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Encoded Memory: Artificial Intelligence and Deep Learning in Architecture

Encoded Memory: Artificial Intelligence and Deep Learning in Architecture

Alberto Tono, Hannah Tono, Andrea Zani
Copyright: © 2020 |Pages: 23
ISBN13: 9781799812340|ISBN10: 1799812340|EISBN13: 9781799812364
DOI: 10.4018/978-1-7998-1234-0.ch012
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MLA

Tono, Alberto, et al. "Encoded Memory: Artificial Intelligence and Deep Learning in Architecture." Impact of Industry 4.0 on Architecture and Cultural Heritage, edited by Cecilia Maria Bolognesi and Cettina Santagati, IGI Global, 2020, pp. 283-305. https://doi.org/10.4018/978-1-7998-1234-0.ch012

APA

Tono, A., Tono, H., & Zani, A. (2020). Encoded Memory: Artificial Intelligence and Deep Learning in Architecture. In C. Bolognesi & C. Santagati (Eds.), Impact of Industry 4.0 on Architecture and Cultural Heritage (pp. 283-305). IGI Global. https://doi.org/10.4018/978-1-7998-1234-0.ch012

Chicago

Tono, Alberto, Hannah Tono, and Andrea Zani. "Encoded Memory: Artificial Intelligence and Deep Learning in Architecture." In Impact of Industry 4.0 on Architecture and Cultural Heritage, edited by Cecilia Maria Bolognesi and Cettina Santagati, 283-305. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-1234-0.ch012

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Abstract

This chapter provides an overview of some artificial intelligence applications in the architecture, engineering, and construction industry. Furthermore, the authors will define Creativity and its limits for the machine in the role of architecture. This chapter raises the importance of start developing framework for artificial intelligence applications and big data to create the fundamental to further developments. Moreover, the importance of sharing data and train models in an open-source community will become a great asset to the development of our industry. In the future, Industry 4.0 will see more entrepreneurs in the field of architecture, engineering, and construction.

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