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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q35-Q40):

NEW QUESTION # 35
Given the following prompts used with a Large Language Model, classify each as employing the Chain-of- Thought, Least-to-most, or Step-Back prompting technique.
L Calculate the total number of wheels needed for 3 cars. Cars have 4 wheels each. Then, use the total number of wheels to determine how many sets of wheels we can buy with $200 if one set (4 wheels) costs $50.
2. Solve a complex math problem by first identifying the formula needed, and then solve a simpler version of the problem before tackling the full question.
3. To understand the impact of greenhouse gases on climate change, let's start by defining what greenhouse gases are. Next, well explore how they trap heat in the Earths atmosphere.

A. 1:Least-to-most, 2 Chain-of-Thought, 3:Step-Back
B. 1:Step-Back, 2:Chain-of-Thought, 3:Least-to-most
C. 1:Chain-of-Thought ,2:Step-Back, 3:Least-to most
D. 1:Chain-of-throught, 2: Least-to-most, 3:Step-Back

Answer: D

Explanation:
Chain-of-Thought: The first prompt calculates the total number of wheels and then uses that information to determine how many sets of wheels can be bought. This sequential reasoning process aligns with the Chain-of-Thought technique.
Least-to-most: The second prompt solves a complex problem by first identifying the needed formula and then solving a simpler version before tackling the full question. This incremental approach matches the Least-to-most technique.
Step-Back: The third prompt starts by defining greenhouse gases and then explores their impact on climate change, taking a step back to establish foundational knowledge before addressing the main question.
Reference
Research articles on prompting techniques for language models
Documentation on effective use of prompting strategies

NEW QUESTION # 36
How does the Retrieval-Augmented Generation (RAG) Token technique differ from RAG Sequence when generating a model's response?

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

Answer: D

NEW QUESTION # 37
You create a fine-tuning dedicated AI cluster to customize a foundational model with your custom training dat a. How many unit hours arc required for fine-tuning if the cluster is active for 10 hours?

A. 30 unit hours
B. 15 unit hours
C. 40 unit hours
D. 10 unit hours

Answer: D

NEW QUESTION # 38
What does the RAG Sequence model do in the context of generating a response?

A. It modifies the input query before retrieving relevant documents to ensure a diverse response.
B. For each input query, it retrieves a set of relevant documents and considers them together to generate a cohesive response.
C. It retrieves a single relevant document for the entire input query and generates a response based on that alone.
D. It retrieves relevant documents only for the initial part of the query and ignores the rest.

Answer: B

Explanation:
RAG (Retrieval-Augmented Generation) Sequence models combine retrieval-based search with LLM-generated responses, ensuring factually grounded and contextually relevant outputs.
How the RAG Sequence Model Works:
Retrieves multiple documents for an input query.
Uses all retrieved documents collectively to generate a well-informed response.
Ensures the answer is contextually aware and factually accurate.
Why Other Options Are Incorrect:
(A) is incorrect because RAG does not ignore part of the query.
(B) is incorrect because it does not rely on a single document.
(C) is incorrect because RAG does not modify the input query but focuses on retrieval and generation.
🔹 Oracle Generative AI Reference:
Oracle AI implements RAG-based architectures to enhance LLM-generated responses by retrieving and grounding responses in factual data.

NEW QUESTION # 39
Given the following code: chain = prompt |11m

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

Answer: A

NEW QUESTION # 40
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