{"id":3085,"date":"2023-07-20T11:45:09","date_gmt":"2023-07-20T03:45:09","guid":{"rendered":"https:\/\/nullthought.net\/?p=3085"},"modified":"2025-11-15T11:46:26","modified_gmt":"2025-11-15T03:46:26","slug":"%e5%85%b3%e4%ba%8e%e8%be%b9%e7%bc%98%e7%ab%afai","status":"publish","type":"post","link":"https:\/\/nullthought.net\/?p=3085","title":{"rendered":"\u5173\u4e8e\u8fb9\u7f18\u7aefAI\uff0cabout Edge AI"},"content":{"rendered":"\n<p>1\u3001\u8fb9\u7f18\u7aefAI\u6a21\u578b\u7684\u90e8\u7f72\u5c06\u4f1a\u8d8a\u6765\u8d8a\u5bb9\u6613\u3002\u8d8a\u6765\u8d8a\u591a\u7684\u5927\u5382\uff0c\u5982\u82af\u7247\u548c\u5de5\u4e1a\u81ea\u52a8\u5316\u5927\u5382\uff0c\u5df2\u7ecf\u6216\u5c06\u4f1a\u63a8\u51fa\u81ea\u5df1\u7684\u8fb9\u7f18\u8bbe\u5907AI\u6a21\u578b\u751f\u6210\u3001\u5904\u7406\u548c\u90e8\u7f72\u5de5\u5177\u3002<a href=\"https:\/\/nullthought.net\/?p=6050\" target=\"_blank\" rel=\"noreferrer noopener\">\u72ec\u7acbEdge AI\u5382\u5546\u5982\u679c\u505a\u5f97\u8fd8\u4e0d\u9519\uff0c\u88ab\u5927\u5382\u6536\u8d2d\u7684\u53ef\u80fd\u6027\u4f1a\u5f88\u5927<\/a>\uff1b<\/p>\n\n\n\n<p>2\u3001\u5c4f\u853d\u8fb9\u7f18\u7aef\u8bbe\u5907\u786c\u4ef6\u67b6\u6784\u5dee\u5f02\uff0c\u8ba9\u6a21\u578b\u5feb\u901f\u9002\u914d\u4e0d\u540c\u67b6\u6784\u8fb9\u7f18\u7aef\u7684\u7f16\u8bd1\u548c\u90e8\u7f72\u5de5\u5177\uff08\u5982<a href=\"https:\/\/nullthought.net\/?p=6511\" target=\"_blank\" rel=\"noreferrer noopener\">Roofline<\/a>\uff09\u5c06\u9646\u7eed\u51fa\u73b0\uff1b<\/p>\n\n\n\n<p>3\u3001\u5bf9\u4e8e\u88ab\u76d1\u6d4b\u7684\u8bbe\u5907\u6216\u9700\u8981\u5904\u7406\u7684\u5bf9\u8c61\uff0c\u91cd\u8981\u7684\u662f\u6839\u636e\u9700\u6c42\u786e\u5b9a\u80fd\u591f\u4f53\u73b0\u5176\u7ed3\u6784\u5316\u7279\u5f81\u7684\u8868\u5f81\u76d1\u6d4b\u9879\u3002\u540c\u6837\u91cd\u8981\u7684\u662f\uff0c\u5982\u4f55\u91c7\u96c6\u8868\u5f81\u76d1\u6d4b\u9879\u6570\u636e\uff1b<\/p>\n\n\n\n<p>4\u3001\u66f4\u91cd\u8981\u7684\u662f\u7528\u4e8eAI\u6a21\u578b\u5b66\u4e60\u7684\u6570\u636e\uff0c\u5305\u62ec\u6570\u636e\u7684\u83b7\u53d6\u548c\u5fc5\u8981\u7684\u6807\u8bc6\uff1b<\/p>\n\n\n\n<p>5\u3001\u5173\u952e\u95ee\u9898\u7684\u5173\u952e\u6837\u672c\u6570\u636e\u53cd\u800c\u4e0d\u5bb9\u6613\u83b7\u53d6\u3002\u5c0f\u6837\u672c\u5b66\u4e60\u662f\u9014\u5f84\u4e4b\u4e00\uff0c<a href=\"https:\/\/nullthought.net\/?p=3963\" target=\"_blank\" rel=\"noreferrer noopener\">\u5408\u6210\u6570\u636e<\/a>\u4e5f\u662f\u4e00\u4e2a\u65b9\u5411\uff1b<\/p>\n\n\n\n<p>6\u3001\u5982\u679c\u80fd\u591f\u7528\u6570\u636e\u5206\u6790\u7684\u6570\u5b66\u6a21\u578b\u8868\u8ff0\u51fa\u8bbe\u5907\u6216\u5bf9\u8c61\u7684\u5185\u5728\u7ed3\u6784\u5316\u7279\u5f81\uff0c\u5c31\u4e0d\u4e00\u5b9a\u8981\u7528AI\u6a21\u578b\u3002\u5982\u679c\u9762\u5bf9\u7684\u662f\u4e2a\u9ed1\u76d2\uff0c\u90a3\u7528AI\u6a21\u578b\u7684\u9524\u5b50\u5148\u7838\u4e00\u7838\u4e5f\u65e0\u59a8\u3002<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p>1. The deployment of edge AI models is becoming increasingly easier. More and more major companies, such as chip manufacturers and industrial automation giants, have launched or will launch their own tools for generating, processing and deploying edge AI models. If independent edge-AI vendors do a decent job, <a href=\"https:\/\/nullthought.net\/?p=6050\" target=\"_blank\" rel=\"noreferrer noopener\">there\u2019s a strong chance they\u2019ll be acquired by big players<\/a>.