Generative AI Leader Practice Test 19 — 15 Questions

Question 1

An organization is using Vertex AI Gemini API for a multimodal chatbot. They notice that the model sometimes provides incorrect information with high confidence. They want to reduce hallucinations without retraining the model. What is the most effective approach?

Accepted Answer

Provide ground-truth context from a knowledge base using grounding. Safety settings reduce hallucinations? Actually, hallucinations are not purely safety. Grounding with a knowledge base provides factual retrieval to reduce hallucinations. Option B is wrong because safety settings block harmful content, not necessarily hallucinations. Option C is wrong because increasing temperature increases randomness. Option D is wrong because reduced token count limits responses but may not reduce hallucinations.

Answer

Increase the temperature parameter to make the model more creative

Answer

Reduce the maximum output tokens to force concise answers

Answer

Adjust safety settings to filter uncertain responses

Question 2

A data scientist wants to quickly prototype a text generation application using Google's foundation models. Which Google Cloud service should they use?

Accepted Answer

Generative AI Studio. Generative AI Studio is designed for rapid prototyping with foundation models. Vertex AI Prediction is for serving, AI Platform Training is for custom training, and Cloud Natural Language API is for analysis, not generation.

Answer

Cloud Natural Language API

Answer

Vertex AI Prediction

Answer

AI Platform Training

Question 3

An organization is building a generative AI application on Vertex AI. Which THREE actions should they take to ensure responsible AI practices?

Accepted Answer

Implement human review for sensitive outputs. Implementing human review, conducting fairness evaluation, and creating a safety policy with content filtering are key responsible AI practices. Using only Google's models does not guarantee responsibility, and disabling filtering is counterproductive.

Answer

Disable content filtering

Answer

Use only Google's foundation models

Question 4

A developer is using the Vertex AI PaLM API to generate code. They want to ensure the output is safe and adheres to company policies. Which THREE attributes can they configure in the safety_settings parameter?

Accepted Answer

Toxicity. B, D, and E are standard safety categories for PaLM API. A and C are not available as safety categories.

Answer

Language detection

Answer

Sentiment analysis

Question 5

An organization is using Vertex AI to fine-tune a large language model. They notice training is taking longer than expected and cost is increasing. Which action is most likely to reduce training time and cost without significantly impacting model quality?

Accepted Answer

Enable mixed-precision training (bfloat16). Mixed-precision training (bfloat16) reduces memory usage and speeds up computation on compatible hardware while maintaining model quality. Increasing batch size or learning rate risks convergence issues; increasing steps increases cost.

Answer

Increase the number of training steps

Answer

Increase the batch size

Answer

Use a higher learning rate

Question 6

A company is building a customer support chatbot using Vertex AI Agent Builder. They want the agent to answer questions based on internal knowledge base documents stored in Cloud Storage. Which feature should they configure to ensure the agent can retrieve relevant information from these documents?

Accepted Answer

Enable grounding with a data store. Grounding connects the agent to external data sources like Cloud Storage, allowing it to retrieve and use information from the knowledge base. Option A is wrong because deploying to an endpoint is for model serving, not data retrieval. Option B is wrong because safety filters control content, not retrieval. Option D is wrong because custom training is for fine-tuning, not retrieval.

Answer

Deploy the agent to a Vertex AI endpoint

Answer

Fine-tune a Gemini model on the knowledge base

Answer

Configure a safety filter to block irrelevant queries

Question 7

A developer wants to integrate Gemini multimodal capabilities (text + image) into a mobile app using Python. Which Google Cloud client library should they use?

Accepted Answer

Vertex AI client library (google-cloud-aiplatform). The Google Generative AI client library (or Vertex AI client library for Gemini API) supports multimodal inputs. Option A is wrong because Cloud Vision is for image analysis, not generative. Option B is wrong because Natural Language is text-only. Option D is wrong because Dialogflow is for conversational agents, not direct API calls.

Answer

Dialogflow CX

Answer

Cloud Vision API

Answer

Natural Language API

Question 8

A security team wants to prevent prompt injection attacks on their generative AI application hosted on Vertex AI. Which best practice should they implement?

Accepted Answer

Implement input validation and output filtering. Input validation and output filtering are key defenses against prompt injection. Custom models do not inherently prevent it; disabling logging reduces visibility; private endpoints do not block injection.

