nerdexam
Google

GENERATIVE-AI-LEADER · Question #77

A development team is building an internal knowledge base chatbot to answer employee questions about company policies and procedures. This information is stored across various documents in Google…

The correct answer is C. They enable the generative AI model to retrieve the most up-to-date and relevant information from. RAG (Retrieval-Augmented Generation) APIs let a generative model query an external, up-to-date document store-such as Google Cloud Storage-at inference time, so answers always reflect the latest policy documents rather than a fixed training snapshot. This directly solves the…

Implementing Retrieval Augmented Generation (RAG) Solutions

Question

A development team is building an internal knowledge base chatbot to answer employee questions about company policies and procedures. This information is stored across various documents in Google Cloud Storage and is updated regularly by different departments. What is the primary benefit of using Google Cloud's RAG APIs in this scenario?

Options

  • AThey provide a pre-built user interface for the chatbot, simplifying the front-end development
  • BThey allow the development team to train a single foundation model on all company documents.
  • CThey enable the generative AI model to retrieve the most up-to-date and relevant information from
  • DThey automatically create summaries of all company policies, which are then presented to

How the community answered

(33 responses)
  • A
    3% (1)
  • B
    3% (1)
  • C
    88% (29)
  • D
    6% (2)

Explanation

RAG (Retrieval-Augmented Generation) APIs let a generative model query an external, up-to-date document store-such as Google Cloud Storage-at inference time, so answers always reflect the latest policy documents rather than a fixed training snapshot. This directly solves the problem of regularly updated content across departments. Option A is incorrect because RAG APIs are back-end retrieval mechanisms, not UI frameworks. Option B is incorrect because RAG does not retrain the foundation model. Option D is incorrect because RAG retrieves relevant passages for the model to use; it does not pre-generate static summaries.

Topics

#RAG APIs#Generative AI Applications#Knowledge Management#Google Cloud AI

Community Discussion

No community discussion yet for this question.

Full GENERATIVE-AI-LEADER Practice