SPECIFICATIONS OF C-AIG-2412 PRACTICE EXAM SOFTWARE

Specifications of C-AIG-2412 Practice Exam Software

Specifications of C-AIG-2412 Practice Exam Software

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Tags: Reliable C-AIG-2412 Cram Materials, Reliable C-AIG-2412 Study Plan, C-AIG-2412 PDF, Latest C-AIG-2412 Dumps, Dumps C-AIG-2412 Free

All three SAP C-AIG-2412 exam questions formats are easy to use and compatible with all devices, operating systems, and the latest browsers. Now take the best decision for your career and take part in the SAP Certified Associate - SAP Generative AI Developer C-AIG-2412 Certification test and start preparation with SAP C-AIG-2412 PDF Questions and practice tests. 2Pass4sure offers free updates for 365 days.

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
  • 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 3
  • 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 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 (Q46-Q51):

NEW QUESTION # 46
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 in SAP HANA.
  • B. The model can be deployed for inferencing.
  • C. The model's accuracy can be optimized directly in SAP HANA.
  • D. The model can be registered in the hyperscaler object store.

Answer: B,D


NEW QUESTION # 47
You want to download a json output for a prompt and the response.
Which of the following interfaces can you use in SAP's generative Al hub in SAP AI Launchpad?

  • A. Prompt Editor
  • B. Prompt management
  • C. Chat
  • D. Administration

Answer: B

Explanation:
* Prompt managementis the section within SAP's generative AI hub (accessed via the SAP AI Launchpad) where you work with prompts, including:
* Creating and saving prompts:You can write and store your prompts for later use.
* Viewing prompt history:You can see a record of your past prompts and the AI's responses.
* Exporting prompts and responses:This is where you'd find the option to download your prompt and its corresponding response in JSON format.
Why the other options are incorrect:
* A. Chat:The chat interface is where you have interactive conversations with the generative AI. While you can see your conversation history there, you wouldn't typically find options to download it in JSON format.
* C. Administration:The administration section focuses on managing settings and configurations for the AI hub, not on individual prompts and responses.
* D. Prompt Editor:While a prompt editor might be used to create and refine prompts, it wouldn't necessarily be the place to manage or download them.


NEW QUESTION # 48
Which of the following statements accurately describe the RAG process?
Note: There are 2 correct answers to this question.

  • A. The embedding model stores the generated answers for future reference.
  • B. The retrieved content is combined with the LLM's capabilities to generate a response.
  • C. The LLM directly answers the user's question without accessing external information.
  • D. The user's question is used to search a knowledge base or a set of documents.

Answer: B,D


NEW QUESTION # 49
What is a part of LLM context optimization?

  • A. Providing the model with domain-specific knowledge needed to solve a problem
  • B. Adjusting the model's output format and style
  • C. Enhancing the computational speed of the model
  • D. Reducing the model's size to improve efficiency

Answer: A

Explanation:
LLM context optimization involves tailoring a Large Language Model's (LLM) input context to enhance its performance on specific tasks, particularly by incorporating domain-specific knowledge.
1. Understanding LLM Context Optimization:
* Definition:Context optimization refers to the process of adjusting the input provided to an LLM to ensure it includes relevant information, thereby enabling the model to generate more accurate and contextually appropriate outputs.
* Domain-Specific Knowledge Integration:By embedding domain-specific information into the model's context, the LLM can better understand and address specialized queries, leading to improved problem- solving capabilities.
2. Importance of Domain-Specific Knowledge:
* Enhanced Relevance:Providing domain-specific context ensures that the model'sresponses are pertinent to the particular field or subject matter, increasing the utility of the generated content.
* Improved Accuracy:With access to specialized knowledge, the LLLM is less likely to produce generic or incorrect answers, thereby enhancing the overall quality of its outputs.
3. Methods of Context Optimization:
* Prompt Engineering:Crafting prompts that include necessary domain-specific information to guide the model towards generating desired responses.
* Retrieval-Augmented Generation (RAG):Incorporating external data sources into the model's context to provide up-to-date and relevant information pertinent to the domain.


NEW QUESTION # 50
What are some benefits of SAP Business Al? Note: There are 3 correct answers to this question.

  • A. Face detection and face recognition
  • B. Personalized recommendations based on Al algorithms
  • C. Al-powered forecasting and predictions
  • D. Automatic human emotion recognition
  • E. Intelligent business document processing

Answer: B,C,E

Explanation:
SAP Business AI offers a suite of capabilities designed to enhance various business processes through intelligent automation and data-driven insights.
1. Intelligent Business Document Processing:
* Document Information Extraction:SAP Business AI includes services that automate the extraction of relevant information from business documents, such as invoices and purchase orders. This automation reduces manual data entry, minimizes errors, and accelerates processing times.
2. AI-Powered Forecasting and Predictions:
* Predictive Analytics:SAP Business AI leverages machine learning models to analyze historical data and predict future trends. This capability assists businesses in demand forecasting, financial planning, and inventory management, enabling proactive decision-making.
3. Personalized Recommendations Based on AI Algorithms:
* Personalized Recommendation Services:By analyzing user behavior and preferences, SAP Business AI provides personalized product or service recommendations. This personalization enhances customer experience and can lead to increased sales and customer satisfaction.


NEW QUESTION # 51
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