scenario questions

A retail company wants to build an internal knowledge base chatbot using Vertex AI. They need to ensure the chatbot only answers from approved company documents and can handle updates without retraining. Which TWO components should they include? (Choose 2)

A healthcare startup uses a generative model fine-tuned on general medical literature to provide preliminary diagnostic suggestions from patient text. The model frequently misses rare diseases and sometimes suggests common conditions that are unlikely given the symptoms. The startup has a curated dataset of rare disease case reports and wants to improve the model’s sensitivity to rare conditions without sacrificing overall accuracy. They cannot afford to retrain the entire model from scratch. The model is deployed on Vertex AI Prediction with low latency requirement. Which approach should they take?

A media company is building an internal tool that generates first-draft marketing copy from campaign briefs. Legal insists that the tool never reproduce copyrighted third-party text verbatim, and the content team wants a measurable way to compare draft quality across prompt revisions. Which two-part approach best addresses both needs?

A large enterprise is deploying a generative AI system for automated contract review. The system must provide confidence indicators for its legal analysis. How should confidence indicators be implemented to maximize transparency?

A company uses a generative AI model to produce financial reports. They want to ensure content safety and prevent the generation of harmful or misleading information. Which TWO Google Cloud features should they configure? (Choose 2)

A financial services firm uses a fine-tuned model for contract analysis. They observe that the model's performance degrades after a few months because contract language evolves. The team wants to maintain accuracy without full retraining. What is the MOST cost-effective approach?

A company is establishing governance practices for generative AI models. Which three actions are essential for responsible AI deployment?

A team is fine-tuning a large language model on custom data using Vertex AI. They find that the training loss decreases but validation loss increases. What is the best course of action?

A global retailer's customer service team wants to deploy a generative AI chatbot that answers questions about order status, return policies, and product availability. The chatbot must always reflect the latest policies and inventory data without requiring frequent model retraining. Which approach should they use?

A financial institution wants to ensure compliance with GDPR when using a generative AI service that processes EU user data. Which measure is most directly required?

A government agency is deploying a generative AI chatbot to answer citizen questions about public services. The chatbot must provide accurate and consistent information, scale to handle peak loads during tax season, and comply with strict data sovereignty laws that require all data to stay within the country. The agency has a moderate budget and in-house IT team but limited AI expertise. Which deployment architecture should they choose?

A media company uses a generative AI model to create marketing images. They want to ensure that AI-generated images can be identified as synthetic. Which Google Cloud capability should they use?

A government agency is procuring a generative AI solution for public service information. They require that the system can provide explanations for its answers, protect citizen privacy, and comply with data residency laws. Which three capabilities should they mandate? (Choose three.)

A healthcare startup wants to generate synthetic patient notes for training medical residents. They need the output to follow a strict template with sections: Chief Complaint, History, Assessment, Plan. Which prompt engineering strategy should they use to ensure consistent structure?

A startup is using Vertex AI to build a generative AI application. They need to ensure that the AI-generated content does not contain hate speech or violence. Which service should they use?

A developer wants to experiment with Gemini Nano for on-device inference in a mobile app. Which Gemini API tier or environment provides access to Gemini Nano?

A company is fine‑tuning a large language model for a domain‑specific task. They have a limited budget and want to minimize the cost of fine‑tuning. Which TWO approaches are most cost‑effective?

A healthcare organization is deploying a generative AI application that processes Protected Health Information (PHI). They must ensure compliance with HIPAA. Which Google Cloud offering should they use?

A retail bank uses a generative AI assistant to answer customer questions about account policies. Compliance requires that every response cite the specific internal policy document section it used. Which approach best enforces this requirement?

A media company wants to automatically generate captions for video content in multiple languages. The captions should be synced with the audio timeline. Which combination of Google Cloud services is most appropriate?

A financial services firm is developing a GenAI application for investment advice. They need to ensure regulatory compliance. Which business strategy should they prioritize?

A data scientist is using Vertex AI generative AI studio to create a chatbot. The chatbot gives inconsistent answers to similar questions. Which parameter should they adjust to make responses more consistent?

A team is fine-tuning a large language model for medical advice. Which TWO techniques are most effective for improving the safety and reliability of the model's outputs?

Which TWO of the following are key differences between generative AI and discriminative AI? (Choose two.)

Despite applying safety filters, a generative AI model still produces toxic outputs in some cases. Which additional technique should be applied?

A company is building a generative AI chatbot for customer support using Vertex AI. They want to ground the model responses with their internal knowledge base stored in Cloud Storage and BigQuery. Which feature should they use to ensure the model only answers from the provided data and avoids hallucination?

Which TWO features are available in Vertex AI Studio for prompt engineering? (Choose two.)

A team is selecting a foundation model for a text summarization use case. They need to consider factors that affect both model performance and production deployment. Which THREE factors are most critical? (Choose three.)

A company wants to scale their generative AI application globally with low latency. Which infrastructure configuration is most suitable?

Which Google Cloud product provides access to pre-trained foundation models like Gemini?

A marketing team is using Vertex AI's text generation model to create product descriptions. They want to control the randomness of the output to ensure consistent, focused messaging for a new product line. Which parameter should they adjust to reduce randomness and make the output more deterministic?

A financial services firm is using a generative AI model to answer customer queries about account balances. The model sometimes provides outdated information because it relies on its training data. The firm wants to ensure the model always uses the most current account data. Which technique should they use?

A compliance officer requires that all AI-generated content in Google Workspace be reviewed before sharing externally. Which change management approach BEST supports this requirement while maintaining user adoption?

A research team is using a large language model to analyze medical research papers and generate summaries. They need to minimize hallucinations while retaining key details. They have access to a curated database of paper abstracts. Which approach is best?

A financial services company needs to deploy an AI model that handles highly sensitive transaction data. They require that the model's predictions cannot be inspected by any third party, and the data must remain encrypted at all times, including during inference. Which Google Cloud feature should they use?

A company wants to generate marketing images for a new product launch using GenAI. Which Google Cloud service should they use?

A company is migrating a GenAI proof-of-concept to production. During the pilot, they used a large model (e.g., Gemini 1.5 Pro) and incurred high costs. The use case is simple: generating short product descriptions from structured data. Which cost optimization strategy should they implement first?

A retail company wants to use generative AI to generate product descriptions for thousands of items. They need to ensure that the descriptions are consistent with their brand voice and do not contain factual inaccuracies. What is the most effective strategy?

A marketing team is using a generative AI model to create ad copy. They want to control the randomness of the output so that the same prompt produces consistent results for A/B testing. Which parameter should they adjust?

A large e-commerce company deploys a generative AI chatbot on Vertex AI for customer service. The chatbot is powered by a fine-tuned model on the company's historical support tickets. Despite high accuracy on training topics, the chatbot frequently gives irrelevant or off-topic answers when customers ask about new products or promotions. The company maintains a comprehensive product catalog and a knowledge base of current promotions. The chatbot's prompts include a system instruction to 'Answer based on your knowledge' and no other retrieval mechanism. The response time requirement is under 3 seconds. Which course of action should the team take?

A global retailer wants to deploy a generative AI assistant that answers employee questions about HR policies in English, Spanish, and Japanese. The HR policy documents are updated monthly, and the company wants to avoid retraining the underlying large language model. Which approach should the retailer use?

A global corporation with 50,000 employees has seen rapid adoption of GenAI across marketing, product, and engineering teams. Each team selected its own models and cloud accounts, resulting in fragmented governance, unexpected costs, and varying output quality. The CFO demands a unified strategy to control costs and ensure consistency. The Chief AI Officer proposes several solutions. Which course of action best balances control with innovation?

Which THREE approaches are effective for reducing bias in generative model outputs? (Choose three.)

A company is building a GenAI chatbot that needs to answer questions using real-time data from their CRM and inventory systems. They want to ensure the model can access external data on demand. Which approach should they use?

A financial institution wants to use Gemini to analyze customer support transcripts and generate summaries. They need to ensure that personally identifiable information (PII) is not included in the summaries. Which approach should they take?

A retail bank uses a Gemini model on Vertex AI to answer customer questions about its mortgage products. Testers report that the model sometimes invents interest rates that do not exist in the bank's rate sheet. The team wants the model to ground its answers only in an approved corpus of product documents and cite the passages it used. Which approach should they implement?

A media company wants its editors to summarize long internal research documents. Legal requires that no document content be used to train or improve any model, and that data stays within the company's Google Cloud project. Which capability should the company verify before adopting a Gemini-based solution on Vertex AI?

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?

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?

A software company wants to build a generative AI application that can answer questions based on its internal documentation. The documentation is stored in Google Drive and Confluence. They need a managed solution that can index these sources, provide relevant answers with citations, and integrate with their existing identity provider for access control. Which Google Cloud service should they use?

A marketing team wants to generate social media posts using generative AI. They need the tone to be consistent with their brand voice. Which two prompt engineering techniques should they use? (Choose TWO)

A team is tuning a large language model for a question-answering task. They notice the model gives high confidence scores to answers that are factually incorrect. Which evaluation metric should they primarily use to detect this overconfidence problem?

A financial services firm needs to deploy a generative AI model that generates reports from structured and unstructured data. The solution must ensure that outputs never contain sensitive customer information. Which combination of Google Cloud services should they use?

A company is fine-tuning a generative AI model on proprietary customer data. They are concerned about copyright and IP issues when using the model commercially. What is the BEST practice to mitigate these risks?

A retail company is building a product description generator using a large language model on Vertex AI. They need to ensure the generated descriptions do not contain offensive language. Which strategy should they implement?

A developer is using Vertex AI Studio to prototype a chat application. They want to provide the model with a system instruction to set the tone and style. How should they configure this in the Vertex AI Studio interface?

Which of the following is a best practice when using Vertex AI for prompt engineering?

A team is fine-tuning a model for a legal document summarization task. They need to ensure high accuracy and avoid hallucinations. Which TWO approaches should they combine? (Choose two.)

A marketing team is using a generative AI model to create ad copy. They notice that the outputs sometimes include made-up statistics and false claims about their products. They want to reduce these hallucinations without retraining the model. What should they do?

An e-commerce company fine-tunes a model on customer reviews to generate product feedback summaries. They want to ensure the model does not reproduce toxic language from the training data. Besides filtering the training data, which additional technique is most effective at inference time?

A startup with limited ML expertise wants to add a GenAI feature to their SaaS application that can generate personalized email drafts for users. They need fast time-to-market and low maintenance. Which build-vs-buy decision is BEST?

A company is using Vertex AI RAG Engine to ground a chatbot in internal documents. The chatbot sometimes returns outdated information. Which TWO steps should they take to improve freshness?

A user provides a long document as context for a question-answering task, but the model outputs irrelevant answers. What is the most likely cause?

A company is using Google Cloud's generative AI offerings to build a customer-facing application. They need to ensure that the AI-generated content complies with their brand guidelines and does not produce harmful or inappropriate responses. They also want to monitor and filter content in real-time. Which Google Cloud feature should they use?

A financial analytics firm is building a generative AI application that must analyze long earnings call transcripts and produce summaries. The transcripts often exceed 200,000 tokens, and the firm wants to minimize cost while maintaining high accuracy. They plan to use Gemini models on Vertex AI. Which approach should they take?

A company is evaluating the ROI of implementing GenAI for code generation. Which metric BEST captures the productivity improvement of developers?

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?

A marketing team wants to use generative AI to create ad copy that matches their brand voice. They have several examples of previous high-performing ads. Which Vertex AI Studio feature would best help them achieve consistent tone and style without custom model training?

An employee wants to use GenAI to assist with writing formulas in Google Sheets. Which Gemini for Google Workspace feature should they use?

A social media company uses a generative AI model to moderate user posts. The model occasionally allows offensive content. Which safety technique should be implemented?

What is the primary purpose of the temperature parameter in a generative language model?

A developer is using Vertex AI PaLM API to generate code snippets. The responses sometimes contain security vulnerabilities. What is the best practice to mitigate this?

A fintech startup is building a generative AI application that generates personalized investment advice based on user profiles and market data. They are using Vertex AI Agent Builder to create an agent that retrieves information from a BigQuery table containing user data and from a real-time market data API. The agent needs to ensure that responses comply with financial regulations, meaning the model must not give specific stock recommendations unless the user explicitly requests them after disclaimers. The team has implemented grounding with both sources. During testing, the agent sometimes spontaneously suggests buying a particular stock without being asked, which could lead to regulatory issues. The team wants to enforce strict control over the agent's behavior. What should the team do?

A large enterprise has deployed generative AI assistants in three separate departments (HR, Marketing, and Customer Support) using different tools and models. Over the past quarter, the company has observed escalating cloud costs, inconsistent user experiences, and reports of data leakage in Customer Support logs. The CTO wants to address these issues while maintaining innovation velocity. As the Generative AI Leader, what course of action should you recommend?

A multinational corporation is using Vertex AI to generate multilingual customer support responses. They have fine-tuned the Gemini model on support tickets in English and now want to extend to 10 additional languages. The fine-tuning dataset for new languages is small (1000 tickets each). During evaluation, the model performs well for common languages (Spanish, French) but poorly for languages like Finnish and Thai. The team needs to improve performance for low-resource languages. They have budget constraints and cannot collect more data quickly. Which approach should they take?

A company is deploying a generative AI system that generates customer-facing emails. The system must ensure outputs are not toxic, biased, or harmful. Which TWO techniques are most effective for reducing toxicity in model outputs without significantly affecting performance?

Which of the following is a key Google AI Principle that directly addresses the need to avoid creating or reinforcing unfair bias?

A large enterprise is planning to roll out a GenAI assistant for contract negotiation. The legal team wants to ensure that the assistant's outputs are consistent and follow a predefined format for downstream processing. What is the BEST prompt engineering technique?

A company is considering migrating from AWS Bedrock to Google Cloud for generative AI. They want to leverage Google's unique differentiators. Which THREE advantages does Google Cloud offer over AWS Bedrock and Azure OpenAI? (Select 3 options.)

A data science team wants to compare semantic similarity between thousands of customer reviews to identify emerging themes. Which Google Cloud service and approach should they use?

A research team is training a large multimodal model and needs to minimize training time for a fixed budget. Which Google Cloud infrastructure is specifically designed for large-scale training workloads?

A company is evaluating whether to use a pre-built API or fine-tune a model for their use case. They have a large dataset of domain-specific jargon and need high accuracy on specialized terms. Which factor MOST strongly suggests fine-tuning?

A data scientist is evaluating a generative AI model for gender bias in its text outputs. They have a test set of 1,000 gender-neutral prompts. Which approach is MOST appropriate for measuring output bias?

A media company wants to automatically generate concise summaries of news articles using a generative AI model. They need a fully managed service that provides access to Google's foundation models without requiring machine learning expertise. Which Google Cloud offering should they choose?

A national logistics company is preparing a board presentation on responsible generative AI adoption. The board wants assurance that the program includes concrete organizational controls, not just technical safeguards. Which TWO actions should be included in the governance plan? (Choose two.)

A global e-commerce company is using Vertex AI to build a generative AI chatbot for customer support. The chatbot is powered by the Gemini 1.5 Pro model and uses a vector search index for retrieval-augmented generation (RAG) over product documentation. The company has deployed the application in four regions (us-central1, europe-west4, asia-east1, and australia-southeast1) using a multi-region deployment with a global endpoint. The application is critical and requires high availability with a target latency of under 500ms for the RAG pipeline. Recently, users in Australia are experiencing inconsistent latency spikes, with response times exceeding 2 seconds during peak hours. The team suspects that the issue is related to the vector search index's replication and serving configuration. The index has 10 million embeddings with a dimension of 768. It is stored in a single regional bucket in us-central1, and the vector search index endpoint is deployed in all four regions with the same deployed index ID. The team is using the default configuration for index updates and serving. Which action should the team take to resolve the latency issue for Australian users?

A data scientist is evaluating the output quality of a text generation model. They observe that the model often repeats phrases and produces very generic responses. Which THREE parameter adjustments could help increase diversity and reduce repetition? (Choose three.)

A company is using Vertex AI to fine-tune a large language model on proprietary customer support transcripts. The transcripts contain personally identifiable information (PII) such as names and email addresses. What is the BEST practice to comply with Google's AI Principles on privacy?

A developer is tuning a text-generation model for creative writing. They want the outputs to be more diverse and less repetitive. Which THREE parameters/changes can help? (Choose three.)

A media company uses Gemini models on Vertex AI to draft news briefs from long press releases. Editors report that drafts sometimes invent quotes and statistics that do not appear in the source. The team wants to reduce these fabrications while keeping the model's fluent writing. Which TWO techniques should they apply? (Choose two.)

An enterprise wants to adopt GenAI across departments but faces resistance from legal and compliance. Which strategy should the AI leader prioritize?

A retail bank's risk committee will only approve a generative AI assistant for internal policy questions if every model output can be traced to an approved source, unsafe outputs are blocked before display, and reviewers can see why a response was allowed or denied. Which combination of Google Cloud capabilities should the architects design around?

A company wants to offer a generative AI feature where the output must follow a very specific tone and style as per the brand guidelines. Which strategy is most reliable?

A healthcare company is using a generative AI model to produce patient education materials. They want to ensure the output is accurate, avoids harmful advice, and adheres to medical guidelines. Which TWO techniques should they implement to improve the safety and reliability of the model's output? (Choose two.)

A startup is deciding between using a pre-trained model via API vs. hosting their own open-source model. Which factor is most critical for their decision?

A data science team wants to build a RAG pipeline to ground a chatbot in proprietary knowledge. They need to choose a vector database and embedding model. Which combination is NATIVELY integrated with Vertex AI and requires the least custom infrastructure?

Which TWO of the following are capabilities of Vertex AI Model Garden? (Choose 2)

What is the primary purpose of Google DeepMind's SynthID technology?

A hospital wants to use a generative AI model to draft patient discharge summaries. The model must be able to understand medical terminology and generate coherent, context-aware text. Which type of generative AI model is most suitable?

A data scientist fine-tunes a model on a small proprietary dataset. After fine-tuning, the model repeats training examples verbatim. What is the most effective mitigation?

A startup wants to experiment with Gemini prompts in a browser-based console, compare responses from different models, and save promising prompts for later reuse, without provisioning infrastructure. Which Google Cloud offering best fits this need?

A telecom company wants to launch a generative AI assistant that summarizes support tickets for agents. Leadership asks how to measure whether the pilot is delivering business value before expanding it. Which approach best evaluates business impact?

A marketing agency wants to use Vertex AI to automatically generate social media posts for clients. They plan to use the Gemini API with few-shot prompting. The agency's developers have limited experience with generative AI and want the fastest way to prototype and iterate on prompts. They are already using Google Cloud for other services. Which approach should they take to quickly develop and test prompts?

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?

A company is using a fine-tuned generative model to create marketing copy. They want to ensure that when the model references statistics, it provides citations to original sources. Which technique should they use?

A hospital deploys a generative AI model to assist in diagnosing rare diseases. The model sometimes suggests treatments that are not widely accepted. To align with Google's AI Principle of being accountable to people, what should the hospital implement?

A healthcare startup needs to deploy an AI model that processes protected health information (PHI). They require a HIPAA BAA with the cloud provider. Which Google Cloud AI service can meet this compliance requirement?

A media company plans to use generative AI to draft marketing copy for dozens of regional brands. Legal wants confidence that outputs respect brand tone and avoid unapproved claims, while finance wants to know how usage will be metered. Which two Google Cloud practices best support these goals? (Choose two.)

A healthcare company needs to process medical records at scale, extracting structured information from forms and enabling natural language queries. They require HIPAA compliance and want to avoid training custom models. Which TWO services should they use? (Choose 2)

A healthcare organization is evaluating Google Cloud's generative AI offerings for building a patient triage assistant. They need a model that can process text and images from patient records and generate text responses. They also require the ability to fine-tune the model on their own data. Which two Google Cloud services or features should they use? (Choose two.)

A government agency is deploying a generative AI system to assist in processing visa applications. The system must be transparent about its limitations and provide clear indications of its confidence in each recommendation. Which approach BEST addresses explainability and accountability?

A marketing analyst at a retail company wants to use a generative AI model to draft product descriptions for 500 new items. The analyst expects the model to understand the context of each product from a short prompt and produce varied, coherent text. Which core capability of generative AI is the analyst primarily relying on?

A team is evaluating whether to build a custom fine-tuned model or use a pre-built API for a document summarization task. Which TWO factors most strongly support using a pre-built API?

A healthcare analytics team uses Gemini on Vertex AI to extract structured data from clinical notes. The model occasionally outputs invalid JSON, breaking downstream processing. The team wants to enforce a strict output schema. Which approach should they use?

A startup wants to build a text-to-speech application for generating audiobooks. Which Google Cloud generative AI service is best suited for this task?

A company wants to build a chatbot that can answer questions about recent news events up to the current date. They want to minimize hallucinations and ensure factual accuracy. Which Google Cloud feature should they integrate?

