Aeon: “In recent years, however, things have changed dramatically, and understanding what one might call ‘the geometry of smell’ is a field that now enlists task forces of neuroscientists working together with mathematically trained theorists and artificial intelligence (AI) experts. While we’re notoriously bad at intuiting how our minds organise phenomena like colours and smells, machines offer a potential route for outsourcing introspection, and doing it with rigour. They can be trained to mimic human performance on perceptual tasks, and they make available the internal representations they use to do this – the abstract spaces and coordinate frames in which the ineffable stuff of thought lives. The recent publication of an unprecedentedly comprehensive and accurate ‘odour map’ in the journal Science is a declaration of this new paradigm for smell. In the same way that a map of the United States tells you that Buffalo is a bit closer to Detroit than to Boston, the odour map can tell you that the smell of lily is closer to grape than it is to cabbage. That much may seem obvious, but the real magic comes from the fact that any arbitrary chemical’s precise location on the odour map can be calculated. From having only a few facts on hand about a chemical, we can compute that it smells, say, 13 per cent closer to lily than to grape. By analogy, it would be something like having a formula that takes in information about an unknown city’s population size and soil composition, and spits out, correctly, the exact longitude and latitude of Philadelphia…”