{"id":202814,"date":"2026-11-12T02:35:22","date_gmt":"2026-11-12T07:35:22","guid":{"rendered":"https:\/\/innowise.com\/?p=202814"},"modified":"2026-11-13T05:39:20","modified_gmt":"2026-11-13T10:39:20","slug":"machine-learning-trends","status":"publish","type":"post","link":"https:\/\/innowise.com\/pt\/blog\/machine-learning-trends\/","title":{"rendered":"Tend\u00eancias de aprendizagem autom\u00e1tica para 2026: mudan\u00e7as tecnol\u00f3gicas e impacto nos neg\u00f3cios"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"202814\" class=\"elementor elementor-202814\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5a59af9 e-flex e-con-boxed e-con e-parent\" data-id=\"5a59af9\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-93e0744 elementor-widget__width-initial elementor-hidden-mobile elementor-widget elementor-widget-html\" data-id=\"93e0744\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\n    \n<\/style>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-92fed16 elementor-widget-tablet__width-inherit elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"92fed16\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Machine learning trends <span id=\"current-year\">2026<\/span>: technology shifts and business impact<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fba61ea elementor-widget__width-initial elementor-widget elementor-widget-html\" data-id=\"fba61ea\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"heroBottom\">\r\n\r\n  <div class=\"second\">\r\n    <span>Nov 12, 2026<\/span>\r\n    <span>17 min read<\/span>\r\n  <\/div>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-970be0b article-description e-con-full e-flex e-con e-parent\" data-id=\"970be0b\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-f2465c0 author-article e-con-full e-flex e-con e-child\" data-id=\"f2465c0\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-d180726 e-con-full e-flex e-con e-child\" data-id=\"d180726\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-ef3c399 e-con-full e-flex e-con e-child\" data-id=\"ef3c399\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ce13d5e elementor-widget elementor-widget-shortcode\" data-id=\"ce13d5e\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">\n    <div class=\"expert_card-container\">\n        <div class=\"expert_card-top\">\n            <div class=\"expert_card-top-img\">\n                                    <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/03\/Philip-Tikhanovich.png\" alt=\"Philip Tikhanovich, Head of Big Data, AI\/ML\/DS Departments.\">\n                                                <a href=\"https:\/\/www.linkedin.com\/in\/tihonfil\/\" class=\"expert_card-top-img-link\" target=\"_blank\" rel=\"noopener noreferrer\">\n                    <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" viewBox=\"0 0 40 40\" fill=\"none\">\n                        <rect width=\"40\" height=\"40\" rx=\"20\" fill=\"#E8E8E8\"\/>\n                        <path d=\"M10.0002 12.8001C10.0002 11.4802 10.0002 10.8202 10.4102 10.4102C10.8203 10.0001 11.4802 10.0001 12.8002 10.0001H27.2002C28.5201 10.0001 29.1801 10.0001 29.5901 10.4102C30.0002 10.8202 30.0002 11.4802 30.0002 12.8001V27.2001C30.0002 28.52 30.0002 29.18 29.5901 29.5901C29.1801 30.0001 28.5201 30.0001 27.2002 30.0001H12.8002C11.4802 30.0001 10.8203 30.0001 10.4102 29.5901C10.0002 29.18 10.0002 28.52 10.0002 27.2001V12.8001Z\" fill=\"white\"\/>\n                        <path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M28.6112 10C29.3782 10 30.0001 10.6218 30.0001 11.3889V28.6111C30.0001 29.3782 29.3782 30 28.6112 30H11.3889C10.6219 30 10.0001 29.3782 10.0001 28.6111V11.3889C10.0001 10.6218 10.6219 10 11.3889 10H28.6112ZM13.0591 26.9444H15.9842V17.5H13.0591V26.9444ZM23.507 17.2114C21.5029 17.2114 20.6595 18.7722 20.6595 18.7722V17.5H17.8543V26.9444H20.6595V21.9868C20.6595 20.6584 21.2709 19.868 22.4412 19.8679C23.5171 19.8679 24.0338 20.6275 24.0338 21.9868V26.9444H26.9445V20.9649C26.9445 18.4349 25.5103 17.2114 23.507 17.2114ZM14.5077 12.7778C13.5522 12.7778 12.7778 13.5583 12.7778 14.5207C12.7779 15.483 13.5522 16.2633 14.5077 16.2633C15.4631 16.2632 16.237 15.483 16.237 14.5207C16.237 13.5583 15.4632 12.7778 14.5077 12.7778Z\" fill=\"#2867B2\"\/>\n                    <\/svg>\n                <\/a>\n                            <\/div>\n            <div class=\"expert_card-top-right\">\n                <div class=\"expert_card-top-name\">\n                    By <a href=\"https:\/\/innowise.com\/pt\/authors\/philip-tikhanovich\/\">Philip Tikhanovich<\/a>\n                <\/div>\n                                <div class=\"expert_card-top-position\">\n                    Head of Big Data, AI\/ML\/DS Departments                <\/div>\n                                <div class=\"expert_card-top-right-bottom desc\">\n                    <div class=\"expert_card-top-ver\">\n                        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"18\" height=\"18\" viewBox=\"0 0 18 18\" fill=\"none\"><path d=\"M17.486 9.00039L15.6037 6.8481L15.866 4.00153L13.0811 3.36896L11.6231 0.900391L9.00024 2.02668L6.37738 0.900391L4.91938 3.36125L2.13453 3.9861L2.39681 6.84039L0.514526 9.00039L2.39681 11.1527L2.13453 14.007L4.91938 14.6395L6.37738 17.1004L9.00024 15.9664L11.6231 17.0927L13.0811 14.6318L15.866 13.9992L15.6037 11.1527L17.486 9.00039Z\" fill=\"#717171\"\/><path d=\"M12.2783 7.55371L8.10059 11.7324L5.72168 9.35352L6.42871 8.64648L8.09961 10.3174L11.5713 6.84668L12.2783 7.55371Z\" fill=\"white\"\/><\/svg>                        Verified expert\n                        <div class=\"expert_card-top-ver-text\">\n                            Every article at Innowise is created by authors with real-world experience. They understand the topic beyond theory and bring insight from real projects.\n                            <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"16\" height=\"8\" viewBox=\"0 0 16 8\" fill=\"none\">\n                                <path d=\"M8 8L16 0L6.99382e-07 -1.39876e-06L8 8Z\" fill=\"#717171\"\/>\n                            <\/svg>\n                        <\/div>\n                    <\/div>\n                    \n                                        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"3\" height=\"3\" viewBox=\"0 0 3 3\" fill=\"none\"><path d=\"M1.5 0C2.32843 0 3 0.671573 3 1.5C3 2.32843 2.32843 3 1.5 3C0.671573 3 0 2.32843 0 1.5C0 0.671573 0.671573 0 1.5 0Z\" fill=\"#717171\"\/><\/svg>                    <div class=\"expert_card-top-year\">\n                        11+ years of experience                    <\/div>\n                                    <\/div>\n            <\/div>\n        <\/div>\n        <div class=\"expert_card-top-right-bottom mob\">\n            <div class=\"expert_card-top-ver\">\n                <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"18\" height=\"18\" viewBox=\"0 0 18 18\" fill=\"none\"><path d=\"M17.486 9.00039L15.6037 6.8481L15.866 4.00153L13.0811 3.36896L11.6231 0.900391L9.00024 2.02668L6.37738 0.900391L4.91938 3.36125L2.13453 3.9861L2.39681 6.84039L0.514526 9.00039L2.39681 11.1527L2.13453 14.007L4.91938 14.6395L6.37738 17.1004L9.00024 15.9664L11.6231 17.0927L13.0811 14.6318L15.866 13.9992L15.6037 11.1527L17.486 9.00039Z\" fill=\"#717171\"\/><path d=\"M12.2783 7.55371L8.10059 11.7324L5.72168 9.35352L6.42871 8.64648L8.09961 10.3174L11.5713 6.84668L12.2783 7.55371Z\" fill=\"white\"\/><\/svg>                Verified expert\n                \n            <\/div>\n                        <svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"3\" height=\"3\" viewBox=\"0 0 3 3\" fill=\"none\"><path d=\"M1.5 0C2.32843 0 3 0.671573 3 1.5C3 2.32843 2.32843 3 1.5 3C0.671573 3 0 2.32843 0 1.5C0 0.671573 0.671573 0 1.5 0Z\" fill=\"#717171\"\/><\/svg>            <div class=\"expert_card-top-year\">\n                11+ years of experience            <\/div>\n                    <\/div>\n                <div class=\"expert_card-text\">\n            Philip builds data infrastructures that provide clarity. He focuses on the &quot;why&quot; behind the data, architecting systems that process massive volumes into actionable insights while ensuring the technical vision remains sharp and purposeful.        <\/div>\n                <div class=\"expert_card-bottom\">\n\t\t\t<div class=\"expert_card-bottom-col\">\n\t\t\t\t\t\t\t\t<div class=\"expert_card-bottom-expertise\">\n\t\t\t\t\t<div class=\"expert_card-bottom-expertise-title\">\n\t\t\t\t\t\tExpertise\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"expert_card-bottom-expertise-list\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tBig data\t\t\t\t\t\t\t\t\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"3\" height=\"3\" viewBox=\"0 0 3 3\" fill=\"none\"><path d=\"M1.5 0C2.32843 0 3 0.671573 3 1.5C3 2.32843 2.32843 3 1.5 3C0.671573 3 0 2.32843 0 1.5C0 0.671573 0.671573 0 1.5 0Z\" fill=\"#717171\"\/><\/svg>\t\t\t\t\t\t\tAI &amp; ML\t\t\t\t\t\t\t\t\t\t\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"3\" height=\"3\" viewBox=\"0 0 3 3\" fill=\"none\"><path d=\"M1.5 0C2.32843 0 3 0.671573 3 1.5C3 2.32843 2.32843 3 1.5 3C0.671573 3 0 2.32843 0 1.5C0 0.671573 0.671573 0 1.5 0Z\" fill=\"#717171\"\/><\/svg>\t\t\t\t\t\t\tPython\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"expert_card-bottom-featured\">\n\t\t\t\t\t<div class=\"expert_card-bottom-expertise-title\">\n\t\t\t\t\t\tFeatured in\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"expert_card-bottom-featured-imgs\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/09\/the_AI_journal.svg\" alt=\"The AI journal logo.\">\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\n            <a href=\"#contact-form\" class=\"expert_card-bottom-a\">\n                Let's talk\n            <\/a>\n        <\/div>\n    <\/div>\n\n    <style>\n        .expert_card-container{\n            max-width:1000px;\n            width:100%;\n            padding:40px 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class=\"elementor-heading-title elementor-size-default\">Key takeaways<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c1c3b2 elementor-widget elementor-widget-text-editor\" data-id=\"3c1c3b2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul class=\"blackUl\"><li class=\"translation-block\"><b>ML in <span id=\"current-year\">2026<\/span> is getting more practical.<\/b> A lot of the progress is in reuse, efficiency, monitoring, calibration, and making models less painful to run in production.<\/li><li class=\"translation-block\"><b>Pretrained and self-supervised models are changing how much needs to be built from scratch.<\/b> Tabular foundation models, reusable visual representations, and synthetic training data can reduce some of the usual training and labeling work.<\/li><li class=\"translation-block\"><b>Deployment constraints matter more than benchmark wins.<\/b> Latency, memory, energy use, drift, subgroup performance, and inference cost can matter more than squeezing out another fraction of a percent in accuracy.<\/li><li class=\"translation-block\"><b>The same trends are changing very different workflows.<\/b> In retail it shows up in forecasting and recommendations; in banking, fraud and credit risk; in healthcare, patient prioritization; in manufacturing, predictive maintenance and defect detection; in logistics, ETAs and delay prediction.<\/li><li class=\"translation-block\"><b>A few promising areas are still very much works in progress.