Free Practice Oracle 1Z0-184-25 Exam Questions 2025

Stay ahead with 100% Free Oracle Database 23ai AI Professional - Early Access 1Z0-184-25 Dumps Practice Questions

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Total 108 Questions | Updated On: Mar 28, 2025

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Question 1

A machine learning team is using IVF indexes in Oracle Database 23ai to find similar images in a large dataset. During testing, they observe that the search results are often incomplete, missing relevant images. They suspect the issue lies in the number of partitions probed. How should they improve the search accuracy?

A : Add the TARGET_ACCURACY clause to the query with a higher value for the accuracy

B : Change the index type to HNSW for better accuracy

C : Increase the VECTOR_MEMORY_SIZE initialization parameter

D : Re-create the index with a higher EFCONSTRUCTION value

Answer: A

Question 2

What is the correct order of steps for building a RAG application using PL/SQL in Oracle Database 23ai?

A : Load ONNX Model, Vectorize Question, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output

B : Load Document, Split Text into Chunks, Load ONNX Model, Create Embeddings, Vectorize Question, Perform Vector Search, Generate Output

C : Vectorize Question, Load ONNX Model, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output

D : Load Document, Load ONNX Model, Split Text into Chunks, Create Embeddings, VectorizeQuestion, Perform Vector Search, Generate Output

Answer: B

Question 3

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

A : VECTOR_DIMENSION_FORMAT

B : VECTOR_CHUNKS

C : VECTOR_NORM

D : VECTOR_EMBEDDING

Answer: A

Question 4

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

A : VECTOR_DIMENSION_FORMAT

B : VECTOR_CHUNKS

C : VECTOR_NORM

D : VECTOR_EMBEDDING

Answer: A

Question 5

How does an application use vector similarity search to retrieve relevant information from a database, and how is this information then integrated into the generation process?

A : Encodes the question and database chunks into vectors, finds the most similar using cosine similarity, and includes them in the LLM prompt

B : Trains a separate LLM on the database and uses it to answer, ignoring the general LLM

C : Converts the question to keywords, searches for matches, and inserts the text into the response

D : Clusters similar text chunks and randomly selects one from the most relevant cluster

Answer: A

Page: 1 / 22

Total 108 Questions | Updated On: Mar 28, 2025

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