FAST-14

How Large Language Models Work

12 hours · 4 live sessions × 3h · Wadood Chaudhary
Session 1 · From text prediction to transformers · Lesson 10 of 35

Session 1 activities

ACTIVITIES · 27 MIN
Poll

What does the model actually do?

in-class · 3 min · O1

Poll at the start of session 1, then discuss.

When Cape Harbor Inn's (fictional) assistant answers 'What time is check-out?' from its FAQ, what is the model doing at its core?

Sort

More tokens or fewer?

Live or online · 6 min · O1, O3

For each string, guess whether a typical English-trained tokenizer splits it into one token or several. Then check in Lab 1.

Buckets: Likely one tokenLikely several tokens
  1. breakfast
  2. Chatham
  3. 8:15
  4. desayuno incluido
  5. the
0 of 5 sorted
Scenario

Price the FAQ bot

Live or online · 10 min · O3

Branching. The Cape Harbor Inn FAQ is about 1,950 tokens. Each question sends the whole FAQ plus 100 tokens of instructions and question, and gets a 150-token answer. Practice prices: $1.00 per million input tokens, $4.00 per million output.

  1. What is the cost per question?

Reflection

Explain-it-back: tokens and attention

Online · 8 min · O1

After session 1, in pairs, then post.

In three or four sentences a coworker would understand, explain what a token is and what attention lets the model do. Use one Cape Harbor Inn example.

  • Token defined in plain words.
  • Why token counts matter (cost, limits).
  • What attention does with context.
  • One concrete example.
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