Update.

Author: Sherry Yang

learn-pr/wwl-data-ai/get-started-with-generative-ai-and-agents/includes/2-generative-ai-models.md

@@ -88,7 +88,10 @@ A common way you can evaluate is to start in Foundry's model catalog, choose a m
 
 There are various ways to score a model in Foundry portal, including *Natural Language Processing (NLP) metrics* and *AI‑assisted quality metrics*. Examples of classic *NLP quality metrics* are: accuracy, precision, recall, and F1. Examples of *AI‑assisted metrics* include groundedness, relevance, coherence and fluency, and GPT similarity. Choose AI-assisted metrics for qualitative scoring beyond traditional metrics. 
 
-Safety evaluators can be used help ensure responsible AI output. They scan for harmful or unsafe content, bias and unfairness, violence, self‑harm, or protected‑class harms. Foundry's Evaluator Library offers reusable evaluators for quality scoring, safety scanning, and more.
+In Foundry, **evaluators** are components used to measure the quality, safety, and effectiveness of AI model or agent outputs. For example, safety evaluators can be used help ensure responsible AI output. They scan for harmful or unsafe content, bias and unfairness, violence, self‑harm, or protected‑class harms. Foundry's Evaluator Library offers reusable evaluators for quality scoring, safety scanning, and more.
+
+>[!NOTE]
+>On their own, Foundry's evaluators detect, scan, and score issues but do not actively resolve them.  
 
 ## Deploy models in Foundry