Question 1

How does OCI Generative AI contribute to a secure data lifecycle when working with your custom datasets?

Options :

A : Users are responsible for implementing their own data encryption methods.

B : OCI Generative AI automatically encrypts data at rest and in transit by default.

C : Data uploaded to OCI Generative AI becomes publicly accessible for collaboration.

D : Users retain full control over data location and access within the O

Answer: B

Question 2

Which statement describes the difference between "Top k" and "Top p" in selecting the next token in the OCI Generative AI Generation models?

Options :

A : "Top k" and "Top p" both select from the same set of tokens but use different methods to prioritize them based on frequency.

B : "Top k" and "Top p" are identical in their approach to token selection but differ in their application of penalties to tokens.

C : "Top k" selects the next token based on its position in the list of probable tokens, whereas "Top p" selects based on the cumulative probability of the top tokens.

D : "Top k" considers the sum of probabilities of the top tokens, whereas "Top p" selects from the "Top k" tokens sorted by probability.

Answer: C

Question 3

In the context of fine-tuning with OCI Generative AI Service, what is the role of a custom dataset?

Options :

A : It defines the new tasks the model should be able to perform.

B : It provides additional training data specific to your domain.

C : It acts as a validation set to evaluate the fine-tuned model-s performance.

D : It replaces the pre-trained weights of the base model entirely.

Answer: B

Question 4

Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?

Options :

A : Encoder-decoder

B : Ranker

C : Generator

D : Retriever

Answer: B

Question 5

How can fine-tuning an LLM model with OCI Generative AI contribute to improved performance of semantic search in your application?

Options :

A : By enabling the LLM to directly generate documents based on semantic similarity.

B : By allowing the LLM to interpret the retrieved documents and provide more context-aware responses.

C : By improving the accuracy of vector representations generated for the documents in the database.

D : By optimizing the search algorithms used by the vector database for specific LLM tasks.

Answer: B

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