The article discusses how to choose the best algorithm for computer vision tasks like semantic segmentation. They found that evaluating algorithms based on specific tasks is crucial for selecting the most suitable one. By using high-level symbolic knowledge, the accuracy of algorithm selection can be improved by 10 to 15%, leading to better segmentation quality.