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SAP Certified Associate - SAP Generative AI Developer exam collection，C-AIG-2412 actual test

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q52-Q57):

NEW QUESTION # 52
What is the goal of prompt engineering?

A. To develop new neural network architectures for Al models
B. To replace human decision-making with automated processes
C. To craft inputs that guide Al systems in generating desired outputs
D. To optimize hardware performance for Al computations

Answer: C

Explanation:
Prompt engineering involves designing and refining inputs, known as prompts, to effectively guide AI systems, particularly Large Language Models (LLMs), in producing desired outputs.
1. Understanding Prompt Engineering:
* Definition:Prompt engineering is the process of creating and optimizing prompts to elicit specific responses from AI models. It serves as a crucial interface between human intentions and machine- generated content.
* Purpose:The primary goal is to communicate the task requirements clearly to the AI model, ensuring that the generated output aligns with user expectations.
2. Importance in AI Systems:
* Guiding AI Behavior:Well-crafted prompts can direct AI models to perform a wide range of tasks, from answering questions to generating creative content, by setting the context and specifying the desired format of the output.
* Enhancing Output Quality:Effective prompt engineering can improve the relevance, coherence, and accuracy of AI-generated responses, making AI systems more useful and reliable in practical applications.
3. Application in SAP's Generative AI Hub:
* Prompt Management:SAP's Generative AI Hub provides tools for prompt management, allowing developers to create, edit, and manage prompts to interact with various AI models efficiently.
* Exploration and Development:The hub offers features like prompt editors and AI playgrounds, enabling users to experiment with different prompts and models to achieve optimal results for their specific use cases.

NEW QUESTION # 53
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

A. Direct deployment of Al models to SAP HANA.
B. Centralized Al lifecycle management for all Al scenarios.
C. Simplified model retraining and performance improvement.
D. Integration with non-SAP platforms like Azure and AWS.

Answer: B,C

Explanation:
SAP AI Launchpad offers several benefits that enhance the development, deployment, and management of AI models within an organization.
1. Centralized AI Lifecycle Management for All AI Scenarios:
* Unified Platform:SAP AI Launchpad provides a centralized platform to manage the entire AI lifecycle, including model development, training, deployment, monitoring, and maintenance.
* Efficiency:This centralized approach streamlines workflows, reduces complexity, and ensures consistency across various AI projects and scenarios.

NEW QUESTION # 54
Which of the following are features of the SAP AI Foundation?
Note: There are 2 correct answers to this question.

A. Joule integration in SAP SuccessFactors
B. Open source Al model repository
C. Ready-to-use Al services
D. Al runtimes and lifecycle management

Answer: C,D

NEW QUESTION # 55
Which of the following is a benefit of using Retrieval Augmented Generation?

A. It reduces the computational resources required for language modeling.
B. It eliminates the need for fine-tuning LLMs for specific tasks.
C. It enables LLMs to learn new languages without additional training.
D. It allows LLMs to access and utilize information beyond their initial training data.

Answer: D

Explanation:
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by enabling them to access and utilize information beyond their initial training data.
1. Understanding Retrieval-Augmented Generation (RAG):
* Definition:RAG combines the generative capabilities of LLMs with retrieval mechanisms that access external knowledge bases or documents. This integration allows the model to incorporate up-to-date and domain-specific information into its responses.
* Mechanism:When presented with a query, the RAG system retrieves pertinent information from external sources and uses this data to inform and generate a more accurate and contextually appropriate response.
2. Benefits of RAG:
* Access to External Information:RAG allows LLMs to access and utilize information beyond their initial training data, enabling them to provide more accurate and relevant responses.
* Up-to-Date Information:Since RAG systems can query current data sources, they are capable of providing the most recent information available, which is crucial in dynamic fields.
* Improved Accuracy and Relevance:By leveraging external data, RAG enhances theaccuracy and relevance of the generated content, making it particularly useful for tasks requiring detailed or domain- specific information.

NEW QUESTION # 56
How does SAP deal with vulnerability risks created by generative Al? Note: There are 2 correct answers to this question.

A. By implementing responsible Al use guidelines and strong product security standards.
B. By focusing on technological advancement only.
C. By identifying human, technical, and exfiltration risks through an Al Security Taskforce.
D. By relying on external vendors to manage security threats.

Answer: A,C

NEW QUESTION # 57
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