1st Edition

Democratization of Artificial Intelligence for the Future of Humanity




  • Available for pre-order. Item will ship after January 15, 2021
ISBN 9780367524128
January 15, 2021 Forthcoming by CRC Press
390 Pages 8 Color & 80 B/W Illustrations

USD $100.00

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Book Description

Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously, from real-world use and experience, and its capability to improve its performance. It is no wonder that the applications of AI span from complex high-technology equipment manufacturing to personalized exclusive recommendations to end-users. Many deployments of AI software, given its continuous learning need, require computation platforms that are resource intense, and have sustained connectivity and perpetual power through central electrical grid.

In order to harvest the benefits of AI revolution to all of humanity, traditional AI software development paradigms must be upgraded to function effectively in environments that have resource constraints, small form factor computational devices with limited power, devices with intermittent or no connectivity and/or powered by non-perpetual source or battery powered.

The aim this book is to prepare current and future software engineering teams with the skills and tools to fully utilize AI capabilities in resource-constrained devices. The book introduces essential AI concepts from the perspectives of full-scale software development with emphasis on creating niche Blue Ocean small form factored computational environment products. It also:

  • Outlines Artificial Intelligence Software Architecture & Cloud Architecture with emphasis to Edge Computing.

  • Provides comprehensive comparison and applicability of AI algorithms in constrained environments: Supervised, Unsupervised, and Reinforcement

  • Emphasis real-time embedded storages for AI applications, specific to constrained environments

  • Develops AI Driver Software code with real-time deep learning small footprint frameworks such as tensor flow, python, C, Android and iOS Swift.

  • Provides exclusive AI field deployments that operate in remote & non-connected environments

  • Explains AI solution development from a Product management perspective

The book details several AI reference architectures with emphasis on democratizing Artificial Intelligence to environments that operate under compute & network connectivity issues.

Table of Contents

SECTION I - INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND FRAMEWORKS

Introduction

What is AI?

AI Epoch’s: Waves of Compute

AI Hype Cycle – Current and Emerging Technologies

AI - End-To-End (E2E) Process – Turning Data into Actionable Insights

Microsoft Azure - AI E2E Platform

AI Development Operations (DevOps) Loop for Data Science

AI –Performance and Computational Notations

AI for Greater Good – Solving Humanity and Societal Challenges

References

Standard Processes and Frameworks

Digital Transformation

Digital Feedback Loop

Insights Value Chain

The CRISP-DM Process

Building Blocks of AI - Major Components of AI

AI Reference Architectures

References

SECTION II - DATA SOURCES AND ENGINEERING TOOLS

Data – Call for Democratization

Call for Action

The Last Mile - Constrained Compute Devices AND "AI Chasm"

References

Machine Learning Frameworks and Device Engineering

Machine Learning Device Deployments

xRC Modeling: Model Accuracy-Connectivity-Hardware (MCH) Framework

Circular Buffers

AI Democratization – "Crossing the Chasm"

References

Device Software and Hardware Engineering Tools

Software Engineering Tools

Hardware and Engineering Tools

Libraries

References

SECTION III - MODEL DEVELOPMENT AND DEPLOYMENT

Supervised Models

Decision Trees

XGBoost

Random Forrest

Naïve Bayesian

Linear Regression

Kalman Filter

References

Unsupervised Models

Hierarchical Clustering

K-Means Clustering

References

SECTION IV - DEMOCRATIZATION AND FUTURE OF AI

National Strategies

National Technology Strategies for Serving People

The United Nations AI Technology Strategy

The role of the UN

AI in the Hands of People

References

Future

Democratization of Artificial Intelligence for the Future of Humanity

Dedication

Acknowledgement

Preface

Appendix

Index

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Author(s)

Biography

Chandra is a Software IT Executive and Entrepreneur with diverse experience in Software Technologies, Enterprise Software Architectures, Cloud Computing, Data Analytics, Internet of Things (IoT), and Software Product & Program Management. Chandra has held engineering architectures and product leadership roles at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies, a Bell Laboratories Company. Chandra teaches Software Engineering, Large Scale Analytics, Data Science, Mobile Technologies, Cloud Technologies, and Web & Data Mining for Masters program in San Jose State University. Additionally, Chandra held market research, strategy and technology architecture advisory roles in Cisco Systems, Lam Research and performed Principal Investigator role for Valley School of Nursing where he connected Nursing Educators & Students with Virtual Reality technologies. Chandra has authored several international conference papers and published book on Building Enterprise IoT Applications. Chandra has functioned as Chair in numerous technology and advanced computing conferences such as: IEEE Oxford, UK, IEEE Big Data Services 2017, San Francisco USA, Future of Information and Communication Conference 2018, Singapore and Intelligent Human Systems Integration (IHSI) 2020, Modena, Italy. Chandra graduated from San Jose State University Masters Program, specializing Software Engineering, and completed his Master of Business Administration from Santa Clara University, Santa Clara, California, USA.