The latest from Coral
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We're pleased to announce that we have signed an agreement with ASUS IoT, to help scale our manufacturing, distribution and support. 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.
Earlier this year, Pratexo began working to bring the "electricity grid edge" to HKN, starting with putting intelligent computing nodes running Pratexo software enabled with Coral intelligence at transformer stations. This system allows predictions about each transformer’s performance and future reliability and, ultimately, the system as a whole.
Mendel 5.0, Windows support for PCIe, and open-sourced runtime.
An automotive component supplier in the U.S. autonomously monitors safety and productivity on its assembly lines. A life sciences company in France sorts thousands of Petri dishes an hour to speed drug discovery. And a French manufacturer checks the integrity of food containers as they speed down the production line. Edge AI from Coral implemented by Accenture makes it all possible.
Earlier this year, Pratexo began working to bring the "electricity grid edge" to HKN, starting with putting intelligent computing nodes running Pratexo software enabled with Coral intelligence at transformer stations. This system allows predictions about each transformer’s performance and future reliability and, ultimately, the system as a whole.
Darcy and its user-friendly software make the potentially challenging task of standing up AI applications much easier for the likes of city administrators, school districts, and even farmers looking for ways to monitor remote fields and orchards for areas that need attention.
Silicon Valley-based start-up Companion Labs is putting automated training in reach of every animal shelter and dog owner. Training that could not only save more dogs, but also has the potential to save human lives. It all comes down to a box, smaller than a minifridge, with artificial intelligence on board.
Coral engineers have packed the Google Edge TPU machine learning co-processor into a solderable multi-chip module that’s smaller than a US penny. The new Accelerator Module lets developers solder privacy-preserving, low-power, and high performance edge ML acceleration into just about any hardware project.
Kura Revolving Sushi Bar in Japan has built an AI powered system that not only allows for better customer experiences, but also enables better tracking to prevent food borne illnesses.
High-end conference room setups can be expensive and cumbersome for most businesses to deploy and maintain. Google’s new Series One meeting room kits use on-device AI to filter out unwanted noise while focusing audio pickup on individual participants.
Around a third of the food farmers produce never make it to the table. Growers lose as much as 10 percent of their grains or beans at harvest. Waste is a very big problem, and it starts out in the field.
Now, farmers can manage potential losses during harvest in real-time, thanks to an AI-powered tool from Farmwave.
The data that highway departments, factories, and industrial plants need to head off unplanned obstacles often comes too late.
To help solve the problem, NEXCOM—an industrial computing company with two decades of experience—is using Coral products built into Internet of Things (IoT) gateways that analyze and deliver key information exactly when and where it’s needed.
Olea Edge, based in Austin, Texas, is helping water utilities and businesses conserve water by adding smarts to commercial water meters using Coral’s AI-at-the-edge platform.
Colorectal cancer is the second most lethal cancer after breast cancer. Virgo uses Coral in its endoscopic video system to help doctors spot abnormalities in colonoscopies.
Care.ai deploys computer vision to detect falls and other dangers. A vital factor in its success; Coral's AI platform, which keeps processing local, providing safety while preserving patient privacy.
Since we launched Coral back in March 2019, we’ve added a number of new product form factors to accommodate the many ways users are adding on-device ML to their products.
We're pleased to announce that we have signed an agreement with ASUS IoT, to help scale our manufacturing, distribution and support. 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.
The VisionAI smart camera features a quad-core Cortex-A53 ARM processor and a Coral Accelerator to support AI, deep learning, and machine learning applications.
The new release brings parity across the C++ and Python SDKs and includes more efficient memory usage. Other updates include additional pre-trained models and general availability of model pipelining.
The mini board has a 40-pin GPIO header, a pair of USB-C ports for power and connecting to a PC, and a 24-pin ribbon cable port for a camera module, which should give it plenty of field utility. This is not an all-in-one solution like the Jetson Nano dev kit, but should work for anybody with a PC who wants to get started in AI.
