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  • Specifications: Arm 32-bit Cortex-M0+ Microprocessor (MCU): Up to 32 MHz max 16 KB Flash memory with ECC 2 KB RAM Connections: USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed).
  • Features: Google Edge TPU ML accelerator coprocessor, USB 3.0 Type-C socket, Supports Debian Linux on host CPU, Models are built using TensorFlow. Fully supports MobileNet and Inception architectures through custom architectures are possible. Compatible with Google Cloud..
Coral USB Accelerator brings powerful ML (machine learning) inferencing capabilities to existing Linux systems. Featuring the Edge TPU, a small ASIC designed and built by Google, the USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface. For example, it can execute state-of-the-art mobile vision models, such as MobileNet v2 at 100+ fps, in a power-efficient manner. This allows fast ML inferencing to embedded AI devices in a power-efficient and privacy-preserving way. Models are developed in TensorFlow Lite and then compiled to run on the USB Accelerator. Edge TPU key benefits: High speed TensorFlow Lite inferencing Low power Small footprint Features Google Edge TPU ML accelerator coprocessor USB 3.0 Type-C socket Supports Debian Linux on host CPU Models are built using TensorFlow. Fully supports MobileNet and Inception architectures though custom architectures are possible Compatible with Google Cloud Specifications Arm 32-bit Cortex-M0+ Microprocessor (MCU): Up to 32 MHz max 16 KB Flash memory with ECC 2 KB RAM Connections: USB 3.1 (gen 1) port and cable (SuperSpeed, 5Gb/s transfer speed) Included cable is USB Type-C to Type-A Coral, a division of Google, helps build intelligent ideas with a platform for local AI.

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USB Edge TPU ML Accelerator coprocessor for Raspberry Pi and Other Embedded Single Board Computers

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