Applications of Foundation Models

A marketing firm uses Amazon Bedrock to generate ad copy. They notice that the generated text often includes factual inaccuracies about their products. Which technique would most effectively reduce these inaccuracies?

A developer is using Amazon Bedrock to build a chatbot that answers customer queries. The chatbot must only respond based on the provided company documentation. Which approach best meets this requirement?

A financial services company is deploying a foundation model to analyze customer sentiment from call transcripts. The model outputs must be consistent and deterministic for auditing purposes. Which parameter configuration should the company use?

An e-commerce company is using a foundation model to generate product descriptions. They want to reduce costs by caching frequently requested descriptions. Which AWS service should they use to implement a cache?

A company wants to use a foundation model to automatically moderate user-generated content. The model must filter out inappropriate content with high accuracy. Which Amazon service is best suited for this task?

A startup is using Amazon Bedrock to power a virtual assistant. They need to ensure that personally identifiable information (PII) is not included in the model's responses. Which feature should they enable?

A company is using Amazon Bedrock to generate marketing content. They want to evaluate the quality of the generated text. Which TWO metrics are most appropriate for evaluating text quality?

A data scientist is fine-tuning a foundation model on Amazon Bedrock for a custom summarization task. Which THREE practices should they follow to optimize the fine-tuning process?

A company is using Amazon Bedrock to generate code snippets. They want to ensure the generated code is secure. Which TWO practices should they implement?

Refer to the exhibit. An IAM policy is attached to a user. Which models can the user invoke?

A company is building a chatbot using Amazon Bedrock to answer customer questions about their product catalog. The chatbot should only use information from the company's internal knowledge base and should not generate answers based on the model's pre-training data. Which feature should be enabled?

A company is using a foundation model on Amazon Bedrock to generate customer support responses. They notice that the model sometimes produces harmful or offensive content. Which approach is MOST effective to mitigate this issue?

A company wants to use a foundation model to automatically summarize lengthy documents. Which capability of foundation models is being utilized?

A company uses Amazon Bedrock to generate product descriptions. They want to ensure the outputs consistently follow a specific brand tone (professional yet friendly). They have a small set of example descriptions (few-shot examples) but do not want to fine-tune the model. Which strategy best achieves consistent tone without modifying the base model?

A company wants to build a chatbot that responds to customer queries using a foundation model. They need low latency and want to avoid managing infrastructure. Which AWS service should they use?

A developer is using Amazon Bedrock to generate text summaries. The output sometimes includes irrelevant information. What is the most effective prompt engineering technique to improve relevance?

A financial services company uses a foundation model for document analysis. They need to ensure the model does not output sensitive customer information from its training data. What is the most effective mitigation?

An e-commerce company uses Amazon Bedrock to generate product descriptions. They notice the descriptions are too long and contain repetitive phrases. Which parameter adjustment can help?

A healthcare company needs to use a foundation model for analyzing medical records while complying with HIPAA. They plan to use Amazon Bedrock. What should they do to meet HIPAA requirements?

A company uses a foundation model for real-time translation in a chat application. The latency is high. Which optimization would reduce latency the most?

Which TWO of the following are valid methods to reduce the risk of foundation models generating harmful or biased content?

Refer to the exhibit. A data scientist created this endpoint config for a foundation model in Amazon SageMaker. However, the endpoint fails to scale under load. What is the most likely reason?

Refer to the exhibit. A developer runs this command but gets an error: 'An error occurred (AccessDeniedException) when calling the ListFoundationModels operation'. What is the most likely cause?

A company uses Amazon Bedrock to generate product descriptions. They notice that the output sometimes contains incorrect information. What should they do to improve accuracy?

A healthcare company uses Amazon Bedrock to generate patient summaries. They need to ensure no protected health information (PHI) is leaked in the output. Which AWS service can they use to detect and mask PHI in text?

A company uses Amazon Bedrock to build a conversational AI. They want to enforce role-based access to the model. Which AWS service should they use?

A data scientist uses Amazon Bedrock. The model responses are too long. Which parameter should they adjust to limit the output length?