<\/b> Continual learning, causal ML, hybrid models, cross-domain adaptation, and uncertainty-aware prediction all look useful, but I\u2019d separate what has been demonstrated from what is ready to deploy.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9063246 e-con-full e-flex e-con e-child\" data-id=\"9063246\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dbd89c3 elementor-widget elementor-widget-shortcode\" data-id=\"dbd89c3\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">[summarize_button_ai]<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5b3b682 elementor-widget elementor-widget-shortcode\" data-id=\"5b3b682\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">[summarize_button_google]<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9da5222 elementor-absolute elementor-widget elementor-widget-html\" data-id=\"9da5222\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\n    @media (max-width: 768px) {\n        .summarize_ai_button, .summarize_google_button {\n            width: 100%;\n            justify-content: center;\n        }\n    }\n<\/style>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-65b37a6 e-con-full e-flex e-con e-child\" data-id=\"65b37a6\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-db56f52 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"db56f52\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>ML is boring now. That\u2019s the trend.<\/p><p>Or, at least, a lot of the interesting progress is happening in places that don\u2019t make very good headlines: shaving 40 milliseconds off inference, training with fewer labels, reusing a model instead of building another one, finding out why a 96%-accurate system keeps screwing up the same group of users.<\/p><p>And this is probably good news. I believe most companies don\u2019t really need a grand ML breakthrough. They wouldn&#8217;t mind a good model that keeps working when the data changes, doesn\u2019t cost a fortune to run, and gives some warning when it starts behaving strangely.<\/p><p>So, let\u2019s look at the latest trends in machine learning to see where that work is heading.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-b92c541 e-con-full elementor-hidden-desktop e-flex e-con e-child\" data-id=\"b92c541\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-cf76d63 e-con-full e-flex e-con e-child\" data-id=\"cf76d63\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6958332 elementor-widget-tablet__width-inherit elementor-widget__width-initial max100 elementor-widget elementor-widget-heading\" data-id=\"6958332\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Put ML to work<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ab04def e-con-full e-flex e-con e-child\" data-id=\"ab04def\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d49b868 elementor-absolute elementor-widget-mobile__width-inherit transform elementor-widget elementor-widget-html\" data-id=\"d49b868\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"wave-container\"><\/div>\r\n\r\n<style>\r\n  .wave-container {\r\n    width: 400px;\r\n    height: 400px;\r\n  }\r\n\r\n  @media(max-width: 767px) {\r\n    .wave-container {\r\n      width: 100%;\r\n      height: 100%;\r\n    }\r\n  }\r\n\r\n\r\n  .wave {\r\n    position: absolute;\r\n    border: 1px solid rgba(210, 184, 214, 1);\r\n    border-radius: 50%;\r\n    animation: drop 16s infinite;\r\n    top: 50%;\r\n    left: 50%;\r\n    transform: translate(-50%, -50%);\r\n    box-sizing: border-box;\r\n  }\r\n\r\n  @keyframes drop {\r\n    0% {\r\n      width: 0px;\r\n      height: 0px;\r\n      border: 1px solid rgba(210, 184, 214, 1);\r\n    }\r\n\r\n    100% {\r\n      width: 400px;\r\n      height: 400px;\r\n      border: 1px solid rgba(210, 184, 214, 0);\r\n    }\r\n  }\r\n<\/style>\r\n\r\n<script>\r\n\r\n  document.addEventListener('DOMContentLoaded', () => {\r\n    function createWaves(numberOfWaves) {\r\n      const waveContainers = document.querySelectorAll('.wave-container');\r\n\r\n      waveContainers.forEach((waveContainer) => {\r\n        for (let i = 0; i < numberOfWaves; i++) {\r\n          const wave = document.createElement('div');\r\n          wave.classList.add('wave');\r\n\r\n          wave.style.animationDelay = `${i * 0.8}s`;\r\n\r\n          waveContainer.appendChild(wave);\r\n        }\r\n      });\r\n    }\r\n\r\n    createWaves(10)\r\n  });\r\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-03ebd5c elementor-align-left elementor-widget__width-initial elementor-widget-mobile__width-inherit cta-btn elementor-widget elementor-widget-button\" data-id=\"03ebd5c\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#contact-form\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Talk to us<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f2858d1 e-con-full e-flex e-con e-child\" data-id=\"f2858d1\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-86cbb77 elementor-widget elementor-widget-heading\" data-id=\"86cbb77\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Machine learning market overview and forecast<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-96bef19 e-con-full e-flex e-con e-child\" data-id=\"96bef19\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b0674ef elementor-widget elementor-widget-html\" data-id=\"b0674ef\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\r\n\r\n.results {\r\n  --color-dark: #2e2e2e;\r\n  --color-light-bg: #fbfbfd;\r\n  --color-line: #999999;\r\n\r\n  --font-heading: \"Sora\", Arial, Helvetica, sans-serif;\r\n  --font-body: \"Karla\", Arial, Helvetica, sans-serif;\r\n\r\n  background-color: var(--color-light-bg);\r\n  color: var(--color-dark);\r\n}\r\n\r\n.results,\r\n.results *,\r\n.results *::before,\r\n.results *::after {\r\n  box-sizing: border-box;\r\n}\r\n\r\n\/* ---------- Desktop (base): fixed 280px columns, gap 80 ---------- *\/\r\n\r\n.results__list {\r\n  display: flex;\r\n  flex-direction: row;\r\n  align-items: stretch;\r\n  gap: 80px;\r\n  margin: 0;\r\n  padding: 0;\r\n  list-style: none;\r\n}\r\n\r\n.results__item {\r\n  display: flex;\r\n  flex-direction: column;\r\n  flex: 0 0 280px;\r\n  min-width: 0;\r\n  gap: 20px;\r\n  padding-bottom: 20px;\r\n  border-bottom: 1px solid var(--color-line);\r\n}\r\n\r\n.results__value {\r\n  margin: 0 !important;\r\n  font-family: var(--font-heading);\r\n  font-weight: 400;\r\n  font-size: 50px;\r\n  line-height: 1.26;\r\n}\r\n\r\n.results__text {\r\n  margin: 0;\r\n  font-family: var(--font-body);\r\n  font-weight: 400;\r\n  font-size: 18px;\r\n  line-height: 1.5;\r\n  margin-bottom: 0 !important;\r\n}\r\n\r\n.results__source {\r\n  margin: auto 0 0; \/* stick to the bottom when descriptions differ in height *\/\r\n  font-family: var(--font-body);\r\n  font-weight: 400;\r\n  font-size: 16px;\r\n  line-height: 24px;\r\n}\r\n\r\n.results__source a {\r\n  color: inherit;\r\n  text-decoration: underline;\r\n  text-decoration-skip-ink: auto;\r\n}\r\n\r\n\/* ---------- Laptop and tablet: fluid columns, gap 40 ---------- *\/\r\n\r\n@media (max-width: 1439px) {\r\n  .results__list {\r\n    gap: 40px;\r\n  }\r\n\r\n  .results__item {\r\n    flex: 1 1 0;\r\n  }\r\n\r\n  .results__value {\r\n    font-size: 40px;\r\n  }\r\n}\r\n\r\n\/* ---------- Mobile: single column ---------- *\/\r\n\r\n@media (max-width: 767px) {\r\n  .results__list {\r\n    flex-direction: column;\r\n    gap: 30px;\r\n  }\r\n\r\n  .results__item {\r\n    flex: 0 0 auto;\r\n    gap: 10px;\r\n  }\r\n\r\n  .results__value {\r\n    font-size: 30px;\r\n  }\r\n\r\n  .results__text {\r\n    font-size: 14px;\r\n  }\r\n\r\n  .results__source {\r\n    font-size: 14px;\r\n    line-height: 21px;\r\n  }\r\n}\r\n<\/style>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-332aabd elementor-widget elementor-widget-html\" data-id=\"332aabd\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<section class=\"results\">\r\n  <ul class=\"results__list\">\r\n    <li class=\"results__item\">\r\n      <p class=\"results__value\">$65.28B<\/p>\r\n      <p class=\"results__text\">global ML market in 2026<\/p>\r\n      <p class=\"results__source\">Source: <a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-market-102226\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a><\/p>\r\n    <\/li>\r\n    <li class=\"results__item\">\r\n      <p class=\"results__value\">53.14%<\/p>\r\n      <p class=\"results__text\">cloud share of the ML market in 2026<\/p>\r\n      <p class=\"results__source\">Source: <a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-market-102226\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a><\/p>\r\n    <\/li>\r\n    <li class=\"results__item\">\r\n      <p class=\"results__value\">$26.44B<\/p>\r\n      <p class=\"results__text\">spending on data science and ML platforms in 2026<\/p>\r\n      <p class=\"results__source\">Source: <a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-market-102226\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a><\/p>\r\n    <\/li>\r\n  <\/ul>\r\n<\/section>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c717074 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"c717074\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The ML market is growing fast. But nobody quite agrees on how big it is.<\/p><p><a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-market-102226\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a> puts the global machine learning market at <b>$65.28 billion in 2026<\/b> and expects it to reach <b>$432.63 billion by 2034<\/b>. <a href=\"https:\/\/www.thebusinessresearchcompany.com\/report\/machine-learning-global-market-report\" target=\"_blank\" rel=\"noopener noreferrer\">The Business Research Company<\/a> gives a much larger estimate for the same year: <b>$127.94 billion in 2026<\/b>, rising to <b>$445.25 billion by 2030<\/b>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8ff9171 elementor-widget elementor-widget-image\" data-id=\"8ff9171\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"800\" height=\"361\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml-market-growth.png\" class=\"attachment-large size-large wp-image-202824\" alt=\"Global machine learning market growth 2025-2034.\" srcset=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml-market-growth.png 1000w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml-market-growth-300x135.png 300w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml-market-growth-768x346.png 768w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml-market-growth-18x8.png 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43d9b65 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"43d9b65\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>That\u2019s almost a twofold difference for 2026. Mostly, it tells us that \u201cmachine learning market\u201d is a surprisingly elastic category: different analysts include different mixes of software, infrastructure, services, and hardware.<\/p><p>The details inside the forecasts are useful too. Fortune expects <b>cloud deployment to account for 53.14% of the ML market in 2026<\/b>, with <b>large enterprises at 55.61%<\/b> and <b>IT and telecom at 17.56%<\/b> of end use.<\/p><p>Meanwhile, <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2026-07-20-gartner-forecasts-worldwide-ai-platforms-and-models-market-to-grow-63-percent-in-2026\" target=\"_blank\" rel=\"noopener noreferrer\">Gartner<\/a> expects spending on <b>AI platforms for data science and machine learning to reach $26.44 billion in 2026<\/b>, up <b>36.3%<\/b> from 2025.