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Databricks-Generative-AI-Engineer-Associate Exam Dumps - Databricks Generative AI Engineer Questions and Answers

Question # 14

A team wants to serve a code generation model as an assistant for their software developers. It should support multiple programming languages. Quality is the primary objective.

Which of the Databricks Foundation Model APIs, or models available in the Marketplace, would be the best fit?

Options:

A.

Llama2-70b

B.

BGE-large

C.

MPT-7b

D.

CodeLlama-34B

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Question # 15

A Generative Al Engineer is building a RAG application that answers questions about internal documents for the company SnoPen AI.

The source documents may contain a significant amount of irrelevant content, such as advertisements, sports news, or entertainment news, or content about other companies.

Which approach is advisable when building a RAG application to achieve this goal of filtering irrelevant information?

Options:

A.

Keep all articles because the RAG application needs to understand non-company content to avoid answering questions about them.

B.

Include in the system prompt that any information it sees will be about SnoPenAI, even if no data filtering is performed.

C.

Include in the system prompt that the application is not supposed to answer any questions unrelated to SnoPen Al.

D.

Consolidate all SnoPen AI related documents into a single chunk in the vector database.

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Question # 16

A Generative AI Engineer is building an LLM to generate article summaries in the form of a type of poem, such as a haiku, given the article content. However, the initial output from the LLM does not match the desired tone or style.

Which approach will NOT improve the LLM’s response to achieve the desired response?

Options:

A.

Provide the LLM with a prompt that explicitly instructs it to generate text in the desired tone and style

B.

Use a neutralizer to normalize the tone and style of the underlying documents

C.

Include few-shot examples in the prompt to the LLM

D.

Fine-tune the LLM on a dataset of desired tone and style

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Question # 17

A Generative Al Engineer is creating an LLM-based application. The documents for its retriever have been chunked to a maximum of 512 tokens each. The Generative Al Engineer knows that cost and latency are more important than quality for this application. They have several context length levels to choose from.

Which will fulfill their need?

Options:

A.

context length 514; smallest model is 0.44GB and embedding dimension 768

B.

context length 2048: smallest model is 11GB and embedding dimension 2560

C.

context length 32768: smallest model is 14GB and embedding dimension 4096

D.

context length 512: smallest model is 0.13GB and embedding dimension 384

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Question # 18

A Generative AI Engineer is developing a patient-facing healthcare-focused chatbot. If the patient’s question is not a medical emergency, the chatbot should solicit more information from the patient to pass to the doctor’s office and suggest a few relevant pre-approved medical articles for reading. If the patient’s question is urgent, direct the patient to calling their local emergency services.

Given the following user input:

“I have been experiencing severe headaches and dizziness for the past two days.”

Which response is most appropriate for the chatbot to generate?

Options:

A.

Here are a few relevant articles for your browsing. Let me know if you have questions after reading them.

B.

Please call your local emergency services.

C.

Headaches can be tough. Hope you feel better soon!

D.

Please provide your age, recent activities, and any other symptoms you have noticed along with your headaches and dizziness.

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Question # 19

A Generative AI Engineer is designing a chatbot for a gaming company that aims to engage users on its platform while its users play online video games.

Which metric would help them increase user engagement and retention for their platform?

Options:

A.

Randomness

B.

Diversity of responses

C.

Lack of relevance

D.

Repetition of responses

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Question # 20

A Generative AI Engineer is developing an LLM application that users can use to generate personalized birthday poems based on their names.

Which technique would be most effective in safeguarding the application, given the potential for malicious user inputs?

Options:

A.

Implement a safety filter that detects any harmful inputs and ask the LLM to respond that it is unable to assist

B.

Reduce the time that the users can interact with the LLM

C.

Ask the LLM to remind the user that the input is malicious but continue the conversation with the user

D.

Increase the amount of compute that powers the LLM to process input faster

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Question # 21

A company has a typical RAG-enabled, customer-facing chatbot on its website.

Select the correct sequence of components a user's questions will go through before the final output is returned. Use the diagram above for reference.

Options:

A.

1.embedding model, 2.vector search, 3.context-augmented prompt, 4.response-generating LLM

B.

1.context-augmented prompt, 2.vector search, 3.embedding model, 4.response-generating LLM

C.

1.response-generating LLM, 2.vector search, 3.context-augmented prompt, 4.embedding model

D.

1.response-generating LLM, 2.context-augmented prompt, 3.vector search, 4.embedding model

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Exam Name: Databricks Certified Generative AI Engineer Associate
Last Update: Apr 3, 2025
Questions: 61
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