Why are RNNs powerful for NLP problems? Select an answer:
A) The output from one layer will be carried into the input into the next layer so the model can form a sense of "memory."
B) The input of the function will be reviewed multiple times, and thus the quality will be improved.
C) The output of the function will be reviewed multiple times for accuracy, and thus the quality will be improved.
D) The input from one function will be the output of several other functions, which can then be examined independently.