C1000-185熱門考題 & C1000-185題庫下載

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>> C1000-185熱門考題 <<

C1000-185題庫下載 - C1000-185認證資料

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最新的 IBM Certified watsonx Generative AI Engineer - Associate C1000-185 免費考試真題 (Q40-Q45):

問題 #40
A developer is using a GitHub Code Retrieval API to help build a search engine that can locate relevant code snippets from public repositories. The API is designed to retrieve code based on the semantic similarity of the query (e.g., a description of what the code does) to the code itself.
What is the primary advantage of using a vector-based approach for code retrieval in this scenario?

A. It speeds up retrieval by limiting the search to repositories where the user has committed code in the past.
B. It ensures that the code snippets returned are exact matches to the keywords in the query, avoiding irrelevant code.
C. It provides real-time updates to the code embeddings, ensuring the latest code is always retrieved.
D. It retrieves code snippets based on the semantic similarity between the query and the code, enabling the discovery of relevant code even when the query and code do not use the same keywords.

答案：D

問題 #41
You are working on deploying a generative AI model into production. The goal is to ensure that different versions of prompts can be tracked and rolled back in case of degradation in the model's performance.
Which of the following strategies would best address versioning for deployment?

A. Use manual version control through logging and local storage.
B. Integrate prompt versioning into the model deployment pipeline using automated versioning tools like Git.
C. Use endpoint monitoring tools only, without any versioning approach, to track and assess prompt changes in production.
D. Maintain different versions of the model and prompts by duplicating them across multiple endpoints without a centralized repository.

答案：B

問題 #42
In a generative AI-based customer service chatbot, you notice that the model sometimes generates user responses that inadvertently reveal sensitive personal information, such as names, addresses, or social security numbers.
What is the most effective prompt engineering technique to reduce this risk while preserving the chatbot's functionality?

A. Increase the model's randomness by adjusting the temperature parameter
B. Introduce explicit instructions in the prompt to avoid generating personal information
C. Reduce the model's token limit to restrict the amount of text generated
D. Use generic prompts that include placeholders for sensitive information (e.g., [USER_NAME])

答案：B

問題 #43
A machine learning engineer is optimizing a generative AI model for creative writing. They are debating the use of soft prompts over hard prompts.
What is the primary advantage of using soft prompts in this context, despite their complexity?

A. Soft prompts allow for more nuanced control of the model's behavior through learned embeddings, which can adapt to a variety of tasks without requiring explicit human intervention.
B. Soft prompts improve the simplicity of the model's overall structure, making it easier to debug and interpret the generation process.
C. Soft prompts provide more direct control over the model's behavior by offering explicit, human-readable instructions.
D. Soft prompts enforce stricter generation outputs due to the deterministic nature of the learned embeddings, leading to higher consistency in results.

答案：A

問題 #44
In the context of using Tuning Studio in IBM watsonx, which of the following is the primary benefit of fine-tuning a pre-trained Generative AI model using this tool?

A. Improves model performance on domain-specific tasks without retraining from scratch.
B. Increases the size of the model to handle more complex prompts.
C. Reduces the time needed to generate text responses by simplifying the model's architecture.
D. Allows you to train the model from scratch on a new dataset.

答案：A

問題 #45
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C1000-185熱門考題 & C1000-185題庫下載

C1000-185題庫下載 - C1000-185認證資料

最新的 IBM Certified watsonx Generative AI Engineer - Associate C1000-185 免費考試真題 (Q40-Q45):

最新的C1000-185認證考試的題目與答案

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