BrainChip Presents on AI in Edge Devices at Linley Fall Processor Conference 2020
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BrainChip Presents on AI in Edge Devices at Linley Fall Processor Conference 2020

ALISO VIEJO, Calif. — (BUSINESS WIRE) — October 1, 2020BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low power high performance AI technology, today announced that Chief Development Officer Anil Mankar will present “A Neuromorphic Processor for Power Efficient Edge AI Applications” at the Linley Fall Processor Conference 2020 October 20 at 9:30 a.m. PDT.

BrainChip’s presentation is part of the conference’s first-day session “AI in Edge Devices.” As part of the presentation, Mankar will provide an update on the AKD1000, BrainChip’s first Neural network SoC (NSoC), and describe the advantages of processing information in the event-domain. A 10-minute Q&A session will immediately follow the conclusion of his speech.

“Many edge-AI processors take advantage of the spatial sparsity in neural network models to eliminate unnecessary computations and save power,” said Mankar. “But 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. I look forward to sharing with attendees of the Linley Conference how this unique approach is revolutionizing artificial intelligence at the edge.”

The company’s 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.

"Industry demand for AI performance has skyrocketed over the last few years, driven by rapid adoption from the data center to the edge,” said Linley Gwennap, principal analyst at the Linley Group and Linley Fall Processor Conference chairperson. “This year's Linley Fall Processor Conference will feature our biggest program yet and will introduce a host of new technology disclosures and product announcements of innovative processor architectures and IP technologies. In spite of the challenges posed by the pandemic, development of these technologies continues to accelerate and we're excited to be sharing these presentations with a global audience via our live-streamed format."

For more than a decade, The Linley Group has delivered the industry’s premier processor conference. This year, the Linley Fall Processor Conference will feature virtual presentations that run half days on October 20-22 and 27-29, 2020. Presentations will address processors and IP cores for AI applications, embedded, data center, automotive, and communications. Attendees will be able to view live-streamed presentations and interact with the speakers during Q&A, breakout sessions, or scheduled one-on-one meetings. Additional information about the event is available at https://www.linleygroup.com/events/event.php?num=49

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.

Additional information is available at https://www.brainchipinc.com

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