The automation of things is happening on a global, planetary scale. Old traditional building paradigms are losing their relevancy. Automation disrupts not only labor markets, but the configuration, design and occupation of entire territories. Using GAN's has become an increasing factor in the architecture platform. But to what end is it actually relevant yet? Here, the project makes use of GAN's Style Transfer algorithm to decontextualize the monotony of gentrification by using machine learning. A prominent Standard hotel in the meat-packing district of New York City received a raw, flesh facelift. Constructing a new dichotomy within amended community, this superimposition exposes the existing patterns of contemporary urban transformations and atomization of the old. Articulating these new dynamics to find potentials for altered, urban experience.