A company uses Amazon Bedrock to generate code. They want to ensure the code follows security best practices and does not contain vulnerabilities. Which approach is most effective?

A company wants to use a pre-trained foundation model for sentiment analysis without any customization. Which Amazon Machine Learning service provides access to foundation models via API?

A company uses Amazon Bedrock to generate marketing copy. They want to measure the quality of generated text compared to reference text. Which metric is most appropriate?

A company uses Amazon Bedrock with a custom model deployed via Amazon SageMaker. They want to monitor for data drift in input prompts over time. Which AWS service is best suited for this?

A data science team is fine-tuning a foundation model on Amazon SageMaker. Which THREE steps are part of the best practice? (Choose three.)

A company uses Amazon Bedrock to build a question-answering system. Which THREE features of Amazon Bedrock can improve answer accuracy? (Choose three.)

A security engineer creates the above IAM policy to allow a user to invoke an Amazon Bedrock model. However, invocation fails. What is the issue?

A developer invokes an Amazon Bedrock model and receives the above response. What does the 'stopReason' field indicate?

A company uses Amazon Bedrock to build a chatbot. The chatbot needs to answer questions based on internal company documents. Which AWS service should be integrated with Bedrock to enable Retrieval Augmented Generation (RAG) without managing infrastructure?

A developer is using Amazon Bedrock with the Claude model for text summarization. The output sometimes includes inaccurate information. What is the best practice to reduce hallucinations?

A startup needs to generate product descriptions from bullet points using a foundation model. They want a fully managed serverless experience. Which AWS service should they use?

A company fine-tunes a foundation model on SageMaker using a custom dataset. They notice the training job takes too long. Which optimization technique is specifically designed to reduce training time for foundation models?

An enterprise deploys a foundation model on Amazon Bedrock with a knowledge base. Users report that the model is returning outdated information. What is the most likely cause?

A data scientist is fine-tuning a foundation model on SageMaker. They want to prevent overfitting. Which THREE actions can help? (Select THREE.)

A developer receives the above response from invoking a Bedrock model. Which field indicates that the model completed its response normally?

A developer sends the above request to Amazon Bedrock with Anthropic Claude. The model returns a response that stops before reaching 500 tokens. What is the most likely reason?

A company uses Amazon Bedrock to generate summarizations of lengthy reports. Users report that the summaries are too verbose and include excessive detail. Which prompt engineering technique should the team apply to address this issue?

A healthcare company is deploying a conversational AI using a foundation model on Amazon Bedrock for patient triage. The application must minimize hallucinations and ensure factual accuracy. Which combination of techniques should the team implement?

An e-commerce company uses Amazon Bedrock to generate product descriptions from keywords. Some descriptions contain inaccurate details about product specifications. Which approach should the company take to reduce factual errors?

A media company is using Amazon Bedrock to generate marketing copy with a foundation model. They want to ensure the output adheres to brand voice guidelines (e.g., friendly, professional). Which prompt engineering strategy is most effective for this requirement?

A startup is deploying a foundation model on Amazon SageMaker for real-time inference. They notice high latency (over 2 seconds per request). Which action is most likely to reduce latency?

A research team is using Amazon Bedrock to analyze scientific papers. They want the model to generate answers based only on papers published after 2023. Which approach should they use?

A company is using Amazon Bedrock to generate code snippets. Developers report that the generated code sometimes contains security vulnerabilities. Which action should the team take to mitigate this risk?

Which THREE are benefits of using Amazon Bedrock over self-managing foundation models on EC2? (Choose THREE.)

Which TWO techniques can reduce the cost of running a fine-tuned foundation model on Amazon SageMaker? (Choose TWO.)

A company wants to automatically summarize customer support tickets into a short paragraph. Which AWS service is MOST appropriate for this task?

A company runs a chatbot using a large language model on Amazon Bedrock. They notice high latency during peak hours. Which action would be MOST effective to reduce latency without degrading response quality?

A generative AI application occasionally produces factually incorrect responses. The team has already tried prompt engineering and increasing the temperature parameter. Which next step is MOST effective to improve factual accuracy?

