Energous Corp. (WATT)

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Energous and Syntiant Collaborate for Wireless Charging of Always-on Edge AI Processors

Source: Business Wire
Companies to Demonstrate Energous’ WattUp PowerBridge Technology Combined With Syntiant's Ultra-Low-Power Deep Learning Architecture for IoT Network Edge Applications at CES 2022
Energous Corporation (Nasdaq: WATT), a leading developer of RF-based charging for wireless power networks, today announced a collaboration with Syntiant, a provider of deep learning solutions making edge AI a reality for always-on voice, sensor and image applications, to develop and implement Energous’ WattUp wireless power network technology with Syntiant’s Neural Decision Processors™ (NDPs) for edge artificial intelligence (AI) deployments across a wide range of consumer and industrial use cases.
Demonstrations of the Energous and Syntiant technology will take place January 5-8 during CES 2022 in Las Vegas at the Energous booth (#51965) located on the show floor of the Venetian Expo Hall (formerly the Sands Convention Center).
California-based Syntiant combines the industry’s most efficient silicon with a data platform and training pipeline, providing customers with low-cost, turn-key solutions that put deep learning processing into almost any edge device, free from cloud connectivity, ensuring privacy and security. The company’s ultra-low-power NDPs are being designed into earbuds, wearables, medical devices, mobile phones, laptops, smart home appliances, as well as industrial IoT equipment and automobiles. Designed by applying a clean-sheet, hardware/software co-design methodology, Syntiant’s AI processors deliver 100x more efficiency and 10x the throughput compared to current low-power microcontroller unit solutions.
“Deployment of IoT edge devices for industrial, retail and other applications is expanding as they enable new data processing capabilities,” said Cesar Johnston, CEO of Energous. “With this expansion, however, comes concerns around delivering guaranteed levels of power to these billions of devices that are often significant distances away from a reliable power source. Our collaboration with Syntiant is aimed at addressing this challenge by integrating our WattUp receiver technology with Syntiant’s deep learning technology for edge AI applications, enabling them to harvest RF-based energy from Energous WattUp PowerBridge transmitters.”
“Syntiant’s Neural Decision Processors help reduce infrastructure costs by moving AI processing from the cloud to the edge, reliably, securely and with nominal power consumption,” said Kurt Busch, CEO of Syntiant. “We share a similar perspective with Energous that much of tomorrow’s innovation is happening at the edge, and our collaboration will successfully demonstrate both technologies working together, delivering power where it is not, while providing highly accurate, cloud-free inference across a wide range of consumer and industrial applications.”
Unlike passive solutions that harvest ambient energy from the surrounding environment, which typically offer extremely low amounts of power and can be unpredictable in terms of how much power is available, Energous’ wireless power network solutions include a WattUp PowerBridge transmitter that emits conducted RF power in a specific area or direction. This RF-based energy is then harvested by receiving devices. Energous’ wireless power networks support “one to many” charging, allowing multiple devices to be simultaneously charged from a single transmitter. It is applicable to a wide range of industries and applications, from drug storage monitors and patient trackers in a healthcare setting, to smoke detectors and motion sensors in a smart home, to fault prevention, temperature and other safety sensors in an industrial environment.
For more information on Energous WattUp or to request a developer kit, please visit energous.com.
About Syntiant
Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering end-to-end deep learning solutions for always-on applications by combining purpose-built silicon with an edge-optimized data platform