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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q29-Q34):

                                                  NEW QUESTION # 29
                                                  Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                                  Answer: D

                                                  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 # 30
                                                  What is " in-context learning " in the realm of Large Language Models (LLMs)?

                                                  Answer: B

                                                  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 # 31
                                                  How does AI enhance human efforts?

                                                  Answer: B

                                                  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 # 32
                                                  Which feature of OCI Speech helps make transcriptions easier to read and understand?

                                                  Answer: A

                                                  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 # 33
                                                  Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                                  Answer: D


                                                  NEW QUESTION # 34
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