최신 C1000-185 무료덤프 - IBM watsonx Generative AI Engineer

문제1

You are tasked with deploying a generative AI solution for a client who operates in the healthcare sector. Due to the sensitive nature of the data, the client requires a highly secure deployment with continuous monitoring for regulatory compliance.
Which role is primarily responsible for ensuring the AI solution is compliant with these security and regulatory requirements?

A. AI Model Developer

B. Security Engineer

C. Chief Technology Officer (CTO)

D. Data Privacy Officer

정답: B

문제2

After conducting a prompt tuning experiment in IBM Watsonx, which two statistical metrics are most indicative of a model's ability to generalize well to unseen data? (Select two)

A. Low validation loss

B. High training accuracy

C. Low training loss

D. Large difference between training and validation accuracy

E. Small difference between training and validation loss

정답: A,E

문제3

You are tasked with fine-tuning a language model using a prompt-tuning approach on a dataset consisting of customer service chat logs. The goal is to optimize the model's ability to generate polite and contextually appropriate responses.
Which of the following steps are essential when preparing the dataset for prompt-tuning in this context? (Select two)

A. Remove any conversations that contain excessive user slang or misspellings.

B. Ensure each conversation includes both customer input and agent response as context for the model.

C. Convert all user queries into lowercase to reduce noise in the dataset.

D. Separate the dataset into training, validation, and test subsets.

E. Ensure all examples in the dataset follow the exact same input-output format.

정답: B,D

문제4

You are tasked with developing a RAG system that integrates a transformer-based language model with a large document corpus. To speed up the development process, you are considering using specialized libraries designed for RAG.
Which of the following reasons best explains why these libraries are essential for your development process?

A. They provide pre-trained retrieval models and generators, eliminating the need for any fine-tuning or customization of the system.

B. They allow for the retrieval of documents based purely on keyword search, optimizing for exact match over semantic similarity.

C. They streamline the integration of retrievers and generators, providing out-of-the-box support for embedding models and vector databases.

D. They provide a graphical interface for users to build RAG systems without requiring any programming knowledge.

정답: C

문제5

How can developers leverage Prompt Lab in IBM Watsonx to build reusable prompts for a conversational AI system that handles multiple topics?

A. By utilizing Prompt Lab's automatic suggestion feature, which builds new prompts based on the system's training data.

B. By creating a single prompt template that adapts to all user inputs regardless of the subject.

C. By generating a unique prompt for each possible user query to ensure maximum precision.

D. By designing prompts with dynamic variables for user-specific information, allowing for flexibility across different topics.

정답: D

문제6

You are tasked with designing a prompt to fine-tune an IBM Watsonx model to summarize legal documents. The summaries must include only factual information, highlight key legal terms, and exclude any personal interpretations or subjective analysis.
Which of the following is the best prompt to achieve this goal?

A. "Create a brief summary of this legal document, ensuring to exclude any legal jargon and simplifying the content for a layperson audience."

B. "Provide a summary of this legal document, focusing on factual information, including key legal terms and avoiding personal interpretation or subjective analysis."

C. "Generate a detailed and engaging summary of this legal document, adding your insights to clarify complex legal points for the reader."

D. "Summarize this legal document, focusing on key arguments and providing an analysis of the potential outcomes of the case."

정답: B

문제7

You are tasked with reconstructing a prompt used in an AI-based customer support chatbot. The current prompt generates lengthy, detailed answers that are often overly verbose and unnecessary for the customer's inquiries. Your objective is to optimize this prompt to reduce model usage costs without compromising the quality of the responses.
Which of the following strategies is the most effective in reducing the cost of using a Generative AI model while maintaining response relevance and clarity?

