Aspinity CEO Tom Doyle explains how an analyze-first approach to voice wake-up preserves user privacy by enabling more localized intelligence and sending only the relevant data to the cloud.
Amelia Dalton interviews CEO Tom Doyle for her weekly EE Journal Fish Fry podcast
Nanalyze.com reviews AI chip design, the benefits of neuromorphic processing for low-power edge computing, and key players in this space.
Aspinity CEO Tom Doyle discusses how the energy efficiency of the brain inspired the idea of an ultra-low-power analyze-first edge architecture for always-on applications and how it is enabled by the Aspinity RAMP technology. Read the full story on Semi.org.
Steve Taranovich explains how a better understanding of our brain’s efficiency in processing and analyzing sounds is leading to a lower-power edge processing solution for always-on sensing.
The Aspinity RAMP analog neural processing chip enables an analyze-first architecture that is more power and data efficient for always-on sensing and voice wake-up.
Julien Happich discusses the Aspinity analyze-first architecture and how it can save 10x the power of a traditional digitize-first solution for low power voice or acoustic trigger and industrial vibration monitoring.
Battery-powered devices using RAMP for voice wake-up could last 10x longer than the current standard before needing recharging or replacement batteries.
Junko Yoshida compares the Aspinity “analyze-first” approach to low power always-on sensing to alternative solutions.
One tech company originating from West Virginia University, has made a splash in the industry during the past few years, demonstrating the power and data benefits of using analog for always-on edge sensing.
Aspinity CEO Tom Doyle explains how an analyze-first approach to voice wake-up preserves user privacy by enabling more localized intelligence and sending only the relevant data to the cloud.
Amelia Dalton interviews CEO Tom Doyle for her weekly EE Journal Fish Fry podcast
Nanalyze.com reviews AI chip design, the benefits of neuromorphic processing for low-power edge computing, and key players in this space.
Aspinity CEO Tom Doyle discusses how the energy efficiency of the brain inspired the idea of an ultra-low-power analyze-first edge architecture for always-on applications and how it is enabled by the Aspinity RAMP technology. Read the full story on Semi.org.
Steve Taranovich explains how a better understanding of our brain’s efficiency in processing and analyzing sounds is leading to a lower-power edge processing solution for always-on sensing.
The Aspinity RAMP analog neural processing chip enables an analyze-first architecture that is more power and data efficient for always-on sensing and voice wake-up.
Julien Happich discusses the Aspinity analyze-first architecture and how it can save 10x the power of a traditional digitize-first solution for low power voice or acoustic trigger and industrial vibration monitoring.
Battery-powered devices using RAMP for voice wake-up could last 10x longer than the current standard before needing recharging or replacement batteries.
Junko Yoshida compares the Aspinity “analyze-first” approach to low power always-on sensing to alternative solutions.
One tech company originating from West Virginia University, has made a splash in the industry during the past few years, demonstrating the power and data benefits of using analog for always-on edge sensing.
