Step into the universe of AI with our easy-to-understand guide. This introductory segment offers an extensive overview of artificial intelligence, discussing concepts like machine learning and deep learning without inundating you with technical jargon. Unlike conventional AI books grounded in computer science perspectives, our guide views AI as an encompassing term for machine learning and deep learning, paving the way for in-depth discussions in subsequent chapters.
Decoding AI: What Is It, Exactly?
Let’s start by dissecting the term artificial intelligence. The term ‘artificial’ typically implies a synthetic or created substitute, sometimes considered inferior. However, artificial objects can resemble, or even surpass their natural counterparts, primarily due to the absence of maintenance requirements. Understanding ‘intelligence,’ on the other hand, is a more challenging task. Renowned psychologist Robert Sternberg defines it as the ability to learn from experiences, reason effectively, retain important information, and adapt to everyday situations.
Evaluating Intelligence
Determining intelligence is a complex task. While for humans, we tend to gauge intelligence through conversations and interactions, when it comes to animals, it’s their behavior that reveals intelligence. Notable instances include Clever Hans, a horse known for its arithmetical abilities, or ant colonies displaying a collective intelligence far beyond an individual ant’s capability.
Intelligence Beyond Humans
Non-human intelligence is not limited to animals. For instance, dolphins showcase high intelligence metrics like the brain-to-body mass ratio. They demonstrate self-awareness, the ability to remember complex sequences, and even tool use – a trait often associated with human ancestors. The question then arises: can inanimate objects, like computers, possess intelligence?
Artificial Intelligence: The Goal
The ambition of AI is to create systems capable of mirroring human-like thinking or showing traits traditionally associated with human intelligence. The ability to reason, analyze, and formulate ideas is often confused with intelligence. However, intelligence, in essence, refers to efficient and effective thinking. AI aims to bridge this gap between inanimate machines and the concept of intelligence.
Diverging Views: Weak AI vs. Strong AI
The AI world is currently divided into two main schools of thought. The first, known as weak AI, associated with the Massachusetts Institute of Technology (MIT), perceives intelligent behavior in any system as an example of AI. Contrarily, strong AI, linked to Carnegie-Mellon University, insists that intelligent behavior in a system should be based on human-like methodologies. These two contrasting views lead to a fascinating AI spectrum, with potential advancements and discoveries.
In this chapter, we’ve only scratched the surface of AI. As you delve deeper into subsequent chapters, you’ll explore various AI use-cases, early approaches to neural computing, Natural Language Processing (NLP), bioinformatics, and major AI subfields. You will also find sample codes in Java and Python to tackle challenging problems like the Red Donkey and Rubik’s Cube. This guide aims to make the complex world of AI accessible and intriguing for all.
Related Articles
