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Entropy Project is a design research practice integrating protocols of computational architecture, remote-sensing earth science, artificial intelligence, and design informatics into an in silico experimental system and augmented interface––in order to perform architecture-oriented existential riskologies. The practice advances a self-reflexive approach to existential risks, using ‘intelligence’ to investigate intelligence through planet-scale computational systems. It is an obverse architecture, a feedforward spatial thought praxis to mediate patterns of anthropogenic change, as a species-wide gesture of self-annihilation after humans emerged as a terraforming force.
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Entropy Project foregrounds architecture as an augmented intelligence of ‘risk perception’ to anticipate adverse events through information-based environmental scanning. It is a self-lacerating attempt of sapient intelligence at feedforward propulsion to anticipate possible future substrates and habitable zones. Intelligence anticipates the ex-catastrophic world in a ‘future perfect’ temporal architecture, cascading towards a temporal locus to build retrospections and binding prospects and retrospect together in a diagrammatic manner. It escalates dormant existential risk indicators into architectural accounts of hitherto unknown material realities while encoding the ‘it will have happened’ scenario.
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Entropy Project advances model pluralism as an epistemic approach, synthesising partial local profiles into a ‘synthetic environment’ to develop a multi-scalar, multi-regional and multi-modal configuration of the ex-catastrophic space. The architectural artefact is a spatiotemporal condensation of an ex-catastrophic field, a miniature annihilation. The project situates design as intelligence in-situ, implicated in base-material processes, in regions exposed to the compound effects of anthropogenic changes––to model threats of cascading failures at a global scale. It is enacted through field research, in collaboration with government and non-government organisations.
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The sites perform as 'analogue environments' of an ex-catastrophic world, ranging from subterranean nutrient-void caves, and inundated coastal suburbs to toxic, high-altitude landscapes with tenuous atmospheres, echoing geo-environmental traits of extremophilic planets and post-extinction astrobiological landscape. The practice re-casts the catastrophic scope of small, localised anthropogenic changes, including built infrastructure through commissioned works, as near-future uninhabitable sectors in the ‘astrobiological landscape’. The core aim is to read human-environment interactions under the cataclysmic twilight of existential ‘disasters’ (dis- ‘cut off’ and -astrum- ‘star’).
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In territories foreclosed to field research, the practice uses geospatial intelligence enacted through ground-breaking practices of remote sensing earth science, including satellite and terrestrial-based light detection and ranging methods, synthetic aperture radar sensing, hyper-spectral imaging, and geographic information systems modelling. The core emphasis is on design informatics of ‘point clouds’ acquired through light detection and ranging methods. The point cloud is a forensic-grade accurate rendition of geo-environmental conditions in-situ, translating sensor-based spectrometric physics into n-body models with billions of topographic and radiometric details. It is precise enough to geo-locate an airborne particle.
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The design informatics procedure operates in a step-wise manner: (a) deep learning-based neural networks for pattern recognition and automating tasks of object classification and semantic segmentation to discriminate natural and artificial signatures in a selected environment and detect outliers; (b) computational simulation as a portable lab to manipulate gaseous-fluid dynamics physics and approximate non-linear, stochastic phenomena using complex interaction between nth points, constrained under cosmological forces; (c) data visualisation, static-, interactive or time-based as an analysis-oriented, autographic approach to detect signatures of airborne saturation, moisture content, surface reflection, temperature levels, spectral emission, and electromagnetic feedback.
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The outcomes include forensic-grade point cloud architectural diagrams and digital animations, analysis-oriented data visualisations, interaction-based simulated immersions, large-scale post-cinematic installations, digital fabrications, software applications and computer games, disseminated through public exhibitions and peer-reviewed academic formats. The project contributes to academic ecosystems through pedagogical engagement, including the development of course modules, design briefs, seminar series, technical workshops and public events across leading graduate studios in computational architecture, design informatics and digital media across the United Kingdom and the Middle East.
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The project is directed by Asad Khan.