RECOGNIZED AS A FINALIST IN THE INNOVATIVE PRODUCT OF THE YEAR CATEGORY FOR ABR'S ULTRA-EFFICIENT EDGE AI TIME-SERIES PROCESSOR (TSP) CHIP.
Waterloo, Ontario, Canada – June 23, 2022 - Applied Brain Research today announces it has been named a finalist in the Innovative Product of the Year category of the Best of Sensors Awards for their ultra-efficient edge AI Time-Series Processor (TSP) chip. The ABR TSP offers sensor, IoT device, car, appliance, consumer electronics and all device makers the ability to process large-scale time-series data at the edge. The chip enables full speech recognition, robust natural language understanding, anomaly detection, pattern recognition, machine health monitoring, and more.
“Applied Brain Research is honored to be a finalist in the Best of Sensors Awards for our TSP chip,” said ABR’s Co-CEO, Peter Suma. “Cloud reliance is a large barrier to entry to ubiquitous speech and sensor processing. Our chip removes this barrier by bringing large-scale time series capabilities to the edge.”
The ABR TSP is a low-SWaP, edge, time-series AI processor chip that is used to implement ultra-low-SWaP embedded sensor data processing, AI speech processing and language processing systems. The ABR TSP implements on-chip ABR’s patented optimally efficient time-series and signal processing algorithm, the Legendre Memory Unit (LMU).
For a few dollars, device companies can now communicate their device set-up and manuals to users in a natural and intuitive way without a cloud connection. ABR TSP embeds training-free, natural language voice interfaces, including troubleshooters and user manuals, and will revolutionize device interaction.
ABR offers sensors the ability to process complex AI edge event detection, over longer windows of signal time, for far less power, with longer battery life, while only sending events for further processing.
Charlene Soucy, Senior Director, Sensors & Electronics said, “Again this year the innovation in the sensors industry did not disappoint with new, innovative ground-breaking technologies and individuals doing spectacular work. The Best of Sensors Awards was created to recognize the industry’s best innovations. We congratulate Applied Brain Research Inc. on being named a finalist.”
Submissions were judged based on the value to the marketplace, the impact of the problems it solves or issues it addresses and the uniqueness of the design. The judges for the Best of Sensors awards were Roger Grace, Roger Grace Associates, Jack Gold, J. Gold Associates, Matt Hamblen, Fierce Electronics, Brian Zahnstecher, PowerRox, Leonard Lee, neXt Curve, and Mary Ann Maher, SoftMEMS.
Award winners will be announced on June 28 at Sensors Converge. Sensors Converge will be co-located with Embedded Technologies Conference & Expo, Autonomous Technologies Conference, and Metaverse Global Congress.
Applied Brain Research, Inc. designs AI inspired by the efficiency of brain circuits and backed by neuroscientists and AI engineers. ABR builds AI chips and makes software to build low-power embedded AI systems used in devices like smartphones, drones, robots, cars, cameras, clothing, wearables, and sensors. ABR discovered an AI time-series processing algorithm called the Legendre Memory Unit (LMU) from this work. The LMU algorithm outperforms LSTMs and Transformers on time-series applications by a factor of 10x. ABR has used the LMU to create an ultra-efficient time series processor chip which will be available in Q4 of 2023.
Sensors Converge delivers the ultimate combination of education, networking, and training for the sensors and electronics industry. There are several registration options, including the All-Access Pass, which provides access to the entire event, Conference passes to Sensors and co-located events, and the Expo Hall Pass, which offers access to the Expo Hall. Advance registration rates are available. For more information, visit: https://www.sensorsconverge.com/sensorsconvergecom/register. The awards program is presented by Sensors Converge and Fierce Electronics and honors the best in sensor technologies and the sensor ecosystem, people and companies.
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