Recent advancements in machine learning (ML) in architectural design led to new developments in automated generation of floor plans. However, critical evaluation of ML-based generated floor plans has not progressed proportionally due to the subjectivity and complexity of the assessment, particularly for large and more complex floor plans. Accordingly, a hybrid (quantitative and qualitative) floor plan evaluation scheme is introduced in this study, focusing on multiple architectural aspects. To verify the effectiveness of the proposed framework, the evaluation scheme is applied on the generated floor plans resulting from two baseline computer vision models. The models have been trained on a newly introduced large-scale floor plan dataset called Modified Swiss Dwellings (MSD). The results showed that despite the progression of computer vision models for floor plan generation, they still have difficulty capturing the more complex architectural qualities. In addition, the prospect of floor plan generation and evaluation and possible future developments are discussed.@en

In recent years, “data” has become one of the most important aspects of architectural design. With the advent of new technologies, architects are now able to collect and analyse data about everything from building materials to weather patterns. This data can be used to create more efficient and sustainable buildings. In some cases, data can even be used to create entire new neighbourhoods or cityscapes.’ The sentences sound like a quote, one that could have come from an interview about the history of digital culture or the interconnections between architecture and technology. But as authentic as this statement sounds, it was never said. Anyone who thinks they hear the voice of an architect, computer scientist or historian is mistaken. Strictly speaking, the words do not come from a human being, but from the language software Generative Pre-Trained Transformer, GPT-3 for short. The program is the third generation of artificial intelligence, considered one of the most impressive products our digital culture has produced to date. On a timeline of disruptive technologies, it currently occupies the most current position. GPT-3 is a text generator that can write poems and dramas, provide answers to complex questions on topics such as love or trust, discuss the weather or international climate policy with us—and that has also written the short statement on the subject of ‘data and architectural design’ mentioned above. The New York Times calls the program ‘amazing, spooky, humbling and more than a little terrifying‘. [...]@en

In der Epoche der Kybernetik sahen sich die Architekten mit neuen operativen Möglichkeitsräumen in technischen Systemen konfrontiert: Gebäude wurden durch Schaltdiagramme errechnet, Kreativität und Phantasie wurde die technische Intelligenz von Denkmaschinen gegenübergestellt. Im Fadenkreuz der Kybernetik befand sich der Architekt selbst. Es ging es um nichts Geringeres als das Fortbestehen seiner Autorschaft in einer technologisch-wissenschaftlichen Welt. Heute erleben wir, wie die einst so schweren Rechenmaschinen an Gewicht verlieren, doch an Macht gewinnen, wie Computer die Umwelt bevölkern, sich eigene digitale Ökosysteme schaffen und Gesellschaftsformen und Existenzweisen entstehen, die sich ohne Big Data gar nicht mehr erzählen lassen. @en

In the philosophical travel report Brazilian Mind, Max Bense processes his impressions of Brazil in the 1960s. With linguistic precision and rich in spatial imagination, he describes his fascination with the just-completed capital of Brasilia, designed by the two architects Lúcio Costa and Oscar Niemeyer. Bense describes how he is attracted to concrete poetry there and how he immerses himself ever more deeply in Brazil's intellectual and artistic avant-garde. The result is a dense essay that is not only one of the remarkable pieces of German postwar literature, but also makes clear the intense interrelations between the Latin American and European avant-garde of the time. Brazilian Mind appears in a new edition, supplemented with an afterword as well as unpublished archival material from Max Bense's archive.@en