AI In a Weekend An Executive's Guide

AI in a Weekend An Executives Guide

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Copyright © 2024 Unriveted Media

No part of this book may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or by an information storage and retrieval system – except by a reviewer who may quote brief passages in a magazine, newspaper, or on the web – without permission in writing from the publisher.

First Edition

ISBN: 979-8-9905516-0-2

Unriveted Media

Authors: John Sukup & Martin Miller

www.expectedx.com

www.m-vision.com

Unleashing the Potential

of Artificial Intelligence

Hello and welcome to AI in a Weekend: An Executive’s Guide! This guide offers a brief overview of artificial intelligence (AI), laying the foundation from fundamental concepts to advanced business applications and upcoming trends. Tailored for executives, it aims to illustrate the transformative potential of AI in organizational contexts, empowering leaders to make well-informed decisions regarding the adoption and integration of these cutting-edge technologies and, additionally, how to avoid costly mistakes!

If there is one thing we hope you take away from this book, it’s this:

AI is a transformative technology that enhances decision-making, operational efficiency, and customer experiences. For its successful integration, a profound understanding is essential, coupled with a capacity to navigate ethical–and privacy, considerations while not getting overwhelmed in the continuous chase for the next best thing.

Executives play a crucial role in leading the integration of AI within organizations. They have the responsibility for creating an environment that is receptive to it by promoting a culture that is focused on data-driven decision-making. Additionally, executives can enhance the organization’s adaptability to AI by improving data literacy, providing ongoing training and development opportunities, and nurturing an atmosphere conducive to innovation and technological advancement.

AI holds a promising future with the transformative potential to revolutionize businesses and entire industries (let alone the entire human race) in unprecedented ways. Executives proactive in embracing these evolving technologies will be strategically positioned for success and innovation in the emerging landscape.

Contents

Chapter 1: Introduction

The Rise of AI: From Machine Learning to Generative AI

Importance of Executives’ Understanding of AI

Generative AI: The Latest Emergent AI Subfield

Augmented Intelligence: The Other AI

Objectives and Structure of the Book

Chapter 2: Foundations of AI

Brief Overview of Concepts

Learning Algorithms

Artificial Neural Networks in Deep Learning

Contrasting ML Systems with LLM-based AI Systems

Chapter 3: Business AI

Enhancing Decision-Making Processes

Improving Operational Efficiency

Transforming Customer Experience

Chapter 4: Considerations for Executives

Establishing a Culture of Data-Driven Decision-Making

Addressing Ethical and Privacy Concerns

Managing Risks and Challenges

Chapter 5: Building an AI Strategy

Defining Business Objectives and Use Cases

Establishing Data Governance and Infrastructure

Selecting Appropriate AI Technologies

Assembling the Right Team and Skill Sets

Developing a Roadmap for Implementation

Chapter 6: Collaboration between Humans and Machines

Augmented Intelligence: Humans and AI Working Together

Reskilling and Upskilling the Workforce

Building Trust and Confidence in AI Systems and their Capability

Chapter 7: Case Studies: Real-World Stories

Industry-Specific Examples of AI Implementation

Business Outcomes and Lessons Learned

Chapter 8: Looking Ahead Towards Future Trends and Opportunities

Implications for Business Strategy and Competitive Advantage

Ethical Considerations and Responsible AI

Role of Generative AI

Chapter 9: Conclusion

The Role of Executives in Driving AI Adoption

The Future of AI in Business

Appendix

Emerging Architecture for LLM App Stack

References

About Unriveted and the Authors, John Sukup & Martin Miller

Chapter 1:

Introduction

The Rise of AI: From Machine

Learning to Generative AI

While AI has recently seen a resurgence in interest; make no mistake, businesses have been seeking efficiencies and competitive advantages from it for years in some form or another (although most of what we called AI in previous years was far from what we’d currently liken it to). This resurgence began fairly recently with Machine Learning (ML), a subfield of AI, that empowers computers to learn autonomously without explicit programming. It’s only recently that ML has stood at the forefront among businesses flexing their muscles in the realm of predictive analytics.

AI, however, encompasses a broader spectrum that includes both ML and its own subfield, Deep Learning (DL), a technique used for developing mathematical models that mimic human intelligence and logical reasoning, a formidable undertaking! It’s from these fields that have given rise to today’s AI technologies: Generative AI (GenAI) and most notably Large Language Models (LLMs) like OpenAI’s GPT-4. These stand at the head of technological innovation in contemporary times.

In the dynamic landscape of technology, news of advancements in these fields permeate daily headlines, reflecting their pervasive influence across diverse businesses and industries. Such rapid progression renders information obsolete swiftly, underscoring the volatile nature of technological evolution. It can also lead to hype, which can hinder progress when expectations are set too high.

Grouping GenAI, LLMs, and ML under the umbrella term AI,