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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q48-Q53):

NEW QUESTION # 48
What are some use cases for fine-tuning of a model? Note: There are 2 correct answers to this question.

A. To introduce new knowledge to a model in a resource-efficient way
B. To customize outputs for specific types of inputs
C. To quickly create iterations on a new use case
D. To sanitize model outputs

Answer: A,B

NEW QUESTION # 49
What is Machine Learning (ML)?

A. A technology that equips machines with human-like capabilities such as problem-solving, visual perception, and decision-making.
B. A form of Al that only focuses on creating new content, including text, images, sound, and videos.
C. A statistical method for data processing that does not involve any Al techniques.
D. A subset of Al that focuses on enabling computer systems to learn and improve from experience or data.

Answer: D

Explanation:
Machine Learning (ML) is a branch of Artificial Intelligence (AI) that empowers computer systems to learn from data and experiences, enhancing their performance over time without explicit programming for each task.
1. Definition and Core Concept:
* Learning from Data:ML algorithms process and analyze large datasets to identify patterns and make informed decisions or predictions based on new, unseen data.
* Improvement Over Time:Through iterative processes, ML models refine their accuracy and efficiency as they are exposed to more data, leading to continuous performance enhancement.
2. Types of Machine Learning:
* Supervised Learning:Models are trained on labeled datasets, where the desired output is known, to make predictions or classifications.
* Unsupervised Learning:Models work with unlabeled data to identify inherent structures or patterns without predefined outcomes.
* Reinforcement Learning:Systems learn by interacting with an environment, receiving feedback in the form of rewards or penalties, and adjusting actions accordingly.
3. Applications in SAP's AI Solutions:
* SAP AI Core and AI Launchpad:SAP provides a unified framework for managing and deploying ML models, facilitating seamless integration into business processes.
* Generative AI Hub:This platform offers access to a variety of large language models (LLMs) and supports the orchestration of AI tasks, enabling the development of AI-driven applications.

NEW QUESTION # 50
What are some advantages of using agents in training models? Note: There are 2 correct answers to this question.

A. To improve the quality of results
B. To guarantee accurate decision making in complex scenarios
C. To streamline LLM workflows
D. To eliminate the need for human oversight

Answer: A,C

NEW QUESTION # 51
You want to use the orchestration service through SAP's generative-Al-hub-sdk. What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM 11m =
LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})

A. Run the Orchestration Request
B. Define the Template and Default Input Values
C. Define the LLM
D. Create the Orchestration Configuration

Answer: C

Explanation:
The provided code snippet defines a Large Language Model (LLM) within the SAP Generative AI Hub SDK's orchestration service:
from gen_ai_hub.orchestration.models.llm import LLM
llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})
1. Importing the LLM Class:
* Code:from gen_ai_hub.orchestration.models.llm import LLM
* Purpose:Imports the LLM class from the SDK, enabling the creation of an LLM instance.
2. Defining the LLM Instance:
* Code:llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature":
0.2})
* Parameters:
* name:Specifies the model's name, in this case, "gpt-40".
* version:Indicates the model version, set to "latest" to use the most recent version.
* parameters:A dictionary defining model-specific parameters:
* max_tokens:Sets the maximum number of tokens (words or word pieces) the model can generate, here limited to 256 tokens.
* temperature:Controls the randomness of the output; a lower value like 0.2 results in more deterministic responses.
3. Role in Orchestration Pipeline:
* Function:This definition is a crucial step in the orchestration pipeline, specifying which LLM to use and configuring its behavior for subsequent tasks.
Conclusion:
The code snippet defines an LLM named "gpt-40" with specific parameters, preparing it for integration into an AI-driven workflow within SAP's Generative AI Hub.

NEW QUESTION # 52
What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.

A. Executables that define the training process
B. The SAP HANA database for model storage
C. Input datasets stored in a hyperscaler object store
D. Automated deployment to Kubernetes clusters

Answer: A,C

NEW QUESTION # 53
......

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Pass Guaranteed Quiz 2025 SAP Pass-Sure C-AIG-2412: Reliable SAP Certified Associate - SAP Generative AI Developer Cram Materials

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q48-Q53):

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