2025 1Z0-1122-25: ORACLE CLOUD INFRASTRUCTURE 2025 AI FOUNDATIONS ASSOCIATE–TRUSTABLE PASS4SURE EXAM PREP

2025 1Z0-1122-25: Oracle Cloud Infrastructure 2025 AI Foundations Associate–Trustable Pass4sure Exam Prep

2025 1Z0-1122-25: Oracle Cloud Infrastructure 2025 AI Foundations Associate–Trustable Pass4sure Exam Prep

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The 1Z0-1122-25 PDF Questions of PracticeVCE are authentic and real. These Oracle Cloud Infrastructure 2025 AI Foundations Associate (1Z0-1122-25) exam questions help applicants prepare well prior to entering the actual Oracle Cloud Infrastructure 2025 AI Foundations Associate (1Z0-1122-25) exam center. Due to our actual 1Z0-1122-25 Exam Dumps, our valued customers always pass their Oracle 1Z0-1122-25 exam on the very first try hence, saving their precious time and money too.

Oracle 1Z0-1122-25 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Get started with OCI AI Portfolio: This section measures the proficiency of Cloud AI Specialists in exploring Oracle Cloud Infrastructure (OCI) AI services. It provides an overview of OCI AI and machine learning services, details AI infrastructure capabilities and explains responsible AI principles to ensure ethical and transparent AI development.
Topic 2
  • Intro to ML Foundations: This section evaluates the knowledge of Machine Learning Engineers in understanding machine learning principles and methodologies. It explores the basics of supervised learning, focusing on regression and classification techniques, along with unsupervised learning methods such as clustering and anomaly detection. It also introduces reinforcement learning fundamentals, helping professionals grasp the different approaches used to train AI models.
Topic 3
  • Intro to OCI AI Services: This section tests the expertise of AI Solutions Engineers in working with OCI AI services and related APIs. It provides insights into key AI services such as language processing, computer vision, document understanding, and speech recognition, allowing professionals to leverage Oracle’s AI ecosystem for building intelligent applications.

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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q12-Q17):

NEW QUESTION # 12
How does AI enhance human efforts?

  • A. By completely replacing human workers in all tasks
  • B. By increasing the physical strength of humans
  • C. By processing data at a speed and effectiveness far beyond human capability
  • D. By deleting data humans need to handle

Answer: C

Explanation:
AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI's ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.


NEW QUESTION # 13
What is the benefit of using embedding models in OCI Generative AI service?

  • A. They optimize the use of computational resources.
  • B. They simplify managing databases.
  • C. They enable creating detailed graphics.
  • 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 # 14
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

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

Answer: C

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

  • A. Translation models
  • B. Generation models
  • C. Embedding models
  • D. Chat 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 # 16
What does "fine-tuning" refer to in the context of OCI Generative AI service?

  • A. Adjusting the model parameters to improve accuracy
  • B. Doubling the neural network layers
  • C. Encrypting the data for security reasons
  • D. Upgrading the hardware of the AI clusters

Answer: A

Explanation:
Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.


NEW QUESTION # 17
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