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SAP C_AIG_2412 認定試験の出題範囲：
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質問 # 32
What are some use cases for fine-tuning of a model? Note: There are 2 correct answers to this question.
- A. To quickly create iterations on a new use case
- B. To sanitize model outputs
- C. To customize outputs for specific types of inputs
- D. To introduce new knowledge to a model in a resource-efficient way
正解：C、D
質問 # 33
How does the Al API support SAP AI scenarios? Note: There are 2 correct answers to this question.
- A. By providing a unified framework for operating Al services
- B. By integrating Al services into business applications
- C. By managing Kubernetes clusters automatically
- D. By integrating Al models into third-party platforms like AWS
正解：A、B
解説：
The AI API in SAP plays a crucial role in supporting AI scenarios by facilitating the integration of AI services into business applications and providing a unified framework for operating these services.
1. Integration of AI Services into Business Applications:
* Seamless Integration:The AI API enables developers to incorporate AI functionalities directly into SAP and non-SAP business applications, enhancing their capabilities with intelligent features.
* Use Case Example:Integrating AI models into SAP Build Apps allows for the creation of AI-powered applications that can perform tasks such as data analysis, predictive modeling, and more.
2. Unified Framework for Operating AI Services:
* Standardized Operations:The AI API provides a consistent and standardized framework for managing AI services, ensuring uniformity in deployment, monitoring, and maintenance across different platforms.
* Scalability and Flexibility:This unified approach allows for scalable AI operations, accommodating various AI models and services within a cohesive operational structure.
質問 # 34
What are the benefits of SAP's generative Al hub? Note: There are 2 correct answers to this question.
- A. Accelerate Al development with flexible access to a broad range of models
- B. Provide libraries for no-code development
- C. Send your data to various LLM providers for training feedback
- D. Build custom Al solutions and extend SAP applications
正解：A、D
質問 # 35
What must be defined in an executable to train a machine learning model using SAP AI Core? Note: There are 2 correct answers to this question.
- A. Deployment templates for SAP AI Launchpad
- B. Pipeline containers to be used
- C. User scripts to manually execute pipeline steps
- D. Infrastructure resources such as CPUs or GPUs
正解：B、D
質問 # 36
Which of the following are grounding principles included in SAP's AI Ethics framework? Note: There are 3 correct answers to this question.
- A. Maximize business profits
- B. Avoid bias and discrimination
- C. Transparency and explainability
- D. Human agency and oversight
- E. Store all user data for legal proceedings
正解：B、C、D
解説：
SAP's AI Ethics framework is built upon several grounding principles to ensure responsible AI development and deployment:
1. Transparency and Explainability:
* Definition:Ensuring that AI systems are understandable and their decision-making processes can be clearly explained to stakeholders.
* Implementation:SAP commits to making AI systems transparent, providing clearinformation about how decisions are made to build trust and facilitate accountability.
2. Human Agency and Oversight:
* Definition:Maintaining human control over AI systems, ensuring that humans can intervene or oversee AI operations as necessary.
* Implementation:SAP emphasizes the importance of human oversight in AI applications, ensuring that AI augments human decision-making rather than replacing it.
3. Avoid Bias and Discrimination:
* Definition:Preventing AI systems from perpetuating or amplifying biases, ensuring fair and equitable treatment for all users.
* Implementation:SAP strives to develop AI systems that are free from bias, implementing measures to detect and mitigate discriminatory outcomes.
質問 # 37
What can be done once the training of a machine learning model has been completed in SAP AI Core? Note: There are 2 correct answers to this question.
- A. The model can be registered in the hyperscaler object store.
- B. The model can be deployed for inferencing.
- C. The model's accuracy can be optimized directly in SAP HANA.
- D. The model can be deployed in SAP HANA.
正解：A、B
質問 # 38
What are some characteristics of the SAP generative Al hub? Note: There are 2 correct answers to this question.
- A. It operates independently of SAP's partners and ecosystem.
- B. It only supports traditional machine learning models.
- C. It ensures relevant, reliable, and responsible business Al.
- D. It provides instant access to a wide range of large language models (LLMs).
正解：C、D
質問 # 39
What can be done once the training of a machine learning model has been completed in SAP AI Core? Note: There are 2 correct answers to this question.
- A. The model can be registered in the hyperscaler object store.
- B. The model can be deployed in SAP HAN
- C. The model can be deployed for inferencing.
- D. The model's accuracy can be optimized directly in SAP HANA.
正解：A、C
質問 # 40
Which of the following steps must be performed to deploy LLMs in the generative Al hub?
- A. Run the booster
- B. Provision SAP AI
- C. Provision SAP AI Core
- D. Check for foundation model scenario
正解：C
質問 # 41
Which technique is used to supply domain-specific knowledge to an LLM?
- A. Prompt template expansion
- B. Domain-adaptation training
- C. Retrieval-Augmented Generation
- D. Fine-tuning the model on general data
正解：C
解説：
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.
質問 # 42
Which of the following steps must be performed to deploy LLMs in the generative Al hub?
- A. Check for foundation model scenario
* Create a deployment
* Configuring entitlements - B. Run the booster
* Create service keys
* Select the executable ID - C. Provision SAP AI Core
* Check for foundation model scenario
* Create a configuration
* Create a deployment - D. Provision SAP AI
* Core Create a configuration
* Run the booster
正解：C
質問 # 43
What are some functionalities provided by SAP Al Core?
