Glossary

The glossary explains the most important terms relating to artificial intelligence - briefly, clearly and to the point.

A

B

Bias	Distortions that can arise from unrepresentative or biased data in AI models.

D

Data set	A collection of data used to train or test AI models.
Deep learning	Specialized area of machine learning based on deep neural networks.

M

Machine Learning

Sub-area of AI in which algorithms learn from data.

N

Natural Language Processing	AI field that deals with the processing and analysis of natural language.
Neural network	Model inspired by the human brain, which is used for data processing.

O

Overfitting

Problem where a model fits the training data too accurately but performs poorly on new data.

P

Prompt

An input or instruction given to an AI model such as ChatGPT to obtain a desired response. Can consist of text, questions, commands or context and controls how the AI responds or what information it provides.

S

Speech-to-Text (STT)

Refers to the technology that converts spoken language into written text. It is used, for example, in speech recognition systems, digital assistants or transcription services.

T

Text Simplification	Refers to the process of converting a complex text into a simpler, easier-to-understand version. Difficult words, long sentences or complex structures are simplified without changing the original content or meaning.
Text-to-Speech (TTS)	Refers to the technology that converts written text into spoken language. It is used, for example, in voice assistants, navigation systems or reading apps.
Training	The process by which an AI model learns from data.

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