1 Introducing AI-powered search

The search box has become the default user interface for interacting with data in most modern applications. If you think of every major app or website you use daily, one of the first things you likely do on each visit is make a query to find the content or actions most relevant to you.

Even in scenarios where you are not explicitly searching, you may instead be consuming streams of content customized for your tastes and interests. Whether these be video recommendations, items for purchase, e-mails sorted by priority or recency, news articles, or other content, you are likely still looking at filtered or ranked results and given the option to either page through or explicitly filter the content with your own query.

Although the phrase "search engine" to most people brings up thoughts of a website like Google, Bing, or Baidu that enables queries based upon a crawl of the entire public internet, the reality is that search is now available in nearly all our digital interactions every day across the numerous websites and applications we use.

1.1 What is AI-powered search?

1.2 Understanding User Intent

1.2.1 What do search engines offer?

1.2.2 What do recommendation engines offer?

1.2.3 The Information Retrieval Continuum

1.2.4 Semantic Search and Knowledge Graphs

1.2.5 Understanding the dimensions of user intent

1.3 This book’s audience

1.4 When to consider AI-powered search

1.5 How does AI-powered search work?

1.5.1 The core search foundation

1.5.2 Reflected intelligence through feedback loops

1.5.3 Curated vs. black-box AI

1.5.4 Architecture for an AI-powered search engine

1.6 Summary