A gen AI application produces hallucinations (factually incorrect outputs). Which mitigation strategy is LEAST effective?

A machine learning engineer is deploying a large generative model on Vertex AI. The model requires a GPU with high memory. Which machine configuration should they choose?

A company is using Vertex AI Gemini API to analyze customer feedback. They notice that the model occasionally generates offensive content. They have already set safety settings to block high-probability harmful content. What additional step should they take to further reduce offensive outputs?

A healthcare organization wants to use generative AI for clinical decision support. They must comply with regulatory requirements for high-risk AI systems. Which THREE measures should they implement? (Choose 3)

A media company uses Vertex AI to generate video captions. The generated captions sometimes contain factual errors about named entities (e.g., actor names). Which technique would most likely reduce these errors?

An enterprise architect must let a fleet of internal applications call Gemini models on Google Cloud while enforcing VPC Service Controls perimeters, customer-managed encryption keys, and audit logging tied to the organization's existing IAM. Which Google Cloud offering should the architect standardize on?

A financial services firm wants to deploy a generative AI assistant for employees. The assistant must not reveal any customer data and must comply with internal policies. Which Google Cloud capability should they use to control the assistant's responses based on defined safety and privacy rules?

A marketing team wants to generate product descriptions from a short list of features using a Google Cloud generative AI model. They have no labeled examples and want to avoid any model training. Which approach should they use?

A marketing team wants to use a generative AI model to create ad copy in multiple languages. They are new to Google Cloud and want the fastest way to start experimenting without writing code. Which tool should they use?

A financial services firm is deploying a Gemini-based application that must comply with GDPR. The application processes customer queries and may include personal data. Which Google Cloud capability should the firm use to ensure that the model does not expose personally identifiable information (PII) in its responses?

A research team is fine-tuning a large language model on a dataset containing personal data of EU citizens. They must comply with GDPR. Which measure is ESSENTIAL?

A financial institution wants to deploy a gen AI model for fraud detection but must comply with strict regulations regarding explainability. What is the best strategy?

Which TWO methods are most effective for improving factual accuracy in a language model's responses? (Choose two.)

A team is evaluating whether to use reinforcement learning from human feedback (RLHF) or in-context learning for a chatbot. Which TWO statements correctly describe trade-offs? (Select two.)

A healthcare technology company is using Vertex AI to build a generative AI assistant that answers patient questions about medications. They must ensure the assistant does not provide medical advice and adheres to safety guidelines. Which Google Cloud feature should they use to enforce these constraints?

A developer is experimenting with a Gemini model in Vertex AI Studio and notices that for the same prompt, the model produces different answers each time. The developer needs the output to be as consistent and deterministic as possible for a classification task. Which parameter change should they make?

A media production studio wants to create short video clips from text prompts for social media content. They need a Google Cloud generative AI model that can generate videos from text. Which offering should they use?

A developer is building a generative AI application using Vertex AI and wants to ensure that the model's responses are safe and aligned with their company's content policies. They need to filter out harmful content such as hate speech and harassment from both user inputs and model outputs. Which Vertex AI feature should they configure?

A graphic design company wants to generate high-quality synthetic images for product mockups. Which Google Cloud generative AI service is most suitable?

A company uses a generative AI model to generate product descriptions. They notice variations in style and length across products. How can they enforce consistent formatting?

A healthcare company wants to use generative AI to summarize patient notes while ensuring compliance with strict data privacy regulations. They plan to use Google Cloud's Vertex AI. Which two features should they implement to protect sensitive data? (Choose two.)

A university research team wants to summarize long academic papers using a Google Cloud model. They need a model that supports very large context windows so an entire paper fits in a single request. Which Gemini model characteristic should they prioritize?

A bank is deploying a Gemini-powered assistant on Vertex AI to answer questions about loan products. Compliance requires that every answer be traceable to an approved internal source and that the assistant refuse to answer when no approved source supports the response. Which configuration should the bank implement?

A machine learning engineer needs to deploy a Gemini model on an Android device for offline inference (no internet connection) to provide real-time suggestions. Which Gemini model variant is MOST appropriate?

A project manager wants to measure the success of a generative AI feature that summarizes meeting transcripts. Which TWO metrics are MOST appropriate for evaluating quality improvement?

A startup is developing an AI tool that generates legal contract summaries. Lawyers will use these summaries for advice. What human oversight mechanism is MOST critical for responsible deployment?

A marketing team wants to generate product descriptions from a short bullet list of features. They need a Google Cloud service that provides a web-based console for writing prompts, comparing model responses, and adjusting parameters like temperature without writing code. Which service should they use?

A company notices that their GenAI-powered code review assistant sometimes suggests code with security vulnerabilities. They want to reduce this risk without sacrificing review speed. Which approach is MOST effective?

To improve factuality in generative AI, which is the best approach?

A data science team is fine-tuning a large language model using Vertex AI to generate marketing copy. They notice that the generated text is often repetitive and lacks creativity. Which technique should they apply to improve output diversity?

A financial services company uses a generative AI model to produce customer-facing investment advice. They need to ensure the model's outputs can be traced back to specific sources. Which explainability technique is BEST suited for this requirement?

A research team uses a generative AI model to answer questions about internal technical documents. The model sometimes provides outdated information because it relies on its pretrained knowledge instead of the latest documents. The team wants the answers to be based on the current document set. Which technique should they implement?

A hospital wants to build a generative AI assistant that answers clinician questions using the hospital's own clinical guidelines. The guidelines change frequently, and the hospital wants the assistant to cite the exact guideline section used. Which approach best meets these requirements while minimizing model retraining?

A company is evaluating the ROI of deploying a GenAI code review assistant. They want to measure productivity gains. Which metric is MOST directly tied to developer efficiency?

A developer wants to quickly prototype a multimodal application that can process images and text using the Gemini API without incurring any cost. Which access tier should they use?

To ensure that a generative AI model uses the most current information from the web for answering user queries, which Vertex AI feature should be enabled?

A company wants to measure the ROI of a GenAI-based report generation tool. Which metric is MOST directly tied to business value?

A mid-size accounting firm wants to deploy a generative AI assistant that summarizes client meeting notes and drafts follow-up emails. The partners require that client financial data never leaves the firm's Google Cloud project boundary for third-party training, and that usage costs stay predictable month to month. Which two Google Cloud practices should the firm adopt? (Choose two.)

A product team is using a generative AI model to summarize customer feedback from multiple sources. The summaries are sometimes missing key themes or including irrelevant details. The team wants to improve the quality of the summaries without retraining the model. (Choose two.)

A financial services firm is deploying a generative AI chatbot to answer employee questions about internal policies. The firm must ensure that the chatbot does not reveal sensitive information from other departments. Which technique should they implement?

A global retailer's legal team is reviewing a proposed generative AI solution that drafts personalized marketing copy for customers in the EU. The team wants to confirm whether the solution can meet the EU AI Act's transparency obligations for AI-generated content while still using Google Cloud managed services. Which approach best satisfies the transparency requirement?

A media company is evaluating Google Cloud generative AI offerings to build a production application that summarizes long articles and generates headlines. They want to use Gemini models with enterprise controls and need to understand which capabilities are provided by Vertex AI. (Choose two.)

A developer is using Vertex AI Studio to test prompts for a text generation model. They want the model to follow a specific output format (JSON). Which prompt engineering approach is most effective?

A developer is building a code‑generation assistant using the Codey API on Vertex AI. The assistant should generate Python functions based on natural language descriptions. However, the generated code sometimes contains syntax errors. Which parameter adjustment would MOST directly help reduce syntax errors?

A company is evaluating Google Cloud vs AWS Bedrock for building a multimodal application that needs to understand images, video, and text in a single model. Which unique Google Cloud capability supports this requirement?

A team is using Vertex AI Pipelines to deploy a generative AI model for real-time inference. The model sometimes generates harmful content. They want to implement a safety filter that checks the output before returning it to the user, but they need to minimize latency. Which approach best balances safety and performance?

A data science team is building a document question-answering assistant on Vertex AI. Users report that answers are sometimes fabricated when the retrieved passages do not contain the answer. Which TWO techniques should the team apply to reduce hallucinations? (Choose two.)

A research team uses a generative AI model to analyze historical texts. They want to provide users with insight into the model's reasoning process. Which explainability technique should they implement?

A media company wants to use Google Cloud generative AI to produce short video clips from text prompts for internal storyboarding. The team needs a managed model that can generate video from text and wants to evaluate it before committing to production. Which two Google Cloud offerings or capabilities should they use? (Choose two.)

A media company wants to add generative AI features to its mobile app but must control costs and prevent unexpected spend as usage grows. Leadership wants visibility into consumption by product team. Which governance approach should the GenAI Leader recommend on Google Cloud?

A developer is building a code generation assistant using Codey. They notice that the generated code sometimes contains deprecated API calls. What is the most likely cause?

An e-commerce company is using Vertex AI PaLM 2 for Text (via Model Garden) to generate product descriptions. They have an existing pipeline that calls the model with a prompt including product attributes. Recently, they migrated to the Gemini API. The team notices that the Gemini model sometimes outputs descriptions that are factually inconsistent with the input (e.g., wrong color or size). This was less frequent with PaLM 2. They have not changed the prompts. What is the most likely cause and solution?

A developer wants to generate Python code using Google Cloud's generative AI. Which model should they invoke?

An organization is planning to roll out a generative AI internal knowledge base assistant to employees. They want to ensure adoption and manage change effectively. Which two change management practices should they prioritize? (Choose TWO)

A developer uses the Gemini API to summarize long articles. The summaries often miss key points from the end of the article. Which technique specifically addresses this length-based loss of information?

A media company wants to use a generative AI model to create marketing copy that includes citations to original sources. Which feature should they enable to ensure the model provides accurate attributions?

A company plans to commercially use images generated by a text-to-image model. What should they check to avoid copyright issues?

A model response deployed on Vertex AI includes safety attributes with a toxicity score of 0.9 and an insult score of 0.3. The application must reject any prediction where the toxicity score exceeds 0.8. Based on the response, what action should the application take?

A social media company uses a generative AI to moderate user comments. They need to filter hate speech, violence, and sexual content. What is the most efficient way to implement content safety in Vertex AI?

A company with limited AI expertise wants to adopt gen AI. They need a solution that integrates with existing data and applications. Which Google Cloud offering is best?

A company is deploying a generative AI application using Vertex AI. They need to minimize latency for real‑time inference while maintaining high quality. Which TWO actions are most effective?

A data science team wants to decide between using a pre-built API (e.g., Vertex AI Gemini API) and fine-tuning a custom model for a specific business task. Which TWO factors are most important in making this build versus buy decision?

A global nonprofit organization is deploying a generative AI chatbot to provide educational content in multiple languages to underserved communities. They operate in regions with limited internet connectivity. The chatbot must work offline or with minimal data usage. The team has a moderate budget and limited technical staff. Which deployment strategy should they use?

A data scientist wants to apply reinforcement learning from human feedback (RLHF) to improve a chatbot's helpfulness. Which TWO steps are part of the RLHF process? (Select 2)

A company is piloting a GenAI feature for internal knowledge base search. During the pilot, users report that the AI sometimes gives incorrect answers based on outdated documents. What is the MOST effective way to address this issue?

A startup is building a multimodal application that needs to process both images and text. They want to prototype quickly for free before moving to production with enterprise controls. Which TWO services should they use? (Choose 2)

A healthcare startup is using a large language model (LLM) to generate discharge summaries. To comply with regulations, they need to ensure that a human reviews all AI-generated summaries before they are sent to patients. Which Google Cloud feature should they use to enforce this workflow?

A marketing team wants to generate blog post ideas and draft outlines. They need a solution that works within Google Docs and leverages a foundation model without leaving the document editor. Which service should they use?

A developer wants to use a pre-trained model to identify objects in images. Which Google Cloud AI API should they use?

A software vendor is building a product that must call a Gemini model through a stable, versioned API with enterprise controls such as VPC Service Controls, and must run on Google Cloud infrastructure. Which Google Cloud offering should the vendor use?

Refer to the exhibit. A developer executed the command to list endpoints. They notice that two models are deployed to the same endpoint. What is the most likely reason for this configuration?

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

A retail company uses Vertex AI Agent Builder to create a virtual assistant for order tracking. Users frequently ask about delivery dates, but the assistant sometimes gives incorrect information. The team wants to improve accuracy without retraining the underlying model. Which technique should they apply?

A startup wants to embed generative AI features into their mobile app but has limited ML expertise. Which Google Cloud service is best suited for rapid integration with no ML training?

A financial services firm is evaluating Google Cloud generative AI offerings for an internal knowledge assistant. They need capabilities for controlling access to model endpoints and for monitoring model usage and safety signals. (Choose two.)

A company is transitioning a generative AI pilot to production. They need to ensure cost predictability and scalability. Which THREE actions should they take?

A financial services firm needs to use Gemini for analyzing customer transaction data. They require that all data remain within their VPC and that model inference logs be auditable. Which access tier should they choose?

A financial services firm uses a generative AI model on Vertex AI to answer employees' HR policy questions. The model sometimes invents policy details. The firm wants answers grounded in the official HR handbook and needs to cite the source section. Which solution should they implement?

A global retailer wants to build a generative AI application on Google Cloud that answers employee questions about HR policies. The team must ensure the application uses their private policy documents, keeps answers grounded in those documents, and avoids exposing confidential content to unauthorized staff. Which two Google Cloud components should they include in the architecture? (Choose two.)

A healthcare organization wants to build a generative AI application that summarizes patient notes. They are concerned about the model generating harmful or inappropriate content. Which Google Cloud service should they use to filter out such content in real time?

A company uses a generative AI model to answer customer queries. The model sometimes returns outdated information. Which technique should they apply to ensure responses rely on current data?

A marketing team wants to use a generative AI model to create blog post drafts from short product descriptions. They need the model to produce varied, creative text each time they run it. Which configuration parameter should they adjust to control the randomness of the output?

A developer is using the Gemini API to generate creative product taglines. The taglines are often bland and uncreative. The developer wants more variety and novelty in the outputs. Which parameter adjustment would most effectively increase the diversity of the generated taglines?

A healthcare company is using a generative AI model to draft patient education materials. The model sometimes includes outdated medical advice. The team wants to ensure the content reflects the latest clinical guidelines. They have a database of current guidelines and want to integrate it into the generation process without retraining the model. Which approach should they use?

A financial services firm is using Vertex AI to generate investment reports. They need to ensure that the model outputs are explainable and comply with regulatory requirements. Which Vertex AI feature should they use?

A company deploys a Gemini model on Vertex AI for a healthcare application. They need to ensure that the model does not generate medical advice and that responses are grounded in trusted medical sources. Which combination of safety measures should they implement?

A global e-commerce company uses generative AI to generate product descriptions in multiple languages. They want to ensure consistency across markets while respecting cultural nuances. Which THREE strategies should they adopt?

A national retailer's generative AI pilot for product description writing succeeded technically, but six months later only two of forty merchandising teams use it. Interviews reveal that teams were never trained, the tool sits outside their existing content workflow, and no one owns adoption targets. Which action best addresses the root cause of this outcome?

What is the primary function of embeddings in the context of generative AI?

A project manager wants to reduce the cost of using Gemini API for batch processing of customer feedback. The team is on a tight budget. Which cost management strategy is MOST effective?

A machine learning engineer is tuning a large language model on Vertex AI for question answering. They want to evaluate the model's performance before deployment. Which THREE metrics should they consider?

A data science team is choosing between Gemini Pro and Gemini Flash for a real-time content moderation API. They need low cost and low latency, but can tolerate slightly lower accuracy. Which TWO Gemini variants should they consider?

An organization wants to use AI-generated images commercially. According to Google's AI principles and copyright guidelines, what should they do FIRST?

A company develops a generative AI model for resume screening. They discover that the model is rejecting candidates from certain demographic groups disproportionately. Which step should they take first to address unfair bias?

Which TWO are advantages of using Retrieval-Augmented Generation (RAG) over fine-tuning?

A developer is using the Gemini API to generate creative marketing copy. They want the output to be more diverse and unexpected. Which parameter should they increase?

A team is deciding between using fine-tuning and in-context learning for a document classification task. They have 500 labeled examples and need low latency. Which TWO statements are accurate?

Which Google Cloud offering allows you to create a machine-readable document that describes a model's intended use, performance, and limitations?

A media company wants its editorial staff to draft blog posts inside a web-based workspace where Gemini can summarize uploaded research PDFs, generate outlines, and cite files from the team's shared drive, all without writing code or managing any Google Cloud infrastructure. Which Google Cloud generative AI offering best fits this requirement?

A company wants to use AI-generated images commercially. They are concerned about copyright and IP issues. Which action should they take FIRST to mitigate legal risk?

Refer to the exhibit. A Vertex AI endpoint configured with the above deployment is returning HTTP 429 (Too Many Requests) errors during peak traffic. The current CPU utilization reaches 80% consistently. What should the team adjust to resolve this?

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

A company uses Gemini 1.5 Pro to analyze customer call transcripts and generate summaries. They notice that the summaries occasionally include fabricated details that were not in the transcript. Which technique is specifically designed to reduce such hallucinations?

A multinational corporation deploys a generative AI chatbot for customer support in the EU. They must ensure compliance with GDPR regarding user data used for fine-tuning. Which data governance practice is REQUIRED?

A bank wants to use LLMs to generate responses for customer support chat. All conversations must be logged, and any PII must be masked. The solution must comply with financial regulations. Which combination of Vertex AI services should be used?

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?

Refer to the exhibit. A team has deployed a model to an endpoint with the configuration shown. They notice that during peak traffic, the endpoint frequently returns 429 (Too Many Requests) errors. Which action should they take to resolve this issue?

A financial services company wants to automate contract analysis to extract key clauses and identify risky terms. They have thousands of PDF contracts and need a solution that can be quickly integrated into their existing document management system. Which Google Cloud service is MOST suitable?

Refer to the exhibit. A data scientist is fine-tuning a model. The training loss and accuracy are improving each epoch. However, after training, the model performs poorly on a held-out validation set. What is the most likely issue?

A media company uses a generative AI model to draft weekly newsletter articles from bullet points. The drafts are factually correct but read as terse and disjointed. Editors want smoother narrative flow without changing the underlying facts. Which technique should they apply first to improve the output?

A software company is using a large language model to generate code snippets from natural language descriptions. The generated code often contains syntax errors or uses deprecated functions. The team wants to improve the correctness of the code. Which technique should they use?

A company is migrating an on-premises NLP pipeline to Vertex AI. Which three capabilities of Vertex AI align with common MLOps best practices for generative AI? (Choose THREE)

A financial services firm uses a generative AI model to summarize quarterly earnings calls. The summaries must consistently follow a strict format: an executive summary, key financial metrics, and forward-looking statements. The model sometimes omits sections or changes the order. Which technique should they use to enforce the structure?

A developer uses a code generation model to write Python functions. The output frequently contains syntax errors due to incorrect braces and indentation. Which technique should be used to produce syntactically valid code?

A marketing agency uses gen AI for content generation. They need to brand consistently. What is a key business consideration?

A real-time customer support chatbot using Gemini is experiencing high latency. The team must maintain response quality while improving speed. Which technique should they implement?

A team uses PaLM 2 API to generate product descriptions, but the output sometimes contains factual inaccuracies. What is the best approach to improve accuracy?

A startup wants to generate images from text descriptions for their marketing materials. They prefer a managed service that requires minimal coding. Which Google Cloud generative AI offering should they use?

A company wants to extract structured data from scanned invoices. Which Google Cloud AI service is purpose-built for this use case?

A data scientist runs the above command to upload a model to Vertex AI Model Registry. The model is a TensorFlow 2.6 model trained on tabular data. After deployment to an endpoint, the prediction latency is higher than expected. What is the most likely cause?

A developer wants to quickly experiment with different foundation models available in Google Cloud. Which tool should they use?

An organization is developing a GenAI strategy for multiple business units. Which THREE steps should they take to ensure alignment? (Select three.)

A media company uses Gemini on Vertex AI to generate short news summaries from long articles. The summaries frequently miss key facts and sometimes include details not in the source. The team wants to improve factual grounding and coverage without retraining the model. (Choose two.)

A company wants to use generative AI to summarize customer support tickets. Which Google Cloud tool is best suited for this task?

A healthcare AI application provides diagnostic suggestions based on patient data. To comply with Google's AI Principles, which practice should be implemented?

A healthcare organization deploys a generative AI model to assist in diagnosing rare diseases from medical images. To comply with the EU AI Act's requirements for high-risk AI systems, what is the MOST critical control they must implement?

A developer is using Vertex AI's Generative AI Studio to prototype a text summarization model. The initial results are too verbose. What is the most efficient way to adjust the output length without retraining?

A company uses a text-to-image model to generate marketing visuals. The outputs often contain distorted human faces. Which technique is most likely to improve face generation?

