{"id":114133,"date":"2025-11-14T07:52:28","date_gmt":"2025-11-14T07:52:28","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=114133"},"modified":"2025-11-21T07:31:34","modified_gmt":"2025-11-21T07:31:34","slug":"check-aif-c01-free-dumps-part-2-q41-q80-to-verify-the-v15-02-real-aif-c01-exam-questions-help-you-prepare-well","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/check-aif-c01-free-dumps-part-2-q41-q80-to-verify-the-v15-02-real-aif-c01-exam-questions-help-you-prepare-well.html","title":{"rendered":"Check AIF-C01 Free Dumps (Part 2, Q41-Q80) to Verify the V15.02: Real AIF-C01 Exam Questions Help You Prepare Well"},"content":{"rendered":"<p>Success in the AWS Certified AI Practitioner (AIF-C01) exam requires a reliable learning resource, and the AIF-C01 dumps (V15.02) stand out. We have the latest study materials, aligned with the actual exam objectives, to enhance your targeted practice with real exam questions, time management skills, and confidence. The <a href=\"https:\/\/www.dumpsbase.com\/freedumps\/get-the-most-updated-aif-c01-dumps-v15-02-to-make-preparations-start-with-aif-c01-free-dumps-part-1-q1-q40-today.html\"><em><strong>AIF-C01 free dumps (Part 1, Q1-Q40) of V15.02<\/strong><\/em><\/a> are online to help you check the quality. From the demo questions, you can trust that all the questions and answers in the dumps will maximize your chances of success. Join thousands of satisfied professionals who have trusted DumpsBase to help them achieve their certification goals. With the most updated AIF-C01 dumps (V15.02), you&#8217;ll be fully prepared to pass on your first attempt.<\/p>\n<h2>Continue to check our <span style=\"background-color: #ccffff;\"><em>AIF-C01 free dumps (Part 2, Q41-Q80) of V15.02 below<\/em><\/span>:<\/h2>\n<script>\n\t  window.fbAsyncInit = function() {\n\t    FB.init({\n\t      appId            : '622169541470367',\n\t      autoLogAppEvents : true,\n\t      xfbml            : true,\n\t      version          : 'v3.1'\n\t    });\n\t  };\n\t\n\t  (function(d, s, id){\n\t     var js, fjs = d.getElementsByTagName(s)[0];\n\t     if (d.getElementById(id)) {return;}\n\t     js = d.createElement(s); js.id = id;\n\t     js.src = \"https:\/\/connect.facebook.net\/en_US\/sdk.js\";\n\t     fjs.parentNode.insertBefore(js, fjs);\n\t   }(document, 'script', 'facebook-jssdk'));\n\t<\/script><script type=\"text\/javascript\" >\ndocument.addEventListener(\"DOMContentLoaded\", function(event) { \nif(!window.jQuery) alert(\"The important jQuery library is not properly loaded in your site. Your WordPress theme is probably missing the essential wp_head() call. You can switch to another theme and you will see that the plugin works fine and this notice disappears. If you are still not sure what to do you can contact us for help.\");\n});\n<\/script>  \n  \n<div  id=\"watupro_quiz\" class=\"quiz-area single-page-quiz\">\n<p id=\"submittingExam11086\" style=\"display:none;text-align:center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\"><\/p>\n\n<div class=\"watupro-exam-description\" id=\"description-quiz-11086\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-11086\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-436283'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_1' value='436283' \/><input type='hidden' id='answerType436283' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436283[]' id='answer-id-1688265' class='answer   answerof-436283 ' value='1688265'   \/><label for='answer-id-1688265' id='answer-label-1688265' class=' answer'><span>Decrease the batch size.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436283[]' id='answer-id-1688266' class='answer   answerof-436283 ' value='1688266'   \/><label for='answer-id-1688266' id='answer-label-1688266' class=' answer'><span>Increase the epochs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436283[]' id='answer-id-1688267' class='answer   answerof-436283 ' value='1688267'   \/><label for='answer-id-1688267' id='answer-label-1688267' class=' answer'><span>Decrease the epochs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436283[]' id='answer-id-1688268' class='answer   answerof-436283 ' value='1688268'   \/><label for='answer-id-1688268' id='answer-label-1688268' class=' answer'><span>Increase the temperature parameter.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-436284'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>What does an F1 score measure in the context of foundation model (FM) performance?<\/div><input type='hidden' name='question_id[]' id='qID_2' value='436284' \/><input type='hidden' id='answerType436284' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436284[]' id='answer-id-1688269' class='answer   answerof-436284 ' value='1688269'   \/><label for='answer-id-1688269' id='answer-label-1688269' class=' answer'><span>Model precision and recall.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436284[]' id='answer-id-1688270' class='answer   answerof-436284 ' value='1688270'   \/><label for='answer-id-1688270' id='answer-label-1688270' class=' answer'><span>Model speed in generating responses.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436284[]' id='answer-id-1688271' class='answer   answerof-436284 ' value='1688271'   \/><label for='answer-id-1688271' id='answer-label-1688271' class=' answer'><span>Financial cost of operating the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436284[]' id='answer-id-1688272' class='answer   answerof-436284 ' value='1688272'   \/><label for='answer-id-1688272' id='answer-label-1688272' class=' answer'><span>Energy efficiency of the model's computations.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-436285'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>A company is using a pre-trained large language model (LLM) to build a chatbot for product recommendations. The company needs the LLM outputs to be short and written in a specific language. <br \/>\r<br>Which solution will align the LLM response quality with the company's expectations?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='436285' \/><input type='hidden' id='answerType436285' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436285[]' id='answer-id-1688273' class='answer   answerof-436285 ' value='1688273'   \/><label for='answer-id-1688273' id='answer-label-1688273' class=' answer'><span>Adjust the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436285[]' id='answer-id-1688274' class='answer   answerof-436285 ' value='1688274'   \/><label for='answer-id-1688274' id='answer-label-1688274' class=' answer'><span>Choose an LLM of a different size.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436285[]' id='answer-id-1688275' class='answer   answerof-436285 ' value='1688275'   \/><label for='answer-id-1688275' id='answer-label-1688275' class=' answer'><span>Increase the temperature.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436285[]' id='answer-id-1688276' class='answer   answerof-436285 ' value='1688276'   \/><label for='answer-id-1688276' id='answer-label-1688276' class=' answer'><span>Increase the Top K value.