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| {{DISPLAYTITLE:Matiss - Architecture's Mirror Worlds}}
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| '''Architecture's Mirror Worlds'''
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| An image is not a building, and a building is not an image. Yet, the ongoing enmeshment of computational and material worlds suggests they may not exist too far apart either. The realm of corporate software platforms—whether digital twins of buildings, cities, landscapes, or even the entire planet—relies on increasingly accurate replicas of reality. More fidelity means more data, which, in turn, means better information. Increasingly, every object in the world, no matter the scale, type or form, is mirrored by an operational version of a digital twin—proteins, pacemakers, microchips, wind turbine blades, cars, rainforests, and buildings and cities can this way participate in management, simulations, and stress-tests independent of the laws of physics, space, or time. In other words, while it remains speculative whether our social reality is itself a computer simulation, it is already certain that we live within a constellation of simulations that replicate parts of the material world.
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| Such replicas of reality depend on software. Over three decades ago, during the utopian enthusiasm for cyberspace, David Gelernter (1992) predicted that fractions of reality would be subsumed by simulated environments. He termed these software environments “mirror worlds,” i.e., worlds that would mirror reality and contain information akin to a database run as a simulation. When describing the user experience of the mirror world, Gelernter identified five conceptual building blocks: (1) deep pictures, (2) agents, (3) history, (4) experience, and (5) a connective idea that ties these elements together. The most fundamental building block, deep pictures, functions much like a digital twin model of a building; they can be interacted with at multiple zoom levels, perspectives, and time scales, including the ability to rewind and accelerate time. Deep pictures are dynamic databases containing entire living worlds that never remain static, and from today's perspective, they are not different from software platforms and protocols that shape most of today's built environments.
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| Architecture’s deep pictures can also be inhabited; they can contain cities. In 1998, the Dutch architecture practice MVRDV presented a speculative urbanism project, “Metacity/Datatown,” which envisioned a digital twin of a hypothetical city “based only upon data.” (Maas 1999, 58). Unlike today’s smart cities or smart landscapes—infused with sensors and tethered to metrics and dashboards—this project relied on the premise that the increasing density of communication infrastructures and computational power would likely alter the meaning of urban space itself. As the architects’ imagery suggested, converging cities around the globe might merge into a global “metacity,” with its data footprint constituting “Datatown,” governed entirely by statistics, diagrams, and information. In this way, “Metacity/Datatown” exemplifies a built environment where representation and operation converge. While none of the 1990s cyberspace utopias have fully materialized in contemporary built environments, the influence of these ideas on today’s corporate software platforms is undeniable.
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| Most buildings nowadays are built at least twice—first as a model, then as a physical object. Both instances contain identical information, with the difference being how the information is stored: as data or as physical matter. The first instance of a building relies on sophisticated data structures, software platforms, and networks. The second instance, the physical building, involves coordinating material resources and labor to assemble objects in accordance with the prescriptions of its digital replica (Bernstein 2017, 35). This setup differs from traditional conceptions of architecture, where sets of drawings and specifications eventually materialize into a built form. John May (2017) attributes this shift to the adoption of electric media and computation, resulting in the displacement of the architectural drawing by a real-time image sustained by technical systems. Unlike physical gestures inscribing information onto paper, the real-time image exists as an electric signal, statistics, data processing and storage, and networked software infrastructures. May (2017) frames this as a shift from ortography to post-ortography, where images and models are the same thing, and are no longer based of physical gestures (of drawing, reading), but rather on electronic signals stored as data. In other words, all architecture is a simulation and an abstraction of the reality through computation.
