Transitional Architecture

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TRANSITIONAL ARCHITECTURE

Graduate Thesis 2022

Kangxin Wu



Graduate Thesis 2022 Provocations Positions Project

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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

Cla

nO utpu

t

0

Pre-emption fallacy Correlation as causation

Patter n gen e

ion gnit reco tern Pat

on

Subject of control

Gen e

icati

ratio

ssif

OBFUSCATION

Outp ut

(Policeman, scientist, artist)

Subject of control

ADVERSARIAL ATTACK

PR

IN PU T

Operator

IM ER

Cla

ss

ific

ati

on

Black box horizon

Inp

Ge

on

rati

ne

ut

ut

Inp

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

H

Operator Fitting Overfitting

Statistical inference

Extrapolation

Model fitting

Interpolation

Pre-emption

Extrapolation

Approximation

Curve fitting X

X

X

X

X

X

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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