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[Hardware] IBM C1000-185 Valid Mock Exam | VCE C1000-185 Dumps

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【Hardware】 IBM C1000-185 Valid Mock Exam | VCE C1000-185 Dumps

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q291-Q296):NEW QUESTION # 291
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 model pre-trained on financial and business data but with limited language capabilities.
  • B. A pre-trained model that has been optimized for creative text generation.
  • C. A small pre-trained model specifically designed for open-domain tasks.
  • D. A large pre-trained language model that has been fine-tuned on generic business communication.
Answer: A

NEW QUESTION # 292
You are tasked with fine-tuning prompts for a customer support chatbot built using IBM Watsonx. You decide to leverage Prompt Lab to improve the model's responses.
Which of the following best describes the key benefits of using Prompt Lab for this task?
  • A. Prompt Lab enables you to train the model with new data, ensuring continuous learning and improved performance over time.
  • B. Prompt Lab provides an environment to experiment with different prompt structures and analyze their impact on model outputs in real-time, helping optimize responses.
  • C. Prompt Lab offers pre-trained prompts specific to industry verticals, making it unnecessary to create customized prompts.
  • D. Using Prompt Lab guarantees that the model will never produce biased responses, regardless of the input data used.
Answer: B

NEW QUESTION # 293
In a system that generates product recommendations using a generative AI model, you are tasked with creating prompts that incorporate dynamic variables to ensure more relevant and personalized responses.
Prompt Template: "Recommend products for [customer_name] based on their interest in [product_category]." Which portion of the prompt is the best candidate to be replaced with variables to achieve greater personalization and flexibility? (Select two)
  • A. "based on their interest"
  • B. "[product_category]"
  • C. "Recommend products"
  • D. "[customer_name]"
  • E. "for"
Answer: B,D

NEW QUESTION # 294
You are working on a task that involves generating marketing copy using IBM Watsonx. The goal is to craft a prompt that leads to detailed and persuasive content about a new product launch.
Which of the following approaches would most likely result in high-quality, detailed, and contextually appropriate content?
  • A. Use a very short prompt: "Generate marketing copy for a product launch."
  • B. Use complex, technical jargon to generate highly specific content: "Produce syntactically dense prose with multifaceted aspects of ecological ramifications and commodification for a consumer base."
  • C. Avoid specifying any constraints and rely on Watsonx's default model behavior: "Write product launch marketing content."
  • D. Provide specific context and audience information: "Generate marketing copy for a new eco-friendly water bottle targeting health-conscious consumers. Include persuasive language and focus on the sustainability features of the product."
Answer: D

NEW QUESTION # 295
You are generating product descriptions for an online marketplace using a generative AI model. The output is coherent but tends to repeat the same phrases and words excessively. You decide to apply a repetition penalty to reduce this repetition while keeping the temperature set to a value that maintains creativity in the text generation.
Which of the following adjustments would best achieve this goal?
  • A. Set repetition penalty to 1.0 and decrease temperature from 0.8 to 0.3
  • B. Set repetition penalty to 0.0
  • C. Set repetition penalty to 1.5 and maintain temperature at 0.8
  • D. Set repetition penalty to 2.0 and increase temperature from 0.7 to 1.2
Answer: C

NEW QUESTION # 296
......
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