Imagine a future where AI helps cities make smarter decisions, optimizing everything from traffic flow to resource allocation. Researchers are exploring how AI can revolutionize urban planning, particularly in the complex world of freight transportation. One of the biggest challenges in urban planning is dealing with the constant influx of new data and simulations. Think about the mountains of information generated by traffic sensors, GPS devices, and logistics companies – it's overwhelming! This research dives into how AI, specifically large language models (LLMs) like ChatGPT, can be used to automatically build "knowledge representations." These representations act like a digital librarian for urban data, organizing and connecting information from research papers, technical manuals, and real-world datasets. The researchers tested their approach by creating an AI-powered system to optimize intermodal freight transport, which involves moving goods across different modes like trucks, trains, and ships. Their system uses LLMs to understand the relationships between different factors, such as delivery times, costs, traffic congestion, and emissions. By building a knowledge graph – a visual representation of how different concepts are connected – the AI can identify the most efficient and sustainable ways to move goods. This research offers a glimpse into the future of urban planning, where AI can help us make sense of complex data and create more livable, sustainable cities. While still in its early stages, this approach has the potential to transform how we manage urban systems and tackle the challenges of a rapidly urbanizing world.