Tools and methods for Edge-AI-systems

The enormous potential of artificial intelligence, especially artificial neural networks, when used for edge computing applications in cars, traffic lights or smart watches, has not yet been fully exploited today. The reasons for this are the computing, energy and memory requirements of modern neural networks, which typically cannot be met by embedded devices. This article provides a detailed summary of today's challenges and gives a deeper insight into existing solutions that enable neural network performance with modern HW/SW co-design techniques.