In the realm of Recurrent Neural Networks (RNNs), gates play a important role in determining what information from the previous time step should be retained or discarded. These gates serve as adaptive mechanisms that enable RNNs to selectively update their hidden states, allowing them to capture long-term dependencies in sequential data. In this answer, we