<\/p><p>So I wouldn\u2019t get too attached to one giant market number. The useful part is the direction: spending is rising, cloud takes a large share of deployment, and the tooling around ML is becoming a sizeable market of its own.<\/p><p>Now, let\u2019s see the recent trends in machine learning themselves.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-00acca1 elementor-widget elementor-widget-shortcode\" data-id=\"00acca1\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">[blog_related_services post_in='32027,176599,172979' title='See related services we offer']<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-ea80ee6 e-con-full e-flex e-con e-child\" data-id=\"ea80ee6\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-301817a elementor-widget elementor-widget-heading\" data-id=\"301817a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Current trends in machine learning<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7692203 elementor-widget elementor-widget-text-editor\" data-id=\"7692203\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Some of the top machine learning trends are new. Others have been around for years and are only now becoming practical enough to go outside research teams. I\u2019m more interested in the second group, to be honest, but anyway, let&#8217;s get into it.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b14fbc0 elementor-widget elementor-widget-image\" data-id=\"b14fbc0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"418\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/machine-learning-trends.png\" class=\"attachment-large size-large wp-image-202825\" alt=\"Key machine learning trends this year.\" srcset=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/machine-learning-trends.png 1000w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/machine-learning-trends-300x157.png 300w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/machine-learning-trends-768x401.png 768w, https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/machine-learning-trends-18x9.png 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6e8943b e-con-full e-flex e-con e-child\" data-id=\"6e8943b\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9c2a6e4 elementor-widget elementor-widget-heading\" data-id=\"9c2a6e4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Foundation models for tabular data and time series<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-94de73b translation-block elementor-widget elementor-widget-text-editor\" data-id=\"94de73b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Tables are having their foundation-model moment.<\/p><p>In June 2026, <a href=\"https:\/\/research.google\/blog\/introducing-tabfm-a-zero-shot-foundation-model-for-tabular-data\" target=\"_blank\" rel=\"noopener noreferrer\">Google introduced <b>TabFM<\/b><\/a>, a model for tabular classification and regression that can make predictions on new datasets without the usual round of task-specific training and hyperparameter tuning. Google tested it across <b>38 classification and 13 regression datasets<\/b>, including tables with up to 150,000 samples.<\/p><p>What\u2019s curious about it? It\u2019s how it was trained. There isn\u2019t some gigantic public warehouse of clean enterprise tables, so Google generated <b>hundreds of millions of synthetic datasets<\/b> instead.<\/p><p>I wouldn\u2019t delete <a href=\"https:\/\/xgboost.ai\/\" target=\"_blank\" rel=\"noopener noreferrer\">XGBoost<\/a> just yet. For many structured-data problems, conventional models are still cheaper, easier to debug, and very hard to beat. But the idea of opening a new dataset and getting a decent baseline without another tuning marathon is pretty attractive.<\/p><p>And time series are moving in the same direction. Google\u2019s <a href=\"https:\/\/research.google\/blog\/a-decoder-only-foundation-model-for-time-series-forecasting\/\" target=\"_blank\" rel=\"noopener noreferrer\">TimesFM<\/a> is pretrained on large collections of time-series data and can produce zero-shot forecasts for datasets it hasn\u2019t seen before. The attraction is similar to TabFM: less task-specific training every time somebody needs a new demand, traffic, or capacity forecast.<\/p><p>Would I replace every existing forecasting pipeline with it? No. But it\u2019s worth testing when the alternative is another round of model training and tuning from scratch.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-165b859 e-con-full e-flex e-con e-child\" data-id=\"165b859\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-52bf465 elementor-widget elementor-widget-heading\" data-id=\"52bf465\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Self-supervised learning needs fewer labels<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-10eed7e translation-block elementor-widget elementor-widget-text-editor\" data-id=\"10eed7e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Labeling data is one of those jobs everyone agrees is essential and nobody is excited to pay for.<\/p><p>Self-supervised learning gets around part of that problem by learning useful representations from unlabeled data first, then adapting them to a smaller labeled dataset.<\/p><p><a href=\"https:\/\/ai.meta.com\/blog\/dinov3-self-supervised-vision-model\/\" target=\"_blank\" rel=\"noopener noreferrer\">Meta\u2019s <b>DINOv3<\/b><\/a> is a good example. It was trained on <b>1.7 billion images without human labels<\/b>, with the largest model reaching <b>7 billion parameters<\/b>. The same frozen visual backbone can then support tasks such as classification, object detection, segmentation, and tracking.<\/p><p>For companies sitting on years of unlabeled inspection photos, satellite images, medical imagery, or video, that changes the economics a little. You may still need labels. Just perhaps not several million of them.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-58786e5 e-con-full e-flex e-con e-child\" data-id=\"58786e5\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-abdf224 elementor-widget elementor-widget-heading\" data-id=\"abdf224\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Smaller models are becoming more interesting again<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-65b7ecd translation-block elementor-widget elementor-widget-text-editor\" data-id=\"65b7ecd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>A beautiful model that needs a data center to answer a simple question has limited charm on a phone, sensor, camera, or industrial controller.<\/p><p>So model compression keeps getting more attention: <b>quantization<\/b> reduces numerical precision, <b>pruning<\/b> removes less useful weights, and <b>distillation<\/b> transfers knowledge into a smaller model. <a href=\"https:\/\/www.tensorflow.org\/model_optimization\/guide\" target=\"_blank\" rel=\"noopener noreferrer\">TensorFlow\u2019s own optimization toolkit<\/a> lists latency, memory use, power consumption, and model size as central constraints for edge deployment.<\/p><p>There is no free lunch here. Compress too aggressively and accuracy drops.<\/p><p>The job is finding the point where nobody notices except the infrastructure bill.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-612474c e-con-full e-flex e-con e-child\" data-id=\"612474c\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4c52f2f elementor-widget elementor-widget-heading\" data-id=\"4c52f2f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">MLOps is becoming less optional<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4314ecd translation-block elementor-widget elementor-widget-text-editor\" data-id=\"4314ecd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Training the model was never the entire job. We just spent a surprising amount of time pretending it was.<\/p><p>Once an ML system is live, someone has to know which dataset produced it, which code version trained it, whether input data has changed, whether performance is drifting, when retraining is allowed, and how to roll back a bad release.<\/p><p>Tools are reflecting this. <a href=\"https:\/\/mlflow.org\/releases\/3\/\" target=\"_blank\" rel=\"noopener noreferrer\">MLflow 3<\/a>, for example, expanded its model-management architecture around stronger lineage and comparison between model versions and experiments.<\/p><p>This is probably one of the least glamorous machine learning trends on the list, and one of the ones I\u2019d take most seriously.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-c08f8e0 e-con-full e-flex e-con e-child\" data-id=\"c08f8e0\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e599bfd elementor-widget elementor-widget-heading\" data-id=\"e599bfd\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Synthetic data gets a reality check<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-23d3181 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"23d3181\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Synthetic data sounds wonderfully convenient. Missing examples? Make some.<\/p><p>That can work. It can also make a model very good at understanding an artificial world that doesn\u2019t quite exist.<\/p><p><a href=\"https:\/\/machinelearning.apple.com\/research\/beyond-real-data\" target=\"_blank\" rel=\"noopener noreferrer\">A 2026 Apple research paper<\/a> looked at mixing real and synthetic training data and found something more useful than \u201csynthetic data helps.\u201d Their results suggest an <b>optimal ratio<\/b> can exist: add synthetic data and performance improves up to a point, then starts getting worse as the synthetic and real distributions move too far apart.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-05b149d e-con-full e-flex e-con e-child\" data-id=\"05b149d\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-38f3cd5 elementor-widget elementor-widget-heading\" data-id=\"38f3cd5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Multimodal ML moves into ordinary prediction<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43f09c9 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"43f09c9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Multimodal doesn\u2019t have to mean a model that can discuss your photo and write a poem about it.<\/p><p>For predictive ML, it can be much less exciting and much more useful: product image + description + price, medical scan + patient history, sensor readings + maintenance notes.<\/p><p><a href=\"https:\/\/auto.gluon.ai\/stable\/api\/autogluon.multimodal.MultiModalPredictor.html\" target=\"_blank\" rel=\"noopener noreferrer\">Current AutoGluon tooling<\/a>, for example, can combine <b>image, text, tabular, and document data<\/b> for tasks including classification and regression.<\/p><p>The annoying part comes later. What happens when the image is missing? Or the sensor dies? Or one data source arrives two hours later than the others?<\/p><p>That needs to be part of evaluation, not a surprise discovered after launch.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9a2f4eb e-con-full e-flex e-con e-child\" data-id=\"9a2f4eb\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-21aa741 elementor-widget elementor-widget-heading\" data-id=\"21aa741\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">AutoML keeps taking away the boring bits<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e8f7a83 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"e8f7a83\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Model selection, hyperparameter tuning, ensembling, parts of feature processing: a lot of this can already be automated reasonably well.