A healthcare company is building a generative AI assistant to answer patient questions about medications. The team wants to ensure the model's responses are grounded in approved clinical guidelines and avoid fabricated information. Which approach best addresses this requirement?

A data scientist is fine-tuning a large language model using Vertex AI. The training job fails with an out-of-memory error. Which action should they take to resolve this issue?

A financial services firm is evaluating generative AI use cases and must present a business case to its risk committee. The committee requires that each proposed use case have a measurable benefit and a clear owner before funding. Which action best aligns with a generative AI value-assessment practice?

A company wants to deploy a GenAI system for contract analysis that must produce structured output (e.g., JSON) for downstream processing. They need to ensure the output format is consistent. Which prompt engineering technique is MOST effective?

A data analyst wants to train and deploy a custom image classification model with minimal ML engineering overhead. Which Google Cloud service should they use?

Refer to the exhibit. What access does the IAM policy grant to developer@example.com?

A multinational corporation wants to deploy a generative AI chatbot for its global customer service. They must ensure that data residency requirements are met for EU customers, meaning all prompts and responses from EU users must be processed and stored within the European Union. Which Google Cloud capability should they use?

A financial institution needs to deploy a document processing pipeline to extract data from invoices. They must ensure data isolation, audit logging, and compliance with SOC 2. Which THREE Google Cloud services should they combine?

Which TWO options are best practices for deploying generative AI models on Vertex AI? (Choose two.)

A generative AI model for code generation sometimes produces syntactically incorrect code. The team wants to reduce syntax errors without retraining the entire model. Which approach is most effective?

A bank is building a Gemini-powered assistant on Vertex AI that must answer questions about internal policy documents and must not fabricate policy details. The architects want to reduce hallucination and provide auditable sourcing. Which two Google Cloud capabilities should they combine? (Choose two.)

Which Google Cloud AI API is used to convert spoken language into text?

A retail company wants to build a generative AI application that creates personalized product descriptions. They need the model to stay current with weekly inventory changes and brand voice guidelines without retraining the model. Which approach should they use?

A company is comparing Google Cloud Vertex AI with AWS Bedrock and Azure OpenAI. They need a model that can natively process text, images, audio, and video. Which differentiator does Google Cloud offer?

A media company wants its internal knowledge assistant to answer employee questions using the company's own policy documents and past project reports, while keeping the Gemini model's general reasoning ability intact. The team has a large corpus stored in Cloud Storage and does not want to retrain or fine-tune the model. Which Google Cloud approach should they use?

A marketing team wants to use GenAI to generate social media posts. They need consistent brand voice and the ability to output structured JSON for downstream scheduling. Which combination of Vertex AI features should they use?

A company is deciding between using a pre-built GenAI API (like Gemini API) and building a custom fine-tuned model. Which factor would MOST strongly favor the custom fine-tuned model?

A healthcare startup wants to use generative AI to provide clinical decision support. They must minimize the risk of harmful hallucinations. Which business strategy is most appropriate?

A data scientist wants to run ML models directly on their BigQuery data without moving data out. Which THREE statements about BigQuery ML are correct? (Choose 3)

A company is using a generative AI model to generate product descriptions. They notice the outputs often include factual inaccuracies about product specifications. Which technique would best address this issue without modifying the model's architecture?

A large enterprise is evaluating gen AI for internal knowledge management. They need to ensure accuracy and reduce hallucinations. Which strategy is most effective?

Refer to the exhibit. The endpoint is experiencing high latency during traffic spikes. The team wants to improve response time by reducing queueing. Which change to the configuration would be most effective?

A startup wants to generate product descriptions from a few keywords using a large language model. They have no prior ML experience and need the fastest time-to-market. Which Google Cloud service should they use?

A company wants to build a GenAI application that summarizes customer reviews into actionable insights. The solution must be cost-effective and handle variable traffic. Which TWO strategies should they implement? (Choose 2)

A law firm uses a generative model to analyze contracts and extract key clauses. The model often outputs irrelevant clauses or misses important ones. They want to improve the relevance of the outputs without retraining the entire model. Which approach is best?

A company wants to adopt GenAI for contract analysis. They are evaluating build vs. buy. Which TWO factors are MOST important when deciding to build a custom fine-tuned model instead of using a pre-built API? (Choose 2)

A marketing team is using a text generation model to create ad copy. They notice that the model's output is often bland and lacks creativity. They want to increase the diversity of the generated text while keeping it relevant. Which parameter should they adjust?

A marketing team wants to use Vertex AI to generate ad copy. They need the model to follow a specific tone and style. What is the best approach?

A software company wants to use a Google Cloud generative AI model to automatically generate code snippets from natural language descriptions. The developers need the model to produce syntactically correct code in multiple programming languages. Which Google Cloud offering is specifically designed for this use case?

A healthcare company is building a chatbot to answer patient queries based on their medical documents stored in Cloud Storage. They want to minimize latency and ensure data residency in the EU. Which Vertex AI service should they use?

A company is fine-tuning a large language model for a domain-specific legal document summarization task. They have limited labeled data but want to adapt the model efficiently without catastrophic forgetting. Which technique is most suitable?

A healthcare startup is using Vertex AI Imagen to generate synthetic medical images for training a diagnostic model. The images must comply with HIPAA regulations and cannot contain any real patient data. The team fine-tuned Imagen on a dataset of de-identified medical scans. However, during testing, they notice that some generated images closely resemble specific patients from the original dataset, even though the dataset was de-identified. They suspect that the model memorized some training examples. The team needs to address this issue without losing image quality. They have access to the original training data and Vertex AI tools. What action should they take?

A company is deploying a generative AI application that must meet HIPAA compliance. They need audit logging, data isolation, and a Business Associate Agreement (BAA). Which Gemini API access tier should they use?

An AI research lab wants to publish a model card for their new generative AI model. According to Google's Responsible AI practices, which information is ESSENTIAL to include in the model card?

A financial services firm is deploying a generative AI model to answer customer questions about investment products. They want to ensure the model's responses are compliant with regulations and do not provide personalized financial advice. Which TWO techniques can help achieve this? (Choose two.)

A developer wants to generate high-quality images from text descriptions using Google Cloud. Which service should they use?

Which TWO features are available in Vertex AI Agent Builder to enhance the conversational abilities of an agent? (Choose TWO.)

A retail company uses the Vertex AI Gemini API to generate product descriptions. Recently, the model started producing factually incorrect statements about product specifications, such as wrong dimensions and materials. Which strategy should be implemented to improve factual accuracy?

A software company wants to embed an AI coding assistant into its internal developer portal. The assistant must complete code in the developer's current editor context and also answer natural-language questions about the repository. Which Google Cloud offering is designed for this use case?

A company wants to measure the business impact of a GenAI content generation tool. Which metric is most appropriate?

What is the primary purpose of the temperature parameter when using a generative language model?

A startup wants to leverage Google Cloud's generative AI but has limited ML expertise. Which Google Cloud service allows them to build generative AI applications without deep ML knowledge?

A company wants to generate images from text descriptions. Which model in Vertex AI Model Garden should they use?

A company uses Vertex AI to deploy a generative model for customer support. They need to ensure that the model does not produce harmful content when responding to user queries. Which of the following is the MOST effective approach?

A retail company is building a chatbot for customer service. They need the model to generate product descriptions based on a catalog but also answer questions about store policies. The team wants to minimize latency and cost while maintaining high accuracy. Which Google Cloud generative AI offering should they use?

A team is designing a generative AI application that must avoid generating harmful or biased content. They are considering various techniques to implement safety measures. Which two approaches are recommended for mitigating harmful outputs in generative AI models? (Choose two.)

A developer is building a multimodal application that needs to analyze images, understand spoken language, and generate text responses. Which Google Cloud generative AI model is BEST suited for this task?

A machine learning engineer is fine-tuning a large language model using LoRA (Low-Rank Adaptation) to reduce memory usage. During training, they notice that the model's performance on the downstream task is not improving. What is the most likely issue?

A developer is building a mobile app that needs to run an AI model on-device for low-latency inference even without internet. Which Gemini model variant is designed for on-device deployment?

A sales team needs to draft personalized emails to prospects. They want a tool integrated into Gmail that suggests completions and can generate full drafts based on brief prompts. Which Gemini for Google Workspace feature should they use?

A healthcare organization wants to deploy a GenAI chatbot for patient intake. They must ensure that the model does not generate harmful advice and that patient data remains confidential. Which set of controls should they implement on Vertex AI?

A healthcare organization wants to build a generative AI application that can answer patient questions based on their own medical knowledge base. They need the model to cite sources and avoid generating unsupported information. Which Google Cloud feature should they use to ground the model's responses in their proprietary data?

A developer is deploying a generative AI model on Vertex AI for a production application that requires low latency and high throughput. They need to choose an appropriate endpoint type. Which deployment option should they use?

A researcher wants to quickly prototype an AI model using a free, hosted Jupyter notebook environment with GPU support. Which Google product is BEST suited for this?

A small startup wants to add image generation to its design tool. The developers want to call a Google Cloud generative AI model through a simple API without provisioning infrastructure, managing model servers, or handling GPU capacity planning. Which Google Cloud offering best fits this requirement?

A national retail chain wants to add a generative AI shopping assistant to its existing mobile app. The CIO insists the project show measurable business value within one quarter and that spending stay predictable, with no long-term infrastructure commitments. Which Google Cloud approach best fits these constraints?

An organization is deploying a summarization model on Vertex AI and needs to ensure that the model's responses are consistent and avoid hallucinations. They have a labeled dataset of source documents and human-written summaries. Which approach would best align the model with their quality requirements?

A logistics company wants an AI agent that answers driver questions about delivery procedures, can look up a shipment's live status through an internal REST API, and can escalate to a dispatcher when it cannot resolve an issue. Which Google Cloud offering is purpose-built for assembling this kind of agent?

A financial institution is deploying a generative AI model to recommend investment strategies. They must ensure the model's outputs are explainable to clients and regulators. Which approach BEST meets this requirement?

A marketing team wants to generate product descriptions for 1000 new items. They need consistent brand voice and the ability to review and edit outputs before publishing. Which approach is most suitable?

A healthcare organization is developing a generative AI system to assist doctors with clinical decision support. They are concerned about regulatory compliance (e.g., HIPAA) and potential liability. What is the most important business strategy to mitigate these risks?

A company is building a generative AI application that will generate marketing copy. They want to ensure that the content does not contain hate speech, violence, sexual content, or dangerous instructions. Which Google Cloud feature should they enable?

A marketing team wants to generate product descriptions using generative AI. They need to ensure factual accuracy and avoid hallucinations. Which approach should they use?

A data science team wants to run a large-scale transformer training job with custom model architectures. They need the highest compute density for a multi-node job and want to minimize inter-node communication latency. Which Google Cloud infrastructure is BEST suited for this workload?

A company needs to fine-tune a foundation model on Vertex AI for a custom text classification task with only 500 labeled examples. They want to minimize cost while achieving high accuracy. What is the MOST cost-effective approach?

A retail company wants to use GenAI to generate product descriptions. They have a small team of data scientists. What is the most efficient approach?

A company wants to deploy a generative AI application that must comply with both Google's AI Principles and the EU AI Act. Which THREE practices should they adopt?

You are a Generative AI architect at a large financial services firm. The firm has deployed a custom large language model (LLM) fine-tuned on proprietary financial reports to assist analysts in generating quarterly earnings summaries. The model is hosted on Vertex AI using a dedicated endpoint with autoscaling enabled. Recently, the model's output has exhibited two issues: (1) occasional factual inaccuracies about specific financial figures, and (2) a tendency to produce overly verbose and repetitive text in the summaries, sometimes exceeding the desired length of 200 words. The team has already tried adjusting the temperature parameter from 0.7 to 0.2 and increased the top-k sampling from 40 to 50, but the problems persist. The model's training data includes over 10,000 financial reports, and the fine-tuning process used low-rank adaptation (LoRA) with rank 16. The production environment uses a batch size of 1 for inference. You need to recommend a course of action that most directly addresses both the factual accuracy and verbosity issues without requiring a full retraining of the model. Which approach should you take?

A company is building a chatbot that must answer questions based on a large internal knowledge base that is updated weekly. They want to avoid retraining the model frequently. Which technique should they use?

You are a data scientist at a financial institution. You are using Vertex AI to fine-tune a large language model (LLM) for generating financial reports. You have prepared a dataset of 10,000 examples. During fine-tuning, you notice that the training loss is decreasing steadily, but the validation loss is increasing after 5 epochs. The model's generated reports on the validation set contain many factual errors and nonsensical statements. You suspect overfitting. You have limited compute budget and need to improve generalization. What should you do?

A media company needs to generate short video clips from text prompts for a marketing campaign. They want to use a Google Cloud service that can create videos up to 8 seconds long, 720p resolution, and can be accessed via Vertex AI. Which Google Cloud generative AI offering should they use?

A law firm wants to use generative AI to analyze contracts and extract key clauses. They need high accuracy and the ability to handle diverse contract formats. Which three steps should they take in their proof-of-concept (PoC) phase? (Choose THREE)

Which Google Cloud tool allows you to document the intended use, training data, and evaluation results of a machine learning model to promote transparency?

Which TWO techniques effectively reduce bias in generative model outputs? (Choose two.)

A media company wants to build a multi-modal generative app that accepts text, image, and video inputs and produces summaries. The app must handle variable-length videos up to 10 minutes. Which architecture is most scalable and cost-effective?

What are THREE best practices for responsible generative AI deployment?

A startup is building a multimodal application that allows users to upload a photo of a plant and ask questions about its care. They want to use Google Cloud generative AI services. Which combination of services is MOST suitable?

An engineer is testing a generative AI application using the Gemini API. They receive a 400 error with message 'INVALID_ARGUMENT: text has been blocked.' What is the most likely cause?

A logistics company stores delivery exception reports as PDFs in a Cloud Storage bucket. An analyst needs to ask natural-language questions across all the reports and receive answers with citations to the source pages, with minimal development work. Which Google Cloud capability should the analyst use?

A data analyst wants to use Gemini for Google Workspace to assist with Sheets. Which two capabilities does Duet AI in Sheets provide? (Choose TWO)

A team set a budget alert for their GenAI API usage at $10,000. They received the alert with current spend of $12,500. Which business action is most appropriate as a first step?

A software company is using Vertex AI to build a generative AI application that creates code snippets from natural language descriptions. They want to improve the model's performance on their specific coding style and libraries. Which two techniques should they use? (Choose two.)

A media company is using a generative AI model to create summaries of news articles. They notice that the summaries sometimes include information not present in the original articles, leading to factual errors. They want to reduce the likelihood of such hallucinations. Which approach should they take?

A company is planning an iterative rollout of a GenAI assistant for sales teams. They want to maximize adoption and minimize disruption. Which TWO change management practices should they prioritize? (Choose two.)

A software team is using a generative AI model to write code snippets. They want to control the model's creativity and ensure it produces consistent, deterministic output for the same prompt. Which parameter should they adjust?

A research team wants to generate high-quality images from text descriptions for a marketing campaign. They need the ability to edit specific regions of generated images while preserving the rest. Which Google Cloud AI service should they use?

A small marketing agency wants to quickly experiment with prompts for Gemini to draft social media posts, without writing code or provisioning infrastructure. They need a Google Cloud console experience for iterating on prompts and comparing model outputs. Which offering should they use?

During a proof-of-concept, a team notices that their GenAI-powered meeting summarizer occasionally includes hallucinated details. They want to improve summary accuracy before production. Which action would be most effective?

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?

What are THREE benefits of using embedding models in a Retrieval Augmented Generation (RAG) system?

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?

Which TWO statements are true about generative AI models?

A company wants to use GenAI to create a knowledge base assistant that can answer questions from internal documentation. They need the assistant to always have access to the latest documents without retraining. Which TWO services should they combine? (Choose 2)

A machine learning engineer is defining a Vertex AI pipeline for model evaluation using the JSON representation shown. The pipeline fails with an error that the 'eval_dataset' parameter is missing. What is the issue?

A team is using a pre-trained language model to summarize legal documents. They find that summaries often miss key dates and parties involved. Which technique would most effectively improve factual accuracy?

A company is piloting a GenAI code review assistant. Developers report that the assistant often suggests incorrect or insecure code snippets. The team wants to improve the assistant's reliability before expanding the pilot. Which approach should they prioritize?

A support team is using a generative AI model to answer customer questions from an internal knowledge base. They notice that when the same question is asked twice, the model sometimes gives different answers, and occasionally includes details not found in the knowledge base. They want to reduce variability and keep responses closer to the source content. Which action should they take?

A data scientist observes that their text generation model frequently uses gender stereotypes when generating job descriptions. Which responsible AI practice should be applied FIRST to address this issue?

A financial services firm is deploying a generative AI model to answer customer questions about investment products. They need to ensure that the model's responses comply with regulatory requirements and do not provide personalized financial advice. Which approach should they take?

A company wants to ensure only authorized users can deploy gen AI models. The current policy allows all users in the domain. What is the best practice to restrict deployment?

A team is building a generative AI model for customer support. They notice the model often produces overly polite but unhelpful responses. Which technique would best improve response quality without sacrificing helpfulness?

A marketing team wants to use a generative AI model to create product descriptions from a short list of features. They need the output to be creative but also follow a specific brand voice. Which approach should they take?

A company is using a fine-tuned LLM for generating technical support responses. After deployment, they notice that the model sometimes produces incorrect but plausible-sounding answers (hallucinations). They have a large repository of verified technical manuals. Which technique would BEST reduce hallucinations while minimizing the need for additional training?

Which THREE components are core to a typical Retrieval Augmented Generation (RAG) system?

Which TWO techniques are commonly used to control the style and tone of a generative model's output?

A media company is using a generative AI model to create short video scripts. They notice that the model sometimes produces content that is factually incorrect or nonsensical. Which term best describes this phenomenon?

A developer is configuring a Vertex AI Agent Builder agent to use grounding. They receive the following error when calling the API: `404 Not Found: Data store resource not found.` What is the most likely cause?

A bank is piloting a Gemini-powered assistant that summarizes internal audit reports. Compliance requires that prompts and responses never leave the company's chosen Google Cloud region, that customer-managed encryption keys protect data at rest, and that no data is used to improve Google's models. Which combination of Vertex AI capabilities should the team configure to meet these requirements?

A retail company wants to build an internal assistant that answers employee HR policy questions using their existing policy documents, without exposing sensitive data to external APIs. They need a managed Google Cloud service that supports retrieval-augmented generation (RAG) and integrates with their existing data in Cloud Storage. Which Google Cloud service should they use?

A sales team wants to use Gemini for Google Workspace to draft emails in Gmail. Which feature should they enable to generate full email drafts from a brief prompt?

A marketing team is using a generative AI model to create ad copy. They notice that the outputs are often too creative and sometimes include exaggerated claims. They want to reduce creativity and make the outputs more predictable and factual. Which parameter should they adjust?

A media company wants to generate short video clips from text prompts for social media ads. The creative team needs a managed Google Cloud service that produces video from descriptive prompts and offers controls for aspect ratio and duration, without managing GPU infrastructure. Which offering should they use?

According to Google's AI Principles, AI systems should be 'accountable to people.' What does this principle primarily require?

A small marketing agency with 10 employees is exploring generative AI to create personalized ad copy for their clients. They have a limited budget of $5,000 per month and no in-house machine learning expertise. The CEO wants to have a working prototype within two weeks to show to a potential client. The agency's data is sensitive and cannot be shared with unauthorized third parties. Which strategy should they pursue?

A company is deploying a generative AI application that must comply with GDPR's right to explanation. The application must be able to justify its decisions. Which model or approach provides the MOST inherent interpretability?

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

Which TWO techniques are most effective for improving the quality of a generative AI model's output when summarizing complex documents?

What is the fundamental difference between a foundation model and a fine-tuned model?

A team is designing prompts for a generative AI model to summarize legal documents. They want to improve the quality and relevance of the summaries. Which two prompt engineering best practices should they follow? (Choose two.)

A company wants to deploy a chatbot for customer support. To comply with the AI Principle of being 'accountable to people', which practice should they implement?

A company wants to evaluate the ROI of their GenAI content creation tool. Which metric is LEAST useful for assessing productivity gains?

A marketing team is using Google Cloud's Vertex AI Studio to generate product descriptions. They want the model to produce output in a very specific JSON format so it can be parsed by their downstream application. Which feature should they use to reliably constrain the model's output to that structure?

A media company is deploying a generative AI application that must handle bursts of traffic while keeping costs predictable. They want to pay only for the compute resources actually consumed and avoid managing infrastructure. Which Google Cloud option best matches these requirements for serving a foundation model?

A company wants to ground Gemini responses with real-time Google Search results to improve accuracy of current events. Which feature enables this?

Which TWO factors are most critical when deciding to build a custom GenAI model vs. using a pre-built API? (Select two.)

