Artificial Intelligence All-In-One for Dummies.

Format:

Book

Author/Creator:

Minnick, Chris.

Contributor:

Mueller, John Paul.

Massaron, Luca.

Diamond, Stephanie.

Baker, Pam.

Stanton, Daniel.

Singh, Shiv.

Mladjenovic, Paul.

Lindsell-Roberts, Sheryl.

Allan, Jeffrey.

Series:

--For dummies.

For dummies

Language:

English

Subjects (All):

Artificial intelligence.

Artificial intelligence--Data processing.

Physical Description:

1 online resource (755 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2025.

Summary:

"Artificial intelligence is everywhere. Major software organizations like Microsoft, Google, and Apple have built AI directly into products and invited the world to become part of the AI revolution. And it's impossible to use these tools to their fullest potential without understanding the basics of what AI is and what it can do"-- Provided by publisher.

Contents:

Intro

Title Page

Copyright Page

Table of Contents

Introduction

About This Book

Foolish Assumptions

Icons Used in This Book

Beyond the Book

Where to Go from Here

Book 1 Understanding AI Foundations

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

Chapter 5 Parsing Machine Learning and Deep Learning

Decoding Machine and Deep Learning

Defining key concepts

Thinking about neural networks

Input layer

Hidden layer

Output layer

Training and testing models

Demystifying Natural-Language Processing

History of NLP

Overcoming the challenges of NLP

Understanding supervised and unsupervised learning

Language generation techniques

Understanding Transformers

Learning to pay attention

Getting tokens

Illuminating Generative AI Models

Recognizing AI's Limitations

Language models are bad at math

Language models are wordy

AI has limited knowledge

AI lacks common sense

AI has accuracy issues

AI has the potential to be biased

Chapter 6 Upholding Responsible AI Standards in GenAI Use

Achieving Originality and Excellence in GenAI-Generated Content

Strategies for ensuring originality in GenAI creations

Maintaining quality standards in GenAI outputs.

Applying Journalism Ethics to GenAI-Generated Content

Following basic journalistic principles

Adhering to truth and integrity in GenAI-assisted reporting

Balancing speed with ethical considerations in GenAI content generation

Joining the Responsible AI Movement

Understanding the goals of the responsible AI movement

Contributing to ethical AI development and use

Aligning with global efforts for responsible AI practices

Chapter 7 Finding Job Security in an AI World

Identifying Tasks That AI Can't Replace

Cultivating emotional intelligence and human interaction

Sparking creative and strategic thinking

Engaging in jobs of the future

Discovering new roles that use AI

Upskilling for AI-Proof Jobs

Translating Your Current Skills into AI-Proof Roles

Analyzing skills transferability

Understanding role evolution and adaptation

Presenting the AI-resilient career journey

Navigating Career Transitions

Adapting to new realities

Shifting professional landscapes

Steering clear of pitfalls

Becoming an Early Adopter

Adopting new technologies

Utilizing AI for thought leadership

Gaining a competitive advantage through innovation

Book 2 Prompting and Generative AI Techniques

Chapter 1 Mapping the Lay of the Generative AI Land

So, What Exactly Is Generative AI?

Understanding parameters

How GenAI uses parameters

Unveiling the BIG Secret to Working Successfully with GenAI

Understanding the Infamous Finger Problem and Other GenAI Quirks

Figuring Out How to Work with GenAI - It's All About Your Prompts

Why GenAI appears so human

Realizing the human influences behind generative AI's abilities

Discovering the Differences in GenAI Models and Options

Checking Out Practical Uses of GenAI

Separating Gen AI Fact from Fiction.

Chapter 2 Introducing the Art of Prompt Engineering

First Things First: What Is a Prompt?

Revealing the Secret Behind Successful Prompting

Discovering the secret sauce in prompt engineering

Understanding how prompts guide GenAI responses

Crafting Effective Prompts for Diverse AI Applications

Tips and Tricks for Optimizing Your Prompts

Using Prompts to Provide Supplemental Data for the Model

Avoiding Common Prompting Pitfalls

Chapter 3 Navigating the Evolving Landscape of GenAI

Identifying Key Players and Evaluating GenAI Providers

Who's who in the GenAI market

Marking the GenAI trailblazers

Watching the AI innovators

The tech titans

Assessing GenAI services and solutions

Getting GenAI that Plays Nice with Other Technologies

Integrating ChatGPT with other software

Bringing in autonomous AI agents

Keeping Up with the Pace of GenAI Advancements

Staying informed on GenAI trends

Follow the leaders

Dive into research papers

Engage with the community

Educational resources

Preparing for the future of generative AI

Upskill continuously

Adopt an agile mindset

Invest in infrastructure

Ethical considerations

Chapter 4 Introducing ChatGPT

Comparing Different Account Versions of ChatGPT

Setting Up an Individual Account

Touring the User Interface

Selecting a GPT Model on the ChatGPT UI

Model options in the drop-down menu

The GPT's latest release

Considering GPT Minis in the GPT Store on the ChatGPT UI

Rendering ChatGPT Outputs to Final Forms

Chapter 5 Getting Started with Microsoft Copilot

Defining Copilot

Overview of Microsoft Copilot

Core functionalities and benefits

Key differentiators from other AI assistants

Understanding how Copilot works

Learning from all the data

Context is key

Integration with Microsoft 365 apps.

Signing Up for Copilot

Installing Copilot

Eligibility criteria

Subscription plans and pricing

Copilot Free

Copilot Pro

Which plan do you need?

Step-by-step sign-up process

Taking Copilot for a Test Flight

Understanding why mine looks different

Prompting and interacting

Chapter 6 Learning Advanced Prompting

Starting at the End: Defining Desired Outputs before Prompting

Managing Data for Targeted Impact on Outputs

Adding Data to Prompts

Using image inputs in ChatGPT prompts

Pictures as prompt input

Random brilliant thoughts as prompt input

Refining with chained prompts

Adding information to memory in ChatGPT

Manipulating memory in ChatGPT

Promoting consistent results

Testing ChatGPT memory

Managing chat history

Changing the Model's Temperature

Changing the Model's Weights

Book 3 Increasing Productivity with AI

Chapter 1 Applying GenAI in Practical Scenarios

GenAI as Writing Assistant

Using GenAI to generate ideas

Drafting content with the help of GenAI

Sprucing up your writing with GenAI

Getting a Visual Assist from GenAI

GenAI in graphic design and visual arts

Generating visual content with AI tools

Harnessing GenAI for even more visual creativity

Problem-Solving with AI in Creative Projects

Chapter 2 Crunching the Numbers with Copilot

Launching Copilot in Excel

Working with Data

Understanding the two kinds of data

Unstructured data

Structured data

Finding free data

Preparing the Data

Converting the data to a table

Adding context to the headers

Formatting data

Changing data types

Sorting data

Cleaning data

Automating Data Analysis

Using Copilot for automated insights

Asking for a specific analysis

Creating Formulas with Copilot's Assistance

Formula creation and troubleshooting.

Advanced formula techniques.

Notes:

"7 books in one!"--Cover.

Includes index.

Description based on publisher supplied metadata and other sources.

ISBN:

1-394-34174-1

OCLC:

1519830175