AUTHORIZED LATEST C1000-185 EXAM GUIDE & LEADER IN QUALIFICATION EXAMS & HIGH-QUALITY C1000-185: IBM WATSONX GENERATIVE AI ENGINEER - ASSOCIATE

Authorized Latest C1000-185 Exam Guide & Leader in Qualification Exams & High-quality C1000-185: IBM watsonx Generative AI Engineer - Associate

Authorized Latest C1000-185 Exam Guide & Leader in Qualification Exams & High-quality C1000-185: IBM watsonx Generative AI Engineer - Associate

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q113-Q118):

NEW QUESTION # 113
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 a full-text indexing engine, such as Elasticsearch, to store the vector embeddings
  • C. Adding a plugin that provides support for k-nearest neighbors (k-NN) search
  • D. Using graph database extensions to enable vector embeddings within a SQL database

Answer: C


NEW QUESTION # 114
You are designing a Retrieval-Augmented Generation (RAG) system that will handle real-time queries from users, using a combination of a retriever and a transformer-based generator.
Which of the following implementation details is the most critical to ensure that the system delivers responses in a timely manner while maintaining accuracy?

  • A. The retriever and generator should operate independently of each other to avoid communication overhead.
  • B. The retriever should utilize an efficient vector search algorithm with approximate nearest neighbor (ANN) techniques to balance speed and accuracy.
  • C. The system should cache previous queries and responses to avoid invoking the retriever and generator multiple times.
  • D. The retriever should use exact match algorithms to minimize retrieval time and complexity.

Answer: B


NEW QUESTION # 115
You are designing a prompt for a generative AI model in a customer support chatbot. The goal is to help users troubleshoot issues with a software installation.
Which of the following prompts would be the most effective for guiding the AI to deliver clear, actionable troubleshooting steps?

  • A. "Please list all the possible errors that occur during software installation."
  • B. "Guide the user through troubleshooting software installation issues, starting from common problems like insufficient disk space and incompatible OS."
  • C. "Tell the user what software installation is and how it works."
  • D. "Can you tell the user about software installation?"

Answer: B


NEW QUESTION # 116
You are deploying a new version of a generative AI model in IBM Watsonx, and you want to maintain the integrity of prompt versioning throughout the deployment lifecycle.
Which of the following methods is the most effective for ensuring that the correct prompt version is used with the corresponding model version in production?

  • A. Hard-code the prompt within the model deployment script to ensure that the correct prompt is always used
  • B. Use semantic versioning for both the model and the associated prompts, and track them independently in separate systems.
  • C. Use the latest available prompt version for every deployment, without specifying an exact version
  • D. Implement model registry tags that associate a specific prompt version with each model version during deployment.

Answer: D


NEW QUESTION # 117
IBM Watsonx's Prompt Lab offers various options to refine prompts for generating more effective AI outputs.
Which of the following is an accurate description of an editing option available in Prompt Lab?

  • A. Users can apply real-time machine learning to modify the underlying model parameters within Prompt Lab.
  • B. Users can use Prompt Lab to train the AI model on new datasets and retrain it based on prompt performance.
  • C. Users can disable the model's access to certain pre-trained knowledge domains within Prompt Lab to focus its output on specific areas.
  • D. Prompt Lab allows users to experiment with prompt structures, such as adjusting token limits or adding contextual instructions, to improve responses.

Answer: D


NEW QUESTION # 118
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