This groundbreaking talk dives into the intriguing intersections between geospatial data science and the high-dimensional embeddings generated by large language models (LLMs) like ChatGPT. Just as geospatial experts map the physical world, data scientists use embeddings to chart abstract spaces, creating a unique opportunity for geospatial professionals to leverage their expertise in the emerging field of explainable AI. Through visually engaging examples, the talk will address questions such as: (1) How is embedding similar to surveying, and what does “distance” signify in abstract space? (2) How do dimensionality reduction techniques and clustering enable cartographic representations of conceptual spaces? (3) Can foundation models serve as a “GPS” for meaning and context? By drawing parallels between geospatial and AI methodologies, attendees will gain new perspectives on their potential role in this burgeoning, interdisciplinary domain.
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