{"id":12248,"date":"2024-06-04T10:58:42","date_gmt":"2024-06-04T02:58:42","guid":{"rendered":"https:\/\/www.1ai.net\/?p=12248"},"modified":"2024-06-04T10:58:42","modified_gmt":"2024-06-04T02:58:42","slug":"%e4%ba%9a%e9%a9%ac%e9%80%8a%e6%8e%a8%e5%87%ba%e4%be%a6%e6%8e%a2%e9%a1%b9%e7%9b%ae%ef%bc%9aai-%e7%81%ab%e7%9c%bc%e9%87%91%e7%9d%9b%e7%a1%ae%e4%bf%9d%e5%95%86%e5%93%81%e5%8f%91","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/12248.html","title":{"rendered":"Amazon launches &quot;Detective&quot; project: AI&#039;s sharp eyes ensure that products are flawless before shipment"},"content":{"rendered":"<p data-vmark=\"96b8\">In order to ensure that customers receive satisfactory products,<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e4%ba%9a%e9%a9%ac%e9%80%8a\" title=\"[View articles tagged with [Amazon]]\" target=\"_blank\" >Amazon<\/a>Use your sharp weapon\u2014\u2014&quot;<a href=\"https:\/\/www.1ai.net\/en\/tag\/project-pi\" title=\"[See article with [Project PI] label]\" target=\"_blank\" >Project PI<\/a>\u201d (Detective Project). This combination<a href=\"https:\/\/www.1ai.net\/en\/tag\/%e7%94%9f%e6%88%90%e5%bc%8fai\" title=\"[SEE ARTICLES WITH [GENERATED AI] LABELS]\" target=\"_blank\" >Generative AI<\/a> Systems that use AI and computer vision technology can identify damaged, wrong-color or wrong-size products before they are shipped to customers.<\/p>\n<p data-vmark=\"3cb7\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-12249\" title=\"d624d9f5-3076-407d-8cdd-b2f3ad28bc31\" src=\"https:\/\/www.1ai.net\/wp-content\/uploads\/2024\/06\/d624d9f5-3076-407d-8cdd-b2f3ad28bc31.png\" alt=\"d624d9f5-3076-407d-8cdd-b2f3ad28bc31\" width=\"1199\" height=\"585\" \/><\/p>\n<p data-vmark=\"9e5d\">Here\u2019s how it works: The incoming goods pass through a tunnel equipped with a scanner. A computer vision program (an AI technology that analyzes the content of an image) checks the goods for defects.<span class=\"accentTextColor\">If a problem is found, the system will separate the product.<\/span>, and conduct defect assessment, and check whether similar problems exist in other batches of goods in order to trace the source.<\/p>\n<p data-vmark=\"fa2e\">According to Amazon, Project PI is currently in use in multiple warehouses in the United States and will cover more sites this year. Last year, Amazon also launched another system that can mark frequently returned items to help customers avoid potential problem products before purchasing. These measures are all aimed at avoiding customers from falling into a &quot;nightmare&quot; return process, which is not only beneficial to customers, but also to Amazon itself and the environment (reducing carbon emissions).<\/p>\n<p data-vmark=\"385a\">Amazon said,<span class=\"accentTextColor\">Human reviewers will review the products flagged by Project PI<\/span>, and decide whether to sell it in Amazon&#039;s unique &quot;Second Chance&quot; discount area or donate it to other organizations.<\/p>\n<p data-vmark=\"b417\">Amazon is also working on introducing a multimodal large language model to investigate the causes of customer dissatisfaction. The AI tool will analyze customer feedback and then combine it with images captured by Project PI and other data sources to find out where the problem lies. Amazon said the technology can help other sellers identify whether they accidentally mislabeled items.<\/p>","protected":false},"excerpt":{"rendered":"<p>In order for customers to receive satisfactory goods, Amazon has come up with a powerful tool -- \"Project PI\" (Project Inspector). This system, which combines generative AI and computer vision technology, can identify damaged, wrong color or wrong size products before they are delivered to customers. Here's how it works: the item to be delivered passes through a tunnel equipped with a scanning device. A computer vision program (an AI technology that analyzes the content of the images) checks for defects. If a problem is found, the system separates the item and evaluates it for defects, while checking to see if similar problems exist in other batches of merchandise in order to trace them back to their roots. According to Amazon, Project PI is currently in use in multiple warehouses in the U.S.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[2921,370,383],"collection":[],"class_list":["post-12248","post","type-post","status-publish","format-standard","hentry","category-news","tag-project-pi","tag-370","tag-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/12248","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=12248"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/12248\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=12248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=12248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=12248"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=12248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}