{"id":25511,"date":"2022-11-09T00:00:00","date_gmt":"2024-09-13T08:48:56","guid":{"rendered":"https:\/\/wordpress-583806-4798031.cloudwaysapps.com\/ai-it-architecture-and-what-to-expect-in-2023-2030\/"},"modified":"2024-11-15T16:21:16","modified_gmt":"2024-11-15T15:21:16","slug":"ai-it-architecture-and-what-to-expect-in-2023-2030","status":"publish","type":"post","link":"https:\/\/informator.se\/en\/ai-it-architecture-and-what-to-expect-in-2023-2030\/","title":{"rendered":"AI, IT Architecture, and What to Expect in 2023-2030"},"content":{"rendered":"<div class=\"product\"><div class=\"product\"><span style=\"vertical-align: inherit;\"><span style=\"vertical-align: inherit;\">\n<p class=\"wp-block-paragraph\"><em>The global AI market is predicted to <a href=\"https:\/\/informator.se\/blogg\/ai-summer-2022-hospital-green-apps-keep-level-with-army-green\/\">seven-fold<\/a> in 7 years, 2021-28, and the US National Security Commission on AI expects it to reorganize the future life of the world. It\u2019s an easy guess that reshaping the field of AI and IT architecture itself is no exception.<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Resource-efficient algorithms<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The vulnerability of long HW-supply chains, laid bare by Covid and Putin\u2019s War, is mitigated by insourcing (scroll down to \u201c3.\u201d <a href=\"https:\/\/informator.se\/blogg\/architects-beware-60-years-since-dartmouth\/\">here<\/a>) and <a href=\"https:\/\/www.csis.org\/analysis\/look-chips-related-portions-chips\">friendshoring<\/a> ranging from <a href=\"https:\/\/www.tweaktown.com\/news\/86705\/tsmc-releases-two-new-renderings-of-its-arizona-usa-office-building\/index.html\">Arizona<\/a> and <a href=\"https:\/\/www.teslarati.com\/tesla-samsung-17b-chip-plant-giga-texas\/?utm_campaign=gs-2020-11-23&amp;utm_source=google&amp;utm_medium=smart_campaign&amp;gclid=EAIaIQobChMI1bmp28-X-wIVOUeRBR0_kwOZEAAYASAAEgLFEfD_BwE\">Texas<\/a> to <a href=\"https:\/\/www.euractiv.com\/section\/5g\/news\/europes-first-digitalised-chip-plant-opens-in-dresden\/?_ga=2.11752119.2011324609.1630318262-227404064.1620245118\">Saxony<\/a> and <a href=\"https:\/\/techcrunch.com\/2022\/03\/15\/intel-plans-to-build-a-19-billion-chip-plant-in-germany\/?guccounter=1&amp;guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLnNlLw&amp;guce_referrer_sig=AQAAAB3vFzJgPxaVcJQgPPp2wIVt5K-jmLube3_8o65cGIVlMSQX3UdC0vS_lDeKp84cTvHTiQgJeNeTof6mQGwpix10a77TqIjgpNISMCiwm_KK8W1r2SUbWI_C6mzVzxsbjd8BgivU3JOpAUyHWSv9BbY_yupRzKCqF1WIthh6KdkR\">Anhalt<\/a> or <a href=\"https:\/\/new.abb.com\/plc\/ja\/references\/by-date\/clean-room-hvac-for-semiconductors-plant-in-czech-republic\">Sweden and Czechia<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This transition takes time nevertheless. Meanwhile, HW bottlenecks amplify the demand for simple robust algorithms already needed in <a href=\"https:\/\/informator.se\/blogg\/green-ai-versus-big-data-10-architectural-stepping-stones-to-new-avenues\/\">green IT<\/a>, tiny ML, small data, and <a href=\"https:\/\/informator.se\/blogg\/edge-ai-architects-keep-edging-even-after-the-skiing-season\/\">edge<\/a> <a href=\"https:\/\/informator.se\/blogg\/deep-ml-on-gpus-ai-industry-and-rd-soar\/\">computing<\/a> including edge ML.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Google Cloud VP Andrew Moore points out that much of AI is now <strong>converging <\/strong>behind intuitive single points of entry for users, e. g. conversational AI, and performs increasingly <strong>sophisticated tasks<\/strong>, while the core (or business-logic layer) is becoming a set of <strong>intelligent problem-solver engines<\/strong> foundational to our ways of doing business. Moore lists five <a href=\"https:\/\/cloud.google.com\/blog\/transform\/ai-2030-andrew-moore-five-areas-to-invest-in-ai\">key areas<\/a> in corporate AI for the coming years:<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Use Case-Driven AI, <\/strong>integrating <strong>R&amp;D and product-focused <\/strong>enterprise-grade services<\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">In my opinion, this shall be top-of-the-agenda in your ITA and EA.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Data harmony and interoperability<\/strong> to clean and unify potential training data<\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <\/strong>IMO, good data and cross-connecting disparate data is essential, be big data or small or tiny.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>&nbsp; &nbsp;&nbsp;<strong>Responsible and explainable AI <\/strong>as key part of design\/training and refinement\/retraining.<\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&nbsp;&nbsp;&nbsp;&nbsp; <\/strong>&nbsp;IMO, closing the <a href=\"https:\/\/informator.se\/blogg\/three-big-ai-news-for-it-architects-and-uml-or-sysml-users\/\">gap<\/a> between AI accuracy and <a href=\"https:\/\/informator.se\/blogg\/intelligible-intelligence-deep-xai-still-more-rd-than-toolbox\/\">explainability<\/a>\/<a href=\"https:\/\/informator.se\/blogg\/leveled-up-auditability-of-ai-and-machine-learning\/\">transparency<\/a> is a prerequisite of corporate-wide acceptance .<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Democratization of corporate culture, tools, and <\/strong>i<strong>nterfaces <\/strong>to abstract the complexity<\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&nbsp;&nbsp;&nbsp;&nbsp; <\/strong>&nbsp;IMO, these three boost each other, although any of them can <a href=\"https:\/\/informator.se\/blogg\/animators-auditability-ai-high-tech-history-and-a-near-future\/\">pave the way<\/a> for the rest.