Google發表本地AI平台Coral
Google 發表本地 AI 平台 Coral
News from: iThome & Google Developers.
Web stie:
https://developers.googleblog.com/2019/03/introducing-coral-our-platform-for.html
Google發表本地AI平台Coral的公開測試版，內含開發AI裝置必要的軟、硬體及內容，以讓開發人員可於本地端的裝置上建立、訓練及執行神經網路，協助開發人員實現自己的創意，打造出原型並進入生產階段。
Coral平台包含了Google在去年發表的Edge張量處理器（Tensor Processing Unit，TPU），這是個專為機器學習應用所打造的特殊應用積體電路（ASIC）；以及作為模組系統（SoM）的Coral開發板（Coral Dev Board），在此一開發板上安裝NXP iMX8M SoC、Edge TPU、Wi-Fi、藍牙、記憶體與eMMC。
另外還有個可透過MIPI連結開發板的500萬畫素相機，以及將Edge TPU嵌入既有系統的Coral USB Accelerator，該加速器能藉由USB 2.0或3.0介面整合至包括Raspberry Pi在內的各種Linux系統，隨後也會支援PCIe介面。
上述的Coral開發板售價為149.99美元，USB加速器為74.99美元，相機則是24.99美元。至於軟體工具則主要源自TensorFlow與TensorFlow Lite，其中的TensorFlow Lite模型必須先行量化再與Google的工具鏈編譯，才能直接於Edge TPU運作。且Google提供了十多種已訓練及編譯完畢的模型供開發人員參考。
Coral平台不但能協助開發人員快速打造原型，還標榜很容易就可擴大至生產線，因為Google也提供了模組系統及PCIe版本的加速器供大量採購。
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Coral平台包含了Google在去年發表的Edge張量處理器（Tensor Processing Unit，TPU），這是個專為機器學習應用所打造的特殊應用積體電路（ASIC）；以及作為模組系統（SoM）的Coral開發板（Coral Dev Board），在此一開發板上安裝NXP iMX8M SoC、Edge TPU、Wi-Fi、藍牙、記憶體與eMMC。
另外還有個可透過MIPI連結開發板的500萬畫素相機，以及將Edge TPU嵌入既有系統的Coral USB Accelerator，該加速器能藉由USB 2.0或3.0介面整合至包括Raspberry Pi在內的各種Linux系統，隨後也會支援PCIe介面。
上述的Coral開發板售價為149.99美元，USB加速器為74.99美元，相機則是24.99美元。至於軟體工具則主要源自TensorFlow與TensorFlow Lite，其中的TensorFlow Lite模型必須先行量化再與Google的工具鏈編譯，才能直接於Edge TPU運作。且Google提供了十多種已訓練及編譯完畢的模型供開發人員參考。
Coral平台不但能協助開發人員快速打造原型，還標榜很容易就可擴大至生產線，因為Google也提供了模組系統及PCIe版本的加速器供大量採購。
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Introducing Coral: Our platform for development with local AI
Wednesday, March 6, 2019
Posted by Billy Rutledge (Director) and Vikram Tank (Product Mgr), Coral Team
AI can be beneficial for everyone, especially when we all explore, learn, and build together. To that end, Google's been developing tools like TensorFlow and AutoML to ensure that everyone has access to build with AI. Today, we're expanding the ways that people can build out their ideas and products by introducing Coral into public beta.
Coral is a platform for building intelligent devices with local AI.
Coral offers a complete local AI toolkit that makes it easy to grow your ideas from prototype to production. It includes hardware components, software tools, and content that help you create, train and run neural networks (NNs) locally, on your device. Because we focus on accelerating NN's locally, our products offer speedy neural network performance and increased privacy — all in power-efficient packages. To help you bring your ideas to market, Coral components are designed for fast prototyping and easy scaling to production lines.
Our first hardware components feature the new Edge TPU, a small ASIC designed by Google that provides high-performance ML inferencing for low-power devices. For example, it can execute state-of-the-art mobile vision models such as MobileNet V2 at 100+ fps, in a power efficient manner.
