Edge deployment: Among AI deployment options, which term describes running the AI model directly on local

Running the model on local devices near the data source is edge deployment.

The question

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1. Cloud deployment, running the model on a provider's remote, centrally managed infrastructure accessed over the internet.

   Almost right but opposite: cloud deployment centralizes execution on remote infrastructure, the reverse of running on local devices.
2. Edge deployment, running the model on local devices near the data source instead of in a centralized data center. ✓

   Correct: edge deployment places model execution on local devices close to the data, by definition.
3. On-premise deployment, running the model on servers the organization owns and operates inside its own controlled data center.

   Almost right but distinct: on-premise still centralizes on organizational servers rather than on local devices at the data source.
4. Retrieval-augmented deployment, running the model with an external knowledge store queried to ground each generated response.

   Plausible but wrong: RAG is a grounding technique, not a description of where the model physically runs.

How to remember it

Running the model on local devices near the data source is edge deployment.

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