01 / The Model
Parameters
The numbers inside the model, usually billions of them, set during training. Everything the model knows lives here, in a form nobody can read or audit directly. Also called weights.
How you’ll hear it
“Is this one bigger?”
“More parameters, yes. That does not make it better for our task.”
Avoid
Treating parameter count as a quality score. Size is one input among many.
The longer version
Parameters are the adjustable numbers inside a model, fixed during training. More of them can hold more patterns, but a smaller model trained well, or pointed at the right material, often beats a larger one on a specific job and costs far less to run.