John Hopfield and Geoffrey Hinton, laureates of the 2024 Nobel Prize in Physics, were recognized for their pioneering work in machine learning using artificial neural networks. The surprising decision (it’s uncommon for the Nobel Prize in Physics to be awarded for achievements in the field of information technology) clearly illustrates our relationship to the development of AI in general: we don’t know how to classify it, we don’t know what to think about it, but we can’t ignore it.

House for Julie, the first children’s hospice in the Czech Republic, is located on the grounds of the Kociánka Retirement Home in Brno. The hospice provides palliative and respite care, rehabilitation, psychotherapy, and comprehensive family care. It’s a refuge, a place where one can experience the most difficult moments but also find peace, relief, mutual support or solitude. It’s a place for everyday life and joyful gatherings, too. Despite its size, the building appears quite inconspicuous, set carefully into the existing naturally formed amphitheatre of the park and organized around a central courtyard with mature trees and a small pond. All common spaces, as well as private children’s rooms, are oriented towards this central green space. A walkway on the roof leads to a hilltop meditation spot, easily accessible at any time, from the parents’ rooms on the second floor.

Antoni Gaudí’s Casa Batlló, one of the most famous buildings in architectural history books, became the first UNESCO World Heritage Site to be transformed into a dynamic NFT using contemporary digital tools and AI. The piece was then sold at auction as a work of art. The digitized building changes in real time based on Barcelona’s weather data and the scenes depicted on the building’s façade. The result is a rare synthesis of historical architectural canon with cutting edge technology, blurring the boundary between the past and the present.

Like COVID-19, social media, or the fall of the Berlin Wall, AI has rapidly and unexpectedly become a part of our lives. As with any major event that reshapes society, for better or worse, it's essential that we understand its fundamentals—its ABCs. 

For architects, the construction of a dataset for use in AI, whether imported from somewhere else or newly created, is fundamentally an epistemological canon of references, likes and preoccupations often predictated on the selection of so-called masterpieces of Western art. The canon represents ideals of beauty and knowledge, but it also reflects a bias in favor of art created by those who have occupied the most socially, politically, and economically powerful positions in culture. The article leads us through a succinct series of eras and architectural styles to demonstrate this fact and their lack of diversity.

In this interview, architecture historian and critic Mario Carpo takes us on a tour around the inner workings of generative AI. With great storytelling, he illustrates his answers with dogs and dragonflies, robots and craftsmen, and rules and precedents.

Artificial intelligence already has a deeper presence in our lives than we are prepared to admit—integrated into the apps we use every day, increasingly shaping design practices. AI’s rapid development in recent years has already impacted automation and work optimization. What kind of effect can we expect in architecture studios? Will AI replace architects, or does its true strength lie elsewhere?

Ludwig Wittgenstein’s aphoristic words, “The limits of my language mean the limits of my world,” resonate in a different frequency in the era of natural language text-to-image applications powered by artificial intelligence algorithms. Apps such as Midjourney, Stable Diffusion, and DALL-E have spread like wildfire throughout the architecture community, yielding thousands of astonishing images. This explosion of novel design tools has given rise to two notable outcomes. Firstly, it has produced an abundance of extraordinary images. Secondly, it provokes theoretical inquiries within the architecture discipline, suggesting the dawn of a posthuman design ecology. The confluence of these factors has precipitated a seismic shift within the architectural landscape, fundamentally altering the relationship between the human and the machine in the act of creation.

Generative AI is rapidly revolutionizing architectural design, enabling novel explorations by significantly expanding the design search space beyond conventional human cognitive limits. Generative AI models, as well as large language models (LLMs), are pivotal in driving this transformation. These systems not only enhance creative agency but also challenge established design paradigms, continually redefining the conceptual boundaries of architectural design. AI-driven design processes are reshaping architectural exploration, enabling a collaborative dynamic between human designers and machine intelligence. In this context, instead of viewing design as a fixed, finite condition, it can be understood as a latent condition—a continuously expanding space of possibilities.

Oana Taut, a Romanian architect and co-founder of infrared.city, a startup specializing in AI-modeled environmental simulations, shares her insights with ERA21. She spoke about AI’s ability to make a designer’s job easier. We discussed planning and construction processes that could be automated, touched on different ways new technology could be applied to current practices, and explained the importance of accepting AI simply as a clever assistant, instead of getting carried away, fascinated with its new possibilities.

The many popular tools known today, which use artificial intelligence for generating images in a matter of seconds, can represent a valuable extension of one’s imagination. The results have the potential to be very innovative, which in turn forces us to keep refining our descriptions. The generated images—hallucinations—are then repeatedly subject to criticism, interpretation, and spatial materialization, creating an imaginative dialogue with AI, a legitimate process of re-evaluating the usual design processes.

Big tech is playing its part in reaching net zero targets, but its vast new data centres are run at huge cost to the environment. It’s time we focus on the sector’s environmental footprint—otherwise our goal of limiting fossil fuel dependence could compromise other climate goals.

Jorge Luis Borges once wrote that to live in a time of great peril and promise is to experience both tragedy and comedy, with “the imminence of a revelation” in understanding ourselves and the world. Today our supposedly revolutionary advancements in artificial intelligence are indeed cause for both concern and optimism. Optimism because intelligence is the means by which we solve problems. Concern because we fear that the most popular and fashionable strain of AI—machine learning—will degrade our science and debase our ethics by incorporating into our technology a fundamentally flawed conception of language and knowledge.

We could say, with a bit of poetic license, that due to continuous scientific and technological advancements we have entered into a new era of creativity, where one word is enough for the computer to generate an image or a 3D model. And it won’t take long until this image will just as easily be 3D-printed, full-scale. My question is simple: are we slaves or are we creators?

The Garden Me Tender project reflects on several recent legal cases where environmental entities were granted personhood, and responds to the transience and fragility of residual sites, sometimes called “vague terrains,” “délaissé,” or classified as “others” in land use maps and law dictionaries. Fitting this profile, plot number 981 in Staré Brno has become a test site for growing and imagining unique flora, using collected datasets and generative AI, while also applying research on the wider issue of recognizing nature as a legal person.