NEW SAP C_AIG_2412 EXAM PATTERN | C_AIG_2412 ADVANCED TESTING ENGINE

New SAP C_AIG_2412 Exam Pattern | C_AIG_2412 Advanced Testing Engine

New SAP C_AIG_2412 Exam Pattern | C_AIG_2412 Advanced Testing Engine

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Tags: New C_AIG_2412 Exam Pattern, C_AIG_2412 Advanced Testing Engine, C_AIG_2412 Exam Sample, C_AIG_2412 Reliable Mock Test, C_AIG_2412 Exam Pattern

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SAP C_AIG_2412 Exam Syllabus Topics:

TopicDetails
Topic 1
  • SAP Business AI: This section of the exam measures the skills of business analysts and covers the features and capabilities of SAP Business AI. It includes exploring how AI can automate processes, provide real-time insights, and enhance decision-making across various business functions.
Topic 2
  • SAP's Generative AI Hub: This section of the exam measures the skills of technology strategists and covers the functionalities provided by SAP's Generative AI Hub. It emphasizes how organizations can use generative AI to create new content and automate complex tasks. A vital skill evaluated is applying generative AI techniques to enhance business processes and customer experiences.
Topic 3
  • Large Language Models (LLMs): This section of the exam measures the skills of AI Developers and covers the evolution of large language models, distinguishing them from traditional IT operations analytics. It also explores the current stages of AIOps systems and their implications for organizations. A key skill assessed is understanding the foundational concepts behind LLMs and their applications in various contexts.
Topic 4
  • SAP AI Core: This section of the exam measures the skills of SAP developers and covers the core components of SAP's AI framework. It emphasizes how these components integrate with existing systems to enhance functionality and performance. Leveraging SAP AI Core to develop intelligent applications that meet business needs is a critical skill that needs to be evaluated.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q35-Q40):

NEW QUESTION # 35
What are some SAP recommendations to evaluate pricing and rate information of model usage within SAP's generative Al hub?
Note: There are 2 correct answers to this question.

  • A. Adopt best practice pricing strategies, such as outcome-based pricing
  • B. Weigh the cost of using advanced models against the expected return on investment
  • C. Use pricing models that have fixed rates irrespective of the usage patterns
  • D. Avoid subscription-based pricing models

Answer: A,B


NEW QUESTION # 36
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 deployed for inferencing.
  • B. The model can be registered in the hyperscaler object store.
  • C. The model's accuracy can be optimized directly in SAP HANA.
  • D. The model can be deployed in SAP HAN

Answer: A,B


NEW QUESTION # 37
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?

  • A. Enhance the accuracy and relevance of Al applications that use SAP's data assets
  • B. Design new product interfaces for SAP applications
  • C. Get more training data for new models
  • D. Train new models using SAP and non-SAP data

Answer: A

Explanation:
Leveraging different models from multiple providers through SAP's Generative AI Hub offers significant advantages:
1. Access to a Diverse Range of Large Language Models (LLMs):
* Integration with Multiple Providers:SAP's Generative AI Hub provides instant access to a broad spectrum of LLMs from various providers, such as GPT-4 by Azure OpenAI andopen-source models like Falcon-40b.
2. Enhancing Accuracy and Relevance:
* Model Selection Flexibility:By offering a variety of models, developers can select the most suitable one for their specific use cases, thereby enhancing the accuracy and relevance of AI applications that utilize SAP's data assets.
3. Seamless Orchestration and Integration:
* Orchestration Capabilities:The Generative AI Hub enables the orchestration of multiple models, allowing for seamless integration into SAP solutions like SAP S/4HANA and SAP SuccessFactors.


NEW QUESTION # 38
Which of the following executables in generative Al hub works with Anthropic models?

  • A. SAP AI Core
  • B. AWS Bedrock
  • C. Azure OpenAl Service
  • D. GCP Vertex Al

Answer: B

Explanation:
In SAP's Generative AI Hub, the integration with Anthropic models is facilitated through specific executables:
1. AWS Bedrock:
* Integration with Anthropic Models:AWS Bedrock provides access to Anthropic's Claude models, enabling developers to utilize these models within their applications.
* Execution via Generative AI Hub:Through the Generative AI Hub, developers can select AWS Bedrock as the executable to work with Anthropic models, integrating them into their AI solutions.
Conclusion:
To work with Anthropic models within SAP's Generative AI Hub, developers should utilize the AWS Bedrock executable, which provides access to these models for integration into their applications.


NEW QUESTION # 39
Match the components of a Retrieval Augmented Generation architecture to the diagram.

Answer:

Explanation:


NEW QUESTION # 40
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