SKIBIIDI TOILET ASK

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

How can Joule improve workforce productivity? Note: There are 2 correct answers to this question. 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.

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 identifying human, technical, and exfiltration risks through an Al Security Taskforce. By focusing on technological advancement only. By relying on external vendors to manage security threats.

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

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

What is Machine Learning (ML)?. A subset of Al 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 Al techniques. A form of Al 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 perception, and decision-making.

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

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

What contract type does SAP offer for Al 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.

Why is generative Al gaining significant attention and investment in the current business landscape? Note: There are 2 correct answers to this question. 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 features of Joule? Note: There are 3 correct answers to this question. Generating standalone applications. Providing coding assistance and content generation. Maintaining data privacy while offering generative Al capabilities. Streamlining tasks with an Al assistant that knows your unique role. Downloading and processing data.

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

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

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

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 Al model. Create a deployment for orchestration. Modify the underlying Al models.

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

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

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

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. 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 does the Prompt Management feature of the SAP AI launchpad 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 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. Meta prompting. One-shot prompting.

Which of the following steps must be performed to deploy LLMs in the generative Al 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.

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}). Define the LLM. Run the Orchestration Request. Create the Orchestration Configuration. Define the Template and Default Input Values.

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

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

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 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. To interpret human instructions and control software systems always producing output for human consumption.

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 '\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.

What are some benefits of using an SDK for evaluating prompts within the context of generative Al? 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.

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?. Chat. Prompt management. Administration. Prompt Editor.

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

Where can you configure language models in generative Al 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.

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

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. Automatic model selection. Develop and debug ABAP code. Prompt editor and management.

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 statement best describes the Chain-of-Thought (COT) prompting technique?. Linking multiple Al 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.

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.

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

What is a Large Language Model (LLM)?. A rule-based expert system to analyze and generate grammatically correct sentences. An Al 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.

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.

What are some use cases for fine-tuning of a model? Note: There are 2 correct answers to this question. 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 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.

Match the components of a Retrieval Augmented Generation architecture to the diagram. Embedding Model. LLM. Frontend. Vector Database. Backend.

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.

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 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.

What is the goal of prompt engineering?. To replace human decision-making with automated processes. 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.

Which of the following statements accurately describe the RAG process? Note: There are 2 correct answers to this question. 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.

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.

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.

What can be done once the training of a machine learning model has been completed in SAP AI Core? Note: There are 2 correct answers to this question. 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.

What are some components of the training pipeline in SAP AI Core? Note: There are 2 correct answers to this question. 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.

How does the Al API support SAP AI 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 integrating Al models into third-party platforms like AWS. By managing Kubernetes clusters automatically.

What must be defined in an executable to train a machine learning model using SAP AI Core? Note: There are 2 correct answers to this question. 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.

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

How do resource groups in SAP AI Core improve the management of machine learning workloads? Note: There are 2 correct answers to this question. 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 Al artifacts.

What does SAP recommend you do before you start training a machine learning model in SAP AI Core? Note: There are 3 correct answers to this question. 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 Al Launchpad. Register the input dataset in SAP AI Core.

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. Continuous delivery and tenant isolation for scalability. Orchestration of Al workflows such as model training and inference. Management of SAP S/4HANA cloud infrastructure. Monitoring and retraining models in SAP Al Core.

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 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.