PROFESSIONAL IBM LATEST EXAMPREP–RELIABLE NEW C1000-185 LEARNING MATERIALS

Professional IBM Latest Examprep–Reliable New C1000-185 Learning Materials

Professional IBM Latest Examprep–Reliable New C1000-185 Learning Materials

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q245-Q250):

NEW QUESTION # 245
You are experimenting with a generative AI model to write a personalized email response template. You want to ensure that the output maintains a formal tone but occasionally produces creative phrasing without making nonsensical sentences. You are advised to adjust the top-p (nucleus sampling) parameter.
Which of the following settings would most effectively balance between formal coherence and occasional creativity in the generated output?

  • A. Set top-p to 0.5
  • B. Set top-p to 0.95
  • C. Set top-p to 0.0
  • D. Set top-p to 1.0

Answer: B


NEW QUESTION # 246
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 is highly effective when multiple equally probable tokens are available at each step
  • B. Greedy decoding guarantees the highest overall probability for the output sequence
  • C. Greedy decoding maximizes local probabilities but can lead to suboptimal global coherence
  • D. Greedy decoding works best when combined with temperature scaling to increase randomness

Answer: C


NEW QUESTION # 247
While working on generating a concise response to a user prompt, you notice that the generative AI model in IBM watsonx is producing excessively long outputs. You want to ensure that the response is informative but doesn't exceed a specific length.
Which of the following parameters should you adjust, and what is the most appropriate value to achieve a concise output without cutting off essential information?

  • A. Set max_tokens to 100
  • B. Set max_tokens to 10
  • C. Set max_tokens to 1000
  • D. Set max_tokens to 5

Answer: A


NEW QUESTION # 248
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. Using Prompt Lab guarantees that the model will never produce biased responses, regardless of the input data used.
  • B. Prompt Lab offers pre-trained prompts specific to industry verticals, making it unnecessary to create customized prompts.
  • C. Prompt Lab provides an environment to experiment with different prompt structures and analyze their impact on model outputs in real-time, helping optimize responses.
  • D. Prompt Lab enables you to train the model with new data, ensuring continuous learning and improved performance over time.

Answer: C


NEW QUESTION # 249
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 a graphical interface for users to build RAG systems without requiring any programming knowledge.
  • B. They provide pre-trained retrieval models and generators, eliminating the need for any fine-tuning or customization of the system.
  • C. They allow for the retrieval of documents based purely on keyword search, optimizing for exact match over semantic similarity.
  • D. They streamline the integration of retrievers and generators, providing out-of-the-box support for embedding models and vector databases.

Answer: D


NEW QUESTION # 250
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