Architecture of RNNs
The main concept behind an RNN is to take advantage of previous information in a sequence. In a traditional neural network, it is assumed that all inputs and outputs are independent of one another. In some domains and use cases, this assumption is not correct, and we can take advantage of this interconnectedness.
I will use a personal example. I believe that in many cases, I can predict what my wife will say next based on a couple initial sentences. I tend to believe that I have a high accuracy rate with my predictive ability. That said, if you ask my wife, she may tell you a quite different story! A similar concept is being used by Google's email service, Gmail. If you are a user of the service, you will have noticed that, from 2019, it started making suggestions when it thinks it can complete a sentence. If it guesses right, all you do is hit the tab key and the sentence is completed. If it doesn't, you can continue typing and it might...