Pass Guaranteed Quiz Authoritative SAP - C-AIG-2412 - SAP Certified Associate - SAP Generative AI Developer Reliable Test Labs

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SAP C-AIG-2412 Exam Syllabus Topics:

Topic	Details
Topic 1	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 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	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 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.

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q55-Q60):

NEW QUESTION # 55
What is one primary benefit of using LLMs in business applications?

A. They replace the need for human decision-making entirely
B. They enhance automation and scalability of processes
C. They eliminate all data privacy concerns in business operations
D. They require no maintenance or updates once implemented

Answer: B

Explanation:
The primary benefit of using LLMs in business applications is their ability to enhance automation and scalability, making processes more efficient and adaptable to large-scale needs. Option A is incorrect because LLMs augment, rather than fully replace, human decision-making-human oversight remains critical. Option B is false as LLMs do not inherently eliminate privacy concerns; data privacy must still be managed (e.g., through SAP's privacy-preserving techniques like differential privacy). Option C is inaccurate since LLMs require ongoing maintenance, updates, and monitoring to remain effective. Option D is correct because LLMs automate tasks like document processing, content generation, and customer interaction, while their scalability allows businesses to handle increasing data volumes and user demands efficiently, as seen in SAP's integration with tools like Joule and SAP Business AI.

NEW QUESTION # 56
What is a part of LLM context optimization?

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

Answer: C

NEW QUESTION # 57
Which of the following is a benefit of using Retrieval Augmented Generation?

A. It reduces the computational resources required for language modeling.
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 eliminates the need for fine-tuning LLMs for specific tasks.

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 # 58
What are some components of the training pipeline in SAP AI Core? Note: There are 2 correct answers to this question.

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

Answer: A,B

Explanation:
The training pipeline in SAP AI Core comprises several key components that facilitate the development and deployment of machine learning models.
1. Input Datasets Stored in a Hyperscaler Object Store:
* Data Storage:Input datasets are often stored in hyperscaler object stores, which provide scalable and secure storage solutions. These datasets serve as the foundational data for training machine learning models.
* Integration:SAP AI Core integrates with various hyperscaler object stores, allowing seamless access to training data during the model development process.

NEW QUESTION # 59
What are some functionalities provided by SAP Al Core? Note: There are 3 correct answers to this question.

A. Continuous delivery and tenant isolation for scalability
B. Integration of Al services with business applications using a standardized API
C. Orchestration of Al workflows such as model training and inference
D. Monitoring and retraining models in SAP Al Core
E. Management of SAP S/4HANA cloud infrastructure

Answer: A,B,C

Explanation:
You're asking about the key functionalities of SAP AI Core. Here's a breakdown of the correct answers:
* A. Integration of AI services with business applications using a standardized API:SAP AI Core provides a standardized way to connect AI models and services to your existing business applications.
This means you can easily integrate AI capabilities into your core business processes, regardless of the specific AI technology you're using. This is done through APIs (Application Programming Interfaces), which allow different software systems to communicate with each other.
* B. Continuous delivery and tenant isolation for scalability:
* Continuous delivery:AI Core supports continuous delivery, which means you can quickly and easily deploy and update your AI models. This allows you to adapt to changing business needs and keep your AI solutions up-to-date.
* Tenant isolation:AI Core provides tenant isolation, which is important for security and scalability. This means that different users or departments within your organization can have their own separate AI environments, preventing interference and ensuring data privacy.
* C. Orchestration of AI workflows such as model training and inference:AI Core helps you manage the entire lifecycle of your AI models, including:
* Training:Automating the process of training your AI models on large datasets.
* Inference:Deploying your trained models and using them to make predictions or generate insights.
* Monitoring:Tracking the performance of your AI models over time.
Why the other options are incorrect:
* D. Management of SAP S/4HANA cloud infrastructure:While AI Core can be used with S/4HANA, it's not specifically designed to manage the cloud infrastructure of S/4HANA. That's handled by other SAP services.
* E. Monitoring and retraining models in SAP AI Core:While AI Core supports monitoring, the retraining of models is typically done using other tools and services within the SAP AI ecosystem.

NEW QUESTION # 60
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Pass Guaranteed Quiz Authoritative SAP - C-AIG-2412 - SAP Certified Associate - SAP Generative AI Developer Reliable Test Labs

SAP C-AIG-2412 Exam Syllabus Topics:

100% Pass-Rate C-AIG-2412 Reliable Test Labs & Leading Offer in Qualification Exams & Fantastic C-AIG-2412: SAP Certified Associate - SAP Generative AI Developer

SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q55-Q60):

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