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[General] Pass Guaranteed Quiz IBM - C1000-185–High-quality Free Learning Cram

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【General】 Pass Guaranteed Quiz IBM - C1000-185–High-quality Free Learning Cram

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q224-Q229):NEW QUESTION # 224
You are implementing a Retrieval-Augmented Generation (RAG) system to enhance a large language model's (LLM) ability to answer questions based on an external document store.
What role do embeddings play in the RAG architecture, and how can you optimize them for more relevant document retrieval? (Select two)
  • A. Embeddings are vector representations of text, used to measure the similarity between queries and documents.
  • B. Increasing the dimensionality of embeddings always improves retrieval accuracy by providing a more detailed representation of the documents.
  • C. Fine-tuning the embedding model with task-specific data can lead to more accurate retrievals.
  • D. The cosine similarity metric is typically less effective than Euclidean distance for comparing embeddings in RAG systems.
  • E. Embeddings are only used during the generation phase of RAG to enhance language model outputs.
Answer: A,C

NEW QUESTION # 225
You are tasked with designing a prompt to translate a sentence from English to French using an AI model.
Which of the following prompt would best guide the AI to achieve accurate translation, while maintaining cultural nuance and avoiding literal word-for-word translation?
  • A. "Explain the meaning of 'The weather is nice today' in French."
  • B. "Translate the sentence 'The weather is nice today' into French and make sure to avoid literal translation, focusing on cultural nuances."
  • C. "Translate 'The weather is nice today' to French but ensure that the translation reflects word-for-word accuracy and no cultural considerations."
  • D. "Translate the following sentence from English to French: 'The weather is nice today.'"
Answer: B

NEW QUESTION # 226
In IBM Watsonx's Prompt Lab, example input prompts can be used to improve the effectiveness of generated responses.
Which of the following best describes a key benefit of utilizing example input prompts in Prompt Lab?
  • A. Example input prompts help generate responses that are more aligned with the specific context or style intended by the user.
  • B. Example input prompts guarantee consistency across all outputs, regardless of variability in user-provided data.
  • C. Example input prompts allow the model to learn new concepts and update its knowledge base dynamically.
  • D. Example input prompts automatically adjust the model's training dataset for more accurate predictions.
Answer: A

NEW QUESTION # 227
You are tasked with integrating watsonx.ai into a legacy system that operates over HTTP and requires strict security and monitoring of the API calls. The legacy system lacks modern authentication mechanisms like OAuth.
Which integration method would best suit the needs of this environment while ensuring security and efficient API management?
  • A. Use REST API with API key-based authentication, leveraging HTTPS for encrypted communication between the legacy system and watsonx.ai.
  • B. Directly embed the watsonx.ai SDK into the legacy system to handle API management and security, eliminating the need for external API calls.
  • C. Implement a GraphQL API to allow the legacy system to query specific fields and reduce payload size, thereby improving efficiency.
  • D. Use a REST API with OAuth authentication and token management to secure the communication.
Answer: A

NEW QUESTION # 228
You are fine-tuning a generative AI model in IBM Watsonx and need to define appropriate stopping criteria to ensure the generated text is relevant and coherent.
Which of the following would be an example of a valid stopping criterion for a text generation task?
  • A. The model will stop generating text once it detects a repetitive sequence of words or phrases, automatically cutting off redundancy.
  • B. The model will stop generating text once a predefined number of characters is reached, ensuring that the output does not exceed a set length.
  • C. The model will stop generating text when it encounters a special end-of-sequence token or punctuation such as a period or question mark.
  • D. The model will stop generating text once the average probability of each word in the output falls below a 50% threshold.
Answer: C

NEW QUESTION # 229
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