{"id":2617,"date":"2020-10-21T17:50:57","date_gmt":"2020-10-21T16:50:57","guid":{"rendered":"https:\/\/process-chemistry-analytics.com\/?p=2617"},"modified":"2020-10-21T23:59:40","modified_gmt":"2020-10-21T22:59:40","slug":"successfully-evaluating-ai-models-in-industry","status":"publish","type":"post","link":"https:\/\/process-chemistry-analytics.com\/index.php\/2020\/10\/21\/successfully-evaluating-ai-models-in-industry\/","title":{"rendered":"Successfully Evaluating AI Models in Industry"},"content":{"rendered":"

An interesting article from University of Delaware:<\/p>\n

“A new approach to artificial intelligence that builds in uncertainty.”<\/p>\n

AI workers are combining the best of both worlds. Deterministic models based on scientific understanding of processes and statistical models, to create more accurate and precise probabilistic models.<\/p>\n

The model itself identifies what data are needed to reduce model error and helps to identify the most productive areas for further work.<\/p>\n

Researchers, manufacturers and suppliers producing AI models for improved control of industrial processes will increasingly compete based on the accuracy and precision of their models.<\/p>\n

Using rigorous methods, PCA can assist industrial sites to evaluate complex models coming from equipment and chemical suppliers.<\/p>\n

As McKinsey & Co. says, “The Fourth Industrial Revolution is Happening Now in Manufacturing.” The winners will be those who act now and are successful at making the incremental improvements in performance.<\/p>\n

When modelling our world, we use observations, thoughts and concepts. But, be aware that these are only our approximations to reality, not actual reality!<\/p>\n

 <\/p>\n

A new approach to artificial intelligence that builds in uncertainty, October 19, 2020, University of Delaware<\/a><\/p>\n

Modelling and Observing Reality in an Uncertain, Interconnected World, September 19, 2020, PCA<\/a><\/p>\n

The Fourth Industrial Revolution is Happening Now in Manufacturing<\/a><\/p>\n

Over-Reliance on Expert Intuition<\/a><\/p>\n

The Risks Associated with Predictive Models \u2013 What We All Need to Remember: We Can\u2019t Predict Everything!<\/a><\/p>\n

 <\/p>\n

\"Broken<\/picture>

Using rigorous methods, PCA can assist companies to successfully implement AI process control models<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

An interesting article from University of Delaware: “A new approach to artificial intelligence that builds in uncertainty.” AI workers are combining the best of both worlds. Deterministic models based on scientific understanding of processes and statistical models, to create more accurate and precise probabilistic models. The model itself identifies what data are needed to reduce […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[1],"tags":[92,90,93,30,23,150,91,109,46,33,121,15,94,85,80,102,51,148,149,53,31,135],"class_list":["post-2617","post","type-post","status-publish","format-standard","hentry","category-uncategorised","tag-ai","tag-big-data","tag-black-box","tag-chemical","tag-control","tag-data","tag-data-science","tag-decisions","tag-digitally-enabled-services","tag-industry","tag-manufacturing","tag-mining-industry","tag-modelling","tag-predictive-analytics","tag-quality-control","tag-risk-management","tag-risks","tag-science","tag-scientific-method","tag-statistics","tag-supplier","tag-uncertainty"],"_links":{"self":[{"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/posts\/2617","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/comments?post=2617"}],"version-history":[{"count":8,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/posts\/2617\/revisions"}],"predecessor-version":[{"id":2629,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/posts\/2617\/revisions\/2629"}],"wp:attachment":[{"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/media?parent=2617"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/categories?post=2617"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/process-chemistry-analytics.com\/index.php\/wp-json\/wp\/v2\/tags?post=2617"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}