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SAP Certified Associate - SAP Generative AI Developer Sample Questions (Q13-Q18):

NEW QUESTION # 13
Which of the following capabilities does the generative Al hub provide to developers? Note: There are 2 correct answers to this question.

A. Code generation to extend SAP BTP applications
B. Integration of foundation models into applications
C. Proprietary LLMs exclusively
D. Tools for prompt engineering and experimentation

Answer: A,D

NEW QUESTION # 14
What are some benefits of the SAP AI Launchpad? Note: There are 2 correct answers to this question.

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

Answer: A,B

Explanation:
SAP AI Launchpad offers several benefits that enhance the development, deployment, and management of AI models within an organization.
1. Centralized AI Lifecycle Management for All AI Scenarios:
* Unified Platform:SAP AI Launchpad provides a centralized platform to manage the entire AI lifecycle, including model development, training, deployment, monitoring, and maintenance.
* Efficiency:This centralized approach streamlines workflows, reduces complexity, and ensures consistency across various AI projects and scenarios.

NEW QUESTION # 15
Which neural network architecture is primarily used by LLMs?

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

Answer: C

NEW QUESTION # 16
You want to assign urgency and sentiment categories to a large number of customer emails. You want to get a valid json string output for creating custom applications. You decide to develop a prompt for the same using generative Al hub.
What is the main purpose of the following code in this context?
prompt_test = """Your task is to extract and categorize messages. Here are some examples:
{{?technique_examples}}
Use the examples when extract and categorize the following message:
{{?input}}
Extract and return a json with the following keys and values:
- "urgency" as one of {{?urgency}}
- "sentiment" as one of {{?sentiment}}
"categories" list of the best matching support category tags from: {{?categories}} Your complete message should be a valid json string that can be read directly and only contains the keys mentioned in t import random random.seed(42) k = 3 examples random. sample (dev_set, k) example_template = """<example> {example_input} examples
' --- '.join([example_template.format(example_input=example ["message"], example_output=json.dumps (example[ f_test = partial (send_request, prompt=prompt_test, technique_examples examples, **option_lists) response = f_test(input=mail["message"])

A. Train a language model from scratch
B. Preprocess a dataset for machine learning
C. Generate random examples for language model training
D. Evaluate the performance of a language model using few-shot learning

Answer: D

NEW QUESTION # 17
Which of the following steps must be performed to deploy LLMs in the generative Al hub?

A. Provision SAP AI Core
*Check for foundation model scenario
*Create a configuration
*Create a deployment
B. Provision SAP AI
*Core Create a configuration
*Run the booster
C. Run the booster
*Create service keys
*Select the executable ID
D. Check for foundation model scenario
*Create a deployment
*Configuring entitlements

Answer: A

Explanation:
Deploying Large Language Models (LLMs) in SAP's Generative AI Hub involves a structured process:
1. Provision SAP AI Core:
* Setup:Ensure that SAP AI Core is provisioned in your SAP Business Technology Platform (BTP) account to manage AI workloads.
2. Check for Foundation Model Scenario:
* Validation:Verify the availability of the foundation model scenario within SAP AI Core to confirm that the necessary resources and configurations are in place for deploying LLMs.
3. Create a Configuration:
* Configuration Setup:Define the parameters and settings required for the LLM deployment, including model specifications and resource allocations.
4. Create a Deployment:
* Deployment Execution:Initiate the deployment process within SAP AI Core, making the LLM available for integration and use within your applications.

NEW QUESTION # 18
......

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