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Passive infrared (PIR) sensors are almost always used to detect whether a human has moved within the sensor’s range, but the simple triggering algorithms used are sensitive to other types of movement. High rates of false alarms are produced when the sensor is triggered by movement from unwanted subjects like

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Kurt Busch: ‘Following Your Passion is Horrible Advice’ Kurt Busch is the CEO of Syntiant, a California company that makes AI accelerator co-processors for low-power battery-operated systems. The chips are aimed at acceleration of neural networks for voice control in consumer devices. Kurt’s career has afforded him extensive experience in

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Deep Learning App Detects Motion and Gesture Recognition; Expands Uses Beyond Voice; Demonstrates High Accuracy, Reduced Latency and Ultra-Low Power Consumption Students from Harvey Mudd College successfully designed and trained the Syntiant® NDP101™ Neural Decision Processor™ (NDP) to detect and classify hand motions for a wearable device. As part of

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Just a short time ago, we unveiled our ultra-low-power analog neural network technology at the Intel Capital Global Summit in Palm Springs, California. Within less than two years from first funding, we were able to develop, qualify and ship an unparalleled always-on voice solution to customers all over the world.

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As the world embraces the current pandemic due to COVID-19, the health and safety of our community are of the utmost importance. Like many organizations, our staff has been working remotely and instructed to follow guidance from local, state and federal authorities. We are closely monitoring updated direction from these

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By Jeremy Holleman Overview With the explosion of audio content over the last 15 years, headphones have evolved from passive wired devices to intelligent wireless devices, with a large role in a user’s experience with a mobile device. True Wireless Stereo (TWS) represents the latest step in this evolution. Syntiant’s

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By Jeremy Holleman Keyword spotting (KWS) in edge devices is a challenging task. The algorithm must avoid false alarms and reliably respond to target words. All this must be accomplished while consuming only a small fraction of a device’s battery supply. Until recently, the only devices capable of performing KWS

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