BrainChip Takes a Look at what ML and AI can Achieve with Arm Fellow Jem Davies

Latest ‘This is our Mission’ podcast episode continues outside-looking-in theme with insight into the future of differentiated solutions and their impact on respective markets

Aliso Viejo, Calif. – June 30, 2021 BrainChip Holdings Ltd (ASX: BRN), (OTCQX: BRCHF), a leading provider of ultra-low power high performance artificial intelligence technology, today announced that Jem Davies, VP, Fellow and GM of the Machine Learning Group at Arm joins BrainChip Vice President of Worldwide Sales, Rob Telson, on the latest “This is our Mission” podcast episode designed to provide insight on the Company’s strategy and progress.  The 23-minute podcast will be available through the company’s website,, as well as across all major podcast platforms July 6, at 4 p.m. PDT.

An experienced technologist and architect, Davies has run the ML group within Arm for the past 4 years, driving the technology inflection across the company and guiding the direction of the company as it supports evolving workloads. In the eighth episode of the series, Davies and Telson discuss the process that technology undergoes before implementation at the consumer level, how AI on devices is helping to evolve the direction of the technology, and how these transformations can ultimately benefit society.

“With hundreds of billions of Arm-designed chips in devices, there is a tremendous opportunity to implement AI and ML technologies that provide efficiencies and optimization, which will transform business in the coming years,” said Telson. “Jem’s deep appreciation for what ML and AI can achieve, places him in a unique position to not only envision what the world will look like with the transition to these emerging workloads, but will help drive the very solutions for Arm partners looking to provide faster and more efficient devices that can get us there.  His amazing insights into how small measures in deploying AI-based devices can provide cascading benefits in energy efficiencies, faster and more accurate business decisions, and the ability to solve problems, with the ‘three V’s’, make for an informative podcast.”

BrainChip’s Akida 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) 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 BrainChip Podcast is a monthly event intended to provide company and industry insight for the engineering community in target markets, as well as analysts, technical and financial press and investors.

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

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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