GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #7
GENERATIVE-AI-ENGINEER-ASSOCIATE Question #7: Real Exam Question with Answer & Explanation
The correct answer is C: Pick an embedding model trained on related domain knowledge. For a RAG (Retrieve and Generate) application, the most effective embedding model would be one that is trained on domain-specific knowledge. This ensures that the model is familiar with the context and terminology related to the application, leading to better performance in retri
Question
A Generative AI Engineer is developing a RAG application and would like to experiment with different embedding models to improve the application performance. Which strategy for picking an embedding model should they choose?
Options
- APick an embedding model with multilingual support to support potential multilingual user
- BPick the most recent and most performant open LLM released at the time
- CPick an embedding model trained on related domain knowledge
- DPick the embedding model ranked highest on the Massive Text Embedding Benchmark (MTEB)
Explanation
For a RAG (Retrieve and Generate) application, the most effective embedding model would be one that is trained on domain-specific knowledge. This ensures that the model is familiar with the context and terminology related to the application, leading to better performance in retrieving relevant information and generating accurate responses.
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