A startup needs to build a real-time text translation feature for a customer chat application. Latency must be under 200 ms per request. Which AWS approach is BEST suited?

A team is fine-tuning a foundation model using SageMaker. They want to minimize training time while keeping the model's original knowledge. Which technique is BEST suited?

A team deployed a text generation model on Amazon Bedrock. They want to monitor for toxic content in model outputs. Which evaluation approach is MOST effective?

A company is building a multi-modal application that processes images and text to answer questions about product defects. Which foundation model approach is BEST?

Which TWO actions can help reduce bias in a foundation model’s outputs? (Choose two.)

Which THREE practices are recommended for responsible AI when deploying foundation models? (Choose three.)

Refer to the exhibit. This is an Amazon Bedrock invocation request for Claude. What is the purpose of the "stop_sequences" parameter?

Refer to the exhibit. A developer sees this error when calling Amazon Bedrock for inference. What is the MOST likely cause and recommended solution?

A company is building a customer support chatbot using Amazon Bedrock. They need to store conversation history for context across sessions. Which AWS service is best suited for this purpose?

A company uses Amazon Bedrock to generate marketing copy. The summaries are too verbose. Which parameter should be decreased to directly limit the length of the output?

A company uses Amazon Bedrock to generate product descriptions. They need to ensure outputs do not contain offensive language. Which service should they integrate to filter content?

A developer is building a RAG-based Q&A bot with Amazon Bedrock Knowledge Bases. They need a managed vector store for document embeddings. Which service should they use?

Which pricing model does Amazon Bedrock use for foundation model inference?

A company wants to adapt a foundation model for a custom domain with very limited labeled data and minimal cost. Which approach is most suitable?

A developer uses Amazon Bedrock to generate code. Some outputs contain syntax errors. What is the most likely cause?

Which AWS service provides a serverless API for accessing foundation models with per-token pricing?

Which parameter controls the randomness of generated text in a foundation model?

Which TWO actions are recommended for improving the factual accuracy of a foundation model's responses when using RAG?

Which THREE are best practices for ensuring generated content complies with corporate brand guidelines when using Amazon Bedrock?

Which TWO AWS services can be used together to build a chatbot that leverages a foundation model for natural language understanding?

Refer to the exhibit. You receive this response from Amazon Bedrock. What is the most likely cause of the incomplete information?

A company operates a customer service platform that uses Amazon Bedrock with a foundation model to generate automated responses. The system has been in production for three months. Recently, customers have reported that responses are becoming repetitive and less relevant over time. The development team notices that the model's performance has degraded, especially for queries about newer products that were added after the initial deployment. The team currently uses a static prompt with a fixed knowledge base that was set up at launch. The model is invoked via the Bedrock API with standard settings. The team wants to improve response quality without incurring high costs or extensive re-engineering. What should the team do?

A company needs to summarize thousands of customer reviews daily using a foundation model. The solution must minimize latency and cost while handling variable traffic. Which AWS service should they use?

A startup uses Amazon Bedrock with a provisioned throughput to generate product images. They now have unpredictable traffic and want to reduce costs. What should they do?

Which TWO of the following are benefits of using Amazon Bedrock for building applications with foundation models?

A data scientist is using a foundation model to summarize long documents. Which TWO of the following steps are most likely to improve the quality of the summaries?

A marketing team is using a foundation model to generate marketing copy. Which THREE of the following should they consider to ensure responsible and cost-effective use?

A multinational corporation uses a foundation model via Amazon Bedrock to translate internal communication documents from English to multiple languages. They notice that the translations often miss company-specific jargon and acronyms, leading to confusion. The company has a glossary of approved translations for terms like 'Project Atlas' and 'Operation Synergy.' They want to improve translation accuracy quickly and with minimal effort. What approach should they take?

A marketing agency uses a foundation model to generate images for social media campaigns. Some generated images have contained violent or inappropriate content, damaging the brand. The agency needs to prevent such content from being displayed automatically. They are using Amazon Bedrock for image generation with Stable Diffusion. What is the most effective way to filter out inappropriate images?

