1Z0-1122-25 EXAM DUMPS PDF | REAL 1Z0-1122-25 EXAM QUESTIONS

1Z0-1122-25 Exam Dumps Pdf | Real 1Z0-1122-25 Exam Questions

1Z0-1122-25 Exam Dumps Pdf | Real 1Z0-1122-25 Exam Questions

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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q10-Q15):

NEW QUESTION # 10
In machine learning, what does the term "model training" mean?

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

Answer: B

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 # 11
What is the benefit of using embedding models in OCI Generative AI service?

  • A. They optimize the use of computational resources.
  • B. They enable creating detailed graphics.
  • C. They simplify managing databases.
  • D. They facilitate semantic searches.

Answer: D

Explanation:
Embedding models in the OCI Generative AI service are designed to represent text, phrases, or other data types in a dense vector space, where semantically similar items are located closer to each other. This representation enables more effective semantic searches, where the goal is to retrieve information based on the meaning and context of the query, rather than just exact keyword matches.
The benefit of using embedding models is that they allow for more nuanced and contextually relevant searches. For example, if a user searches for "financial reports," an embedding model can understand that "quarterly earnings" is semantically related, even if the exact phrase does not appear in the document. This capability greatly enhances the accuracy and relevance of search results, making it a powerful tool for handling large and diverse datasets .


NEW QUESTION # 12
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

  • A. It is ideal for tasks such as text-to-speech conversion.
  • B. It provides a cost-effective solution for simple AI tasks.
  • C. It delivers exceptional performance and scalability for complex AI tasks.
  • D. It offers seamless integration with social media platforms.

Answer: C

Explanation:
Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.


NEW QUESTION # 13
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

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

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 # 14
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. Clustering
  • C. Regression
  • D. Binary Classification

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 # 15
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