# A timestep's prediction depends on future data

Consider an LSTM model with 100 timesteps, each of which with input and target data. Let f(99) be the function mapping the input data of the 99th timestep and hidden state of the 98th timestep to the output data of the 99th timestep.

The mapping f(99) of another LSTM model will be different if the other LSTM model is fitted only to the data in the first 99 timesteps. It follows that future data -- that is, data from the 100th timestep -- was used to generate the 99th timestep's prediction in the first LSTM model.

What are the implications of this for forecasting methodology?