AI Fundamentals

Tokenization

Tokenization is the process of breaking text into smaller units (tokens) so AI models can process and understand it. Each token can be a character, word, or subword. This process directly affects how AI 'reads' your content.

Why It Matters for AEO

Understanding tokenization helps you optimize content length and structure. AI has limited context windows, so core information should be placed early in content. Chinese content has more tokens per character, meaning AI processes shorter effective content lengths in Chinese.

Practical Examples

  1. 1English 'optimization' might be split into 'optim' + 'ization' as two tokens
  2. 2Each Chinese character is typically an independent token, so Chinese content usually has more tokens
  3. 3GPT-4's context window is 128K tokens, roughly equivalent to 96,000 English words

Related Terms

Large Language Model (LLM)Context WindowNatural Language Processing (NLP)Embedding

FAQ

AC

AEO Strategy Director | SurfIO Founder

Founder of SurfIO

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