<\/p><p>Good.<\/p><p>I\u2019m not convinced a highly paid ML engineer needs to spend an afternoon manually testing 47 combinations of learning rate and tree depth just to prove dedication to the craft.<\/p><p>What AutoML doesn\u2019t automate very well is deciding whether the target makes sense, whether the training data leaks information from the future, whether the evaluation metric reflects the business cost, or whether the model should exist at all.<\/p><p>Those remain inconveniently human problems.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2f2a042 e-con-full e-flex e-con e-child\" data-id=\"2f2a042\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2983da2 elementor-widget elementor-widget-heading\" data-id=\"2983da2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Federated learning still doesn\u2019t equal privacy<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-15bf6e2 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"15bf6e2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Federated learning has a very appealing setup: train across several devices or organizations without moving all the raw data into one central database.<\/p><p>Useful, yes. Automatically private, no.<\/p><p><a href=\"https:\/\/www.nist.gov\/blogs\/cybersecurity-insights\/privacy-attacks-federated-learning\" target=\"_blank\" rel=\"noopener noreferrer\">NIST has documented attacks<\/a> that can recover information from the <b>model updates exchanged during federated training<\/b>, and recommends additional protections rather than treating decentralization itself as a privacy guarantee.<\/p><p>And real deployments are messy. Different devices have different compute, participants disappear, data distributions differ, security assumptions break. <a href=\"https:\/\/www.nist.gov\/blogs\/cybersecurity-insights\/implementation-challenges-privacy-preserving-federated-learning\" target=\"_blank\" rel=\"noopener noreferrer\">NIST\u2019s 2024 implementation review<\/a> puts the gap between neat federated-learning theory and production systems rather plainly.<\/p><p>One expert quoted there, Dr. Mat Weldon from the UK Office for National Statistics, put it better than I can:<\/p><p style=\"text-align: center;\">\u201c<i>It\u2019s easier to design a new federated learning architecture than it is to red team it.<\/i>\u201d<\/p><p>Fair.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-eb965e1 e-con-full e-flex e-con e-child\" data-id=\"eb965e1\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-775ebd0 elementor-widget elementor-widget-heading\" data-id=\"775ebd0\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Explainability gets less ceremonial<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9da68c4 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"9da68c4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>For years, adding a SHAP chart to a dashboard could make a model feel satisfyingly \u201cexplainable.\u201d<\/p><p>That\u2019s a low bar.<\/p><p><a href=\"https:\/\/airc.nist.gov\/airmf-resources\/playbook\/measure\/\" target=\"_blank\" rel=\"noopener noreferrer\">NIST distinguishes<\/a> between <b>explainability<\/b>, or understanding how a system produced an outcome, and <b>interpretability<\/b>, meaning what that result means in its context. Its guidance also recommends testing explanation methods before deployment rather than assuming the explanation is correct because the chart looks convincing.<\/p><p><a href=\"https:\/\/www.nist.gov\/publications\/explainable-validation-and-feature-reduction-machine-learning\" target=\"_blank\" rel=\"noopener noreferrer\">NIST researchers published work in 2026<\/a> on explainable validation and feature reduction as well, which is interesting because it pulls explainability closer to model testing rather than leaving it as a layer added afterward.<\/p><p>I like that direction. An explanation should be something we test, not decoration for the model card.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3a9098b e-con-full e-flex e-con e-child\" data-id=\"3a9098b\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-29ed5f2 elementor-widget elementor-widget-heading\" data-id=\"29ed5f2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Machine unlearning becomes a real engineering question<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a6a3747 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"a6a3747\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Suppose someone asks you to delete their data.<\/p><p>You delete the database record.<\/p><p>Fine.<\/p><p>What about the model that already trained on it?<\/p><p>That is where <b>machine unlearning<\/b> comes in: removing the influence of particular training data without retraining the entire model from zero. In June 2026, <a href=\"https:\/\/research.google\/blog\/new-framework-for-auditing-machine-unlearning\/\" target=\"_blank\" rel=\"noopener noreferrer\">Google Research published a framework<\/a> for auditing whether an unlearned model really behaves more like a freshly retrained model than the original one.<\/p><p>And that second part matters. Forgetting something is one problem. Proving the model forgot it is another.<\/p><p>Machine unlearning is still much closer to active research than routine enterprise tooling, but I\u2019d keep an eye on it. The moment \u201cdelete my data\u201d has to mean more than deleting a row, this stops being theoretical.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7c133ca e-con-full e-flex e-con e-child\" data-id=\"7c133ca\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-9aeddbc e-con-full e-flex e-con e-child\" data-id=\"9aeddbc\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f583a60 elementor-widget-tablet__width-inherit elementor-widget__width-initial max100 elementor-widget elementor-widget-heading\" data-id=\"f583a60\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Build an ML solution for your business<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3f21aca e-con-full e-flex e-con e-child\" data-id=\"3f21aca\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4a87067 elementor-absolute elementor-widget-mobile__width-inherit transform elementor-widget elementor-widget-html\" data-id=\"4a87067\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"wave-container\"><\/div>\r\n\r\n<style>\r\n  .wave-container {\r\n    width: 400px;\r\n    height: 400px;\r\n  }\r\n\r\n  @media(max-width: 767px) {\r\n    .wave-container {\r\n      width: 100%;\r\n      height: 100%;\r\n    }\r\n  }\r\n\r\n\r\n  .wave {\r\n    position: absolute;\r\n    border: 1px solid rgba(210, 184, 214, 1);\r\n    border-radius: 50%;\r\n    animation: drop 16s infinite;\r\n    top: 50%;\r\n    left: 50%;\r\n    transform: translate(-50%, -50%);\r\n    box-sizing: border-box;\r\n  }\r\n\r\n  @keyframes drop {\r\n    0% {\r\n      width: 0px;\r\n      height: 0px;\r\n      border: 1px solid rgba(210, 184, 214, 1);\r\n    }\r\n\r\n    100% {\r\n      width: 400px;\r\n      height: 400px;\r\n      border: 1px solid rgba(210, 184, 214, 0);\r\n    }\r\n  }\r\n<\/style>\r\n\r\n<script>\r\n\r\n  document.addEventListener('DOMContentLoaded', () => {\r\n    function createWaves(numberOfWaves) {\r\n      const waveContainers = document.querySelectorAll('.wave-container');\r\n\r\n      waveContainers.forEach((waveContainer) => {\r\n        for (let i = 0; i < numberOfWaves; i++) {\r\n          const wave = document.createElement('div');\r\n          wave.classList.add('wave');\r\n\r\n          wave.style.animationDelay = `${i * 0.8}s`;\r\n\r\n          waveContainer.appendChild(wave);\r\n        }\r\n      });\r\n    }\r\n\r\n    createWaves(10)\r\n  });\r\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e3669da elementor-align-left elementor-widget__width-initial elementor-widget-mobile__width-inherit cta-btn elementor-widget elementor-widget-button\" data-id=\"e3669da\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#contact-form\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Talk to our team<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-46c0716 e-con-full e-flex e-con e-child\" data-id=\"46c0716\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-ea60a4f elementor-widget elementor-widget-heading\" data-id=\"ea60a4f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How ML trends are changing workflows across industries<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-207269c elementor-widget elementor-widget-text-editor\" data-id=\"207269c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The same ML trend can behave very differently once it lands in a real workflow. In retail, faster inference can mean updating recommendations while someone is still browsing. In manufacturing, it can mean catching a defect before the product has already moved down the line.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-9612ab9 e-con-full e-flex e-con e-child\" data-id=\"9612ab9\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-55daab3 switcher-section elementor-widget elementor-widget-html\" data-id=\"55daab3\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<!--link in mob example-->\r\n<!--<a href=\"\/services\/ui-ux-design\/\" class=\"see-more-acc\">See more-->\r\n<!--    <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/06\/akar-icons_arrow-down.svg\" alt=\"Right arrow icon.\" class=\"more-arrow\">-->\r\n<!--<\/a>-->\r\n\r\n<style>\r\n.mobile-domain-list-new img:not(.more-arrow) {\r\n    width: 100%;\r\n    height: auto;\r\n    aspect-ratio: 680 \/ 250;\r\n    object-fit: cover;\r\n    display: block;\r\n    background-color: #f5f5f7;\r\n}\r\n\r\n.domains-toggle{\r\n    margin-top: 20px;\r\n    padding-bottom: 8px;\r\n    border-bottom: 1px solid #C63031;\r\n    color: #C63031;\r\n    font-family: Sora;\r\n    font-weight: 600;\r\n    font-size: 14px;\r\n    line-height: 130%;\r\n    width: fit-content;\r\n    cursor: pointer;\r\n}\r\n.see-more-acc {\r\n    display: flex;\r\n    align-items: center;\r\n    gap: 8px;\r\n    font-family: Karla;\r\n    font-size: 14px;\r\n    line-height: 150%;\r\n    text-decoration: none !important;\r\n    color: #C63031;\r\n}\r\n\r\n.domains-container-new .domains__descriptions-new {\r\n    padding-bottom: 0;\r\n    overflow: hidden;\r\n}\r\n\r\n\/* Descriptions container is a column so the wrapper can fill its full height *\/\r\n.domains__descriptions-new {\r\n    display: flex;\r\n    flex-direction: column;\r\n}\r\n\r\n\/* Wrapper fills the container; slides stretch to the tallest one so the 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line-height: 21px !important;\r\n}\r\n\r\n\/* Collapsible part; JS sets max-height from the content height *\/\r\n.mobile-domain-list-new {\r\n    max-height: 0;\r\n    overflow: hidden;\r\n    transition: max-height 0.5s ease;\r\n    cursor: default;\r\n}\r\n\r\n.mobile-domain-content-new {\r\n    display: flex;\r\n    flex-direction: column;\r\n    gap: 16px;\r\n    padding: 8px 0 12px 12px;\r\n}\r\n\r\n.mobile-domain-list-new li {\r\n    margin-bottom: 0;\r\n}\r\n\r\n.switcher-section {\r\n    position: relative;\r\n}\r\n\r\n.switcher-section .domains-container-new .domains__descriptions-new {\r\n    padding: 0;\r\n}\r\n\r\n.domains__list-new {\r\n  width: 100%;\r\n}\r\n\r\n\r\n\r\n.domains__descriptions-item_active-new {\r\n  display: flex;\r\n  flex-direction: column;\r\n  height: 100%;\r\n}\r\n\r\na.slider-link-new{\r\n    font-family: Karla;\r\n    font-weight: 400;\r\n    font-size: 18px;\r\n    line-height: 150%;\r\n    color: #C63031;\r\n    