Dev_GEN_TEST

What is Machine Learning (ML)?. A subset of AI that focuses on enabling computer systems to learn and improve from experience or data. A statistical method for data processing that does not involve any AI techniques. A form of AI that only focuses on creating new content, including text, images, sound, and videos. A technology that equips machines with human-like capabilities such as problem-solving, visual.

Which of the following is a benefit of using Retrieval Augmented Generation?. It allows LLMs to access and utilize information beyond their initial training data. It enables LLMs to learn new languages without additional training. It eliminates the need for fine-tuning LLMs for specific tasks. It reduces the computational resources required for language modeling.

You want to download a JSON output for a prompt and the response. Which of the following interfaces can you use in SAP's generative AI hub in SAP AI Launchpad?. Chat. Prompt management. Administration. Prompt Editor.

Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP AI Core? (2 correct answers). A. Store the dataset in a hyperscaler object store. Grant access rights to the SAP BTP cockpit. Provide the storage secret to access the dataset. Store the dataset in the SAP HANA Vector Engine.

What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system? (2 correct answers). Carbon footprint. Faithfulness. Speed. Relevance.

What can be done once the training of a machine learning model has been completed in SAP AI Core? (2 correct answers). The model can be deployed in SAP HANA. The model's accuracy can be optimized directly in SAP HANA. The model can be deployed for inferencing. The model can be registered in the hyperscaler object store.

You want to assign urgency and sentiment categories to a large number of customer emails. 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 "\n---\n' 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"]). Generate random examples for language model training. Evaluate the performance of a language model using few-shot learning. Train a language model from scratch. Preprocess a dataset for machine learning.

Why would a user include formatting instructions within a prompt?. To force the model to separate relevant and irrelevant output. To ensure the model's response follows a desired structure or style. To increase the faithfulness of the output. To redirect the output to another software program.

Which technique is used to supply domain-specific knowledge to an LLM?. Domain-adaptation training. Prompt template expansion. Retrieval-Augmented Generation. Fine-tuning the model on general data.

Which neural network architecture is primarily used by LLMs?. Transformer architecture with self-attention mechanisms. Recurrent neural network architecture. Convolutional Neural Networks (CNNs). Sequential encoder-decoder architecture.

What are some characteristics of the SAP generative AI hub? (2 correct answers). A. It operates independently of SAP's partners and ecosystem. It ensures relevant, reliable, and responsible business AI. It only supports traditional machine learning models. It provides instant access to a wide range of large language models (LLMs).

Which of the following steps must be performed to deploy LLMs in the generative AI hub?. Run the booster •Create service keys •Select the executable ID. Provision SAP AI Core •Check for foundation model scenario •Create a configuration •Create a deployment. Check for foundation model scenario •Create a deployment •Configuring entitlements. Provision SAP AI Core •Create a configuration •Run the booster.

Which of the following describes Large Language Models (LLMs)?. They rely on traditional rule-based algorithms to generate responses. They utilize deep learning to process and generate human-like text. They can only process numerical data and are not capable of understanding text. They generate responses based on pre-defined templates without learning from data.

What is a Large Language Model (LLM)?. A rule-based expert system to analyze and generate grammatically correct sentences. An AI model that specializes in processing, understanding, and generating human language. A database system optimized for storing large volumes of textual data. A gradient boosted decision tree algorithm for predicting text.

What is a significant risk associated with using LLMs?. Complete elimination of human oversight in content creation. Inability to generate text in multiple languages. Potential biases in generated content. Unlimited processing power usage without cost control.

Why is generative AI gaining significant attention and investment in the current business landscape? (2 correct answers). It lowers barriers to adoption. It can replicate complex technical skills without training or quality control. It can run entire business operations without human intervention. It only requires natural language skills to use.

What are some functionalities provided by SAP AI Core? (3 correct answers). Integration of AI services with business applications using a standardized API. Continuous delivery and tenant isolation for scalability. Orchestration of AI workflows such as model training and inference. Management of SAP S/4HANA cloud infrastructure. Monitoring and retraining models in SAP AI Core.

What is the goal of prompt engineering?. To replace human decision-making with automated processes. To craft inputs that guide AI systems in generating desired outputs. To optimize hardware performance for AI computations. To develop new neural network architectures for AI models.

Which of the following are grounding principles included in SAP's AI Ethics framework? (3 correct answers). Transparency and explainability. Human agency and oversight. Avoid bias and discrimination. Store all user data for legal proceedings. Maximize business profits.

How can Joule improve workforce productivity? (2 correct answers). By maintaining strict adherence to data privacy regulations. By resolving hardware malfunctions. By offering generic task recommendations unrelated to specific roles. By providing context-based role-specific task assistance.

What are some examples of generative AI technologies? (2 correct answers). AI models that generate new content based on training data. Rule-based algorithms. Robotic process automation. Foundation models.

How do resource groups in SAP AI Core improve the management of machine learning workloads? (2 correct answers). They ensure workload separation for different tenants or departments. They enhance pipeline execution speeds through workload distribution. They enable simultaneous orchestration of Kubernetes clusters. They provide isolation for datasets and AI artifacts.

