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Raspberry Pi AI Kit (damaged box during shipping)

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New product

The Raspberry Pi AI Kit bundles an M.2-format Hailo 8L AI accelerator with the Raspberry Pi M.2 HAT+ to offer customers access to excellent inferencing performance on the Raspberry Pi 5.

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1 Item

Warning: Last items in stock!

376,40 lei
tax incl.

Valid in the limit of the available stock

The price includes the costs for collection, treatment and ellimination of WEEE

-10,00 lei

386,40 lei tax incl.

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The Raspberry Pi AI Kit bundles the Raspberry Pi M.2 HAT+ with a Hailo AI acceleration module for use with Raspberry Pi 5. It provides an accessible, cost-effective, and power-efficient way to integrate high-performance AI. Explore applications including process control, security, home automation, and robotics.

Contains:
• a Hailo AI module containing a Neural Processing Unit (NPU)
• a Raspberry Pi M.2 HAT+, to connect the AI module to your Raspberry Pi 5
• a thermal pad pre-fitted between the module and the M.2 HAT+
• a mounting hardware kit
• a 16mm stacking GPIO header


The AI module is a 13 tera-operations per second (TOPS) neural network inference accelerator built around the Hailo-8L chip. The module uses the M.2 2242 form factor, and comes pre-installed in the M.2 HAT+, to which it connects through an M key edge connector. The M.2 HAT+ communicates between the AI module’s M.2 interface and the Raspberry Pi 5’s PCIe 2.0 interface. When the host Raspberry Pi 5 is running an up-to-date Raspberry Pi OS image, it automatically detects the Hailo module and makes the NPU available for AI computing tasks. The built-in rpicam-apps camera applications in Raspberry Pi OS natively support the AI module, automatically using the NPU to run compatible post-processing tasks.

GET STARTED BY CLICKING ON THIS LINK.

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Raspberry Pi AI Kit (damaged box during shipping)

Raspberry Pi AI Kit (damaged box during shipping)

The Raspberry Pi AI Kit bundles an M.2-format Hailo 8L AI accelerator with the Raspberry Pi M.2 HAT+ to offer customers access to excellent inferencing performance on the Raspberry Pi 5.