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[General] Study Guide C_AIG_2412 Pdf | Reliable C_AIG_2412 Dumps

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【General】 Study Guide C_AIG_2412 Pdf | Reliable C_AIG_2412 Dumps

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SAP C_AIG_2412 Exam Syllabus Topics:
TopicDetails
Topic 1
  • SAP's Generative AI Hub: This section of the exam measures the skills of Solution Architects and covers SAP’s Generative AI Hub, which acts as the central layer for designing and managing generative AI solutions. The exam tests knowledge of building, deploying, and connecting AI models to business scenarios through the Hub. Emphasis is placed on leveraging the Hub to streamline workflows and ensure scalable solutions that align with organizational needs.
Topic 2
  • Large Language Models (LLMs): This section of the exam measures the skills of AI Developers and covers the practical use of large language models in SAP environments. Candidates are expected to understand how LLMs can be applied to automate tasks, enhance decision-making, and improve user interaction within SAP systems. The exam evaluates knowledge of handling model selection, fine-tuning, and adapting LLMs to specific business cases.
Topic 3
  • Advanced AI Techniques with SAP’s Generative AI Hub: This section of the exam measures the skills of Solution Architects and covers advanced techniques available through SAP’s Generative AI Hub. Candidates are assessed on their ability to design, optimize, and scale generative AI solutions that go beyond basic implementations. The focus includes applying sophisticated strategies to integrate advanced models, manage performance, and align AI-driven outcomes with complex enterprise goals.
Topic 4
  • SAP AI Core: This section of the exam measures the skills of AI Developers and covers the fundamental components of SAP AI Core. Candidates are assessed on their ability to work with the core services that allow machine learning models to be deployed and managed within SAP environments. The focus is on understanding how AI Core fits into SAP’s ecosystem and ensures smooth integration with enterprise applications.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q58-Q63):NEW QUESTION # 58
What advantage can you gain by leveraging different models from multiple providers through the SAP's generative Al hub?
  • A. Get more training data for new models
  • B. Enhance the accuracy and relevance of Al applications that use SAP's data assets
  • C. Train new models using SAP and non-SAP data
  • D. Design new product interfaces for SAP applications
Answer: B
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 # 59
Which of the following are functionalities provided by the generative-Al-hub-SDK ? Note: There are 2 correct answers to this question.
  • A. Interact with LLMs
  • B. Configure SAP BTP credentials
  • C. Customize SAP AI Launchpad
  • D. Create chat responses and embeddings
Answer: A,D

NEW QUESTION # 60
What are some features of Joule?
Note: There are 3 correct answers to this question.
  • A. Streamlining tasks with an Al assistant that knows your unique role.
  • B. Providing coding assistance and content generation.
  • C. Maintaining data privacy while offering generative Al capabilities.
  • D. Generating standalone applications.
  • E. Downloading and processing data.
Answer: A,B,C

NEW QUESTION # 61
What is the purpose of splitting documents into smaller overlapping chunks in a RAG system?
  • A. To enable the matching of different relevant passages to user queries
  • B. To improve the efficiency of encoding queries into vector representations
  • C. To reduce the storage space required for the vector database
  • D. To simplify the process of training the embedding model
Answer: A
Explanation:
In Retrieval-Augmented Generation (RAG) systems, splitting documents into smaller overlapping chunks is a crucial preprocessing step that enhances the system's ability to match relevant passages to user queries.
1. Purpose of Splitting Documents into Smaller Overlapping Chunks:
* Improved Retrieval Accuracyividing documents into smaller, manageable segments allows the system to retrieve the most relevant chunks in response to a user query, thereby improving the precision of the information provided.
* Context Preservation:Overlapping chunks ensure that contextual information is maintained across segments, which is essential for understanding the meaning and relevance of each chunk in relation to the query.
2. Benefits of This Approach:
* Enhanced Matching:By having multiple overlapping chunks, the system increases the likelihood that at least one chunk will closely match the user's query, leading to more accurate and relevant responses.
* Efficient Processing:Smaller chunks are easier to process and analyze, enabling the system to handle large documents more effectively and respond to queries promptly.

NEW QUESTION # 62
What is the goal of prompt engineering?
  • A. To develop new neural network architectures for Al models
  • B. To craft inputs that guide Al systems in generating desired outputs
  • C. To replace human decision-making with automated processes
  • D. To optimize hardware performance for Al computations
Answer: B

NEW QUESTION # 63
......
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