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Oracle 1z0-1122-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| OCI Generative AI and Oracle Database AI Capabilities | - AI Application Frameworks
|
| Artificial Intelligence and Machine Learning Fundamentals | - Machine Learning Fundamentals
|
| Oracle AI and Machine Learning Services | - Oracle AI Stack
|
| Generative AI and Large Language Models | - Large Language Models
|
Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:
What distinguishes Generative AI from other types of AI?
- A. Generative AI involves training models to perform tasks without human intervention.
- B. Generative AI uses algorithms to predict outcomes based on past data.
- C. Generative AI creates diverse content such as text, audio, and images by learning patterns from existing data.
- D. Generative AI focuses on making decisions based on user interactions.
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Free members. You can sign-up / login (it's free).
Which is NOT a capability of OCI Vision ' s image analysis?
- A. Assigning classification labels to images
- B. Locating and extracting text in images
- C. Translating text in images to another language
- D. Object detection with bounding boxes
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Free members. You can sign-up / login (it's free).
What key objective does machine learning strive to achieve?
- A. Improving computer hardware
- B. Creating algorithms to solve complex problems
- C. Enabling computers to learn and improve from experience
- D. Explicitly programming computers
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Free members. You can sign-up / login (it's free).
Which feature of OCI Speech helps make transcriptions easier to read and understand?
- A. Audio tuning
- B. Timestamping
- C. Text normalization
- D. Profanity filtering
Correct Answer: C 🗳️
Explanation: Only visible for Exam4Free members. You can sign-up / login (it's free).
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?
- A. They ensure that the model size, training time, and data size are balanced for optimal results.
- B. They focus on increasing the number of tokens while keeping the model size constant.
- C. They disregard model size and prioritize high-quality data only.
- D. They prioritize larger model sizes to achieve better performance.
Correct Answer: A 🗳️
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