A neural network can smell like humans do for the first time

Digital smell is a modality that AI community has long ignored, but maybe one day useful for robot chef?

Here's how to do smell2text:

1. Collected 5,000 molecules and ask humans to label "creamy, chocolate, alcoholic, beefy, spicy, citrus", etc. This dataset is one of its kind and a huge contribution from the paper.

2. Train a graph neural network (GNN) to map the molecule to label. Each molecule is a graph of atoms described by valence, degree, hydrogen count, hybridization, formal charge, atomic number, etc.

3. The GNN predictions match well with expert humans on novel smells.

4. The embeddings give us a "Principal Odor map (POM)" that faithfully represents hierarchies and distances among odorants.

Science Paper.

Open access PDF.