Fully connected neural networks and CNNs (convolutional neural networks) struggle with capturing relationships between spatially distant elements in inputs, such as determining the identity of objects far apart in a single image. Similarly, RNNs dealing with time-series data find it challenging to capture relationships between input elements that are temporally distant.