BrainChip Holdings Ltd. (ASX: BRN), (OTCQX: BRCHF), a leading provider of ultra-low power, high-performance AI technology, today announced that Chief Development Officer Anil Mankar will join host Stephen Foskett in highlighting the Akida™ Neural Processor at the AI Field Day 2 event May 26-28.
AI Field Day is the latest entry into the long-running series of Tech Field Day events presented by Gestalt IT. BrainChip will discuss recent developments about its Akida event domain neural processor SoC, a next-generation, fully integrated solution for Edge AI devices and systems, during a live-streamed meeting of invite-only influencers on Monday from 8:00am to 9:30am PDT. The session will later be available for viewing on the program’s social media channels.
BrainChip is delivering on next-generation demands by achieving efficient, effective AI functionality. The company’s Akida neuromorphic processors are revolutionary advanced neural networking processors that bring 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) and intellectual property, 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 Akida NSoC is designed for use as a stand-alone embedded accelerator or as a co-processor, and includes interfaces for ADAS sensors, audio sensors, and other IoT sensors. Akida brings AI processing capability to edge devices for learning, enabling personalization of products without the need for retraining.
“We had such a positive reception debuting the Akida technology at the first AI Field Day that we couldn’t wait to come back and provide updates at this upcoming event,” said Mankar. “With the demand for generating data at the edge, we believe the Edge is best place to deploy a platform for continuous and autonomous learning that adapts to the local environment. As more and more devices come online, Akida is able to allow for incremental learning and high-speed inferencing in a wide variety of use cases. I look forward to sharing our latest developments and how Akida continues to advance to suit the needs of organizations across multiple markets.”
Tech Field Day is a series of invite-only technical meetings between delegates invited from around the world and sponsoring enterprise IT companies that share their products and ideas through presentations, demos, roundtables, and more. Over 2-3 days, a panel of a dozen delegates interact with 6-10 companies on-site in areas like Silicon Valley. These sessions are live-streamed and recordings are shared across our social media channels like YouTube and Twitter. Events focus on enterprise IT topics from the datacenter to the cloud, mobility and networking to security and storage.
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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