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-436286'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/span>A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. <br \/>\r<br>The company wants to classify the sentiment of text passages as positive or negative. <br \/>\r<br>Which prompt engineering strategy meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_4' value='436286' \/><input type='hidden' id='answerType436286' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436286[]' id='answer-id-1688277' class='answer   answerof-436286 ' value='1688277'   \/><label for='answer-id-1688277' id='answer-label-1688277' class=' answer'><span>Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436286[]' id='answer-id-1688278' class='answer   answerof-436286 ' value='1688278'   \/><label for='answer-id-1688278' id='answer-label-1688278' class=' answer'><span>Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436286[]' id='answer-id-1688279' class='answer   answerof-436286 ' value='1688279'   \/><label for='answer-id-1688279' id='answer-label-1688279' class=' answer'><span>Provide the new text passage to be classified without any additional context or examples.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436286[]' id='answer-id-1688280' class='answer   answerof-436286 ' value='1688280'   \/><label for='answer-id-1688280' id='answer-label-1688280' class=' answer'><span>Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-436287'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately. <br \/>\r<br>Which Amazon SageMaker inference option will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_5' value='436287' \/><input type='hidden' id='answerType436287' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436287[]' id='answer-id-1688281' class='answer   answerof-436287 ' value='1688281'   \/><label for='answer-id-1688281' id='answer-label-1688281' class=' answer'><span>Batch transform<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436287[]' id='answer-id-1688282' class='answer   answerof-436287 ' value='1688282'   \/><label for='answer-id-1688282' id='answer-label-1688282' class=' answer'><span>Real-time inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436287[]' id='answer-id-1688283' class='answer   answerof-436287 ' value='1688283'   \/><label for='answer-id-1688283' id='answer-label-1688283' class=' answer'><span>Serverless inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436287[]' id='answer-id-1688284' class='answer   answerof-436287 ' value='1688284'   \/><label for='answer-id-1688284' id='answer-label-1688284' class=' answer'><span>Asynchronous inference<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-436288'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/span>Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?<\/div><input type='hidden' name='question_id[]' id='qID_6' value='436288' \/><input type='hidden' id='answerType436288' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436288[]' id='answer-id-1688285' class='answer   answerof-436288 ' value='1688285'   \/><label for='answer-id-1688285' id='answer-label-1688285' class=' answer'><span>Embeddings<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436288[]' id='answer-id-1688286' class='answer   answerof-436288 ' value='1688286'   \/><label for='answer-id-1688286' id='answer-label-1688286' class=' answer'><span>Tokens<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436288[]' id='answer-id-1688287' class='answer   answerof-436288 ' value='1688287'   \/><label for='answer-id-1688287' id='answer-label-1688287' class=' answer'><span>Models<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436288[]' id='answer-id-1688288' class='answer   answerof-436288 ' value='1688288'   \/><label for='answer-id-1688288' id='answer-label-1688288' class=' answer'><span>Binaries<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-7' style=';'><div id='questionWrap-7'  class='   watupro-question-id-436289'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>A company needs to train an ML model to classify images of different types of animals. The company has a large dataset of labeled images and will not label more data. <br \/>\r<br>Which type of learning should the company use to train the model?<\/div><input type='hidden' name='question_id[]' id='qID_7' value='436289' \/><input type='hidden' id='answerType436289' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436289[]' id='answer-id-1688289' class='answer   answerof-436289 ' value='1688289'   \/><label for='answer-id-1688289' id='answer-label-1688289' class=' answer'><span>Supervised learning.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436289[]' id='answer-id-1688290' class='answer   answerof-436289 ' value='1688290'   \/><label for='answer-id-1688290' id='answer-label-1688290' class=' answer'><span>Unsupervised learning.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436289[]' id='answer-id-1688291' class='answer   answerof-436289 ' value='1688291'   \/><label for='answer-id-1688291' id='answer-label-1688291' class=' answer'><span>Reinforcement learning.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436289[]' id='answer-id-1688292' class='answer   answerof-436289 ' value='1688292'   \/><label for='answer-id-1688292' id='answer-label-1688292' class=' answer'><span>Active learning.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-436290'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>Which AWS feature records details about ML instance data for governance and reporting?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='436290' \/><input type='hidden' id='answerType436290' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436290[]' id='answer-id-1688293' class='answer   answerof-436290 ' value='1688293'   \/><label for='answer-id-1688293' id='answer-label-1688293' class=' answer'><span>Amazon SageMaker Model Cards<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436290[]' id='answer-id-1688294' class='answer   answerof-436290 ' value='1688294'   \/><label for='answer-id-1688294' id='answer-label-1688294' class=' answer'><span>Amazon SageMaker Debugger<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436290[]' id='answer-id-1688295' class='answer   answerof-436290 ' value='1688295'   \/><label for='answer-id-1688295' id='answer-label-1688295' class=' answer'><span>Amazon SageMaker Model Monitor<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436290[]' id='answer-id-1688296' class='answer   answerof-436290 ' value='1688296'   \/><label for='answer-id-1688296' id='answer-label-1688296' class=' answer'><span>Amazon SageMaker JumpStart<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-436291'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/span>A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.<br \/>\r\n<br \/>\r\nWhich solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_9' value='436291' \/><input type='hidden' id='answerType436291' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436291[]' id='answer-id-1688297' class='answer   answerof-436291 ' value='1688297'   \/><label for='answer-id-1688297' id='answer-label-1688297' class=' answer'><span>Optimize the model's architecture and hyperparameters to improve the model's overall performance.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436291[]' id='answer-id-1700111' class='answer   answerof-436291 ' value='1700111'   \/><label for='answer-id-1700111' id='answer-label-1700111' class=' answer'><span>Increase the model's complexity by adding more layers to the model's architecture.