Grove AI HAT Helps Raspberry Pi Run Edge Computing Workloads

#artificialintelligence

Last year we wrote about Kendryte K210 dual core RISC-V processor specifically designed for for machine vision and machine hearing as well as the corresponding Kendryte KD233 which enables inference at the edge, e.g. Latter on we found the processor in Sipeed M1 module which went for as low as $5 in a crowdfunding campaign, and was fitted to some low cost boards now selling for $12.90 on Seeed Studio. The latter company has now designed Grove AI HAT that aims to assist Raspberry Pi in running the edge computing workloads previously described, as exposes 6 Grove interfaces to extend functionality with some of the Grove add-on modules. The board can either be used in conjunction with a Raspberry Pi board, or in standalone via a USB-C cable. It supports the baremetal Kendryte Standalone SDK, as well as ArduinoCore K210 for the Arduino IDE working in Linux, Windows, and Mac OS meaning it's possible to leverage the Grove Arduino libraries and other Arduino libraries on this board.


Seeed Details RISC-V Raspberry Pi AI HAT, Development Board - AB Open

#artificialintelligence

Seeed Studio has announced a new Grove AI HAT for the Raspberry Pi, designed for edge computing projects, based around the Sipeed MAIX-I 64-bit RISC-V system-on-module (SOM) – and, interestingly, it will also function as a standalone development board. Unveiled on the official Seeed forum by Elaine Wu, the new design uses the full-size Hardware Attached on Top (HAT) form factor to connect to a Raspberry Pi single-board computer via its 40-pin GPIO header. Its primary feature: a Sipeed MAIX-1 system-on-module, available with or without Wi-Fi connectivity, which gives the Pi access to a 64-bit RISC-V implementation designed to accelerate deep learning workloads at the edge. The board's design also includes Grove-format connectors for digital IO, pulse-width modulated (PWM) IO, analogue IO, UART, and I²C, alongside camera connectivity. While the board is primarily designed to be used as a co-processor on top of an Arm-based Raspberry Pi, Wu has confirmed that it will also function as a standalone development board powered via a USB Type-C connector at the bottom left of the PCB.


Maixduino: A sub-US$25 Arduino Uno-sized single board computer that supports AI workloads

#artificialintelligence

Sipeed has designed the Maixduino for use in AI and IoT applications. The single board computer (SBC) has the form factor of an Arduino Uno and comes with a 2.4-inch TFT display along with an OV2640 2 MP camera module. The Maixduino has various ports and connectors including USB Type-C and can be pre-ordered for US$23.90 or US$20.90 without the camera and display. The SBC will ship worldwide on May 27.


HuskyLens – An AI Camera: Click, Learn, and Play!

#artificialintelligence

HuskyLens is an easy-to-use AI camera. It can learn to detect objects, faces, and colors just by clicking. The more it learns, the smarter it is. The adoption of the new generation AI chip allows HuskyLens to detect faces at 30 frames per second. HuskyLens can connect to Arduino, Raspberry Pi, LattePanda, or micro:bit, and make your very creative projects without playing with complex algorithms.


Low-Power Play: GAP8 Weds Multicore RISC-V with Machine Learning

#artificialintelligence

Machine learning (ML) on the edge often involves convolutional neural networks (CNNs). This can be done using standard processors, but there's a cost due to performance and matching power requirements. Though specialized ML hardware can significantly reduce the amount of power, a programmable solution would provide a more flexible alternative. GreenWaves Technologies brings a RISC-V-based solution to the table, building on the Parallel Ultra Low Power Platform (PULP). PULP is designed to support four different 32-bit, RISC-V cores, including RISCY, Zero-riscy, Micro-riscy, and Ariane.