For new product development, the Coral Dev Board is a fully integrated system designed as a system on module (SoM) attached to a carrier board. The SoM brings the powerful NXP iMX8M SoC together with our Edge TPU coprocessor (as well as Wi-Fi, Bluetooth, RAM, and eMMC memory). To make prototyping computer vision applications easier, we also offer a Camera that connects to the Dev Board over a MIPI interface.
To add the Edge TPU to an existing design, the Coral USB Accelerator allows for easy integration into any Linux system (including Raspberry Pi boards) over USB 2.0 and 3.0. PCIe versions are coming soon, and will snap into M.2 or mini-PCIe expansion slots.
When you're ready to scale to production we offer the SOM from the Dev Board and PCIe versions of the Accelerator for volume purchase. To further support your integrations, we'll be releasing the baseboard schematics for those who want to build custom carrier boards.
Our software tools are based around TensorFlow and TensorFlow Lite. TF Lite models must be quantized and then compiled with our toolchain to run directly on the Edge TPU. To help get you started, we're sharing over a dozen pre-trained, pre-compiled models that work with Coral boards out of the box, as well as software tools to let you re-train them.
For those building connected devices with Coral, our products can be used with Google Cloud IoT. Google Cloud IoT combines cloud services with an on-device software stack to allow for managed edge computing with machine learning capabilities.
Coral products are available today, along with product documentation, datasheets and sample code at g.co/coral. We hope you try our products during this public beta, and look forward to sharing more with you at our official launch.
AI can be beneficial for everyone, especially when we all explore, learn, and build together. To that end, Google's been developing tools like TensorFlow and AutoML to ensure that everyone has access to build with AI. Today, we're expanding the ways that people can build out their ideas and products by introducing Coral into public beta.
Coral is a platform for building intelligent devices with local AI.
Coral offers a complete local AI toolkit that makes it easy to grow your ideas from prototype to production. It includes hardware components, software tools, and content that help you create, train and run neural networks (NNs) locally, on your device. Because we focus on accelerating NN's locally, our products offer speedy neural network performance and increased privacy — all in power-efficient packages. To help you bring your ideas to market, Coral components are designed for fast prototyping and easy scaling to production lines.
Our first hardware components feature the new Edge TPU, a small ASIC designed by Google that provides high-performance ML inferencing for low-power devices. For example, it can execute state-of-the-art mobile vision models such as MobileNet V2 at 100+ fps, in a power efficient manner.
For new product development, the Coral Dev Board is a fully integrated system designed as a system on module (SoM) attached to a carrier board. The SoM brings the powerful NXP iMX8M SoC together with our Edge TPU coprocessor (as well as Wi-Fi, Bluetooth, RAM, and eMMC memory). To make prototyping computer vision applications easier, we also offer a Camera that connects to the Dev Board over a MIPI interface.
To add the Edge TPU to an existing design, the Coral USB Accelerator allows for easy integration into any Linux system (including Raspberry Pi boards) over USB 2.0 and 3.0. PCIe versions are coming soon, and will snap into M.2 or mini-PCIe expansion slots.
When you're ready to scale to production we offer the SOM from the Dev Board and PCIe versions of the Accelerator for volume purchase. To further support your integrations, we'll be releasing the baseboard schematics for those who want to build custom carrier boards.
Our software tools are based around TensorFlow and TensorFlow Lite. TF Lite models must be quantized and then compiled with our toolchain to run directly on the Edge TPU. To help get you started, we're sharing over a dozen pre-trained, pre-compiled models that work with Coral boards out of the box, as well as software tools to let you re-train them.
For those building connected devices with Coral, our products can be used with Google Cloud IoT. Google Cloud IoT combines cloud services with an on-device software stack to allow for managed edge computing with machine learning capabilities.
Coral products are available today, along with product documentation, datasheets and sample code at g.co/coral. We hope you try our products during this public beta, and look forward to sharing more with you at our official launch.
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