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Valid 1z0-1122-24 Test Notes - High Pass-Rate Latest 1z0-1122-24 Test Camp and Fantastic Mock Oracle Cloud Infrastructure 2024 AI Foundations Associate Exam

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Oracle 1z0-1122-24 Exam Syllabus Topics:

Topic
Details

Topic 1

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 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

Get Started with OCI AI Portfolio: This section is about the OCI AI Portfolio which offers a comprehensive suite of services and infrastructure for developing and deploying AI models. Exploring the overview of OCI AI Services provides insight into the tools available for AI development.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q42-Q47):

NEW QUESTION # 42
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

A. They are free of charge for all users.
B. They allow access to unlimited database resources.
C. They provide faster internet connection speeds.
D. They provide high performance compute resources for fine-tuning tasks.

Answer: D

Explanation:
The primary advantage of using dedicated AI clusters in the Oracle Cloud Infrastructure (OCI) Generative AI service is the provision of high-performance compute resources that are specifically optimized for fine-tuning tasks. Fine-tuning is a critical step in the process of adapting pre-trained models to specific tasks, and it requires significant computational power. Dedicated AI clusters in OCI are designed to deliver the necessary performance and scalability to handle the intense workloads associated with fine-tuning large language models (LLMs) and other AI models, ensuring faster processing and more efficient training.

NEW QUESTION # 43
In machine learning, what does the term "model training" mean?

A. Establishing a relationship between input features and output
B. Writing code for the entire program
C. Analyzing the accuracy of a trained model
D. Performing data analysis on collected and labeled data

Answer: A

Explanation:
In machine learning, "model training" refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.

NEW QUESTION # 44
You are working on a multilingual public announcement system. Which AI task will you use to implement it?

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

Answer: B

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 # 45
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Generation models
B. Embedding 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 # 46
Which feature of OCI Speech helps make transcriptions easier to read and understand?

A. Audio tuning
B. Profanity filtering
C. Timestamping
D. Text normalization

Answer: D

Explanation:
The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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NEW QUESTION # 47
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