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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q53-Q58):

NEW QUESTION # 53
What is the primary purpose of LangSmith Tracing?

A. To analyze the reasoning process of language
B. To generate test cases for language models
C. To debug issues in language model outputs
D. To monitor the performance of language models

Answer: A

NEW QUESTION # 54
Which is a key characteristic of the annotation process used in T-Few fine-tuning?

A. T-Few fine-tuning requires manual annotation of input-output pain.
B. T- Few fine-tuning involves updating the weights of all layers in the model.
C. T-Few fine-tuning relies on unsupervised learning techniques for annotation.
D. T-Few fine-tuning uses annotated data to adjust a fraction of model weights.

Answer: C

NEW QUESTION # 55
In the simplified workflow for managing and querying vector data, what is the role of indexing?

A. To categorize vectors based on their originating data type (text, images, audio)
B. To map vectors to a data structure for faster searching, enabling efficient retrieval
C. To convert vectors into a nonindexed format for easier retrieval
D. To compress vector data for minimized storage usage

Answer: B

Explanation:
Vector indexing plays a crucial role in vector search and retrieval systems, particularly in AI-driven databases. The key functions of vector indexing include:
Efficient Search and Retrieval - Vector indexing structures (such as HNSW, FAISS, or Annoy) help organize vector embeddings to enable fast retrieval of similar vectors.
Mapping to Searchable Data Structures - The process involves creating indexes that efficiently store and map vectors, reducing computational overhead when searching for similar embeddings.
Handling High-Dimensional Data - Since vector embeddings (used in NLP, image recognition, etc.) are often high-dimensional, indexing helps compress and cluster similar vectors, improving retrieval speed.
Used in Vector Databases - Many AI applications, including Oracle's AI-driven database solutions, use indexing techniques for faster similarity searches.
🔹 Oracle Generative AI Reference:
Oracle integrates vector search within its AI and database services, allowing enterprises to efficiently manage and retrieve vectorized data.

NEW QUESTION # 56
When should you use the T-Few fine-tuning method for training a model?

A. For data sets with a few thousand samples or less
B. For complicated semantical undemanding improvement
C. For data sets with hundreds of thousands to millions of samples
D. For models that require their own hosting dedicated Al duster

Answer: C

NEW QUESTION # 57
Given the following code: chain = prompt |11m

A. LCEL is a declarative and preferred way to compose chains together.
B. LCEL is a programming language used to write documentation for LangChain.
C. LCEL is a legacy method for creating chains in LangChain
D. Which statement is true about LangChain Expression language (ICED?

Answer: A

Explanation:
LangChain Expression Language (LCEL) is a declarative language used to compose chains together in LangChain. It allows users to define the flow and interaction of different components in a clear and concise manner. By using LCEL, developers can easily specify how prompts, models, and other elements should interact, making the process of creating and managing chains more straightforward and efficient. This method is preferred due to its readability and ease of use, compared to more imperative or programmatic approaches.
Reference
LangChain documentation on LCEL
Examples and tutorials on using LangChain Expression Language

NEW QUESTION # 58
......

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