C_AIG_2412問題集には練習試験問題解答
C_AIG_2412はSAP Certified Associate実際の無料試験練習テスト
SAP C_AIG_2412 認定試験の出題範囲：
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質問 # 21
How does SAP deal with vulnerability risks created by generative Al? Note: There are 2 correct answers to this question.
- A. By focusing on technological advancement only.
- B. By relying on external vendors to manage security threats.
- C. By implementing responsible Al use guidelines and strong product security standards.
- D. By identifying human, technical, and exfiltration risks through an Al Security Taskforce.
正解：C、D
解説：
SAP addresses vulnerability risks associated with generative AI through a comprehensive strategy:
1. Implementation of Responsible AI Use Guidelines and Strong Product Security Standards:
* AI Ethics Policy:SAP has established an AI Ethics Policy that mandates responsible AI usage, ensuring that AI systems are designed and deployed ethically, with considerations for fairness, transparency, and accountability.
* Product Security Standards:SAP integrates robust security measures into its AI products, adhering to stringent security protocols to protect against vulnerabilities and potential threats.
2. Identification of Risks through an AI Security Taskforce:
* AI Security Taskforce:SAP has established an AI Security Taskforce dedicated to identifying and mitigating risks associated with generative AI, including human factors, technical vulnerabilities, and data exfiltration threats.
質問 # 22
Which of the following techniques uses a prompt to generate or complete subsequent prompts (streamlining the prompt development process), and to effectively guide Al model responses?
- A. Meta prompting
- B. One-shot prompting
- C. Chain-of-thought prompting
- D. Few-shot prompting
正解：A
質問 # 23
What contract type does SAP offer for Al ecosystem partner solutions?
- A. Bring Your Own License (BYOL) for embedded partner solutions
- B. All-in-one contracts, with services that are contracted through SAP
- C. Annual subscription-only contracts
- D. Pay-as-you-go for each partner service
正解：B、C、D
質問 # 24
What are some benefits of SAP Business Al? Note: There are 3 correct answers to this question.
- A. Personalized recommendations based on Al algorithms
- B. Face detection and face recognition
- C. Al-powered forecasting and predictions
- D. Intelligent business document processing
- E. Automatic human emotion recognition
正解：A、C、D
解説：
SAP Business AI offers a suite of capabilities designed to enhance various business processes through intelligent automation and data-driven insights.
1. Intelligent Business Document Processing:
* Document Information Extraction:SAP Business AI includes services that automate the extraction of relevant information from business documents, such as invoices and purchase orders. This automation reduces manual data entry, minimizes errors, and accelerates processing times.
2. AI-Powered Forecasting and Predictions:
* Predictive Analytics:SAP Business AI leverages machine learning models to analyze historical data and predict future trends. This capability assists businesses in demand forecasting, financial planning, and inventory management, enabling proactive decision-making.
3. Personalized Recommendations Based on AI Algorithms:
* Personalized Recommendation Services:By analyzing user behavior and preferences, SAP Business AI provides personalized product or service recommendations. This personalization enhances customer experience and can lead to increased sales and customer satisfaction.
質問 # 25
What is a part of LLM context optimization?
- A. Adjusting the model's output format and style
- B. Enhancing the computational speed of the model
- C. Providing the model with domain-specific knowledge needed to solve a problem
- D. Reducing the model's size to improve efficiency
正解：C
質問 # 26
How does SAP deal with vulnerability risks created by generative Al? Note: There are 2 correct answers to this question.
- A. By focusing on technological advancement only.
- B. By relying on external vendors to manage security threats.
- C. By implementing responsible Al use guidelines and strong product security standards.
- D. By identifying human, technical, and exfiltration risks through an Al Security Taskforce.
正解：C、D
質問 # 27
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. Supporting low code evaluations using graphical user interface
- B. Automating prompt testing across various scenarios
- C. Providing metrics to quantitatively assess response quality
- D. Creating custom evaluators that meet specific business needs
- E. Maintaining data privacy by using data masking techniques
正解：B、C、D
解説：
Utilizing an SDK for evaluating prompts within the context of generative AI offers several benefits:
1. Creating Custom Evaluators That Meet Specific Business Needs:
* Tailored Evaluation Metrics:An SDK allows developers to design and implement custom evaluation metrics that align with specific business objectives, ensuring that prompt assessments are relevant and meaningful.
* Flexibility in Evaluation Criteria:Developers can define criteria that reflect the unique requirements of their applications, leading to more accurate and business-aligned evaluations.
2. Automating Prompt Testing Across Various Scenarios:
* Scalability:An SDK enables the automation of prompt testing across multiple scenarios, facilitating large-scale evaluations without manual intervention.
* Consistency:Automated testing ensures consistent application of evaluation criteria, reducing the potential for human error and increasing reliability.
