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News: BRN Brainchip Awarded New Patent For AI Dynamic Neural Network, page-2

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    BrainChip Awarded New Patent for Artificial Intelligence Dynamic Neural NetworkBusiness WireOctober 23, 2019, 2:29 AM GMT+11SAN FRANCISCO--(BUSINESS WIRE)--BrainChip, a leading provider of ultra-low power, high performance edge AI technology, has been awarded a new patent for dynamic neural function libraries, a key component of its AI processing chip AkidaTM.United States Patent number 10,410,117 addresses a dynamic neural network within an AI device. During a learning process, values are generated and stored in the synaptic registers of the AI device to generate a training model. Training models are themselves stored in the dynamic neural function library of the AI device, and the function library can then be used to train another device.

    The innovation was credited to Peter Van der Made, BrainChip founder and CTO, who has been at the forefront of computer innovation for 40 years. Van der Made is the inventor of a computer immune system at cybersecurity developer vCIS Technology, where he served as CTO and later Chief Scientist when it was acquired by Internet Security Systems and subsequently IBM. Previously, he designed a high resolution, high-speed color Graphics Accelerator Chip for IBM PC graphics. Van der Made is the author of the book Higher Intelligence, which explains the architecture of the brain from a computer science perspective.

    “This patent addresses efficiency that contributes to how Akida technology excels in speed, accuracy, and ultra-low power consumption,” said Van der Made. “Synapses store values, these thousands of synapses connect to thousands of neurons, and that neural output can be used by another set of neurons – which is closer to the way the human brain processes information.”

    BrainChip’s intellectual portfolio consists of 11 patents issued or in process, including a foundational patent in the area of Spiking Neural Networks (SNN) that has been cited by leading companies such as IBM, Qualcomm, Samsung, and Hewlett Packard.

    With the proliferation of intelligence into edge devices, there is a new and growing need for fast, small, and power-efficient neural network processors. By performing neural processing and memory accesses on the edge, Akida vastly reduces the computing resources required of the host CPU. This unprecedented efficiency not only delivers faster results, it consumes only a tiny fraction of the power resources of traditional AI processing, reducing the high environmental and economic costs of running hyperscale data centers.

    Akida is available as a licensable IP technology that can be integrated into ASIC devices and will be available as an integrated SoC, both suitable for applications such as surveillance, advanced driver assistance systems (ADAS), autonomous vehicles (AV), vision guided robotics, drones, augmented and virtual reality (AR/VR), acoustic analysis, and Industrial Internet-of-Things (IoT).

    Follow us on Twitter: https://twitter.com/BrainChip_incFollow us on LinkedIn: https://www.linkedin.com/company/7792006About BrainChip Holdings Ltd (BRN.AX)BrainChip is a global technology company that has developed a revolutionary advanced neural networking processor that brings artificial intelligence to the edge in a way that existing technologies are not capable. The solution is high performance, small, ultra-low power and enables a wide array of edge capabilities that include local training, learning and inference. The Company markets an innovative event-based neural network processor that is inspired by the spiking nature of the human brain and implements the network processor in an industry standard digital process. By mimicking brain processing BrainChip has pioneered a spiking neural network, called AkidaTM, which is both scalable and flexible to address the requirements in edge devices. At the edge, sensor inputs are analyzed at the point of acquisition rather than transmission to the cloud or a datacenter. Akida is designed to provide a complete ultra-low power AI Edge Network for vision, audio and smart transducer applications. The reduction in system latency provides faster response and a more power efficient system that can reduce the large carbon footprint datacenters. Additional information is available at https://www.brainchipinc.com.

    https://www.businesswire.com/news/home/20191022005863/en/


 
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