FREE 1Z0-1122-24 TEST QUESTIONS - 1Z0-1122-24 VALID TEST QUESTION

Free 1z0-1122-24 Test Questions - 1z0-1122-24 Valid Test Question

Free 1z0-1122-24 Test Questions - 1z0-1122-24 Valid Test Question

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1z0-1122-24 Valid Test Question | 1z0-1122-24 Relevant Questions

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Oracle 1z0-1122-24 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.
Topic 2
  • Intro to ML Foundations: This section covers Machine Learning (ML) which is a critical area within AI, and understanding its fundamentals is crucial for anyone interested in this field. The section covers delving into the basics of ML allowing for a better grasp of how machines learn from data.
Topic 3
  • Intro to Generative AI & LLMs: This section is about covering generative AI which represents a powerful area of AI that involves creating new content or data. Exploring the overview of Generative AI helps in understanding its potential and applications.
Topic 4
  • Intro to DL Foundations: This section covers Deep Learning (DL) is a subset of ML that focuses on neural networks with many layers, and understanding its core concepts is vital for working with complex models.

Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q36-Q41):

NEW QUESTION # 36
What is the primary benefit of using the OCI Language service for text analysis?

  • A. It provides image processing capabilities.
  • B. It allows for text analysis at scale without machine learning expertise.
  • C. It only works with structured data.
  • D. It requires extensive machine learning expertise to use.

Answer: B

Explanation:
The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre-built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.


NEW QUESTION # 37
What is the purpose of Attention Mechanism in Transformer architecture?

  • A. Break down a sentence into smaller pieces called tokens.
  • B. Weigh the importance of different words within a sequence and understand the context.
  • C. Apply a specific function to each word individually.
  • D. Convert tokens into numerical forms (vectors) that the model can understand.

Answer: B

Explanation:
The purpose of the Attention Mechanism in Transformer architecture is to weigh the importance of different words within a sequence and understand the context. In essence, the attention mechanism allows the model to focus on specific parts of the input sequence when producing an output, which is crucial for understanding context and maintaining coherence over long sequences. It does this by assigning different weights to different words in the sequence, enabling the model to capture relationships between words that are far apart and to emphasize relevant parts of the input when generating predictions.
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NEW QUESTION # 38
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 # 39
What are Convolutional Neural Networks (CNNs) primarily used for?

  • A. Text processing
  • B. Time series prediction
  • C. Image classification
  • D. Image generation

Answer: C

Explanation:
Convolutional Neural Networks (CNNs) are primarily used for image classification and other tasks involving spatial data. CNNs are particularly effective at recognizing patterns in images due to their ability to detect features such as edges, textures, and shapes across multiple layers of convolutional filters. This makes them the model of choice for tasks such as object recognition, image segmentation, and facial recognition.
CNNs are also used in other domains like video analysis and medical image processing, but their primary application remains in image classification.


NEW QUESTION # 40
How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?

  • A. By analyzing sentiment in text documents
  • B. By automating data extraction from documents
  • C. By generating lifelike speech from documents
  • D. By transcribing spoken language

Answer: B

Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service facilitates business processes by automating data extraction from documents. This service leverages machine learning to identify, classify, and extract relevant information from various document types, reducing the need for manual data entry and improving efficiency in document processing workflows. Automation of these tasks enables organizations to streamline operations and reduce errors associated with manual data handling.


NEW QUESTION # 41
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