Techniques to Improve Generative AI Model Output →hardMultiple ChoiceObjective-mapped

Generative AI Leader Practice Question: Techniques to Improve Generative AI Model Output

Exhibit

{
  "bindings": [
    {
      "role": "roles/aiplatform.user",
      "members": ["user:dev@example.com"]
    },
    {
      "role": "roles/aiplatform.modelUser",
      "members": ["user:dev@example.com"]
    }
  ]
}

Refer to the exhibit. A team's IAM policy for Vertex AI includes the following binding. They can deploy models but cannot create tuning jobs. Which statement is true?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

The aiplatform.user role lacks permission to create tuning jobs

The roles/aiplatform.user role does not include permission to create tuning jobs (aiplatform.tuningJobs.create). The modelUser role does not override the user role, admin role is not needed, and specialist role doesn't exist.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
The developer needs the aiplatform.admin role
Why it's wrong here
Admin role would work but not the only option.
✗
The aiplatform.user role overrides the modelUser role
Why it's wrong here
Roles are additive, not overriding.
✓
The aiplatform.user role lacks permission to create tuning jobs
Why this is correct
Missing aiplatform.tuningJobs.create permission.
✗
The policy is missing the aiplatform.specialist role
Why it's wrong here
No such role exists in Vertex AI.

Go deeper

Generative AI Leader Practice Question: Techniques to Improve Generative AI Model Output

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question