1Z0-1122-25 PDF DUMPS FILES FOR BUSY PROFESSIONALS

1Z0-1122-25 PDF Dumps Files for Busy Professionals

1Z0-1122-25 PDF Dumps Files for Busy Professionals

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Oracle 1Z0-1122-25 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Get started with OCI AI Portfolio: This section measures the proficiency of Cloud AI Specialists in exploring Oracle Cloud Infrastructure (OCI) AI services. It provides an overview of OCI AI and machine learning services, details AI infrastructure capabilities and explains responsible AI principles to ensure ethical and transparent AI development.
Topic 2
  • Intro to ML Foundations: This section evaluates the knowledge of Machine Learning Engineers in understanding machine learning principles and methodologies. It explores the basics of supervised learning, focusing on regression and classification techniques, along with unsupervised learning methods such as clustering and anomaly detection. It also introduces reinforcement learning fundamentals, helping professionals grasp the different approaches used to train AI models.
Topic 3
  • Intro to OCI AI Services: This section tests the expertise of AI Solutions Engineers in working with OCI AI services and related APIs. It provides insights into key AI services such as language processing, computer vision, document understanding, and speech recognition, allowing professionals to leverage Oracle’s AI ecosystem for building intelligent applications.

Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q40-Q45):

NEW QUESTION # 40
What is "in-context learning" in the realm of Large Language Models (LLMs)?

  • A. Teaching a model through zero-shot learning
  • B. Modifying the behavior of a pretrained LLM permanently
  • C. Providing a few examples of a target task via the input prompt
  • D. Training a model on a diverse range of tasks

Answer: C

Explanation:
"In-context learning" in the realm of Large Language Models (LLMs) refers to the ability of these models to learn and adapt to a specific task by being provided with a few examples of that task within the input prompt. This approach allows the model to understand the desired pattern or structure from the given examples and apply it to generate the correct outputs for new, similar inputs. In-context learning is powerful because it does not require retraining the model; instead, it uses the examples provided within the context of the interaction to guide its behavior.


NEW QUESTION # 41
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

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

Answer: A

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 # 42
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

  • A. Embedding models
  • B. Chat models
  • C. Generation 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 # 43
You are working on a multilingual public announcement system. Which AI task will you use to implement it?

  • A. Speech recognition
  • B. Text summarization
  • C. Text to speech
  • D. Audio recording

Answer: C

Explanation:
For a multilingual public announcement system, the AI task that would be most relevant is "Text to Speech" (TTS). This task involves converting written text into spoken words, which can then be broadcasted over public address systems in multiple languages.
Text to Speech technology is crucial for creating accessible and understandable announcements in different languages, especially in environments like airports, train stations, or public events where clear verbal communication is essential. The TTS system would be configured to support multiple languages, allowing it to deliver announcements to diverse audiences effectively .


NEW QUESTION # 44
What can Oracle Cloud Infrastructure Document Understanding NOT do?

  • A. Classify documents into different types
  • B. Generate transcript from documents
  • C. Extract text from documents
  • D. Extract tables from documents

Answer: B

Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .


NEW QUESTION # 45
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