A. Reducing the token limit in the model configuration to restrict the length of responses.

B. Splitting the prompt into multiple sub-prompts to generate responses for different sections separately.

C. Revising the prompt to make it more specific by narrowing the scope of expected responses.

D. Using temperature scaling to increase randomness and reduce token usage.

정답: C

문제8

You are working with a Watsonx Generative AI model to create marketing content that balances creativity with efficiency. The goal is to generate engaging content within a predefined time limit without compromising on quality.
Given this context, which two optimization strategies will most effectively help you achieve both speed and content quality? (Select two)

A. Implement early stopping criteria based on token repetition to avoid lengthy generation.

B. Reduce the batch size to decrease training time and speed up generation.

C. Apply top-k sampling with k = 50 to ensure diverse and creative outputs.

D. Increase the model's learning rate to accelerate content generation.

E. Use beam search with a beam width of 1 to minimize computation time.

정답: A,C

문제9

You are tasked with fine-tuning a pre-trained generative AI model for customer support automation. The goal is to enhance the model's performance in generating concise, relevant answers to frequently asked questions (FAQs). To do this, you need to optimize the prompt-tuning process.
Which two of the following techniques would be most effective for creating a prompt-tuned model for this purpose? (Select two)

A. Utilize reinforcement learning to penalize long or irrelevant responses during the tuning phase, optimizing the model for concise output.

B. Limit the training data to 100 samples of FAQs to prevent overfitting and keep the prompt-tuning process computationally efficient.

C. Use a large set of domain-specific FAQs and fine-tune the model using those examples, ensuring that prompts are tailored to each type of question.

D. Shorten the prompts to the minimum number of words needed to address the FAQ directly, focusing on the key terms that drive the correct output.

E. Introduce randomness in prompts by using variations in the wording for similar FAQs to improve the model's adaptability to different styles.

정답: C,D

문제10

You are building a question-answering system using a Retrieval-Augmented Generation (RAG) architecture. You are deciding whether to incorporate a vector database into the system to handle the document embeddings.
Under which of the following circumstances is the use of a vector database most appropriate?

A. When the corpus consists mainly of short, structured text like JSON records and traditional SQL indexing will suffice

B. When the text corpus consists entirely of predefined categories that can be handled by simple keyword matching algorithms

C. When the data consists primarily of binary files such as images and videos, and full-text search is required

D. When real-time similarity search over high-dimensional embeddings is needed for large-scale unstructured text data

정답: D

문제11

When optimizing the tuning process in IBM Watsonx Tuning Studio for a Generative AI model, which approach would best reduce training time and computational cost while maintaining model performance?

A. Perform full-scale retraining of the model for each new task to ensure maximum adaptability and accuracy.

B. Focus the tuning on adjusting only the model's last few layers, which are responsible for task-specific outputs, while leaving the majority of the model unchanged.

C. Increase the batch size and reduce the learning rate simultaneously to speed up the tuning process and minimize training iterations.

D. Use all available training data, including unrelated examples, to ensure the model has a broad understanding of multiple tasks before tuning.

정답: B

문제12

You are tuning a generative AI model to control the length of the generated responses.
Which of the following parameter configurations will ensure that the model generates responses that are at least 50 tokens long but no longer than 150 tokens?

A. Setting the minimum tokens to 50 and maximum tokens to 150

B. Setting the minimum tokens to 150 and maximum tokens to 50

C. Setting no minimum token value but configuring the maximum tokens to 150

D. Setting the maximum tokens to 50 and minimum tokens to 150

정답: A

문제13

When analyzing the results of a prompt tuning experiment, which two of the following actions are most appropriate if you observe a consistently high variance in model predictions across different prompt templates? (Select two)

A. Enable regularization techniques like dropout

B. Tune the prompt templates further by standardizing the structure

C. Increase the batch size during training

D. Increase the number of training samples used for tuning

E. Add more layers to the model to increase complexity

정답: B,D

문제14

IBM Watsonx Tuning Studio offers several benefits when fine-tuning pre-trained models for specific tasks.
Which of the following is not a key benefit of using Tuning Studio?

A. Tuning Studio offers fine-tuning with minimal data, allowing users to adapt models to niche tasks without needing large datasets.

B. Tuning Studio enables real-time, dynamic adjustments to the model's architecture during inference to handle new tasks.

