
Artificial Intelligence For Dummies
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Dive into the intelligence that powers artificial intelligence
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.
- Learn the basics of AI hardware and software, and how intelligence is created from code
- Get up to date with the latest AI trends and disruptions across industries
- Wrap your mind around what the AI revolution means for humanity, and for you
- Discover tips on using generative AI ethically and effectively
Artificial Intelligence For Dummies is the ideal starting point for anyone seeking a deeper technological understanding of how artificial intelligence works and what promise it holds for the future.
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Persons
John Paul Mueller was a long-time tech author whose credits include previous editions of this book along with Machine Learning For Dummies and Algorithms For Dummies.
Luca Massaron is a data scientist who specializes in organizing big data and transforming it into smart data. He is a Google Developer Expert (GDE) in AI and machine learning.
Stephanie Diamond is a marketing professional and author of or contributor to over two dozen books, including Digital Marketing All-in-One For Dummies and Writing AI Prompts For Dummies.
Content
Introduction 1
Part 1: Introducing AI 5
Chapter 1: Delving into What AI Means 7
Chapter 2: Defining Data's Role In AI 23
Chapter 3: Considering the Use of Algorithms 45
Chapter 4: Pioneering Specialized Hardware 63
Part 2: Understanding How AI Works 79
Chapter 5: Crafting Intelligence for AI Data Analysis 81
Chapter 6: Employing Machine Learning in AI 97
Chapter 7: Improving AI with Deep Learning 117
Part 3: Recognizing How We Interact with AI Every Day 135
Chapter 8: Unleashing Generative AI for Text and Images 137
Chapter 9: Seeing AI Uses in Computer Applications 173
Chapter 10: Automating Common Processes 183
Chapter 11: Relying on AI to Improve Human Interaction. 193
Part 4: AI Applied in Industries 203
Chapter 12: Using AI to Address Medical Needs 205
Chapter 13: Developing Robots 225
Chapter 14: Flying with Drones 239
Chapter 15: Utilizing the AI-Driven Car 257
Part 5: Getting Philosophical About AI 275
Chapter 16: Understanding the Nonstarter Application - Why We Still Need Humans 277
Chapter 17: Engaging in Human Endeavors 291
Chapter 18: Seeing AI in Space 305
Part 6: The Part of Tens 321
Chapter 19: Ten Substantial Contributions of AI to Society 323
Chapter 20: Ten Ways in Which AI Has Failed 331
Index 339
Chapter 1
Delving into What AI Means
IN THIS CHAPTER
Defining AI and its history
Using AI for practical tasks
Seeing through AI hype
Connecting AI with computer technology
Common apps, such as Google Assistant Alexa, and Siri, have all of us who are online every day, using artificial intelligence (AI) without even thinking about it. Productivity and creative apps such as ChatGPT, Synesthesia, and Gemini help us focus on the content rather than on how to get there. The media floods our entire social environment with so much information and disinformation that many people see AI as a kind of magic (which it most certainly isn't). So the best way to start this book is to define what AI is, what it isn't, and how it connects to computers today.
Of course, the basis for what you expect from AI is a combination of how you define AI, the technology you have for implementing AI, and the goals you have for AI. Consequently, everyone sees AI differently. This book takes a middle-of-the-road approach by viewing AI from as many different perspectives as possible. We don't buy into the hype offered by proponents, nor do we indulge in the negativity espoused by detractors. Instead, we strive to give you the best possible view of AI as a technology. As a result, you may find that you have expectations somewhat different from those you encounter in this book, which is fine, but it's essential to consider what the technology can actually do for you - rather than expect something it can't.
Defining the Term AI
Before you can use a term in any meaningful and useful way, you must have a definition for it. After all, if nobody agrees on a meaning, the term has none; it's just a collection of characters. Defining the idiom (a term whose meaning isn't clear from the meanings of its constituent elements) is especially important with technical terms that have received more than a little press coverage at various times and in various ways.
Saying that AI is an artificial intelligence doesn't tell you anything meaningful, which is why people have so many discussions and disagreements over this term. Yes, you can argue that what occurs is artificial, not having come from a natural source. However, the intelligence part is, at best, ambiguous. Even if you don't necessarily agree with the definition of AI as it appears in the sections that follow, this book uses AI according to that definition, and knowing it will help you follow the text more easily.
