Mapping the Complex Topography of Odours with AI
Recent advancements in neuroscience and artificial intelligence have led to the creation of an unprecedentedly comprehensive and accurate 'odour map', which provides a set of derived rules for calculating the placement of different odours. This map offers a new paradigm for understanding the geometry of smell, enlisting neuroscientists, theorists, and AI experts. The map not only catalogs relative locations and perceptual similarities of odours but also raises philosophical questions about how our noses perceive chemicals. Machine learning models are being used to train and develop dense code repositories to understand the complex nature of odour perception, leading to the creation of a graphical 'deep net' that mimics human judgments and provides insights into the space that chemicals occupy in our olfactory system.