ALISO VIEJO, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd (ASX: BRN), a leading provider of Ultra-Low Power, high performance AI technology, today announced an Early Access Program (EAP) for the Akida™ neural processor System-on-Chip (SoC). The EAP has been targeted at specific customers in a diversity of end markets for early adoption of the Akida device.
Since announcing the start of wafer fabrication in April 2020, the demand for evaluation systems, including engineering prototypes, has been significant. In response to this demand, BrainChip has established an EAP for select partners to ensure availability of initial devices and evaluation systems for key applications. Multiple customers have committed to the advanced purchase of evaluation systems for a range of strategic Edge applications including ADAS/AV, Unmanned Aerial Vehicles (UAV), Edge vision systems and factory automation.
The EAP includes evaluation boards with the Akida device, software and hardware support and dedicated engineering resources. The EAP agreements include payments intended to offset the Company’s expenses to support partner needs.
Partners have engaged in the early development of systems and solutions utilizing the powerful software development environment and chip simulator all contained in the Akida Development Environment (ADE). By utilizing the complete flow available in the ADE, designers have successfully developed and trained highly-optimized neural network solutions using the Company’s development flow, including the Tensorflow and Keras environments. Optimized and trained models can be run on the ADE to evaluate performance on the Akida processor. With the Akida evaluation board, the same trained networks and control files used in the ADE will be used to program the neural processor SoC to run the complete neural network. This enables partners to implement their hardware solutions quickly and efficiently.
Louis DiNardo, BrainChip CEO, commented, “We are very pleased with the level of interest and commitment to the Akida neural processor. Leading companies in the automotive industry and surveillance market have committed to the Early Access Program or signed Development Agreements. Additionally, we are focused on opportunities in the Smart Home area, Smart Health and Industrial IoT.” DiNardo continued, “The level of engagement with key partners and industry leaders is a testament to the value of the Akida neural processor which enables ultra-low power AI technology with continuous learning to be implemented effectively in a wide range of Edge applications.”
“I am excited to see the application of BrainChip’s innovative neural processor solution to solve challenging problems facing industries implementing Edge AI, such as automotive ADAS and AV,” said Rich Wawrzyniak of Semico Research. “BrainChip’s Akida neural processor is an ideal fit for applications in which high performance is required in a tight power budget. The capability to process only the relevant event-driven data in an application is a great solution for many situations where much of the data can be extraneous and processing it just wastes power. Good job BrainChip!”
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 datacenter. 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 datacenters.
Additional information is available at https://www.brainchipinc.com
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