Architectural Intelligence—Harnessing AI for Design Intent

Abstract

This thesis investigates and develops state-of-the-art technologies in the field of generative content and examines how designers can leverage inherent training biases and input data to swiftly generate textures and imagery for use within the design process.

Ultimately, the developed workflows aid in formulating a cohesive project vision from early stages. By combining proceduralization, simplified modeling techniques, and intelligent masking, the design process accelerates. This not only enables the creation of high-quality renders but more importantly, encourages a nuanced approach to design thinking.

Research Question

How Can the Real-time Masking and Layering of AI-generated Imagery Be Used to Effectively Realize and Refine Design Intent?

Author

Name: Luke Kratsios
LinkedIn: Link
Institution: Cornell AAP
Program: B.Arch

Advisors

Christopher Battaglia
Patrick Kastner
Donald Greenberg

Technical Consultants

John Wolford
Leul Tesfaye

Keywords

Architectural Intelligence, AI, Design Intent, Generative Content, Proceduralization, Intelligent Masking

Source

Link to the thesis.