Machine Learning
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Table of Contents

Acknowledgments IntroductionForeword by Mark Greaves

1 - PROCESS 1.1 Tools and technologies

1.2 - What is AI?

1.3 Professional Information and Knowledge

1.4 AI and Process Transformation in Design, and Beyond

1.5 Scopes of Service

1.6 Delivery, Means and Methods 2 - RELATIONSHIPS 2.1 Economics

2.2 Laws, Policy, and Risk

2.3 Professionalism

2.4 Education, Certification, and Training 3 - RESULTS 3.1 Objectives of design

3.2 Creating, Consuming and Curating Data

3.3 Tasks, Automation

3.4 Labour of Design

3.5 Value Propositions and Business Models IndexBibliography

About the Author

Phil Bernstein is an architect and technologist who is an Associate Dean and Professor, Adjunct at the Yale School of Architecture where he has been a member of the faculty since 1988. Prior to his current full-time role at Yale he was a vice president at Autodesk, where he helped develop and execute the company strategy that resulted in Building Information Modelling. Prior to Autodesk he was a principal at Pelli Clarke Pelli Architects. He is the author of Architecture Design Data: Practice Competency in the Era of Computation, and co-author of Building (In) the Future: Recasting Labor in Architecture and Goat Rodeo: Practicing Built Environments. He writes, lectures, and consults extensively on the implications of technology on architectural practice.

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