3. Providing Metrics to Quantitatively Assess Response Quality:
* Objective Assessment:The SDK can generate quantitative metrics, such as accuracy, relevance, and coherence scores, providing an objective basis for evaluating prompt performance.
* Performance Monitoring:These metrics enable continuous monitoring and improvement of prompt quality, ensuring that AI models deliver optimal results.
質問 # 28
How can few-shot learning enhance LLM performance?
- A. By providing a large training set to improve generalization
- B. By enhancing the model's computational efficiency
- C. By reducing overfitting through regularization techniques
- D. By offering input-output pairs that exemplify the desired behavior
正解：D
質問 # 29
Which of the following is unique about SAP's approach to Al?
- A. SAP's deep integration of Al with business processes and analytics.
- B. Focusing Al solely on customer support services.
- C. Offering Al capabilities in their future products as of 2025.
- D. Utilizing Al mainly for marketing purposes.
正解：A
質問 # 30
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. Infrastructure resources such as CPUs or GPUs
- C. Pipeline containers to be used
- D. User scripts to manually execute pipeline steps
正解：B、C
質問 # 31
Which of the following is a benefit of using Retrieval Augmented Generation?
- A. It enables LLMs to learn new languages without additional training.
- B. It reduces the computational resources required for language modeling.
- C. It allows LLMs to access and utilize information beyond their initial training data.
- D. It eliminates the need for fine-tuning LLMs for specific tasks.
正解：C
解説：
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.
質問 # 32
Which statement best describes the Chain-of-Thought (COT) prompting technique?
- A. Writing a series of connected prompts creating a chain of related information.
- B. Linking multiple Al models in sequence, where each model's output becomes the input for the next model in the chain.
- C. Connecting related concepts by having the LLM generate chains of ideas.
- D. Concatenating multiple related prompts to form a chain, guiding the model through sequential reasoning steps.
正解：D
解説：
Chain-of-Thought (CoT) prompting is a technique that involves concatenating multiple related prompts to guide a language model through a series of reasoning steps, leading to a final conclusion.
1. Structure of CoT Prompting:
* Sequential Reasoning:By breaking down a complex problem into a sequence of intermediate prompts, the model addresses each step methodically, enhancing its problem-solving capabilities.
* Logical Progression:Each prompt builds upon the previous one, ensuring a coherent flow of information that mirrors human logical reasoning.
2. Advantages of CoT Prompting:
* Enhanced Comprehension:This structured approach helps the model understand and process intricate tasks by focusing on one aspect at a time.
* Improved Accuracy:By guiding the model through detailed reasoning steps, CoT prompting reduces the likelihood of errors in the final output.
質問 # 33
Why is generative Al gaining significant attention and investment in the current business landscape?
Note: There are 2 correct answers to this question.
- A. It only requires natural language skills to use.
- B. It can replicate complex technical skills without training or quality control.
- C. It can run entire business operations without human intervention.
- D. It lowers barriers to adoption.
正解：A、D
質問 # 34
Why is generative Al gaining significant attention and investment in the current business landscape? Note:
There are 2 correct answers to this question.
- A. It only requires natural language skills to use.
- B. It can replicate complex technical skills without training or quality control.
- C. It can run entire business operations without human intervention.
- D. It lowers barriers to adoption.
正解：A、D
解説：
Generative AI is attracting significant attention and investment in the current business landscape due to several compelling factors:
1. Lowering Barriers to Adoption:
* Accessibility of Tools:The proliferation of user-friendly generative AI tools has made advanced AI capabilities accessible to a broader audience, including those without specialized technical expertise.
* Integration with Existing Systems:Generative AI solutions, such as SAP's Joule, are designed to integrate seamlessly with existing business systems, reducing the complexity and cost associated with adoption.
2. Natural Language Interaction:
* Ease of Use:Generative AI models are capable of understanding and processing natural language inputs, allowing users to interact with AI systems using everyday language. This reduces the need for specialized training and enables more intuitive user experiences.
* Enhanced User Engagement:The ability to communicate with AI systems in natural language fosters greater user engagement and facilitates the integration of AI into daily business operations.
質問 # 35
What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.
- A. Input datasets stored in a hyperscaler object store
- B. Automated deployment to Kubernetes clusters
- C. Executables that define the training process
- D. The SAP HANA database for model storage
正解：A、C
質問 # 36
Where can you configure language models in generative Al hub?
- A. The Configuration tab within ML Operations in SAP AI Launchpad
- B. The Models tab in Prompt Editor
- C. The Orchestration tab in SAP AI Launchpad
- D. The Configuration tab of the SAP BTP cockpit
正解：A
質問 # 37
What does SAP recommend you do before you start training a machine learning model in SAP AI Core?
Note: There are 3 correct answers to this question.
- A. Define the required infrastructure resources for training.
- B. Configure the model deployment in SAP Al Launchpad.
- C. Register the input dataset in SAP AI Core.
