning. The ultra-low-power Tensai chip is well suited to battery-operated systems, including those that require continuous (always-on) processing. The startup completes its solution with optimized neural-network software for machine learning. It expects Tensai to enter production early next year.

Tensai starts as a hyper-efficient microcontroller built around Eta’s asynchronous CPU core and low-power analog blocks. The startup previously disclosed its Cortex-M3 CPU, which it also licenses as a 55nm hard macro. For machine learning, it adds a CoolFlux DSP16 core licensed from NXP. It uses the DSP’s dual 16x16 MACs to implement convolutional neural networks (CNNs) as well as spiking neural networks (SNNs). Tensai has common MCU features such as embedded flash memory, analog I/Os, and a power-management unit.

By crunching data at its source, Tensai can dramatically reduce communications requirements for IoT devices. Applications include cameras that detect and track objects, smart speakers with wake-word detection, and industrial sensors that detect anomalies without extensive offline training. Eta isn’t alone in addressing edge AI, but it’s the first to offer an Arm-based MCU with a machine-learning engine. Its holistic approach should appeal to IoT developers lacking AI expertise.

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