Abstract
In digital design practice, the connection and feedback between physical and digital modelling is receiving increasing attention and is seen as a source of creativity and design innovation. The authors present a workflow that supports real-time design collaboration between human and machine intelligence through physical model building. The proposed framework is investigated through a case study, where we test the direct connectivity of physical and digital modelling environments with the integration of artificial neural networks. By combining 3D capturing tools and machine learning algorithms, the research creates an instant feedback loop between human and machine, introducing a hybrid immediacy that puts physical model building back at the centre of the digitally focused design process. By fusing physical models and digital workflows, the research aims to create interactivity between data, material and designer already at the early stage of the design.
Keywords
- Computational immediacy
- Early design phase
- ANN
- Physical model building
- Hybrid design tool
- 3D capturing
- Machine intelligence
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- 1.
A famous example of such a concept model is the digital model for the Moebius house by UN Studio. See image in (Hirschberg et al., 2020).
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Acknowledgements
This work was funded by the Austrian Science Fund (FWF) project F77 (SFB “Advanced Computational Design”).
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Bank, M. et al. (2023). Hybrid Immediacy: Designing with Artificial Neural Networks Through Physical Concept Modelling. In: Gengnagel, C., Baverel, O., Betti, G., Popescu, M., Thomsen, M.R., Wurm, J. (eds) Towards Radical Regeneration. DMS 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-13249-0_2
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