Features & Benefits
- Performs high-speed ML inferencing
- Works with Debian Linux
- Supports tensorflow Lite
- Supports automl vision edge
- Ml Accelerator: Google edge TPU Coprocessor
- Connector: USB 3.0 Type-C (data/power)
Price Details
Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )
*All items will import from US
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The USB accessory performs high-speed ML inferencing and connects to any debian-based Linux system with an included USB 3.0 Type-C cable. It supports tensorflow Lite and automl vision edge
| Compatible Devices | Computers with Linux Debian 6.0 or above, Ubuntu 10.0 or above, Raspberry Pi with Raspbian, PC with USB 3.1 port, Single board computer with ARMv8 architecture |
| Connector Type | USB Type C |
| Number of Ports | 1 |
| Power Plug Type | No Plug |
| Brand | |
| Model Number | G950-06809-01 |
| UPC | 842776110077 |
| Global Trade Identification Number | 00842776110077 |
| Manufacturer | Google LLC |
| Built-In Media | USB Cable |
| Mfr Part Number | G950-01456-01 |
| Item Dimensions | 5.51 x 2.36 x 4.72 inches (14 x 6 x 12 cm) |
| Package Quantity | 1 |
| Unit Count | 1 Count |
| Number of Items | 1 |
| Color | Coral |
| Compatible Devices | Computers with Linux Debian 6.0 or above, Ubuntu 10.0 or above, Raspberry Pi with Raspbian, PC with USB 3.1 port, Single board computer with ARMv8 architecture See more |
| Item dimensions L x W x H | 5.51 x 2.36 x 4.72 inches (14 x 6 x 12 cm) |
| Package Weight | 1 Pound |
USB Cable
Perfect for researchers who require accelerated processing for machine learning models and quick experimentation with ML workloads.
Ideal for developers building AI applications in IoT devices, leveraging powerful edge processing capabilities for real-time analytics.
Great for hobbyists and makers experimenting with machine learning projects, providing accessible and affordable ML inference capabilities.
Not suitable for casual users without technical knowledge or experience in machine learning and hardware configuration.
Introducing the Coral USB Accelerator – the ultimate USB AI Accelerator designed specifically for Raspberry Pi and powered by Google Edge TPU technology. Boost the processing power of your Raspberry Pi and take your AI projects to new heights with the Coral USB Accelerator. Whether you're a hobbyist, researcher, or developer, this cutting-edge accessory opens up a world of possibilities. The Coral USB Accelerator allows you to harness the full potential of Google Edge TPU, a specialized chip designed for AI inference.
With the power of TPU at your fingertips, you can accelerate machine learning algorithms and execute complex AI tasks with lightning speed. Designed with convenience in mind, the Coral USB Accelerator simply plugs into your Raspberry Pi's USB port, making it effortless to integrate into your existing setup. No complicated configurations or wiring required – simply connect and start unleashing the power of AI. With this powerful USB AI Accelerator by your side, you can now tackle advanced AI projects with ease. From image classification and object detection to speech recognition and natural language processing, the possibilities are endless.
Take your projects to the next level and turn your ideas into reality. But the Coral USB Accelerator is not just for AI enthusiasts. It's also a valuable tool for businesses and entrepreneurs. Enhance the capabilities of your e-commerce platforms, online stores, and digital marketing efforts with the help of AI.
Improve customer experiences, optimize operations, and gain valuable insights to stay ahead in the competitive online landscape. Experience the future of AI with the Coral USB Accelerator for Raspberry Pi. Unlock the true potential of your projects and revolutionize the way you work with artificial intelligence. Don't miss out on this game-changing accessory – get your Coral USB Accelerator today and take your AI endeavors to new heights.
The Coral USB Accelerator is a game-changer for anyone using Frigate and Home Assistant for object detection. It significantly speeds up processing time, reduces CPU usage, and improves overall performance. It is compact, easy to set up, and energy efficient. However, some customers have experienced overpricing and delays in delivery.
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