Fig. 1. Analogy explaining the difference between the working of recurrent neural network (RNN) and transformer models. A: RNNs can be considered a chain of people passing down a message where each person adds and retains information from previous steps. B: Transformer models can be considered a group of experts discussing where each expert considers all parts of the input simultaneously. The attention mechanism then weighs the importance of different elements in the data and combines them.