⚙️ Under the hood
Temperature
A setting for how randomly a model picks the next token. Low = predictable, high = creative and more error-prone.
💭 Imagine …
At low temperature, the chef follows the recipe. At high temperature, they improvise: sometimes brilliant, sometimes strawberries on pizza.
🔎 Example
Low for data extraction, higher for brainstorming.
🎯 Why it matters
Explains why the same question can produce different answers.
🎓 Prefer step by step?
The AI Literacy course: 6 short modules with quizzes, a solid foundation in about 60 minutes.