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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q19-Q24):

NEW QUESTION # 19
Why is normalization of vectors important before indexing in a hybrid search system?

A. It standardizes vector lengths for meaningful comparison using metrics such as Cosine Similarity.
B. It ensures that all vectors represent keywords only.
C. It significantly reduces the size of the database.
D. It converts all sparse vectors to dense vectors.

Answer: A

NEW QUESTION # 20
Which role docs a "model end point" serve in the inference workflow of the OCI Generative AI service?

A. Serves as a designated point for user requests and model responses
B. Updates the weights of the base model during the fine-tuning process
C. Evaluates the performance metrics of the custom model
D. Hosts the training data for fine-tuning custom model

Answer: D

NEW QUESTION # 21
Which statement best describes the role of encoder and decoder models in natural language processing?

A. Encoder models convert a sequence of words into a vector representation, and decoder models take this vector representation to sequence of words.
B. Encoder models take a sequence of words and predict the next word in the sequence, whereas decoder models convert a sequence of words into a numerical representation.
C. Encoder models and decoder models both convert sequence* of words into vector representations without generating new text.
D. Encoder models are used only for numerical calculations, whereas decoder models are used to interpret the calculated numerical values back into text.

Answer: A

NEW QUESTION # 22
How does the Retrieval-Augmented Generation (RAG) Token technique differ from RAG Sequence when generating a model's response?

A. RAG Token retrieves documents oar/at the beginning of the response generation and uses those for the entire content
B. Unlike RAG Sequence, RAG Token generates the entire response at once without considering individual parts.
C. RAG Token does not use document retrieval but generates responses based on pre-existing knowledge only.
D. RAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally.

Answer: A

NEW QUESTION # 23
Which technique involves prompting the Large Language Model (LLM) to emit intermediate reasoning steps as part of its response?

A. Chain-of-Through
B. Least to most Prompting
C. Step-Bock Prompting
D. In context Learning

Answer: A

NEW QUESTION # 24
......

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1Z0-1127-24 UPDATED CBT | 1Z0-1127-24 RELIABLE EXAM TUTORIAL

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