A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make more accurate predictions based on data linked to locations. Researchers from the University of Glasgow and Florida State University have found a way to overcome a key limitation of TabPFN, one of a class of AI tools known as foundation models.
Geospatial upgrade gives TabPFN sharper local predictions on datasets up to 70,000 rows