Note: There are 3 correct answers to this question.
- A. Monitoring and retraining models in SAP Al Core
- B. Management of SAP S/4HANA cloud infrastructure
- C. Continuous delivery and tenant isolation for scalability
- D. Integration of Al services with business applications using a standardized API
- E. Orchestration of Al workflows such as model training and inference
正解：C、D、E
質問 # 44
Which of the following are features of the SAP AI Foundation? Note: There are 2 correct answers to this question.
- A. Ready-to-use Al services
- B. Open source Al model repository
- C. Joule integration in SAP SuccessFactors
- D. Al runtimes and lifecycle management
正解：A、D
解説：
SAP AI Foundation is an all-in-one AI toolkit that provides developers with the necessary tools to build AI- powered extensions and applications on SAP Business Technology Platform (SAP BTP).
1. Ready-to-Use AI Services:
* Pre-Built AI Capabilities:AI Foundation offers a suite of ready-to-use AI services, enabling developers to integrate AI functionalities into their applications without the need to build models from scratch. These services include capabilities such as document information extraction, translation, and personalized recommendations.
2. AI Runtimes and Lifecycle Management:
* Comprehensive AI Management:AI Foundation provides tools for managing AI runtimes and the entire AI lifecycle, including model deployment, monitoring, and maintenance. This ensures that AI models operate efficiently and remain up-to-date, facilitating seamless integration into business processes.
3. Integration with SAP BTP:
* Unified Platform:By integrating with SAP BTP, AI Foundation allows for the development of AI solutions that are grounded in business data and context, ensuring relevance and reliability in AI-driven applications.
質問 # 45
How does SAP ensure the enterprise-readiness of its Al solutions?
- A. By implementing rigorous product standards for Al capabilities
- B. By using generic Al models without business context complying with Al ethics standards
- C. By ensuring that Al models make bias-free decisions without human input
正解：A
解説：
SAP ensures the enterprise-readiness of its AI solutions through the implementation of rigorous product standards:
1. Rigorous Product Standards for AI Capabilities:
* Development Guidelines:SAP adheres to strict guidelines during the development of AI systems, ensuring they meet high standards of quality, security, and performance.
* Ethical Framework:SAP's AI Ethics Policy governs the development, deployment, use, and sale of AI systems, defining clear ethical rules aligned with global standards.
* Compliance and Governance:SAP has established governance bodies and processes to oversee AI ethics, ensuring that AI solutions are developed and deployed responsibly.
質問 # 46
What are some drivers for the rapid adoption of generative AI? Note: There are 2 correct answers to this question.
- A. Wide availability
- B. Ease of use
- C. Significant hardware cost savings
- D. Availability of skilled developers
正解：A、B
解説：
The rapid adoption of generative AI is driven by several key factors:
1. Wide Availability:
* Access to Generative AI Tools:The proliferation of generative AI tools and platforms has made the technology widely accessible to businesses and individuals. This widespread availability facilitates experimentation and integration into various applications.
2. Ease of Use:
* User-Friendly Interfaces:Modern generative AI tools often feature intuitive interfaces that require minimal technical expertise, enabling a broader range of users to leverage AI capabilities without deep technical knowledge.
質問 # 47
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. Providing metrics to quantitatively assess response quality
- B. Supporting low code evaluations using graphical user interface
- C. Automating prompt testing across various scenarios
- D. Maintaining data privacy by using data masking techniques
- E. Creating custom evaluators that meet specific business needs
正解：A、C、E
質問 # 48
How does SAP deal with vulnerability risks created by generative Al?
Note: There are 2 correct answers to this question.
- A. By relying on external vendors to manage security threats.
- B. By implementing responsible Al use guidelines and strong product security standards.
- C. By focusing on technological advancement only.
- D. By identifying human, technical, and exfiltration risks through an Al Security Taskforce.
正解：B、D
質問 # 49
What contract type does SAP offer for Al ecosystem partner solutions?
- A. Pay-as-you-go for each partner service
- B. Annual subscription-only contracts
- C. Bring Your Own License (BYOL) for embedded partner solutions
- D. All-in-one contracts, with services that are contracted through SAP
正解：D
解説：
SAP collaborates with a wide ecosystem of partners, including leading general-purpose AI vendors, to provide tailored solutions to its customers. Through the SAP Store, customers have access to numerous partner applications and a variety of tools, allowing them to choose solutions that best fit their requirements.
Contractual Approach:
* All-in-One Contracts:SAP offers all-in-one contracts for AI ecosystem partner solutions, where services are white-labeled and contracted directly through SAP. This approach simplifies the procurement process for customers, as they engage with SAP as the single point of contact for both SAP and partner services.
* Exclusion of Bring Your Own License (BYOL) Model:SAP does not adopt a "bring your own license" model for these embedded partner solutions. Instead, all services are integrated and provided under unified contracts managed by SAP.
Benefits of This Contractual Model:
* Simplified Procurement:Customers benefit from a streamlined purchasing process, dealing with a single contract and point of contact for multiple services.
* Integrated Solutions:The all-in-one contract ensures that partner solutions are seamlessly integrated with SAP's offerings, providing a cohesive experience.
* Assured Compliance and Support:By contracting through SAP, customers can be confident in the compliance, security, and support standards upheld across all services.
質問 # 50
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