Answer

Use a custom model instead of a foundation model

Answer

Disable all logging

Answer

Use a private endpoint

Question 9

A data scientist is using Vertex AI Model Registry to manage multiple versions of a custom text classification model. They need to ensure that only the version that passes all evaluation metrics can be deployed to a Vertex AI Endpoint for online predictions. What deployment strategy should they use?

Accepted Answer

Set up continuous evaluation with model monitoring to auto-promote versions that meet thresholds. Model Registry supports continuous evaluation and can automatically promote versions that meet thresholds. Option A is wrong because manual version control is error-prone. Option B is wrong because A/B testing is for traffic splitting, not automatic promotion. Option D is wrong because batch predictions are offline.

Answer

Use A/B testing between versions and manually select the best performer

Answer

Manually track version IDs and deploy the latest version

Answer

Deploy all versions to a single endpoint and route traffic manually

Question 10

A company deploys a fine-tuned text generation model on Vertex AI Endpoints. They want to monitor for data drift and performance degradation over time. Which GCP service should they integrate?

Accepted Answer

Vertex AI Model Monitoring. Vertex AI Model Monitoring is specifically designed for drift detection and performance monitoring of deployed models. Option A is wrong because Cloud Monitoring is general infrastructure monitoring. Option B is wrong because Cloud Logging is for logs. Option D is wrong because Vertex AI Experiments is for tracking training runs.

Answer

Cloud Monitoring

Answer

Cloud Logging

Answer

Vertex AI Experiments

Question 11

Which THREE capabilities does Vertex AI Agent Builder provide out of the box? (Select THREE.)

Accepted Answer

Automatic escalation to human agents when confidence is low. Agent Builder includes pre-built agents (A), grounding (D), and automatic fallback (E). B is done via Model Garden, not Agent Builder directly. C is a feature of Vertex AI Search.

Answer

Fine-tuning of foundation models using custom datasets

Answer

Enterprise search over internal documents

Question 12

A developer is using the Vertex AI PaLM API and receives a 429 Resource Exhausted error. What is the most likely cause?

Accepted Answer

The user has exceeded the allowed number of requests per minute. 429 errors indicate rate limiting or quota exhaustion for the API.

Answer

The request payload is too large

Answer

The model is not available in the current region

Answer

The API key is invalid

Question 13

A company is building a document summarization tool using Vertex AI Gemini API. They notice that the model sometimes returns incomplete summaries that miss key points. Which approach is most likely to improve summary quality without increasing token usage significantly?

Accepted Answer

Refine the system instruction to specify the desired summary format and key elements to include. Option A is correct because updating the system instruction to explicitly request bullet points or structure improves output quality with minimal token overhead. Option B (increasing max output tokens) may help but increases cost and latency. Option C (switching to a larger model) increases cost and may not resolve instruction following. Option D (using longer context) is unrelated to summary completeness.

Answer

Increase the context window to include more of the document

Answer

Switch to a larger Gemini model (e.g., from 1.0 Pro to 1.5 Pro)

Answer

Increase the max output token limit to allow longer summaries

Question 14

Which THREE benefits does Vertex AI Agent Builder provide over building a custom conversational agent from scratch?

Accepted Answer

Automatic scaling and load balancing. Options B, C, and E are correct. Pre-built grounding with your data reduces development effort; built-in safety filters ensure compliance; automatic scaling handles traffic without manual ops. Option A (full control over ML models) is more true for custom builds. Option D (lower latency) is not guaranteed; custom builds can optimize latency.

Answer

Full control over the underlying ML model architecture

Answer

Guaranteed lower inference latency

Question 15

A company is building a generative AI application that must adhere to strict data residency regulations. Which TWO Google Cloud features can help ensure that data does not leave a specific geographic region?

Accepted Answer

Using the regional endpoint for Vertex AI. Options B and D are correct. Dedicated VMs and the regional endpoint for Vertex AI ensure data stays in a specified region. Option A is wrong because model caching may use regional resources but does not enforce residency. Option C is wrong because Cloud CDN distributes data globally. Option E is wrong because Global Load Balancer routes traffic globally.

Answer

Vertex AI Model Caching

Answer

Global load balancer with Cloud Armor

Answer

Cloud CDN for content delivery