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C-AIG-2412 Reliable Exam Book - Latest C-AIG-2412 Braindumps Sheet

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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

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 4

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.

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Latest SAP C-AIG-2412 Braindumps Sheet & Latest C-AIG-2412 Exam Pdf

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q45-Q50):

NEW QUESTION # 45
Which neural network architecture is primarily used by LLMs?

A. Convolutional Neural Networks (CNNs)
B. Recurrent neural network architecture
C. Transformer architecture with self-attention mechanisms
D. Sequential encoder-decoder architecture

Answer: C

Explanation:
Large Language Models (LLMs) primarily utilize the Transformer architecture, which incorporates self- attention mechanisms.
1. Transformer Architecture:
* Overview:Introduced in 2017, the Transformer architecture revolutionized natural language processing by enabling models to handle long-range dependencies in text more effectively than previous architectures.
GeeksforGeeks
* Components:The Transformer consists of an encoder-decoder structure, where the encoder processes input sequences, and the decoder generates output sequences.
2. Self-Attention Mechanisms:
* Functionality:Self-attention allows the model to weigh the importance of different words in a sequence relative to each other, enabling it to capture contextual relationships regardless of their position.
* Benefits:This mechanism facilitates parallel processing of input data, improving computational efficiency and performance in understanding complex language patterns.
3. Application in LLMs:
* Model Examples:LLMs such as GPT-3 and BERT are built upon the Transformer architecture, leveraging self-attention to process and generate human-like text.
* Advantages:The Transformer architecture's ability to manage extensive context and dependencies makes it well-suited for tasks like language translation, summarization, and question-answering.

NEW QUESTION # 46
Which of the following is a principle of effective prompt engineering?

A. Write vague and open-ended instructions to encourage creativity.
B. Combine multiple complex tasks into a single prompt.
C. Use precise language and providing detailed context in prompts.
D. Keep prompts as short as possible to avoid confusion.

Answer: C

NEW QUESTION # 47
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's accuracy can be optimized directly in SAP HANA.
B. The model can be deployed in SAP HANA.
C. The model can be deployed for inferencing.
D. The model can be registered in the hyperscaler object store.

Answer: C,D

NEW QUESTION # 48
What is a significant risk associated with using LLMs?

A. Complete elimination of human oversight in content creation
B. Potential biases in generated content
C. Unlimited processing power usage without cost control
D. Inability to generate text in multiple languages

Answer: B

Explanation:
A significant risk of using LLMs is the potential for biases in generated content, stemming from biases present in their training data. Option A is incorrect because LLMs do not inherently eliminate human oversight; oversight is often maintained, especially in enterprise settings like SAP's. Option B is false as LLMs can generate text in multiple languages, as seen with models like GPT-4. Option D, while a concern in terms of resource management, is not the most significant risk compared to bias, and cost control can be implemented. Option C is correct because biased outputs can lead to unfair decisions or misinformation, a risk SAP mitigates through its AI Ethics framework, which includes principles like avoiding bias and discrimination, ensuring responsible AI deployment.

NEW QUESTION # 49
Match the components of a Retrieval Augmented Generation architecture to the diagram.

Answer:

Explanation:

NEW QUESTION # 50
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