text-decoration: none;\r\n    position: relative;\r\n    width: fit-content;\r\n    display: block;\r\n}\r\n\r\na.slider-link-new::after{\r\n    content: '';\r\n    width: 20px;\r\n    height: 20px;\r\n    background: url('https:\/\/innowise.com\/wp-content\/uploads\/2026\/09\/akar-icons_arrow-down.svg');\r\n    background-size: cover;\r\n    background-position: center;\r\n    position: absolute;\r\n    left: calc(100% + 10px);\r\n    top: 50%;\r\n    transform: translateY(-50%);\r\n}\r\n\r\na.slider-link-new:hover{\r\n    text-decoration: underline;\r\n}\r\n\r\n\r\n\r\n@media (max-width:1279px) and (min-width: 768px) {\r\n    .switcher-section .domains-container-new {\r\n        grid-template-columns: 300px minmax(auto, 1fr);\r\n        padding: 0;\r\n        gap: 37px;\r\n    }\r\n\r\n    .slider-title-new {\r\n        font-family: Sora;\r\n        font-size: 24px;\r\n        font-weight: 600;\r\n        line-height: 32.4px;\r\n        text-align: left;\r\n    }\r\n\r\n    .switcher-section .domains-container-new {\r\n        column-gap: 40px;\r\n    }\r\n    \r\n    .slider-title-new h3{\r\n        padding-bottom: 30px;\r\n    }\r\n\r\n\r\n.domains__list-new {\r\n  max-width: 260px;\r\n  min-width: 260px;\r\n  padding-right: 0;\r\n}\r\n\r\n\/* max-height removed: it clipped slides taller than 435px *\/\r\n.domains__descriptions-new{\r\n  min-height: 435px;\r\n}\r\n\r\n.domains__list-new {\r\n  max-height: 435px;\r\n}\r\n\r\n}\r\n\r\n@media (max-width:820px){\r\n\r\n       .slider-image-block-new img {\r\n  height: 150px;\r\n}\r\n}\r\n\r\n\r\n\r\n@media (max-width: 767px) {\r\n\r\n    .slider-desc-new {\r\n        font-family: Karla;\r\n        font-size: 14px;\r\n        font-weight: 400;\r\n        line-height: 21px;\r\n        text-align: left;\r\n    }\r\n\r\n    \/* Mobile bullet box: 12px between items, 5px dot, 8px gap to text *\/\r\n    .slider-points-new {\r\n        gap: 12px;\r\n        padding: 20px;\r\n    }\r\n\r\n    .slider-points-new li {\r\n        padding-left: 13px;\r\n        font-size: 14px;\r\n        line-height: 21px;\r\n    }\r\n\r\n    .slider-points-new li::before {\r\n        top: 8px;\r\n        width: 5px;\r\n        height: 5px;\r\n    }\r\n\r\n    .domains-container-new {\r\n        display: none !important;\r\n        flex-direction: column;\r\n        gap: 40px;\r\n    }\r\n\r\n    .mobile-domains-new {\r\n        display: flex;\r\n        flex-direction: column;\r\n    }\r\n\r\n    a.slider-link-new{\r\n        font-size: 14px;\r\n        margin-top: 0;\r\n        margin-bottom: 0;\r\n    }\r\n\r\n    a.slider-link-new::after{\r\n        content: '';\r\n        width: 18px;\r\n        height: 18px;\r\n        left: calc(100% + 8px);\r\n    }\r\n}\r\n<\/style>\r\n\r\n<script>\r\n    document.addEventListener('DOMContentLoaded', () => {\r\n\r\n        \/\/ Local to this block, so other tab sections on the page can't overwrite it\r\n        let activateDesktopItem = null;\r\n\r\n        const mobileNavItems = document.querySelectorAll('.mobile-domains-navitem-new');\r\n\r\n        const domainsListItems = document.querySelectorAll(\r\n            '.domains__list-new.num1 li'\r\n        );\r\n        const toggle = document.querySelector('.domains-toggle');\r\n        const visibleCount = 7;\r\n\r\n        \/\/ hide rows 7+\r\n        if(toggle) {\r\n            mobileNavItems.forEach((row, index) => {\r\n                if (index >= visibleCount) row.classList.add(\"hidden\");\r\n            });\r\n\r\n            let expanded = false;\r\n\r\n            toggle.addEventListener(\"click\", () => {\r\n              expanded = !expanded;\r\n\r\n              mobileNavItems.forEach((row, index) => {\r\n                if (!expanded && index >= visibleCount) {\r\n                  row.classList.add(\"hidden\");\r\n                } else {\r\n                  row.classList.remove(\"hidden\");\r\n                }\r\n              });\r\n\r\n              toggle.textContent = expanded ? \"Show less\" : \"Show more\";\r\n            });\r\n        }\r\n\r\n        function showMobileItem(item) {\r\n            item.classList.add('active');\r\n\r\n            const content = item.querySelector('.mobile-domain-list-new');\r\n\r\n            if (content) {\r\n                content.style.transitionDuration = '0.5s';\r\n                content.style.maxHeight = content.scrollHeight + 100 + 'px';\r\n            }\r\n        }\r\n\r\n        function hideMobileItem(item) {\r\n            item.classList.remove('active');\r\n\r\n            const content = item.querySelector('.mobile-domain-list-new');\r\n\r\n            if (content) {\r\n                content.style.transitionDuration = '0.5s';\r\n                content.style.maxHeight = '0';\r\n            }\r\n        }\r\n\r\n        function activateMobileItem(index, canClose = true) {\r\n            const item = mobileNavItems[index];\r\n            const isActive = item.classList.contains('active');\r\n\r\n            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           if (domainsListItems.length > 0 && typeof activateDesktopItem === 'function') {\r\n                       activateDesktopItem(index);\r\n                    }\r\n                });\r\n            }\r\n        });\r\n\r\n        if (mobileNavItems.length > 0) {\r\n            activateMobileItem(0, false);\r\n            window.addEventListener('load', refreshOpenMobileItem);\r\n        }\r\n\r\n        let mobileResizeTimer;\r\n        window.addEventListener('resize', () => {\r\n            clearTimeout(mobileResizeTimer);\r\n            mobileResizeTimer = setTimeout(refreshOpenMobileItem, 150);\r\n        });\r\n\r\n        const domainsSwiperEl = document.querySelector('.domains__descriptions-new.num1');\r\n\r\n        if (domainsSwiperEl) {\r\n            const domainsSwiper = new Swiper('.domains__descriptions-new.num1', {\r\n                slidesPerView: 1,\r\n                spaceBetween: 24,\r\n                effect:'fade',\r\n                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elementor-element-78b1146 switcher-section elementor-widget elementor-widget-html\" data-id=\"78b1146\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"domains-container-new\">\r\n    <ul class=\"domains__list-new num1\">\r\n        <li class=\"active\">Education<\/li>\r\n        <li>Retail and e-commerce<\/li>\r\n        <li>Banking and finance<\/li>\r\n        <li>Healthcare<\/li>\r\n        <li>Manufacturing<\/li>\r\n        <li>Logistics and transportation<\/li>\r\n    <\/ul>\r\n\r\n    <div class=\"domains__descriptions-new num1\">\r\n      <div class=\"swiper-wrapper\">\r\n        <div class=\"swiper-slide swiper-slide-active\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Education<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Education platforms already have a lot of data: answers, attempts, response times, skipped tasks, course progress. The harder part is turning that into something useful without pretending a model understands a student better than a teacher does.<\/p>\r\n                        <p class=\"slider-desc-new\">Machine learning was already the <a href=\"\/blog\/machine-learning-for-education\/\">largest technology segment in the AI-in-education market<\/a> in 2025, with performance tracking, personalization, and intelligent tutoring among the main applications.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Adapt exercise difficulty and sequencing<\/strong> based on previous performance instead of forcing everyone through the same path.<\/li>\r\n                        <li><strong>Predict dropout risk<\/strong> from patterns such as declining participation, repeated failures, or long gaps between sessions.<\/li>\r\n                        <li><strong>Spot knowledge gaps earlier<\/strong> and schedule revision before the student reaches the next topic completely unprepared.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"swiper-slide\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Retail and e-commerce<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\"><a href=\"\/blog\/why-machine-learning-is-good-for-retail-ecommerce\/\">Retail has been using ML for years<\/a>, but the interesting changes are happening in speed and data variety. Forecasting can update more often, recommendations can use more than purchase history, and visual search can combine images with product descriptions and catalog data.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Forecast demand and automate replenishment<\/strong> using sales history, seasonality, promotions, and fresher operational data.<\/li>\r\n                        <li><strong>Personalize recommendations<\/strong> from browsing and buying behavior rather than static customer segments.<\/li>\r\n                        <li><strong>Improve product search<\/strong> by combining text and image data, which is useful when the customer doesn\u2019t know what the item is called but has a photo.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"swiper-slide\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Banking and finance<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Banking is where model monitoring, explainability, and drift become hard to ignore. Fraud patterns change, customer behavior changes, and a model that looked good six months ago can become very expensive very quickly.<\/p>\r\n                        <p class=\"slider-desc-new\">The global <strong><a href=\"\/blog\/ai-and-ml-in-banking-and-finance\/\">machine learning in banking<\/a> market was worth roughly $40 billion in 2025<\/strong> and is projected to reach around <strong>$150 billion by 2034<\/strong>, according to <a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-in-banking-market-119143\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a>.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Detect suspicious transactions<\/strong> and rank cases so investigators start with the ones that look most risky.<\/li>\r\n                        <li><strong>Explain <a href=\"\/blog\/ai-credit-scoring\/\">credit decisions<\/a><\/strong> by showing which factors had the strongest influence on a score.<\/li>\r\n                        <li><strong>Monitor model drift<\/strong> as fraud techniques, spending behavior, and customer profiles change.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"swiper-slide\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Healthcare<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Healthcare is one of those areas where a good benchmark number is nowhere near enough. Models can behave differently across hospitals, patient groups, devices, and clinical settings, so calibration and monitoring matter just as much as raw <a href=\"\/blog\/predictive-analytics-in-healthcare\/\">predictive performance<\/a>.<\/p>\r\n                        <p class=\"slider-desc-new\">The global healthcare predictive analytics market is estimated at <strong>$19.7 billion in 2026<\/strong> by <a href=\"https:\/\/www.grandviewresearch.com\/industry-analysis\/healthcare-predictive-analytics-market\" target=\"_blank\" rel=\"noopener noreferrer\">Grand View Research<\/a>, which expects it to reach <strong>$49.3 billion by 2033<\/strong>.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Identify early signs of deterioration<\/strong>, including sepsis risk, before the situation becomes obvious clinically.<\/li>\r\n                        <li><strong>Predict readmission risk<\/strong> and prioritize follow-up for patients more likely to return.