Overview

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

Full Product Details

Author:   David R. Martinez ,  Bruke Kifle
Publisher:   MIT Press Ltd
Imprint:   MIT Press
Weight:   0.567kg
ISBN:  

9780262048989

ISBN 10:   0262048981
Pages:   576
Publication Date:   11 June 2024
Audience:   General/trade ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   To order  
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Table of Contents

Table of Contents Preface 3 Acknowledgements 6 1 Overview 17 Part I AI System Architecture 49 2 Fundamentals of Systems Engineering 50 3 Data Conditioning 86 4 Machine Learning 127 5 Modern Computing 181 6 Human-Machine Teaming 258 7 Robust AI Systems 297 8 Responsible AI 343 Part II Strategic Principles 375 9 AI Strategy and Roadmap 376 10 AI Deployment Guidelines 427 11 MLOps: Transitioning from Development into Deployment 473 12 Fostering an Innovative Team Environment 518 13 Communicating Effectively 574 14 Use-Case Example #1: Misty Companion Robot as Alzheimer’s Application 605 15 Use-Case Example #2: Bose AI-Powered Cycling Coach and Warning System 614 16 Use-Case Example #3: Meal Evaluation & Attainment Logistics System (MEALS) 622 17 Use-Case Example #4: Managing Energy for Smart Homes (MESH) 632 18 Use-Case Example #5: AquaAI—An AI-Powered Modernized Marine Maintenance System 641 Appendices 649 Glossary 677 Index 680

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Author Information

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.

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