Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment

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Description

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 deploymentExisting methods for applying machine learning operations (MLOps)AI system architecture including a description of each of the AI pipeline building blocksChallenges 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 

Additional information

Weight 1.22 kg
Dimensions 4.15 × 18.42 × 23.5 cm
PubliCanadanadation City/Country

USA

by

,

Format

Hardback

Language

Pages

580

Publisher

Year Published

2024-6-11

Imprint

ISBN 10

0262048981

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.

Other text

“Truly a masterpiece, providing a unique how-to guide on developing Al strategies and roadmaps using a system engineering approach, including academic and industry insights and human-machine augmentation use cases.”—Liliana Horne, Executive Director, IBM; Top 100 Most Influential Global Hispanic Technology Executives “A comprehensive and engaging guide to AI implementation drawing on history, best practice, and the authors' impressive experience. This is an empowering read for industry leaders looking to build AI capability into their workflows.”—Mike Moulin-Ramsden, Haslam Advisory “Unlike typical books in AI or machine learning, the authors have succeeded in bringing a wide range of topics in technology, processes, and people at sufficient depth to explain what it takes to ‘engineer’ complex AI systems.”  —Padmanaban Santhanam, Principal Research Staff Member, IBM Research; coauthor of Beyond Algorithms: Delivering AI for Business

Table Of Content

Table of ContentsPreface 3Acknowledgements 61 Overview 17Part I AI System Architecture 492 Fundamentals of Systems Engineering 503 Data Conditioning 864 Machine Learning 1275 Modern Computing 1816 Human-Machine Teaming 2587 Robust AI Systems 2978 Responsible AI 343Part II Strategic Principles 3759 AI Strategy and Roadmap 37610 AI Deployment Guidelines 42711 MLOps: Transitioning from Development into Deployment 47312 Fostering an Innovative Team Environment 51813 Communicating Effectively 57414 Use-Case Example #1: Misty Companion Robot as Alzheimer’s Application 60515 Use-Case Example #2: Bose AI-Powered Cycling Coach and Warning System 61416 Use-Case Example #3: Meal Evaluation & Attainment Logistics System (MEALS) 62217 Use-Case Example #4: Managing Energy for Smart Homes (MESH) 63218 Use-Case Example #5: AquaAI—An AI-Powered Modernized Marine Maintenance System 641Appendices 649Glossary 677Index 680

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