The synthesis of artificial intelligence, deep learning and parametric design in regenerative digital design can significantly reshape the pre-design phase in climate scenarios. By formulating a new workflow linking computational processes with human-centred design, it is possible to realise a more adaptive approach to environmental design that anticipates the complexities of our built environment and fosters responsive and resilient collective creativity. Starting from the abstract and introduction, a focus is proposed to investigate the complexity and emerging field of regenerative digital design, particularly in climate scenarios. The basic premise is that AI’s deep learning and natural language processing capabilities can go beyond simple visual outcomes to address nuanced and multifaceted design challenges.

Generative IA and complexity. Towards a new paradigm in regenerative digital design / Nava, Consuelo; Melis, Alessandro. - In: AGATHÓN. - ISSN 2532-683X. - 16:1(2024), pp. 40-49. [10.19229/2464-9309/1632024]

Generative IA and complexity. Towards a new paradigm in regenerative digital design

Nava Consuelo
Methodology
;
2024-01-01

Abstract

The synthesis of artificial intelligence, deep learning and parametric design in regenerative digital design can significantly reshape the pre-design phase in climate scenarios. By formulating a new workflow linking computational processes with human-centred design, it is possible to realise a more adaptive approach to environmental design that anticipates the complexities of our built environment and fosters responsive and resilient collective creativity. Starting from the abstract and introduction, a focus is proposed to investigate the complexity and emerging field of regenerative digital design, particularly in climate scenarios. The basic premise is that AI’s deep learning and natural language processing capabilities can go beyond simple visual outcomes to address nuanced and multifaceted design challenges.
2024
artificial intelligence, regenerative digital design, enabling technologies, emerging technologies, exaptation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/154527
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