FREE PDF QUIZ ORACLE - HIGH-QUALITY 1Z0-1127-25 - VERIFIED ORACLE CLOUD INFRASTRUCTURE 2025 GENERATIVE AI PROFESSIONAL ANSWERS

Free PDF Quiz Oracle - High-quality 1Z0-1127-25 - Verified Oracle Cloud Infrastructure 2025 Generative AI Professional Answers

Free PDF Quiz Oracle - High-quality 1Z0-1127-25 - Verified Oracle Cloud Infrastructure 2025 Generative AI Professional Answers

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Oracle Cloud Infrastructure 2025 Generative AI Professional Sample Questions (Q58-Q63):

NEW QUESTION # 58
How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models (LLMs) fundamentally alter their responses?

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

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation=
RAG integrates vector databases to retrieve real-time external data, augmenting the LLM's pretrained knowledge with current, specific information, shifting response generation to a hybrid approach-Option B is correct. Option A is false-architecture remains neural; only data sourcing changes. Option C is incorrect-pretraining is still required; RAG enhances it. Option D is wrong-RAG improves, not limits, generation. This shift enables more accurate, up-to-date responses.
OCI 2025 Generative AI documentation likely details RAG's impact under responsegeneration enhancements.


NEW QUESTION # 59
What is the function of "Prompts" in the chatbot system?

  • A. They handle the chatbot's memory and recall abilities.
  • B. They are responsible for the underlying mechanics of the chatbot.
  • C. They are used to initiate and guide the chatbot's responses.
  • D. They store the chatbot's linguistic knowledge.

Answer: C

Explanation:
Comprehensive and Detailed In-Depth Explanation=
Prompts in a chatbot system are inputs provided to the LLM to initiate and steer its responses, often including instructions, context, or examples. They shape the chatbot's behavior without altering its core mechanics, making Option B correct. Option A is false, as knowledge is stored in the model's parameters. Option C relates to the model's architecture, not prompts. Option D pertains to memory systems, not prompts directly. Prompts are key for effective interaction.
OCI 2025 Generative AI documentation likely covers prompts under chatbot design or inference sections.


NEW QUESTION # 60
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. Shared among multiple customers for efficiency
  • C. Stored in Key Management service
  • D. Stored in an unencrypted form in Object Storage

Answer: A

Explanation:
Comprehensive and Detailed In-Depth Explanation=
In OCI, fine-tuned models are stored in Object Storage, encrypted by default, ensuring privacy and security per cloud best practices-Option B is correct. Option A (shared) violates privacy. Option C (unencrypted) contradicts security standards. Option D (Key Management) stores keys, not models. Encryption protects customer data.
OCI 2025 Generative AI documentation likely details storage security under fine-tuning workflows.


NEW QUESTION # 61
Which statement is true about string prompt templates and their capability regarding variables?

  • A. They require a minimum of two variables to function properly.
  • B. They support any number of variables, including the possibility of having none.
  • C. They can only support a single variable at a time.
  • D. They are unable to use any variables.

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation=
String prompt templates (e.g., in LangChain) are flexible frameworks that can include zero, one, or multiple variables (placeholders) to customize prompts dynamically. They can be static (no variables) or complex (many variables), making Option C correct. Option A is too restrictive. Option B is false-variables are a core feature. Option D is incorrect, as no minimum is required. This flexibility aids prompt engineering.
OCI 2025 Generative AI documentation likely covers prompt templates under LangChain or prompt design.


NEW QUESTION # 62
How are documents usually evaluated in the simplest form of keyword-based search?

  • A. Based on the number of images and videos contained in the documents
  • B. Based on the presence and frequency of the user-provided keywords
  • C. By the complexity of language used in the documents
  • D. According to the length of the documents

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation=
In basic keyword-based search, documents are evaluated by matching user-provided keywords, with relevance often determined by their presence and frequency (e.g., term frequency in TF-IDF). This makes Option C correct. Option A (language complexity) is unrelated to simple keyword search. Option B (multimedia) isn't considered in text-based keyword methods. Option D (length) may influence scoring indirectly but isn't the primary metric. Keyword search prioritizes exact matches.
OCI 2025 Generative AI documentation likely contrasts keyword search with semantic search under retrieval methods.


NEW QUESTION # 63
......

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