TOP C-AIG-2412 VALID TEST BRAINDUMPS PASS CERTIFY | HIGH-QUALITY C-AIG-2412 RELIABLE PRACTICE MATERIALS: SAP CERTIFIED ASSOCIATE - SAP GENERATIVE AI DEVELOPER

Top C-AIG-2412 Valid Test Braindumps Pass Certify | High-quality C-AIG-2412 Reliable Practice Materials: SAP Certified Associate - SAP Generative AI Developer

Top C-AIG-2412 Valid Test Braindumps Pass Certify | High-quality C-AIG-2412 Reliable Practice Materials: SAP Certified Associate - SAP Generative AI Developer

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SAP C-AIG-2412 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 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 (Q28-Q33):

NEW QUESTION # 28
Which neural network architecture is primarily used by LLMs?

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

Answer: A

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 # 29
Which of the following are functionalities provided by the generative-Al-hub-SDK ? Note: There are 2 correct answers to this question.

  • A. Configure SAP BTP credentials
  • B. Interact with LLMs
  • C. Create chat responses and embeddings
  • D. Customize SAP AI Launchpad

Answer: B,C

Explanation:
The Generative AI Hub SDK offers functionalities that empower developers to:
1. Interact with Large Language Models (LLMs):
* Model Access:The SDK provides a developer-friendly way to consume foundational models available in the SAP Generative AI Hub, facilitating seamless interactions with these models.
2. Create Chat Responses and Embeddings:
* Natural Language Processing:With this SDK, developers can interact with models to create natural language completions, chat responses, and embeddings, enabling the development of sophisticated AI- driven applications.
Conclusion:
The Generative AI Hub SDK enables developers to interact with LLMs and create chat responses and embeddings, supporting the development of advanced AI functionalities within applications.


NEW QUESTION # 30
What capabilities does the Exploration and Development feature of the generative Al hub provide?
Note: There are 2 correct answers to this question.

  • A. Prompt editor and management
  • B. Automatic model selection
  • C. Al playground and chat
  • D. Develop and debug ABAP code

Answer: A,C


NEW QUESTION # 31
Why is generative Al gaining significant attention and investment in the current business landscape?
Note: There are 2 correct answers to this question.

  • A. It can replicate complex technical skills without training or quality control.
  • B. It can run entire business operations without human intervention.
  • C. It lowers barriers to adoption.
  • D. It only requires natural language skills to use.

Answer: C,D


NEW QUESTION # 32
What are some functionalities provided by SAP Al Core?
Note: There are 3 correct answers to this question.

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

Answer: A,B,D


NEW QUESTION # 33
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