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Mercedes Applies Neuromorphic Computing in EV Concept Car viaSally Ward-Foxton The Mercedes Vision EQXX concept car, promoted as “the most efficient Mercedes-Benz ever built,” incorporates neuromorphic computing to help reduce power consumption and extend vehicle range. To that end, BrainChip’s Akida neuromorphic chip enables in-cabin keyword spotting as a more power-efficient way than existing AI-based keyword detection systems. As automakers shift their focus to electric vehicles, many are struggling to squeeze every last volt from a single battery charge. The need to reduce power consumption in vehicle electronic systems has therefore become critical to extending EV range. Touting Vision EQXX as “a car that thinks like you,” Mercedes promises range of more than 1,000 km (about 620 miles) on a single charge. “Working with California-based artificial intelligence experts BrainChip, Mercedes-Benz engineers developed systems based on BrainChip’s Akida hardware and software,” Mercedes noted in a statement describing the Vision EQXX. “The example in the Vision EQXX is the “Hey Mercedes” hot-word detection. Structured along neuromorphic principles, it is five to ten times more efficient than conventional voice control,” the carmaker claimed…READ THE FULL ARTICLE The postMercedes Applies Neuromorphic Computing in EV Concept Carappeared first onBrainChip. Read On BrainChip.com

Developing Optimized Systems with BrainChip’s Akida Neuromorphic Processor February 24, 2022 – 9:00 am US-PT BrainChip’s Akida processor today finds use in a diversity of applications, such as classifying images, identifying odors and tastes, recognizing breath data for disease classification, identifying air quality, interpreting LiDAR laser light data, recognizing keywords, and detecting cybersecurity attacks. Akida leverages advanced neuromorphic computing as its processing “engine”, delivering key features such as one-shot learning and on-device computing with no “cloud” dependencies. As such, it’s particularly valuable in evolving smart “edge” devices, where privacy, security, low power consumption, low latency and high performance, low cost, and small size are all important criteria. In this session, you’ll learn how to easily develop efficient AI in edge devices by implementing Akida IP either into your SoC or as standalone silicon. The webinar is co-presented by Rob Telson, Vice President of Worldwide Sales, and Todd Vierra, Director of Customer Engagement, both of BrainChip. The presenters will provide detailed performance and other results, derived from real-life system implementations using production Akida silicon, as well as share a variety of design techniques and support resources. A question-and-answer session will follow the presentation. RegisterHERE The postWebinar: Edge AI + Vision Alliance – February 24, 2022appeared first onBrainChip. Read On BrainChip.com