← LLMs & Transformers
02 · LLMs & Transformers

What are Parameters?

Parameters are learned numerical values inside an AI model.

What is it?

Parameters are learned numerical values inside an AI model.

Training adjusts these values so the model becomes better at its task. A parameter count describes capacity, not a complete list of facts.

Think of it like...

Think of parameters like millions of tiny settings in a machine. Training adjusts them gradually; inference uses the final settings.

Tiny settings inside a model
Parameters are learned settings, not a list of stored answers.

How it works

Training changes parameters. Inference keeps them fixed while using them to produce a result.

1 · ExampleShow a targetTraining provides an input and expected result.
2 · PredictionTry current settingsThe model produces an output.
3 · CompareMeasure errorThe output is compared with the target.
4 · UpdateAdjust valuesAn optimizer changes many parameters slightly.
5 · InferenceUse the modelThe trained values shape responses to new inputs.

Real-world examples

Language model · Next token

Input: The sky is

System: Parameters score possible continuations

Output: A likely next token such as blue

Image model · Label

Input: A photo

System: Parameters represent learned visual relationships

Output: An object label

Fine-tuning · Style

Input: A writing request

System: Targeted training changes selected values or adapters

Output: More consistent style

What it is NOT

Parameters ≠ Tokens

Parameters: Learned values inside a model

Tokens: Input and output units processed by the model

Parameters ≠ Knowledge database

Parameters: Statistical relationships encoded in values

Knowledge database: Explicit records stored for retrieval

More parameters ≠ Always better

More parameters: Can increase capacity

Always better: Quality also depends on data, training, architecture, and task fit

Remember this

Parameters are learned numerical settings that shape how a model responds.

Independent video · Azure Neural voice

Video

visual explainer
learned values · training · model capacityMP4 · H.264 + AAC
↑