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Oracle Cloud Infrastructure Oracle AI Vector Search Professional

Oracle AI Vector Search Professional

Last Update Jun 15, 2025
Total Questions : 60

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Questions 2

What are the key advantages and considerations of using Retrieval Augmented Generation (RAG) in the context of Oracle AI Vector Search?

Options:

A.  

It excels at optimizing the performance and efficiency of LLM inference through advanced caching and precomputation techniques, leading to faster response times but potentially increasing storage requirements

B.  

It prioritizes real-time data extraction and summarization from various sources to ensure the LLM always has the most up-to-date information

C.  

It focuses on training specialized LLMs within the database environment for specific tasks, offering greater control over model behavior and data privacy but potentially requiring more development effort

D.  

It leverages existing database security and access controls, thereby enabling secure and controlled access to both the database content and the LLM

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Questions 3

Which function should you use to determine the storage format of a vector?

Options:

A.  

VECTOR_DIMENSION_FORMAT

B.  

VECTOR_CHUNKS

C.  

VECTOR_NORM

D.  

VECTOR_EMBEDDING

Discussion 0
Questions 4

You are tasked with creating a table to store vector embeddings with the following characteristics: Each vector must have exactly 512 dimensions, and the dimensions should be stored as 32-bitfloating point numbers. Which SQL statement should you use?

Options:

A.  

CREATE TABLE vectors (id NUMBER, embedding VECTOR(512))

B.  

CREATE TABLE vectors (id NUMBER, embedding VECTOR)

C.  

CREATE TABLE vectors (id NUMBER, embedding VECTOR(*, INT8))

D.  

CREATE TABLE vectors (id NUMBER, embedding VECTOR(512, FLOAT32))

Discussion 0
Questions 5

What is the advantage of using Euclidean Squared Distance rather than Euclidean Distance in similarity search queries?

Options:

A.  

It is the default distance metric for Oracle AI Vector Search

B.  

It supports hierarchical partitioning of vectors

C.  

It is simpler and faster because it avoids square-root calculations

D.  

It guarantees higher accuracy than Euclidean Distance

Discussion 0

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