100% PASS 2025 IBM PERFECT C1000-185: IBM WATSONX GENERATIVE AI ENGINEER - ASSOCIATE VALID TEST QUESTION

100% Pass 2025 IBM Perfect C1000-185: IBM watsonx Generative AI Engineer - Associate Valid Test Question

100% Pass 2025 IBM Perfect C1000-185: IBM watsonx Generative AI Engineer - Associate Valid Test Question

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Tags: C1000-185 Valid Test Question, Pdf C1000-185 Pass Leader, Pass4sure C1000-185 Pass Guide, C1000-185 Latest Real Exam, C1000-185 Latest Dumps Book

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q71-Q76):

NEW QUESTION # 71
You have completed a prompt-tuning experiment for a large language model (LLM) using IBM Watsonx, aimed at improving its ability to generate accurate responses to customer support queries. After the tuning process, you are analyzing the performance statistics of the model.
Which statistical metric is the most appropriate to prioritize when evaluating the success of the prompt-tuning experiment?

  • A. BLEU score
  • B. Log-likelihood of generated responses
  • C. Token generation speed
  • D. Perplexity score

Answer: D


NEW QUESTION # 72
During the deployment of a generative AI model using IBM Watsonx, you are responsible for ensuring that the model does not generate content containing hate speech, abusive language, or profanity. However, in some scenarios, the model might bypass basic filtering mechanisms and produce subtle or context-specific harmful language.
Which of the following best addresses edge cases where hate speech or abuse may slip through more basic filtering mechanisms?

  • A. Implement regular expression-based filters that cover a wide range of variations in harmful language.
  • B. Use sentiment analysis to detect and block negative content that may indicate hate speech or abuse.
  • C. Continuously monitor and retrain the model on datasets containing edge cases of hate speech, abuse, and profanity.
  • D. Use IBM Watsonx's HAP (Hate, Abuse, and Profanity) filter, which is designed to handle context-specific and subtle forms of harmful language.

Answer: D


NEW QUESTION # 73
You are enhancing an existing relational database system to support vector-based similarity search, integrating RAG into your infrastructure.
Which of the following technologies or approaches represents a valid method for extending a traditional SQL database to handle vector embeddings and similarity searches?

  • A. Normalizing vector embeddings into relational tables with foreign key constraints
  • B. Using graph database extensions to enable vector embeddings within a SQL database
  • C. Using a full-text indexing engine, such as Elasticsearch, to store the vector embeddings
  • D. Adding a plugin that provides support for k-nearest neighbors (k-NN) search

Answer: D


NEW QUESTION # 74
Consider an organization implementing a RAG system to enhance the accuracy of their internal documentation search tool. The retriever is responsible for fetching relevant documents based on user queries.
What is the core capability of the retriever in this context?

  • A. To perform pre-defined template matching on queries to retrieve documents that exactly match pre-configured templates.
  • B. To return relevant documents or passages from a knowledge base by calculating semantic similarity between the query and documents.
  • C. To generate new responses based on training data, without relying on external data sources.
  • D. To perform entity recognition and classify documents based on specific keywords, ignoring the overall document meaning.

Answer: B


NEW QUESTION # 75
Which prompt engineering strategy is most effective for reducing the risk of generating biased content in a generative AI model?

  • A. Using a larger number of examples in the prompt to steer the model towards safer and more neutral outputs.
  • B. Including specific disclaimers or guidelines in the prompt instructing the model to avoid biased language.
  • C. Designing prompts that explicitly ask for balanced perspectives, such as "Provide both pros and cons of this issue."
  • D. Adjusting the model's temperature to a lower value to generate more deterministic and consistent outputs.

Answer: C


NEW QUESTION # 76
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