An implicit shared belief of all of the practitioners the author mentions is that they attempt to construct models that correspond to some underlying "data generating process". Machine learning practitioners may use similar models or even the same models as Bayesian statisticians, but they tend to evaluate their models primarily or entirely based on their predictive performance,
not on intuitions about why the data is taking on the values that it is.
See Breiman's classic "Two Cultures" paper that this post's title is referencing: https://projecteuclid.org/journals/statistical-science/volum...