<\/li>\r\n                        <li><strong>Rank cases for review<\/strong> so clinicians can focus attention where the predicted risk is highest.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"swiper-slide\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Manufacturing<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\"><a href=\"\/blog\/ai-in-manufacturing\/\">Manufacturing is probably the clearest case<\/a> for on-device ML. If a camera is checking parts moving down a line, there often isn\u2019t much sense in shipping every image to the cloud and waiting for a response.<\/p>\r\n                        <p class=\"slider-desc-new\">The broader AI-in-manufacturing market <a href=\"https:\/\/www.fortunebusinessinsights.com\/artificial-intelligence-ai-in-manufacturing-market-102824\" target=\"_blank\" rel=\"noopener noreferrer\">is estimated at <strong>$9.85 billion in 2026<\/strong><\/a>, with machine learning and computer vision used for predictive maintenance, inspection, quality control, and production planning.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Predict equipment failures<\/strong> from vibration, temperature, pressure, and maintenance history.<\/li>\r\n                        <li><a href=\"\/ai\/computer-vision\/\"><strong>Detect defects with computer vision<\/strong><\/a> while the product is still on the production line.<\/li>\r\n                        <li><strong>Predict product quality<\/strong> from manufacturing parameters before final inspection.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"swiper-slide\">\r\n            <div>\r\n                <div class=\"slider-title-new\">\r\n                    <h3>Logistics and transportation<\/h3>\r\n                <\/div>\r\n                <div class=\"slider-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Logistics is full of prediction problems, which makes it a natural ML playground: arrival times, delays, warehouse demand, traffic, route changes, missed connections.<\/p>\r\n                        <p class=\"slider-desc-new\">The <strong>machine learning in logistics market is estimated at $5.3 billion in 2026<\/strong> and projected to reach <strong>$44.5 billion by 2035<\/strong>, according to <a href=\"https:\/\/www.gminsights.com\/industry-analysis\/machine-learning-in-logistics-market?\" target=\"_blank\" rel=\"noopener noreferrer\">Global Market Insights<\/a>.<\/p>\r\n                        <p class=\"slider-desc-new\">Here, uncertainty matters too. \u201cETA 14:10\u201d and \u201cETA 14:10, but we\u2019re really not sure\u201d are two very different pieces of information for someone waiting at a loading dock.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Predict arrival times<\/strong> using historical delays, traffic conditions, and live vehicle positions.<\/li>\r\n                        <li><strong>Forecast shipment delays<\/strong> early enough to adjust warehouse or delivery plans.<\/li>\r\n                        <li><strong>Predict travel time and demand<\/strong> to support route planning and fleet allocation.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n      <\/div>\r\n    <\/div>\r\n<\/div>\r\n\r\n<div class=\"mobile-domains-new num1\">\r\n        <div class=\"mobile-domains-navitem-new active\" data-mobile-domain=\"domain-1\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Education<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Education platforms already have a lot of data: answers, attempts, response times, skipped tasks, course progress. The harder part is turning that into something useful without pretending a model understands a student better than a teacher does.<\/p>\r\n                        <p class=\"slider-desc-new\">Machine learning was already the <a href=\"\/blog\/machine-learning-for-education\/\">largest technology segment in the AI-in-education market<\/a> in 2025, with performance tracking, personalization, and intelligent tutoring among the main applications.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Adapt exercise difficulty and sequencing<\/strong> based on previous performance instead of forcing everyone through the same path.<\/li>\r\n                        <li><strong>Predict dropout risk<\/strong> from patterns such as declining participation, repeated failures, or long gaps between sessions.<\/li>\r\n                        <li><strong>Spot knowledge gaps earlier<\/strong> and schedule revision before the student reaches the next topic completely unprepared.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"mobile-domains-navitem-new\" data-mobile-domain=\"domain-2\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Retail and e-commerce<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\"><a href=\"\/blog\/why-machine-learning-is-good-for-retail-ecommerce\/\">Retail has been using ML for years<\/a>, but the interesting changes are happening in speed and data variety. Forecasting can update more often, recommendations can use more than purchase history, and visual search can combine images with product descriptions and catalog data.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Forecast demand and automate replenishment<\/strong> using sales history, seasonality, promotions, and fresher operational data.<\/li>\r\n                        <li><strong>Personalize recommendations<\/strong> from browsing and buying behavior rather than static customer segments.<\/li>\r\n                        <li><strong>Improve product search<\/strong> by combining text and image data, which is useful when the customer doesn\u2019t know what the item is called but has a photo.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"mobile-domains-navitem-new\" data-mobile-domain=\"domain-3\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Banking and finance<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Banking is where model monitoring, explainability, and drift become hard to ignore. Fraud patterns change, customer behavior changes, and a model that looked good six months ago can become very expensive very quickly.<\/p>\r\n                        <p class=\"slider-desc-new\">The global <strong><a href=\"\/blog\/ai-and-ml-in-banking-and-finance\/\">machine learning in banking<\/a> market was worth roughly $40 billion in 2025<\/strong> and is projected to reach around <strong>$150 billion by 2034<\/strong>, according to <a href=\"https:\/\/www.fortunebusinessinsights.com\/machine-learning-in-banking-market-119143\" target=\"_blank\" rel=\"noopener noreferrer\">Fortune Business Insights<\/a>.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Detect suspicious transactions<\/strong> and rank cases so investigators start with the ones that look most risky.<\/li>\r\n                        <li><strong>Explain <a href=\"\/blog\/ai-credit-scoring\/\">credit decisions<\/a><\/strong> by showing which factors had the strongest influence on a score.<\/li>\r\n                        <li><strong>Monitor model drift<\/strong> as fraud techniques, spending behavior, and customer profiles change.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"mobile-domains-navitem-new\" data-mobile-domain=\"domain-4\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Healthcare<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Healthcare is one of those areas where a good benchmark number is nowhere near enough. Models can behave differently across hospitals, patient groups, devices, and clinical settings, so calibration and monitoring matter just as much as raw <a href=\"\/blog\/predictive-analytics-in-healthcare\/\">predictive performance<\/a>.<\/p>\r\n                        <p class=\"slider-desc-new\">The global healthcare predictive analytics market is estimated at <strong>$19.7 billion in 2026<\/strong> by <a href=\"https:\/\/www.grandviewresearch.com\/industry-analysis\/healthcare-predictive-analytics-market\" target=\"_blank\" rel=\"noopener noreferrer\">Grand View Research<\/a>, which expects it to reach <strong>$49.3 billion by 2033<\/strong>.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Identify early signs of deterioration<\/strong>, including sepsis risk, before the situation becomes obvious clinically.<\/li>\r\n                        <li><strong>Predict readmission risk<\/strong> and prioritize follow-up for patients more likely to return.<\/li>\r\n                        <li><strong>Rank cases for review<\/strong> so clinicians can focus attention where the predicted risk is highest.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"mobile-domains-navitem-new\" data-mobile-domain=\"domain-5\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Manufacturing<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\"><a href=\"\/blog\/ai-in-manufacturing\/\">Manufacturing is probably the clearest case<\/a> for on-device ML. If a camera is checking parts moving down a line, there often isn\u2019t much sense in shipping every image to the cloud and waiting for a response.<\/p>\r\n                        <p class=\"slider-desc-new\">The broader AI-in-manufacturing market <a href=\"https:\/\/www.fortunebusinessinsights.com\/artificial-intelligence-ai-in-manufacturing-market-102824\" target=\"_blank\" rel=\"noopener noreferrer\">is estimated at <strong>$9.85 billion in 2026<\/strong><\/a>, with machine learning and computer vision used for predictive maintenance, inspection, quality control, and production planning.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Predict equipment failures<\/strong> from vibration, temperature, pressure, and maintenance history.<\/li>\r\n                        <li><a href=\"\/ai\/computer-vision\/\"><strong>Detect defects with computer vision<\/strong><\/a> while the product is still on the production line.<\/li>\r\n                        <li><strong>Predict product quality<\/strong> from manufacturing parameters before final inspection.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n        <div class=\"mobile-domains-navitem-new\" data-mobile-domain=\"domain-6\">\r\n            <h3 class=\"mobile-domains-navitem-new-title\">Logistics and transportation<\/h3>\r\n            <div class=\"mobile-domain-list-new\">\r\n                <div class=\"mobile-domain-content-new\">\r\n                    <div class=\"slider-text-new\">\r\n                        <p class=\"slider-desc-new\">Logistics is full of prediction problems, which makes it a natural ML playground: arrival times, delays, warehouse demand, traffic, route changes, missed connections.<\/p>\r\n                        <p class=\"slider-desc-new\">The <strong>machine learning in logistics market is estimated at $5.3 billion in 2026<\/strong> and projected to reach <strong>$44.5 billion by 2035<\/strong>, according to <a href=\"https:\/\/www.gminsights.com\/industry-analysis\/machine-learning-in-logistics-market?\" target=\"_blank\" rel=\"noopener noreferrer\">Global Market Insights<\/a>.<\/p>\r\n                        <p class=\"slider-desc-new\">Here, uncertainty matters too. \u201cETA 14:10\u201d and \u201cETA 14:10, but we\u2019re really not sure\u201d are two very different pieces of information for someone waiting at a loading dock.<\/p>\r\n                    <\/div>\r\n                    <ul class=\"slider-points-new\">\r\n                        <li><strong>Predict arrival times<\/strong> using historical delays, traffic conditions, and live vehicle positions.<\/li>\r\n                        <li><strong>Forecast shipment delays<\/strong> early enough to adjust warehouse or delivery plans.