// MODEL OPTIMIZATION AND PROMPT SYNTAX TERM
Ground Truth
The actual, correct answer or value that a machine learning model is trying to predict or classify, used to train and evaluate the model.
TECHNICAL DEFINITION
Ground Truth refers to the verifiable, accurate data or labels used as the objective standard for training supervised machine learning models and assessing their predictive performance against real-world observations.
BACKGROUND
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence systems. It encompasses AI alignment, monitoring AI systems for risks, and enhancing their robustness. The field is particularly concerned with existential risks posed by advanced AI models.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- True Label
- Actual Value
- Reference Data
- Gold Standard
- Target Variable
USAGE NOTE
Essential for supervised learning, where models learn from labeled examples and are validated against these known correct outputs.