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Summary How LLMs Work – Tokenization Explained

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This document explains how large language models (LLMs) process text through tokenization rather than reading words directly. It visually covers key concepts such as subword tokenization, Byte Pair Encoding (BPE), token vocabularies, and why different languages and symbols consume different numbers of tokens. The material is well suited as an introductory overview for students or learners interested in understanding how AI models handle language and how tokenization impacts prompting and costs.

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AI's Secret Language

Why LLM’S doesn't actually read your words.

Understanding the magic of Tokenization.

, Computers speak Math, not English.

To an AI, "Unbelievable" is just a confusing string of 13
letters. Tokenization breaks it into chunks it can actually
calculate.

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Study Level: BTEC
Examinator: AQA
Subject: Artificial intelligence
Unit: Introduction to How LLMS works

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Uploaded on: December 18, 2025
Number of pages: 7
Written in: 2025/2026
Type: SUMMARY

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saikiran1 Ace Engineering College

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Summary How LLMs Work – Tokenization Explained

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