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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q10-Q15):

NEW QUESTION # 10
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. 15 unit hours
B. 30 unit hours
C. 10 unit hours
D. 40 unit hours

Answer: C

NEW QUESTION # 11
Given a block of code:
qa = Conversational Retrieval Chain, from 11m (11m, retriever-retv, memory-memory) when does a chain typically interact with memory during execution?

A. Before user input and after chain execution
B. After user input but before chain execution, and again after core logic but before output
C. Continuously throughout the entire chain execution process
D. Only after the output has been generated

Answer: D

NEW QUESTION # 12
What does the Loss metric indicate about a model's predictions?

A. Loss describes the accuracy of the right predictions rather than the incorrect ones.
B. Loss is a measure that indicates how wrong the model's predictions are.
C. Loss indicates how good a prediction is, and it should increase as the model improves.
D. Loss measures the total number of predictions made by a model.

Answer: B

Explanation:
In machine learning and AI models, the loss metric quantifies the error between the model's predictions and the actual values.
Definition of Loss:
Loss represents how far off the model's predictions are from the expected output.
The objective of training an AI model is to minimize loss, improving its predictive accuracy.
Loss functions are critical in gradient descent optimization, which updates model parameters.
Types of Loss Functions:
Mean Squared Error (MSE) - Used for regression problems.
Cross-Entropy Loss - Used in classification problems (e.g., NLP tasks).
Hinge Loss - Used in Support Vector Machines (SVMs).
Negative Log-Likelihood (NLL) - Common in probabilistic models.
Clarifying Other Options:
(B) is incorrect because loss does not count the number of predictions.
(C) is incorrect because loss focuses on both right and wrong predictions.
(D) is incorrect because loss should decrease as a model improves, not increase.
🔹 Oracle Generative AI Reference:
Oracle AI platforms implement loss optimization techniques in their training pipelines for LLMs, classification models, and deep learning architectures.

NEW QUESTION # 13
In LangChain, which retriever search type is used to balance between relevancy and diversity?

A. similarity_score_threshold
B. similarity
C. top k
D. mmr

Answer: D

Explanation:
In LangChain, the "mmr" (Maximal Marginal Relevance) search type is used to balance between relevancy and diversity when retrieving documents. This technique aims to select documents that are not only relevant to the query but also diverse from each other. This helps in avoiding redundancy and ensures that the retrieved set of documents covers a broader aspect of the topic.
Maximal Marginal Relevance (MMR) works by iteratively selecting documents that have high relevance to the query but low similarity to the documents already selected. This ensures that each new document adds new information and perspectives, rather than repeating what is already included.
Reference
LangChain documentation on retrievers and search types
Research papers and articles on Maximal Marginal Relevance (MMR)

NEW QUESTION # 14
Given the following code:
Prompt Template
(input_variable[''rhuman_input",'city''], template-template)
Which statement is true about Promt Template in relation to input_variables?

A. PromptTemplate can support only a single variable M a time.
B. PromptTemplate requires a minimum of two variables to function property.
C. PromptTemplate is unable to use any variables.
D. PromptTemplate supports Any number of variable*, including the possibility of having none.

Answer: D

Explanation:
The PromptTemplate in relation to input_variables is designed to be flexible and can support any number of variables, including the possibility of having none. This means that users can define a template with multiple variables or none at all, depending on their specific needs. The PromptTemplate facilitates dynamic prompt creation by inserting variable values into predefined template slots.
Reference
LangChain documentation on PromptTemplate
Examples and tutorials on using PromptTemplate in generative AI applications

NEW QUESTION # 15
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Ian Taylor Ian Taylor

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