  The origin of life can be understood mathematically to be the origin of
information that can replicate. The likelihood that entropy spontaneously
becomes information can be calculated from first principles, and depends
exponentially on the amount of information that is necessary for replication.
We do not know what the minimum amount of information for self-replication is
because it must depend on the local chemistry, but we can study how this
likelihood behaves in different known chemistries, and we can study ways in
which this likelihood can be enhanced. Here we present evidence from numerical
simulations (using the digital life chemistry "Avida") that using a biased
probability distribution for the creation of monomers (the "biased typewriter")
can exponentially increase the likelihood of spontaneous emergence of
information from entropy. We show that this likelihood may depend on the length
of the sequence that the information is embedded in, but in a non-trivial
manner: there may be an optimum sequence length that maximizes the likelihood.
We conclude that the likelihood of spontaneous emergence of self-replication is
much more malleable than previously thought, and that the biased probability
distributions of monomers that are the norm in biochemistry may significantly
enhance these likelihoods
