AI engineering glossary · MLOps, LLMOps cloud
What is feedback loop?
Feedback loop: A cycle in which a model's outputs influence the data it is later trained on or evaluated with. It can be useful, as when user ratings improve a system, or harmful, when a recommender keeps showing what it already showed and narrows its own data.
Feedback loop: an example
A feed that promotes popular videos gets more clicks on them, so retraining strengthens the same bias.
Related terms
- Delayed labels
- Continuous training
- Model monitoring
- Human feedback collection
More MLOps, LLMOps cloud terms
- FinOps
- GitOps
- Google Cloud Storage
- GPU instance
- Grafana
- Health check
- High availability
- Horizontal Pod Autoscaler
Where you learn it
Feedback loop is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.