A developer wants to swap the embedding model used in an NVIDIA AI Blueprint that implements retrieval-augmented generation. Which structural characteristic of AI Blueprints makes this kind of targeted substitution practical?
- ABlueprints are structured as reference architectures that wire together discrete NIM microservices, so the embedding NIM can be replaced or reconfigured without rewriting the surrounding pipeline. Correct
- BBlueprints package all AI logic as a single compiled binary, so the developer recompiles with a different embedding library flag.
- CBlueprints expose a single REST endpoint that proxies all model calls, so the developer redirects that endpoint to a different embedding service URL.
- DBlueprints rely on a shared CLIP backbone for all retrieval tasks, so the developer fine-tunes the CLIP model to change embedding behaviour.
Why A is correct: An AI Blueprint provides a reference architecture that combines NIM microservices as modular units, meaning any single service such as an embedding model can be swapped independently while the rest of the pipeline remains intact.
Why B is wrong: Blueprints are not compiled monoliths; this misrepresents the composable microservice architecture and confuses it with traditional software packaging.
Why C is wrong: While NIM microservices do expose REST endpoints, the single-proxy description mischaracterises how blueprint components are individually addressed and replaced.
Why D is wrong: CLIP is a vision-language model relevant to multimodal retrieval but is not a universal backbone for all RAG blueprints; this conflates a specific technique with the general blueprint architecture.