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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: OCI AI Portfolio | 15% | - Overview of OCI AI offerings
|
| Topic 2: Generative AI and Large Language Models | 15% | - Generative AI concepts
|
| Topic 3: AI Foundations | 10% | - Artificial Intelligence basics and terminology
|
| Topic 4: Machine Learning Foundations | 15% | - Machine Learning fundamentals
|
| Topic 5: Deep Learning Foundations | 15% | - Deep Learning and neural networks
|
| Topic 6: Introduction to OCI AI Services | 20% | - OCI AI Service APIs
|
| Topic 7: OCI Generative AI and Oracle 23ai | 10% | - OCI Generative AI Service features
|
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NEW QUESTION # 10
You are working on a multilingual public announcement system. Which AI task will you use to implement it?
Answer: A
Explanation:
For a multilingual public announcement system, the AI task that would be most relevant is " Text to Speech " (TTS). This task involves converting written text into spoken words, which can then be broadcasted over public address systems in multiple languages.
Text to Speech technology is crucial for creating accessible and understandable announcements in different languages, especially in environments like airports, train stations, or public events where clear verbal communication is essential. The TTS system would be configured to support multiple languages, allowing it to deliver announcements to diverse audiences effectively .
NEW QUESTION # 11
Which capability is supported by the Oracle Cloud Infrastructure Vision service?
Answer: C
Explanation:
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.
NEW QUESTION # 12
What distinguishes Generative AI from other types of AI?
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 # 13
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?
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 # 14
Which AI domain can be employed for identifying patterns in images and extract relevant features?
Answer: D
Explanation:
Computer Vision is the AI domain specifically employed for identifying patterns in images and extracting relevant features. This field focuses on enabling machines to interpret and understand visual information from the world, automating tasks that the human visual system can perform, such as recognizing objects, analyzing scenes, and detecting anomalies. Techniques in Computer Vision are widely used in applications ranging from facial recognition and image classification to medical image analysis and autonomous vehicles.
NEW QUESTION # 15
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