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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q14-Q19):
NEW QUESTION # 14
What does "fine-tuning" refer to in the context of OCI Generative AI service?
- A. Doubling the neural network layers
- B. Adjusting the model parameters to improve accuracy
- C. Upgrading the hardware of the AI clusters
- D. Encrypting the data for security reasons
Answer: B
Explanation:
Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.
NEW QUESTION # 15
What distinguishes Generative AI from other types of AI?
- A. Generative AI involves training models to perform tasks without human intervention.
- B. Generative AI creates diverse content such as text, audio, and images by learning patterns from existing data.
- C. Generative AI uses algorithms to predict outcomes based on past data.
- D. Generative AI focuses on making decisions based on user interactions.
Answer: B
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 # 16
In machine learning, what does the term "model training" mean?
- A. Establishing a relationship between input features and output
- B. Analyzing the accuracy of a trained model
- C. Performing data analysis on collected and labeled data
- D. Writing code for the entire program
Answer: A
Explanation:
In machine learning, "model training" refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.
NEW QUESTION # 17
What feature of OCI Data Science provides an interactive coding environment for building and training models?
- A. Notebook sessions
- B. Accelerated Data Science (ADS) SDK
- C. Conda environment
- D. Model catalog
Answer: A
Explanation:
In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.
NEW QUESTION # 18
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?
- A. It enhances the visual quality of documents.
- B. It recognizes and extracts text from a document.
- C. It converts audio files into text.
- D. It provides real-time translation of text.
Answer: B
Explanation:
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI's OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.
NEW QUESTION # 19
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