A data scientist is fine-tuning a large language model for a legal document summarization task. The dataset contains only 500 examples, and the model must not forget its general language capabilities. Which fine-tuning method is most suitable?

An organization wants to ensure their generative AI application does not produce toxic or harmful content. Which Vertex AI feature should they implement?

A company wants to ensure that AI-generated images can be traced back to their origin to prevent misuse. Which Google technology provides invisible watermarking for AI-generated content?

A fintech company is deploying a generative AI system that offers investment advice. To comply with regulations and Google's AI Principles, they need to ensure appropriate human oversight and transparency. Which two actions should they take? (Choose two.)

A logistics company wants to build a generative AI application that answers employee questions about internal HR policies. The company's policy documents are already stored in Google Drive and must stay synchronized automatically as they are edited. The team has limited ML engineering resources and prefers a managed, low-code path. Which Google Cloud approach should they choose?

A marketing team wants to use a generative AI model to create dozens of unique social media captions for a new product launch. They need the outputs to vary in tone and wording each time they run the prompt, while staying on topic. Which model parameter should they adjust to directly control this variability?

A retail company is building a generative AI assistant on Google Cloud that drafts personalized product recommendations in natural language. Business leaders want to measure whether the pilot is delivering value before expanding it to all customers. They need a metric that reflects ongoing operational benefit rather than one-time build effort. Which metric should they prioritize?

A retail company wants to build a customer service chatbot that can handle returns, order status, and FAQs. They need to integrate with their existing backend systems. Which Google Cloud service should they use?

A data analyst wants to experiment with ML models using a free, cloud-based Jupyter notebook environment with GPU support. Which Google tool should they use?

A company wants to evaluate the ROI of deploying a GenAI tool for customer support. They plan to measure productivity gains. Which metric is most directly tied to productivity improvement?

What is the primary advantage of using embeddings and vector search for semantic search over traditional keyword search?

A marketing team uses a text generation model to create ad copy. They want the output to be more diverse and creative, exploring unusual angles. Which parameter should they adjust?

Which TWO are benefits of using pre-trained foundation models instead of training from scratch?

Refer to the exhibit. A user wants formal translations from a generative AI model, but the model outputs informal style inconsistently. Which prompt engineering technique would best ensure consistent formal translations?

A company uses a text-to-image model to generate marketing visuals. The results often misinterpret the prompt, e.g., 'a red car' generates a blue car. Which technique should they try first to align the output with the prompt?

A global company deploys a generative AI chatbot in the European Union. They must ensure compliance with GDPR regarding user data used for fine-tuning the model. What is the MOST important requirement they must fulfill?

A media company is using Vertex AI's Imagen model to generate images for marketing campaigns. They have a set of prompts that describe desired scenes, but the generated images often contain artifacts such as distorted faces or unnatural lighting. The team has tried varying the prompt wording but the issues persist. They are using the default parameters (no modifications). They have a budget for additional compute resources and want to improve image quality without switching to a more expensive model. The team has access to a small set of high-quality images in the same style as their target outputs. What should the team do?

A marketing team uses a generative AI model on Vertex AI to create ad copy variations. The outputs are often too random and include off-brand phrases. They want to reduce randomness while still allowing some creativity. Which parameter should they adjust?

A developer wants to use Gemini 1.5 Pro to analyze hour-long video content and generate a summary. Which feature of Gemini 1.5 Pro is most suitable for this task?

During a RAG pipeline implementation, the retrieval system frequently returns irrelevant documents, causing the generator to produce incorrect answers. Which change is most likely to improve the relevance of retrieved documents?

A telecommunications provider plans to offer a generative AI feature that answers billing questions in multiple languages through its mobile app. Leadership wants to control costs as usage grows unpredictably while keeping responses fast. Which combination of practices best supports cost governance for this workload on Google Cloud?

A media company wants to generate personalized video summaries for users based on their viewing history. They plan to use a generative AI model on Vertex AI. Which technique should they use to ensure the summaries are tailored to each user's preferences?

A machine learning engineer is building a text-to-image model using Vertex AI. They want to reduce inference latency. Which strategy is most effective?

A startup wants to quickly integrate a generative AI chatbot into their customer support platform. They need a solution that can answer questions based on their internal knowledge base with minimal setup. Which Google Cloud service should they use?

A company is deploying a chatbot that uses a foundation model. They want to minimize latency for user queries. Which action is most effective?

A marketing team wants to generate social media posts in a consistent brand voice. They have a few examples of high-performing posts. Which prompt engineering technique should they use?

A machine learning engineer notices that a generative AI model consistently produces outputs that reinforce gender stereotypes when describing occupations. What is the MOST likely cause?

A retail analytics team uses a Gemini model to answer questions over a large product catalog stored in BigQuery. Answers are sometimes outdated because the model relies on its training data. They want responses to reflect the latest catalog rows and cite the source table. Which technique should they implement?

A data scientist wants to fine-tune a foundation model from Vertex AI Model Garden on their custom dataset. They want to choose a cost-effective method that updates only a small subset of parameters. Which fine-tuning approach should they use?

Which parameter controls the randomness of a language model's output?

A global e-commerce company wants to translate product descriptions into 50 languages with high accuracy. They need to handle domain-specific terms (e.g., 'size chart', 'return policy'). Which approach should they use?

A developer is using Vertex AI Studio to design a prompt for a content moderation system. They need the model to return a structured JSON with fields 'category' and 'confidence_score'. Which prompt engineering technique should they use?

A media company is evaluating Google Cloud's generative AI offerings for two distinct needs: enabling its journalists to summarize research inside Google Docs, and building a custom internal tool that calls Gemini models programmatically with its own authentication and logging. Which two Google Cloud offerings map to these needs? (Choose two.)

A media company wants to build a generative AI application that answers questions using its proprietary video transcripts. They need the model to cite specific transcript segments and avoid hallucinating content not present in those transcripts. Which Google Cloud approach best meets these requirements?

A company is using a large language model for a customer-facing chat application. They notice that the model sometimes generates plausible-sounding but incorrect information. Which strategy is most effective to reduce this issue?

A company is choosing between Gemini Pro and Gemini Ultra for a document summarization task. Which THREE factors should they consider when deciding between the two model variants? (Choose THREE)

A company is planning an iterative rollout of a GenAI tool. Which change management practice is MOST critical for ensuring high adoption among employees?

A team is building a customer support assistant on Vertex AI using a foundation model. They notice the model occasionally invents policy details that don't exist in their internal documentation. They want the model to ground its answers in the company's knowledge base and provide citations. Which approach should they use?

What is the primary purpose of SynthID, developed by Google DeepMind?

A multinational corporation is deploying a generative AI chatbot for customer support across Europe, Asia, and North America. The legal team requires compliance with GDPR for EU users, data residency controls, and the ability to audit prompts and responses for safety. Which THREE actions should the company take?

A logistics company wants to build a generative AI application that answers questions using its internal policy documents stored in Cloud Storage. They want a managed, serverless way to index those documents and retrieve relevant passages for grounding responses, without managing their own vector database. Which Google Cloud service should they use?

A manufacturing company wants to use generative AI to create maintenance manuals from sensor data. The manuals must be accurate and reflect the latest equipment configurations. Which approach best ensures data freshness and consistency?

A marketing team wants to launch a generative AI campaign-copy tool. Executives ask the team to justify the investment by identifying the primary business objective before any technical design begins. Which statement best represents a valid business objective for this initiative?

A healthcare provider is building a generative AI assistant on Vertex AI to answer patient questions about appointment scheduling. They must ensure the model does not produce harmful or medically unsafe content, and they want to monitor and tune safety behavior over time. Which two Google Cloud features should they use? (Choose two.)

A developer is using Vertex AI's text generation model to create product descriptions. They want to ensure the output adheres to a specific brand voice and style. Which approach is most effective without retraining the model?

A financial analytics firm wants to query its BigQuery data using natural language, without exporting data to a separate service. They need a solution that integrates directly with BigQuery and uses Gemini models to generate SQL and interpret results. Which Google Cloud capability should they use?

A company wants to use Generative AI for customer support chatbots. They are concerned about cost and latency. Which deployment option best balances these concerns?

A company is evaluating Google Cloud's generative AI offerings to build a custom chatbot that can answer questions about their proprietary product manuals. They want to ensure the solution can be grounded in their own data and can be integrated into their existing applications. Which two Google Cloud services should they consider? (Choose two.)

A company is evaluating the ROI of deploying a GenAI-powered code review assistant. Which metric would BEST capture the quality improvement from using the assistant?

Which of the following best describes the transformer architecture's key innovation that enabled modern large language models?

A company is developing a generative AI application that will be used by customers in the EU. To comply with the GDPR and the upcoming EU AI Act, which THREE measures should they implement? (Select 3)

A company is evaluating the ROI of a generative AI project. Which metric is most appropriate?

A logistics company must answer employee questions using its internal policy manuals, which change weekly. The manuals are stored in a Cloud Storage bucket and must never be used to train a shared model. The company wants relevant, up-to-date answers with citations. Which Google Cloud approach should it use?

An enterprise uses a fine-tuned PaLM 2 model for code generation. They want to ensure the generated code passes security audits. Which combination of techniques would be most effective?

A startup wants to generate concise summaries of long news articles using an LLM on Vertex AI. They prioritize low latency and cost. Which model choice is most appropriate?

Which THREE factors should be considered when choosing between Gemini 1.5 Pro and Gemini 1.5 Flash for a customer-facing chatbot? (Choose three.)

A media company is using a generative AI model to produce news summaries. They notice that the summaries sometimes include fabricated details not present in the source articles. Which approach should they take to reduce these hallucinations?

A marketing team uses a generative AI model to create short social media posts from long product briefs. The posts frequently include made-up statistics and product claims that are not in the brief. The team wants to reduce these unsupported statements without retraining the model. Which technique should they apply first?

A company wants to use a generative AI model to create marketing content that will be used commercially. They are concerned about copyright infringement from the model's training data. Which step should they take to mitigate this risk?

A financial institution is evaluating Google Cloud's generative AI offerings to build an internal knowledge assistant. They require a solution that can understand and generate text, support conversational interactions, and be customized with their proprietary data. They also need to ensure that sensitive data is not used to train the underlying models. Which two Google Cloud services or features should they use? (Choose two.)

A company is deploying a large language model (LLM) for customer support using Vertex AI. Which TWO best practices should they follow to ensure high-quality and cost-effective responses?

A company wants to implement a change management strategy for GenAI adoption. Which TWO actions are MOST effective in driving adoption among employees?

A company is considering using gen AI for customer support. Which two business strategies are most important for success?

A financial analyst wants to run a regression model inside BigQuery using SQL, without moving data to a separate ML environment. Which Google Cloud service allows this directly?

A financial services firm wants to deploy generative AI for automated investment advice. They are subject to strict regulatory oversight requiring explainability and audit trails. Which strategy best meets these requirements?

An enterprise deploys a large language model (LLM) for internal document summarization. Users complain that summaries sometimes include statements not present in the original document. Which mitigation strategy should the team prioritize to address this hallucination issue?

A data scientist is using Vertex AI to build a question-answering system. They want to use the Responsible AI toolkit to document and communicate the model's characteristics. Which TWO tools from the toolkit are MOST relevant? (Select two.)

A team is using a language model for customer feedback analysis. They want to improve the accuracy of sentiment extraction. Which TWO techniques should they apply? (Choose two.)

A bank is deploying a Gemini model on Vertex AI to draft responses to customer complaints. Compliance requires that the deployment (Choose two.)

A financial analyst uses a generative AI model to answer questions about recent market trends. They notice that the model sometimes provides outdated information. They want to ensure the model's responses are based on the most current data. Which approach should they take?

A healthcare provider plans to implement gen AI for clinical note summarization. They have limited AI expertise. Which Google Cloud approach best aligns with their business strategy?

A machine learning engineer wants to reduce the latency of a Gemini-based chatbot running in production. Which TWO strategies would be MOST effective?

A marketing team wants to generate product descriptions from a short bullet list of features. They need the model to produce creative, varied phrasing rather than a single deterministic output, while keeping the text grammatically correct. Which Vertex AI generative AI parameter should they adjust to introduce randomness into the model's word choices?

Which TWO techniques are most effective for improving factual accuracy in a generative AI model's responses? (Choose two.)

A machine learning engineer is using a generative AI model that occasionally outputs biased content. Which TWO actions should they take to address this issue?

A startup wants to quickly prototype a multimodal AI application that can process images and text using Gemini. They have minimal budget and need a free tier for initial development. Which access tier should they use?

A logistics company wants to measure whether its new generative AI assistant for dispatchers is delivering business value. Leadership asks for indicators that connect assistant usage to operational outcomes. Which two metrics should the company track? (Choose two.)

A healthcare startup has fine-tuned a Vertex AI PaLM 2 model on a dataset of medical records to generate patient summaries. The model produces fluent text but occasionally fabricates diagnoses not present in the input. The team has already tried increasing the training data size by 20% and adjusting the temperature from 0.7 to 0.2, but hallucinations persist. The summaries must be factually accurate for regulatory compliance. What should the team do next?

A marketing team wants to generate multiple versions of ad copy for A/B testing. They need consistent brand tone across all outputs. Which prompt engineering technique is most effective?

A team notices their text generation model repeats phrases excessively. Which technique would most directly reduce repetition?

A data scientist is building a text generation model and wants to evaluate bias using diverse test sets. Which Google AI Principle is directly relevant to this practice?

A customer support team uses a foundation model via the Gemini API to answer billing questions. Responses are often vague and sometimes omit required steps. The team wants to improve output quality without fine-tuning the model. Which approach should they use?

A company wants to build a proof-of-concept generative AI application quickly. They have limited ML expertise and need to test multiple foundation models with different prompts. Which Vertex AI tool should they use?

A bank's risk team must review every AI-generated customer communication for compliance before it is sent. They want to enforce a policy that blocks any message containing prohibited financial advice and routes flagged messages to a human reviewer. Which Vertex AI capability should they configure?

A healthcare provider uses a Gemini model on Vertex AI to summarize patient intake notes for clinicians. The summaries must consistently follow a fixed structure: chief complaint, history, medications, and plan. Early tests show the model sometimes reorders or omits sections. Which technique most reliably enforces the required structure?

What is the primary purpose of the temperature parameter when generating text with an LLM?

A company wants to use Google DeepMind's advances in protein structure prediction to accelerate drug discovery. Which DeepMind achievement is most relevant to this goal?

A model generates biased output. Which technique is least effective?

An enterprise wants to use a foundation model through Google Cloud but must ensure that their prompts and responses are not used to train the underlying model and that data is encrypted in transit and at rest. They also want to avoid managing infrastructure. Which approach best meets these requirements?

Which TWO options are benefits of using Vertex AI Model Garden compared to using raw pre-trained models from external sources? (Choose two.)

A logistics company needs an assistant that answers driver questions about shipment status. The answers must reflect live data from an operational database and must include citations so dispatchers can verify each claim. The company wants a managed Google Cloud capability rather than custom retrieval code. Which capability should they use?

Which THREE capabilities are provided by Vertex AI Agent Builder? (Choose three.)

A company is using a generative AI model to answer customer questions. The answers are often vague and do not use the company's specific terminology. They want to improve the relevance and specificity of the responses. Which technique should they use?

Which THREE techniques are commonly used to improve the overall quality and coherence of generative model outputs? (Choose three.)

A retail company is building a generative AI chatbot to assist customers with product recommendations and order tracking. The chatbot uses Vertex AI with Gemini 1.5 Pro, and the development team has implemented a Retrieval-Augmented Generation (RAG) pipeline using Vertex AI Search for grounding. The pipeline uses a vector store containing product descriptions and order history. During testing, the team observes that the chatbot sometimes provides incorrect order statuses—for example, claiming an order is 'shipped' when it is actually 'pending'. The team suspects the issue is related to how context is retrieved and used. The RAG pipeline currently retrieves the top 5 chunks based on cosine similarity from the vector store, and passes them as context to the model. The team is considering several changes to improve factual accuracy. Which single action would most effectively reduce hallucinations in this scenario?

Refer to the exhibit. What is the most likely cause of this error?

A retail company wants to use a generative AI model to create unique product descriptions for thousands of items. They need the model to produce varied, creative text without requiring them to provide any examples. Which type of model should they use?

A developer is using Vertex AI Gemini API for a chatbot. The chatbot sometimes outputs harmful content. What is the best first step to mitigate this?

A support team uses a generative AI assistant to answer customer questions. Agents report that the answers are often too long and include unnecessary background. The team wants the responses to be concise and directly address the question. Which prompt adjustment is most appropriate?

An organization wants to use a generative model to automatically generate legal contracts. The model must produce clauses that are not only grammatically correct but also legally enforceable and consistent with current jurisdiction laws. Which combination of techniques best ensures legal compliance?

A researcher wants to detect whether text was generated by an AI model to identify potential misinformation. Which Google technology is specifically designed for this purpose?

A company wants to use GenAI to automate customer support. They have a large knowledge base. Which approach maximizes ROI in the first 6 months?

A research lab is planning to train a massive protein folding model similar to AlphaFold. They want to use Google Cloud infrastructure and tools. Which THREE components are most relevant?

A product manager wants to communicate the limitations of a new generative AI feature to stakeholders. According to Google's People + AI Guidebook, what is the BEST approach?

A company wants to build a customer service chatbot that answers questions about their internal policy documents. The documents are updated monthly, and the team cannot afford to retrain a model each time. Which approach is MOST appropriate?

A healthcare company is deploying a GenAI-powered report generation system that processes patient summaries. They need the output to be structured JSON for downstream ingestion. The team is using Vertex AI Studio prompt design. Which approach best ensures consistent structured output?

A data scientist is using Vertex AI to generate product descriptions from a list of features. They notice that the model sometimes omits key features or invents details not present in the input. They want to reduce hallucinations and ensure all provided features are included. Which technique should they apply?

A company is evaluating Google Cloud's AI portfolio versus competitors. They want to leverage Gemini's unique capabilities. Which THREE differentiators should they highlight when comparing to AWS Bedrock and Azure OpenAI? (Choose 3)

According to Google's AI Principles, which TWO of the following are core commitments? (Select 2)

A data scientist is using the Gemini API to generate product descriptions for an e-commerce site. The descriptions are often too verbose and include speculative claims that are not in the product specifications. The scientist wants to reduce hallucinations and control the length of the output without retraining the model. What should they do?

A regional insurance company wants to launch a generative AI claims-triage assistant. The CISO requires that no claims data leave the company's existing Google Cloud project boundary and that every model call be attributable to a named employee for audit. Which combination of Google Cloud controls should the architecture team prioritize?

Which TWO of the following are valid Google Cloud AI APIs for natural language processing?

A company fine-tunes a text model on internal HR policies. After deployment, the model sometimes outputs sensitive employee information. What is the most likely cause?

A marketing agency wants to generate personalized product descriptions at scale but has no machine learning engineers on staff. They need a managed Google Cloud option that provides access to foundation models through an API with minimal infrastructure work. Which offering should they choose?

A retail company is deploying a generative AI chatbot on Vertex AI to provide product recommendations. The chatbot uses a base foundation model with no fine-tuning. Users report that the chatbot sometimes gives offensive or insensitive responses. The team must quickly implement safety controls without modifying the model. They also want to reduce irrelevant off-topic answers. Which combination of techniques should they apply?

Refer to the exhibit. A team attempted to start a model tuning job but received the error 'Quota limit exceeded for tuning jobs in region us-central1'. What is the most appropriate action?

A data scientist is documenting a new dataset for a generative AI project. According to the Responsible AI toolkit, which TWO elements should they include in a Datasheet for Datasets?

A healthcare organization wants to use generative AI to draft patient education materials. They are concerned about the model generating incorrect medical information. Which combination of Google Cloud services should they use to ground the model's responses in trusted medical literature?

A company is evaluating whether to build a custom fine-tuned model for code generation or use a pre-built API like Gemini API. The code generation needs to follow the company's internal coding standards. Which consideration is MOST important in deciding to build vs buy?

A global media company wants to add generative AI capabilities to its existing applications, including text summarization, image generation, and code assistance. They plan to use Google Cloud services and need a managed solution that provides access to multiple foundation models through a single API, with enterprise-grade security and scalability. Which Google Cloud offering should they choose?

A developer wants to generate product descriptions from a list of features using Vertex AI. Which model type is best suited for this task?

What is the primary purpose of the 'top-p' (nucleus sampling) parameter in text generation?

A healthcare startup is building a GenAI application that answers patient queries based on medical literature. They need to ensure factual accuracy and compliance with healthcare regulations. Which TWO strategies should they use? (Choose 2)

A multinational corporation uses Vertex AI to fine-tune a language model on proprietary customer data. They want to ensure that the fine-tuned model does not inadvertently memorize and regurgitate sensitive customer information. Which approach is most effective?

A company is deploying a large language model on Vertex AI for real-time inference. They observe high latency and want to optimize. They have already enabled model caching. What next step should they take to reduce latency?