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436291[]' id='answer-id-1700112' class='answer   answerof-436291 ' value='1700112'   \/><label for='answer-id-1700112' id='answer-label-1700112' class=' answer'><span>Create effective prompts that provide clear instructions and context to guide the model's generation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436291[]' id='answer-id-1700113' class='answer   answerof-436291 ' value='1700113'   \/><label for='answer-id-1700113' id='answer-label-1700113' class=' answer'><span>Select a large, diverse dataset to pre-train a new generative model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-10' style=';'><div id='questionWrap-10'  class='   watupro-question-id-436292'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_10' value='436292' \/><input type='hidden' id='answerType436292' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436292[]' id='answer-id-1688298' class='answer   answerof-436292 ' value='1688298'   \/><label for='answer-id-1688298' id='answer-label-1688298' class=' answer'><span>Deploy optimized small language models (SLMs) on edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436292[]' id='answer-id-1688299' class='answer   answerof-436292 ' value='1688299'   \/><label for='answer-id-1688299' id='answer-label-1688299' class=' answer'><span>Deploy optimized large language models (LLMs) on edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436292[]' id='answer-id-1688300' class='answer   answerof-436292 ' value='1688300'   \/><label for='answer-id-1688300' id='answer-label-1688300' class=' answer'><span>Incorporate a centralized small language model (SLM) API for asynchronous communication with edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436292[]' id='answer-id-1688301' class='answer   answerof-436292 ' value='1688301'   \/><label for='answer-id-1688301' id='answer-label-1688301' class=' answer'><span>Incorporate a centralized large language model (LLM) API for asynchronous communication with edge devices.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-436293'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/span>A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. <br \/>\r<br>The company needs the LLM to produce more consistent responses to the same input prompt. <br \/>\r<br>Which adjustment to an inference parameter should the company make to meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_11' value='436293' \/><input type='hidden' id='answerType436293' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436293[]' id='answer-id-1688302' class='answer   answerof-436293 ' value='1688302'   \/><label for='answer-id-1688302' id='answer-label-1688302' class=' answer'><span>Decrease the temperature value<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436293[]' id='answer-id-1688303' class='answer   answerof-436293 ' value='1688303'   \/><label for='answer-id-1688303' id='answer-label-1688303' class=' answer'><span>Increase the temperature value<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436293[]' id='answer-id-1688304' class='answer   answerof-436293 ' value='1688304'   \/><label for='answer-id-1688304' id='answer-label-1688304' class=' answer'><span>Decrease the length of output tokens<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436293[]' id='answer-id-1688305' class='answer   answerof-436293 ' value='1688305'   \/><label for='answer-id-1688305' id='answer-label-1688305' class=' answer'><span>Increase the maximum generation length<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-12' style=';'><div id='questionWrap-12'  class='   watupro-question-id-436294'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.<br \/>\r\n<br \/>\r\nWhich solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_12' value='436294' \/><input type='hidden' id='answerType436294' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436294[]' id='answer-id-1688306' class='answer   answerof-436294 ' value='1688306'   \/><label for='answer-id-1688306' id='answer-label-1688306' class=' answer'><span>Customize the model by using fine-tuning.\r\n<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436294[]' id='answer-id-1700114' class='answer   answerof-436294 ' value='1700114'   \/><label for='answer-id-1700114' id='answer-label-1700114' class=' answer'><span>Decrease the number of tokens in the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436294[]' id='answer-id-1700115' class='answer   answerof-436294 ' value='1700115'   \/><label for='answer-id-1700115' id='answer-label-1700115' class=' answer'><span>Increase the number of tokens in the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436294[]' id='answer-id-1700116' class='answer   answerof-436294 ' value='1700116'   \/><label for='answer-id-1700116' id='answer-label-1700116' class=' answer'><span>Use Provisioned Throughput.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-436295'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>A company's large language model (LLM) is experiencing hallucinations. <br \/>\r<br>How can the company decrease hallucinations?<\/div><input type='hidden' name='question_id[]' id='qID_13' value='436295' \/><input type='hidden' id='answerType436295' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436295[]' id='answer-id-1688307' class='answer   answerof-436295 ' value='1688307'   \/><label for='answer-id-1688307' id='answer-label-1688307' class=' answer'><span>Set up Agents for Amazon Bedrock to supervise the model training.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436295[]' id='answer-id-1688308' class='answer   answerof-436295 ' value='1688308'   \/><label for='answer-id-1688308' id='answer-label-1688308' class=' answer'><span>Use data pre-processing and remove any data that causes hallucinations.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436295[]' id='answer-id-1688309' class='answer   answerof-436295 ' value='1688309'   \/><label for='answer-id-1688309' id='answer-label-1688309' class=' answer'><span>Decrease the temperature inference parameter for the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436295[]' id='answer-id-1688310' class='answer   answerof-436295 ' value='1688310'   \/><label for='answer-id-1688310' id='answer-label-1688310' class=' answer'><span>Use a foundation model (FM) that is trained to not hallucinate.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-436296'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>A company built an AI-powered resume screening system. The company used a large dataset to train the model. The dataset contained resumes that were not representative of all demographics. <br \/>\r<br>Which core dimension of responsible AI does this scenario present?<\/div><input type='hidden' name='question_id[]' id='qID_14' value='436296' \/><input type='hidden' id='answerType436296' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436296[]' id='answer-id-1688311' class='answer   answerof-436296 ' value='1688311'   \/><label for='answer-id-1688311' id='answer-label-1688311' class=' answer'><span>Fairness.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436296[]' id='answer-id-1688312' class='answer   answerof-436296 ' value='1688312'   \/><label for='answer-id-1688312' id='answer-label-1688312' class=' answer'><span>Explainability.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436296[]' id='answer-id-1688313' class='answer   answerof-436296 ' value='1688313'   \/><label for='answer-id-1688313' id='answer-label-1688313' class=' answer'><span>Privacy and security.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436296[]' id='answer-id-1688314' class='answer   answerof-436296 ' value='1688314'   \/><label for='answer-id-1688314' id='answer-label-1688314' class=' answer'><span>Transparency.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-436297'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.