What's the difference between model supervision and model safety in this stack?
Model supervision is about observability: monitoring live performance, tracking behavioral drift, catching bias in production outputs — the equivalent of application performance monitoring, but for model behavior. Model safety is about the guardrails placed around the model's outputs before they reach a user — content filtering, prompt injection defenses, ensuring outputs meet ethical and security bars. Supervision tells you something's wrong; safety is the layer that stops the wrong output from shipping.
Answered in
The Generative AI Tech Stack, Layer by LayerFrom GPU infrastructure to model safety, a working map of the nine layers that turn a foundation model into a shippable GenAI product.
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