Spatial & Cultural Intelligence
Data–as well as how we access this data–plays a significant role in guiding decisions. It serves as an invisible layer that determines what we see, where we go, who we interact with, and how we live. The proliferation of Large Language Models have marked a paradigm shift in how we organize and utilize this data. These models know everything that exists on the internet, but know very little about the physical world in which we live. Gathering the data, synthesizing the data in a unified data architecture, and training new models of intelligence on this data will unlock a powerful ability to understand and transform our world. Moreover, it will create a wide range of new opportunities for creative endeavors, products, and businesses.
-
Cultural producers are particularly affected by this lack of intelligence. While artificial intelligence service providers offer these producers a range of tools, few have been able to give them a product or service that genuinely understands what goes into their work, how they operate in the world, and how to guide future action. They don’t help them design a new product or space, help match customers to products based on specific tastes, needs, and point on their journey, coordinate collaborators, plan a season, garner insights for their archive, analyze the market for future projects, help plan a tour and navigate logistics, or manage a complex project. Moreover, they don’t understand the business model and value of cultural production. This is a particularly dire situation as many cultural producers are faced with rapidly rising costs, growing organizational complexity, regulations that can be difficult to navigate, and customers that are also feeling economic pressure and may thus have less money to spend on these cultural products.
In this context, we should develop an intelligence that helps navigate and organize the complexity of the physical world and, in doing so, make it easier and less expensive to produce and maintain cultural initiatives across a range of industries. While this intelligence will ultimately benefit individual consumers of culture, the initial focus should be on enterprises and institutions that have the resources to invest in building such a model and who will benefit most directly from the efficiency it provides. We can begin by gathering the necessary data sets, designing the model architecture, and then embarking on the training process. At the same time, it should involve research in physical space to understand how human agents operate, how they meet goals associated with producing cultural objects, and how sensors and interfaces can capture this process and prompt future action guided by the spatial and cultural intelligence that we are developing. The end result will ideally be a cultural companion that can serve both individuals and enterprises.
Research
2025
2025
2025
Potential Clients & Collaborators
Given that this line of research sits at the intersection of AI, culture, design, and spatial intelligence, potential clients and collaborators include a wide spectrum of creative, institutional, and infrastructural organizations that rely on understanding the relationship between people, space, and culture. Some examples include:
Cultural Institutions (Nonprofit / Public) – Organizations that steward, interpret, and produce culture, often with complex spatial, archival, and logistical needs.
Design, Architecture, and Planning Firms (For-Profit / Hybrid) – Organizations that rely on deep spatial, cultural, and behavioral understanding to produce built environments and experiences.
Media, Entertainment, and Creative Technology Companies (For-Profit)– Enterprises that manage complex production ecosystems across physical and digital realms.
Heritage, Conservation, and Cultural Tourism Entities – Organizations maintaining or interpreting cultural and physical heritage.
Emerging AI and Spatial Computing Ventures– Startups and research groups developing new interfaces for human-environment interaction.
