Artificial Intelligence for Dummies / John Paul Mueller, Luca Massaron, and Stephanie Diamond.

Format:

Book

Author/Creator:

Mueller, John, 1958- author.

Massaron, Luca, author.

Diamond, Stephanie, author.

Series:

--For dummies.

For dummies

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (371 pages)

Edition:

Third edition.

Place of Publication:

Hoboken, NJ : John Wiley & Sons, Inc., [2025]

Summary:

Artificial intelligence is swiftly moving from a sci-fi future to a modern reality. This edition of Artificial Intelligence For Dummies keeps pace with the lighting-fast expansion of AI tools that are overhauling every corner of reality. This book demystifies how artificial intelligence systems operate, giving you a look at the inner workings of AI and explaining the important role of data in creating intelligence. You'll get a primer on using AI in everyday life, and you'll also get a glimpse into possible AI-driven futures. What's next for humanity in the age of AI? How will your job and your life change as AI continue to evolve? How can you take advantage of AI today to make your live easier? This jargon-free Dummies guide answers all your most pressing questions about the world of artificial intelligence.

Contents:

Intro

Title Page

Copyright Page

Table of Contents

Introduction

About This Book

Icons Used in This Book

Beyond the Book

Where to Go from Here

Part 1 Introducing AI

Chapter 1 Delving into What AI Means

Defining the Term AI

Discerning intelligence

Examining four ways to define AI

Acting humanly

Thinking humanly

Thinking rationally

Acting rationally

Reviewing AI categories

Understanding the History of AI

Considering AI Uses

Avoiding AI Hype and Overestimation

Defining the five tribes and the master algorithm

Considering sources of hype

Managing user overestimation

Connecting AI to the Underlying Computer

Chapter 2 Defining Data's Role In AI

Finding Data Ubiquitous in This Age

Using data everywhere

Putting algorithms into action

Using Data Successfully

Considering the data sources

Obtaining reliable data

Making human input more reliable

Using automated data collection

Collecting data ethically

Manicuring the Data

Dealing with missing data

Considering data misalignments

Separating useful data from other data

Considering the Five Mistruths in Data

Commission

Omission

Perspective

Bias

Frame of reference

Defining the Limits of Data Acquisition

Considering Data Security Issues

Understanding purposefully biased data

Dealing with data-source corruption

Handling botnets

Chapter 3 Considering the Use of Algorithms

Understanding the Role of Algorithms

Examining what an algorithm does

Planning and branching: Trees and nodes

Extending the tree using graph nodes

Traversing the graph

Playing adversarial games

Using local search and heuristics

Discovering the Learning Machine

Leveraging expert systems

MYCIN: A beginning expert system

The components of expert systems.

Introducing machine learning

Achieving new heights

Chapter 4 Pioneering Specialized Hardware

Relying on Standard Hardware

Examining the standard hardware

Describing standard hardware deficiencies

Relying on new computational techniques

Using GPUs

Considering the von Neumann bottleneck

Defining the GPU

Considering why GPUs work well

Working with Deep Learning Processors (DLPs)

Defining the DLP

Using the mobile neural processing unit (NPU)

Accessing the cloud-based tensor processing unit (TPU)

Creating a Specialized Processing Environment

Increasing Hardware Capabilities

Advancing neuromorphic computing

Exploring quantum processors

Adding Specialized Sensors

Integrating AI with Advanced Sensor Technology

Devising Methods to Interact with the Environment

Part 2 Understanding How AI Works

Chapter 5 Crafting Intelligence for AI Data Analysis

Defining Data Analysis

Understanding why analysis is important

Reconsidering the value of data

Defining Machine Learning (ML)

Understanding how ML works

Understanding the benefits of ML

Being useful

being mundane

Specifying the limits of ML

Considering How to Learn from Data

Supervised learning

Unsupervised learning

Reinforcement learning

Chapter 6 Employing Machine Learning in AI

Taking Many Different Roads to Learning

Recognizing five main approaches to AI learning

Symbolic reasoning

Connections modeled on the brain's neurons

Evolutionary algorithms that test variation

Bayesian inference

Systems that learn by analogy

Exploring the three most promising AI learning approaches

Awaiting the next breakthrough

Exploring the Truth in Probabilities

Determining what probabilities can do

Considering prior knowledge

Conditional probability and naïve Bayes.

