Generative AI Leader Practice Test 18 — 15 Questions

Question 1

A healthcare company is building a chatbot to answer patient queries using Vertex AI Agent Builder. They want to ensure the chatbot only uses approved medical references and does not generate unverified advice. How should they configure the agent?

Accepted Answer

Set up grounding with a private data store containing verified medical documents. Grounding with a curated data store ensures the chatbot only retrieves information from approved sources. Option B is wrong because safety filters block categories but not unverified content. Option C is wrong because high temperature increases creativity, risking unverified answers. Option D is wrong because model monitoring detects drift but does not restrict sources.

Answer

Enable strict safety filters to block any medical advice

Answer

Increase the temperature parameter to get more diverse responses

Answer

Use Vertex AI Model Monitoring to track answer accuracy

Question 2

A company wants to build a chatbot that can answer questions about its internal knowledge base using natural language. Which Google Cloud Generative AI offering should they use to quickly prototype and deploy this chatbot with minimal coding?

Accepted Answer

Generative AI Studio. Generative AI Studio provides a no-code/low-code environment to prototype and deploy chatbots with foundation models.

Answer

Vertex AI Endpoints

Answer

Cloud Natural Language API

Answer

Vertex AI Model Garden

Question 3

Which THREE of the following are features of Vertex AI Studio (Gen AI Studio)? (Choose 3)

Accepted Answer

Compare responses from different models side-by-side.. Option A, B, and E are correct. Gen AI Studio provides design, test, and prompt engineering capabilities. Option C (deployment of custom containers) is not a feature of Studio. Option D (pre-built safety filters) is a feature of the overall Vertex AI platform, but Studio focuses on prototyping.

Answer

Configure pre-built safety filters for generated content.

Answer

Deploy custom container images to Vertex AI endpoints.

Question 4

Refer to the exhibit. A developer has defined a dynamic action in the Vertex AI Agent Builder agent YAML. The agent is not triggering the action. What is the most likely issue?

Accepted Answer

The action name is misspelled. Option B is correct because the action name in the YAML is 'book_flight' but the agent may be expecting a different name (typo). Option A is wrong because the endpoint uses HTTPS, which is correct. Option C is wrong because the agent is defined. Option D is wrong because a 4xx error would still trigger the action but result in an error response.

Answer

The endpoint returns a 4xx status

Answer

The endpoint is not HTTPS

Answer

The agent is not enabled

Question 5

A company is evaluating Google Cloud's generative AI offerings for enterprise use. Which TWO considerations are most important when selecting the right model deployment option?

Accepted Answer

Data residency. Latency requirements and data residency are critical enterprise considerations. Model size and training time are secondary, and developer preference is not a primary factor.

Answer

Developer preference

Answer

Model size

Answer

Training time

Question 6

Which TWO safety features are available in Vertex AI Gemini API? (Select TWO.)

Accepted Answer

Safety filters for categories like hate speech and harassment. Vertex AI Gemini API provides safety filters (A) and content restrictions (C). B is not a standard Gemini API feature. D is a separate service. E is not a specific safety feature.

Answer

Model-level encryption at rest

Answer

Automatic redaction of personally identifiable information (PII)

Answer

Integration with Cloud Data Loss Prevention (DLP)

Question 7

A company is building a customer support chatbot using Vertex AI Agent Builder. They want the agent to answer questions based on their internal knowledge base. Which feature should they use?

Accepted Answer

Grounding with enterprise data stores. Option B is correct because Vertex AI Agent Builder supports grounding with enterprise data stores, allowing the agent to answer from internal knowledge bases. Option A is wrong because Google Search grounding is for public data. Option C is wrong because model tuning adapts the model, not the data source. Option D is wrong because prompt engineering is used to shape responses, not to provide data.

Answer

Grounding with Google Search

Answer

Model tuning

Answer

Prompt engineering

Question 8

A data scientist is using Vertex AI Model-as-a-Service (MaaS) to deploy a fine-tuned open-source model. They notice high latency during inference. What is the most likely cause?

