Humans are not alone in this limitation. We have invented machines that can “see” and “hear”: Audio was first recorded and played back in 1877, and the first moving image followed a year later. A musical note is defined by its pitch, a single number, and computers represent a color with three numbers—the red, green, and blue (RGB) values that correspond to the types of color-receiving cells in our eyes. A song is a sequence of sounds, and an image, a map of pixels. But there has never been a machine that can flawlessly detect, store, and reproduce odors.
Scientists are working to change that. At the end of August, researchers published a paper presenting a model that can describe a molecule’s scent as well as, or even better than, a person (at least in limited trials). The computer program does so by placing molecules on a sort of odor map
“The paper implicitly advances the argument that you don’t need to understand the brain in order to understand smell perception,” Datta said. The research reflects a new, AI-inflected scientific understanding that seems to be popping up everywhere—using chatbots to study the human brain’s language network, or using deep-learning algorithms to fold proteins. It is an understanding rooted not in observation of the world so much as that of data: prediction without intuition.
I mentioned the mysteries of scent recently which is something I have long been interested in. Who would have guessed that AI is telling us a great deal about it. This article opens some fascinating avenues of research as science tries to teach a computer to smell.
The practical uses of a computer that can detect them is equally large.