Definition
Evaluation Engineering in the context of AI involves developing and implementing automated systems to rigorously test and measure the performance of AI models, particularly in production environments. This moves beyond manual checks to continuous, systematic assessment.
Why it matters (in Poovi’s context)
Vital for FDEs to ensure the reliability, accuracy, and efficiency of integrated AI models by automatically monitoring key metrics such as retrieval grounding, hallucination rates, and latency on every code change (commit).
Key properties or components
- Automated CI/CD pipelines
- Performance metrics (retrieval grounding, hallucination, latency)
- Continuous monitoring
- Commit-level testing
Contradictions or debates
None.