Within the current global context of rapid change, integrated with the potentials of digital technologies, IAAC’s Master in AI for Architecture and the built environement (MaAI01) is committed to the generation of new ideas and pioneer novel AI-driven solutions applications for the fields of Urban Tech, Smart Construction and Natural Ecosystems. The three transversal objectives of the program are Regenerative Design, Carbon Neutrality and Co-Design Processes.
In this context IAAC and the MaAI works with a multidisciplinary approach, integrating computational design, rapid prototyping, machine learning, data science, and generative AI implementing sustainable practices at an unprecedented scale. Facing the challenges posed by our environment and the future development of cities, architecture and buildings, through a virtuous combination of technology, biology, computational design, digital and robotic fabrication, pushing innovation beyond the boundaries of a more traditional architectural approach.

Agrowealth : Does agriculture correlate to economy?

The goal of this project is to compare between the economic stability of an agriculture first city. Hamburg’s agricultural wealth is largely connected to its surrounding regions—particularly Schleswig-Holstein and Lower Saxony, which are among Germany’s leading food producers. Consequently, we focused on peripheral areas of the city that have recently transitioned into agricultural land, allowing … Read more

GG WORLDS [v.01]

GenAI for Game Environment Creation OverviewUrban environments in games play a crucial role in crafting immersive, dynamic worlds that captivate players and enhance storytelling. These settings not only shape the game’s atmosphere but also introduce strategic challenges and reflect cultural, social, and architectural identities, making virtual spaces feel authentic. However, creating high-quality, realistic game environments … Read more

AI FOR ROBOTIC FABRICATION: Smarter Motion by Bridging Simulation and Reality in Robotic Clay 3D Printing

https://github.com/PaintDumpster/ai_for_robotic_fabrication.git In the field of robotic fabrication, precision is everything! Yet there’s often a significant gap between a simulated toolpath and the real-world movement of a robotic arm. Subtle discrepancies can lead to printing errors, structural issues, or failed prototypes. We explored how AI can be used to minimize this gap. This investigation sits at … Read more