NEW RELIABLE C_AIG_2412 BRAINDUMPS SHEET 100% PASS | HIGH PASS-RATE C_AIG_2412: SAP CERTIFIED ASSOCIATE - SAP GENERATIVE AI DEVELOPER 100% PASS

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New Reliable C_AIG_2412 Braindumps Sheet 100% Pass | High Pass-Rate C_AIG_2412: SAP Certified Associate - SAP Generative AI Developer 100% Pass

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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q59-Q64):

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

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

Answer: A,C,E


NEW QUESTION # 60
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note:
There are 2 correct answers to this question.

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

Answer: A,C

Explanation:
The Exploration and Development feature of SAP's Generative AI Hub provides several capabilities to facilitate AI solution development:
1. AI Playground and Chat:
* Interactive Environment:The AI playground offers an interactive space for developers to experiment with various AI models, test prompts, and observe outputs in real-time.
* Conversational Interface:The chat functionality enables users to engage in dialogue with AI models, refining prompts and understanding model behavior through iterative interactions.
2. Prompt Editor and Management:
* Prompt Creation:The prompt editor allows developers to craft and modify prompts tailored to specific business needs, enhancing the precision of AI responses.
* Prompt Organization:Prompt management tools facilitate the organization, versioning, and storage of prompts, ensuring efficient retrieval and reuse in various projects.


NEW QUESTION # 61
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note: There are 2 correct answers to this question.

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

Answer: A,C


NEW QUESTION # 62
Which of the following describes Large Language Models (LLMs)?

  • A. They rely on traditional rule-based algorithms to generate responses
  • B. They can only process numerical data and are not capable of understanding text
  • C. They generate responses based on pre-defined templates without learning from data
  • D. They utilize deep learning to process and generate human-like text

Answer: D

Explanation:
Large Language Models (LLMs) are advanced AI systems that leverage deep learning techniques, specifically transformer architectures with self-attention mechanisms, to process and generate human-like text. Option A is incorrect because LLMs do not rely on traditional rule-based systems; they learn patterns from vast datasets. Option C is false as LLMs are designed for text processing, not limited to numerical data. Option D is also inaccurate since LLMs generate responses based on learned patterns, not static templates. Option B is correct, reflecting how LLMs, like those accessible via SAP's Generative AI Hub, use deep learning to understand context, semantics, and generate coherent text for applications such as chatbots, translations, and content creation.


NEW QUESTION # 63
What are the applications of generative Al that go beyond traditional chatbot applications? Note: There are 2 correct answers to this question.

  • A. To follow a specific schema - human input, Al processing, and output for human consumption.
  • B. To produce outputs based on software input.
  • C. To interpret human instructions and control software systems always producing output for human consumption.
  • D. To interpret human instructions and control software systems without necessarily producing output for human consumption.

Answer: C,D

Explanation:
* C. To interpret human instructions and control software systems without necessarily producing output for human consumption.This is a key area where generative AI is breaking new ground. Think of it as AI acting as a "middleman" between you and software. Here are some examples:
* Automating complex tasks:You could tell the AI to "optimize this database for performance" or
"find and fix security vulnerabilities in this code." The AI would then interact with the software systems to carry out these instructions, without needing to show you every step or result.
* Controlling robots or IoT devices:Imagine instructing an AI to "adjust the lighting in the meeting room" or "have the robot retrieve the package from the warehouse." The AI translates your instructions into actions for those systems.
* Managing cloud resources:AI could dynamically allocate cloud resources based on your needs, scaling them up or down without your direct intervention.
* D. To interpret human instructions and control software systems always producing output for human consumption.This is more in line with traditional chatbot interactions, but with a broader scope. It's about AI generating outputs that are directly useful or informative for humans. Examples include:
* Creating realistic images or videos:Based on your description, the AI could generate a photorealistic image of a new product design or a short video clip for a marketing campaign.
* Writing different kinds of creative text formats:AI can generate stories, poems,articles, summaries, and even code, all tailored to your specifications.
* Providing personalized recommendations:AI can analyze your preferences and provide recommendations for products, services, or information.
Why the other options are incorrect:
* A. To produce outputs based on software input.This is a general capability of AI, not something specific to generative AI or beyond chatbots. Many AI systems analyze software input (like sensor data or log files) to produce outputs.
* B. To follow a specific schema - human input, AI processing, and output for human consumption.
This describes the basic interaction pattern of many AI systems, including chatbots. It's not something that specifically differentiates generative AI or goes beyond typical chatbot applications.


NEW QUESTION # 64
......

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