AI & AEO

Vector Embedding

Quick Definition

A vector embedding is a numerical representation of text (or images, audio) in high-dimensional space, used by AI engines to find semantically similar content for retrieval.

In context

When ChatGPT or Perplexity searches, it converts the query into a vector and finds the chunks of indexed content with the closest vectors. Sites optimized for embedding-based retrieval use clear, focused, semantically rich content rather than keyword-stuffed pages.

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Related terms

Bing Deep Search

Bing Deep Search is Microsoft's enhanced AI-powered search mode that uses GPT-4-class models to expand queries, fetch more sources, and synthesize longer answers than standard Bing.

Zero-Click Search

A zero-click search is when a user gets their answer directly from the SERP — featured snippets, AI Overviews, Knowledge Panel, calculators — without clicking a result.

LLM (Large Language Model)

An LLM is a deep-learning model trained on vast text data, capable of generating human-like language. Examples: GPT-4, Claude, Gemini, Llama.

Perplexity AI

Perplexity is a search engine that uses LLMs to generate answers with inline citations to source pages.

AI Answer Citation

AI answer citation is when an AI-generated answer explicitly attributes information to a source URL, often as inline citations or a sources list.

AIO (AI Optimization)

AIO is an emerging umbrella term covering all forms of optimization for AI surfaces — AI Overviews, ChatGPT search, Perplexity, Claude, Gemini — across both retrieval and citation contexts.

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