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C_AIG_2412 Dumps Free - Exam C_AIG_2412 Experience

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SAP C_AIG_2412 Dumps | Questions (2025)

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SAP C_AIG_2412 Exam Syllabus Topics:

Topic
Details

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 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 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'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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q50-Q55):

NEW QUESTION # 50
Which of the following are grounding principles included in SAP's AI Ethics framework? Note: There are 3 correct answers to this question.

A. Avoid bias and discrimination
B. Store all user data for legal proceedings
C. Maximize business profits
D. Human agency and oversight
E. Transparency and explainability

Answer: A,D,E

NEW QUESTION # 51
Which of the following is a benefit of using Retrieval Augmented Generation?

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

Answer: A

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 # 52
You want to use the orchestration service through SAP's generative-Al-hub-sdk. What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM 11m =
LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})

A. Create the Orchestration Configuration
B. Define the Template and Default Input Values
C. Define the LLM
D. Run the Orchestration Request

Answer: C

Explanation:
The provided code snippet defines a Large Language Model (LLM) within the SAP Generative AI Hub SDK's orchestration service:
from gen_ai_hub.orchestration.models.llm import LLM
llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})
1. Importing the LLM Class:
* Code:from gen_ai_hub.orchestration.models.llm import LLM
* Purpose:Imports the LLM class from the SDK, enabling the creation of an LLM instance.
2. Defining the LLM Instance:
* Code:llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature":
0.2})
* Parameters:
* name:Specifies the model's name, in this case, "gpt-40".
* version:Indicates the model version, set to "latest" to use the most recent version.
* parameters:A dictionary defining model-specific parameters:
* max_tokens:Sets the maximum number of tokens (words or word pieces) the model can generate, here limited to 256 tokens.
* temperature:Controls the randomness of the output; a lower value like 0.2 results in more deterministic responses.
3. Role in Orchestration Pipeline:
* Function:This definition is a crucial step in the orchestration pipeline, specifying which LLM to use and configuring its behavior for subsequent tasks.
Conclusion:
The code snippet defines an LLM named "gpt-40" with specific parameters, preparing it for integration into an AI-driven workflow within SAP's Generative AI Hub.

NEW QUESTION # 53
What are some components of the training pipeline in SAP AI Core? Note: There are 2 correct answers to this question.

A. Automated deployment to Kubernetes clusters
B. Executables that define the training process
C. Input datasets stored in a hyperscaler object store
D. The SAP HANA database for model storage

Answer: B,C

NEW QUESTION # 54
What is the primary function of the generative Al hub in SAP's Al Foundation?

A. To provide ready-to-use Al services for document processing
B. To serve as an abstraction layer to access a range of foundation Al models
C. To manage the Al lifecycle efforts end-to-end
D. To store embeddings of unstructured data for semantic data retrieval

Answer: B

Explanation:
SAP's Generative AI Hub, a component of the SAP AI Foundation, provides a unified platform for accessing various foundation AI models.
1. Abstraction Layer Functionality:
* Unified Access:The Generative AI Hub acts as an abstraction layer, offering developers seamless access to a diverse range of large language models (LLMs) from multiple providers, such as GPT-4 by Azure OpenAI and open-source models like Falcon-40b.
* Simplified Integration:By providing a standardized interface, the hub simplifies the integration of these models into applications, reducing complexity and development time.
2. Supporting AI Development:
* Toolset Availability:The hub offers a comprehensive toolset for building custom AI solutions, including prompt engineering tools, SDKs, and fine-tuning services, facilitating efficient AI development.
* Model Orchestration:Developers can orchestrate multiple models, enabling the selection of the most suitable model for specific use cases, thereby enhancing the accuracy and relevance of AI applications.

NEW QUESTION # 55
......

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