<br \/>\r\n<br \/>\r\nWhich solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_15' value='436297' \/><input type='hidden' id='answerType436297' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436297[]' id='answer-id-1688315' class='answer   answerof-436297 ' value='1688315'   \/><label for='answer-id-1688315' id='answer-label-1688315' class=' answer'><span>Configure the security and compliance by using Amazon Inspector.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436297[]' id='answer-id-1700117' class='answer   answerof-436297 ' value='1700117'   \/><label for='answer-id-1700117' id='answer-label-1700117' class=' answer'><span>Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436297[]' id='answer-id-1700118' class='answer   answerof-436297 ' value='1700118'   \/><label for='answer-id-1700118' id='answer-label-1700118' class=' answer'><span>Encrypt and secure training data by using Amazon Macie.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436297[]' id='answer-id-1700119' class='answer   answerof-436297 ' value='1700119'   \/><label for='answer-id-1700119' id='answer-label-1700119' class=' answer'><span>Gather more data. Use Amazon Rekognition to add custom labels to the data.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-436298'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/span>A company needs to build its own large language model (LLM) based on only the company's private data. The company is concerned about the environmental effect of the training process. <br \/>\r<br>Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?<\/div><input type='hidden' name='question_id[]' id='qID_16' value='436298' \/><input type='hidden' id='answerType436298' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436298[]' id='answer-id-1688316' class='answer   answerof-436298 ' value='1688316'   \/><label for='answer-id-1688316' id='answer-label-1688316' class=' answer'><span>Amazon EC2 C series<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436298[]' id='answer-id-1688317' class='answer   answerof-436298 ' value='1688317'   \/><label for='answer-id-1688317' id='answer-label-1688317' class=' answer'><span>Amazon EC2 G series<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436298[]' id='answer-id-1688318' class='answer   answerof-436298 ' value='1688318'   \/><label for='answer-id-1688318' id='answer-label-1688318' class=' answer'><span>Amazon EC2 P series<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436298[]' id='answer-id-1688319' class='answer   answerof-436298 ' value='1688319'   \/><label for='answer-id-1688319' id='answer-label-1688319' class=' answer'><span>Amazon EC2 Trn series<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-436299'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>What are tokens in the context of generative AI models?<\/div><input type='hidden' name='question_id[]' id='qID_17' value='436299' \/><input type='hidden' id='answerType436299' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436299[]' id='answer-id-1688320' class='answer   answerof-436299 ' value='1688320'   \/><label for='answer-id-1688320' id='answer-label-1688320' class=' answer'><span>Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436299[]' id='answer-id-1688321' class='answer   answerof-436299 ' value='1688321'   \/><label for='answer-id-1688321' id='answer-label-1688321' class=' answer'><span>Tokens are the mathematical representations of words or concepts used in generative AI models.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436299[]' id='answer-id-1688322' class='answer   answerof-436299 ' value='1688322'   \/><label for='answer-id-1688322' id='answer-label-1688322' class=' answer'><span>Tokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436299[]' id='answer-id-1688323' class='answer   answerof-436299 ' value='1688323'   \/><label for='answer-id-1688323' id='answer-label-1688323' class=' answer'><span>Tokens are the specific prompts or instructions given to a generative AI model to generate output.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-436300'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.<br \/>\r\n<br \/>\r\nWhich business objective should the company use to evaluate the effect of the LLM chatbot?<\/div><input type='hidden' name='question_id[]' id='qID_18' value='436300' \/><input type='hidden' id='answerType436300' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436300[]' id='answer-id-1688324' class='answer   answerof-436300 ' value='1688324'   \/><label for='answer-id-1688324' id='answer-label-1688324' class=' answer'><span>Website engagement rate<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436300[]' id='answer-id-1700120' class='answer   answerof-436300 ' value='1700120'   \/><label for='answer-id-1700120' id='answer-label-1700120' class=' answer'><span>Average call duration<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436300[]' id='answer-id-1700121' class='answer   answerof-436300 ' value='1700121'   \/><label for='answer-id-1700121' id='answer-label-1700121' class=' answer'><span>Corporate social responsibility<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436300[]' id='answer-id-1700122' class='answer   answerof-436300 ' value='1700122'   \/><label for='answer-id-1700122' id='answer-label-1700122' class=' answer'><span>Regulatory compliance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-436301'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team's VPC?<\/div><input type='hidden' name='question_id[]' id='qID_19' value='436301' \/><input type='hidden' id='answerType436301' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436301[]' id='answer-id-1688325' class='answer   answerof-436301 ' value='1688325'   \/><label for='answer-id-1688325' id='answer-label-1688325' class=' answer'><span>Amazon Personalize<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436301[]' id='answer-id-1700123' class='answer   answerof-436301 ' value='1700123'   \/><label for='answer-id-1700123' id='answer-label-1700123' class=' answer'><span>Amazon SageMaker JumpStart<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436301[]' id='answer-id-1700124' class='answer   answerof-436301 ' value='1700124'   \/><label for='answer-id-1700124' id='answer-label-1700124' class=' answer'><span>PartyRock, an Amazon Bedrock Playground<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436301[]' id='answer-id-1700125' class='answer   answerof-436301 ' value='1700125'   \/><label for='answer-id-1700125' id='answer-label-1700125' class=' answer'><span>Amazon SageMaker endpoints<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-436302'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology. <br \/>\r<br>Which solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_20' value='436302' \/><input type='hidden' id='answerType436302' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436302[]' id='answer-id-1688326' class='answer   answerof-436302 ' value='1688326'   \/><label for='answer-id-1688326' id='answer-label-1688326' class=' answer'><span>Generative pre-trained transformers (GPT)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436302[]' id='answer-id-1688327' class='answer   answerof-436302 ' value='1688327'   \/><label for='answer-id-1688327' id='answer-label-1688327' class=' answer'><span>Residual neural network<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436302[]' id='answer-id-1688328' class='answer   answerof-436302 ' value='1688328'   \/><label for='answer-id-1688328' id='answer-label-1688328' class=' answer'><span>Support vector machine<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436302[]' id='answer-id-1688329' class='answer   answerof-436302 ' value='1688329'   \/><label for='answer-id-1688329' id='answer-label-1688329' class=' answer'><span>WaveNet<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-21' style=';'><div id='questionWrap-21'  class='   watupro-question-id-436303'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/span>Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?