Accepted Answer

The endpoint is set to autoscaling with a low minimum node count. Option C is correct because a low minimum node count in autoscaling can cause cold starts and high latency. Option A is wrong because model size is managed by MaaS and typically handled. Option B is wrong because quantization affects model size and speed, but the issue is more likely autoscaling. Option D is wrong because region does not directly cause latency spikes.

Answer

The model is too large for the hardware

Answer

The model is not quantized

Answer

The region is incorrect

Question 9

A company is using Gemini Pro for code generation. They want to ensure that the generated code does not contain security vulnerabilities. Which approach should they implement?

Accepted Answer

Implement a human-in-the-loop review with automated scanning. Option D is correct because for security, human review combined with automated scanning is best practice. Option A is wrong because custom safety filters are generic and not code-specific. Option B is wrong because grounding with scanning tools is not a standard feature. Option C is wrong because safety settings are about content harm, not code vulnerabilities.

Answer

Enable grounding with security scanning tools

Answer

Use the Vertex AI Codey API with safety settings

Answer

Use a custom safety attribute filter

Question 10

You want to use a Google foundation model to generate text summaries of news articles. Which Vertex AI service should you use?

Accepted Answer

Vertex AI Generative AI Studio. Option B is correct because Vertex AI Generative AI Studio provides access to foundation models for text generation. Option A is wrong because Vertex AI Prediction is for deploying custom models. Option C is wrong because Model Registry manages model versions. Option D is wrong because Feature Store is for ML features.

Answer

Vertex AI Prediction

Answer

Vertex AI Model Registry

Answer

Vertex AI Feature Store

Question 11

You are using Vertex AI Model Garden to deploy a Llama model. Which deployment option provides the best latency for real-time inference?

Accepted Answer

Deploy to Vertex AI Endpoint with a fixed number of replicas. Option C is correct because a fixed number of replicas avoids cold starts and provides consistent low latency. Option A is wrong because Compute Engine VMs require manual management and may not be optimized. Option B is wrong because MaaS with autoscaling can have cold starts. Option D is wrong because batch prediction is for asynchronous workloads, not real-time.

Answer

Use Batch Prediction

Answer

Deploy to a Compute Engine VM

Answer

Use MaaS (Model-as-a-Service) with autoscaling

Question 12

A company is using Vertex AI Agent Builder to create a travel booking agent. They want the agent to book flights and hotels dynamically. What action type should they use?

Accepted Answer

Webhook. Option A is correct because webhooks allow the agent to call external APIs dynamically. Option B is wrong because static calls are for predefined responses. Option C is wrong because 'Dynamic call' is not a standard action type. Option D is wrong because notifications are for sending updates, not performing bookings.

Answer

Dynamic call

Answer

Static call

Answer

Notification

Question 13

A team is deploying a real-time chat application using Gemini. They need to ensure the model does not generate harmful content. Which safety filter configuration should they use?

Accepted Answer

Set safety_threshold high for all categories. Option D is correct because setting high safety thresholds for all categories blocks more harmful content. Option A is wrong because model tuning is about task adaptation, not safety. Option B is wrong because grounding does not prevent harmful output. Option C is wrong because custom safety attributes are for additional categories, but still need thresholds.

Answer

Use grounding with a safe knowledge base

Answer

Implement custom safety attribute filters with low thresholds

Answer

Fine-tune the model with safe examples

Question 14

Which TWO components are essential for building a multi-turn conversational agent using Vertex AI Agent Builder? (Choose two.)

Accepted Answer

Dialogflow CX. Options A and C are correct. Dialogflow CX provides conversational flows, and Agent Builder Agent is the core agent resource. Option B is for prediction serving, not conversational building. Options D and E are storage/analytics, not essential for the agent itself.

Answer

BigQuery

Answer

Vertex AI Prediction

Answer

Cloud Storage

Question 15

A company is using Vertex AI Model Garden to discover and test various foundation models. They need a model that can generate code from natural language. Which model should they select?

Accepted Answer

Codey. Codey models are specifically designed for code generation and completion. Imagen generates images, Chirp generates speech, Med-PaLM is for medical domain.

Answer

Chirp

Answer

Med-PaLM

Answer

Imagen