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

NEW QUESTION # 48
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note: There are 2 correct answers to this question.

A. Prompt editor and management
B. Automatic model selection
C. Develop and debug ABAP code
D. Al playground and chat

Answer: A,D

NEW QUESTION # 49
Which of the following statements accurately describe the RAG process? Note: There are 2 correct ans-wers to this question.

A. The user's questi on is used to search a knowledge base or a set of documents.
B. The LLM directly ans wers the user's question without accessing external information.
C. The retrieved content is combined with the LLM's capabilities to generate a response.
D. The embedding model stores the generated ans wers for future reference.

Answer: A,C

NEW QUESTION # 50
Which technique is used to supply domain-specific knowledge to an LLM?

A. Prompt template expansion
B. Retrieval-Augmented Generation
C. Domain-adaptation training
D. Fine-tuning the model on general data

Answer: B

Explanation:
Retrieval-Augmented Generation (RAG) is a technique that enhances Large Language Models (LLMs) by integrating external domain-specific knowledge, enabling more accurate and contextually relevant outputs.
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. Application in Supplying Domain-Specific Knowledge:
* Domain Adaptation:By leveraging RAG, LLMs can access specialized information without the need for extensive retraining or fine-tuning. This approach is particularly beneficial for domains with rapidly evolving information or where incorporating proprietary data is essential.
* Efficiency:RAG enables models to provide informed responses by referencing external data, reducing the necessity for large-scale domain-specific training datasets and thereby conserving computational resources.
3. Advantages of Using RAG:
* 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.
* Enhanced Accuracy:Incorporating external knowledge allows the model to produce more precise and contextually relevant outputs, especially in specialized domains.

NEW QUESTION # 51
What are some benefits of using an SDK for evaluating prompts within the context of generative Al?
Note: There are 3 correct answers to this question.

A. Maintaining data privacy by using data masking techniques
B. Providing metrics to quantitatively assess response quality
C. Creating custom evaluators that meet specific business needs
D. Supporting low code evaluations using graphical user interface
E. Automating prompt testing across various scenarios

Answer: B,C,E

NEW QUESTION # 52
Which of the following is unique about SAP's approach to Al?

A. Offering Al capabilities in their future products as of 2025.
B. SAP's deep integration of Al with business processes and analytics.
C. Utilizing Al mainly for marketing purposes.
D. Focusing Al solely on customer support services.

Answer: B

Explanation:
SAP distinguishes itself by deeply embedding Artificial Intelligence (AI) into its core business processes and analytics, enhancing efficiency and decision-making across various enterprise functions.
1. Integration of AI into Business Processes:
* SAP Business AI:SAP focuses on solving customers' business problems by integrating AI directly into business processes, rather than offering general-purpose AI platforms. This approach ensures that AI solutions are tailored to specific business needs, enhancing process efficiency and effectiveness.
* SAP S/4HANA Integration:By embedding AI into SAP S/4HANA, SAP enables real-time data analysis and process optimization. This integration allows for improved supply chain efficiency, enhanced financial decision-making, and personalized customer experiences.
2. AI-Driven Analytics:
* SAP Analytics Cloud:This solution combines AI with analytics and planning, unlocking the full potential of business data. It provides advanced analytics capabilities, enabling businesses to make informed decisions based on real-time insights.
* Predictive Analytics Library:SAP HANA includes a Predictive Analytics Library with native algorithms for statistical measures, clustering, classification, and time series analysis. This facilitates advanced data processing and predictive analytics within business applications.
3. AI in Enterprise Applications:
* SAP SuccessFactors:AI is integrated into SAP SuccessFactors to enhance human resources processes, such as talent acquisition and employee engagement, by providing data-driven insights and automating routine tasks.
* SAP AI Business Services:These services offer reusable AI capabilities that can be integrated across various business processes, automating tasks like document processing andenriching customer experiences.

NEW QUESTION # 53
......

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C_AIG_2412 Reliable Test Answers & C_AIG_2412 Reliable Exam Papers

Free PDF 2025 First-grade SAP C_AIG_2412: SAP Certified Associate - SAP Generative AI Developer Reliable Test Answers

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

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