Google partners with Asus IoT to spread availability of Coral on-device AI hardware – 9to5Google

Coral is Google’s platform for adding on-device AI and inferencing capabilities to hardware. To make it more widely available, especially for Internet of Things use cases, Google is partnering with Asus IoT.

Asus IoT is a sub-brand of Asus, and Google wants to scale manufacturing, distribution, and support for Coral with this agreement. 

With decades of experience in electronics manufacturing at a global scale, ASUS IoT will provide Coral with the resources to meet our growth demands while we continue to develop new products for edge computing.

This will see Asus IoT “become the primary channel for sales, distribution and support” for Coral, with customers getting “dedicated teams for sales and technical support” in the process. This includes an expanded distribution network that will allow products to become available in more countries.

ASUS IoT already has a long-standing history of collaboration with Coral, being the first partner to release a product using the Coral SoM when they launched the Tinker Edge T development board. ASUS IoT has also integrated Coral accelerators into their enterprise class intelligent edge computers and was the first to release a multi Edge TPU device with the award winning AI Accelerator PCIe Card. Because we have this history of collaboration, we know they share our strong commitment to new innovation in edge computing.

The Coral line of hardware allows AI to run on-device, and therefore offline, without needing to send data to the cloud, which has the upside of being faster and more secure. This can be used for object detection, pose estimation, image segmentation, and key phrase detection. Google uses it for the Series One line (with Lenovo) of video conferencing room kits for “on-the-fly noise removal.”

With this Asus IoT-Coral partnership, Google will “maintain ownership of the brand and product portfolio” and “focus on building the next generation of privacy-preserving features and tools for neural computing at the edge.”

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