RELIABLE C-AIG-2412 TEST PREPARATION - C-AIG-2412 DUMP COLLECTION

Reliable C-AIG-2412 Test Preparation - C-AIG-2412 Dump Collection

Reliable C-AIG-2412 Test Preparation - C-AIG-2412 Dump Collection

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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
  • 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.
Topic 4
  • 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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q21-Q26):

NEW QUESTION # 21
What defines SAP's approach to LLMs?

  • A. Limiting LLM usage to non-business applications only
  • B. Prioritizing the development of proprietary LLMs with no integration to existing systems
  • C. Ensuring ethical AI practices and seamless business integration
  • D. Focusing solely on reducing the computational cost of training LLMs

Answer: C

Explanation:
SAP's approach to Large Language Models (LLMs) is centered on integrating these powerful AI tools into its enterprise ecosystem while adhering to ethical standards. Unlike option A, SAP does not focus solely on proprietary LLMs without integration; instead, it leverages both proprietary and third-party models (e.g., via partnerships with providers like Azure OpenAI) to enhance business applications. Option B is incorrect because reducing computational cost is not the sole focus-SAP prioritizes value delivery through integration with business processes. Option D is also inaccurate, as SAP explicitly targets business applications rather than limiting LLMs to non-business use. Option C is correct because SAP emphasizes ethical AI practices (e.
g., through its AI Ethics Policy) and seamless integration with tools like SAP S/4HANA and SAP SuccessFactors, ensuring LLMs enhance enterprise workflows responsibly and effectively.


NEW QUESTION # 22
How does the Al API support SAP AI scenarios? Note: There are 2 correct answers to this question.

  • A. By managing Kubernetes clusters automatically
  • B. By integrating Al services into business applications
  • C. By integrating Al models into third-party platforms like AWS
  • D. By providing a unified framework for operating Al services

Answer: B,D

Explanation:
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.


NEW QUESTION # 23
Which of the following is a benefit of using Retrieval Augmented Generation?

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

Answer: B

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 # 24
How does SAP ensure the enterprise-readiness of its Al solutions?

  • A. By ensuring that Al models make bias-free decisions without human input
  • B. By implementing rigorous product standards for Al capabilities
  • C. By using generic Al models without business context complying with Al ethics standards

Answer: B


NEW QUESTION # 25
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note:
There are 2 correct answers to this question.

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

Answer: B,D

Explanation:
The Exploration and Development feature of SAP's Generative AI Hub provides several capabilities to facilitate AI solution development:
1. AI Playground and Chat:
* Interactive Environment:The AI playground offers an interactive space for developers to experiment with various AI models, test prompts, and observe outputs in real-time.
* Conversational Interface:The chat functionality enables users to engage in dialogue with AI models, refining prompts and understanding model behavior through iterative interactions.
2. Prompt Editor and Management:
* Prompt Creation:The prompt editor allows developers to craft and modify prompts tailored to specific business needs, enhancing the precision of AI responses.
* Prompt Organization:Prompt management tools facilitate the organization, versioning, and storage of prompts, ensuring efficient retrieval and reuse in various projects.


NEW QUESTION # 26
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