RNN or LSTM are known to hold the previous timestamp data as "memory" so that short or long range dependencies can be remembered.
But in the following simple keras model, where is that delay or memory thing? It is just taking each input at a time and throwing the output at same timestamp!
model = Sequential()
model.add(LSTM(10))
model.add(Dense(2))