Machining and machine learning: Extending architectural digital fabrication through AI

Publications: Chapter in Book/Report/Conference proceedingBook chapterCommunication

Abstract

This chapter details how machine learning can help in the translation between an architectural element’s description and its making. With a specific focus on digital fabrication and deep learning, the chapter identifies new integrative workflows and datasets enabled by machine learning that can enable architects to rethink critical parameters of design, materiality, and fabrication. Three particular trajectories are identified—new opportunities for making fabrication information, new opportunities for material complexity, and new opportunities for interaction between humans and machines. Two case studies then exemplify the use of machine learning within the digital chain to (A) introduce flexibility and simplicity to the making of fabrication information and (B) capture complex interdependencies between material and fabrication parameters.
Original languageEnglish
Title of host publicationThe Routledge Companion to Artificial Intelligence in Architecture
Number of pages11
PublisherRoutledge
Publication date2021
Edition1
Chapter21
ISBN (Electronic)9780367824259
DOIs
Publication statusPublished - 2021

Keywords

  • Machine Learning
  • Digital Fabrication
  • Digital architecture
  • Computational Design
  • Robotic Fabrication

Artistic research

  • No

Cite this