Scientific Definition
Generated training data that mimics real data.
Plain-English Definition
Generated training data that mimics real data.
Feynman Explanation
Real data is expensive. Synthetic is fast. Both have their lies.
Core Principle
Generated training data that mimics real data.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Real data is expensive. Synthetic is fast. Both have their lies.
Examples
- Augmentation for rare classes in fraud detection.
- Useful — and risky — pattern for training data scarcity.
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Famous Experiments
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Design Principles
- Test models on real holdout data. Don't trust synthetic for validation.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Test models on real holdout data. Don't trust synthetic for validation.
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Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Underlying data distribution changes over time.
AI system that takes actions to achieve goals, often across tools.
Designing processes from scratch around AI capability.
The relationship between inputs and outputs changes.
How much input the model can process at once.
Vector representation of content for similarity and search.
Evaluation suites that no longer reflect real-world conditions.
Systematic testing of model quality, safety, and capability.
Models learning from examples in the prompt.
How much delay the user experience tolerates.
Train a smaller model to imitate a larger one.
Performance degradation as real-world data shifts.