Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment (MIT Lincoln Laboratory Series)

Martinez, David R.,Kifle, Bruke M.

ISBN 10: 0262048981 / ISBN 13: 9780262048989

Published by The MIT Press, 2024

About this Item

Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.

Seller Inventory # mon0000050641

Bibliographic Details

• Title: Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment (MIT Lincoln Laboratory Series)
• Publisher: The MIT Press
• Publication Date: 2024
• Language: English
• ISBN 10: 0262048981
• ISBN 13: 9780262048989
• Binding: hardcover
• Condition: Very Good

About this title

Synopsis

The first text to take a systems engineering approach to artificial intelligence (AI), from architecture principles to the development and deployment of AI capabilities.

Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book. 

Key features:

• In-depth look at modern computing technologies 
• Systems engineering description and means to successfully undertake an AI product or service development through deployment
• Existing methods for applying machine learning operations (MLOps)
• AI system architecture including a description of each of the AI pipeline building blocks
• Challenges and approaches to attend to responsible AI in practice    
• Tools to develop a strategic roadmap and techniques to foster an innovative team environment 
• Multiple use cases that stem from the authors’ MIT classes, as well as from AI practitioners, AI project managers, early-career AI team leaders, technical executives, and entrepreneurs 
• Exercises and Jupyter notebook examples 

About the Author

David R. Martinez is a laboratory fellow at the MIT Lincoln Laboratory and the lead instructor for MIT’s “AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment” and “AI and ML: Leading Business Growth” courses. 
Bruke Mesfin Kifle is management consultant and former AI product manager at Microsoft Turing. He co-instructs MIT’s "AI Strategies and Roadmap " course.