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IBM C1000-185 試験シラバストピック:

IBM watsonx Generative AI Engineer - Associate 認定 C1000-185 試験問題：

1. You are tasked with designing a prompt template to assist a chatbot in generating professional email responses for customer service inquiries. The system should prioritize politeness, clarity, and conciseness.
What elements should be included in the prompt template to achieve the best results, considering optimal behavior of a large language model (LLM)? (Select two)

A) Provide the customer's emotional context for better alignment with the tone
B) Ask the model to generate multiple versions of the response and rank them
C) Specify the output tone as polite and professional
D) Include examples of informal customer service responses for variability
E) Instruct the model to limit responses to a specific character count

2. You are selecting a model to fine-tune using Tuning Studio for a financial application that requires high accuracy and domain-specific language understanding.
Which type of model should you select to maximize fine-tuning efficiency and performance?

A) A large pre-trained language model that has been fine-tuned on generic business communication.
B) A model pre-trained on financial and business data but with limited language capabilities.
C) A small pre-trained model specifically designed for open-domain tasks.
D) A pre-trained model that has been optimized for creative text generation.

3. In what situation might greedy decoding fail to generate an optimal output, even though it consistently chooses the most probable token at each step?

A) Greedy decoding maximizes local probabilities but can lead to suboptimal global coherence
B) Greedy decoding works best when combined with temperature scaling to increase randomness
C) Greedy decoding is highly effective when multiple equally probable tokens are available at each step
D) Greedy decoding guarantees the highest overall probability for the output sequence

4. You are creating a prompt template for a generative AI model that helps technical support staff troubleshoot customer issues based on symptoms provided. The goal is to generate a clear, step-by-step diagnostic process.
What elements would improve the effectiveness of the template? (Select two)

A) Incorporate complex technical jargon to ensure expert-level responses
B) Set a high temperature value to explore more creative diagnostic approaches
C) Include an instruction to ask clarifying questions when the issue is unclear
D) Provide explicit instructions to break the response into steps
E) Ask the model to generate multiple diagnostic paths for each issue

5. A financial services company is building a generative AI model to assist with customer support. The company is concerned about potential legal liabilities if the model generates customer information, such as bank account numbers or personal identification data, as part of its responses.
Which of the following techniques would best mitigate the risk of generating Personally Identifiable Information (PII) during inference?

A) Use greedy decoding to ensure the model generates only the most probable tokens, which are less likely to include PII.
B) Set a strict token limit to prevent the model from generating long sequences, assuming PII tends to appear in longer outputs.
C) Train the model on sensitive customer data but ensure that the temperature is set low to avoid generating diverse outputs.
D) Implement a real-time PII filter that detects and removes sensitive data before the output is presented to the user.

質問と回答：