<\/div><input type='hidden' name='question_id[]' id='qID_21' value='436303' \/><input type='hidden' id='answerType436303' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436303[]' id='answer-id-1688330' class='answer   answerof-436303 ' value='1688330'   \/><label for='answer-id-1688330' id='answer-label-1688330' class=' answer'><span>Calculate the total cost of resources used by the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436303[]' id='answer-id-1700126' class='answer   answerof-436303 ' value='1700126'   \/><label for='answer-id-1700126' id='answer-label-1700126' class=' answer'><span>Measure the model's accuracy against a predefined benchmark dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436303[]' id='answer-id-1700127' class='answer   answerof-436303 ' value='1700127'   \/><label for='answer-id-1700127' id='answer-label-1700127' class=' answer'><span>Count the number of layers in the neural network.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436303[]' id='answer-id-1700128' class='answer   answerof-436303 ' value='1700128'   \/><label for='answer-id-1700128' id='answer-label-1700128' class=' answer'><span>Assess the color accuracy of images processed by the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-436304'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>A company has a database of petabytes of unstructured data from internal sources. The company wants to transform this data into a structured format so that its data scientists can perform machine learning (ML) tasks.<br \/>\r\n<br \/>\r\nWhich service will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_22' value='436304' \/><input type='hidden' id='answerType436304' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436304[]' id='answer-id-1688331' class='answer   answerof-436304 ' value='1688331'   \/><label for='answer-id-1688331' id='answer-label-1688331' class=' answer'><span>Amazon Lex<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436304[]' id='answer-id-1700129' class='answer   answerof-436304 ' value='1700129'   \/><label for='answer-id-1700129' id='answer-label-1700129' class=' answer'><span>Amazon Rekognition<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436304[]' id='answer-id-1700130' class='answer   answerof-436304 ' value='1700130'   \/><label for='answer-id-1700130' id='answer-label-1700130' class=' answer'><span>Amazon Kinesis Data Streams<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436304[]' id='answer-id-1700131' class='answer   answerof-436304 ' value='1700131'   \/><label for='answer-id-1700131' id='answer-label-1700131' class=' answer'><span>AWS Glue<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-436305'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.<br \/>\r\n<br \/>\r\nWhat should the firm do when developing and deploying the LLM? (Select TWO.)<\/div><input type='hidden' name='question_id[]' id='qID_23' value='436305' \/><input type='hidden' id='answerType436305' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-436305[]' id='answer-id-1688332' class='answer   answerof-436305 ' value='1688332'   \/><label for='answer-id-1688332' id='answer-label-1688332' class=' answer'><span>Include fairness metrics for model evaluation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-436305[]' id='answer-id-1700132' class='answer   answerof-436305 ' value='1700132'   \/><label for='answer-id-1700132' id='answer-label-1700132' class=' answer'><span>Adjust the temperature parameter of the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-436305[]' id='answer-id-1700133' class='answer   answerof-436305 ' value='1700133'   \/><label for='answer-id-1700133' id='answer-label-1700133' class=' answer'><span>Modify the training data to mitigate bias.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-436305[]' id='answer-id-1700134' class='answer   answerof-436305 ' value='1700134'   \/><label for='answer-id-1700134' id='answer-label-1700134' class=' answer'><span>Avoid overfitting on the training data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-436305[]' id='answer-id-1700135' class='answer   answerof-436305 ' value='1700135'   \/><label for='answer-id-1700135' id='answer-label-1700135' class=' answer'><span>Apply prompt engineering techniques.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-436306'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock. <br \/>\r<br>What are the key benefits of using Amazon Bedrock agents that could help this retailer?<\/div><input type='hidden' name='question_id[]' id='qID_24' value='436306' \/><input type='hidden' id='answerType436306' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436306[]' id='answer-id-1688333' class='answer   answerof-436306 ' value='1688333'   \/><label for='answer-id-1688333' id='answer-label-1688333' class=' answer'><span>Generation of custom foundation models (FMs) to predict customer needs<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436306[]' id='answer-id-1688334' class='answer   answerof-436306 ' value='1688334'   \/><label for='answer-id-1688334' id='answer-label-1688334' class=' answer'><span>Automation of repetitive tasks and orchestration of complex workflows<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436306[]' id='answer-id-1688335' class='answer   answerof-436306 ' value='1688335'   \/><label for='answer-id-1688335' id='answer-label-1688335' class=' answer'><span>Automatically calling multiple foundation models (FMs) and consolidating the results<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436306[]' id='answer-id-1688336' class='answer   answerof-436306 ' value='1688336'   \/><label for='answer-id-1688336' id='answer-label-1688336' class=' answer'><span>Selecting the foundation model (FM) based on predefined criteria and metrics<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-436307'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>A company is building a contact center application and wants to gain insights from customer conversations. The company wants to analyze and extract key information from the audio of the customer calls.<br \/>\r\n<br \/>\r\nWhich solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_25' value='436307' \/><input type='hidden' id='answerType436307' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436307[]' id='answer-id-1688337' class='answer   answerof-436307 ' value='1688337'   \/><label for='answer-id-1688337' id='answer-label-1688337' class=' answer'><span>Build a conversational chatbot by using Amazon Lex.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436307[]' id='answer-id-1700136' class='answer   answerof-436307 ' value='1700136'   \/><label for='answer-id-1700136' id='answer-label-1700136' class=' answer'><span>Transcribe call recordings by using Amazon Transcribe.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436307[]' id='answer-id-1700137' class='answer   answerof-436307 ' value='1700137'   \/><label for='answer-id-1700137' id='answer-label-1700137' class=' answer'><span>Extract information from call recordings by using Amazon SageMaker Model Monitor.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436307[]' id='answer-id-1700138' class='answer   answerof-436307 ' value='1700138'   \/><label for='answer-id-1700138' id='answer-label-1700138' class=' answer'><span>Create classification labels by using Amazon Comprehend.