- D. Perform manual data integration with SAP HANA.
- E. Configure the training pipeline using templates.
正解：A、C、E
解説：
Before initiating the training of a machine learning model in SAP AI Core, SAP recommends the following steps:
* Configure the training pipeline using templates:Utilize predefined templates to set up the training pipeline, ensuring consistency and efficiency in the training process.
* Define the required infrastructure resources for training:Specify the computational resources, such as CPUs or GPUs, necessary for the training job to ensure optimal performance.
* Register the input dataset in SAP AI Core:Ensure that the dataset intended for training is properly registered within SAP AI Core, facilitating seamless access during the training process.
These preparatory steps are crucial for the successful training of machine learning models within the SAP AI Core environment.
質問 # 38
Which of the following is a principle of effective prompt engineering?
- A. Use precise language and providing detailed context in prompts.
- B. Keep prompts as short as possible to avoid confusion.
- C. Combine multiple complex tasks into a single prompt.
- D. Write vague and open-ended instructions to encourage creativity.
正解：A
解説：
Effective prompt engineering is crucial for guiding AI models to produce accurate and relevant outputs.
1. Importance of Precision and Context:
* Clarity:Using precise language in prompts minimizes ambiguity, ensuring the AI model comprehends the exact requirements.
* Detailed Context:Providing comprehensive context helps the model understand the background and nuances of the task, leading to more accurate and tailored responses.
2. Best Practices in Prompt Engineering:
* Specificity:Clearly define the desired outcome, including any constraints or specific formats required.
* Instruction Inclusion:Incorporate explicit instructions within the prompt to guide the model's behavior effectively.
* Avoiding Ambiguity:Steer clear of vague or open-ended language that could lead to varied interpretations.
3. Benefits of Effective Prompt Engineering:
* Enhanced Output Quality:Well-crafted prompts lead to responses that closely align with user expectations.
* Efficiency:Reduces the need for iterative refinements, saving time and computational resources.
質問 # 39
Match the components of a Retrieval Augmented Generation architecture to the diagram.
正解：
解説：
質問 # 40
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 HAN
- 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.
正解：B、C
質問 # 41
Which of the following sequence of steps does SAP recommend you use to solve a business problem using generative Al hub?
- A. Create a basic prompt in SAP AI Launchpad
*Enhance the prompts
*Create a baseline evaluation method for the simple prompt
*Evaluate various models for the problem using generative-ai-hub-sdk
*Scale the solution using generative-ai-hub-sdk - B. Create a basic prompt in SAP AI Launchpad
*Scale the solution using generative-ai-hub-sdk
*Create a baseline evaluation method for the simple prompt
*Enhance the prompts
*Evaluate various models for the problem using generative-ai-hub-sdk - C. Create a basic prompt in SAP AI Launchpad
*Evaluate various models for the problem using generative-ai-hub-sdk
*Scale the solution using generative-ai-hub-sdk
*Create a baseline evaluation method for the simple prompt
*Enhance the prompts.
正解：A
解説：
SAP recommends the following sequence of steps to effectively solve a business problem using the Generative AI Hub:
1. Create a Basic Prompt in SAP AI Launchpad:
* Initiation:Begin by formulating a simple prompt within SAP AI Launchpad to address the business problem. This serves as the foundation for subsequent refinements.
2. Enhance the Prompts:
* Refinement:Iteratively improve the initial prompt to better capture the nuances of the business problem, ensuring clarity and relevance.
3. Create a Baseline Evaluation Method for the Simple Prompt:
* Establish Metrics:Develop an evaluation framework to assess the performance of the prompt, setting a baseline for comparison as enhancements are made.
4. Evaluate Various Models for the Problem Using generative-ai-hub-sdk:
* Model Assessment:Utilize the generative-ai-hub-sdk to test different large language models (LLMs) against the refined prompt, identifying the model that delivers optimal results.
5. Scale the Solution Using generative-ai-hub-sdk:
* Deployment:Once the optimal model and prompt are determined, employ the generative-ai-hub-sdk to scale the solution, integrating it into the business workflow for widespread application.
Conclusion:
Following this structured approach ensures a methodical development and deployment of AI-driven solutions, enhancing their effectiveness in addressing specific business challenges.
質問 # 42
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. Supporting low code evaluations using graphical user interface
- B. Automating prompt testing across various scenarios
- C. Providing metrics to quantitatively assess response quality
- D. Creating custom evaluators that meet specific business needs
- E. Maintaining data privacy by using data masking techniques
正解：B、C、D
質問 # 43
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無料SAP Certified Associate C_AIG_2412試験問題：https://jp.fast2test.com/C_AIG_2412-premium-file.html
C_AIG_2412問題集でSAP Certified Associate必ず合格できる練習問題集：https://drive.google.com/open?id=1gEKwFo32YaM3DXsNo0fLSyHUxHSP13QG