Title: Pass Guaranteed Quiz 2026 IBM - C1000-185 - IBM watsonx Generative AI Engineer - [Print This Page] Author: benshaw268 Time: 15 hour before Title: Pass Guaranteed Quiz 2026 IBM - C1000-185 - IBM watsonx Generative AI Engineer - What's more, part of that Lead1Pass C1000-185 dumps now are free: https://drive.google.com/open?id=1ze3TK3LfEmYxZ85JCJnmEtn7_13SQtJc
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C1000-185 Exam Torrent: IBM watsonx Generative AI Engineer - Associate & C1000-185 Practice TestWith the IBM C1000-185 Certification Exam, you can demonstrate your skills and upgrade your knowledge.The IBM C1000-185 certification exam will provide you with many personal and professional benefits such as more career opportunities, updated and in demands expertise, an increase in salary, instant promotion, and recognition of skills across the world. IBM watsonx Generative AI Engineer - Associate Sample Questions (Q358-Q363):NEW QUESTION # 358
You are tasked with fine-tuning a pre-trained large language model (LLM) for a customer service chatbot using IBM's InstructLab. You need to customize the LLM to improve its ability to handle specific user instructions related to order management, such as tracking orders, processing returns, and issuing refunds.
Which of the following components in InstructLab is the most critical for guiding the LLM to respond appropriately to these specific instructions?
A. The feedback loop system for real-time user input validation.
B. The data loader module for transforming data into tokenized inputs.
C. The prompt engineering interface for designing task-specific instructions.
D. The pre-processing pipeline for normalizing and standardizing the dataset.
Answer: C
NEW QUESTION # 359
When deploying a generative AI model using IBM watsonx, which of the following actions should be prioritized to ensure high availability and minimize downtime in production environments? (Select two)
A. Deploying the model on a single cloud-based server with load balancing enabled
B. Disabling failover mechanisms to reduce deployment complexity
C. Implementing containerization for the model through Kubernetes
D. Configuring auto-scaling policies based on usage patterns and resource demand
E. Setting up redundant storage for the model's dataset but not for the model itself
Answer: C,D
NEW QUESTION # 360
You are working on a task that involves generating marketing copy using IBM Watsonx. The goal is to craft a prompt that leads to detailed and persuasive content about a new product launch.
Which of the following approaches would most likely result in high-quality, detailed, and contextually appropriate content?
A. Avoid specifying any constraints and rely on Watsonx's default model behavior: "Write product launch marketing content."
B. Provide specific context and audience information: "Generate marketing copy for a new eco-friendly water bottle targeting health-conscious consumers. Include persuasive language and focus on the sustainability features of the product."
C. Use complex, technical jargon to generate highly specific content: "Produce syntactically dense prose with multifaceted aspects of ecological ramifications and commodification for a consumer base."
D. Use a very short prompt: "Generate marketing copy for a product launch."
Answer: B
NEW QUESTION # 361
You are developing a document understanding system that integrates IBM watsonx.ai and Watson Discovery to extract insights from large sets of documents. The system needs to leverage watsonx.ai's large language model to summarize documents and Watson Discovery to search and extract relevant data from those documents.
What is the best approach to achieve this integration?
A. Use Watson Discovery to index and search documents, and then send the retrieved documents to watsonx.ai's LLM for summarization through API calls.
B. Use watsonx.ai's LLM to both retrieve and summarize the documents, bypassing Watson Discovery.
C. Use Watson Discovery for summarizing documents and watsonx.ai's LLM for only retrieving relevant content from the documents.
D. Use watsonx.ai's LLM to create a summary for each document in advance, and Watson Discovery only for searching pre-generated summaries.
Answer: A
NEW QUESTION # 362
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. Manually write every possible customer inquiry scenario to ensure quality
B. Generate synthetic customer inquiries and responses based on company policy guidelines
C. Generate synthetic data without aligning it with company policies to maximize diversity
D. Use random generation to create a diverse range of responses without constraints
Answer: B
NEW QUESTION # 363
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