Should you Observe ML Metrics or Inferences?
From Safe and Sound AI by Fiddler AI
February 12, 2025 · 13 min · Episode 2
About this episode
This episode explores two key approaches for monitoring AI models: metrics and inference observation, discussing their trade-offs and real-world examples.
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.
Topics covered
- AI monitoring
- machine learning metrics
- inference observation
- responsible AI
- model monitoring strategies
Keywords
- AI observability
- model monitoring
- metrics
- inference
- responsible AI development
Mentioned in this episode
Organizations: Fiddler AI
More episodes of Safe and Sound AI
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- Industry’s Fastest Guardrails Now Native to NVIDIA NeMo · April 2, 2025 · 10 min
- Introducing Fiddler Guardrails: The Fastest in the Industry · February 27, 2025 · 7 min
- Tracking Drift to Monitor LLM Performance · December 12, 2024 · 12 min
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