TRANSITIONAL ARCHITECTURE
Graduate Thesis 2022
Kangxin Wu
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Thesis Statement This thesis discusses the possibility of new architecture aesthetics with the help of AI. With the development in the digitial realm, forms can be rapidly generated and customized. AI scripts such as StyleGAN can merge two kinds of images with high resolution. Applied to buildings, such power enables a revolution on styles. Processing a historical building with a filter of modern design suggests a redefinition of renovation. This thesis is also influenced by the philosophical idea of "Mereology", a study of parthood relationships. I aim to rethink building through a reorganization and manipulation of its parts and details. Aside from the Boolean operations that people
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usually adopt for designing part relations, what new relationship will the AI generated pattern bring? How to utilize these 2d information into 3d design? Can it suggest something new in the process of form generation?
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INITIAL IDEAS WORDS technology/ post-digital/ simulations/ mass production details/ material/ craftsmanship/ tectonics resolution/ representation/ camera logic
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PROJECTS OF INSPIRATION parts/ figures collection/ system interior/ exterior image/ volume
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1. Cae Lique Dolest Abo 2. Lorem Ipsum Dolor — Eicidentist
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Mark Foster Gage
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READINGS ON MEREOLOGY For example, inside a factory, individuals were cast as workers, inside schools as students. Man without a cast and without an enclosure seemed to be freed from class and struggle. The freedom of an individual was interlinked with their transcendence from physical enclosures. It is a mistake to compute buildings as though they are repositories or enclosures, no matter how fine-grain their resolution is. The value of a building is no longer derived only from the amount of rent for a slot of space, but from its capacities to partake with. By this, the core function of a building changes from inhabitation to participation. Buildings do not anymore frame and contain: they bind, blend, bond, brace, catch, chain, chunk, clamp, clasp, cleave, clench, clinch, clutch, cohere, combine, compose, connect, embrace, fasten, federate, fix, flap, fuse, glue, grip, gum, handle, hold, hook, hug, integrate, interlace, interlock, intermingle, interweave, involve, jam, join, keep, kink, lap, lock, mat, merge, mesh, mingle, overlay,
palm, perplex, shingle, stick, stitch, tangle, tie, unit, weld, wield, and wring. In daily practice, BIM models do not highlight resolution but linkages, integration and collaboration. With further computation, distributed manufacturing, automated design, smart contracts and distributed ledgers, building parts will literally compute the Internet of Things and eventually our built environment, peer-to-peer, or better, part-to-part – via the distributive relationships between their parts. For the Internet of Things, what else should be its hubs besides buildings? Part-to-part habitats can shape values through an ecology of linkages, through a forest of participatory capacities. So, what if we can participate in the capacities of a house? What if we no longer have to place every brick, if we no longer have to delegate structures, but rather let parts follow their paths and take their own decisions, and let them participate amongst us together in architecture?
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READINGS ON MEREOLOGY Following Roberto Casati and Achim Varzi, the four fundamental mathematical formularisations of mereology are: “Relations are reflexive, antisymmetric and transitive. (...) First, everything is part of itself. Second, two different objects cannot be part of each other. Third, each part of a part of a whole is also part of that whole. Fourth, an object can be a part of another object, if both exist.”[10] Part-to-Part Without Whole – The Ultimate Parts For part-to-part relations, local interactions are emphasised, and interactions occur at multiple levels of compositions, where the part-to-part relations in some cases are similar to that between wholes. It has following classifications: juxtapose, interrelate, contain, partition, overlap, trans-juxtapose, over-juxtapose, over-partition, over-overlap. The nature of these relations has different influences on the components. The intrinsic relation tends to define the identities
of all the parts and fix them into exact location, while the extrinsic relation connects the parts in exteriority – without interfering with their identities. DeLanda summarised four characteristics of assemblage: 1) individuality, an assemblage is an individual entity, despite different scale or different number of components; 2) heterogeneity, components of an assemblage are always heterogeneous; 3) composable, assemblages can be composed into another assemblage; 4) bilateral-interactivity, an assemblage emerges from parts interactions, it also passes influences on parts.[18] DeLanda then moved on to the two parameters of assemblage. The first parameter is directed toward the whole, the “degree of territorialisation and deterritorialisation”, meaning how much the whole “homogenises” its component parts. The second parameter is directed toward the parts, the “degree of coding and decoding”, meaning how much the identities of parts are fixed by the rules of the whole. The concept of assemblage provides us
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a new lens of investigating these mereological relations. With this model, the heterogeneities and particularity of parts are fully respected. The wholes become immanent, individual entities, existing “alongside the parts in the same ontological plane”,[19] while parts in a whole are included in the whole but not belonging to it, and according to Bryant’s discourse, the absence of belonging dispelled the existence of the whole.[20] From the study of regime of attraction and assemblage, this essay proposes a new concept – “the ultimate parts” – in which a proper “part-to-part without whole” is embedded. A part (P) horizontally interacts with its neighbouring parts (Pn), with parts of neighbouring parts (Pnp), as well as interacting downwardly with parts that compose it (Pp) and upwardly with wholes it is constituting which are also parts (Pw). This concept significantly increases the initiatives of parts and decreases the limitations and reductions of them. It doesn’t deny the utilities of the whole, but con-
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siders the whole as another independent entity, another part. It’s neither top-down, nor bottom-up, but projects all relations from a hierarchical structure to a comprehensive flattened structure. The ultimate parts concept provides a new perspective for observing relations between objects from a higher dimension.
