Sense of Smell Predicted by Artificial Intelligence

Our sense of smell is often overlooked when we consider the tidal wave of artificial intelligence applications. Find out how a new machine-learning model can predict how a new chemical compound will smell without involving humans.

We’ve been deluged with news about artificial intelligence (AI) over the past year. We’ve heard how machines are learning to write and speak almost as well as we can.

Computers are even driving cars and composing paintings and music. They can often see and hear better than people when they perform tasks for us.

One area we haven’t been hearing so much about is how machine learning can mimic our sense of smell. It’s been hard to predict how new chemical products will smell, for example.

‘Chemoinformatics’ of Odours

There’s even a field of study called “chemoinformatics” The chemoinformatics of odours involves using computers to analyze, model and understand how chemical properties stimulate our sense of smell.

In the past, perfumers and chemists simply relied on empirical evidence to associate smells and chemicals. They knew chemical structures influenced odours, but usually, they’d just take a whiff and write down their impressions.

More recently, researchers have worked out how to calculate the Quantitative-Structure-Odour Relationship (QSOR). This establishes mathematical correlations between molecules and their smells.

Dr. Emily Mayhew Studies Food Sensory Properties

Dr. Emily Mayhew is a food scientist at Michigan State University. For the past six years, she’s been working to understand how the chemistry of a food dictates its sensory properties, like taste and smell.

Professor Mayhew is a co-leader of study that the journal Science published this week. The study describes a machine-learning model that can predict how a new chemical will smell without having anyone smell it.

The model is called the Principal Odor Map, and it’s predicted smells for…