VALID C1000-185 BRAINDUMPS - TEST C1000-185 SIMULATOR

Valid C1000-185 Braindumps - Test C1000-185 Simulator

Valid C1000-185 Braindumps - Test C1000-185 Simulator

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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q186-Q191):

NEW QUESTION # 186
You are tasked with managing multiple versions of a generative AI model in a production environment. The team has decided to utilize IBM watsonx deployment spaces to version control both models and prompts.
What is the most efficient way to organize these assets within the deployment space?

  • A. Use a third-party version control tool like Git to manage prompt and model versions, syncing with the deployment space only for final deployment.
  • B. Assign version tags to both models and prompts within a single deployment space, using metadata and associations to track prompt-model pairings for each version.
  • C. Create separate deployment spaces for each model and prompt version, linking the spaces manually to ensure consistency between model and prompt versions.
  • D. Store all versions of both models and prompts in a single deployment space, and use comments to track differences between versions.

Answer: B


NEW QUESTION # 187
You are tasked with reconstructing a prompt used in an AI-based customer support chatbot. The current prompt generates lengthy, detailed answers that are often overly verbose and unnecessary for the customer's inquiries. Your objective is to optimize this prompt to reduce model usage costs without compromising the quality of the responses.
Which of the following strategies is the most effective in reducing the cost of using a Generative AI model while maintaining response relevance and clarity?

  • A. Revising the prompt to make it more specific by narrowing the scope of expected responses.
  • B. Using temperature scaling to increase randomness and reduce token usage.
  • C. Splitting the prompt into multiple sub-prompts to generate responses for different sections separately.
  • D. Reducing the token limit in the model configuration to restrict the length of responses.

Answer: A


NEW QUESTION # 188
You are tasked with integrating IBM watsonx with a third-party customer relationship management (CRM) system to enhance customer interactions through conversational AI.
Which of the following approaches best ensures real-time responses while minimizing the latency caused by data exchange between systems?

  • A. Utilize watsonx's real-time streaming API with pre-configured webhooks in the CRM system for instant data retrieval and response.
  • B. Employ an asynchronous message queue between IBM watsonx and the CRM system to handle customer requests.
  • C. Set up periodic data synchronization between the CRM system and IBM watsonx using FTP file transfers.
  • D. Use IBM watsonx API for batch processing of customer requests, triggering the CRM system via a scheduled job.

Answer: A


NEW QUESTION # 189
You are training a chatbot to handle customer inquiries for a telecommunications company. To augment your training data, you decide to generate synthetic data using IBM's InstructLab platform. You aim to improve the model's ability to handle rare or edge-case scenarios, such as technical issues with specific device models. You are following the LAB (Large-scale Alignment for chatBots) methodology to ensure alignment of the chatbot's responses with company policies.
Which of the following steps is most aligned with LAB methodology principles for generating synthetic data in this case?

  • A. Generate synthetic customer inquiries and responses based on company policy guidelines
  • B. Manually write every possible customer inquiry scenario to ensure quality
  • C. Use random generation to create a diverse range of responses without constraints
  • D. Generate synthetic data without aligning it with company policies to maximize diversity

Answer: A


NEW QUESTION # 190
You are designing a generative AI model to generate detailed technical

  • A. Stop Sequence = '<END>', Max Tokens = 100
  • B. Max Tokens = 500: This provides enough space for a detailed technical
  • C. Stop Sequence = 'END', Max Tokens = 500
  • D. Stop Sequence = None, Max Tokens = 700

Answer: C


NEW QUESTION # 191
......

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