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| Section | Weight | Objectives |
|---|---|---|
| Introduction to OCI AI Services | 20% | - OCI AI Service APIs
|
| OCI Generative AI and Oracle 23ai | 10% | - OCI Generative AI Service features
|
| Machine Learning Foundations | 15% | - Machine Learning fundamentals
|
| AI Foundations | 10% | - Artificial Intelligence basics and terminology
|
| OCI AI Portfolio | 15% | - Overview of OCI AI offerings
|
| Generative AI and Large Language Models | 15% | - Generative AI concepts
|
| Deep Learning Foundations | 15% | - Deep Learning and neural networks
|
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NEW QUESTION # 33
Which is NOT a capability of OCI Vision ' s image analysis?
Answer: B
Explanation:
OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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NEW QUESTION # 34
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?
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 # 35
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?
Answer: D
Explanation:
Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence " deep " ).
In this hierarchy:
* AI includes all methods to make machines intelligent.
* ML refers to the methods within AI that focus on learning from data.
* DL is a specialized field within ML that deals with deep neural networks.
NEW QUESTION # 36
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 # 37
Which feature is NOT supported as part of the OCI Language service ' s pretrained language processing capabilities?
Answer: A
Explanation:
The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.
NEW QUESTION # 38
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