  The goal of identifying the Standard Model of particle physics and its
extensions within string theory has been one of the principal driving forces in
string phenomenology. Recently, the incorporation of artificial intelligence in
string theory and certain theoretical advancements have brought to light
unexpected solutions to mathematical hurdles that have so far hindered progress
in this direction. In this review we focus on model building efforts in the
context of the $E_8\times E_8$ heterotic string compactified on smooth
Calabi-Yau threefolds and discuss several areas in which machine learning is
expected to make a difference.
