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Oracle 1z0-1127-24 Exam Syllabus Topics:

Topic	Details
Topic 1	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.
Topic 2	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 3	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.

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Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q52-Q57):

NEW QUESTION # 52
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. RAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally.
C. Unlike RAG Sequence, RAG Token generates the entire response at once without considering individual parts.
D. RAG Token retrieves documents oar/at the beginning of the response generation and uses those for the entire content

Answer: B

Explanation:
The Retrieval-Augmented Generation (RAG) technique enhances the response generation process of language models by incorporating relevant external documents. RAG Token and RAG Sequence are two variations of this technique.
RAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally. This means that during the response generation process, the model continuously retrieves and incorporates information from external documents as it generates each token (or part) of the response. This allows for more dynamic and contextually relevant answers, as the model can adjust its retrieval based on the evolving context of the response.
In contrast, RAG Sequence typically retrieves documents once at the beginning of the response generation and uses those documents to generate the entire response. This approach is less dynamic compared to RAG Token, as it does not adjust the retrieval process during the generation of the response.
Reference
Research articles on Retrieval-Augmented Generation (RAG) techniques
Documentation on advanced language model inference methods

NEW QUESTION # 53
How are fine-tuned customer models stored to enable strong data privacy and security in the OCI Generative AI service?

A. Stored in Object Storage encrypted by default
B. Stored in an unencrypted form in Object Storage
C. Stored in Key Management service
D. Shared among multiple customers for efficiency

Answer: A

NEW QUESTION # 54
What distinguishes the Cohere Embed v3 model from its predecessor in the OCI Generative AI service?

A. Improved retrievals for Retrieval Augmented Generation (RAG) systems
B. Capacity to translate text in over u languages
C. Support for tokenizing longer sentences
D. Emphasis on syntactic clustering of word embedding's

Answer: A

NEW QUESTION # 55
Which role docs a "model end point" serve in the inference workflow of the OCI Generative AI service?

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

Answer: A

NEW QUESTION # 56
An AI development company is working on an advanced AI assistant capable of handling queries in a seamless manner. Their goal is to create an assistant that can analyze images provided by users and generate descriptive text, as well as take text descriptions and produce accurate visual representations. Considering the capabilities, which type of model would the company likely focus on integrating into their AI assistant?

A. A language model that operates on a token-by-token output basis
B. A Retrieval Augmented Generation (RAG) model that uses text as input and output
C. A diffusion model that specializes in producing complex outputs.
D. A Large Language Model based agent that focuses on generating textual responses

Answer: B

NEW QUESTION # 57
......

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1z0-1127-24 Valid Test Guide | 1z0-1127-24 Exam Collection Pdf

Oracle 1z0-1127-24 Exam Syllabus Topics:

1z0-1127-24 Exam Collection Pdf & Latest 1z0-1127-24 Exam Questions Vce

Oracle Cloud Infrastructure 2024 Generative AI Professional Sample Questions (Q52-Q57):

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