Considering Bayes' theorem

Envisioning the world as a graph

Growing Trees That Can Classify

Predicting outcomes by splitting data

Making decisions based on trees

Pruning overgrown trees

Chapter 7 Improving AI with Deep Learning

Shaping Neural Networks Similar to the Human Brain

Introducing the neuron

Starting with the miraculous perceptron

Mimicking the Learning Brain

Considering simple neural networks

Figuring out the secret is in the weights

Understanding the role of backpropagation

Introducing Deep Learning

Deep learning versus simpler solutions

Finding even smarter solutions

Using online learning

Using transfer learning

Using open source frameworks

Using end-to-end learning

Detecting Edges and Shapes from Images

Starting with character recognition

Explaining how convolutions work

Advancing using image challenges

Part 3 Recognizing How We Interact with AI Every Day

Chapter 8 Unleashing Generative AI for Text and Images

Getting an Overview of Generative AI

Memorizing sequences that matter

Employing self-attention models

Discovering the Magic Smooth Talk of AI

Creating generative adversarial networks

Revolutionizing art with diffusion models

Applying reinforcement learning

Understanding how reinforcement learning works

Progressing with Google AI and DeepMind discoveries

Understanding reinforcement learning from human feedback

Recapping the recent history of GenAI

Working with Generative AI

Creating text using Generative AI

Creating images using Generative AI

Understanding the Societal Implications of Generative AI

Managing media hype

Promoting positive uses

Addressing security concerns

Attempting to mimic human creativity

Understanding the illusion of creativity

Reviewing human versus machine creativity.

Enhancing human creativity

Defining the side effects

Deciding What Makes a Good Generative AI App

Assessing accuracy and reliability

Enhancing the user experience

Implementing innovation

Monitoring stability and performance

Looking at ethical considerations

Identifying economic considerations

Maximizing ROI potential

Commercializing Generative AI

Viewing the GPT store

Looking at basic app creation techniques

Monetizing your Generative AI app

Addressing the regulatory environment in commercializing Generative AI

Complying with data protection laws

Reviewing intellectual property issues

Navigating sector-specific regulations

Meeting international standards

Chapter 9 Seeing AI Uses in Computer Applications

Introducing Common Application Types

Using AI in typical applications

Realizing AI's wide range of fields

Seeing How AI Makes Applications Friendlier

Performing Corrections Automatically

Considering the kinds of corrections

Seeing the benefits of automatic corrections

Understanding why automated corrections don't always work

Making Suggestions

Getting suggestions based on past actions

Getting suggestions based on groups

Obtaining the wrong suggestions

Considering AI-Based Errors

Chapter 10 Automating Common Processes

Developing Solutions for Boredom

Making tasks more interesting

Helping humans work more efficiently

Examining how AI reduces boredom

Recognizing that AI can't reduce boredom

Working in Industrial Settings

Developing various levels of automation

Using more than just robots

Relying on automation alone

Creating a Safe Environment

Considering the role of boredom in accidents

Seeing AI to avoid safety issues

Accepting that AI cannot eliminate safety issues.

Chapter 11 Relying on AI to Improve Human Interaction

Developing New Ways to Communicate

Creating new alphabets

Working with emojis and other meaningful graphics

Automating language translation

Incorporating body language

Exchanging Ideas

Creating connections

Augmenting communication

Defining trends

Using Multimedia

Embellishing Human Sensory Perception

Shifting data spectrum

Augmenting human senses

Part 4 AI Applied in Industries

Chapter 12 Using AI to Address Medical Needs

Implementing Portable Patient Monitoring

Wearing helpful monitors

Relying on critical wearable monitors

Using movable monitors

Making Humans More Capable

Using games for therapy

Considering the use of exoskeletons

Addressing Special Needs

Considering the software-based solutions

Relying on hardware augmentation

Completing Analysis in New Ways

Relying on Telepresence

Defining telepresence

Considering examples of telepresence

Understanding telepresence limitations

Devising New Surgical Techniques

Making surgical suggestions

Assisting a surgeon

Replacing the surgeon with monitoring

Performing Tasks Using Automation

Working with medical records

Predicting the future

Making procedures safer

Creating better medications

Combining Robots and Medical Professionals

Considering Disruptions AI Causes for Medical Professionals

Chapter 13 Developing Robots

Defining Robot Roles

Overcoming the sci-fi view of robots

Considering robotic laws

Defining actual robot capabilities

Being humanoid can be hard

Creating a robot that walks

Overcoming human reluctance: The uncanny valley

Working with robots

Enhancing economic output

Taking care of you

Providing services

Venturing into dangerous environments.

Understanding the role of specialty robots.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes index.

ISBN:

9781394270729

1394270720

9781394270736

1394270739

OCLC:

1477807235