A law firm uses a foundation model to draft legal briefs. To ensure accuracy, they want to ground the model's outputs in authoritative legal sources. They have a large database of prior case law and statutes stored in Amazon S3. The firm's IT team must implement a solution that reduces hallucinations while being cost-effective. The solution should allow the model to retrieve relevant documents and generate responses based on them. Which approach should they take?

A startup company is developing an e-commerce platform and wants to use Amazon Bedrock to generate product descriptions automatically. They have a small team of developers who are not machine learning experts. The product catalog is stored in a DynamoDB table, and each product has attributes like name, category, price, and a brief description. The company wants the generated descriptions to reflect the unique brand voice, which is documented in a few internal style guides stored as PDF files in Amazon S3. They need a solution that allows them to quickly test the approach without significant infrastructure changes or model training. The development team is familiar with AWS SDKs and want to minimize ongoing maintenance. The team has already set up a Bedrock foundation model (Claude) and can make API calls. They tested simple prompts but the output lacked the brand's informal yet professional tone. They want to incorporate examples from the style guides directly into the prompt without retraining. The team fears that including the entire style guide in each prompt would exceed token limits and increase costs. Which approach should they take to effectively incorporate the brand voice with minimal changes?

A financial services company is deploying a foundation model on Amazon Bedrock to generate compliance reports from internal audit logs. The model must not output any personally identifiable information (PII). They have configured a Bedrock Guardrail with sensitive information filters set to the 'HIGH' sensitivity level. During testing in a staging environment, testers still observed PII being occasionally generated in the report outputs. The guardrail did not block these instances because the PII was embedded in a context that the guardrail's pattern matching did not catch (e.g., structured JSON data with embedded names). The company requires a solution that minimizes latency and cost, as they process thousands of reports daily. They cannot afford to increase inference time significantly due to strict SLAs. They also want to avoid re-engineering the entire solution. Which additional step should they take to effectively eliminate PII leakage while maintaining performance?

A developer is trying to invoke the Claude v2 model in Amazon Bedrock from a Lambda function. The Lambda function's IAM role has the following policy attached: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "bedrock:InvokeModel", "Resource": "*" } ] } When the Lambda function runs, it receives the error shown in the exhibit. Which additional step is most likely needed to resolve this issue?

A financial services company has built an internal assistant on Amazon Bedrock using Anthropic Claude 3 Sonnet. Employees ask questions that require retrieving the latest internal policy documents, which are updated frequently and stored in Amazon S3. The company wants the assistant to answer with accurate, up-to-date citations without retraining the model. Which approach should they implement?

A media company uses Amazon Bedrock to generate short product descriptions. They notice that outputs vary in tone and sometimes include unwanted promotional claims. They want consistent, brand-aligned results while keeping the same foundation model. Which action best addresses this requirement?

A solutions architect needs to build a generative AI application that can invoke foundation models from Amazon and third-party providers through a single, unified API without managing any infrastructure. The architect wants the fastest path to a working prototype using AWS-native tooling. Which AWS service should the architect choose?

A media company uses Amazon Bedrock to generate personalized news summaries. They notice that summaries sometimes include details not present in the source articles. They want to reduce these hallucinations without retraining the model. Which approach should they use?

A developer is building a retrieval-augmented generation (RAG) assistant on Amazon Bedrock. The assistant must answer questions about internal policy documents that change frequently, and answers must cite the source passages. The developer wants a managed capability that handles chunking, embedding, and retrieval so the application code stays minimal. Which Amazon Bedrock feature should the developer use?

A financial services firm uses Amazon Bedrock with Anthropic Claude to analyze earnings call transcripts. They need the model to output results in a strict JSON schema for downstream processing. The model occasionally returns prose or invalid JSON. Which Amazon Bedrock feature should they use to enforce the output structure?

A company wants its Amazon Bedrock application to always answer in a formal tone, never discuss competitors, and never reveal internal project codenames. The controls must apply consistently to every request and response without changing the underlying model. Which Amazon Bedrock capability should the company configure?

