Online Access Free 1Z0-184-25 Exam Questions

Which parameter is used to define the number of closest vector candidates considered during HNSW index creation?

• A.EFCONSTRUCTION
• B.TARGET_ACCURACY
• C.VECTOR_MEMORY_SIZE
• D.NEIGHBOURS

What is the first step in setting up the practice environment for Select AI?

• A.Create a policy to enable access to OCI Generative AI
• B.Create a new user account with elevated privileges
• C.Optionally create an OCI compartment
• D.Drop any compartment that does not use OCI Generative AI

Which is NOT a feature or capability related to AI and Vector Search in Exadata?

• A.Vector Replication with GoldenGate
• B.Loading Vector Data using SQL*Loader
• C.Native Support for Vector Search Only within the Database Server
• D.AI Smart Scan

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

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

• A.Load Document, Split Text into Chunks, Load ONNX Model, Create Embeddings, Vectorize Question, Perform Vector Search, Generate Output
• B.Load Document, Load ONNX Model, Split Text into Chunks, Create Embeddings, VectorizeQuestion, Perform Vector Search, Generate Output
• C.Load ONNX Model, Vectorize Question, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output
• D.Vectorize Question, Load ONNX Model, Load Document, Split Text into Chunks, Create Embeddings, Perform Vector Search, Generate Output