This project sought to find a way to integrate architecture and AI into a solution to NYC's scaffolding problem. The project took input of a typical scaffolding into a neural network that synthesized the images into a database and generated a 'typical' scaffolding image. From there, we took the image and used a text to image software to design 'solutions' to utilize these spaces and revitalize them for the general public.
This was a group project with - Cass Seto and Haseena Doost
Our main goal with this project was to link Architecture and AI in new and inventive ways to improve society.
From the ChatGPT response and broader research we defined our research questions and our three aims of the project: to improve safety, aesthetics and functionality
From this, we then gathered a data bank of images of preexisting scaffolding to use to train a neural network on and AI platform called Runway. This data bank allowed us to generate AI images of scaffolding based on the input and use it towards generating our ideas.
From the AI generated idea of a scaffolding structure we then used a text to image program in Runway to integrate our three key ideas and generate imagery of these.
And heres a visualization of that process ...
And a visual map of the process taking place from start to finish...
In the end, the goal was to create new ideas on how to beautify these otherwise dark and gloomy areas in NYC and use AI and related softwares in conjunction with architecture to work together and reimagine a landscape.
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