A retail company wants to build an application that uses a foundation model on Amazon Bedrock to answer customer questions about product availability. They need the model to access real-time inventory data from their internal database and perform actions such as reserving an item. Which TWO capabilities should they implement to achieve this? (Choose two.)

A financial services company uses Amazon Bedrock with the Anthropic Claude 3 Haiku model to answer employee questions about internal policies. The knowledge base is updated weekly, and the company wants the model to cite the exact source document and page number in its responses. Which approach should the company use to meet these requirements?

A team is deploying a foundation model on Amazon Bedrock for a customer-facing assistant. They must reduce hallucinations and keep answers grounded in approved company content while controlling inference cost. Which TWO approaches should the team implement? (Choose two.)

A financial services company uses Amazon Bedrock with the Anthropic Claude 3 Sonnet model to answer employee questions about internal policies. The policy documents are updated frequently, and the model occasionally provides outdated or incorrect policy details. The company wants the model to base its answers on the most current authoritative documents without retraining the model. Which approach should they use?

A developer wants to compare the output quality of several foundation models available in Amazon Bedrock for a text summarization task. They need to evaluate responses side by side using the same prompt. Which Amazon Bedrock feature should they use?

A media company uses Amazon Bedrock to generate article summaries. They notice that for long articles, the model sometimes ignores instructions placed at the beginning of the prompt. The company wants to improve the model's adherence to instructions without changing the model or increasing cost significantly. Which prompt engineering technique should they apply?

A developer is integrating an Amazon Bedrock foundation model into an application that must support multi-turn conversations, maintain chat history, and switch between different provider models with minimal code changes. The application should use a consistent request and response format. Which Amazon Bedrock API should the developer use?

A media company wants to automatically generate short video captions from uploaded audio files using a foundation model on AWS. The solution should transcribe speech and then produce concise captions. Which combination of AWS services should they use?

A developer is using Amazon Bedrock to generate summaries of news articles. They notice that the model sometimes includes information not present in the original article. Which term describes this phenomenon?

A media company runs a daily news digest built on Amazon Bedrock with Anthropic Claude. Editors complain that summaries of long policy documents sometimes omit the final recommendations, even though the source text clearly contains them near the end. The requests currently pass only the document body and set a maximum output length of 300 tokens. Which change best addresses the truncation of the source content before the model reasons over it?

A healthcare company uses Amazon Bedrock with a foundation model to generate patient education materials. They must ensure that the model does not include protected health information (PHI) in its responses, even if it appears in the prompt. Which Amazon Bedrock feature should they configure?

A media company uses Amazon Bedrock to generate personalized news summaries for its subscribers. The model occasionally produces summaries that include outdated facts from its training data. The company wants the summaries to reflect only the most recent articles from its internal content management system (CMS). The CMS exposes a REST API that returns the latest articles. Which approach should the company take to ensure the generated summaries are grounded in the latest articles?

A startup wants to build a mobile app that generates personalized workout plans using a foundation model. They need to minimize infrastructure management and pay only for what they use. Which AWS service should they use to access foundation models via a single API?

A company is using Amazon Bedrock to build a conversational agent. They want to ensure the agent maintains context across multiple turns in a conversation. Which TWO strategies should the developer implement? (Choose two.)

A healthcare company is building an application on Amazon Bedrock that uses a foundation model to answer patient questions about medications. The company must reduce the risk of harmful or inaccurate medical advice. Which TWO strategies should they implement? (Choose two.)

A retail analytics team wants an assistant that answers questions about last quarter's sales using data stored in an Amazon S3 bucket of PDF reports and CSV exports. They want the model to cite the underlying documents and avoid inventing figures. Which Amazon Bedrock capability should they use?

A developer is building a prototype that needs to generate product descriptions from a few keywords. The developer wants to use a foundation model on Amazon Bedrock but has no labeled training data and wants to avoid managing infrastructure. Which approach should the developer use?

A company is deploying a foundation model on Amazon Bedrock to generate product descriptions. They want to ensure the model's output is factually consistent with the provided product specifications and avoids hallucinated features. Which TWO techniques should they use? (Choose two.)

