LLM Semantics Explained Through a Night Sky Analogy

A developer compares large language models to galaxies, where prompts act as entry points into vast semantic spaces. Temperature controls token selection, with low temperature yielding predictable outputs and high temperature enabling more creative leaps. The analogy helps developers visualize how LLMs navigate meaning through probability distributions.