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Examinations C-AIG-2412 Actual Questions, New C-AIG-2412 Exam Questions

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Don't waste your time with unhelpful study methods. There are plenty of options available, but not all of them are suitable to help you pass the SAP Certified Associate - SAP Generative AI Developer (C-AIG-2412) exam. Some resources out there may even do more harm than good by leading you astray. Our C-AIG-2412 Exam Dumps are available with a free demo and up to 1 year of free updates.

SAP C-AIG-2412 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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.

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q58-Q63):

NEW QUESTION # 58
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 simplify the process of training the embedding model
D. To reduce the storage space required for the vector database

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 Accuracy:Dividing 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 # 59
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. Human agency and oversight
C. Transparency and explainability
D. Maximize business profits
E. Store all user data for legal proceedings

Answer: A,B,C

NEW QUESTION # 60
What are some components of the training pipeline in SAP AI Core?
Note: There are 2 correct answers to this question.

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

Answer: B,D

NEW QUESTION # 61
Which of the following steps is NOT a requirement to use the Orchestration service?

A. Get an auth token for orchestration
B. Create a deployment for orchestration
C. Create an instance of an Al model
D. Modify the underlying Al models

Answer: D

Explanation:
To utilize the Orchestration service in SAP's Generative AI Hub, several steps are required; however, modifying the underlying AI models is not among them:
1. Required Steps:
* Get an Auth Token for Orchestration:Obtain authentication credentials to access the orchestration service.
* Create an Instance of an AI Model:Set up an instance of the desired AI model to be used within the orchestration pipeline.
* Create a Deployment for Orchestration:Deploy the configured AI model instance to the orchestration service, enabling it for processing requests.
2. Not Required:
* Modify the Underlying AI Models:The orchestration service allows users to utilize pre-existing AI models without the need to alter their foundational architecture or training.

NEW QUESTION # 62
What is Machine Learning (ML)?

A. A statistical method for data processing that does not involve any Al techniques.
B. A technology that equips machines with human-like capabilities such as problem-solving, visual perception, and decision-making.
C. A form of Al that only focuses on creating new content, including text, images, sound, and videos.
D. A subset of Al that focuses on enabling computer systems to learn and improve from experience or data.

Answer: A,B,C

NEW QUESTION # 63
......

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Examinations C-AIG-2412 Actual Questions, New C-AIG-2412 Exam Questions

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q58-Q63):

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