A retail company wants to compare the output quality of several foundation models available in Amazon Bedrock for a product description generation task. They need a repeatable, automated way to score responses against reference descriptions. Which AWS capability should they use?

A financial services company is building an application on Amazon Bedrock that generates personalized investment summaries. The compliance team requires that every generated summary includes an exact, verifiable citation from the company's approved regulatory documents, and that the model must not fabricate any citation. The company has a large corpus of approved PDF documents stored in Amazon S3. Which approach should the company use to meet these requirements?

A financial services company is using Amazon Bedrock to generate investment summaries. They must ensure that the model does not provide personalized financial advice, which is a regulatory requirement. Which AWS feature should they use to block the model from generating such advice?

A financial services firm uses Amazon Bedrock with a foundation model to draft client emails. Compliance requires that no personally identifiable information from the prompt ever appear in the response, and that the model refuse requests for investment guarantees. The team wants a managed, configurable layer rather than custom prompt engineering alone. Which combination should they apply?

A developer is using Amazon Bedrock with the Cohere Command model to generate summaries of technical documents. They need to control the length of the summaries and ensure they do not exceed a certain number of tokens. Which parameter should they use in the InvokeModel API call?

A financial services company uses Amazon Bedrock to power an internal assistant that answers employee questions about HR policies. The company must ensure that the assistant never reveals sensitive employee data. The HR policy documents are stored in an Amazon S3 bucket and are updated frequently. The company wants the assistant to cite the exact policy document and section for each answer. Which solution meets these requirements with the LEAST operational overhead?

A software company is deploying a generative AI assistant on Amazon Bedrock. They need the assistant to include citations to source documents in its answers and to avoid answering when no supporting document is found. Which configuration should they use?

A media company uses Amazon Bedrock to generate short video scripts. Writers report that outputs are inconsistent in tone and sometimes ignore the required scene structure. The team wants a reusable, versioned artifact that enforces the role, tone, and output format across many invocations without retraining the model, and they want to track changes over time. Which Amazon Bedrock feature should they use?

A logistics company is building an internal assistant on Amazon Bedrock that must answer operational questions using its private runbooks and must return citations so staff can verify answers. The team also needs to control cost by limiting how much source text is sent with each request. Which TWO capabilities should they combine to meet these requirements? (Choose two.)

A healthcare startup is using Amazon Bedrock to build a patient education chatbot. The chatbot must generate responses that are empathetic, accurate, and compliant with medical privacy regulations. The startup wants to implement safeguards to prevent the model from generating harmful or inappropriate content. Which TWO actions should the startup take to meet these requirements? (Choose two.)

A retail company runs a product-question answering feature on Amazon Bedrock. During peak hours, requests intermittently fail with a ThrottlingException even though average usage is well within quota. The team needs a solution that smooths bursty traffic, retries failed calls, and avoids overwhelming the model endpoint, with minimal application code changes. Which approach should they take?

A startup prototypes a support assistant using Amazon Bedrock and needs to compare how three different foundation models handle the same set of 200 support tickets. They want objective quality scores, including accuracy against reference answers and robustness, before committing to one model. Which approach should they use?

A startup wants to add image generation to its design tool. The team does not want to manage GPU infrastructure, train models, or host endpoints, and they want to call a managed API for a text-to-image foundation model available in Amazon Bedrock. Which action should they take?

A retail company is using Amazon Bedrock to generate personalized product recommendations in real time. The model sometimes produces recommendations that include products the company no longer sells. The company wants to ensure that only in-stock products are recommended. The product catalog is stored in an Amazon DynamoDB table that is updated continuously. Which solution should the company implement to meet this requirement with minimal latency?

A hospital is deploying an Amazon Bedrock-powered assistant that answers staff questions about internal policies. The compliance team requires that the assistant refuse requests for individual patient diagnoses and that any response containing protected health information be masked before it is returned. Which TWO capabilities should the team configure in Amazon Bedrock Guardrails to meet these requirements? (Choose two.)