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-436308'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_26' value='436308' \/><input type='hidden' id='answerType436308' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436308[]' id='answer-id-1688338' class='answer   answerof-436308 ' value='1688338'   \/><label for='answer-id-1688338' id='answer-label-1688338' class=' answer'><span>Implement moderation APIs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436308[]' id='answer-id-1688339' class='answer   answerof-436308 ' value='1688339'   \/><label for='answer-id-1688339' id='answer-label-1688339' class=' answer'><span>Retrain the model with a general public dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436308[]' id='answer-id-1688340' class='answer   answerof-436308 ' value='1688340'   \/><label for='answer-id-1688340' id='answer-label-1688340' class=' answer'><span>Perform model validation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436308[]' id='answer-id-1688341' class='answer   answerof-436308 ' value='1688341'   \/><label for='answer-id-1688341' id='answer-label-1688341' class=' answer'><span>Automate user feedback integration.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-436309'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>A retail store wants to predict the demand for a specific product for the next few weeks by using the Amazon SageMaker DeepAR forecasting algorithm. <br \/>\r<br>Which type of data will meet this requirement?<\/div><input type='hidden' name='question_id[]' id='qID_27' value='436309' \/><input type='hidden' id='answerType436309' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436309[]' id='answer-id-1688342' class='answer   answerof-436309 ' value='1688342'   \/><label for='answer-id-1688342' id='answer-label-1688342' class=' answer'><span>Text data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436309[]' id='answer-id-1688343' class='answer   answerof-436309 ' value='1688343'   \/><label for='answer-id-1688343' id='answer-label-1688343' class=' answer'><span>Image data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436309[]' id='answer-id-1688344' class='answer   answerof-436309 ' value='1688344'   \/><label for='answer-id-1688344' id='answer-label-1688344' class=' answer'><span>Time series data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436309[]' id='answer-id-1688345' class='answer   answerof-436309 ' value='1688345'   \/><label for='answer-id-1688345' id='answer-label-1688345' class=' answer'><span>Binary data<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-436310'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/span>A company has installed a security camera. The company uses an ML model to evaluate the security camera footage for potential thefts. The company has discovered that the model disproportionately flags people who are members of a specific ethnic group.<br \/>\r\n<br \/>\r\nWhich type of bias is affecting the model output?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='436310' \/><input type='hidden' id='answerType436310' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436310[]' id='answer-id-1688346' class='answer   answerof-436310 ' value='1688346'   \/><label for='answer-id-1688346' id='answer-label-1688346' class=' answer'><span>Measurement bias\r\n<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436310[]' id='answer-id-1700139' class='answer   answerof-436310 ' value='1700139'   \/><label for='answer-id-1700139' id='answer-label-1700139' class=' answer'><span>Sampling bias<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436310[]' id='answer-id-1700140' class='answer   answerof-436310 ' value='1700140'   \/><label for='answer-id-1700140' id='answer-label-1700140' class=' answer'><span>Observer bias<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436310[]' id='answer-id-1700141' class='answer   answerof-436310 ' value='1700141'   \/><label for='answer-id-1700141' id='answer-label-1700141' class=' answer'><span>Confirmation bias<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-29' style=';'><div id='questionWrap-29'  class='   watupro-question-id-436311'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>A company is building an application that needs to generate synthetic data that is based on existing data. <br \/>\r<br>Which type of model can the company use to meet this requirement?<\/div><input type='hidden' name='question_id[]' id='qID_29' value='436311' \/><input type='hidden' id='answerType436311' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436311[]' id='answer-id-1688347' class='answer   answerof-436311 ' value='1688347'   \/><label for='answer-id-1688347' id='answer-label-1688347' class=' answer'><span>Generative adversarial network (GAN)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436311[]' id='answer-id-1688348' class='answer   answerof-436311 ' value='1688348'   \/><label for='answer-id-1688348' id='answer-label-1688348' class=' answer'><span>XGBoost<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436311[]' id='answer-id-1688349' class='answer   answerof-436311 ' value='1688349'   \/><label for='answer-id-1688349' id='answer-label-1688349' class=' answer'><span>Residual neural network<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436311[]' id='answer-id-1688350' class='answer   answerof-436311 ' value='1688350'   \/><label for='answer-id-1688350' id='answer-label-1688350' class=' answer'><span>WaveNet<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-436312'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly. <br \/>\r<br>What should the company do to mitigate this problem?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='436312' \/><input type='hidden' id='answerType436312' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436312[]' id='answer-id-1688351' class='answer   answerof-436312 ' value='1688351'   \/><label for='answer-id-1688351' id='answer-label-1688351' class=' answer'><span>Reduce the volume of data that is used in training.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436312[]' id='answer-id-1688352' class='answer   answerof-436312 ' value='1688352'   \/><label for='answer-id-1688352' id='answer-label-1688352' class=' answer'><span>Add hyperparameters to the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436312[]' id='answer-id-1688353' class='answer   answerof-436312 ' value='1688353'   \/><label for='answer-id-1688353' id='answer-label-1688353' class=' answer'><span>Increase the volume of data that is used in training.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436312[]' id='answer-id-1688354' class='answer   answerof-436312 ' value='1688354'   \/><label for='answer-id-1688354' id='answer-label-1688354' class=' answer'><span>Increase the model training time.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-31' style=';'><div id='questionWrap-31'  class='   watupro-question-id-436313'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/span>A company is using a pre-trained large language model (LLM) to extract information from <br \/>\r<br>documents. The company noticed that a newer LLM from a different provider is available on Amazon Bedrock. The company wants to transition to the new LLM on Amazon Bedrock. <br \/>\r<br>What does the company need to do to transition to the new LLM?