Which of the following is unique about SAP's approach to AI?. SAP's deep integration of AI with business processes and analytics. Offering AI capabilities in their future products as of 2025. Utilizing AI mainly for marketing purposes. Focusing AI solely on customer support services.

What are the benefits of SAP's generative AI hub? (2 correct answers). Accelerate AI development with flexible access to a broad range of models. Provide libraries for no-code development. Build custom AI solutions and extend SAP applications. Send your data to various LLM providers for training feedback.

What are some benefits of the SAP AI Launchpad? (2 correct answers). Direct deployment of AI models to SAP HANA. Integration with non-SAP platforms like Azure and AWS. Centralized AI lifecycle management for all AI scenarios. Simplified model retraining and performance improvement.

What must be defined in an executable to train a machine learning model using SAP AI Core? (2 correct answers). Pipeline containers to be used. Infrastructure resources such as CPUs or GPUs. User scripts to manually execute pipeline steps. Deployment templates for SAP AI Launchpad.

How can few-shot learning enhance LLM performance?. By enhancing the model's computational efficiency. By providing a large training set to improve generalization. By reducing overfitting through regularization techniques. By offering input-output pairs that exemplify the desired behavior.

Which of the following executables in generative AI hub works with Anthropic models?. GCP Vertex AI. Azure OpenAI Service. SAP AI Core. AWS Bedrock.

What is the purpose of splitting documents into smaller overlapping chunks in a RAG system?. To simplify the process of training the embedding model. To enable the matching of different relevant passages to user queries. To improve the efficiency of encoding queries into vector representations. To reduce the storage space required for the vector database.

What does SAP recommend you do before you start training a machine learning model in SAP AI Core? (3 correct answers). Configure the training pipeline using templates. Define the required infrastructure resources for training. Perform manual data integration with SAP HANA. Configure the model deployment in SAP AI Launchpad. Register the input dataset in SAP AI Core.

Which statement best describes the Chain-of-Thought (COT) prompting technique?. Linking multiple AI models in sequence, where each model's output becomes the input for the next model in the chain. Writing a series of connected prompts creating a chain of related information. Concatenating multiple related prompts to form a chain, guiding the model through sequential reasoning steps. Connecting related concepts by having the LLM generate chains of ideas.

What is the primary function of the generative AI hub in SAP's AI Foundation?. To serve as an abstraction layer to access a range of foundation AI models. To provide ready-to-use AI services for document processing. To store embeddings of unstructured data for semantic data retrieval. To manage the AI lifecycle efforts end-to-end.

What are some features of Joule? (3 correct answers). Generating standalone applications. Providing coding assistance and content generation. Maintaining data privacy while offering generative AI capabilities. Streamlining tasks with an AI assistant that knows your unique role. Downloading and processing data.

What capabilities does the Exploration and Development feature of the generative AI hub provide? (2 correct answers). AI playground and chat. Automatic model selection. Develop and debug ABAP code. Prompt editor and management.

Which of the following capabilities does the generative AI hub provide to developers? (2 correct answers). Proprietary LLMs exclusively. Code generation to extend SAP BTP applications. Tools for prompt engineering and experimentation. Integration of foundation models into applications.

How does SAP ensure the enterprise-readiness of its AI solutions?. By implementing rigorous product standards for AI capabilities. By ensuring that AI models make bias-free decisions without human input. By using generic AI models without business context complying with AI ethics standards. By managing all AI lifecycle steps solely through open-source tools.

Which of the following statements accurately describe the RAG process? (2 correct answers). The user's question is used to search a knowledge base or a set of documents. The embedding model stores the generated answers for future reference. The retrieved content is combined with the LLM's capabilities to generate a response. The LLM directly answers the user's question without accessing external information.

How does the AI API support SAP AI scenarios? (2 correct answers). By integrating AI services into business applications. By providing a unified framework for operating AI services. By integrating AI models into third-party platforms like AWS. By managing Kubernetes clusters automatically.

What advantage can you gain by leveraging different models from multiple providers through the SAP's generative AI hub?. Get more training data for new models. Train new models using SAP and non-SAP data. Enhance the accuracy and relevance of AI applications that use SAP's data assets. Design new product interfaces for SAP applications.

What are some components of the training pipeline in SAP AI Core? (2 correct answers). Input datasets stored in a hyperscaler object store. Executables that define the training process. The SAP HANA database for model storage. Automated deployment to Kubernetes clusters.

Which of the following are features of the SAP AI Foundation? (2 correct answers). Ready-to-use AI services. AI runtimes and lifecycle management. Open source AI model repository. Joule integration in SAP SuccessFactors.

Which of the following are functionalities provided by the generative-ai-hub-SDK? (2 correct answers). Interact with LLMs. Configure SAP BTP credentials. Customize SAP AI Launchpad. Create chat responses and embeddings.

Which of the following sequence of steps does SAP recommend you use to solve a business problem using generative AI hub?. Create a basic prompt •Evaluate various models •Scale the solution •Create a baseline •Enhance prompts. Create a basic prompt •Enhance the prompts •Create a baseline evaluation method •Evaluate various models •Scale the solution. Create a basic prompt •Scale the solution •Create a baseline •Enhance prompts •Evaluate various models.

