Generative Adversarial Networks in a Design Practice

Description: 

From Building Connections Congress 2021: Machine Learning’s Impact on Architecture and Design hosted by the AIA Technology in Architectural Practice (TAP) Knowledge Community. This course explores Generative Adversarial Networks (GANs), and how they could be leveraged by the design team.  

 

Learning objectives

  • Discuss existing tools and applications that are dramatically reducing the barrier of entry for using machine learning. 
  • Explain the basic premise and operation of GANs. 
  • Describe GANs’ current strengths and weaknesses as related to creative applications. 
  • Explore how designers might soon incorporate machine learning into how they communicate design intent. rn about existing tools and applications that are dramatically reducing the barrier of entry for using machine learning. 

This session was recorded live on February 11, 2021.

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 $40  non-member
 $25  member
1.00 LU
  • RIBA

Instructors

  • Thiyagarajan Adi Raman

    Thiyagarajan Adi Raman

    Tech Lead | Sasaki

    As a Tech lead at Sasaki, Raj works with a team of data analysts, statisticians, UX/UI designers...
  • Elizabeth Christoforetti

    Elizabeth Christoforetti

    Founding Principal | Supernormal

    Elizabeth Bowie Christoforetti is founding principal at Supernormal, an architecture and research...
  • Ken Goulding

    Ken Goulding

    Director | Sasaki Strategies

    Ken is a principal and serves as director of Sasaki Strategies—a team of analysts, statisticians,...
  • Scott Penman

    Scott Penman

    Design Technologist | Sasaki Strategies

    Scott Penman is a multi-disciplinary designer and researcher interested in architecture, emerging...