Google Coral AI Board Steps Out Of Beta To Battle Raspberry Pi
Many tech companies are investing heavily in artificial intelligence (AI). These kinds of programs and products can be rather expensive, but there are a few that are more accessible to the public and small companies. Google’s Coral AI board has just come out of beta and has been released on a wider scale.
Coral is a complete AI toolkit that helps researchers to “bring new models out of the data center and onto devices, running TensorFlow models efficiently at the edge.” The toolkit has allowed a variety of institutions to incorporate AI into new solutions. For example, Virgo Surgical Video Solutions has used Coral to improve the accuracy of endoscopies. This type of technology could be essential in detecting colon cancer.
Coral has been in beta for six months and Google has started to offer a few products that respond to their testers’ needs. Google has been selling a Coral Dev Board or a “a single-board computer with a removable system-on-module (SoM)”. Users will now be able to purchase the SoM on its own. Google now also offers three Accelerators that include the Edge TPU-- Mini PCIe, M.2 A+E key, and M.2 B+M key. All three of these Accelerators can be purchased separately.
On top of everything, there is a new baseboard developer guide to help users integrate a Coral SoM into their own products. Users can also find code samples and project tutorials. The samples assist users with common AI solutions such as image classification, keyword spotting, and even how to perform classifications with a “TensorFlow Lite Python API and Raspberry Pi Camera”.
Google is still working on updating Coral and expanding it to new markets. Their Dev Board and SoM should be available in Taiwan, Australia, New Zealand, India, Thailand, Singapore, Oman, Ghana, and the Philippines by the end of the year. They also plan to release a new version of Mendel Linux, the OS that is used on the Coral Dev Board.
Although Google is actively encouraging the use of AI, they are also trying to battle its excesses. They recently released a free database of deepfake videos to help researchers and engineers create better detection tools. The database is part of Google’s goal to develop AI best practices.
Coral is a complete AI toolkit that helps researchers to “bring new models out of the data center and onto devices, running TensorFlow models efficiently at the edge.” The toolkit has allowed a variety of institutions to incorporate AI into new solutions. For example, Virgo Surgical Video Solutions has used Coral to improve the accuracy of endoscopies. This type of technology could be essential in detecting colon cancer.
Coral has been in beta for six months and Google has started to offer a few products that respond to their testers’ needs. Google has been selling a Coral Dev Board or a “a single-board computer with a removable system-on-module (SoM)”. Users will now be able to purchase the SoM on its own. Google now also offers three Accelerators that include the Edge TPU-- Mini PCIe, M.2 A+E key, and M.2 B+M key. All three of these Accelerators can be purchased separately.
On top of everything, there is a new baseboard developer guide to help users integrate a Coral SoM into their own products. Users can also find code samples and project tutorials. The samples assist users with common AI solutions such as image classification, keyword spotting, and even how to perform classifications with a “TensorFlow Lite Python API and Raspberry Pi Camera”.
Google is still working on updating Coral and expanding it to new markets. Their Dev Board and SoM should be available in Taiwan, Australia, New Zealand, India, Thailand, Singapore, Oman, Ghana, and the Philippines by the end of the year. They also plan to release a new version of Mendel Linux, the OS that is used on the Coral Dev Board.
Although Google is actively encouraging the use of AI, they are also trying to battle its excesses. They recently released a free database of deepfake videos to help researchers and engineers create better detection tools. The database is part of Google’s goal to develop AI best practices.
