GET UPDATED ORACLE 1Z0-1122-24 DUMPS FOR GUARANTEED SUCCESS

Get Updated Oracle 1z0-1122-24 Dumps For Guaranteed Success

Get Updated Oracle 1z0-1122-24 Dumps For Guaranteed Success

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Applicants of the 1z0-1122-24 test who invest the time, effort, and preparation with updated 1z0-1122-24 questions eventually get success. Without the latest Oracle Cloud Infrastructure 2024 AI Foundations Associate (1z0-1122-24) exam dumps, candidates fail the test and waste their time and money. As a result, preparing with actual 1z0-1122-24 Questions is essential to clear the test.

Oracle 1z0-1122-24 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.
Topic 3
  • OCI Generative AI and Oracle 23ai: This section covers CI Generative AI Services that are a key component of Oracle's AI offerings, and exploring these services provides a clear understanding of how Oracle supports generative AI applications.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q37-Q42):

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

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

Answer: A

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
What is the purpose of the model catalog in OCI Data Science?

  • A. To store, track, share, and manage models
  • B. To deploy models as HTTP endpoints
  • C. To provide a preinstalled open source library
  • D. To create and switch between different environments

Answer: A

Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.


NEW QUESTION # 39
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

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

Answer: B

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 # 40
You are working on a multilingual public announcement system. Which AI task will you use to implement it?

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

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 # 41
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

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

Answer: A

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 # 42
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