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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Objectives
Artificial Intelligence and Machine Learning Fundamentals	- Deep Learning Fundamentals 1. Convolutional and sequence models 2. Neural networks - Artificial Intelligence Concepts 1. AI fundamentals and terminology 2. AI use cases and applications - Machine Learning Fundamentals 1. Supervised and unsupervised learning 2. Machine learning models and architectures
OCI Generative AI and Oracle Database AI Capabilities	- OCI Generative AI 1. Generative AI models and applications 2. OCI Generative AI services - Oracle AI Database 1. Vector database concepts 2. AI capabilities in Oracle Database - AI Application Frameworks 1. Retrieval and AI application concepts 2. Language frameworks
Oracle AI and Machine Learning Services	- OCI Machine Learning Services 1. OCI Data Science and machine learning workflows 2. Machine learning capabilities in OCI - OCI AI Services 1. Document Understanding 2. Speech 3. Language 4. Vision - Oracle AI Stack 1. AI data and machine learning services 2. AI infrastructure
Generative AI and Large Language Models	- Generative AI Fundamentals 1. Generative AI concepts and capabilities 2. Generative AI use cases - Large Language Models 1. Language models and generative AI applications 2. LLM fundamentals

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q17-Q22):

NEW QUESTION # 17
Which AI Ethics principle leads to the Responsible AI requirement of transparency?

A. Prevention of harm
B. Fairness
C. Explicability
D. Respect for human autonomy

Answer: C

Explanation:
Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans.
Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.
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NEW QUESTION # 18
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

A. They provide faster internet connection speeds.
B. They allow access to unlimited database resources.
C. They are free of charge for all users.
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 # 19
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

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

Answer: A

NEW QUESTION # 20
Emma is developing a customer support chatbot for an e-commerce website. The chatbot needs to provide accurate and up-to-date return policies, which change frequently. She initially tries fine-tuning but finds that the model still uses outdated information. Which approach should Emma use instead?

A. Reinforcement Learning
B. Retrieval-Augmented Generation (RAG)
C. Prompt Engineering
D. Zero-shot Prompting

Answer: B

Explanation:
Retrieval-Augmented Generation is the appropriate approach when a chatbot must answer using information that changes frequently. Oracle defines RAG as a technique that retrieves information from specific external data sources and augments an LLM ' s response with that retrieved context, producing grounded answers.
Oracle Docs Oracle further explains that RAG can incorporate information that is more current than the model
' s original training data and that knowledge repositories can be continually updated without retraining the underlying LLM. Oracle Docs Fine-tuning is better suited to adapting model behavior or specialization, not continuously changing factual information. Prompt engineering and zero-shot prompting control how instructions are presented but do not independently supply current return-policy data. Therefore, RAG is the correct solution for providing accurate, current, organization-specific policy responses.

NEW QUESTION # 21
What distinguishes Generative AI from other types of AI?

A. Generative AI involves training models to perform tasks without human intervention.
B. Generative AI focuses on making decisions based on user interactions.
C. Generative AI creates diverse content such as text, audio, and images by learning patterns from existing data.
D. Generative AI uses algorithms to predict outcomes based on past data.

Answer: C

Explanation:
Generative AI is distinct from other types of AI in that it focuses on creating new content by learning patterns from existing data. This includes generating text, images, audio, and other types of media. Unlike AI that primarily analyzes data to make decisions or predictions, Generative AI actively creates new and original outputs. This ability to generate diverse content is a hallmark of Generative AI models like GPT-4, which can produce human-like text, create images, and even compose music based on the patterns they have learned from their training data.

NEW QUESTION # 22
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