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Get ready for really low-power AI: Synaptics and Eta Compute envision neural nets that observe every sound, motion

In a bid to make inroads into the industrial IoT, Synaptics is this month going into production with the first silicon in a planned family of ultra-low-power chips, called Katana, a name for a type of samurai sword. The big problem that Synaptics and Eta are trying to solve is making really, really low-power chips that can support applications written in machine learning frameworks such as Google's TensorFlow. 

"Areas where we are differentiating is in low-power for voice and audio neural network operation, and this hybrid platform that will do both audio and image processing at micro-watts of power." Competitors' parts, contended Ganju, tend to handle only image or audio processing, not both. 

Synaptics and Eta are helping to fulfill a broad mandate for low-power devices that Google and others have been describing in recent years as a stretch goal for the entire chip field. Of course, Synaptics is not the only company that is developing ultra-low-power parts. Startups are focusing on highly efficient parts for the edge, such as Ambient Scientific of San Jose, California, which claims to be able to re-train neural nets continuously even in low-power mode.See the full story here:

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