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Oracle 1z0-1127-24 Exam Syllabus Topics:

Topic	Details
Topic 1	Building an LLM Application with OCI Generative AI Service: For AI Engineers, this section covers Retrieval Augmented Generation (RAG) concepts, vector database concepts, and semantic search concepts. It also focuses on deploying an LLM, tracing and evaluating an LLM, and building an LLM application with RAG and LangChain.
Topic 2	Using OCI Generative AI Service: For AI Specialists, this section covers dedicated AI clusters for fine-tuning and inference. The topic also focuses on the fundamentals of OCI Generative AI service, foundational models for Generation, Summarization, and Embedding.
Topic 3	Fundamentals of Large Language Models (LLMs): For AI developers and Cloud Architects, this topic discusses LLM architectures and LLM fine-tuning. Additionally, it focuses on prompts for LLMs and fundamentals of code models.

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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q16-Q21):

NEW QUESTION # 16
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 is unable to use any variables.
B. PromptTemplate supports Any number of variable*, including the possibility of having none.
C. PromptTemplate requires a minimum of two variables to function property.
D. PromptTemplate can support only a single variable M a time.

Answer: B

NEW QUESTION # 17
Why is normalization of vectors important before indexing in a hybrid search system?

A. It converts all sparse vectors to dense vectors.
B. It significantly reduces the size of the database.
C. It ensures that all vectors represent keywords only.
D. It standardizes vector lengths for meaningful comparison using metrics such as Cosine Similarity.

Answer: D

NEW QUESTION # 18
How does the architecture of dedicated Al clusters contribute to minimizing GPU memory overhead forT- Few fine-tuned model inference?

A. By sharing base model weights across multiple fine-tuned model's on the same group of GPUs
B. By allocating separate GPUS for each model instance
C. By optimizing GPIJ memory utilization for each model's unique para
D. By loading the entire model into G PU memory for efficient processing

Answer: A

NEW QUESTION # 19
Which role docs a "model end point" serve in the inference workflow of the OCI Generative AI service?

A. Evaluates the performance metrics of the custom model
B. Updates the weights of the base model during the fine-tuning process
C. Hosts the training data for fine-tuning custom model
D. Serves as a designated point for user requests and model responses

Answer: C

NEW QUESTION # 20
How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models(LLMS) fundamentally alter their responses?

A. It transforms their architecture from a neural network to a traditional database system.
B. It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.
C. It limits their ability to understand and generate natural language.
D. It enables them to bypass the need for pretraining on large text corpora.

Answer: B

NEW QUESTION # 21
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Oracle 1z0-1127-24 Exam Syllabus Topics:

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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q16-Q21):

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