Week 3: Behind the Scenes
Day 17: Embeddings and Semantic Search
Goal
Learn how AI can search by meaning, not just keywords.
Learn
Embeddings turn text, images, or other data into numerical vectors. Similar meanings land near each other in vector space. This allows semantic search, recommendation, clustering, and retrieval. Embeddings are often used in knowledge-base chat systems.
Behind the scenes
AI tools are products wrapped around models, data, prompts, retrieval, safety systems, and user interfaces. The better you understand the wrapper, the better your results get.Example
Example: in a real workflow, this idea helps you decide how to use AI carefully. For this lesson, connect the goal to one task you already do: learn how AI can search by meaning, not just keywords..
Practice
Write three different phrasings of the same idea and ask an AI why semantic search might match them.
Checkpoint
Checkpoint
You understand why AI search can find related ideas even without exact words.