A company is deciding between building a custom fine-tuned model vs. using a pre-built API for a document summarization task. The documents contain domain-specific jargon. Which factor STRONGLY favors using a pre-built API with prompt engineering?

A startup wants to quickly prototype a generative AI application that can write marketing copy. They have limited machine learning expertise and want to avoid managing infrastructure. They prefer a fully managed, no-code or low-code solution that provides access to Google's foundation models. Which Google Cloud offering should they use?

A product team is new to generative AI and wants to understand which characteristics distinguish foundation models from traditional task-specific ML models. Which two statements accurately describe foundation models? (Choose two.)

A logistics company wants to build a generative AI application that answers questions over thousands of internal policy PDFs stored in Cloud Storage. They need Google Cloud to handle document ingestion, chunking, indexing, and retrieval for grounding, while they focus only on the application logic. Which Google Cloud offering should they use?

A logistics company wants its internal assistant to answer questions using its private fleet maintenance manuals. The manuals change weekly, and the company does not want to retrain a model each time. Accuracy must be traceable to the source document. Which Google Cloud approach should they implement?

A logistics company wants to build a generative AI application that answers employee questions using its internal policy documents while keeping the data inside its own Google Cloud project. The team needs enterprise-grade security, access control, and the ability to choose among multiple foundation models. Which offering should they choose?

A team is using a generative AI model to answer customer questions about a complex product. They want to improve the factual accuracy and reduce hallucinations. Which TWO techniques should they apply? (Choose two.)

A company is running a GenAI proof-of-concept (PoC) for internal document Q&A. The PoC shows high latency and cost. The team suspects they are using an unnecessarily large model for the task. What is the BEST action to optimize?

A financial services firm is designing a generative AI assistant for advisors. Compliance requires that every response be traceable to an approved source document and that no response rely on the model's pretrained knowledge alone. The team plans to use Gemini models on Vertex AI. Which design choice most directly satisfies the traceability requirement?

A marketing team uses a Gemini model through the Vertex AI API to draft campaign copy. The drafts are creative but frequently wander off topic and include unsupported claims. The team wants a low-effort improvement before considering any model customization. Which action should they take first?

A company wants to deploy a GenAI code review assistant that integrates into their existing Git workflow. They want to use a managed Google Cloud service to minimize operational overhead. Which TWO services should they consider? (Choose two.)

A company has a Gemini-based application that sometimes produces factually incorrect answers. They want to improve accuracy without retraining the model. Which technique should they implement?

A company has a large dataset of customer support tickets stored in BigQuery. They want to predict ticket severity (high, medium, low) using SQL queries without moving data out of BigQuery. Which service should they use?

A company is using a fine-tuned LLM for generating financial reports. They need to ensure that the output complies with regulatory standards and does not include speculative content. Which combination of techniques should they implement?

A small marketing agency wants to experiment with Google's generative AI models without writing code or managing cloud infrastructure. They need a browser-based environment to draft campaign ideas and test prompts quickly. Which Google Cloud offering should they use?

A company is deploying a generative AI system for resume screening. They want to ensure fairness and avoid bias. Which TWO actions should they take? (Choose 2)

A data scientist is using Vertex AI RAG Engine to build a question-answering system over a large corpus of technical manuals. Users report that answers are often verbose and include irrelevant details. Which configuration change is MOST likely to improve answer conciseness?

A company is building a legal document review assistant using Gemini 1.5 Pro. They want to ensure the model can handle large documents of up to 500 pages in a single prompt. Which feature of Gemini 1.5 Pro is MOST important for this requirement?

A financial services company wants to build a generative AI application that drafts personalized emails to clients. They require the model to be accessible via a fully managed API with minimal infrastructure management. Which Google Cloud service should they use?

An e-commerce company wants to generate realistic product images from text descriptions using Google Cloud AI. Which service should they use?

A marketing team is using an LLM on Vertex AI to generate product descriptions. They want to consistently control the creativity and randomness of the output. Which parameter should they adjust?

A company uses a Gemini 1.5 Pro model with a 1 million token context window. They want to process a large 500-page PDF for Q&A. What is the MAIN advantage of using the long context window over a RAG approach?

Which THREE of the following are key considerations when deploying a generative AI model in a production environment with strict latency requirements? (Choose three.)

A company is using a generative AI model to automatically screen job applications. They want to ensure the model does not discriminate based on gender or ethnicity. Which of the following actions should they take as part of responsible AI?

A research team wants to train a very large transformer model using Google's custom AI accelerators. They need the highest compute density and tightest interconnection for distributed training. Which THREE are true about Google's TPU infrastructure? (Choose 3)

A media company wants to generate realistic images for a new marketing campaign. They need a Google Cloud service that can create images from text prompts and offers enterprise-grade controls for content safety and intellectual property. Which service should they use?

A global company deploying gen AI across multiple regions needs to minimize latency and comply with data sovereignty. What architecture should they adopt?

You are an ML engineer at a retail company. You have deployed a generative AI model on Vertex AI to generate product descriptions. The model uses a custom container and is deployed to a single endpoint. Recently, you noticed that inference latency has increased significantly during peak hours, causing timeouts. You have checked the logs and found that the CPU utilization on the deployed instances is consistently above 90% during peak hours. The model is currently deployed with a single machine type (n1-standard-4) and no scaling. You need to reduce latency without incurring excessive cost. What should you do?

A company is using a generative AI model to screen job applications. They want to ensure compliance with Google's AI Principle of avoiding unfair bias. Which practice is most effective in mitigating bias during the screening process?

A company is rolling out a generative AI tool to employees. To ensure successful adoption, they plan to provide training and identify early adopters. Which change management practice is MOST critical early in the rollout?

The exhibit shows the deployment configuration for a conversational AI model used in a finance application. Users report that responses are creative but often contain factually incorrect financial advice. Which parameter change would most improve factual accuracy?

A logistics company wants to forecast delivery delays and also generate plain-language explanations for dispatchers. Leadership asks the GenAI Leader to choose an approach that keeps the numeric forecast auditable while adding generative explanations. Which design should the GenAI Leader propose?

A team is designing prompts for a generative AI application that summarizes long legal contracts. They want outputs that are accurate, consistently formatted, and safe from leaking instructions. Which two prompt engineering practices should they apply? (Choose two.)

A healthcare startup needs to process medical claims and extract structured data (e.g., patient name, procedure codes, amounts) from scanned PDF forms. They require HIPAA compliance and prefer a pre-built Google Cloud service. Which service should they use?

A media company is using a generative AI model to create video captions. The model is deployed on Vertex AI with autoscaling. During peak hours, they observe high latency and request timeouts. Which action would most effectively address this issue?

A financial analyst needs to quickly extract key figures and summarize insights from a 200-page earnings report PDF. They want to use a Google Cloud generative AI model that can process long documents and answer questions. Which Gemini model capability should they leverage?

A financial analytics team needs a managed Google Cloud environment to ground Gemini responses in their proprietary market reports and to evaluate model outputs before releasing an internal research assistant. They want minimal infrastructure management and native integration with BigQuery. Which Google Cloud offering should they choose?

A healthcare company is building a generative AI application using Vertex AI. They need to ensure that the application adheres to responsible AI principles, such as avoiding harmful outputs and protecting patient data. Which two Google Cloud features or practices should they implement? (Choose two.)

After deploying a text-to-image model, the output images often contain distorted objects. The team suspects the prompt is too complex. Which prompt engineering technique should they try first?

A logistics company wants its operations analysts to ask natural-language questions such as 'Which routes had the most delays last quarter?' and receive answers grounded in data stored in BigQuery, without analysts writing SQL. The team has no plans to build or train custom models. Which Google Cloud offering should they adopt?

A product team uses Gemini via the Vertex AI API to draft customer emails. The drafts are accurate but often too long and include unnecessary background. The team wants shorter, more direct outputs while keeping the same model. Which approach should they take?

A company runs a pilot for a GenAI-powered internal knowledge base assistant. They want to measure adoption. Which metric is BEST for this purpose?

A company is deploying a generative AI model on Vertex AI for real-time chat. They observe that the model sometimes generates toxic or biased responses. They want to implement a safety mechanism to filter out such content before it reaches users. Which Google Cloud feature should they use?

A hospital network wants to build a generative AI search experience over its clinical guideline PDFs so clinicians can ask natural-language questions and receive answers with citations to the source documents. The solution must run on Google Cloud and keep data within the network's project. Which offering is purpose-built for this requirement?

Which Google DeepMind technology can be used to embed an invisible watermark into AI-generated images to help identify their origin?

A small marketing team wants to use a Google Cloud generative AI model to generate creative text for social media posts. They prefer a fully managed, ready-to-use API that requires minimal setup and does not need model training. Which Google Cloud service should they use?

A data science team wants to run a machine learning model directly on data stored in BigQuery without moving the data to a separate environment. Which Google Cloud service should they use?

Which THREE are best practices for responsible deployment of generative AI in a customer-facing application?

A logistics company plans to embed a generative AI assistant into its dispatch workflow, where it will draft driver instructions and answer operations questions. The executive sponsor insists that the initiative include mechanisms to measure whether the assistant is delivering business value and to keep its behavior within approved limits as usage grows. (Choose two.)

A marketing agency wants to quickly generate original images for social media campaigns without deep technical expertise. They need a fully managed Google Cloud service that provides an API for text-to-image generation. Which service should they use?

A legal team wants to use GenAI to review contracts and highlight risky clauses. They need the AI to consistently follow a specific classification taxonomy. The team has a small set of labeled examples (500 contracts). Which approach yields the BEST accuracy for this use case?

Which tool from Google's Responsible AI toolkit is designed to document the intended use, performance, and limitations of a machine learning model?

A telecommunications provider is preparing a business case for a generative AI virtual assistant that handles billing inquiries. Executives want the proposal to address financial viability, not just technical feasibility. Which two elements should the business case include to demonstrate responsible financial planning? (Choose two.)

A company is building a search application that requires grounding answers in their internal knowledge base. They want to use Vertex AI Search and Conversation with a custom datastore. Which configuration is essential to ensure the model only answers based on their documents?

A healthcare company needs to generate synthetic medical images for research while ensuring compliance with patient privacy regulations. Which Google Cloud generative AI service should they use?

A legal firm wants to automate contract analysis. They need to extract key clauses (e.g., termination, indemnification) from scanned PDFs. The team expects high accuracy and must maintain data privacy. Which combination of services is most suitable?

A retail company wants to build an internal assistant that answers employee questions using the company's own HR policy documents. The team has no machine learning engineers and wants a managed Google Cloud approach that grounds responses in those documents without training a new foundation model. Which Google Cloud capability best fits this need?

An enterprise is evaluating whether to build a custom fine-tuned model or use a pre-built API for code generation. Which three factors should they consider in the build vs. buy decision? (Choose THREE)

During a proof-of-concept for a GenAI document summarization tool, the team wants to evaluate whether the summaries are accurate and retain key information before scaling. Which evaluation approach is most appropriate for this stage?

A team wants to reduce hallucinations in a question-answering model. Which THREE techniques should they consider?

A financial technology company has deployed a custom-tuned PaLM 2 model on Vertex AI to generate personalized investment recommendations for retail clients. The model was fine-tuned on a corpus of historical market data and advisory transcripts. Recently, the compliance team flagged that several recommendations contradicted SEC guidelines, and the model sometimes repeated prohibited statements from outdated training materials. The team has already implemented safety filters (e.g., blocking toxic content) and adjusted the model's system instructions to be more conservative. However, the issues persist. The model's deployment parameters are: temperature=0.4, top_p=0.9, max_output_tokens=500, and no grounding. The company must maintain compliance without significantly increasing latency. What should they do next?

A product team at a retailer is using Vertex AI Studio to build a Gemini-powered assistant that answers questions about their internal return policy. Early tests show the model invents policy details such as a 45-day return window, even though the official policy allows only 30 days. The team wants the assistant to answer strictly from a set of approved policy PDFs stored in a Cloud Storage bucket, and they want to avoid retraining the model. Which technique should they use?

A retail company wants to generate personalized marketing content (emails, social posts) at scale using generative AI. They need consistent brand voice and the ability to review outputs before publishing. Which two Google Cloud capabilities should they use? (Choose TWO)

A financial institution is deploying a generative AI chatbot to provide investment advice. According to regulatory requirements, high-stakes AI decisions must have human review. Which setup BEST satisfies this requirement?

A startup is building a customer service chatbot that generates responses in real-time. They want the model to have up-to-date information on the latest product catalog but cannot afford frequent fine-tuning. Which technique should they use to inject current data into the model without retraining?

An ML engineer sees the above deployment output. The business wants to reduce inference cost. Which action should they take?

A media company plans to add generative AI features to its video editing suite. Executives want to prove business value within one quarter but cannot predict which of three candidate features editors will actually adopt. Which strategy best balances fast validation against wasted investment?

A retail company wants to build a chatbot that answers product questions and provides personalized recommendations. They have a small labeled dataset and limited ML expertise. Which approach should they take?

A retailer wants to use generative AI to write product descriptions automatically. They have a large dataset of existing product descriptions and need to customize a foundation model for their brand voice. Which Vertex AI feature should they use?

A company is evaluating whether to build a custom generative AI solution from scratch or use a pre-built API from a cloud provider. Which factor most strongly supports the build-from-scratch approach?

A developer wants to build a RAG application using Vertex AI. Which vector database is natively integrated with Vertex AI for storing embeddings?

A developer deployed a large language model on Vertex AI for real-time chat. Users report slow response times. The model generates sentences one word at a time. Which optimization should be applied to reduce latency?

A company wants to build a chatbot that answers questions based on internal documents. Which approach is most appropriate?

An enterprise customer needs to ensure that all data sent to the Gemini API is not used by Google for model improvement and must support a HIPAA BAA. Which access tier should they use?

A healthcare startup is building a generative AI application to draft patient education materials. They need to ensure the outputs are accurate, up-to-date, and tailored to each patient's condition. Which two techniques should they use to ground the model's responses in reliable medical knowledge? (Choose two.)

A data scientist wants to generate photorealistic images of products from text descriptions for an e-commerce catalog. The images must be brand-consistent and avoid generating distorted product features. Which Google Cloud generative AI service should they use?

A company wants to build a customer support chatbot that answers based on internal documentation. They use Vertex AI Search and want to ensure the model only uses retrieved documents. What should they do?

A retail company wants to use a generative AI model to create personalized product descriptions for thousands of items. They need the descriptions to be consistent in style and format, but they also want to avoid the model inventing false features. Which approach best balances consistency and accuracy?

A team is building a medical diagnosis assistant using a foundation model. To comply with regulations, they need to ensure the model does not make up facts. What is the best approach?

A company wants to generate a video from a text description using Google Cloud. Which service is designed for this?

A media company uses generative AI to produce personalized news summaries. They notice that summaries occasionally contain factual errors and biased language. What business strategy should they implement to address these issues while maintaining user engagement?

A media company plans to launch a generative AI feature that creates personalized article summaries for subscribers. Before launch, the product team must choose an operating model for ongoing quality, cost, and safety oversight. Which approach best supports responsible scaling of the feature?

A marketing team wants to generate product descriptions using a text generation model on Vertex AI. They need consistent output style across all descriptions, including tone and length. They have a small set of 10 high-quality example descriptions that capture the desired style. The team has limited ML expertise and wants a quick solution that does not require model retraining. Which approach should they use?

A marketing team wants to generate personalized email subject lines that match their brand voice. They need a Google Cloud service that allows them to fine-tune a generative model on their own email data. Which service should they use?

A data scientist wants to generate realistic product images for an online catalog using Google Cloud's generative AI. Which service should they use?

A healthcare company is using a generative AI model to draft patient education materials. The model sometimes generates content that includes specific medical advice, which could be harmful if inaccurate. The company wants to ensure that the model's outputs are safe and do not provide medical recommendations. Which technique should they implement?

A marketing team is using a generative AI model to create ad copy. They want to ensure the outputs align with their brand voice and avoid offensive language. Which two practices should they adopt? (Choose two.)

Which TWO techniques are effective for reducing bias in generative AI model outputs?

A university research group wants to experiment with Google's Gemini models through a simple web interface, without writing any code or provisioning cloud infrastructure. They need to upload PDFs, ask questions, and iterate on prompts interactively. Which Google Cloud offering should they use?

A financial institution deploys a chatbot using Gemini Pro in Vertex AI. Compliance requires logging all user inputs and model outputs for audit. Which approach meets this requirement?

A financial analyst uses generative AI to summarize earnings reports. The summaries vary in style. Which THREE methods can improve consistency? (Choose three.)

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?

A data science team wants to build a custom model for generating product descriptions that adhere to specific brand guidelines. They have 5,000 high-quality examples. Which approach balances cost and accuracy?

A user reports that the model's response to the same prompt varies significantly across different calls. Which parameter change would most likely reduce variability?

A multimodal generative AI system processes both image and text inputs to produce captions. During inference, the image encoder sometimes produces noisy or missing features. Which architectural design decision best handles such input degradation without retraining?

A company is developing a generative AI application that will be used by customers in multiple countries, including those with strict data residency laws. How should they approach data governance?

After fine-tuning a model on customer support data, the model starts using profanity. What is the most effective mitigation?

A marketing team uses a Gemini model to generate ad copy. They notice the outputs are repetitive and lack variety across multiple runs for the same prompt. They want more diverse creative options without sacrificing relevance. Which parameter adjustment should they make?

A product manager wants to quickly build a conversational agent that can answer FAQs from the company's help center articles. They have limited coding experience. Which Google Cloud service is BEST suited for this task?

A developer is using the Gemini API to generate text summaries. They want to control the creativity and diversity of the output. Which THREE parameters can they adjust?

A research lab is fine-tuning a large language model on a small dataset of medical records. They observe that the model overfits, memorizing specific patient details and producing outputs that violate privacy regulations. Which technique should they apply to improve generalization and reduce memorization?

A team wants to improve the factual accuracy of their chatbot responses regarding internal company policies. What is the most effective approach?

A company notices that their AI chatbot occasionally generates incorrect information. Which technique can best reduce hallucinations without retraining?

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

A global software company uses a generative AI model to produce localized release notes. Outputs are accurate but inconsistently formatted: some use tables, some bullet lists, and some paragraphs, which breaks the publishing pipeline. The team wants stable, machine-parseable formatting across all runs. Which technique should they prioritize?

A developer is using the Gemini API to generate marketing copy. They want the output to be diverse and creative but still relevant to the topic. Which THREE parameter adjustments would help achieve this? (Choose 3)

A startup develops a generative AI tool for legal document review. To ensure explainability, they want the model to cite specific clauses from source documents when making assertions. Which technique should they use?

A healthcare startup needs to process sensitive patient data using NLP models on Google Cloud. They require HIPAA compliance and the ability to run models within their VPC. Which service should they use to access Gemini models?

A company is piloting a GenAI feature for email drafting in Gmail. They want to measure productivity improvement. Which metric is MOST directly tied to the business goal of reducing time spent on email composition?

A company wants to estimate the total cost of ownership (TCO) for a gen AI solution on Google Cloud. Which factors are most important?

A company is using Vertex AI Model Registry to manage multiple versions of its custom generative model. They want to automatically route a percentage of traffic to a new model version for testing. What should they do?

A company is deploying a generative AI model for medical diagnosis assistance. To comply with both Google's AI Principles and emerging regulations (e.g., EU AI Act), they must ensure appropriate human oversight. Which THREE measures should they implement?

A marketing team wants to generate consistent brand-aligned social media posts using Vertex AI Studio. Which prompt engineering technique should they use to ensure the output tone matches their brand voice?

The exhibit shows the output of describing a model on Vertex AI. What does 'modelSource: MODEL_GARDEN' indicate about this model?

A retail company uses a generative AI model to create personalized product recommendations. The model sometimes generates recommendations that include products the company does not sell. Which technique should be used to prevent the model from generating non-existent products?

A streaming platform uses a large generative model for personalized content suggestions. Budget constraints require minimizing inference costs without significantly degrading quality. Which approach is most effective?

A bank is deploying a retrieval-augmented generation application on Vertex AI so that a Gemini model answers employee policy questions using the bank's internal document repository. The team wants the model's responses to cite source documents and to reduce fabricated content. Which two capabilities should they implement to ground the model in the bank's own content? (Choose two.)

A project manager wants to understand which Google Cloud generative AI services are subject to the 'Prohibited Use' policy. Where can they find the most up-to-date information?

A marketing team uses a generative AI model to produce ad copy. They notice that when they set the temperature parameter to 0.1, the outputs are very similar across runs, but when they set it to 0.9, the outputs vary widely. They want a balance between creativity and consistency for a campaign that requires some variation but also brand alignment. Which temperature value should they choose?

A logistics company plans to use generative AI to draft responses to customer shipment inquiries. Legal requires a documented process for reviewing model outputs and handling harmful or inaccurate content before responses reach customers. Which practice should be built into the solution?

