VALID 1Z0-1122-25 EXAM FEE | 1Z0-1122-25 TEST PATTERN

Valid 1Z0-1122-25 Exam Fee | 1Z0-1122-25 Test Pattern

Valid 1Z0-1122-25 Exam Fee | 1Z0-1122-25 Test Pattern

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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q14-Q19):

NEW QUESTION # 14
Which capability is supported by the Oracle Cloud Infrastructure Vision service?

  • A. Detecting and preventing fraud in financial transactions
  • B. Detecting vehicle number plates to issue speed citations
  • C. Generating realistic images from text
  • D. Analyzing historical data for unusual patterns

Answer: B

Explanation:
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.


NEW QUESTION # 15
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

  • A. Embedding models
  • B. Generation models
  • C. Chat models
  • D. Translation models

Answer: D

Explanation:
The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service's current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.


NEW QUESTION # 16
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

  • A. Prevention of harm
  • B. Explicability
  • C. Fairness
  • D. Respect for human autonomy

Answer: B

Explanation:
Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans. Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.
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NEW QUESTION # 17
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

  • A. It enhances the visual quality of documents.
  • B. It provides real-time translation of text.
  • C. It converts audio files into text.
  • D. It recognizes and extracts text from a document.

Answer: D

Explanation:
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI's OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.


NEW QUESTION # 18
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

  • A. ML is a subset of AI, and DL is a subset of ML.
  • B. AI, ML, and DL are entirely separate fields with no overlap.
  • C. AI is a subset of DL, which is a subset of ML.
  • D. DL is a subset of AI, and ML is a subset of DL.

Answer: A

Explanation:
Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence "deep").
In this hierarchy:
AI includes all methods to make machines intelligent.
ML refers to the methods within AI that focus on learning from data.
DL is a specialized field within ML that deals with deep neural networks.


NEW QUESTION # 19
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