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.
1.00 LU
- RIBA
Instructors
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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
Founding Principal | Supernormal
Elizabeth Bowie Christoforetti is founding principal at Supernormal, an architecture and research... -
Ken Goulding
Director | Sasaki Strategies
Ken is a principal and serves as director of Sasaki Strategies—a team of analysts, statisticians,... -
Scott Penman
Design Technologist | Sasaki Strategies
Scott Penman is a multi-disciplinary designer and researcher interested in architecture, emerging...