A developer is using the Gemini API to generate code snippets. They notice the outputs often contain deprecated API calls. Which parameter adjustment or prompt strategy would most effectively encourage the model to use current APIs?

A company is required by the EU AI Act to ensure high-risk AI systems are transparent and auditable. They are using a proprietary model from a vendor. Which step is CRITICAL?

A company is deploying a generative AI system for medical diagnosis support. To comply with Google's AI Principles and regulatory requirements, which TWO actions are essential? (Select 2)

A healthcare organization is using Vertex AI to build a generative AI application that summarizes patient notes. They need to ensure that the model does not inadvertently generate or expose protected health information (PHI) in its outputs. Which Google Cloud feature should they implement to detect and redact sensitive data in the model's responses?

A financial analytics firm wants to prototype prompts against several Gemini model versions quickly, compare outputs side by side, and then export the winning prompt configuration into a production application with enterprise controls. Which combination of Google Cloud offerings best supports this workflow?

Which Google Cloud generative AI model is specifically designed for code generation tasks?

A financial services company wants to build a generative AI application that can answer questions based on their internal documents, which are constantly updated. They need the model to cite sources and avoid hallucination. Which Google Cloud service should they use?

A logistics company built a Gemini-powered assistant that answers driver questions about routes and hours-of-service rules. The assistant performs well on common questions but produces fabricated regulatory citations when asked about rare edge cases. The team has a curated set of correct answers for these edge cases and wants the model to adopt that behavior reliably. Which approach best fits?

According to Google's AI Principles, which of the following is a key commitment regarding privacy?

A developer wants to add real-time speech transcription to a customer call center application. They need low latency and high accuracy for multiple languages. Which Google AI API is most appropriate?

Which THREE steps are required to secure a generative AI pipeline that uses Vertex AI and involves sensitive customer data?

A media company is using Vertex AI to build a generative AI application that creates personalized news summaries. They want to ensure the model's outputs are factually grounded in their curated article database and that the application can scale to thousands of concurrent users. Which two Google Cloud services should they use to achieve these goals? (Choose two.)

A machine learning team is using Vertex AI to train a custom model. They want to optimize hyperparameters automatically. Which TWO steps are necessary to set up hyperparameter tuning in Vertex AI? (Choose TWO)

Refer to the exhibit. A developer sees this error when trying to deploy a model from Vertex AI Model Registry. What is the most likely cause?

A financial analyst is using a large language model to generate executive summaries from lengthy earnings call transcripts. The summaries often miss key financial figures and include irrelevant details. Which technique should be used to improve the relevance and accuracy of the summaries?

A company deploys a GenAI-powered code review assistant. During evaluation, they find that the assistant often suggests security vulnerabilities as improvements. What is the MOST likely cause?

A product team is designing a generative AI application to create personalized email campaigns. They want to ensure the model produces high-quality, relevant content while minimizing risks such as bias and harmful outputs. Which two practices should the team implement? (Choose two.)

A financial services firm wants to deploy a generative AI assistant that summarizes earnings call transcripts for its analysts. The firm's risk committee requires that the assistant never produce investment recommendations and that all outputs be traceable to source transcript passages. Which design choice most directly enforces both constraints?

A healthcare startup is developing a generative AI system to assist doctors in diagnosing rare diseases. According to Google's AI Principles, what is the MOST important requirement before deployment?

A retail company wants to use a generative AI model to create unique product descriptions for thousands of items. They need the model to produce varied, human-like text without being explicitly programmed for each product. Which core capability of generative AI does this scenario primarily rely on?

A company is using Vertex AI to deploy a text generation model for a chatbot. They want to reduce the response latency. Which configuration change is most effective?

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?

A researcher wants to use Google's AlphaFold for a project. What is the primary capability of AlphaFold?

A data analyst needs to run a simple regression model directly on data stored in BigQuery without moving data to another platform. Which service should they use?

In the transformer architecture, what is the role of the attention mechanism?

A data scientist observes that a text generation model consistently produces outputs that stereotype certain genders. According to Google's AI Principles, what is the BEST first step?

Which Google initiative provides a set of interactive, open-source tools to help UX designers and product managers build human-centered AI products?

Which TWO Google Cloud services can be used together to implement a RAG (retrieval-augmented generation) pipeline? (Select 2)

A company wants to embed a generative AI writing assistant into their Google Docs workflow. The assistant should help users draft emails and reports based on prompts. Which Google Workspace feature should they leverage?

Which TWO are components of the Vertex AI Generative AI Studio?

What is the primary purpose of Google's Content Safety filters in Vertex AI?

A tech company wants to ensure that their generative AI model does not produce harmful content. They plan to use Google Cloud's content safety features. Which two methods can they use to customize content safety? (Choose two.)

An AI team is building a customer support chatbot for a telecom company using a fine-tuned LLM on Vertex AI. The model performs well on common issues but fails to answer correctly for rare or novel problems, often providing plausible-sounding but incorrect solutions. The team has a large corpus of internal troubleshooting documents. They want to minimize incorrect answers while keeping latency low. Which approach should they take?

A financial services firm is deploying a generative AI model to assist in loan approval decisions. To comply with regulatory requirements for fairness and explainability, which THREE actions should they take? (Choose 3)

Which Google AI model was the first to demonstrate that transformers could be pre-trained bidirectionally on a large corpus, leading to major improvements in language understanding?

Which TWO are benefits of using retrieval-augmented generation (RAG) over fine-tuning?

A company wants to build a chatbot that answers questions using their internal knowledge base. Which approach is most suitable?

Which of the following is a key principle in Google's AI Principles that directly addresses the need to avoid creating or reinforcing unfair bias?

Refer to the exhibit. A data scientist runs the gcloud command and sees the model listed. However, when they try to deploy the model to an endpoint, they get an error: 'Model is not deployable'. What is the most likely reason?

A company is prompt engineering a model for customer support. They want to reduce hallucination (false information) in responses. Which TWO techniques are most effective? (Choose two.)

An enterprise is deploying a customer-facing chatbot using a foundation model on Vertex AI. They need to ensure the model does not produce toxic outputs. Which combination of settings and features should they implement?

A company is considering whether to use Vertex AI's Generative AI Studio. Which TWO are benefits?

A software company wants to provide users with a clear understanding of when and why their AI system may produce incorrect answers. Which tool from the Responsible AI toolkit should they use to communicate model limitations?

A company wants to generate high-quality product images from text descriptions for an e-commerce catalog. They need photorealistic results. Which model and approach should they choose?

A development team is integrating a large language model into a healthcare application. They need to reduce the risk of generating harmful medical advice. Which THREE measures should they implement? (Choose three.)

A hospital network wants patients to describe symptoms in a mobile app and receive immediate guidance, but the clinical knowledge base changes weekly and the network must be able to update answers without retraining a model. They also need the assistant to escalate to a nurse when confidence is low. Which Google Cloud approach best meets these requirements?

A project manager wants to automatically generate weekly status reports from meeting notes and project data. The team uses Google Workspace. Which built-in capability is the QUICKEST to implement?

A healthcare organization needs a generative AI model to answer medical questions using proprietary clinical guidelines. They have a large dataset of doctor-patient interactions. Should they fine-tune a pre-trained model or use Retrieval-Augmented Generation (RAG)?

A financial services firm wants to deploy a generative AI assistant that summarizes analyst research for internal advisors. The security team requires that the assistant never expose confidential client data in its responses, and the business wants to move quickly without building a custom model from scratch. Which approach best balances speed, control, and data protection on Google Cloud?

A data scientist needs to generate high-quality images from text prompts using Google Cloud. Which service should they use?

Which TWO of the following are best practices for prompt engineering?

Which Google resource provides interactive visualizations and exercises to help AI practitioners understand concepts like fairness, interpretability, and privacy?

A financial institution is using Vertex AI to generate personalized investment advice. They need to ensure that the model's responses are grounded in the latest regulatory documents and do not include outdated or fabricated information. Which feature should they implement to achieve this?

A team is preparing to use Vertex AI Studio to prototype a generative AI application. They want to understand which factors directly influence the quality and safety of the model's responses. (Choose two.)

A data scientist needs to fine-tune a foundation model for a sentiment analysis task without managing infrastructure. Which Google Cloud service should they use?

A company fine-tunes a model using Vertex AI and notices the model's performance drops on the original training task (e.g., language understanding) after fine-tuning for a new task (e.g., summarization). What could be the cause?

A healthcare organization is using a generative AI model to summarize patient discharge instructions. They need to ensure the summaries are accurate and do not omit critical information. Which technique should they implement to reduce the risk of omissions?

A large enterprise is using Vertex AI to deploy a generative AI model for internal document summarization. They need to ensure that the model's responses are based on the most current internal documents and that the model does not hallucinate. They also want to minimize latency and cost. Which feature of Vertex AI should they implement?

A company is using Vertex AI to generate report summaries. They want to measure ROI. Which three metrics should they track? (Choose THREE)

A company is deploying a document summarization solution using Vertex AI. They want to minimize cost while maintaining quality. Which three strategies should they implement? (Choose THREE)

A developer uses the Vertex AI Python SDK to call a Gemini model for structured JSON output. However, the model often returns malformed JSON. Which parameter should the developer set in the generation configuration to enforce valid JSON output?

A healthcare startup fine-tunes a model to generate patient education materials. They want to ensure the model never gives medical advice, only information. They add a safety instruction, but the model sometimes still gives advice. What advanced technique should they apply?

A developer wants to use the Gemini API to generate creative text. Which TWO parameters can they adjust to influence the output?

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

A financial services firm wants to use generative AI to assist employees in drafting emails. They are evaluating Duet AI in Gmail (now Gemini in Workspace). Which capability directly supports this use case?

A company wants to use a generative AI model to create product descriptions from a list of features. They need the model to consistently follow a specific format: a headline, followed by three bullet points, and a closing sentence. Which technique should they use to guide the model's output structure?

A startup's developer wants to quickly test different prompts against Gemini models, compare model outputs side by side, and export working prompt code, all from a browser interface before committing to an application architecture. Which Google Cloud offering should the developer use?

Which THREE of the following are potential risks when deploying generative AI?

What is the primary benefit of using foundation models (like Gemini) as opposed to training a model from scratch?

A data scientist wants to run large-scale distributed training of a custom deep learning model using Google's custom AI accelerators. Which infrastructure should they choose to minimize cost while leveraging Google's proprietary chips?

A retail chain's leadership wants to understand how generative AI could improve its customer service operations but is unsure where to start. They ask a cloud consultant to identify candidate use cases, estimate potential value, and flag which ones are realistically achievable with current technology. Which activity should the consultant perform first?

A regional insurance company wants to let claims adjusters ask natural-language questions about 12 years of policy documents and claim histories stored in Cloud Storage. Leadership wants a working prototype in two weeks, minimal model-tuning effort, and answers that cite the exact source document. Which Google Cloud approach should the team implement?

A company wants to adopt GenAI for code generation and review. To ensure code quality and security, they plan to implement a change management program. Which THREE actions are most effective?

Which technique allows a model to incorporate real-time data from external APIs?

Which TWO strategies are effective for reducing latency in a generative AI chat application deployed on Vertex AI? (Select 2)

A startup is building a customer support chatbot using Vertex AI and wants to ground responses in their product documentation to reduce hallucinations. Which approach should they use?

A financial institution wants to deploy a generative AI system for automated report generation. They require that the model does NOT expose sensitive information from its training data and that outputs are factually accurate. Which THREE techniques should they combine?

A small marketing agency wants its staff to draft blog posts, summarize meeting notes, and brainstorm campaign ideas using a conversational assistant. The agency has no cloud engineering team and prefers a ready-to-use product with enterprise-grade data protections rather than building anything. Which Google Cloud offering best matches this need?

A small marketing agency wants to add a Google Cloud generative AI assistant that can summarize campaign documents stored in Google Drive and answer follow-up questions about them, with minimal development effort. Which Google Cloud offering should they choose?

A prompt engineer wants to improve the model's adherence to a specific output format (e.g., always start with a greeting). Which technique should they try first?

A team needs to generate photorealistic product imagery for an e-commerce catalog from text descriptions, and later needs to edit existing photos by removing unwanted objects while preserving the rest of the scene. Which Google Cloud generative media capabilities should they use for these two tasks, respectively?

Refer to the exhibit. A developer sees this error when trying to call a Vertex AI endpoint for online prediction. What permission does the requesting identity need to be granted?

A retail company wants to build an assistant that can answer customer questions about its product catalog, but the catalog changes daily. The team wants the model to reference the latest product information without retraining. Which approach should they use?

A healthcare company is using Vertex AI to build a generative AI assistant that helps doctors draft clinical notes. The assistant uses a fine-tuned PaLM 2 model deployed on a private endpoint. Recently, doctors have reported that the assistant takes over 30 seconds to respond, causing workflow delays. Additionally, the monthly Vertex AI costs have increased by 40% without a proportional increase in usage. The model responses are generally accurate but sometimes include irrelevant details. The company wants to improve response time and cost while maintaining acceptable quality. A review of logs shows that most requests are for similar note types (e.g., progress notes, discharge summaries) and that the same prompt is used repeatedly with minor variations. What should the company do first?

A startup is building a generative AI tool that helps users write code. They want to launch quickly but need to ensure the generated code is secure and does not introduce vulnerabilities. They have a small team of developers with some ML experience. The tool should be cloud-hosted. Which approach balances speed, security, and cost?

Refer to the exhibit. This is the IAM policy for a project containing a Vertex AI Agent Builder agent and a data store. The agent is unable to access the data store. What is the most likely cause?

A data analyst wants to build a regression model in BigQuery to predict sales from historical data without writing any Python code. Which BigQuery ML statement should they use to define the model?

A team is deploying a large language model for legal document summarization. They find the model occasionally omits critical legal clauses. Which improvement technique would be most effective?

A developer is building a customer support chatbot using a large language model. The chatbot frequently generates plausible-sounding but incorrect answers to product questions. Which technique should be applied to improve factual accuracy?

A media company wants to create a custom AI assistant that can answer employee questions by referencing internal policy documents stored in Google Drive. They need a low-code solution that allows them to configure the assistant, connect data sources, and deploy it for internal use. Which Google Cloud offering should they use?

A healthcare startup is exploring GenAI for clinical note summarization. They have concerns about patient data privacy. Which Google Cloud approach best addresses privacy while still using powerful models?

A team monitors their generative AI model on Vertex AI. They notice output quality declining. Which metric is most likely the root cause?

A financial institution is deploying a generative AI solution that generates investment advice. They must ensure fairness, avoid toxic outputs, and comply with regulations like GDPR. Which TWO strategies should they implement? (Choose two.)

A content generation model for e-commerce product descriptions repeats the same phrases across multiple descriptions (e.g., 'high-quality', 'best-in-class'). The team wants more varied and engaging output. Which parameter adjustment is most appropriate?

A product team at a retail company is using a foundation model on Vertex AI to generate short marketing taglines for new products. They find the outputs are often too long and sometimes include extra commentary. They want to constrain the model to produce only a single concise tagline. Which parameter should they adjust?

A data scientist is using Vertex AI's Generative AI Studio to experiment with prompt designs. Which THREE features are available in the studio?

A company deployed a large language model on Vertex AI using the configuration shown in the exhibit. During peak usage, users report high latency. Which change is most likely to improve latency?

An e-commerce company is using a generative AI model to write product descriptions. They want to ensure that the model does not generate harmful content such as hate speech or violence. Which Google Cloud feature should they configure?

A financial services firm needs to generate synthetic data for training models while ensuring that no real customer data leaks. Which technique should they use?

A financial services firm is evaluating Google Cloud generative AI offerings to build an internal assistant that answers employee policy questions using the firm's own documents. The firm requires that answers be grounded in those documents rather than the model's general knowledge, and that the assistant cite the source passages it used. Which two capabilities should the firm rely on? (Choose two.)

A retail company with a large FAQ database wants to build a generative AI customer service chatbot that can answer questions accurately with up-to-date information. Which business strategy should they prioritize?

A software development team builds an internal code assistant using a generative model. The assistant writes Python functions that often contain security vulnerabilities such as SQL injection or command injection. The team wants to mitigate these vulnerabilities without adding a manual review step for every code snippet, as that would slow development. They have access to a static analysis security scanner API. Which approach best addresses the vulnerabilities while maintaining developer velocity?

A company wants to build an internal knowledge base that allows employees to ask questions about company policies in natural language. The knowledge base is stored in a Google Cloud SQL database. Which architecture should they use?

A developer uses a generative AI model with the system instruction shown. The response is correct but very brief. Which parameter adjustment could encourage more detail without losing accuracy?

A healthcare company is building a clinical decision support system using Gemini 1.5 Pro on Vertex AI. They need responses that are highly accurate and comply with medical regulations, including traceability to source documents. They have a large corpus of curated medical guidelines stored in PDFs in Cloud Storage. Their team has experience with both fine-tuning and prompt engineering. Which approach best ensures regulatory compliance and accuracy?

Which THREE of the following are generative AI modalities supported by Google Cloud services?

A company wants to generate high-quality images from text descriptions for their marketing materials. They need the ability to edit specific regions of an image without regenerating the entire image. Which Google Cloud service should they use?

A generative AI model for chatbot responses sometimes produces toxic language. The team wants to reduce toxicity without significantly affecting the model's helpfulness. Which approach is best?

A startup with limited budget wants to quickly test a generative AI use case for personalized email marketing. Which approach minimizes time-to-market and cost?

A healthcare organization wants to use generative AI to draft email responses to patient inquiries. They need to ensure that the model never generates medical advice and always includes a disclaimer. Where should they enforce these constraints?

A university's IT department is evaluating Google Cloud generative AI offerings to build a course-assistant tool for students. They want to reduce engineering effort by using managed services rather than hosting models themselves. Which two Google Cloud offerings should they consider? (Choose two.)

A logistics company uses a generative AI model to draft incident reports from sensor logs. Reviewers find the reports are often incomplete, missing fields such as root cause and corrective action. The team wants to improve output completeness without retraining the model. Which TWO techniques should they use? (Choose two.)

A global bank wants to deploy a generative AI assistant for employees across multiple European countries, each with strict data residency laws. Which deployment strategy is most compliant?

A regional insurance company wants to launch a generative AI assistant that answers policyholder questions. Legal requires that every customer-facing answer be traceable to an approved policy document, and that the system never invent coverage terms. The company has about 40,000 internal policy PDFs that change quarterly. Which approach should the GenAI Leader recommend?

Which THREE factors should you consider when selecting a foundation model from Model Garden? (Choose three.)

A cloud architect is designing a generative AI pipeline that must comply with the EU AI Act for high-risk AI systems. Which of the following is a mandatory requirement under the Act?

A financial services firm uses a Gemini model to generate quarterly risk summaries from internal reports. Reviewers note that summaries sometimes contradict the source tables. The team wants the model to reason step by step over the figures before writing the summary. Which technique should they use?

A team is developing a mobile app that must run AI inference on-device for low latency and offline capability. Which Gemini model variant is designed specifically for on-device deployment?

A business wants to build a generative AI application but has limited data science resources. What is the recommended path?

A developer is using Vertex AI Studio to experiment with prompts. They want to ensure that the model's responses are grounded in factual information from a trusted knowledge base. Which feature should they enable?

A financial services company is deploying a generative AI model to summarize sensitive customer emails. The security team requires that no email content is used to train or improve the underlying foundation model. Which Google Cloud approach ensures this requirement is met?

Which THREE are best practices for designing prompts for a generative AI model?

Which TWO techniques can help improve the factual accuracy of a language model's outputs? (Choose two.)

A software company is using a large language model to generate code snippets from natural language descriptions. The generated code often has syntax errors and does not follow the company's coding standards. Which approach is most effective to improve the quality of the generated code?

A company wants to use AI to make hiring decisions. They are concerned about bias against certain demographic groups. According to Google's AI Principles, which approach is MOST aligned?

A utility company's board approves a generative AI program and asks the program lead to present a plan showing how investment will be governed and how value will be tracked from pilot through production. The lead wants a framework that ties each initiative to a business owner, defines stage gates for continued funding, and specifies which metrics justify scaling. Which approach best meets the board's expectation?

A developer wants to add a GenAI feature to their existing web application. They need to integrate with the app's backend using REST APIs. Which integration pattern is MOST appropriate?

A data scientist is using a large language model to generate product descriptions. The descriptions are often too verbose. Which parameter adjustment is most appropriate?

A model generates responses that frequently repeat phrases or words. Which parameter adjustment is most likely to fix this?

A junior developer is experimenting with a large language model and notices that the same prompt produces different outputs each time it is run. Which characteristic of generative AI models explains this behavior?

A startup wants to generate realistic product videos from text descriptions for social media ads. Which Google Cloud service should they use?

Refer to the exhibit. A sudden surge of traffic reaches 15,000 requests per second, but the endpoint can only handle 1,000 req/s per replica. What will happen to new requests?