Discerning intelligence
People define intelligence in many different ways. However, you can say that intelligence involves certain mental activities composed of the following activities:
- Learning: Having the ability to obtain and process new information
- Reasoning: Being able to manipulate information in various ways
- Understanding: Considering the result of information manipulation
- Grasping truths: Determining the validity of the manipulated information
- Seeing relationships: Divining how validated data interacts with other data
- Considering meanings: Applying truths to particular situations in a manner consistent with their relationship
- Separating fact from belief: Determining whether the data is adequately supported by provable sources that can be demonstrated to be consistently valid
The list could easily grow quite long, but even this list is relatively prone to interpretation by anyone who accepts it as viable. As you can see from the list, however, intelligence often follows a process that a computer system can mimic as part of a simulation:
- Set a goal (the information to process and the desired output) based on needs or wants.
- Assess the value of any known information in support of the goal.
- Gather additional information that could support the goal. The emphasis here is on information that could support the goal rather than on information you know will support the goal.
- Manipulate the data such that it achieves a form consistent with existing information.
- Define the relationships and truth values between existing and new information.
- Determine whether the goal is achieved.
- Modify the goal in light of the new data and its effect on the probability of success.
- Repeat Steps 2 through 7 as needed until the goal is achieved (found true) or the possibilities for achieving it are exhausted (found false).
Even though you can create algorithms and provide access to data in support of this process within a computer, a computer's capability to achieve intelligence is severely limited. For example, a computer is incapable of understanding anything because it relies on machine processes to manipulate data using pure math in a strictly mechanical fashion. Likewise, computers can't easily separate truth from mistruth (as described in Chapter 2). In fact, no computer can fully implement any of the mental activities described in the earlier list that describes intelligence.
As part of deciding what intelligence actually involves, categorizing intelligence is also helpful. Humans don't use just one type of intelligence; rather, they rely on multiple intelligences to perform tasks. Howard Gardner a Harvard psychologist has defined a number of these types of intelligence (for details, see the article "Multiple Intelligences" from Project Zero at Harvard University https://pz.harvard.edu/resources/the-theory-of-multiple-intelligences) and knowing them helps you relate them to the kinds of tasks a computer can simulate as intelligence. (See Table 1-1 for a modified version of these intelligences with additional description.)
TABLE 1-1 The Kinds of Human Intelligence and How AIs Simulate Them
Type
Simulation Potential
Human Tools
Description
Bodily kinesthetic
Moderate to High
Specialized equipment and real-life objects
Body movements, such as those used by a surgeon or a dancer, require precision and body awareness. Robots commonly use this kind of intelligence to perform repetitive tasks, often with higher precision than humans, but sometimes with less grace. It's essential to differentiate between human augmentation, such as a surgical device that provides a surgeon with enhanced physical ability, and true independent movement. The former is simply a demonstration of mathematical ability in that it depends on the surgeon for input.
Creative
None
Artistic output, new patterns of thought, inventions, new kinds of musical composition
Creativity is the act of developing a new pattern of thought that results in unique output in the form of art, music, or writing. A truly new kind of product is the result of creativity. An AI can simulate existing patterns of thought and even combine them to create what appears to be a unique presentation but is in reality just a mathematically based version of an existing pattern. In order to create, an AI would need to possess self-awareness, which would require intrapersonal intelligence.
Interpersonal
Low to Moderate
Telephone, audioconferencing, videoconferencing, writing, computer conferencing, email
Interacting with others occurs at several levels. The goal of this form of intelligence is to obtain, exchange, give, or manipulate information based on the experiences of others. Computers can answer basic questions because of keyword input, not because they understand the question. The intelligence occurs while obtaining information, locating suitable keywords, and then giving information based on those keywords. Cross-referencing terms in a lookup table and then acting on the instructions provided by the table demonstrates logical intelligence, not interpersonal intelligence.
Intrapersonal
None
Books, creative materials, diaries, privacy, time
Looking inward to understand one's own interests and then setting goals based on those interests is now a human-only kind of intelligence. As machines, computers have no desires, interests, wants, or creative abilities. An AI processes numeric input using a set of algorithms and provides an output; it isn't aware of anything it does, nor does it understand anything it does.
Linguistic (often divided into oral, aural, and written)
Low
Games, multimedia, books, voice recorders, spoken words
Working with words is an essential tool for communication because spoken and written information exchange is far faster than any other form. This form of intelligence includes understanding oral, aural, and written input, managing the input to develop an answer, and providing an understandable answer as output. Discerning just how capable computers are in this form of intelligence is difficult in light of AIs such as ChatGPT because it's all too easy to create tests where the AI produces nonsense answers.
Logical mathematical
High (potentially higher than...
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