  Interactive coding allows two parties to conduct a distributed computation
despite noise corrupting a certain fraction of their communication. Dani et
al.\@ (Inf.\@ and Comp., 2018) suggested a novel setting in which the amount of
noise is unbounded and can significantly exceed the length of the (noise-free)
computation. While no solution is possible in the worst case, under the
restriction of oblivious noise, Dani et al.\@ designed a coding scheme that
succeeds with a polynomially small failure probability.
  We revisit the question of conducting computations under this harsh type of
noise and devise a computationally-efficient coding scheme that guarantees the
success of the computation, except with an exponentially small probability.
This higher degree of correctness matches the case of coding schemes with a
bounded fraction of noise.
  Our simulation of an $N$-bit noise-free computation in the presence of $T$
corruptions, communicates an optimal number of $O(N+T)$ bits and succeeds with
probability $1-2^{-\Omega(N)}$. We design this coding scheme by introducing an
intermediary noise model, where an oblivious adversary can choose the locations
of corruptions in a worst-case manner, but the effect of each corruption is
random: the noise either flips the transmission with some probability or
otherwise erases it. This randomized abstraction turns out to be instrumental
in achieving an optimal coding scheme.