A national retail chain wants to deploy a generative AI assistant that recommends products to shoppers in six countries. The company's legal team requires that customer conversations never leave the country of origin, while the engineering team wants one consistent deployment pattern across all regions. Which Google Cloud approach best satisfies both requirements?

A financial services firm is using a large language model to generate quarterly investment summaries from raw market data. The summaries occasionally contain fabricated statistics and sometimes omit key risk factors. The team wants to improve factual accuracy and completeness without retraining the model. Which TWO techniques should they apply? (Choose two.)

A team is building a multi-modal agent that needs to accept a user's image of a handwritten note, convert it to text, and then run a sentiment analysis. They want to minimize latency and cost. Which approach is best?

A company is developing an AI-powered interview assistant that screens job applicants. The responsible AI team wants to ensure the model does not discriminate based on gender, race, or age. Which TWO practices should they implement?

An enterprise needs to generate natural-sounding speech from text for a voice assistant. They require low latency and support for custom voice models. Which service should they use?

A marketing team is using a generative AI model on Vertex AI to create ad copy for a new product launch. The initial outputs are generic and do not reflect the brand's tone. The team wants to quickly improve the outputs without retraining the model. They have a set of example ad copies that exemplify the desired tone. Which technique should they use?

A healthcare company is using a generative AI model to summarize patient records. They are concerned about the model generating incorrect medical information. They want to ensure that the summaries are grounded in the provided records and do not include hallucinations. Which technique should they implement?

A retail company wants to build an internal tool that generates short product descriptions from bullet points. They have no machine learning engineers on staff and want to avoid managing any infrastructure. Which Google Cloud approach best fits their need?

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

Which Google Cloud feature enables you to experiment with different prompts and model parameters interactively, and also supports model tuning without writing code?

A company is evaluating ROI for a GenAI-based code review assistant. Which metric set BEST captures both productivity and quality improvements?

An enterprise is concerned about the cost of using a large LLM for a high-volume customer support chatbot. They want to reduce token consumption while maintaining response quality. Which strategy would be MOST effective?

A financial services firm is preparing a board presentation on its generative AI program. Directors want assurance that spending is disciplined and that failures are contained. Which TWO practices should the program adopt? (Choose two.)

An enterprise wants to use Gemini for a customer-facing application. They require the following: data isolation in a VPC, audit logging, and SLA guarantees. Which THREE features of Vertex AI satisfy these requirements?

A data scientist notices that a Gemini model generates inconsistent responses to similar prompts. What is the likely cause?

A financial services firm needs to fine-tune a large language model on proprietary financial data. They require data to never leave their VPC and need full audit logging. Which Gemini access method should they use?

Which THREE of the following are common techniques to reduce harmful biases in generative AI models? (Choose three.)

A company wants to adopt GenAI for internal knowledge management. They plan to start with a small pilot team, gather feedback, and then expand. Which change management approach is MOST aligned with this strategy?

A financial services firm uses a generative AI model to draft client emails. The drafts are accurate but sometimes use an overly casual tone. The firm wants to enforce a consistently formal tone across all drafts. Which approach is most reliable for this requirement?

A company uses Vertex AI PaLM for code generation. The code often contains security vulnerabilities. Which improvement should be applied?

A startup wants to deploy a custom-tuned large language model for real-time inference on Vertex AI. They need the lowest possible latency for end users. What deployment strategy should they choose?

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

A retail marketing team wants to generate product descriptions in five languages. The team has no machine learning engineers and wants to avoid managing any infrastructure. Which Google Cloud option should the GenAI Leader recommend first?

A machine learning engineer wants to convert text into numerical vectors for similarity search. Which Google Cloud service should they use?

A company uses a generative model to produce product descriptions. The descriptions are factually inconsistent with the product specs. Which technique would best ensure factual accuracy?

A company wants to generate images from text descriptions using Google Cloud. Which service should they use?

A company uses a text generation model for customer support but notices it occasionally provides outdated information. Which technique should they implement to improve output accuracy?

A startup wants to integrate a GenAI assistant into Google Workspace (Docs, Gmail, Sheets) to help employees draft emails and create charts. Which Google AI offering is designed for this purpose?

A company wants to ensure that its generative AI application complies with the GDPR right to erasure (right to be forgotten) for user data used in model fine-tuning. What is the best approach?

A small marketing agency wants to let its non-technical staff draft blog posts using generative AI without writing any code or managing infrastructure. The agency already uses Google Workspace. Which Google Cloud offering should they adopt to meet this need most directly?

A data scientist is using Vertex AI to fine-tune a Gemini model for a specialized legal document summarization task. They have a small set of labeled examples (200 pairs). Which fine-tuning method is MOST cost-effective and likely to perform well?

What is the primary purpose of the temperature parameter when configuring a generative AI model?

A company is using generative AI for code generation and wants to evaluate the quality of generated code for security vulnerabilities. Which metric is most appropriate?

Which Google Cloud AI service is specifically designed for extracting structured data from scanned documents, such as invoices and receipts?

A media company wants to let its editors query a large archive of internal video transcripts using everyday conversational questions, and the app must return grounded answers that cite the exact source clips. The team has no machine learning engineers and wants the least operational overhead. Which Google Cloud offering should they use?

An enterprise is comparing Google Cloud Vertex AI vs AWS Bedrock vs Azure OpenAI for a generative AI application. Which unique Google differentiator allows the model to reference up-to-date web information and private data with managed retrieval?

A retail company has deployed a generative AI chatbot for customer support. They notice that the model sometimes provides incorrect product information. The team wants to ground the model's responses in their product catalog to improve accuracy. Which Vertex AI feature should they enable?

A team uses Vertex AI Generative AI Studio to tune a model via RLHF. After tuning, the model outputs are bland. What likely went wrong?

A project manager wants to measure the business impact of a GenAI code review tool. Which THREE metrics should they track to evaluate ROI? (Choose 3)

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?

A company is adopting generative AI for customer support. Which TWO strategies should they implement to manage risks related to brand reputation?

A financial services firm is deploying a GenAI-powered contract analysis tool. The tool must extract key clauses and flag risky language. Which strategy BEST ensures structured, machine-readable output that downstream systems can parse?

A chatbot built with Vertex AI PaLM API often provides outdated information about company policies because the training data is months old. Which approach should the team use?

A team is using a generative AI model to create marketing copy. They want the responses to be more focused and less random. Which parameter should they adjust?

A company is deploying a Gemini-based application and needs to ensure low latency for real-time user interactions. They also want to reduce cost. Which THREE strategies should they consider? (Select 3)

A company is using a generative AI model to create personalized email responses to customer inquiries. The responses sometimes contain factual errors or irrelevant information. The company wants to improve the accuracy and relevance of the responses. Which TWO techniques should they use? (Choose two.)

Which feature in Vertex AI allows users to browse over 300 foundation models and deploy them with minimal code?

A global logistics firm wants to add a generative AI feature that drafts replies to customer shipment inquiries. The team must prove business value to executives within one quarter, keep engineering effort low, and later swap in a different model without rewriting the application. Which design decision best supports those goals?

A retail company wants to build an internal assistant that answers employee questions using the company's HR policy documents. The documents change frequently, and the company does not want to retrain a model every time a policy is updated. Which approach best meets these requirements on Google Cloud?

A company is using Vertex AI generative models for a high-volume text summarization service. Which two strategies can reduce operational costs?

A marketing team needs to generate personalized email campaigns for thousands of customers. They want to maintain brand tone consistency and avoid manual writing. Which GenAI approach is BEST suited?

A data scientist is fine-tuning a foundation model for a specialized legal document summarization task. The labeled dataset is only 5,000 examples. Which fine-tuning technique would be MOST efficient to adapt the model without catastrophic forgetting and with minimal computational cost?

A data scientist fine-tunes a large language model on Vertex AI but gets poor results on validation data. What is the most likely cause?

A project manager wants to track the ROI of a generative AI feature that assists customer support agents. Which metric is MOST directly tied to productivity improvement?

Which Google AI milestone introduced the Transformer architecture that underpins modern LLMs?

A financial services firm is deploying a generative AI chatbot on Vertex AI. They need to ensure that the model's responses comply with strict regulatory requirements and do not include personally identifiable information (PII). They want to automatically filter out any PII from both user inputs and model outputs. Which Google Cloud service should they integrate?

A developer uses Vertex AI to generate code but the output is not syntactically correct. Which parameter should be adjusted?

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?

A company wants to use a pre-trained language model for customer support summarization. They need to ensure responses are concise and accurate. Which prompt engineering technique is most effective?

A financial services firm is deploying a generative AI model to answer customer queries about investment products. They want to ensure the model's responses are based on the most current and authoritative internal documents. Which technique should they implement?

A marketing team is using a generative AI model to create ad copy. They want to ensure the output is creative and diverse, but also relevant to the product. They decide to adjust the model's parameters. Which parameter should they increase to make the output more diverse?

What is the primary purpose of a system instruction in the Gemini API?

A data scientist is evaluating how to ground a generative AI model to reduce hallucinations when answering questions about a private knowledge base. Which TWO techniques are most suitable?

Which statement best describes the difference between the Gemini Flash and Gemini Pro models on Vertex AI?

Which of the following best describes the primary benefit of using Grounding with Google Search when building a GenAI chatbot?

A global bank uses a Gemini model on Vertex AI to generate personalized investment summaries for clients in multiple regions. Compliance requires that the model never recommend products prohibited in a given region. The team wants a control that enforces these rules regardless of how the prompt is phrased. Which approach should they use?

A data scientist fine-tunes a foundation model on customer support transcripts. After evaluation, the model's responses are too formal. Which adjustment during fine-tuning is most likely to make responses more conversational?

A global retailer uses a generative AI model to personalize product recommendations. They need to ensure that customer prompts and responses are not logged for model improvement to meet GDPR data minimization principles. Which configuration should they apply?

Which Google AI research organization is responsible for AlphaFold, a breakthrough in protein structure prediction?

Which Google Cloud service provides a managed environment for prompt engineering and model evaluation?

A data scientist is using the Vertex AI PaLM API for text generation. They notice that the model occasionally generates toxic content. Which parameter should they adjust to reduce the likelihood of toxic outputs?

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?

A healthcare company is evaluating foundation models for a patient triage assistant. They need to ensure the model is appropriate for medical use and that they can control costs. Which two factors should they consider when selecting and using a foundation model in Vertex AI? (Choose two.)

A company wants to use generative AI to create short product videos from text descriptions. Which Google Cloud service should they consider?

An AI company wants to detect whether text was generated by their own model. Which technology developed by Google is specifically designed for this purpose?

A multinational corporation deploys a generative AI chatbot across multiple regions. They need to comply with GDPR and local data residency requirements. Which THREE actions are necessary?

A developer is using a generative AI model to summarize long articles. They want to ensure the summaries are concise and do not exceed a certain length. Which parameter should they adjust to control the maximum length of the generated summary?

A company is piloting a GenAI feature that summarizes customer support tickets. They want to measure the impact on agent productivity before rolling out to all teams. Which approach BEST evaluates the pilot?

A company is deploying a generative AI model for customer support. They want to reduce hallucinations while maintaining fluency. They have a large dataset of previous support conversations. Which strategy should they prioritize?

A developer needs to use the Vertex AI PaLM API to generate text embeddings for a large corpus of documents. Which model should they use?

A company wants to use GenAI to generate marketing content such as blog posts and social media updates. They need the content to be on-brand and factually accurate. Which TWO features should they use?

A company is building a multilingual customer support chatbot that needs to understand and respond in 20 languages. Which Google model is most suitable for this task?

A company is deploying a GenAI-powered email drafting feature. They want to control costs while maintaining low latency for real-time suggestions. Which strategy is MOST effective?

A marketing team wants to use generative AI to draft product descriptions. Legal requires that no customer data or proprietary campaign plans appear in any prompt sent to the model. Which practice should the team adopt first?

A research team wants to fine-tune a Gemini model on Vertex AI using a dataset of proprietary scientific abstracts. They need to adjust the model's behavior with supervised fine-tuning while keeping the base model's general knowledge. Which Vertex AI capability should they use?

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

A researcher wants to adapt a large language model for a specialized medical terminology domain without retraining the entire model. Which fine-tuning method is MOST parameter-efficient?

A team wants to build a GenAI application that can interact with external APIs (e.g., to check inventory or place orders). Which Vertex AI component provides this capability?

A retailer is building a product recommendation chatbot using Vertex AI Agent Builder. They want the agent to answer questions about product availability, prices, and promotions, but also to escalate to a human agent when the query is complex. What should they configure in Agent Builder?

A company is using Gemini to generate marketing copy. They want the outputs to be more creative and varied. Which generation parameters should they adjust?

A regional insurance company wants to launch a generative AI assistant that drafts policyholder responses for its claims team. Before any code is written, the CIO asks the team to produce a document that articulates the intended business outcome, the target user group, the success metrics, and the boundaries of what the assistant may and may not do. Which artifact best matches this request?

A company is deploying a generative AI model for medical diagnosis support. Which THREE considerations are critical for responsible AI?

A university wants to deploy a generative AI study assistant across six faculties. Each faculty has its own curriculum documents and privacy rules, and the central IT team must prevent one faculty's content from appearing in another faculty's answers. Which architecture decision best satisfies this governance requirement?

A startup wants to quickly prototype a conversational AI application using Gemini. They need free access during development and do not require VPC controls. Which access tier should they choose?

Which THREE factors should be considered when choosing between a fine-tuned model and a prompted foundation model for a generative AI solution? (Select 3)

What is the purpose of grounding in Vertex AI?

A company is building a customer service chatbot using Vertex AI Agent Builder. The chatbot needs to answer questions based on a large internal knowledge base stored in a Cloud Storage bucket. The team wants to ensure the model can reference the latest documents without fine-tuning. Which configuration should they use?

What is the main advantage of using a model with a larger context window?

A health-tech startup is fine-tuning a generative AI model on electronic health records (EHR) to assist in clinical decision support. They need to ensure responsible AI practices. Which THREE measures should they implement? (Select three.)

A developer needs to generate embeddings for text data to be used in a semantic search application. Which Google Cloud service should they use?

Which THREE strategies should be combined to effectively reduce biased outputs in a generative AI model? (Choose three.)

A large e-commerce company is experiencing high costs for their generative AI product recommendation system. The system generates personalized product descriptions for millions of users daily. The team wants to reduce cost while maintaining quality. They are using a fine-tuned version of a large foundation model hosted on Vertex AI. The current cost is driven by the number of tokens processed. Which approach should they take?

A company is using a large language model for automated translation of legal contracts. They find that the translations sometimes alter the meaning of specific clauses. Which TWO approaches would most effectively preserve the original meaning? (Choose two.)

A marketing team uses Gemini in Vertex AI to generate campaign taglines. The first drafts are generic and closely mirror the prompt wording. They want more distinctive, varied taglines from the same model without changing the model itself. Which parameter should they adjust?

A developer is building a real-time speech transcription application for customer support calls. The audio is streamed, and the transcription must be returned with low latency. Which Google Cloud AI service should they use?

A company is choosing a generative AI model for code generation. Which TWO considerations are most important?

A company needs to extract structured data from scanned invoices (invoice number, date, total amount) using a pre-built AI solution. Which Google Cloud service is MOST appropriate?

A healthcare startup is developing an AI system to assist radiologists in detecting tumors from X-ray images. Which Google AI Principle is MOST directly applicable to this use case?

A mid-sized insurance company wants to adopt generative AI to help claims adjusters draft customer correspondence. Executives are unsure how to prioritize the first use case and want a framework that balances business value with implementation feasibility. Which first step best aligns with a value-driven generative AI adoption strategy?

During model evaluation, a team observes good performance on training data but poor on validation data. Which regularization technique is most appropriate to address this?

A gaming company is using Vertex AI Imagen to create concept art. They have a stable pipeline that generates images based on text prompts. Recently, they introduced a new feature: using a reference image to guide the style (image-to-image generation). However, when using a reference image, the generated images often have unnatural color shifts and artifacts. The team suspects that the reference image is being resized to a resolution that the model wasn't trained on. They are using the default Imagen settings. What is the most likely cause and the best solution?

A marketing company wants to fine-tune a generative AI model to adopt a specific brand voice. Which tuning method is most appropriate?

A large insurance company is using generative AI to automate claims processing. They have deployed a custom fine-tuned model on Vertex AI that reads claim documents and extracts key information. Recently, they noticed that the model’s performance degrades over time for certain claim types, leading to incorrect payouts. The team needs to detect and address model drift with minimal manual intervention. They have a data pipeline that captures incoming claims and user feedback on predictions. Which approach should they take?

A company is deploying a generative AI chatbot for customer support. They want to ensure that the chatbot does not generate harmful content and that they can customize the safety thresholds. Which TWO features in Vertex AI should they use? (Select 2)

A media company uses a Gemini model to produce short news digests from long articles. Editors complain that digests vary in length and sometimes bury the key fact in the middle. The team wants a repeatable, machine-checkable structure for every digest. Which technique should they use?

A marketing team wants to generate social media posts with Google Cloud's generative AI, but they have no machine learning experience. They need a no-code interface to experiment with prompts and tune settings like temperature. Which Google Cloud service should they use?

A developer is using Gemini 1.5 Pro and needs to process a 2-hour video to answer questions about its content. The video is stored in Cloud Storage. What is the most efficient approach?

A small marketing agency wants to add an AI assistant that summarizes campaign briefs and drafts social posts. The developers have limited cloud experience and prefer a fully managed, serverless way to call Google's Gemini models without provisioning infrastructure. Which approach best meets this requirement?

A media company uses generative AI to produce personalized news summaries for subscribers. They notice that the summaries sometimes contain factual inaccuracies, leading to customer complaints. The team needs to improve accuracy without slowing down the generation speed. They are using a pre-trained model via Vertex AI. What strategy should they implement?

A company is comparing Google Cloud Vertex AI vs AWS Bedrock vs Azure OpenAI. Their application requires grounding responses with real-time search results from the internet. Which platform's feature uniquely supports this requirement?

What is the key advantage of using adapter-based fine-tuning methods like LoRA compared to full fine-tuning of a large language model?

A large enterprise wants to deploy multiple generative AI models across different business units while ensuring cost governance and usage tracking. Which Google Cloud solution is best suited?

A developer is using the Gemini API to classify customer emails. They want to ensure that the model always returns one of three predefined labels: 'complaint', 'inquiry', or 'feedback'. Which model configuration is MOST appropriate?

A product manager wants to generate meeting summaries automatically using Gemini for Google Workspace. They need summaries to be sent to all participants immediately after the meeting ends. Which Gemini feature should they use?

A data scientist wants to train a model using BigQuery ML. Which two statements are true about BigQuery ML? (Choose two.)

An enterprise wants to use Gemini 1.5 Flash for a real-time chat application with low latency. Which trade-off should they expect compared to Gemini 1.5 Pro?

A retail company wants to use a generative AI model to create product descriptions from a list of attributes. They want a fully managed service that allows them to quickly experiment with prompts and adjust parameters without managing infrastructure. Which Google Cloud service should they use?

A retail company plans to use Vertex AI's generative AI to create product descriptions. They need to ensure descriptions are factually accurate and do not misrepresent products. Which strategy should they prioritize?

A retail company wants to use gen AI for customer service chatbots. They have a large volume of customer interactions. What is the primary business consideration for deploying a gen AI solution?

A financial services company wants to use generative AI to summarize large volumes of internal documents while ensuring that sensitive data never leaves their virtual private cloud (VPC). They need a solution that provides Gemini models with enterprise-grade security and data residency controls. Which Google Cloud service should they use?

A mid-size retail company wants to launch a generative AI assistant that drafts promotional product descriptions for its marketing team. The team expects a rapid pilot, but the CIO insists that any generated text must never expose the company's unreleased product roadmap or pricing data that may exist in internal documents. The company has no dedicated AI engineering staff and prefers a managed approach on Google Cloud. Which strategy best balances rapid pilot delivery with this data-exposure requirement?

A healthcare analytics team is evaluating a generative AI model for summarizing clinical notes. They observe that summaries are fluent but occasionally invent details not present in the source notes. They want a practical mitigation that reduces fabricated content without retraining the model. Which approach should they apply first?

An organization is running a large-scale training job for a custom NLP model with a batch size of 2048 and sequence length of 512. They need to minimize training time while keeping costs predictable. Which Google Cloud hardware should they choose?

A media company wants to produce short video clips from text prompts for social media campaigns. They need a Google Cloud service that can generate video from text and edit existing video clips, with enterprise-grade controls. Which Google Cloud offering should they choose?

A data scientist fine-tunes a generative image captioning model to describe medical images. The model outputs safe but very generic captions (e.g., 'An image of cells'). The goal is to produce more specific, clinically relevant descriptions. Which approach is most effective?

A company wants to deploy a generative AI chatbot for customer service but is concerned about cost unpredictability due to variable usage. Which pricing model should they choose to best manage costs?

