BrainChip Chief Development Officer Presents at the Edge AI and Vision Alliance Spotlight Webinar
(ASX: BRN), a leading provider of ultra-low power, high-performance AI technology, announced that the companys Chief Development Officer Anil Mankar will present about using neuromorphic processing to take AI to the Edge in a free 30-minute webinar organized by the Edge AI and Vision Alliance December 17 at 9 a.m. PST.
BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low power, high-performance AI technology, announced that the company’s Chief Development Officer Anil Mankar will present about using neuromorphic processing to take AI to the Edge in a free 30-minute webinar organized by the Edge AI and Vision Alliance December 17 at 9 a.m. PST.
Mankar has spent 30 years developing products in the semiconductor industry, including in management leadership positions at Western Digital, Conexant Systems and Mindspeed Technologies. His presentation, “Power-efficient Edge AI Applications through Neuromorphic Processing,” will describe the advantages of processing information in the event-domain including an update on the AKD1000, BrainChip’s first Neural network SoC (NSoC).
“I look forward to presenting how the AKD1000 is bringing artificial intelligence to the edge in a way that existing technologies are not capable,” said Mankar. “Many Edge-AI processors take advantage of the spatial sparsity in neural network models to eliminate computations and save power. Neuromorphic processors achieve further savings by performing event-based computation, which exploits the temporal sparsity inherent in data generated by audio, vision, olfactory, lidar and other edge sensors.”
The Akida Neural Processor technology, which is implemented in the Neuromorphic System-on-Chip (NSoC), is 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. The Akida NSoC represents a revolutionary new breed of Neural Processing computing devices for Edge AI devices and systems. Comparisons to leading DNN accelerator devices show significantly better images/second/watt running industry standard benchmarks with MobileNet, MobileNet-SSD and Key Word Spotting, while maintaining excellent accuracy.
The Akida NSoC is designed for use as a stand-alone embedded accelerator or as a co-processor. It includes interfaces for ADAS sensors, audio sensors, and other IoT sensors. It also has high-speed data interfaces such as PCI-Express, USB, 12S and 13C. An on-chip MPU is used to control the configuration of the Akida Neuron Fabric as well as off-chip communication of metadata. The Akida NSoC represents a scalable solution utilizing a built-in serial chip to chip connectivity to allow up to 64 devices to be arrayed for a single solution.
Interested parties can visit the event page to register for this free webinar. Additional information is available by emailing [email protected].
About Brainchip Holdings Ltd (ASX: BRN)
BrainChip is a global technology company that is producing a groundbreaking neuromorphic processor that brings artificial intelligence to the edge in a way that is beyond the capabilities of other products. The chip is high performance, small, ultra-low power and enables a wide array of edge capabilities that include on-chip training, learning and inference. The event-based neural network processor is inspired by the spiking nature of the human brain and is implemented in an industry standard digital process. By mimicking brain processing BrainChip has pioneered a processing architecture, called Akida™, 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 through transmission via the cloud to a data center. Akida is designed to provide a complete ultra-low power and fast AI Edge Network for vision, audio, olfactory 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 of data centers.
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