HOT 1z0-1122-24 Test Questions Answers: Oracle Cloud Infrastructure 2024 AI Foundations Associate - Trustable Oracle 1z0-1122-24 New Practice Materials

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Oracle 1z0-1122-24 Exam Syllabus Topics:

Topic	Details
Topic 1	Intro to AI Foundations: This section covers the fundamentals of AI are essential for understanding its wide-ranging impact and applications.
Topic 2	Intro to Generative AI & LLMs: This section is about covering generative AI which represents a powerful area of AI that involves creating new content or data. Exploring the overview of Generative AI helps in understanding its potential and applications.
Topic 3	Get Started with OCI AI Portfolio: This section is about the OCI AI Portfolio which offers a comprehensive suite of services and infrastructure for developing and deploying AI models. Exploring the overview of OCI AI Services provides insight into the tools available for AI development.
Topic 4	Intro to ML Foundations: This section covers Machine Learning (ML) which is a critical area within AI, and understanding its fundamentals is crucial for anyone interested in this field. The section covers delving into the basics of ML allowing for a better grasp of how machines learn from data.
Topic 5	Intro to DL Foundations: This section covers Deep Learning (DL) is a subset of ML that focuses on neural networks with many layers, and understanding its core concepts is vital for working with complex models.
Topic 6	OCI Generative AI and Oracle 23ai: This section covers CI Generative AI Services that are a key component of Oracle's AI offerings, and exploring these services provides a clear understanding of how Oracle supports generative AI applications.

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q41-Q46):

NEW QUESTION # 41
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

A. They disregard model size and prioritize high-quality data only.
B. They prioritize larger model sizes to achieve better performance.
C. They focus on increasing the number of tokens while keeping the model size constant.
D. They ensure that the model size, training time, and data size are balanced for optimal results.

Answer: D

Explanation:
Large Language Models (LLMs) handle the trade-off between model size, data quality, data size, and performance by balancing these factors to achieve optimal results. Larger models typically provide better performance due to their increased capacity to learn from data; however, this comes with higher computational costs and longer training times. To manage this trade-off effectively, LLMs are designed to balance the size of the model with the quality and quantity of data used during training, and the amount of time dedicated to training. This balanced approach ensures that the models achieve high performance without unnecessary resource expenditure.

NEW QUESTION # 42
What key objective does machine learning strive to achieve?

A. Creating algorithms to solve complex problems
B. Improving computer hardware
C. Explicitly programming computers
D. Enabling computers to learn and improve from experience

Answer: D

Explanation:
The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task. As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.

NEW QUESTION # 43
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

A. Natural Language Processing
B. Natural Language Processing
C. Computer Vision
D. Anomaly Detection

Answer: B

Explanation:
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.

NEW QUESTION # 44
In machine learning, what does the term "model training" mean?

A. Establishing a relationship between input features and output
B. Performing data analysis on collected and labeled data
C. Analyzing the accuracy of a trained model
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 # 45
Which feature of OCI Speech helps make transcriptions easier to read and understand?

A. Text normalization
B. Profanity filtering
C. Audio tuning
D. Timestamping

Answer: A

Explanation:
The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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NEW QUESTION # 46
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HOT 1Z0-1122-24 TEST QUESTIONS ANSWERS: ORACLE CLOUD INFRASTRUCTURE 2024 AI FOUNDATIONS ASSOCIATE - TRUSTABLE ORACLE 1Z0-1122-24 NEW PRACTICE MATERIALS

HOT 1z0-1122-24 Test Questions Answers: Oracle Cloud Infrastructure 2024 AI Foundations Associate - Trustable Oracle 1z0-1122-24 New Practice Materials