  It has been demonstrated that cellular automata had the highest computational
capacity at the edge of chaos, the parameter at which their behavior
transitioned from ordered to chaotic. This same concept has been applied to
reservoir computers; a number of researchers have stated that the highest
computational capacity for a reservoir computer is at the edge of chaos,
although others have suggested that this rule is not universally true. Because
many reservoir computers do not show chaotic behavior but merely become
unstable, it is felt that a more accurate term for this instability transition
is the "edge of stability"Here I find two examples where the computational
capacity of a reservoir computer decreases as the edge of stability is
approached; in one case, because generalized synchronization breaks down, and
in the other case because the reservoir computer is a poor match to the problem
being solved. The edge of stability as an optimal operating point for a
reservoir computer is not in general true, although it may be true in some
cases.