C. Tuning Studio allows selective parameter updates, reducing the need to retrain the entire model for each new task.

D. Tuning Studio integrates with existing AI infrastructure to streamline model fine-tuning without requiring complex deployment processes.

정답: B

문제15

While working with IBM Watsonx to generate synthetic data, you import a sensitive dataset containing personally identifiable information (PII). You are tasked with anonymizing the imported data before proceeding with any fine-tuning or data augmentation.
Which of the following steps is the most appropriate to ensure proper anonymization?

A. Generate a synthetic version of the dataset that removes all PII automatically.

B. Apply a differential privacy algorithm that ensures no individual data point can be traced back to a specific user.

C. Use a hashing algorithm to replace PII fields while retaining the ability to reverse the process if needed.

D. Randomly shuffle the sensitive data fields to prevent direct re-identification.

정답: B

문제16

You are tasked with implementing a Retrieval-Augmented Generation (RAG) pipeline for a customer service chatbot. Your goal is to ensure that the model can query a vast knowledge base, retrieve relevant documents, and generate responses that reference these documents. You are using the transformers and faiss libraries in Python to achieve this. After retrieving the relevant passages, the generative model will then process them to formulate a final response.
What is the most appropriate sequence of steps for implementing this RAG pipeline?

A. Initialize the generative model -> Use FAISS to encode the retrieved documents -> Pass the encoded documents to the transformer model for response generation.

B. Encode the query using FAISS -> Use the transformer model to retrieve documents from the knowledge base -> Generate a response using the encoded documents.

C. Use the FAISS library to create an index -> Encode the input query using the transformer model -> Retrieve the most relevant documents -> Pass the retrieved documents to the generative model for response generation.

D. Generate the response first using the transformer model -> Retrieve documents from the knowledge base -> Encode the documents using FAISS -> Use the retrieved documents to fine-tune the generated response.

정답: C

문제17

You are designing a customer support chatbot using watsonx.ai as the primary generative model. You want to enhance the chatbot's capabilities by integrating it with IBM Watson Assistant to handle structured conversations while allowing watsonx.ai to generate responses for open-ended queries.
Which integration approach would most effectively combine both services while maintaining optimal performance and accuracy?

A. Implement Watson Assistant for structured conversations and use a middleware layer that dynamically routes complex, open-ended queries to watsonx.ai, returning the results within the same session.

B. Train Watson Assistant to handle both structured and unstructured conversations, while using watsonx.ai only for rare edge cases that Watson Assistant cannot manage.

C. Use Watson Discovery to preprocess all queries before routing them to either Watson Assistant or watsonx.ai based on query complexity.

D. Create separate chat interfaces for Watson Assistant and watsonx.ai, and allow the user to choose which system to query based on their needs.

정답: A

문제18

You are analyzing prompts submitted to a Generative AI model used for summarizing long research papers.
One user submits the following prompt: "Summarize this 40-page research paper on quantum computing, including details on every section and subsection, providing a detailed description of key points, methodologies, results, discussions, and future work. The summary should be at least 5 pages long." Why is this prompt considered inefficient, and how should it be optimized?

A. The prompt is inefficient because it requests a 5-page summary, which is unnecessary for summarizing the key information from a research paper.

B. The prompt is inefficient because it asks for too much detail across all sections, leading to excessive token usage and unnecessary information in the output.

C. The prompt is efficient because it clearly outlines the expectations and ensures a comprehensive summary.

D. The prompt is inefficient because it does not specify a character limit, which means the model might generate overly verbose output.

정답: B

문제19

You are training a generative AI model using IBM's Tuning Studio and want to optimize its performance. You aim to avoid both overfitting and underfitting by carefully selecting the appropriate number of epochs.
Which of the following strategies would best help you set the optimal number of epochs during the tuning process?

A. Set the number of epochs equal to the size of the dataset

B. Set a high number of epochs and use early stopping to determine the optimal point

C. Gradually increase the number of epochs until the loss on the training set reaches zero

D. Use a single epoch to avoid overfitting

정답: B

최신 C1000-185 무료덤프 - IBM watsonx Generative AI Engineer - Associate

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