Storing Knowledge

In this chapter, you'll dive into the fascinating world of how machines store and understand knowledge. We start by looking at the history of text search techniques that laid the groundwork for today's sophisticated AI systems.

You’ll learn about early methods like word stemming, which simplifies words to their base form; stop word removal, filtering out common, non-essential words; and keyword tagging to categorize content. We'll also explore how PageRank ranks pages based on relationships and how fuzzy search finds matches despite minor differences.

Next, we’ll delve into the concept behind large language models through simple examples and visuals. You'll see how assigning numbers to words makes it easier for computers to handle text data and understand complex relationships between words. We'll cover numerical representations of singular and plural forms, as well as adding context like domestication status to each word.

By the end of this chapter, you’ll have a solid understanding of how machines can store and interpret knowledge in ways that mimic human intelligence. Join us on this journey to unravel the mysteries behind storing knowledge in AI systems!