Table 1 references the Terms defined by MPAI-WMG V1.0. The definition of all MPAI-defined Terms is accessible online.

Table 1 – Terms defined by MPAI-GAM V1.0

Term Definition
Adaptive learning The characteristic of an AI system that can change its behaviour as a result of the  processing of input Data.
AI System A machine able to infer from input Data how to generate outputs relevant to its function.
Data augmentation A technique that increasing the training dataset with new training examples obtained by altering some features of the original training dataset.
Federated learning A machine learning technique that trains algorithms collaboratively keeping the Data in edge devices.
Large Language Model An machine learning technique to train an AI System on extremely large datasets to make it able to understand and generate natural language.
Loss function A function used in training that produces a quantitative assessment of an AI system producing an output.
Machine Learning Techniques that make a system capable of learning how to perform a task from data without explicitly programming it.
Model A component of an AI System that produces outputs by making inferences from inputs.
Natural language processing The processing, analysis, and generation of human language by machine.
Neural Network A set layers of simple processing elements connected by weighted links with adjustable weights.
Prompt Inputs to a generative AI system describing the task the system is requested to perform, such as respond to question.
Reinforcement learning A process that enables a machine to optimise its behaviour in an environment by maximising the advantage earned of its actions.
Small Language Model A Language Model characterised by smaller values of the model’s neural network size, the number of parameters, and the volume of data it is trained on.
Training data Data used for training an AI system, e.g., by determining the weights of a neural network through fitting its learnable parameters.