Aspinity Establishes Technical Advisory Board of Seasoned Semiconductor Industry Veterans
Advisory board members from Kymeta and BCG to provide technical expertise and strategic guidance for Aspinity's next phase of growth.
Read the release →Company announcements, product launches, and coverage of Aspinity's analog machine learning technology.
Every Aspinity press release, most recent first.
Advisory board members from Kymeta and BCG to provide technical expertise and strategic guidance for Aspinity's next phase of growth.
Read the release →A new suite of automotive security algorithms plus a dashcam evaluation kit that detects and records security events for weeks while parked, without draining the battery.
Read the release →Hegberg brings more than 25 years of executive leadership in semiconductor technology from Vesper MEMS, NetApp, SanDisk, Qualcomm and more, as the AML100 enters volume production.
Read the release →Aspinity and new investor Unitrontech aim to deliver high performance, near-zero power aftermarket and integrated AI solutions for automotive applications.
Read the release →The new AB2 Application Board enables rapid prototyping of the AML100 with Renesas Quick-Connect IoT platforms; demonstrated at Embedded World.
Read the release →AML100 is the only glass break detection solution to produce a five-year battery life while also eliminating false alarms to common household sounds.
Read the release →Aspinity announces the AML100, its first AnalogML chip — the industry's first tinyML solution operating completely within the analog domain.
Read the release →Experts in AI/ML, edge computing, analog semiconductors and IoT bring engineering acumen and operational excellence to the AnalogML pioneer.
Read the release →Announcing a new acoustic event detection evaluation kit built on the AnalogML core.
Read the release →Aspinity aligns with a leader in high-performance microcontrollers to support extended battery life in IoT devices.
Read the release →Analog machine learning chip drives a new generation of high-performance voice-enabled products with extended battery life.
Read the release →Aspinity's neuromorphic analog chip dramatically reduces power consumption in always-on IoT and IIoT devices, smart speakers, voice-activated remotes and hearables.
Read the release →A partnership to accelerate development of intelligent sensing products with significantly longer battery life.
Read the release →The most power-efficient end-to-end voice wake-up solution for voice-first devices, using two STMicroelectronics microcontrollers and the Sensory wake word engine.
Read the release →Aspinity announces ultra-low power analog processing technology that overcomes the power and data handling challenges in battery-operated always-on sensing devices.
Read the release →Aspinity raises $2.9M from Birchmere Ventures, the Amazon Alexa Fund and other investors to enable ultra-low power, always-on sensing.
Read the release →Press coverage, podcasts, and video features on Aspinity's analog AI.
Automotive Industries interviewed CEO Richard Hegberg about the new automotive security solution.
Read the article →Matt Ferrell discusses how and why analog is so important for the future of energy-efficient AI.
Read the article →Aspinity featured with Ian Cutress and Sally Ward-Foxton, discussing the AML100.
Read the article →The benefits of analog computing and how they may change the way we interact with our devices.
Read the article →Part of the EE Times Analog Everywhere Trends Series — saving always-on product power with AnalogML.
Read the article →The AML100 made the finals in the Solutions Provider / Innovative Tech category.
Read the article →Editor Brian Bailey explores the “fundamental rethinking” of machine learning in intelligent edge devices.
Read the article →Tom Doyle joins Justin Grammens to discuss applying AI to always-on sensing.
Read the article →The AML100 delivers minimal false alarms alongside a battery life of five years or longer.
Read the article →Daniel Nenni explores the benefits of Aspinity's analog signal processing technology.
Read the article →Rich Nass on how the AML100 brings machine learning into the analog domain to extend battery life.
Read the article →Max Maxfield examines the use of analog and its implementation in the AML100 processing chip.
Read the article →Gareth Halfacree explains how the AML100 lets high-power digital parts stay asleep.
Read the article →Sally Ward-Foxton talks with Tom Doyle about the new AML100.
Read the article →Majeed Ahmad explores the capabilities of Aspinity's new AML100 chip.
Read the article →Jake Hertz explains what happens when you apply the merits of analog computing to machine learning.
Read the article →Sophie Burkholder on what it means to have Aspinity in Pittsburgh, a fertile region for engineering talent.
Read the article →Majeed Ahmad explains how analog plays an important role in battery-operated always-on sensing devices.
Read the article →What is analog computing, and what do engineers need to know about it?
Read the article →TechVibe Radio speaks with Aspinity's Marcie Weinstein about the company's technology and life in Pittsburgh's Strip District.
Read the article →Rich Nass speaks with Tom Doyle about what AnalogML is, how it works, and why anyone should care.
Read the article →How analog is being used in several different ways to solve the always-on power problem — an article by CEO Tom Doyle.
Read the article →What designers need to know about the differences between analog in-memory computing and the AnalogML core.
Read the article →Max Maxfield on the AnalogML core and the emergence of analog as an important component of machine learning at the edge.
Read the article →Amelia Dalton interviews Aspinity to learn why analog is critical for the digital future.
Read the article →Bryon Moyer looks at how analog can be used to save power in machine learning applications.
Read the article →Sally Ward-Foxton writes about the new evaluation kit for analog acoustic event detection and system wake-up.
Read the article →Karen Field talks with Tom Doyle about how AnalogML addresses power challenges for always-on edge processing.
Read the article →Tom Doyle explains how analog machine learning enables a system-level approach to power efficiency.
Read the article →How intelligently minimizing the data running through an always-listening system preserves battery life.
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