A data scientist wants to improve the performance of a text classification model for customer feedback. They have a small labeled dataset of 500 examples and a large unlabeled corpus of 100,000 feedback messages. Which TWO strategies would be most effective? (Choose 2)

A company is deploying a GenAI system that generates product descriptions. During A/B testing, the new system shows a 20% increase in click-through rate (CTR) but a 15% increase in average cost per query due to the model size. The team wants to optimize cost without sacrificing the CTR gain. Which THREE actions should they take? (Choose three.)

A research team wants to use Google's AI to generate video content from text prompts for a creative project. Which Google Cloud generative AI model should they use?

A healthcare analytics team uses a Gemini model to generate patient-friendly discharge summaries from clinical notes. Clinicians report that summaries occasionally omit critical follow-up instructions. The team must improve recall of these instructions without retraining the model. Which two techniques should they apply? (Choose two.)

Which Google Cloud service allows you to run machine learning models directly using SQL queries on data in BigQuery?

A healthcare company is using a generative AI model to summarize patient notes. The model occasionally includes hallucinated medical details. Which strategy best reduces hallucinations?

A data scientist is fine-tuning a generative AI model for customer sentiment analysis. To ensure the fine-tuned model does not inadvertently memorize and reproduce personally identifiable information (PII) from the training data, which THREE practices should they follow? (Select 3)

An enterprise deploys a generative AI chatbot that must comply with GDPR right to deletion. Users can request deletion of their personal data. The chatbot uses a RAG pipeline with a vector database. What is the MOST effective way to handle deletion requests?

A company wants to build a GenAI-powered customer support chatbot. They require the chatbot to provide accurate answers based on the latest product documentation, and they need to control costs by minimizing token usage. Which TWO strategies should they use?

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?

A company is deploying a generative AI system for medical diagnosis. Which TWO measures are essential for responsible AI in this high-stakes domain?

A developer wants to improve the factual accuracy of the model's summaries. Based on the exhibit, what should they do?

You are a generative AI lead at a healthcare startup developing a system to summarize patient medical records for quick review by doctors. The system uses a fine-tuned LLM. After deployment, doctors report that the summaries often miss critical details like medication dosages and allergy information. The current pipeline preprocesses patient records by extracting text from EHR, feeding it to the LLM, and outputting a summary. The team has limited time and budget. They cannot retrain the model because it is hosted as a managed API. Which action should you take to most effectively improve the summarization quality without changing the model?

A company is fine-tuning a Gemma model using Vertex AI. They observe that the model overfits. Which TWO actions should they take to mitigate overfitting?

A retail company wants to integrate generative AI into its customer service chatbot to handle routine inquiries. They have a limited budget and want to launch quickly. Which strategy is most appropriate?

A research team wants to document the intended uses, limitations, and ethical considerations of their newly trained image classification model. Which Google Cloud tool should they use?

A small marketing analytics team wants to build a generative AI assistant that can answer questions about their proprietary campaign performance data. They have very limited machine learning engineering resources and want the fastest possible path to a working prototype on Google Cloud. Which approach should they take?

A company is deploying a chatbot using Vertex AI and wants to ensure that the model's responses are grounded in Google Search results to reduce hallucinations. Which feature should they enable?

A startup wants to build a conversational AI assistant that can understand and generate text, images, and code. They need a single model that can handle multimodal inputs and outputs. Which Google Cloud generative AI model should they choose?

An e-commerce company is using a generative AI model to recommend products. They notice that the recommendations are often irrelevant. What is the most likely cause?

A financial services firm is using a foundation model on Vertex AI to generate investment summaries from quarterly reports. The summaries are accurate but often miss key financial metrics and trends. The team cannot afford to fine-tune the model frequently. Which technique should they use to improve the completeness and relevance of the summaries without modifying the model?

A healthcare chatbot must avoid hallucinations. Which TWO techniques should the team implement? (Choose two.)

A developer is using the Vertex AI Gemini API to generate product descriptions. They get a 400 error 'INVALID_ARGUMENT: The model's maximum input token limit is 8192.' What is the most likely issue?

A startup wants to quickly add a conversational AI assistant to its mobile app without managing any infrastructure. They need a managed API that provides access to Gemini models for chat and content generation. Which Google Cloud offering should they use?

A healthcare organization needs to run ML models on patient data stored in BigQuery while ensuring data never leaves the database. Which service allows them to create and execute ML models directly in BigQuery SQL?

A financial analyst wants to quickly generate a first draft of a market commentary from a few key statistics using a Google Cloud generative AI model. They have no coding experience and want to see the model's response immediately while adjusting the prompt. What should they do first?

A company is choosing between Google's Gemini API and an open-source model. Which factor is most important for a business with limited ML expertise?

Which Google Cloud AI service provides a unified ML platform for building, deploying, and managing ML models in production?

An energy utility is preparing a generative AI assistant that drafts responses to regulator inquiries. Before launch, the GenAI Leader must define how the program will be evaluated and governed on Google Cloud. Which TWO practices should be included? (Choose two.)

A media company is building an application that must summarize 400-page legal contracts. Their current model has a context window of only 32,000 tokens, and truncating the documents loses critical clauses. They want to use a Gemini model on Vertex AI that can ingest the entire contract in a single request. Which Gemini model capability should they select for this workload?

A startup is building a generative AI legal document assistant for small law firms. They want to ensure that the model's outputs are accurate and can be traced back to specific legal statutes. Which approach best supports this requirement?

A marketing team is using a generative AI model to create ad copy. They want to control the model's creativity so that outputs are more focused and deterministic for a formal campaign. Which parameter should they adjust?

What is the primary purpose of Google's Datasheets for Datasets?

A healthcare startup wants to use Vertex AI to deploy a model that helps doctors diagnose rare diseases. The model must be explainable, showing the reasoning path. Which technique should they implement?

A company wants to build a text-to-speech application for generating voiceovers in multiple languages. They need to use a pre-built Google API without training custom models. Which service should they use?

A hospital network wants to transcribe clinician dictation and then have a generative model produce structured discharge summaries from those transcripts, all within Google Cloud. Which combination of offerings matches this workflow?

A startup is building a GenAI application and must decide between using a pre-built API (e.g., Vertex AI Gemini API) or fine-tuning a custom model. Which factor STRONGLY favors using the pre-built API?

A startup wants to use a pre-trained model to generate product descriptions without training. Which Google Cloud service should they use?

A financial services firm must comply with regulations when using gen AI. Which two measures are critical?

A developer runs this command: `gcloud ai models upload --region=us-central1 --display-name=my-model --artifact-uri=gs://my-bucket/model.pkl`. What is the primary purpose?

A bank is evaluating Google Cloud generative AI offerings to build an internal document-processing application. Leadership requires that the solution support grounding responses in the bank's own document repository and provide enterprise controls such as IAM-based access and audit logging. Which two Google Cloud offerings should the bank consider to meet these requirements? (Choose two.)

A media company is using Vertex AI Imagen to generate marketing images. The output frequently contains unrealistic artifacts, especially in human faces. The team has fine-tuned the model using their brand assets. What is the most likely cause and recommended fix?

A legal firm uses a generative AI to draft contracts. They want the output to follow a specific clause structure. Which technique should they use in the prompt?

A marketing agency uses a generative AI model to create slogans for ad campaigns. The model outputs generic slogans like 'Quality you can trust' that lack originality. The agency has a library of past award-winning slogans and wants to generate more creative and brand-specific outputs. They have a requirement that the model must not produce slogans longer than 15 words. Which technique should they prioritize?

A healthcare organization wants to use generative AI for medical report summaries. What is the primary concern?

A company is using Vertex AI to build a language model for generating legal documents. They need to ensure the model's outputs are accurate and verifiable. Which TWO features should they use?

Which of the following best describes how large language models (LLMs) generate text?

A developer receives the above JSON response from a Vertex AI language model. The output content is correct, but the developer expected the model to not answer geography questions. What should the developer do to prevent the model from responding to geography queries?

A product team uses a translation model to convert English product descriptions into French. The model mixes formal and informal French dialects. Which simple prompt modification likely solves this?

A healthcare company needs to process medical records (e.g., discharge summaries) to extract structured data. Which AI API is specifically designed for this purpose?

A music streaming service wants to use AI-generated playlists and artwork, but is concerned about potential copyright infringement. They plan to use a generative model that was trained on a large corpus of publicly available music and images. Which action is MOST important to mitigate IP risk?

Which THREE are essential components of a responsible AI strategy for GenAI? (Select three.)

Which TWO actions can reduce the cost of using Vertex AI Gemini API? (Choose two.)

A startup is prototyping a multimodal AI application that processes images and text. They have a limited budget and want the fastest time to market, with minimal infrastructure setup. Which combination of services should they use for prototyping?

A team is deploying a text generation model for legal document review. They observe that the model occasionally generates factually incorrect legal citations. Which approach best reduces this issue?

A company is deploying a GenAI application that must meet SOC 2 compliance. Which three Google Cloud offerings can be used in a compliant manner? (Choose three.)

A company is deploying a generative AI model for medical advice. What is the most important consideration?

A team is using a generative AI model to create summaries of customer feedback. The summaries are often too long and include unnecessary details. The team wants to make the summaries more concise without losing key information. Which technique should they use?

A developer is using Vertex AI PaLM 2 to generate product descriptions. The output is often too verbose and includes irrelevant details. Which technique should the developer apply?

Refer to the exhibit. The team changed the generation parameters to reduce output variability. However, summaries now often repeat the same phrases. Which parameter change is most likely causing the repetition?

A company is deploying a GenAI contract analysis system that processes confidential legal documents. They need to ensure that the model does not retain or train on customer data. Which configuration is REQUIRED?

A research team wants to leverage Google DeepMind's work to accelerate drug discovery. They are interested in using a model that predicts protein structures and another that can generate novel protein sequences with desired properties. Which TWO Google DeepMind achievements are most relevant? (Select 2 options.)

Which THREE considerations are critical when deploying a generative AI model using Vertex AI Endpoints for a latency-sensitive application? (Choose THREE.)

A company needs to deploy a chatbot on a mobile device that must work offline. They want to use Gemini for natural language understanding but need minimal latency and no cloud dependency. Which Gemini model variant is most appropriate?

A machine learning engineer is evaluating a generative AI model for bias. They have a diverse test set covering gender, race, and age groups. Which metric would best indicate if the model's performance is systematically worse for certain demographic groups?

A logistics company wants employees to ask natural-language questions about shipment trends and have Gemini generate SQL, charts, and narrative summaries directly against data already stored in BigQuery, without moving or duplicating that data. Which Google Cloud capability should the company adopt?

Refer to the exhibit. This JSON describes a Vertex AI endpoint with a deployed model. Which statement about scaling is true?

A global bank wants to use Gemini models in Vertex AI to summarize sensitive customer emails. The security team requires that prompts and responses never leave the bank's controlled network perimeter and that access is restricted to approved projects. Which Google Cloud capability should they configure?

A company uses Vertex AI Agent Builder to create a customer support agent. They need the agent to answer questions about order status by calling an internal API. Which Vertex AI feature should they use?

An e-commerce company wants to add a conversational shopping assistant to its mobile app. The assistant must answer product questions using the company's catalog, call a backend API to check live inventory, and escalate to a human agent when the customer requests it. Which Google Cloud offering is designed for this?

A company wants to use Gemini for Google Workspace to improve productivity. They want to generate meeting summaries in Google Meet and draft email replies in Gmail. Which two Duet AI features should they enable? (Choose TWO)

A logistics company needs a generative AI model that can accept both text and images as input, and produce text output for describing shipping damage. They want to use a Google Cloud model through the Vertex AI API. Which Gemini model capability should they select?

A developer is building a customer support chatbot using Gemini models on Vertex AI. The chatbot must respond in a consistent, professional tone and avoid generating harmful or off-topic content. Which approach should the developer take to enforce these behavioral constraints?

An organization needs to deploy a generative AI application with strict compliance requirements, including data residency and auditability of model decisions. Which Google Cloud feature should they prioritize?

Which Google Cloud AI service would you use to transcribe customer service call recordings into text for subsequent analysis?

A company is using Vertex AI to generate customer support summaries from chat logs. They notice that the summaries sometimes include irrelevant details from the conversation. Which technique should they use to reduce irrelevant details?

A media company is using a large language model to generate scripts for animated shorts. They notice that the model sometimes produces content that closely resembles existing copyrighted scripts from well-known movies. Which technique should they implement to reduce the risk of generating such content?

An organization is building a RAG system using Vertex AI Vector Search. They notice that the retrieved documents are not relevant to the user's query. What is the most likely cause?

A regional insurance provider wants to launch a generative AI claims assistant. The executive sponsor insists the solution be built on a foundation model the company can host inside its own Google Cloud project, with no dependence on a vendor's externally managed endpoint. Which decision does the sponsor need to make first?

A financial services company uses a generative AI model to summarize customer complaints. They notice that summaries for certain demographics consistently omit negative sentiment. Which responsible AI practice should they apply FIRST to address this bias?

A company's generative AI model is producing biased outputs. What is the most effective mitigation strategy?

A data analyst wants to use Gemini in Google Sheets to help with complex formulas. Which feature should they use?

You are a generative AI architect for a large e-commerce company. Your team has built a product description generator using Vertex AI's text-bison model. The model is accessed via the Vertex AI API from a web application. You have set the temperature to 0.5 and top_k to 40. The team reports that the generated descriptions are often too generic and lack creativity. They want the descriptions to be more diverse and engaging. You are also concerned about cost, as each API call is billed. Which change should you recommend to increase creativity while managing cost?

A product manager wants to add a feature that drafts meeting summaries automatically in Google Meet. Which Gemini for Google Workspace capability should they use?

An organization is using Vertex AI Agent Builder to create a customer service agent. They want the agent to be able to hand off to a human agent when it cannot answer a question. What should they configure in the agent's design?

A marketing team at a retail company is using a generative AI model on Vertex AI to produce product descriptions from short bullet lists. They observe that the model's outputs are fluent but frequently invent specifications, such as claiming a jacket is waterproof when no such attribute was provided. The team wants to reduce these fabrications without retraining the model. Which approach should they take?

A developer is using the Gemini API to build a chatbot. They want the model to always respond in a friendly, professional tone. Which prompt engineering technique should they use?

A company wants to integrate generative AI into their existing CRM workflow to draft personalized email responses. They have limited engineering resources. Which two approaches should they consider? (Choose TWO)

A manufacturing company wants to use GenAI to generate maintenance reports from sensor data. They need structured output (JSON) for downstream systems, and they want to reduce token costs. Which THREE strategies should they use?

A company is designing a prompt engineering strategy for a customer service chatbot using Gemini. Which two practices are recommended for improving response quality? (Choose TWO)

A company wants to integrate GenAI into their existing customer relationship management (CRM) system. The CRM is a third-party SaaS application. Which implementation pattern is MOST suitable?

A data scientist uses Vertex AI Model Evaluation to assess a fine-tuned model for sentiment analysis. The evaluation report shows high precision but low recall on the 'negative' class. What is the best course of action to improve recall without sacrificing too much precision?

A logistics company is selecting a generative AI use case to fund first. Leadership wants a project that demonstrates value quickly, has accessible data, and carries limited regulatory exposure. Which use case best fits these selection criteria?

A company is moving a GenAI proof-of-concept to production. They need to ensure the system can handle variable traffic and maintain low latency. Which THREE practices should they implement? (Choose 3)

What is the primary benefit of using embeddings and vector search in a generative AI application?

What is the key advantage of using vector search for retrieval in a RAG system compared to keyword search?

A media company is using a foundation model in Vertex AI to summarize long articles. They notice that summaries sometimes omit key details from the middle of very long articles. Which action should they take to improve summary completeness while staying within the model's context window?

A marketing team wants to generate social media posts from product descriptions using Generative AI. They need consistent brand tone and the ability to iterate quickly. Which tool is BEST suited for this task?

A developer needs to integrate a GenAI model into an existing customer relationship management (CRM) system. The CRM exposes REST APIs and runs on-premises. Which integration pattern is MOST suitable?

A logistics firm wants every generative AI proposal to be judged on whether it reduces cost per shipment. Leadership asks the AI team to define the metric before any project starts. Which practice does this illustrate?

A company has deployed a GenAI-powered report generation system using Vertex AI. They notice that the cost is higher than expected. Investigation shows that many requests include very long prompts with repetitive boilerplate text. Which cost optimization strategy is MOST effective?

A logistics firm's leadership wants a plain-language summary of how generative AI could reduce costs in dispatch operations before approving any budget. The team has no data scientists available. Which first step best aligns with a generative AI business strategy?

A legal firm wants to automate contract analysis to extract key clauses and risks. They have 10,000 contracts in PDF format. The solution must handle varying layouts and be cost-effective. Which approach is BEST?

Which THREE are valid methods to reduce bias in generative AI outputs?

A data scientist is fine-tuning a large language model for a specialized domain using limited labeled data. To avoid catastrophic forgetting and reduce computational cost, which approach is recommended?

A company is deploying a generative AI application that generates medical reports. They need to ensure the output is factual and minimizes hallucinations. Which approach is most effective?

A global news agency is using a generative AI model to summarize breaking news articles in real-time. The model is deployed on Vertex AI across multiple regions (us-central1, europe-west4, asia-southeast1) for low latency worldwide. The agency has a Service Level Objective (SLO) of 99.9% availability and p99 latency under 2 seconds. Recently, during a major event, traffic spiked 10x, and the europe-west4 region experienced latency spikes over 5 seconds and some 503 errors. The team suspects the regional endpoint is under-provisioned. Which combination of actions should they take to meet the SLO consistently?

A large enterprise runs a generative AI solution serving millions of daily inference requests. To reduce costs, they propose using serverless endpoints (Vertex AI Prediction) with a custom container, but they notice high latency during cold starts. Which strategy best addresses this problem while minimizing cost?

A marketing agency uses generative AI to create social media posts. They need the output to be in a specific JSON format for downstream processing. Which prompt technique should they use?

A financial institution is implementing a generative AI chatbot to handle customer inquiries. The institution must comply with regulatory requirements (e.g., GDPR, SOX) and ensure data privacy. Which TWO actions should the institution take?

A company has been using an on-premises ML infrastructure for generative AI and wants to migrate to Google Cloud. They have a pipeline that fine-tunes a large language model weekly using a proprietary dataset. The migration must minimize downtime and data transfer costs. Which approach best addresses these requirements?

A global logistics company wants to build a generative AI assistant that can answer operational questions by retrieving information from internal PDF and HTML documents stored in Cloud Storage. They need a managed, serverless retrieval-augmented generation (RAG) capability that requires minimal infrastructure management and integrates with Vertex AI. Which Google Cloud service should they use?

A media company wants its editorial team to summarize long internal reports and ask follow-up questions about the content, all inside a Google Workspace interface they already use daily. They prefer not to build any custom application or call APIs. Which Google Cloud generative AI offering should they adopt?

An organization wants to ensure that when their employees use the Gemini API via Vertex AI, the grounding searches are restricted to internal company knowledge bases rather than the public web. Which feature should they enable?

A data scientist wants to compare the performance of three different foundation models for a text summarization task. They have a labeled dataset of summaries. Which Vertex AI tool should they use to perform this evaluation?

A game development studio wants to create dynamic non-player character (NPC) dialogues that adapt to player choices. They need a Google Cloud service that allows them to build conversational agents with custom logic and integrate with their game backend. Which service should they use?

A regulated healthcare organization needs to use Google Cloud AI services for processing protected health information (PHI). They require a signed Business Associate Agreement (BAA) and HIPAA compliance. Which service provides these assurances?

Which Google DeepMind achievement is recognized for predicting protein structures and advancing drug discovery?

A marketing team uses a text generation model to draft campaign copy. They want the output to consistently follow a specific brand voice and include a call to action at the end of every draft. Which technique should they apply?

Which Google service provides free access to Jupyter notebooks with GPU support for prototyping ML models?

A company wants to generate images for slide decks using Gemini in Google Slides. Which Gemini feature in Google Slides should they use?

What is the primary purpose of the transformer architecture in large language models (LLMs)?

A software vendor embeds Gemini in its SaaS product and needs each tenant's prompts and outputs isolated so that one tenant's data never appears in another tenant's responses. The vendor also wants usage tracked per tenant for billing. Which design should the team implement on Google Cloud?

A company deploying a generative AI assistant wants to allow users to override the AI's suggestions before final actions are taken. Which design pattern does this represent?

An e-commerce company uses a generative AI model to generate product descriptions. They observe that descriptions for high-end products use more sophisticated language compared to budget products, potentially reinforcing class stereotypes. What is the most likely cause, and what should they do to mitigate it?

A financial services company is using a large language model on Vertex AI to generate summaries of earnings reports. They notice that the model sometimes includes information not present in the source reports, leading to compliance risks. They want to reduce hallucinations by ensuring the model's output is grounded in the provided documents. Which technique should they implement?