What is a part of LLM context optimization?. Reducing the model's size to improve efficiency. Adjusting the model's output format and style. Enhancing the computational speed of the model. Providing the model with domain-specific knowledge needed to solve a problem.

You want to extract useful information from customer emails to augment existing applications in your company. How can you use generative-ai-hub-sdk in this context?. Generate a new SAP application based on the mail data. Generate JSON strings based on extracted information. Generate random email content and send them to customers. Train custom models based on the mail data.

What are some use cases for fine-tuning of a model? (2 correct answers). To introduce new knowledge to a model in a resource-efficient way. To quickly create iterations on a new use case. To sanitize model outputs. To customize outputs for specific types of inputs.

What does the Prompt Management feature of the SAP AI Launchpad allow users to do? (2 correct answers). Create and edit prompts. Provide personalized user interactions. Interact with models through a conversational interface. Access and manage saved prompts and their versions.

Which of the following techniques uses a prompt to generate or complete subsequent prompts (streamlining the prompt development process), and to effectively guide AI model responses?. Chain-of-thought prompting. Few-shot prompting. Meta prompting. One-shot prompting.

You want to use the orchestration service through SAP's generative-ai-hub-sdk. What does the following code do? python from gen_ai_hub.orchestration.models.llm import LLM llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2}). Define the LLM. Run the Orchestration Request. Create the Orchestration Configuration. Define the Template and Default Input Values.

Which of the following is a principle of effective prompt engineering?. Use precise language and providing detailed context in prompts. Combine multiple complex tasks into a single prompt. Keep prompts as short as possible to avoid confusion. Write vague and open-ended instructions to encourage creativity.

What are some SAP recommendations to evaluate pricing and rate information of model usage within SAP's generative AI hub? (2 correct answers). Adopt best practice pricing strategies, such as outcome-based pricing. Weigh the cost of using advanced models against the expected return on investment. Avoid subscription-based pricing models. Use pricing models that have fixed rates irrespective of the usage patterns.

What are some drivers for the rapid adoption of generative AI? (2 correct answers). Availability of skilled developers. Significant hardware cost savings. Wide availability. Ease of use.

What are some benefits of using an SDK for evaluating prompts within the context of generative AI? Note: There are 3 correct answers to this question. Maintaining data privacy by using data masking techniques. Creating custom evaluators that meet specific business needs. Automating prompt testing across various scenarios. Supporting low code evaluations using graphical user interface. Providing metrics to quantitatively assess response quality.

What are some benefits of SAP Business AI? Note: There are 3 correct answers to this question. Intelligent business document processing. Face detection and face recognition. Automatic human emotion recognition. AI-powered forecasting and predictions. Personalized recommendations based on AI algorithms.

Where can you configure language models in generative AI hub?. The Configuration tab within ML Operations in SAP AI Launchpad. The Models tab in Prompt Editor. The Configuration tab of the SAP BTP cockpit. The Orchestration tab in SAP AI Launchpad.

What are the applications of generative AI that go beyond traditional chatbot applications? Note: There are 2 correct answers to this question. To produce outputs based on software input. To follow a specific schema - human input, AI processing, and output for human consumption. To interpret human instructions and control software systems without necessarily producing output for human consumption. To interpret human instructions and control software systems always producing output for human consumption.

Which of the following steps is NOT a requirement to use the Orchestration service?. Get an auth token for orchestration. Create an instance of an AI model. Create a deployment for orchestration. Modify the underlying AI models.

What is the primary function of the embedding model in a RAG system?. To generate responses based on retrieved documents and user queries. To encode queries and documents into vector representations for comparison. To evaluate the faithfulness and relevance of generated answers. To store vector representations of documents and search for relevant passages.

What contract type does SAP offer for AI ecosystem partner solutions?. Annual subscription-only contracts. All-in-one contracts, with services that are contracted through SAP. Pay-as-you-go for each partner service. Bring Your Own License (BYOL) for embedded partner solutions.

What is one primary benefit of using LLMs in business applications?. They replace the need for human decision-making entirely. They eliminate all data privacy concerns in business operations. They require no maintenance or updates once implemented. They enhance automation and scalability of processes.

How does SAP deal with vulnerability risks created by generative AI? Note: There are 2 correct answers to this question. By implementing responsible AI use guidelines and strong product security standards. By identifying human, technical, and exfiltration risks through an AI Security Taskforce. By focusing on technological advancement only. By relying on external vendors to manage security threats.

What defines SAP's approach to LLMs?. Prioritizing the development of proprietary LLMs with no integration to existing systems. Focusing solely on reducing the computational cost of training LLMs. Ensuring ethical AI practices and seamless business integration. Limiting LLM usage to non-business applications only.

What are some advantages of using agents in training models? Note: There are 2 correct answers to this question. To guarantee accurate decision making in complex scenarios. To improve the quality of results. To streamline LLM workflows. To eliminate the need for human oversight.