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Artificial intelligence · Grades 9–12

Generative models, tokens and useful prompts

An autoregressive language model predicts successive tokens from context. A token may be a word piece, punctuation or another encoded unit.

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Prerequisites

AI basics, reading and structured instructions.

Study notes

Generation

An autoregressive language model predicts successive tokens from context. A token may be a word piece, punctuation or another encoded unit.

Prompting

State the task, relevant context, constraints and desired format. Examples can clarify the task, but they can also bias the response.

Context

The context window is finite and measured in model-specific tokens. Word counts are not a universal token-count conversion.

Checking

Generation can produce plausible unsupported content. Important outputs need verification, and private data should not be included without authorization.

Worked examples

Must one token equal one English word?

Tokenization depends on the vocabulary and encoding.

No

Which prompt is better specified for a study task?

A clear task and evidence boundary are testable.

Summarize the supplied passage in five factual sentences and flag missing evidence

Check your understanding

  1. A toy context budget is 1000 tokens with 700 reserved for input. How many tokens remain for output under that simple shared-budget model?

  2. Does adding a request to be accurate guarantee factual accuracy?

    1. Yes, always
    2. Only if repeated ten times
    3. No
    4. Only in capital letters

  3. Why should example answers be chosen carefully in a prompt?

  4. Rewrite a vague request to make a verifiable summarization task.

Answers and marking guidance

Answers and marking notes
  1. 300

    1000−700=300; actual system budgets must follow their documented rules.

  2. No

    Instructions can help but do not replace verification.

  3. They teach format and task patterns but may introduce bias, unwanted assumptions or misleading examples.

    Credit both benefit and risk.

  4. Specify the source text, audience, length, format, and a rule not to add unsupported claims; ask to identify uncertainty or missing information.

    Credit a concrete task specification rather than one mandatory wording.

Further reading and review references

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