Combination of IoT and AI computing technology, Ruff will launch the AI Face Tracking Module

The chip runs high-speed neural network calculations with ultra-low power consumption, targeting testing and image classification, face detection and recognition, multi-classification object detection and recognition. Ruff Face ID has machine vision and audio abilities, when it comes to practical business scenarios, it is able to operate data storage and use edge computing. It also has a convolution artificial neural network hardware accelerator which manages the calculations more efficiently. In the case of high real-time requirements, the demand from cloud to edge is magnified. Critical applications for face recognition and tracking, local data processing and edge computing will become a necessity. Ruff Face ID’s AI chip enables off-line processing for edge calculations and advanced machine learning models for deep neural networks, including video frames, speech synthesis, time series data, and cameras, microphones, and other data generated by sensors or equipment.