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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q36-Q41):

NEW QUESTION # 36
What capabilities does the Exploration and Development feature of the generative Al hub provide? Note:
There are 2 correct answers to this question.

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

Answer: C,D

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 # 37
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. Management of SAP S/4HANA cloud infrastructure
C. Integration of Al services with business applications using a standardized API
D. Monitoring and retraining models in SAP Al Core
E. Continuous delivery and tenant isolation for scalability

Answer: A,C,E

NEW QUESTION # 38
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

A. Simplified model retraining and performance improvement.
B. Integration with non-SAP platforms like Azure and AWS.
C. Direct deployment of Al models to SAP HANA.
D. Centralized Al lifecycle management for all Al scenarios.

Answer: A,D

NEW QUESTION # 39
What is a Large Language Model (LLM)?

A. A database system optimized for storing large volumes of textual data.
B. An Al model that specializes in processing, understanding, and generating human language.
C. A gradient boosted decision tree algorithm for predicting text.
D. A rule-based expert system to analyze and generate grammatically correct sentences.

Answer: B

Explanation:
A Large Language Model (LLM) is an advanced AI model designed to handle various natural language processing tasks.
1. Definition and Purpose:
* Processing:LLMs analyze human language to understand syntax, semantics, and context.
* Understanding:They interpret the meaning behind text, enabling comprehension of nuanced language elements.
* Generating:LLMs can produce coherent and contextually appropriate text, facilitating tasks like content creation and translation.
2. Characteristics of LLMs:
* Scale:These models are trained on vast datasets, encompassing billions of words, which enhances their language capabilities.
* Architecture:LLMs typically utilize complex neural network architectures, such as transformers, to manage and process language data effectively.
3. Applications:
* Content Generation:Creating articles, summaries, and reports.
* Language Translation:Converting text from one language to another with high accuracy.
* Conversational Agents:Powering chatbots and virtual assistants to interact with users naturally.

NEW QUESTION # 40
You want to use the orchestration service through SAP's generative-Al-hub-sdk.
What does the following code do?
from gen_ai_hub.orchestration.models.11m import LLM
11m =
LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2})

A. Run the Orchestration Request
B. Define the LLM
C. Create the Orchestration Configuration
D. Define the Template and Default Input Values

Answer: B

NEW QUESTION # 41
......

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