Open source AI chips making Green Waves: Bringing energy efficiency to IoT architecture

Open source AI chips making Green Waves: Bringing energy efficiency to IoT architecture

What if machine learning applications on the edge were possible, pushing the limits of size and energy efficiency? GreenWaves is doing this, based on an open-source parallel ultra low power microprocessor architecture. Though it’s early days, implications for IoT architecture and energy efficiency could be dramatic.

The benefits open source offers in terms of innovation and adoption have earned it a place in enterprise software. We could even go as far as to say open source is becoming the norm in enterprise software. But open source hardware, chips to be specific, and AI chips to be even more specific? Is that a thing?

Apparently it is. GreenWaves, a startup based in Grenoble, France, is doing just that. GreenWaves is developing custom, ultra-low power specialized chips for machine learning. These specialized chips leverage parallelism and a multi-core architecture to run machine learning workloads at the edge, on battery-powered devices with extreme limitations. The chips GreenWaves makes are based on open source designs, and are making waves indeed.

GreenWaves just announced a 7M€ Series A Funding with Huami, Soitec, and other investors. As per the announcement, funds will finance the sales ramp of GreenWaves’ first product, GAP8, and the development of the company’s next generation product. ZDNet discussed with Martin Croome, GreenWaves VP of Product Development, to find out what this is all about.

Read the full article on ZDNet


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