HatDrive! AI Coral Edge TPU Bundle (NVMe 2230,2242 GEN 2) for Raspberry Pi 5

HatDrive! AI Coral Edge TPU Bundle from Pineboards uniquely combines support for an NVMe drive with the Google Coral Edge TPU, making it an indispensable tool for AI enthusiasts and professionals alike.

Key Features and Specifications:

• Designed Exclusively for Raspberry Pi 5: The HatDrive! AI is crafted to seamlessly integrate with the Raspberry Pi 5, providing a perfect fit and optimal performance.
  
• Includes Google Coral Edge TPU: Includes an M.2 E-Key Google Coral Edge TPU, enabling efficient AI computing capabilities right at your fingertips.
• NVMe Drive Compatibility: Supports one NVMe drive in sizes 2230 and 2242, offering fast and reliable storage options for demanding applications and projects.
• ASMedia PCIe Switch Integration: The board incorporates an ASMedia PCIe Switch (Gen2 variant), facilitating reliable and efficient data transfer between connected devices.
• Easy Installation: With a user-friendly design, the HatDrive! AI allows for quick and straightforward installation of both the NVMe drive and the Google Coral Edge TPU.
• High-Quality Construction: Built with premium materials and components, the HatDrive! AI ensures durability and long-term reliability for all your AI ventures.
• Versatile Application: Whether you're developing AI models, running machine learning algorithms, or simply need high-speed storage, the HatDrive! AI is your go-to solution.
• Comprehensive Accessory Kit: Comes equipped with all necessary mounting hardware and accessories, ensuring you have everything needed to get started without delay.

The HatDrive! AI represents a significant leap forward in making AI technology more accessible and integrated with the Raspberry Pi ecosystem. By combining the speed of NVMe storage with the power of the Google Coral Edge TPU, this board opens up new possibilities for AI research, development, and application.

Important Notice: Please be aware that booting from NVMe storage through a PCIe switch is currently not supported. Users planning to utilize NVMe storage should consider this limitation when designing their projects.