<\/li>\r\n                        <li><strong>Predict travel time and demand<\/strong> to support route planning and fleet allocation.<\/li>\r\n                    <\/ul>\r\n                <\/div>\r\n            <\/div>\r\n        <\/div>\r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0797d1a e-con-full e-flex e-con e-child\" data-id=\"0797d1a\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-210195c elementor-widget elementor-widget-shortcode\" data-id=\"210195c\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">\n    <div class=\"quote_shortcode-container\">\n                <div class=\"quote_shortcode-text\">\n            The model that wins the benchmark is not always the one I\u2019d put into production. Once you add latency, infrastructure cost, drift, and maintenance, a slightly less accurate model can easily become the better engineering decision.        <\/div>\n                <div class=\"quote_shortcode-bottom\">\n                            <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/03\/Dmitry-Nazarevich-1.png\" alt=\"Dmitry Nazarevich, CTO.\" class=\"quote_shortcode-img\">\n                        <div class=\"quote_shortcode-right\">\n                <a href=\"https:\/\/innowise.com\/pt\/authors\/dmitry-nazarevich\/\" class=\"quote_shortcode-name\">\n                    Dmitry Nazarevich                <\/a>\n                                <div class=\"quote_shortcode-position\">\n                    Chief Technology Officer                <\/div>\n                            <\/div>\n        <\/div>\n    <\/div>\n\n    <style>\n        .quote_shortcode-container{\n            background: #F6FAFE;\n            border: 1px solid #9CC6ED;\n            padding:60px;\n        }\n        .quote_shortcode-text{\n            font-family: Karla;\n            font-weight: 400;\n            font-style: Italic;\n            font-size: 22px;\n            line-height: 150%;\n            color:#2E2E2E;\n            margin-bottom:30px;\n        }\n        .quote_shortcode-bottom{\n            display:flex;\n            align-items:center;\n            gap:30px;\n        }\n        .quote_shortcode-container img.quote_shortcode-img{\n            width:80px;\n            height:80px;\n            max-width:80px;\n            border-radius:50%;\n            object-fit:cover;\n            display:block;\n        }\n        .quote_shortcode-right{\n\n        }   \n        .quote_shortcode-name{\n            font-family: Karla;\n            font-weight: 700;\n            font-size: 22px;\n            line-height: 32px;\n            margin-bottom:4px;\n            color:#2E2E2E;\n            transition:0.5s;\n            text-decoration:none!important;\n        }\n        .quote_shortcode-name:hover{\n            color:#C63031;\n            text-decoration:underline!important;\n        }\n        .quote_shortcode-position{\n            font-family: Karla;\n            font-weight: 400;\n            font-size: 18px;\n            line-height: 150%;\n            color:#585858;\n        }\n        @media(max-width:1280px){\n            .quote_shortcode-container{\n                padding:40px;\n            }\n        }\n        @media(max-width:768px){\n            .quote_shortcode-container{\n                padding:20px;\n            }\n            .quote_shortcode-text{\n                font-size:16px;\n                margin-bottom:20px;\n            }\n            .quote_shortcode-container img.quote_shortcode-img{\n                width:60px;\n                height:60px;\n                max-width:60px;\n            }\n            .quote_shortcode-name{\n                font-size:16px;\n            }\n            .quote_shortcode-position{\n                font-size:14px;\n            }\n        }\n    <\/style>\n\n    <\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-11bc71e e-con-full e-flex e-con e-child\" data-id=\"11bc71e\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-94a1175 elementor-widget elementor-widget-heading\" data-id=\"94a1175\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Machine learning future trends<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8516670 translation-block elementor-widget elementor-widget-text-editor\" data-id=\"8516670\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Some ML ideas are already useful today. Others still need better benchmarks, cheaper compute, or a few unpleasant encounters with production before I\u2019d call them ready.<\/span><\/p><p><span style=\"font-weight: 400;\">These are the <\/span><span style=\"font-weight: 400;\">emerging trends in machine learning<\/span><span style=\"font-weight: 400;\"> I\u2019d keep watching.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-1e53efd e-con-full e-flex e-con e-child\" data-id=\"1e53efd\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7ba1a0a elementor-widget elementor-widget-html\" data-id=\"7ba1a0a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\r\n    .points-block {\r\n      --color-dark: #2e2e2e;\r\n      --color-red: #c63031;\r\n      --color-light-bg: #fbfbfd;\r\n    }\r\n\r\n    .points-block {\r\n      box-sizing: border-box;\r\n      color: var(--color-dark);\r\n    }\r\n\r\n    .points-block *,\r\n    .points-block *::before,\r\n    .points-block *::after {\r\n      box-sizing: border-box;\r\n    }\r\n\r\n    .points-block__list {\r\n      display: flex;\r\n      flex-direction: column;\r\n      gap: 40px;\r\n      margin: 0;\r\n      padding: 0;\r\n      list-style: none;\r\n    }\r\n\r\n    .points-block__item {\r\n      display: flex;\r\n      flex-direction: column;\r\n      gap: 20px;\r\n    }\r\n\r\n    .points-block__head {\r\n      display: flex;\r\n      align-items: center;\r\n      gap: 20px;\r\n    }\r\n\r\n    .points-block__icon {\r\n      flex-shrink: 0;\r\n      display: block;\r\n      width: 44px;\r\n      height: 44px;\r\n    }\r\n\r\n    .points-block__title {\r\n      margin: 0;\r\n      font-family: \"Sora\", Arial, sans-serif;\r\n      font-weight: 600;\r\n      font-size: 24px;\r\n      line-height: 1.35;\r\n      color: var(--color-dark);\r\n    }\r\n\r\n    .points-block__text p {\r\n 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width: 44px;\r\n        height: 44px;\r\n      }\r\n\r\n      .points-block__title {\r\n        font-size: 18px;\r\n        line-height: 1.3;\r\n      }\r\n\r\n      .points-block__text p {\r\n        font-size: 16px;\r\n        line-height: 1.4;\r\n      }\r\n\r\n      .points-block__text p + p {\r\n        margin-top: 12px;\r\n      }\r\n    }\r\n  <\/style>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6bc40e0 elementor-widget elementor-widget-html\" data-id=\"6bc40e0\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<section class=\"points-block\">\r\n  <ul class=\"points-block__list\">\r\n    <li class=\"points-block__item\">\r\n      <div class=\"points-block__head\">\r\n        <img loading=\"lazy\" decoding=\"async\" class=\"points-block__icon\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/09\/526.svg\" alt=\"Cross-domain generalization and adaptation icon.\" width=\"44\" height=\"44\" loading=\"lazy\">\r\n        <h3 class=\"points-block__title\">Cross-domain generalization and adaptation<\/h3>\r\n      <\/div>\r\n      <div class=\"points-block__text\">\r\n        <p class=\"translation-block\">One of ML\u2019s oldest problems is still very much alive: train a model in one environment, move it somewhere slightly different, watch performance drop.<\/p>\r\n        <p class=\"translation-block\">Domain generalization tries to make models hold up on data distributions they haven\u2019t seen before. <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0165168426001398\" target=\"_blank\" rel=\"noopener noreferrer\">A 2026 study<\/a> on pattern classification in unseen environments describes exactly this problem: changes in sensors, acquisition conditions, or other domain characteristics can be enough to hurt a model badly.<\/p>\r\n        <p class=\"translation-block\">The practical version is easy to imagine. A vision model trained in one factory has to work in another factory with different cameras. A medical model moves to another hospital. A fraud model sees a new customer population.<\/p>\r\n        <p class=\"translation-block\">I suspect this will become less of a research specialty and more of a basic deployment requirement.<\/p>\r\n      <\/div>\r\n    <\/li>\r\n\r\n    <li class=\"points-block__item\">\r\n      <div class=\"points-block__head\">\r\n        <img loading=\"lazy\" decoding=\"async\" class=\"points-block__icon\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/ml.svg\" alt=\"Continual learning icon.\" width=\"44\" height=\"44\" loading=\"lazy\">\r\n        <h3 class=\"points-block__title\">Continual learning<\/h3>\r\n      <\/div>\r\n      <div class=\"points-block__text\">\r\n        <p class=\"translation-block\">Most production models still learn in chunks: collect new data, retrain, validate, deploy again.<\/p>\r\n        <p class=\"translation-block\">Continual learning aims for something smoother. The model keeps learning as new data arrives without forgetting what it knew before.<\/p>\r\n        <p class=\"translation-block\">That last part is the catch.<\/p>\r\n        <p class=\"translation-block\"><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0893608025011074\" target=\"_blank\" rel=\"noopener noreferrer\">A 2026 systematic review<\/a> of <strong>189 peer-reviewed continual-learning papers<\/strong> still identifies catastrophic forgetting as one of the field\u2019s central problems: learning something new can damage performance on older tasks.<\/p>\r\n        <p class=\"translation-block\">So I wouldn\u2019t replace scheduled retraining with continual learning just because the name sounds better. But for fraud detection, industrial systems, recommendations, and other environments that change constantly, the appeal is obvious.<\/p>\r\n      <\/div>\r\n    <\/li>\r\n\r\n    <li class=\"points-block__item\">\r\n      <div class=\"points-block__head\">\r\n        <img loading=\"lazy\" decoding=\"async\" class=\"points-block__icon\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/07\/425.svg\" alt=\"Hybrid ML models icon.\" width=\"44\" height=\"44\" loading=\"lazy\">\r\n        <h3 class=\"points-block__title\">Hybrid ML models<\/h3>\r\n      <\/div>\r\n      <div class=\"points-block__text\">\r\n        <p class=\"translation-block\">There is something slightly funny about spending years trying to make neural networks learn everything from data, only to discover that known physics can still be useful.<\/p>\r\n        <p class=\"translation-block\">Google\u2019s <strong>NeuralGCM<\/strong> is a good example. It combines machine learning with a physics-based atmospheric solver rather than asking either one to do the whole job. In <a href=\"https:\/\/www.nature.com\/articles\/s41586-024-07744-y\" target=\"_blank\" rel=\"noopener noreferrer\">research published in <em>Nature<\/em><\/a>, the model produced competitive weather and climate forecasts while using <strong>three to five orders of magnitude fewer computational resources<\/strong> than comparable conventional models.<\/p>\r\n        <p class=\"translation-block\">That idea goes far beyond weather.<\/p>\r\n        <p class=\"translation-block\">If we already know physical constraints, engineering rules, or other domain relationships, feeding them into the model can make more sense than asking a neural network to rediscover gravity from a spreadsheet.