1 Intuition of artificial intelligence

This chapter covers

  • Definition of AI as we know it
  • Intuition of concepts that are applicable to AI
  • Problem types in computer science and AI, and their properties
  • Overview of the AI algorithms discussed in this book
  • Real-world uses for AI

What is artificial intelligence?

Intelligence is a mystery—a concept that has no agreed-upon definition. Philosophers, psychologists, scientists, and engineers all have different opinions about what it is and how it emerges. We see intelligence in nature around us, such as groups of living creatures working together, and we see intelligence in the way that humans think and behave. In general, things that are autonomous yet adaptive are considered to be intelligent. Autonomous means that something does not need to be provided constant instructions; and adaptive means that it can change its behavior as the environment or problem space changes. When we look at living organisms and machines, we see that the core element for operation is data. Visuals that we see are data; sounds that we hear are data; measurements of the things around us are data. We consume data, process it all, and make decisions based on it; so a fundamental understanding of the concepts surrounding data is important for understanding artificial intelligence (AI) algorithms.

Defining AI

Understanding that data is core to AI algorithms

Viewing algorithms as instructions in recipes

A brief history of artificial intelligence

Problem types and problem-solving paradigms

Search problems: Find a path to a solution

Optimization problems: Find a good solution

Prediction and classification problems: Learn from patterns in data

Clustering problems: Identify patterns in data

Deterministic models: Same result each time it’s calculated

Stochastic/probabilistic models: Potentially different result each time it’s calculated

Intuition of artificial intelligence concepts

Narrow intelligence: Specific-purpose solutions

General intelligence: Humanlike solutions

Super intelligence: The great unknown

Old AI and new AI

Search algorithms

Biology-inspired algorithms

Machine learning algorithms

Deep learning algorithms

Uses for artificial intelligence algorithms

Agriculture: Optimal plant growth

Banking: Fraud detection

Cybersecurity: Attack detection and handling

Health care: Diagnosis of patients

Logistics: Routing and optimization

Telecoms: Optimizing networks

Games: Creating AI agents

Art: Creating masterpieces

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