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DISCRETE vs. CONTINUOUS
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THE MANIPULATION OF AI everything fluid and interchangeable Architects should set back and enjoy the benefit of technology; employ AI as workers for generating design options an alternate vision of the labor field (not trying to compete with machine) control the input and output spectrum and middle ground discrete and continuous
Casey Rehm Workshop
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StyleGAN2 Training
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NOOSCOPE
THE RISE OF AI STATISTICAL MODELS AS INSTRUMENTS OF KNOWLEDGE A DIAGRAM OF MACHINE LEARNING ERRORS, BIASES AND LIMITATIONS
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3. Model Application
VLADAN JOLER AND MATTEO PASQUINELLI (2020) WWW.NOOSCOPE.AI
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CLASSIFICATION MODALITY
GENERATION MODALITY
Automation of labour Present world
Future world
Calculation of surplus-value
Power of normalisation
Deep dreaming Scientific halucination
Undetection of the new Naturalisation of bias Regeneration of the old
(“New Jim Code”)
Predi ration ctio n
n icatio ssif Cla 1
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Pre-emption fallacy Correlation as causation
Patter n gen e
ion gnit reco tern Pat
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Subject of control
Gen e
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OBFUSCATION
Outp ut
(Policeman, scientist, artist)
Subject of control
ADVERSARIAL ATTACK
PR
IN PU T
Operator
IM ER
Cla
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Black box horizon
Inp
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Accumulated machine bias
Accumulated human bias Multidimensional vector space
Algorithmic statistical
2. Learning Algorithm
Model
Interpolation and Extrapolation
Hyperparameters
Evaluation bias
Evaluation Ghost worker
Operator
(Heteromation)
Pattern extraction
Testing environment
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Operator Fitting Overfitting
Statistical inference
Extrapolation
Model fitting
Interpolation
Pre-emption
Extrapolation
Approximation
Curve fitting X
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Statistical Anomaly
Underfitting
Anomaly loss
Dimensionality reduction
Feature extraction
Algorithm architecture
Topology
Algorithm
1. Training Dataset
Category reduction Metadata / Labels Labeling bias
Labeling Labeling
Bias amplification
Selection bias
Operator
Selection Ghost worker
Format framing Database format
Operator
Information reduction Data Representation bias
Source selection Operator
Capture
Ghost worker
DATA POISONING
Resolution reduction Sensor
DATA ANONIMISATION
Past world
HUMAN BIAS, INTERVENTIONS AND ERRORS
MACHINE AND STATISTICAL BIAS
Machine Bias
Division of labour
Technical structure
Society
Process
Action
Operator
Human bias
Ghost Worker
Historical bias
Information reduction
Ghost worker
Dataset composition
Taxonomies
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AI TRAINING & NEXT STEP For the thesis project, I will focus on the art deco history of Los Angeles and use AI to change its appearance. From the alteration of facade details, I will develop a strategy to manipulate the interior spaces as well.
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OSTAGRAM AI TRAINING CONTENT
FILTER
RESULT
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Art Deco Building
Parametric Building
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Art Deco Building
Glass Building
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REFERENCES • Issue1-Prospectives (https://journal.b-pro.org/issue/issue1/) • Craftsmanship in the Digital Age #2 Mario Carpo (https://vimeo.com/261702777) • The Second Digital Turn | Mario Carpo | Talks at Google (https://www.youtube.com/ watch?v=UVerq5DSdKU) • Google Arts and Culture Experiments - X degrees of Seperation by Mario Klingemann (https://artsexperiments.withgoogle.com/xdegrees/8gHu5Z5RF4BsNg/BgHD_ Fxb-V_K3A) • Making Ready for a Big World (https://makingandbreaking.org/article/patricia-reedmaking-ready-for-a-big-world/) • Discrete Automation, Mollie Claypool (https://www.e-flux.com/architecture/ becoming-digital/248060/discrete-automation/) • Delirious Facade (https://lamas.us/thinking/delirious-facade) • Gilles Retsin: Bits & pieces: discrete architecture (https://www.youtube.com/ watch?v=cfWrPd2Klv8) • AItect:Can AI make designs ? (https://www.makoto-architect.com/aitect.html) • Towards Artificial Intelligence in Architecture: How machine learning can change the way we approach design (https://www.fosterandpartners.com/plus/towardsartificial-intelligence-in-architecture/) • AI & Architecture, An Experimental Perspective, Stanislas Chaillou (https://medium. com/built-horizons/ai-architecture-4c1ec34a42b8) • Nooscope (https://nooscope.ai) • Understanding the StyleGAN and StyleGAN2 Architecture (https://medium.com/ analytics-vidhya/understanding-the-stylegan-and-stylegan2-architectureadd9e992747d)
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