Mehmet EmrahKonyaTR
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Parameter

Parametre

D1

Learnable model parameters are fitted using training data during training, and model parameters can change while an AI model is being built.

Review status: 2027-02-23

Technical explanation

Training data are used to fit learnable parameters, and those parameters are part of a model used to make inferences from inputs to produce outputs.

Conceptual boundaries

This entry is limited to learnable model parameters; training data are distinct data used to fit them.

Provider-neutral example

During model development, parameters can change before the model is used to derive outputs from inputs.

Limitations

Parameters usually remain fixed after deployment once the model-development phase has concluded, although some systems can later adapt or be retrained.

Related concepts

Atomic claims and evidence

  1. 1.1OECD, Explanatory Memorandum on the Updated OECD Definition of an AI System
    Source
    OECD, Explanatory Memorandum on the Updated OECD Definition of an AI System
    Source role
    Authoritative source
    Exact locator
    AI model parameters during build and deployment, p. 7
    Supported claim
    Learnable model parameters are fitted using training data during training, and model parameters can change while an AI model is being built.
    Last verification
    Review due
    Scope limitation
    Parameters usually remain fixed after deployment once the model-development phase has concluded, although some systems can later adapt or be retrained.
    1.2Regulation (EU) 2024/1689 (Artificial Intelligence Act)
    Source
    Regulation (EU) 2024/1689 (Artificial Intelligence Act)
    Source role
    Authoritative source
    Exact locator
    Article 3(29)
    Supported claim
    Learnable model parameters are fitted using training data during training, and model parameters can change while an AI model is being built.
    Last verification
    Review due
    Scope limitation
    Parameters usually remain fixed after deployment once the model-development phase has concluded, although some systems can later adapt or be retrained.
  2. 2.1Regulation (EU) 2024/1689 (Artificial Intelligence Act)
    Source
    Regulation (EU) 2024/1689 (Artificial Intelligence Act)
    Source role
    Authoritative source
    Exact locator
    Article 3(29)
    Supported claim
    Training data are used for training through fitting an AI system’s learnable parameters.
    Last verification
    Review due
    Scope limitation
    This does not imply that all parameters are learned or that fitting alone establishes performance.