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Enterprises, as well as individuals, are racing to reap the benefits of Artificial Intelligence (AI). However, in most cases, they are doing so without understanding the technology or its implications and risks, which can be significant. Artificial Intelligence: A Guide for Everyone is a step in addressing that gap by providing information that readers can easily understand at every level.
This book aims to provide useful information to those planning, developing, or using AI, which has the potential to transform industries and shape the future. Whether you are stepping into the world of AI for the first time or are a seasoned professional seeking deeper insights, this comprehensive guide ensures that both beginners and experienced individuals find value within its pages.
Artificial Intelligence: A Guide for Everyone encompasses theoretical as well as practical aspects of AI across various industries and applications. It demystifies AI by explaining, in a language that non-techies can follow, its history, different types, differentiating technologies, and various aspects of implementation. It explains the connection between AI theory and real-world application across diverse industries and how it fuels innovation.
Whether you are a simple business user, a professional, a tech enthusiast, a manager, an executive, or an aspiring AI developer, this guide is your roadmap to navigate the intricacies of AI. The topics covered in this book are comprehensive and diverse. They include its history, benefits, and disadvantages, as well as its relationship and impact on humans.
This guide explains the prerequisites for building, developing, and deploying an AI system. It discusses its key techniques, technologies, and components, such as Machine Learning, natural language processing, and Deep Learning. It explains the process of constructing an AI system, offering insights into problem definition, data preprocessing, model development, evaluation, testing, deployment, and monitoring. In consideration of practical resource limitations and constraints, pre-built, ready-to-use AI solutions, which democratize AI, are discussed.
The journey concludes by categorizing AI based on intelligence levels and functionality, providing a comprehensive understanding of Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), Artificial Super Intelligence (ASI), and other categories.
Introduction
Benefits and Disadvantages
AI–Human Relationship
Requirements
Technologies, Techniques, and Components
Building an AI System
Pre-built AI
Measuring AI Performance
Comparing Measurement Methods
Simulating Intelligence
Traditional Goals of AI Research
Additional Goals of AI Research
Machine Learning
Machine Learning Development Process
AI Development Process
AI Subfields
AI Categories
Categories Based on Functionality