<\/div><input type='hidden' name='question_id[]' id='qID_31' value='436313' \/><input type='hidden' id='answerType436313' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436313[]' id='answer-id-1688355' class='answer   answerof-436313 ' value='1688355'   \/><label for='answer-id-1688355' id='answer-label-1688355' class=' answer'><span>Create a new labeled dataset<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436313[]' id='answer-id-1688356' class='answer   answerof-436313 ' value='1688356'   \/><label for='answer-id-1688356' id='answer-label-1688356' class=' answer'><span>Perform feature engineering.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436313[]' id='answer-id-1688357' class='answer   answerof-436313 ' value='1688357'   \/><label for='answer-id-1688357' id='answer-label-1688357' class=' answer'><span>Adjust the prompt template.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436313[]' id='answer-id-1688358' class='answer   answerof-436313 ' value='1688358'   \/><label for='answer-id-1688358' id='answer-label-1688358' class=' answer'><span>Fine-tune the LL<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-32' style=';'><div id='questionWrap-32'  class='   watupro-question-id-436314'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>How can companies use large language models (LLMs) securely on Amazon Bedrock?<\/div><input type='hidden' name='question_id[]' id='qID_32' value='436314' \/><input type='hidden' id='answerType436314' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436314[]' id='answer-id-1688359' class='answer   answerof-436314 ' value='1688359'   \/><label for='answer-id-1688359' id='answer-label-1688359' class=' answer'><span>Design clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436314[]' id='answer-id-1688360' class='answer   answerof-436314 ' value='1688360'   \/><label for='answer-id-1688360' id='answer-label-1688360' class=' answer'><span>Enable AWS Audit Manager for automatic model evaluation jobs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436314[]' id='answer-id-1688361' class='answer   answerof-436314 ' value='1688361'   \/><label for='answer-id-1688361' id='answer-label-1688361' class=' answer'><span>Enable Amazon Bedrock automatic model evaluation jobs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436314[]' id='answer-id-1688362' class='answer   answerof-436314 ' value='1688362'   \/><label for='answer-id-1688362' id='answer-label-1688362' class=' answer'><span>Use Amazon CloudWatch Logs to make models explainable and to monitor for bias.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-33' style=';'><div id='questionWrap-33'  class='   watupro-question-id-436315'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information. <br \/>\r<br>Which action will reduce these risks?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='436315' \/><input type='hidden' id='answerType436315' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436315[]' id='answer-id-1688363' class='answer   answerof-436315 ' value='1688363'   \/><label for='answer-id-1688363' id='answer-label-1688363' class=' answer'><span>Create a prompt template that teaches the LLM to detect attack patterns.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436315[]' id='answer-id-1688364' class='answer   answerof-436315 ' value='1688364'   \/><label for='answer-id-1688364' id='answer-label-1688364' class=' answer'><span>Increase the temperature parameter on invocation requests to the LL<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436315[]' id='answer-id-1688365' class='answer   answerof-436315 ' value='1688365'   \/><label for='answer-id-1688365' id='answer-label-1688365' class=' answer'><span>Avoid using LLMs that are not listed in Amazon SageMaker.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436315[]' id='answer-id-1688366' class='answer   answerof-436315 ' value='1688366'   \/><label for='answer-id-1688366' id='answer-label-1688366' class=' answer'><span>Decrease the number of input tokens on invocations of the LL<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-34' style=';'><div id='questionWrap-34'  class='   watupro-question-id-436316'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment. <br \/>\r<br>Which Amazon Bedrock pricing model meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_34' value='436316' \/><input type='hidden' id='answerType436316' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436316[]' id='answer-id-1688367' class='answer   answerof-436316 ' value='1688367'   \/><label for='answer-id-1688367' id='answer-label-1688367' class=' answer'><span>On-Demand<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436316[]' id='answer-id-1688368' class='answer   answerof-436316 ' value='1688368'   \/><label for='answer-id-1688368' id='answer-label-1688368' class=' answer'><span>Model customization<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436316[]' id='answer-id-1688369' class='answer   answerof-436316 ' value='1688369'   \/><label for='answer-id-1688369' id='answer-label-1688369' class=' answer'><span>Provisioned Throughput<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436316[]' id='answer-id-1688370' class='answer   answerof-436316 ' value='1688370'   \/><label for='answer-id-1688370' id='answer-label-1688370' class=' answer'><span>Spot Instance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-35' style=';'><div id='questionWrap-35'  class='   watupro-question-id-436317'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>A customer service team is developing an application to analyze customer feedback and automatically classify the feedback into different categories. The categories include product quality, customer service, and delivery experience. <br \/>\r<br>Which AI concept does this scenario present?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='436317' \/><input type='hidden' id='answerType436317' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436317[]' id='answer-id-1688371' class='answer   answerof-436317 ' value='1688371'   \/><label for='answer-id-1688371' id='answer-label-1688371' class=' answer'><span>Computer vision<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436317[]' id='answer-id-1688372' class='answer   answerof-436317 ' value='1688372'   \/><label for='answer-id-1688372' id='answer-label-1688372' class=' answer'><span>Natural language processing (NLP)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436317[]' id='answer-id-1688373' class='answer   answerof-436317 ' value='1688373'   \/><label for='answer-id-1688373' id='answer-label-1688373' class=' answer'><span>Recommendation systems<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436317[]' id='answer-id-1688374' class='answer   answerof-436317 ' value='1688374'   \/><label for='answer-id-1688374' id='answer-label-1688374' class=' answer'><span>Fraud detection<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-36' style=';'><div id='questionWrap-36'  class='   watupro-question-id-436318'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/span>1.An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data. <br \/>\r<br>How should the AI practitioner prevent responses based on confidential data?<\/div><input type='hidden' name='question_id[]' id='qID_36' value='436318' \/><input type='hidden' id='answerType436318' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436318[]' id='answer-id-1688375' class='answer   answerof-436318 ' value='1688375'   \/><label for='answer-id-1688375' id='answer-label-1688375' class=' answer'><span>Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436318[]' id='answer-id-1688376' class='answer   answerof-436318 ' value='1688376'   \/><label for='answer-id-1688376' id='answer-label-1688376' class=' answer'><span>Mask the confidential data in the inference responses by using dynamic data masking.