--Analog machine learning drives new generation of always-listening products with extended battery life PITTSBURGH — December 8, 2020 – Aspinity, a pioneer in ultra-low-power analog machine learning (AnalogML™) processors, today launched its Voice-First Evaluation Kit (EVK2), a complete hardware/software development kit that demonstrates Aspinity’s ultra-low-power edge processing solution for analog voice activity detection and preroll. The new EVK2 enables customers to easily integrate analog machine learning and analog data compression into battery-operated voice-enabled devices, such as hearables/wearables, smart speakers and smart TV remotes, facilitating significant power savings—without compromising system accuracy. Aspinity’s EVK2 The EVK2 features the latest generation of Aspinity’s Reconfigurable Analog Modular Processor (RAMP™) chip. As the world’s first implementation of compact, ultra-low power analogML, the RAMP chip introduces a new architectural approach to system design that improves battery life in edge devices. In contrast to alternative always-listening system architectures—which digitize all sound data, relevant or not, before wake word analysis—the RAMP chip uses near-zero power to analyze raw, unstructured analog microphone data at the start of the signal chain to determine if voice is present prior to triggering the wake word engine. Since up to 90% of the sound data captured within a day is not voice, the RAMP chip’s