Usedipaq.com offers Machine Learning Development Kits, Accessories and Software Support for Intel, NVIDIA, Google, Xilinx, etc Edge Devices as well as for legacy hp ipaq PDA devices.
ebay special - Google Coral Dev Board Developer Kit with AC
Coral Dev Board
ebay special sale includes the AC and usb C adapter along with the Dev Kit for the same price. Shipping included.
Coral Dev Board is a single-board computer with a removable system-on-module (SOM) that contains eMMC, SOC, wireless radios, and Google’s Edge TPU. It’s perfect for IoT devices and other embedded systems that demand fast on-device ML inferencing. The Dev Board can be used as a single-board computer for accelerated ML processing in a small form factor, or as an evaluation kit for the on-board SOM. Additional 40mm × 48mm SOMs can be combined with your custom PCB hardware using board-to-board connectors for integration into products.
The SOM is based on NXP's iMX8M system-on-chip (SOC), but its unique power comes from the Edge TPU coprocessor. The Edge TPU is a small ASIC designed by Google that provides high performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 100+ fps in a power efficient manner.
Edge TPU key benefits: - High speed TensorFlow Lite inferencing - Low power - Small footprint
NXP i.MX 8M SOC (Quad-core Cortex-A53, plus Cortex-M4F) Google Edge TPU ML Accelerator Coprocessor Cryptographic coprocessor
Wi-Fi 2x2 MIMO (802.11b/g/n/ac 2.4/5GHz) Bluetooth 4.1
8GB eMMC 1GB LPDDR4
USB Type-C power port (5V DC) USB 3.0 Type-C OTG port USB 3.0 Type-A host port USB 2.0 Micro-B serial console port
3.5mm audio jack (CTIA compliant) Digital PDM microphone (x2) 2.54mm 4-pin terminal for stereo speakers
HDMI 2.0a (full size) 39-pin FFC connector for MIPI-DSI display (4-lane) 24-pin FFC connector for MIPI-CSI2 camera (4-lane)
MicroSD card slot Gigabit Ethernet port 40-pin GPIO expansion header
Supports Debian Linux Models are built using TensorFlow Fully supports MobileNet and Inception architectures though custom architectures are possible Compatible with Google Cloud