Partnership integrates neural processor and TinyML platform

May 13, 2020 //By Rich Pell
Edge AI partnership combines neural sensor SoC, TinyML platform
Low-power AI startup Eta Compute and embedded machine learning company Edge Impulse have announced that they are partnering to accelerate the development and deployment of machine learning (ML) at the edge.

The collaboration will combine Eta Compute's ECM3532 ultra-low-power Neural Sensor Processor SoC with Edge Impulse's online TinyML platform. The partnership, say the companies, will speed the time-to-market for machine learning in billions of IoT consumer and industrial products where battery capacity has been a roadblock.

"Collaborating with Edge Impulse ensures our growing ECM3532 developer community is fully equipped to bring innovative designs in digital health, smart city, consumer, and industrial applications to market quickly and efficiently,” says Ted Tewksbury, CEO of Eta Compute. "We believe that our partnership will help companies debut their ground-breaking solutions later in 2020."

The ECM3532 Neural Sensor Processor SoC, which is offered as enabling machine learning at the extreme edge, and its ECM3532 EVB evaluation board are now supported by Edge Impulse's end-to-end ML development and MLOps platform.

Zach Shelby, CEO and Co-founder of Edge Impulse says, "Machine learning at the very edge has the potential to enable the use of the 99% of sensor data that is lost today because of cost, bandwidth, or power constraints. Our online SaaS platform and Eta Compute's innovative processor are the ideal combination for development teams seeking to accurately collect data, create meaningful data sets, spin models, and generate efficient ML at a rapidly accelerated pace."

Developers can register for free to gain access to advanced Eta Compute machine learning algorithms and development workflows through the Edge Impulse portal.

Eta Compute
Edge Impulse

Related articles:
AI at the edge and beyond - whitepaper
Google brings machine learning to the edge
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Edge AI boom faces power consumption, size challenges
IoT dev board brings low-power ML to endpoint devices


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