Google is training graph neural networks to predict smells

A team of chemistry, life science, and AI researchers are using graph neural networks to identify molecules and predict smells. Models made by researchers outperform current state-of-the-art approaches and the top-performing model from the DREAM Olfaction Prediction Challenge, a competition for mapping the chemical properties of odors. The work was created by researchers from Google, Canadian Institute for Advanced Research, Vector Institute for Artificial Intelligence, University of Toronto, and Arizona State University. The researchers believe progress in machine learning application of molecule identification can help deliver machine intelligence that's able to predict smell similar to the way AI that can imitate other senses like vision and hearing has advanced in recent years. With grasping challenges, researchers are also trying to help robotic hands tackle the human sense of touch as well.