Summary of Unintuitive Properties of Neural Networks

Neural network are powerful learning models especially deep learning networks on visual and speech recognition problems. This may result from their capacity of expressing arbitrary computation. However, it is still hard to fully understand their properties, thus, how they made the final decision after a sequence of decisions in a dynamic environment. Since we have many layers engaged in such complicated decision making process, we don't really understand how they think. In spite of having made a lot of efforts (e.g., a researcher created a popular toolkit called Deep Visualization Toolbox) to capture step by step how a neural network get trained, what we can see inside these layers is still very intricate.