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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. You are working with IBM Watsonx and have developed a custom machine learning model using Watson Studio. Now, you need to deploy the model so that it can be accessed via an application.
Which step is NOT required when deploying the custom model for application access?

A) Verifying model accuracy before deployment.
B) Registering the model in Watson Machine Learning (WML)
C) Defining a scoring endpoint for the model in Watson Machine Learning
D) Assigning appropriate IAM roles for users who need access to the model

2. Your team has developed an AI model that generates automated legal documents based on user inputs. The client, a large law firm, wants to deploy this model but has stringent security, compliance, and auditability requirements due to the sensitive nature of the data.
What is the most appropriate deployment strategy to meet these specific requirements?

A) Deploy the model using a serverless architecture to minimize operational overhead and maintain compliance.
B) Deploy the model on a hybrid cloud, with inference done on the client's on-premise servers and training done in the public cloud.
C) Deploy the model on a public cloud with built-in encryption and use APIs to connect to the client's private data.
D) Use a private cloud with role-based access controls (RBAC) and ensure model activity is logged for auditing purposes.

3. You are using IBM watsonx's generative AI model to generate responses for a chatbot, and you want to ensure that the model stops generating text when it encounters a specific phrase like ":End of Response." Which of the following settings for stop sequences is most appropriate to achieve this goal?

A) Set the stop sequence to "STOP"
B) Set the stop sequence to "End of Response"
C) Set the stop sequence to "\ n\ n"
D) Set the stop sequence to "<|stop|>"

4. As a Generative AI engineer, you're tasked with optimizing the performance and cost-efficiency of a model by adjusting the model parameters.
Given that your objective is to reduce the cost of generation while maintaining acceptable quality, which of the following parameter changes is most likely to result in cost savings?

A) Decrease the max tokens parameter.
B) Increase the max tokens parameter to allow for more complex output.
C) Set the temperature parameter to a higher value.
D) Increase the top-k sampling value.

5. You are fine-tuning the output behavior of a generative AI model in IBM Watsonx for creative content generation. You decide to adjust the temperature parameter to influence the randomness of the model's output.
Which of the following best describes the effect of increasing the temperature value?

A) Raising the temperature makes the model more likely to repeat tokens, reducing variability in its responses.
B) Raising the temperature encourages the model to consider less likely tokens, leading to more diverse and creative outputs.
C) A higher temperature setting reduces the length of the generated output by limiting the number of tokens in each response.
D) Increasing the temperature makes the model generate more deterministic responses by always selecting the most probable token at each step.

Solutions: