test test ai gene

Match the components of a Retrieval Augmented Generation architecture to the diagram. Models (2 slots) Applications ( 2 slots) Retrieval (1 slot) Available options: Backend, Vector Databases, Frontend, Embedding Model, LLM. Box - Models- Vector Database Box-> Applications- Backend and Frontend Box-> Retrieval- Embedding Model and LLM. Box - Models- Embedding Model and LLM Box-> Applications- Vector Database Box- Retrieval- Backend and Frontend. Box - Models- Backend and Frontend Box-> Applications- Embedding Model and LLM Box-> Retrieval- Vector Database. Box - Models- Embedding Model and LLM Box- Applications- Backend and Frontend Box- Retrieval- Vector Database.

Which of the following steps must be performed to deploy LLMs in the generative Al hub?. 1. Provision SAP Al 2. Core Create a configuration 3. Run the booster. 1. Run the booster 2. Create service keys 3. Select the executable ID. 1. Provision SAP Al Core 2. Check for foundation model scenario 3. Create a configuration 4. Create a deployment. 1. Check for foundation model scenario 2. Create a deployment 3. Configuring entitlements.

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 random email content and send them to customers. Generate JSON strings based on extracted information. Generate a new SAP application based on the mail data. Train custom models based on the mail data.

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

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

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

Which of the following are features of the SAP Al Foundation? Note: There are 2 correct answers to this question. Al runtimes and lifecycle management. Ready-to-use Al services. Joule integration in SAP SuccessFactors. Open source Al model repository.

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

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

How does the Al API support SAP Al scenarios? Note: There are 2 correct answers to this question. By integrating Al services into business applications. By providing a unified framework for operating Al services. By managing Kubernetes clusters automatically. By integrating Al models into third-party platforms like AWS.

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

What is a significant risk associated with using LLMs?. Immediate accuracy without fine-tuning. Lack of scalability in business applications. Reduced computational requirements. Potential biases in generated content.

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. Creating custom evaluators that meet specific business needs. Automating prompt testing across various scenarios. Providing metrics to quantitatively assess response quality. Supporting low code evaluations using graphical user interface. Maintaining data privacy by using data masking techniques.

Which of the following statements accurately describe the RAG process? Note: There are 2 correct answers to this question. The retrieved content is combined with the LLM's capabilities to generate a response. 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 LLM directly answers the user's question without accessing external information.

You want to use the orchestration service through SAP's generative-Al-hub-sdk. What does the following code do? python code: from gen_ai_hub.orchestration.models.11m import LLM llm = LLM(name="gpt-40", version="latest", parameters={"max_tokens": 256, "temperature": 0.2}). Create the Orchestration Configuration. Define the LLM. Define the Template and Default Input Values. Run the Orchestration Request.

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

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

What does the Prompt Management feature of the SAP Al Iaunchpad allow users to do?. Create and edit prompts. Provide personalized user interactions. Interact with models through a conversational interface. Access and manage saved prompts and their versions.

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

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

Which of the following describes Large Language Models (LLMs)?. They utilize deep learning to process and generate human-like text. They are rule-based systems designed for specific tasks. They cannot process large datasets efficiently. They rely on predefined scripts for decision-making.

How does SAP ensure the enterprise-readiness of its Al solutions?. By using generic Al models without business context complying with Al ethics standards. By ensuring that Al models make bias-free decisions without human input. By implementing rigorous product standards for Al capabilities.

Which of the following are functionalities provided by the generative-Al-hub-SDK? Note: There are 2 correct answers to this question. Create chat responses and embeddings. Interact with LLMs. Configure SAP BTP credentials. Customize SAP Al Launchpad.

What is one primary benefit of using LLMs in business applications?. They eliminate the need for data security measures. They enhance automation and scalability of processes. They are only applicable for customer support scenarios. They require minimal computing power for training.

Which of the following must you do before connecting to a dataset in order to train a machine learning model in SAP Al Core? Note: There are 2 correct answers to this question. Store the dataset in the SAP HANA Vector Engine. Grant access rights to the SAP BTP cockpit. Store the dataset in a hyperscaler object store. Provide the storage secret to access the dataset.

Which of the following capabilities does the generative Al hub provide to developers? Note: There are 2 correct answers to this question. Code generation to extend SAP BTP applications. Tools for prompt engineering and experimentation. Proprietary LLMs exclusively. Integration of foundation models into applications.

What can be done once the training of a machine learning model has been completed in SAP Al Core? Note: There are 2 correct answers to this question. The model can be deployed for inferencing. The model can be deployed in SAP HANA. The model can be registered in the hyperscaler object store. The model's accuracy can be optimized directly in SAP HANA.

Which of the following sequence of steps does SAP recommend you use to solve a business problem using generative Al hub?. 1. Create a basic prompt in SAP Al Launchpad 2. Scale the solution using generative-ai-hub-sdk 3. Create a baseline evaluation method for the simple prompt 4. Enhance the prompts 5. Evaluate various models for the problem using generative-ai-hub-sdk. 1. Create a basic prompt in SAP AI Launchpad 2. Evaluate various models for the problem using generative-ai-hub-sdk 3. Scale the solution using generative-ai-hub-sdk 4. Create a baseline evaluation method for the simple prompt 5. Enhance the prompts. 1. Create a basic prompt in SAP Al Launchpad 2. Enhance the prompts 3. Create a baseline evaluation method for the simple prompt 4. Evaluate various models for the problem using generative-ai-hulb-sdk 5. Scale the solution using generative-ai-hulb-sdk.

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

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

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

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

Which of the following are grounding principles included in SAP's Al Ethics framework? Note: There are 3 correct answers to this question. Human agency and oversight. Maximize business profits. Store all user data for legal proceedings. Avoid bias and discrimination. Transparency and explainability.

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

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

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

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

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

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

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

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

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

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

What are some metrics to evaluate the effectiveness of a Retrieval Augmented Generation system? Note: There are 2 correct answers to this question. Relevance. Speed. Carbon footprint. Faithfulness.

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? python 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 onlycontains 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"]). Evaluate the performance of a language model using few-shot learning. Generate random examples for language model training. Preprocess a dataset for machine learning. Train a language model from scratch.

What capabilities does the Exploration and Development feature of the generative Al hub provide? Note: There are 2 correct answers to this question. Al playground and chat. Prompt editor and management. Automatic model selection. Develop and debug ABAP code.

What are some examples of generative Al technologies? Note: There are 2 correct answers to this question. Rule-based algorithms. Robotic process automation. Al models that generate new content based on training data. Foundation models.

What defines SAP's approach to LLMs?. Using proprietary transformer-based models exclusively. Ensuring ethical AI practices and seamless business integration. Prioritizing only the performance of open-source models. Avoiding partnerships with external AI providers.

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

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

What are some drivers for the rapid adoption of generative AI? Note: There are 2 correct answers to this question. Ease of use. Significant hardware cost savings. Wide availability. Availability of skilled developers.

What are some features of Joule? Note: There are 3 correct answers to this question. Downloading and processing data. Streamlining tasks with an Al assistant that knows your unique role. Generating standalone applications. Maintaining data privacy while offering generative Al capabilities. Providing coding assistance and content generation.

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

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

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

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

What are some SAP recommendations to evaluate pricing and rate information of model usage within SAP's generative Al hub? Note: There are 2 correct answers to this question. 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. Adopt best practice pricing strategies, such as outcome-based pricing.

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

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

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

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

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

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

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 Al hub in SAP AI Launchpad?. Prompt Editor. Prompt management. Chat. Administration.