In this episode, we explore two key approaches for monitoring AI models: metrics and inference observation. We break down their trade-offs and provide real-world examples from various industries to illustrate the advantages of each model monitoring strategy for driving responsible AI development. 
Read the article by Fiddler AI and explore additional resources for more information on how AI observability can help developers build trust into AI services.

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