Machine Learning: Architecture in the age of Artificial Intelligence
Acerca de este libro electrónico
The profession is changing. A new era is rapidly approaching when computers will not merely be instruments for data creation, manipulation and management, but, empowered by artificial intelligence, they will become agents of design themselves. Architects need a strategy for facing the opportunities and threats of these emergent capabilities or risk being left behind. Architecture’s best-known technologist, Phil Bernstein, provides that strategy. Divided into three key sections – Process, Relationships and Results – Machine Learning lays out an approach for anticipating, understanding and managing a world in which computers often augment, but may well also supplant, knowledge workers like architects. Armed with this insight, practices can take full advantage of the new technologies to future-proof their business. Features chapters on:
- Professionalism
- Tools and technologies
- Laws, policy and risk
- Delivery, means and methods
- Creating, consuming and curating data
- Value propositions and business models.
Acerca del autor
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.
