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Currently, OpenAI has made significant progress in developing a model for Natural Language Processing (NLP) using the Generative Pretrained Transformer (GPT), enabling human-computer interaction to generate large data sets for a wide range of global applications. Technology and social changes influence city planning, and each new technology shapes cities for both economic and physical advancement. Ironically, artificial intelligence is transforming city data into multi-dimensional innovations that will shape future cities. OpenAI, as a model for processing data with intelligence architecture, has presented numerous opportunities for innovations in city planning. The research in OpenAI and pattern language particularly looks into the application of NLP for a large spectrum of cities. ChatGPT is one such product of OpenAI, which allows seamless NPL processing for human-centered problem solving. ChatGPT finds extensive use in city planning across various sectors such as environment, transportation, land use, redevelopment, policy, governance, among others. The introduction of CitiesGPT marks a significant advancement in the application of Natural Language Processing (NPL) in city planning. Despite its infancy, ongoing research and innovations have the potential to significantly shape our cities. The research paper explores how OpenAI can be a useful tool for city planning, with particular focus on OpenAI tools and pattern language theory. Then, it looks into the application of OpenAI on a real life project of redevelopment in Delhi, India. The various methods in the redevelopment of a university campus are developed to show the application of OpenAI. Particularly, the research aims at integrating OpenAl in the process of identifying patterns based on Christopher Alexander's idea of patterns. Additionally, it utilizes artificial intelligence to address intricate challenges related to campus redevelopment, aid decision-making, optimize design solutions, and promote sustainable design. The application of OpenAI and pattern language has the potential to introduce new innovations in the near future for cities.

OpenAI's advancements in artificial intelligence have brought new possibilities to urban studies, particularly in the concept of "urban imagibility." Coined by urban planner Kevin Lynch in his seminal 1960 work The Image of the City, imagibility refers to the qualities that make a city memorable, navigable, and engaging. Lynch focused on the city’s legibility—the ease with which residents and visitors can form a coherent image of the urban landscape. OpenAI's tools, including advanced machine learning models and image generation systems, can significantly contribute to enhancing our understanding and analysis of urban imagibility. AI systems developed by OpenAI, such as ChatGPT, can assist in analyzing textual and visual data about cities, enabling urban planners to better understand public perception and interaction with urban spaces. For example, by analyzing social media data, interviews, or even historical archives, AI can identify patterns in how people describe and interact with city landmarks, districts, and streets. This data provides valuable insights into what elements of the urban environment contribute to its sense of place and identity. Additionally, image generation technologies, like OpenAI’s DALL-E model, can simulate various visualizations of cityscapes. Urban designers and architects could use these AI-generated images to explore hypothetical changes to the city’s layout, helping to anticipate which alterations might enhance a city’s imagibility. By creating virtual models of potential building projects or public spaces, planners can visualize the impact on a city’s aesthetic and functional coherence before making real-world changes. Through these applications, OpenAI enables a new level of engagement with urban imagibility. It allows designers, planners, and communities to better imagine the effects of their choices on cityscapes, fostering urban spaces that are not only more navigable but also more memorable and meaningful for those who live and move within them. As AI continues to evolve, its role in shaping the future of cities and enhancing urban imagibility will undoubtedly grow, contributing to cities that are both functional and inspiring.

The platform for capitalism-based locational intelligence model in smart cities includes a cyberphysical system for managing land data, public hearings, and land information exchange. Software-as-a-service (SaaS) is used in a mobile-based urban and rural land management approach to address land-related issues in cities with geo-intelligent architecture. This study serves as an example of a project in Gujarat state, India's Sabarkhantha district. In this initiative, a novel approach to resolving issues with mobile-based land management with local government and residents is put forth. By utilizing Global Positioning Systems (GPS) and Geographic Information Systems (GIS), smart phones can perform tasks that are attributed to smart and intelligent technology. In a geofencing environment, the system sends information to administrators and citizens via a "routing mechanism." In order to settle land conflicts, the system architecture integrates a democratic administration hierarchy. Additionally, the mobile base concept offers a variety of smart city participatory techniques. Research examines topics, including how intelligent technologies might support urban planning. Platform capitalism: what is it? How might geo-AI be used to create new forms of platform capitalism? Thus, the study presents a novel strategy for using smart and intelligent technology to address urban issues.

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