The rapid development of artificial intelligence, particularly in the area of large language models (LLMs), has opened new avenues of research and analysis in various disciplines (Zhao et al., 2023). Large language models, such as the (i) generative GPT-3(4) and ChatGPT, and as the (ii) denoising ones like BERT, RoBERTa, T5 and their successors, have revolutionized the field of natural language processing (NLP) either by (i) generating human-like text based on given prompts or by (ii) understanding semantics of textual context on levels never seen before. These models can understand and generate text in multiple languages, making them powerful tools for text mining and information extraction tasks (Althammer et al., 2021). 

The groundbreaking performance of these LLMs can impact a wide range of domains, including, but not limited to, economics, law, education, and creative writing. However, the full potential of these models for the Geography of Innovation remains untapped, for the denoising models to a lesser extent (Krestel et al., 2021) in comparison to the generative ones (Lee and Hsiang, 2020). This Special Session aims to explore the ways LLMs can be employed to enhance our understanding of the spatial dynamics of innovation, support policymaking, and facilitate the development of novel, data-driven insights. 

By leveraging the capabilities of LLMs, researchers can process and analyze vast amounts of textual data related to innovation, either from traditional sources such as patents, scientific publications, and industry reports; or from novel ones as news, websites and social media. This could lead to the identification of patterns, trends, and linkages that were previously undetected, thus opening new perspectives on the Geography of Innovation. Furthermore, the application of LLMs in this field can help in the development of more informed, targeted, and effective innovation policies by providing data-driven insights and recommendations. At the same time, it may be fair to say the potential ubiquity of LLM-usage in research and consulting may have ethical implications that must be discussed promptly.