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| An example of real-time architectural imaging is building information modeling (BIM) technology. Cardoso-llach (2017) has termed BIM files as “structured images” that are both numeric and visual at the same time. When completed, the first instance of the building exists as multi-dimensional image, where every door knob, floor tile, column or window is held together by parametrically defined interdependencies. Not unlike an MMORPG video game, BIM functions as a network where actors interact by manipulating symbolic representations of buildings and their components. All interactions—and conflicts between intersecting building elements and systems (known as “clashes”)—are mediated by the central model, which serves as a register of truth. BIM models form the foundation of digital twins; they contain all possible information about a building, including material composition, quantities, and dimensions, extending into time-based simulations, carbon accounting, automation, cost, and other performance metrics. However, in BIM and other environments like neural networks, the representation of any material object as data, as K Allado-McDowell (2023) points out, requires “reducing the object to its dimensionality.” A house, for instance, can exist in virtually infinite dimensions as data. Yet, to make it legible as a space, it must be reduced to three dimensions—and further reduced to two or even one dimension to represent its value or other parameters. (Ibid)
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| It is no coincidence that architecture and video game industries increasingly share techniques (rendering, modeling), software (Blender, Unreal Engine), and concepts. For instance, “Level of Detail” (LOD) describes the degree of detail in digital assets. In video games, LOD values depend on polygon counts, texture resolution, and overall graphics performance. Similarly, in the mirror worlds of architecture, LOD measures realism or the degree to which a model represents reality. In BIM environments, an LOD of 100 suggests approximate geometry, while an LOD of 500 corresponds to “as-built conditions” and may function as a legally binding register of construction quality. A high LOD in a digital model is analogous to high resolution in a digital image; a higher value implies a more accurate representation of reality.
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| Yet even the highest LODs of mirror worlds fall short of matching the material reality governed by the laws of physics. Tethering more material and finer scales to real-time electronic images remains a fundamental challenge, if not an impossibility, for the technological project of the mirror world. Physics dictates that atomic and subatomic structures of matter function differently from computational concepts like pixels, vectors, meshes, textures, and simulation engines. While the mirror world is computed via electronic signals, rendered in polygons, and displayed on grids of illuminated squares, the second iteration of the building contains information encoded not as data but as the properties of physical matter and the techniques for manipulating it. Despite the connections between cyberspace, digital twins, and the material realities of the world—via data flows, sensors, robots, screens, and more—they often operate on incompatible protocols and systems. This divide is more than a technical obstacle; it underscores a fundamental dissonance between the tangible and the symbolic. Perhaps, forms of deep pictures already have come to life, and what architects need are deep infrastructures to make a meaning of them.
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| References
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| Allado-McDowell, K. “Designing Neural Media.” Accessed January 6, 2025. <nowiki>https://www.berlinerfestspiele.de/en/gropius-bau/programm/journal/2023/k-allado-mcdowell-designing-neural-media</nowiki>.
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| Bernstein, Phillip. ''Architecture, Design, Data: Practice Competency in the Era of Computation''. Basel, Switzerland: Birkhäuser Verlag GmbH, 2018.
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| Cardoso Llach, Daniel. “Architecture and the Structured Image: Software Simulations as Infrastructures for Building Production.” In _The Active Image_, edited by Sabine Ammon and Remei Capdevila-Werning, 28:23–52. Cham: Springer International Publishing, 2017.
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| Gelernter, David Hillel. ''Mirror Worlds or the Day Software Puts the Universe in a Shoebox: How It Will Happen and What It Will Mean''. 1. issued as an Oxford Univ. Press paperback. Oxford Paperbacks. New York: Oxford Univ. Press, 1992.
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| Maas, Winy and MVRDV (Firm), eds. ''Metacity Datatown''. Rotterdam: MVRDV/010 Publishers, 1999.
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| May, John. “Everything Is Already an Image.” ''Log'', no. 40 (2017): 9–26. <nowiki>http://www.jstor.org/stable/26323867</nowiki>.
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| Poole, Matthew, and Manuel Shvartzerg, eds. ''The Politics of Parametricism: Digital Technologies in Architecture''. London New Delhi New York: Bloomsbury Academic, an imprint of Bloomsbury Publishing Plc, 2015.
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| Siegert, Bernhard. ''Cultural Techniques: Grids, Filters, Doors, and Other Articulations of the Real''. Translated by Geoffrey Winthrop-Young. First edition. Meaning Systems. New York: Fordham University Press, 2015.
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| {{DEFAULTSORT:Matiss - Architecture's Mirror Worlds}}
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| [[Category:emd]]
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| = Comments =
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