The update adds the M.2 Accelerator with Dual Edge TPU which was used in Google’s Series One room kits where it helped remove interruptions and made the audio clearer for better video meetings.
Moving into the fall, the Coral platform continues to grow with the release of the M.2 Accelerator with Dual Edge TPU. Its first application is in Google’s Series One room kits where it helps to remove interruptions and make the audio clearer for better video meetings.
Nexcom announced two Coffee Lake and three Apollo Lake in-vehicle systems that ship with Google’s Coral Edge TPU mini-PCIe cards and 4x to 8x PoE ports. Google recently released an open source runtime for the Edge TPU.
Summer has arrived along with a number of Coral updates. We've released a series of updates to expand platform compatibility, make development easier, and improve the ML capabilities of our devices.
Together, Coral + balena simplify how edge developers provision, deploy, and manage their AI projects. We’re ready for any project, whether it’s working with early prototypes, or in production environments with many thousands of devices.
Recently, we’ve seen communities respond to the challenges of the coronavirus pandemic by using technology in new ways to effect positive change. It’s increasingly important that our systems are able to adapt to new contexts, handle disruptions, and remain efficient.
At Coral, we believe intelligence at the edge is a key ingredient towards building a more resilient future.
The company has expanded its Coral lineup by unveiling two new Coral AI products — Coral Dev Board Mini and Coral Accelerator Module. Announced ahead of the Consumer Electronics Show (CES) this year, the latest addition to the Coral family followed a successful beta run of the platform in October 2019.
e-Con Systems has announced a camera series that can be used with the Google Coral Development board. There are two models: e-CAM50 CUCRL is a 5.0 MP MIPI CSI-2 camera and e-CAM30 CUCRL is a 3.4 MP MIPI CSI-2 camera.
Helping Enterprises Build Local AI Solutions
On-device AI promises to make computers faster and more secure. But applications are useful only so long as they’re fast and secure. These are the sorts of problems Google is trying to solve through a little-known initiative called Coral.
10 of 13: Working in partnership with Coral and Google, Murata Electronics has developed what it is calling the world's smallest AI module.
In this article you will learn how to create a budget AI Cloud that provides an Object Detection REST API with accelerated performance made possible by Google’s Coral EdgeTPU Technology.
More and more industries are beginning to recognize the value of local AI, where the speed of local inference allows considerable savings on bandwidth and cloud compute costs, and keeping data local preserves user privacy.
Google's Coral AI developer board moves out of beta.
Coral Dev Board can execute state-of-the-art mobile vision models such as MobileNet V2 at 100+ fps, in a power-efficient manner. Given the focus on computer vision use cases, Coral Dev Board makes prototyping computer vision applications easier with a Camera that connects to the Dev Board over a MIPI interface.
"There’s a steady drumbeat about how deep learning is going to touch nearly every area of technology, not least from us here at IEEE Spectrum. So, like a lot of folks, I’ve been interested in getting my hands dirty and learning some of the tools and techniques."
Both dev board and accelerator are powered by Google’s Edge TPU chips, which are ASIC processors no bigger than your fingernail
"Through this challenge, our community at Hackster, the UNDP and Avnet’s technology partners are coming together to provide innovative solutions to get lifesaving technology to some of the world’s most vulnerable areas," said Bill Amelio, CEO, Avnet.
EfficientDet is the next-generation version of EfficientNet, a family of advanced object detection models made available last year for Coral boards.
Edge computing is growing in popularity. We look at which IoT applications stand to benefit the most from this technology.
To help make the expanding use of data applications across billions of connected devices more efficient and valuable, there is growing momentum to migrate the processing from centralized third-party cloud servers to decentralized and localized on-device, commonly referred to as edge computing.
One of machine learning’s promises is to help humans do things faster and more efficiently. PerceptiLabs, a two-person Swedish startup, developed a visual drag-and-drop interface to streamline and simplify the entire process.