Kendryte K210 is a RISC-V processor with AI accelerator found in boards such as Maixduino, Grove AI HAT, or HuskyLens among others, and enabling low-cost, low power AI applications such as face detection or object recognition.
You can now add Kendryte K210 AI accelerator to any board or computer with
M.2 socket or [Update: the M.2 connector pinout is non-standard] a USB-C port thanks to Sipeed M1n M.2 module that also comes with an M.2 to USB-C adapter. Sipeed M1n specifications:
- SoC – Kendryte K210 dual-core 64-bit RISC-V processor @ up to 400MHz with FPU, Neural-network Processing Unit (NPU), audio processor, built-in 6MB SRAM memory for CPU, and 2MB AI SRAM
- Storage – 128Mbit SPI flash
- Camera – 24-pin connector for DVP camera (OV0328 camera module provided as part of the kit)
- Host Interface – M.2 socket with some IOs and JTAG interface, accessible via Maix Nano M.2 to USB-C adapter.
- Supply voltage – 5.0V±0.2V with at least 300mA
- Temperature Range – -30°C – 85 °C
Just like other K210 hardware platforms, it supports image recognition at QVGA resolution up to 60FPS, and VGA resolution up to 30FPS. The company also mentions it supports microphone arrays of up to 8 microphones, but I’m not sure how you would connect those microphones. MAIX Nano M.2 to USB-C adapter comes with 2.54mm pitch through-hole pins exposing LCD signals and 16 GPIO pins, as well as an 8-pin female header. The board support Tensorflow/Keras/Darknet deep learning framework, and can be programmed using MicroPython or Arduino as we explained in our Sipeed M1 getting started guide.
Sipeed M1n M.2 card ships with a camera and MAIX Nano adapter as pictured above. You’ll find it for pre-order for $9.90 on Seeed Studio with shipping scheduled for March 9th, 2020. Alternatively, you’ll also find the M.2 card on Aliexpress for $10.33 (card only) or $14.09 with the camera and MAIX Nano. This may end up cheaper as shipping is included.
The datasheets for the M.2 card and adapter board, as well as documentation for MaixPy IDE for Python programming, can be found in the Documentation tab of the aforelinked page on Seeed Studio.