# Inside the Machine

Source: https://dinand.com/reading-notes/inside-the-machine/
Author: Dinand Tinholt

Inside the Machine

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Chapter 1 of 13

## Chapters

Pick any chapter to jump in. The film plays straight through from there.

## Words you will hear

A short glossary for the terms the narrator uses.

token: A chunk of text the model reads as one unit. In English one token averages about three quarters of a word.

embedding: The long list of numbers that places a token in a space where words with related meanings sit close together.

attention: The step where each token weighs every other token in the passage to work out what it means here.

context window: Everything the model can see while it writes, your question and the earlier conversation included.

temperature: A setting for how much chance goes into picking the next token. Turn it down for predictable answers.

RLHF: Reinforcement learning from human feedback. People compare two answers and the model learns to prefer the kind they pick.

test-time compute: Extra tokens a model spends thinking before it answers. Harder problems tend to reward more of them.

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Site guide for AI agents: https://dinand.com/llms.txt