1Z0-1122-25 Free Vce Dumps | Exam 1Z0-1122-25 Bible
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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q31-Q36):
NEW QUESTION # 31
What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?
- A. Storing the input pixel values
- B. Capturing the internal representation of the raw image data
- C. Providing labels for the output neurons
- D. Directly predicting the final output
Answer: B
Explanation:
In an Artificial Neural Network (ANN) designed for recognizing handwritten digits, the hidden layers serve the crucial function of capturing the internal representation of the raw image data. These layers learn to extract and represent features such as edges, shapes, and textures from the input pixels, which are essential for distinguishing between different digits. By transforming the input data through multiple hidden layers, the network gradually abstracts the raw pixel data into higher-level representations, which are more informative and easier to classify into the correct digit categories.
NEW QUESTION # 32
What is the purpose of the model catalog in OCI Data Science?
- A. To deploy models as HTTP endpoints
- B. To provide a preinstalled open source library
- C. To create and switch between different environments
- D. To store, track, share, and manage models
Answer: D
Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.
NEW QUESTION # 33
What does "fine-tuning" refer to in the context of OCI Generative AI service?
- A. Upgrading the hardware of the AI clusters
- B. Adjusting the model parameters to improve accuracy
- C. Doubling the neural network layers
- 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 # 34
You are working on a multilingual public announcement system. Which AI task will you use to implement it?
- A. Text summarization
- B. Speech recognition
- C. Audio recording
- D. Text to speech
Answer: D
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 # 35
What would you use Oracle AI Vector Search for?
- A. Query data based on keywords.
- B. Manage database security protocols.
- C. Query data based on semantics.
- D. Store business data in a cloud database.
Answer: C
Explanation:
Oracle AI Vector Search is designed to query data based on semantics rather than just keywords. This allows for more nuanced and contextually relevant searches by understanding the meaning behind the words used in a query. Vector search represents data in a high-dimensional vector space, where semantically similar items are placed closer together. This capability makes it particularly powerful for applications such as recommendation systems, natural language processing, and information retrieval where the meaning and context of the data are crucial .
NEW QUESTION # 36
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