Orange Pi AI Stick 2801 Neural Compute Stick SDK & Documentation Released

We covered the launch of Orange Pi AI Stick 2801 neural compute stick a few days ago, the first easily available Gyralcon Lightspeeur based USB stick, and noted that while the hardware was there, we had no details about software development kit and documentation at the time.

I’ve got some more information now. First, the company release an English presentation about the neural stick, and while it’s not technical documentation, it provides insights into what it is capable of, and an overview about the workflow.

More importantly, Shenzhen Xunlong Software also released Orange Pi AI Stick SDK and user manual for x86 PC, as well as cat/dog data and pre-trained models to get started.

However, if you want to perform training with your own data, you’ll need to purchase the stick plus PLAI model transformation and training tools sold on Aliexpress for $218 plus shipping, that’s $69 for the hardware, and $149 for the software tools. The company further explains that the tools support model decomposition of convolutional neural network (CNN) based on Caffe, and the training tool can train image, video, voice, and natural language into prototype to be loaded into the neural stick.

PLAI stands for People Learning Artificial Intelligence , and is an ecosystem of hardware and tools provided directly by Gyrfalcon, the ASIC vendor. Shenzhen Xunlong did not provide the full details about the tools, but the tools should be Plai Builder, a PyTorch based “full-stack” framework specially designed to quickly train and build neural network models for Lightspeeur and G.A.I.N series solutions from GTI (Gyrfalcon Technology Inc).

Last time, various people asked what such stick could do, and the generic answer is inference (e.g. object recognition) at the edge at low power, but the presentation also includes a list of potential applications:

• Moving edge calculation
• Intelligent monitoring
• Smart toys and robots
• Smart home
• Virtual reality and augmented reality
• Face detection and recognition
• Speech Recognition
• Natural language processing
• Embedded deep learning device
• Cloud Machine Learning and Deep Learning System
• Artificial intelligence data center server
• Advanced assisted driving and autonomous driving

So lots of fun applications. If you are specially interested in Tensorflow, you’ll have to wait a little longer, as I understand support for the framework is still being worked on.

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