Google researchers created a dataset of nearly 5,000 molecules identified by perfumers and used about 66% of it to train their AI to associate molecules with related descriptors. Researchers tested the AI on the rest of the dataset, which was then able to predict molecules' smells based on their structures. Molecule descriptions ranged from "buttery" to "tropical" and "weedy".