Dear community! Today we want to bring your attention to Smell. Smell has always been the exception.
Unlike vision or sound, it resisted structure.
Similar molecules could smell completely different, while different ones could converge into the same percept.
Recent research changes that from two directions.
Machine learning models begin to organize scent into perceptual spaces, where similarity becomes measurable.
At the same time, new biological findings show that smell is already spatially organized inside the body, from the nose to the brain.
For art, this raises a different question:
what happens when something as subjective as smell becomes structurally accessible?
Summary and visuals by
@freyahermanns
Sources:
Sanchez-Lengeling, Benjamin; Wei, Jennifer N.; Lee, Brian K.; Gerkin, Richard C.; Aspuru-Guzik, Alán; Wiltschko, Alexander B. (2019)
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
/abs/1910.10685
Sanchez-Lengeling, Benjamin; Wei, Jennifer N.; Lee, Brian K.; Gerkin, Richard C.; Aspuru-Guzik, Alán; Wiltschko, Alexander B. (2019)
Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules (ResearchGate version)
/publication/336767812
Keller, Andreas; Gerkin, Richard C.; Guan, Yuyang; Dhurandhar, Amit; Turu, Gur; Szalai, Bálint; Mainland, Joel D.; Ihara, Yoshihito; Yu, Crystal W.; Wolfinger, Russell; Vens, Celine; et al. (2017)
Predicting human olfactory perception from chemical features of odor molecules
/doi/10.1126/science.aal2014
Brann, Daniel H.; Tsukahara, Takashi; Weinreb, Caleb; Lipovsek, Marc; Van den Berge, Koen; Gong, Bo; Chance, Robert; Macosko, Evan Z.; Cepko, Constance L.; Datta, Sandeep Robert (2026)
A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain
/10.1016/j.cell.2026.03.051
Datta, Sandeep Robert et al. (2026)
First detailed map of smell receptors reveals spatial organization in the nose
/articles/d41586-026-00894-1