It is easy to introduce different measure which will make deep learning fail and which will improve the state of the art and humanness significantly. They are: 1) Learning from small amount of examples, make training database very small with 3-4 pictures by class. 2) Learning across classes. Train on evening pictures and learn to recognize daylight. Train on direct sunlight and learn to recognize on side light. 3) Learning of entities. Train on entity in white and learn to recognize a combined picture. Deep learning community intentionally do not consider these tasks, they prefer to increase the training data size to the limit only huge corporation could afford doing a research.