In this chapter
- Defining AI as we know it
- Gaining an intuition of concepts underpinning AI and important terminology
- Defining problem types and approaches to solving them
- Outlining the AI algorithms discussed in this book
- Exploring real-world use cases for AI algorithms
Artificial Intelligence, or AI, has become a foundational tool in modern software engineering. Developers use AI tools to create software, and many software applications now take advantage of content generated by large language models (LLMs), agents, and other AI-powered features. A new generation of easy-to-use tools, frameworks, and APIs offering quick access to sophisticated models makes it easier than ever to use AI without really understanding how it works. As a technology professional, though, it pays to have an idea what’s going on inside the AI black box.
In this book, we’ll discuss how different types of AI work as we explore the basic structures of their implementations. As we go, we’ll trace the evolution of algorithmic intelligence, moving from the explicit logic of search and evolutionary algorithms through the statistical principles of machine learning and finally into the complex architectures of deep learning and generative AI. I hope that as you start to “grok” AI, you’ll be better equipped to reason about, implement, and innovate with the systems that are reshaping the world. Now let’s crack open the black box!