Temperature: how creative your AI gets

In machine learning, "temperature" is a dial that controls how creative or predictable a model's output will be.

High temperature = more random, more surprising. Low temperature = more focused, more conservative.

Think of it like asking different family members to write a birthday message for your cousin.

Your abuela will give you the same exact words every time. Reliable, warm, maybe a little repetitive. That's low temperature.

Your younger cousin who just discovered poetry will come back with something wild — a metaphor about a mango, a line about the highway, maybe nothing that makes total sense. That's high temperature.

Both have their place.

When you're building something precise — a legal summary, a product description, a how-to guide — you want low temperature (0.2 to 0.5). You want consistency.

When you're brainstorming, trying to get unstuck, or writing something that needs a spark — 0.7 to 1.0 is where the magic happens.

The trick: you can run the same prompt at different temperatures and compare. See what changes. Sometimes the weird answer is the good one.

Ask yourself before you hit send: do I want the abuela or the poet?