Description

Book Synopsis

‘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.

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.




Table of Contents

Acknowledgments

Introduction

Foreword 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

Index

Bibliography

Machine Learning: Architecture in the age of

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    Order before 4pm today for delivery by Fri 31 Jul 2026.

    A Paperback / softback by Phil Bernstein

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      View other formats and editions of Machine Learning: Architecture in the age of by Phil Bernstein

      Publisher: RIBA Publishing
      Publication Date: Publication Date: 01/05/2022
      ISBN13: 9781914124013, 978-1914124013
      ISBN10: 1914124014

      Description

      Book Synopsis

      ‘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.

      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.




      Table of Contents

      Acknowledgments

      Introduction

      Foreword 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

      Index

      Bibliography

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