  Task specific hyperparameter tuning in reservoir computing is an open issue,
and is of particular relevance for hardware implemented reservoirs. We
investigate the influence of directly including externally controllable task
specific timescales on the performance and hyperparameter sensitivity of
reservoir computing approaches. We show that the need for hyperparameter
optimisation can be reduced if timescales of the reservoir are tailored to the
specific task. Our results are mainly relevant for temporal tasks requiring
memory of past inputs, for example chaotic timeseries prediciton. We consider
various methods of including task specific timescales in the reservoir
computing approach and demonstrate the universality of our message by looking
at both time-multiplexed and spatially multiplexed reservoir computing.
