# What is Synthetic Data? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Model Training  
> **Canonical Citation:** [https://spidits.com/ai-glossary/synthetic-data](https://spidits.com/ai-glossary/synthetic-data)

## Definition
Synthetic Data is information that is artificially generated by algorithms or computer simulations, rather than being obtained from real-world measurements, often used to train AI models when real data is scarce or sensitive.

## Architectural Mechanics & Deep Dive
Synthetic data is annotated data generated artificially by computer algorithms or AI models, rather than collected from real-world human observations. As internet text limits are reached, synthetic data (such as model-generated math proofs or simulated images) is used to scale dataset creation, requiring careful quality filters.

## Industry Applications & Real-World Use Cases
Model training datasets, privacy-preserving testing, and robotic physics simulations

## Frequently Asked Questions

### Why use synthetic data to train AI?
It resolves privacy constraints (e.g. healthcare records), allows generation of rare edge cases, and is cheaper than manual data labeling.

### What is the risk of training AI models on synthetic data?
Model Collapse, a decay loop where models trained on AI-generated data forget rare features and slowly drift into generating repetitive, low-diversity junk.

## Related Terminology
- [generative-ai](https://spidits.com/ai-glossary/generative-ai)
- [deep-learning](https://spidits.com/ai-glossary/deep-learning)
- [overfitting](https://spidits.com/ai-glossary/overfitting)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*