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IBM C1000-185 Exam Syllabus Topics:

IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. A client is deploying a watsonx Generative AI solution to analyze customer feedback in real time. They require a cost-effective solution that can handle occasional traffic spikes but do not expect constant heavy loads.
What would be the most appropriate approach to minimize costs while ensuring adequate performance during traffic spikes?

A) Deploy the model using a serverless architecture with auto-scaling to handle sudden spikes in traffic.
B) Deploy a cloud-based instance with manual scaling to adjust resources when traffic spikes occur.
C) Deploy a single powerful GPU instance, relying on its ability to handle both regular and peak traffic without scaling.
D) Use a fixed number of on-premise servers that can handle peak traffic, but run them at a lower capacity during low-demand periods.

2. In the context of AI governance, what is the most important aspect of managing model performance in a production environment to ensure compliance with regulatory and ethical guidelines?

A) Deploying the model only in secure, on-premises environments to prevent data breaches
B) Ensuring traceability of model decisions and providing auditability for each inference
C) Maximizing the number of datasets the model is trained on to cover more use cases
D) Minimizing the model's inference time to optimize user experience

3. You are using IBM watsonx Prompt Lab to experiment with different versions of a prompt to generate accurate and creative responses for a customer support chatbot.
Which of the following best describes a key benefit of using Prompt Lab in the process of prompt engineering?

A) It provides a real-time environment for testing and refining prompts, helping to improve response quality.
B) It limits the number of iterations a user can test to prevent overfitting the prompt to specific outputs.
C) It allows users to generate AI models without the need for training data.
D) It automatically generates prompts based on industry-specific data without any user input.

4. As an IBM Watsonx Generative AI engineer, you are tasked with creating a chatbot for a public-facing service. One key concern is ensuring that the model does not generate or propagate hate speech, abusive content, or profanity. To mitigate these risks, you must implement appropriate controls.
Which of the following is the best approach to mitigate hate speech, abuse, and profanity from being generated by your AI model?

A) Apply a simple word-level blacklist filter to detect and remove harmful content from the model output.
B) Use IBM Watsonx's HAP (Hate, Abuse, and Profanity) filter to dynamically detect and block harmful content at inference time.
C) Train the model only on data that excludes all user-generated content to prevent exposure to harmful language.
D) Fine-tune the model with a highly curated dataset that contains labeled examples of hate speech, abuse, and profanity for the model to learn to avoid.

5. Which of the following describes a key benefit of using Prompt Lab in IBM Watsonx for developing generative AI applications?

A) Prompt Lab ensures that all generated outputs are free from bias by automatically filtering inappropriate content.
B) Prompt Lab provides automatic optimization of model hyperparameters, ensuring the best performance without user intervention.
C) Prompt Lab allows users to iteratively test and refine prompts in a controlled environment, improving prompt effectiveness and reducing guesswork.
D) Prompt Lab enables real-time collaboration between developers, allowing them to modify prompts simultaneously for faster development.

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