1Z0-1122-24 EXAM CERTIFICATION - VALID 1Z0-1122-24 EXAM GUIDE

1z0-1122-24 Exam Certification - Valid 1z0-1122-24 Exam Guide

1z0-1122-24 Exam Certification - Valid 1z0-1122-24 Exam Guide

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Valid Exam Guide & 1z0-1122-24 Free Pdf Vce & Oracle Cloud Infrastructure 2024 AI Foundations Associate Latest Practice Questions

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q15-Q20):

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

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

Answer: C

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

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

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 # 17
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?

  • A. Speech
  • B. Vision
  • C. Document Understanding
  • D. Language

Answer: A

Explanation:
For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the "Speech" service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.


NEW QUESTION # 18
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

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

Answer: C

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 # 19
You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

  • A. Multi-Class Classification
  • B. Binary Classification
  • C. Clustering
  • D. Regression

Answer: A

Explanation:
In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.


NEW QUESTION # 20
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