Machine Learning

‘The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.’ - Phil Bernstein

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.

In this revised edition, updated in line with the changes in the AI landscape since initial publication, 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.

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. He writes, lectures, and consults extensively on the implications of technology on architectural practice.