I am going through the following blog on LSTM neural network: http://machinelearningmastery.com/understanding-stateful-lstm-recurrent-neural-networks-python-keras/
The author reshapes the input vector X as [samples, time steps, features] for different configuration of LSTMs.
The author writes
Indeed, the sequences of letters are time steps of one feature rather than one time step of separate features. We have given more context to the network, but not more sequence as it expected
What does this mean?