Papers by Ingrid Mayrhofer-Hufnagl
This Is Not a Building: Architecting the Spectrality of the Latent Space
Architectural design, May 1, 2024
The advent of artificial intelligence, specifically neural networks, has marked a significant tur... more The advent of artificial intelligence, specifically neural networks, has marked a significant turning point in the field of computation. During such transformative times, we are often faced with a dearth of appropriate vocabulary, which forces us to rely on existing terms, regardless of their inadequacy. This paper argues that the term "interpolation," typically used in deep learning (DL), is a prime example of this phenomenon. It is not uncommon for beginners to misunderstand its meaning, as DL pioneer Francois Chollet (2017) has noted. This misreading is especially true in the discipline of architecture, and this study aims to demonstrate how the meaning of "interpolation" has evolved in the second digital turn. We begin by illustrating, using 2D data, the difference between linear interpolation in the context of topological figures and its use in DL algorithms. We then demonstrate how 3DGANs can be employed to interpolate across different topologies in complex 3D space, highlighting the distinction between linear and manifold interpolation. In both 2D and 3D examples, our results indicate that the process does not involve continuous morphing but instead resembles the piecing together of a jigsaw puzzle to form many parts of a larger ambient space. Our study reveals how previous architectural research on DL has employed the term "interpolation" without clarifying the crucial differences from its use in the first digital turn. We demonstrate the new possibilities that manifold interpolation offers for architecture, which extend well beyond parametric variations of the same topology.
Design across multi-scale datasets by developing a novel approach to 3DGANs
International Journal of Architectural Computing
The development of Generative Adversarial Networks (GANs) has accelerated the research of Artific... more The development of Generative Adversarial Networks (GANs) has accelerated the research of Artificial Intelligence (AI) in architecture as a generative tool. However, since their initial invention, many versions have been developed that only focus on 2D image datasets for training and images as output. The current state of 3DGAN research has yielded promising results. However, these contributions focus primarily on building mass, extrusion of 2D plans, or the overall shape of objects. In comparison, our newly developed 3DGAN approach, using fully spatial building datasets, demonstrates that unprecedented interconnections across different scales are possible resulting in unconventional spatial configurations. Unlike a traditional design process, based on analyzing only a few precedents (typology) according to the task, by collaborating with the machine we can draw on a significantly wider variety of buildings across multiple typologies. In addition, the dataset was extended beyond the...
Design across multi-scale datasets by developing a novel approach to 3DGANs
International Journal of Architectural Computing
The development of Generative Adversarial Networks (GANs) has accelerated the research of Artific... more The development of Generative Adversarial Networks (GANs) has accelerated the research of Artificial Intelligence (AI) in architecture as a generative tool. However, since their initial invention, many versions have been developed that only focus on 2D image datasets for training and images as output. The current state of 3DGAN research has yielded promising results. However, these contributions focus primarily on building mass, extrusion of 2D plans, or the overall shape of objects. In comparison, our newly developed 3DGAN approach, using fully spatial building datasets, demonstrates that unprecedented interconnections across different scales are possible resulting in unconventional spatial configurations. Unlike a traditional design process, based on analyzing only a few precedents (typology) according to the task, by collaborating with the machine we can draw on a significantly wider variety of buildings across multiple typologies. In addition, the dataset was extended beyond the...
Advancing justice in a city’s complex systems using designs enabled by space
International Journal of Architectural Computing
Understanding the importance of data is crucial for realizing the full potential of AI in archite... more Understanding the importance of data is crucial for realizing the full potential of AI in architectural design. Satellite images are extremely numerous, continuous, high resolution, and accessible, allowing nuanced experimentation through dataset curation. Combining deep learning with remote-sensing technologies, this study poses the following questions. Do newly available datasets uncover ideas about the city previously hidden because urban theory is predominantly Eurocentric? Do extensive and continuous datasets promise a more refined examination of datasets’ effects on outcomes? Generative adversarial networks can endlessly generate new designs based on a curated dataset, but architectural evaluation has been questionable. We employ quantitative and qualitative assessment metrics to investigate human collaboration with AI, producing results that contribute to understanding AI-based urban design models and the significance of dataset curation.
Paul Klee's Pedagogy and Computational Processing
Bauhaus Effects in Art, Architecture, and Design, 2022
Over the last 50 years, our world has turned digital at breakneck speed. There is a clear line of... more Over the last 50 years, our world has turned digital at breakneck speed. There is a clear line of influence regarding digital esthetics and computational art that starts from the Bauhaus and extends to the computer-generated approach to art taken in the 1960s, as well as more contemporary works of computational processing. The computational approach in art, in particular, can be traced back to Paul Klee’s Bildnerische Gestaltungslehre. This is scarcely surprising, as geometry, abstraction and chance are important themes in all art of the twentieth century, not just for the Bauhaus artist or in generative art, which is a form of artistic creation that uses a computer, in which the artwork or end product is not necessarily at the center but instead the process of creation and the ideas underlying it.
Content
Architekturen, 2022
Untimely Architecture
Architecture, Futurability and the Untimely, 2022
and the Benaki Museum in Athens. Prior to teaching Ingrid has been key designer and project archi... more and the Benaki Museum in Athens. Prior to teaching Ingrid has been key designer and project architect for several international awarded projects of big building scale and urban projects in architectural offices in Europe and China.
Bauhaus Effects in Art, Architecture and Design, Eds. Kathleen James-Chakraborty, Sabine T. Kriebel, 2022
Over the last 50 years, our world has turned digital at breakneck speed. There is a clear line of... more Over the last 50 years, our world has turned digital at breakneck speed. There is a clear line of influence regarding digital esthetics and computational art that starts from the Bauhaus and extends to the computer-generated approach to art taken in the 1960s, as well as more contemporary works of computational processing. The computational approach in art, in particular, can be traced back to Paul Klee’s Bildnerische Gestaltungslehre. This is scarcely surprising, as geometry, abstraction and chance are important themes in all art of the twentieth century, not just for the Bauhaus artist or in generative art, which is a form of artistic creation that uses a computer, in which the artwork or end product is not necessarily at the center but instead the process of creation and the ideas underlying it.
Books by Ingrid Mayrhofer-Hufnagl
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Papers by Ingrid Mayrhofer-Hufnagl
Books by Ingrid Mayrhofer-Hufnagl