<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Multicloud <\/strong>from day one to stay scalable and forward compatible<\/li><\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>&nbsp;&nbsp;&nbsp;&nbsp; <\/strong>&nbsp;IMO, the Vendor-lockin antipattern has been, is, and will be a serious risk. Remember that tools are available for managing and monitoring multiplatform environments, and some of those cover Edge devices as well.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The <strong>SW Engineering Institute<\/strong> of Carnegie Mellon (we use some of their terminology in our Agile Architecture courses, to prevent long hot \u201csame thing twice over\u201d discussions between attendee jargons) emphasizes the <strong>incorporation of ML systems and training data into SW architecture<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Here\u2019s a brief summary of <a href=\"https:\/\/apps.dtic.mil\/sti\/pdfs\/AD1150241.pdf\">their six key points<\/a>:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Include the ML-model <strong>lifecycle <\/strong>and architectural <strong>dependencies<\/strong> of AI components, stress architecturally <strong>significant requirements<\/strong> in ML (both functional and quality attributes) , use <strong>monitorability mechanisms<\/strong> to even handle uncertainty of ML systems, have your data pipeline <strong>cover different rates of change<\/strong> in data and ML-retraining\/redeployment, <strong>co-architect<\/strong> versioning, ML components, and the system at large.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/informator.se\/wp-content\/uploads\/2022\/11\/milan-blogg-9nov.jpg\" alt=\"\" class=\"wp-image-105881\"\/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Summing up, the two-way multiple-lane street between AI and architecture is getting even busier than in the <a href=\"https:\/\/informatorutbildning.blogspot.com\/2019\/04\/6-things-ai-and-machine-learning.html\">recent<\/a> years, just like architects do. Unlike this sign, tradeoffs between architecturally significant requirements are not just three-dimensional; rather, they\u2019re <strong>n<\/strong>-dimensional. &nbsp;: )<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>by <\/em><em><a href=\"http:\/\/se.linkedin.com\/pub\/milan-kratochvil\/26\/b34\/141\">Milan Kratochvil<\/a><\/em><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/informator.se\/wp-content\/uploads\/2022\/11\/milan-blogg-9-nov-2.jpg\" alt=\"\" class=\"wp-image-105884\"\/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Milan&nbsp;and Informator collaborate since 1996 on architecture, AI,<\/em><em> modeling<\/em><em>, UML, rules, requirements, and design. You can meet&nbsp;him this year at these courses <\/em><em>in English or Swedish (<strong>remote<\/strong> participation is encouraged, and classroom participation offered too \u2013 as for November 2022) :<\/em><em><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><a href=\"https:\/\/informator.se\/utbildning\/ai-architecture-and-machine-learning\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI, Architecture, and Machine Learning<\/a><\/em><em><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><a href=\"https:\/\/informator.se\/utbildning\/agile-architecture-fundamentals\/\">Agile Architechture Fundamentals<\/a><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><a href=\"https:\/\/informator.se\/utbildning\/agile-modeling-with-uml\/\" target=\"_blank\" rel=\"noreferrer noopener\">Agile Modeling with UML<\/a><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><a href=\"https:\/\/informator.se\/utbildning\/avancerad-objektmodellering-med-uml\/\">Avancerad objektmodellering med UML<\/a><\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>(on demand: Modular Product Line Architecture<\/em> )<\/p>\n<\/span><\/span>\r\n<h4><span style=\"vertical-align: inherit;\"><span style=\"vertical-align: inherit;\">\u00a0<\/span><\/span><\/h4>\r\n<span style=\"vertical-align: inherit;\"><span style=\"vertical-align: inherit;\"><\/span><\/span><\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>The global AI market is predicted to seven-fold in 7 years, 2021-28, and the US National Security Commission on AI expects it to reorganize the future life of the world. It\u2019s an easy guess that reshaping the field of AI and IT architecture itself is no exception. Resource-efficient algorithms The vulnerability of long HW-supply chains, [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":26777,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[571,570,922],"tags":[593,591,707,628,699,700,704,702,698,701,703,697,696,705,706,687],"class_list":["post-25511","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-blogg","category-blogi","tag-agile","tag-ai","tag-ai-use-cases","tag-architecture","tag-business-driven","tag-data-pipeline","tag-ea","tag-efficient-algorithm","tag-greenit","tag-it-architecture","tag-ita","tag-mlops","tag-models","tag-prediction","tag-swa","tag-uml"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"The global AI market is predicted to seven-fold in 7 years, 2021-28, and the US National Security Commission on AI expects it to reorganize the future life of the world. 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