<\/p>\n\n\n\n<p>2. Tools that hide hardware architecture differences on edge devices and allow models to be quickly compiled and deployed across diverse edge platforms (such as <a href=\"https:\/\/nullthought.net\/?p=6511\" target=\"_blank\" rel=\"noreferrer noopener\">Roofline<\/a>) will start to appear one after another.<\/p>\n\n\n\n<p>3. For the monitored devices or objects that need processing, it is crucial to determine the representative monitoring items that can reflect their structured characteristics based on the requirements. Equally important is how to collect the data for these representative monitoring items.<\/p>\n\n\n\n<p>4. Even more important is the data used for AI model training, including the acquisition and necessary labeling of the data. In a sense, better data is better than better models.<\/p>\n\n\n\n<p>5. Key sample data for critical issues are rather difficult to obtain. Few-shot learning is one of the approaches. <a href=\"https:\/\/nullthought.net\/?p=3963\" target=\"_blank\" rel=\"noreferrer noopener\">Synthetic data<\/a> is another direction.<\/p>\n\n\n\n<p>6. If the intrinsic structured characteristics of the device or object can be described using mathematical models for data analysis, there may not be a need for AI models. However, if faced with a black box, it&#8217;s acceptable to first try using the AI model approach.<\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" src=\"https:\/\/nullthought.net\/wp-content\/uploads\/2023\/07\/AI-on-Edge-Devices.jpg\" alt=\"\" class=\"wp-image-3087\" srcset=\"https:\/\/nullthought.net\/wp-content\/uploads\/2023\/07\/AI-on-Edge-Devices.jpg 1024w, https:\/\/nullthought.net\/wp-content\/uploads\/2023\/07\/AI-on-Edge-Devices-300x300.jpg 300w, https:\/\/nullthought.net\/wp-content\/uploads\/2023\/07\/AI-on-Edge-Devices-150x150.jpg 150w, https:\/\/nullthought.net\/wp-content\/uploads\/2023\/07\/AI-on-Edge-Devices-768x768.jpg 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>1\u3001\u8fb9\u7f18\u7aefAI\u6a21\u578b\u7684\u90e8\u7f72\u5c06\u4f1a\u8d8a\u6765\u8d8a\u5bb9\u6613\u3002\u8d8a\u6765\u8d8a\u591a\u7684\u5927\u5382\uff0c\u5982\u82af\u7247\u548c\u5de5\u4e1a\u81ea\u52a8\u5316\u5927\u5382\uff0c\u5df2\u7ecf\u6216\u5c06\u4f1a\u63a8\u51fa\u81ea\u5df1\u7684\u8fb9\u7f18\u8bbe\u5907A [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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rel=\"category\">\u79d1\u5b66<\/a>","rttpg_excerpt":"1\u3001\u8fb9\u7f18\u7aefAI\u6a21\u578b\u7684\u90e8\u7f72\u5c06\u4f1a\u8d8a\u6765\u8d8a\u5bb9\u6613\u3002\u8d8a\u6765\u8d8a\u591a\u7684\u5927\u5382\uff0c\u5982\u82af\u7247\u548c\u5de5\u4e1a\u81ea\u52a8\u5316\u5927\u5382\uff0c\u5df2\u7ecf\u6216\u5c06\u4f1a\u63a8\u51fa\u81ea\u5df1\u7684\u8fb9\u7f18\u8bbe\u5907A&hellip;","_links":{"self":[{"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/posts\/3085","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/nullthought.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3085"}],"version-history":[{"count":4,"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/posts\/3085\/revisions"}],"predecessor-version":[{"id":6515,"href":"https:\/\/nullthought.net\/index.php?rest_route=\/wp\/v2\/posts\/3085\/revisions\/6515"}],"wp:attachment":[{"href":"https:\/\/nullthought.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3085"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nullthought.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3085"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nullthought.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3085"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}