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436318[]' id='answer-id-1688377' class='answer   answerof-436318 ' value='1688377'   \/><label for='answer-id-1688377' id='answer-label-1688377' class=' answer'><span>Encrypt the confidential data in the inference responses by using Amazon SageMaker.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436318[]' id='answer-id-1688378' class='answer   answerof-436318 ' value='1688378'   \/><label for='answer-id-1688378' id='answer-label-1688378' class=' answer'><span>Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-37' style=';'><div id='questionWrap-37'  class='   watupro-question-id-436319'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>A company wants to use generative AI to increase developer productivity and software development. <br \/>\r<br>The company wants to use Amazon Q Developer. <br \/>\r<br>What can Amazon Q Developer do to help the company meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_37' value='436319' \/><input type='hidden' id='answerType436319' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436319[]' id='answer-id-1688379' class='answer   answerof-436319 ' value='1688379'   \/><label for='answer-id-1688379' id='answer-label-1688379' class=' answer'><span>Create software snippets, reference tracking, and open-source license tracking.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436319[]' id='answer-id-1688380' class='answer   answerof-436319 ' value='1688380'   \/><label for='answer-id-1688380' id='answer-label-1688380' class=' answer'><span>Run an application without provisioning or managing servers.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436319[]' id='answer-id-1688381' class='answer   answerof-436319 ' value='1688381'   \/><label for='answer-id-1688381' id='answer-label-1688381' class=' answer'><span>Enable voice commands for coding and providing natural language search.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436319[]' id='answer-id-1688382' class='answer   answerof-436319 ' value='1688382'   \/><label for='answer-id-1688382' id='answer-label-1688382' class=' answer'><span>Convert audio files to text documents by using ML models.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-38' style=';'><div id='questionWrap-38'  class='   watupro-question-id-436320'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>An AI practitioner is using a large language model (LLM) to create content for marketing campaigns. <br \/>\r<br>The generated content sounds plausible and factual but is incorrect. <br \/>\r<br>Which problem is the LLM having?<\/div><input type='hidden' name='question_id[]' id='qID_38' value='436320' \/><input type='hidden' id='answerType436320' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436320[]' id='answer-id-1688383' class='answer   answerof-436320 ' value='1688383'   \/><label for='answer-id-1688383' id='answer-label-1688383' class=' answer'><span>Data leakage<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436320[]' id='answer-id-1688384' class='answer   answerof-436320 ' value='1688384'   \/><label for='answer-id-1688384' id='answer-label-1688384' class=' answer'><span>Hallucination<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436320[]' id='answer-id-1688385' class='answer   answerof-436320 ' value='1688385'   \/><label for='answer-id-1688385' id='answer-label-1688385' class=' answer'><span>Overfitting<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436320[]' id='answer-id-1688386' class='answer   answerof-436320 ' value='1688386'   \/><label for='answer-id-1688386' id='answer-label-1688386' class=' answer'><span>Underfitting<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-39' style=';'><div id='questionWrap-39'  class='   watupro-question-id-436321'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/span>An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question. <br \/>\r<br>Which solution meets these requirements with the LEAST implementation effort?<\/div><input type='hidden' name='question_id[]' id='qID_39' value='436321' \/><input type='hidden' id='answerType436321' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436321[]' id='answer-id-1688387' class='answer   answerof-436321 ' value='1688387'   \/><label for='answer-id-1688387' id='answer-label-1688387' class=' answer'><span>Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436321[]' id='answer-id-1688388' class='answer   answerof-436321 ' value='1688388'   \/><label for='answer-id-1688388' id='answer-label-1688388' class=' answer'><span>Add a role description to the prompt context that instructs the model of the age range that the response should target.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436321[]' id='answer-id-1688389' class='answer   answerof-436321 ' value='1688389'   \/><label for='answer-id-1688389' id='answer-label-1688389' class=' answer'><span>Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436321[]' id='answer-id-1688390' class='answer   answerof-436321 ' value='1688390'   \/><label for='answer-id-1688390' id='answer-label-1688390' class=' answer'><span>Summarize the response text depending on the age of the user so that younger users receive shorter responses.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-40' style=';'><div id='questionWrap-40'  class='   watupro-question-id-436322'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/span>A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals. <br \/>\r<br>Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?<\/div><input type='hidden' name='question_id[]' id='qID_40' value='436322' \/><input type='hidden' id='answerType436322' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436322[]' id='answer-id-1688391' class='answer   answerof-436322 ' value='1688391'   \/><label for='answer-id-1688391' id='answer-label-1688391' class=' answer'><span>User-generated content<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436322[]' id='answer-id-1688392' class='answer   answerof-436322 ' value='1688392'   \/><label for='answer-id-1688392' id='answer-label-1688392' class=' answer'><span>Moderation logs<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436322[]' id='answer-id-1688393' class='answer   answerof-436322 ' value='1688393'   \/><label for='answer-id-1688393' id='answer-label-1688393' class=' answer'><span>Content moderation guidelines<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-436322[]' id='answer-id-1688394' class='answer   answerof-436322 ' value='1688394'   \/><label for='answer-id-1688394' id='answer-label-1688394' class=' answer'><span>Benchmark datasets<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-41'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons11086\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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   \t \n<\/script>\n<p>&nbsp;<\/p>\n<h3>We also have <span style=\"background-color: #ccffff;\"><a style=\"background-color: #ccffff;\" href=\"https:\/\/www.dumpsbase.com\/freedumps\/get-aif-c01-dumps-v15-02-to-achieve-100-success-continue-to-check-the-aif-c01-free-dumps-part-3-q81-q100.html\"><em>AIF-C01 free dumps (Part 3, Q81-Q100) of V15.02<\/em><\/a><\/span> here for checking more.<\/h3>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Success in the AWS Certified AI Practitioner (AIF-C01) exam requires a reliable learning resource, and the AIF-C01 dumps (V15.02) stand out. 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