BrainChip Goes to the Edge and Beyond at Edge AI Summit

Company executives are featured speakers at multiple presentations, roundtables and discussions during leading industry event

Aliso Viejo, Calif. – DATE, 2021BrainChip Holdings Ltd (ASX: BRN), (OTCQX: BCHPY), a leading provider of ultra-low power, high-performance artificial intelligence technology and the world’s first commercial producer of neuromorphic AI chips and IP, today announced its participation in the Edge AI Summit, a virtual event November 15-18.  Company executives will host a roundtable discussion, present to session attendees and participate on a panel about how neuromorphic computing addresses the challenges at the edge.

The Edge AI Summit aids enterprise adopters, OEMs, AI software and hardware providers in their pursuit of deploying AI at the edge by helping them form partnerships that will improve the performance of embedded hardware, optimize models and compress workloads to enable high-performing and low-footprint AI to exist at the edge. BrainChip session highlights include:

  • Anil Mankar, Chief Development Officer and Co-Founder of BrainChip, hosting the roundtable “BrainChip MetaTF Development Environment: Easy-to-Use Complete ML Framework” November 15 at 11:45 a.m. PST
  • Rob Telson, Vice President of Worldwide Sales at BrainChip, presenting “Intelligent AI at the Edge: Efficient, Effective and Easy” November 17 at 8:45 a.m. PST
  • Mankar returning for a panel discussing overcoming architectural challenges November 17 at noon PST

“With the acceleration of AI at the edge, what better place to demonstrate the capabilities of our Akida advanced neuromorphic architecture than at the Edge AI Summit,” said Mankar. “We are at the stage where evangelizing our approach to this emerging market opportunity is being replaced by our introduction of a production version of the Akida chip. I know Rob and I are eager to present and discuss the possibilities of AI at the edge as well as how Akida will revolutionize the industry in a way that existing technologies are not capable of.”

BrainChip’s Akida brings artificial intelligence to the edge in a way that existing technologies are not capable. With the introduction of one-shot learning and achieving ultra-low power, the solution is high-performance, small, and enables a wide array of edge capabilities. The Akida (NSoC) and intellectual property on chip learning, can be used in applications including Smart Home, Smart Health, Smart City and Smart Transportation. These applications include but are not limited to home automation and remote controls, industrial IoT, robotics, security cameras, sensors, unmanned aircraft, autonomous vehicles, medical instruments, object detection, sound detection, odor and taste detection, gesture control and cybersecurity.

The 4th annual Edge AI Summit unites the technologists from around the world tasked with designing and developing real-world use cases that bring real-time and secure AI to low-power applications from the sensor-edge to device-edge, and to areas that have limited connectivity to the cloud. Additional information about the event is available at

About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BCHPY)

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

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