<\/p>\r\n      <\/div>\r\n    <\/li>\r\n\r\n    <li class=\"points-block__item\">\r\n      <div class=\"points-block__head\">\r\n        <img loading=\"lazy\" decoding=\"async\" class=\"points-block__icon\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/08\/447.svg\" alt=\"Causal ML icon.\" width=\"44\" height=\"44\" loading=\"lazy\">\r\n        <h3 class=\"points-block__title\">Causal ML<\/h3>\r\n      <\/div>\r\n      <div class=\"points-block__text\">\r\n        <p class=\"translation-block\">Prediction answers questions such as:<\/p>\r\n        <p class=\"translation-block\"><em>Who is likely to churn?<\/em><\/p>\r\n        <p class=\"translation-block\">Businesses usually want the next question:<\/p>\r\n        <p class=\"translation-block\"><em>Who will stay if we give them a discount?<\/em><\/p>\r\n        <p class=\"translation-block\">That is a causal question.<\/p>\r\n        <p class=\"translation-block\"><a href=\"https:\/\/www.nature.com\/articles\/s41591-024-02902-1\" target=\"_blank\" rel=\"noopener noreferrer\">Causal ML combines machine learning<\/a> with causal inference to estimate what may happen under different interventions. The field is already being used to estimate individualized treatment effects in medicine, although researchers still warn that incorrect assumptions and confounding can produce convincing but wrong conclusions.<\/p>\r\n        <p class=\"translation-block\">I think this is one of the more interesting directions here because it changes what the model is for. Prediction describes a likely future. Causal ML tries to tell you whether doing something will change it.<\/p>\r\n        <p class=\"translation-block\">Much harder problem.<\/p>\r\n        <p class=\"translation-block\">Much more useful one.<\/p>\r\n      <\/div>\r\n    <\/li>\r\n\r\n    <li class=\"points-block__item\">\r\n      <div class=\"points-block__head\">\r\n        <img loading=\"lazy\" decoding=\"async\" class=\"points-block__icon\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/11\/Icon-44.svg\" alt=\"Uncertainty-aware predictions icon.\" width=\"44\" height=\"44\" loading=\"lazy\">\r\n        <h3 class=\"points-block__title\">Uncertainty-aware predictions<\/h3>\r\n      <\/div>\r\n      <div class=\"points-block__text\">\r\n        <p class=\"translation-block\">A model saying \u201c92% confidence\u201d feels reassuring.<\/p>\r\n        <p class=\"translation-block\">It may also be nonsense.<\/p>\r\n        <p class=\"translation-block\">Uncertainty calibration tries to make confidence line up with real predictive accuracy. Research published in <a href=\"https:\/\/www.nature.com\/articles\/s42256-026-01215-x\" target=\"_blank\" rel=\"noopener noreferrer\"><em>Nature Machine Intelligence<\/em><\/a> in 2026 describes calibration as essential for reliable ML deployment precisely because modern models can be highly confident while being wrong.<\/p>\r\n        <p class=\"translation-block\">Distribution shift makes this worse. <a href=\"https:\/\/www.nature.com\/articles\/s41598-025-32656-w\" target=\"_blank\" rel=\"noopener noreferrer\">A 2026 <em>Scientific Reports<\/em><\/a> study found that predictive models can lose both performance and calibration when moved across heterogeneous real-world datasets.<\/p>\r\n        <p class=\"translation-block\">For businesses, the useful outcome isn\u2019t a model that always gives an answer. Sometimes the better model is the one that says, in effect, <em>I\u2019m not very sure about this one, give it to a human.<\/em><\/p>\r\n        <p class=\"translation-block\">I\u2019d like to see much more of that.<\/p>\r\n      <\/div>\r\n    <\/li>\r\n  <\/ul>\r\n<\/section>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-99a9034 e-con-full e-flex e-con e-child\" data-id=\"99a9034\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-1accdf4 e-con-full e-flex e-con e-child\" data-id=\"1accdf4\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c908d71 elementor-widget-tablet__width-inherit elementor-widget__width-initial max100 elementor-widget elementor-widget-heading\" data-id=\"c908d71\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Need help choosing the right ML approach?<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-8ae131a e-con-full e-flex e-con e-child\" data-id=\"8ae131a\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3f5c5a7 elementor-absolute elementor-widget-mobile__width-inherit transform elementor-widget elementor-widget-html\" data-id=\"3f5c5a7\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"wave-container\"><\/div>\r\n\r\n<style>\r\n  .wave-container {\r\n    width: 400px;\r\n    height: 400px;\r\n  }\r\n\r\n  @media(max-width: 767px) {\r\n    .wave-container {\r\n      width: 100%;\r\n      height: 100%;\r\n    }\r\n  }\r\n\r\n\r\n  .wave {\r\n    position: absolute;\r\n    border: 1px solid rgba(210, 184, 214, 1);\r\n    border-radius: 50%;\r\n    animation: drop 16s infinite;\r\n    top: 50%;\r\n    left: 50%;\r\n    transform: translate(-50%, -50%);\r\n    box-sizing: border-box;\r\n  }\r\n\r\n  @keyframes drop {\r\n    0% {\r\n      width: 0px;\r\n      height: 0px;\r\n      border: 1px solid rgba(210, 184, 214, 1);\r\n    }\r\n\r\n    100% {\r\n      width: 400px;\r\n      height: 400px;\r\n      border: 1px solid rgba(210, 184, 214, 0);\r\n    }\r\n  }\r\n<\/style>\r\n\r\n<script>\r\n\r\n  document.addEventListener('DOMContentLoaded', () => {\r\n    function createWaves(numberOfWaves) {\r\n      const waveContainers = document.querySelectorAll('.wave-container');\r\n\r\n      waveContainers.forEach((waveContainer) => {\r\n        for (let i = 0; i < numberOfWaves; i++) {\r\n          const wave = document.createElement('div');\r\n          wave.classList.add('wave');\r\n\r\n          wave.style.animationDelay = `${i * 0.8}s`;\r\n\r\n          waveContainer.appendChild(wave);\r\n        }\r\n      });\r\n    }\r\n\r\n    createWaves(10)\r\n  });\r\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cb713d elementor-align-left elementor-widget__width-initial elementor-widget-mobile__width-inherit cta-btn elementor-widget elementor-widget-button\" data-id=\"5cb713d\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#contact-form\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Get ML consulting<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-337a4b7 e-con-full e-flex e-con e-child\" data-id=\"337a4b7\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b734859 elementor-widget elementor-widget-heading\" data-id=\"b734859\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Next steps: how businesses can implement ML technology trends<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3b8a67c elementor-widget elementor-widget-text-editor\" data-id=\"3b8a67c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The worst way to use this list is to pick a trend because it sounds current and then go looking for a problem to attach it to.<\/span><\/p><p><span style=\"font-weight: 400;\">Start with the annoying business problem instead.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-86d4dfb e-con-full e-flex e-con e-child\" data-id=\"86d4dfb\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b79424b elementor-element-5acb955 custom-roadmap elementor-widget elementor-widget-html\" data-id=\"b79424b\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\n.blog-roadmap {\n    display: flex;\n    flex-direction: column;\n\n    width: 100%;\n}\n\n.blog-roadmap p {\n    margin: 0 !important;\n}\n\n\n.blog-roadmap-item {\n    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.blog-roadmap-item-mobile__side-arrow-wrapper {\n\n    display: flex;\n    align-items: end;\n\n    align-self: stretch;\n\n    position: relative;\n}\n\n.blog-roadmap-item-mobile .side-arrow--closed {\n    display: flex;\n    transform:translateX(-50%);\n\n    opacity: 0.2;\n}\n.blog-roadmap-item-mobile .side-arrow--open {\n    display: none;\n}\n\n.blog-roadmap-item-mobile.active .side-arrow--closed {\n    display: none;\n}\n.blog-roadmap-item-mobile.active .side-arrow--open {\n    display: flex;\n\n    position: absolute;\n    transform:translateX(-50%);\n    \n    opacity: 1;\n\n    bottom: 0;\n}\n\n\n\n@media (max-width: 767px) {\n    \n    \n    .blog-roadmap {\n        display: none;\n    }\n    .blog-roadmap-mobile {\n        display: flex;\n        flex-direction: column;\n\n        width: 100%;\n    }\n}\n<\/style>\n\n<script>\n\n    document.addEventListener('DOMContentLoaded', () => {\n      const mobileRoadmapItems = [...document.querySelectorAll('.blog-roadmap-item-mobile')];\n  \n      mobileRoadmapItems.forEach(item => {\n\n        item.addEventListener('click', () => {\n          const isActive = item.classList.contains('active');\n  \n          \/\/ Collapse all items\n          mobileRoadmapItems.forEach(nav => {\n            nav.classList.remove('active');\n            \/*const ul = nav.querySelector('.mobile-domain-list');\n            if (ul) ul.style.maxHeight = '0';*\/\n          });\n  \n          \/\/ Expand clicked item only if it was not active\n          if (!isActive) {\n            item.classList.add('active');\n            \/*const ul = item.querySelector('.mobile-domain-list');\n            if (ul) ul.style.maxHeight = \"unset\"; \/\/ul.scrollHeight + 'px';*\/\n          }\n        });\n        \n      });\n    });\n  \n<\/script>\n\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-56c557e elementor-widget elementor-widget-html\" data-id=\"56c557e\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"blog-roadmap\">\r\n    \r\n    <div class=\"blog-roadmap-item\">\r\n        <div class=\"blog-roadmap-item__title\">\r\n            <div class=\"blog-roadmap-item__title__num-block\">\r\n                <span class=\"blog-roadmap-item__title__num-block__num\">01<\/span>\r\n                <img decoding=\"async\" class=\"blog-roadmap-item__title__num-block__arrow\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" \/ alt=\"\">\r\n            <\/div>\r\n            <span class=\"blog-roadmap-item__title__text-block\">Define what needs to improve<\/span>\r\n        <\/div>\r\n        <div class=\"blog-roadmap-item__content\">\r\n            <p>More accurate forecasts? Fewer false fraud alerts? Lower inference cost? Faster inspection? Pick the outcome first and keep the current process as a baseline.<\/p>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item\">\r\n        <div class=\"blog-roadmap-item__title\">\r\n            <div class=\"blog-roadmap-item__title__num-block\">\r\n                <span class=\"blog-roadmap-item__title__num-block__num\">02<\/span>\r\n                <img decoding=\"async\" class=\"blog-roadmap-item__title__num-block__arrow\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" \/ alt=\"\">\r\n            <\/div>\r\n            <span class=\"blog-roadmap-item__title__text-block\">Check whether the data can support it<\/span>\r\n        <\/div>\r\n        <div class=\"blog-roadmap-item__content\">\r\n            <p>Before comparing models, look at labels, missing values, access rights, class imbalance, coverage, and whether production data will resemble the data used for training. This is also where a lot of ML projects become less exciting very quickly.<\/p>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item\">\r\n        <div class=\"blog-roadmap-item__title\">\r\n            <div class=\"blog-roadmap-item__title__num-block\">\r\n                <span class=\"blog-roadmap-item__title__num-block__num\">03<\/span>\r\n                <img decoding=\"async\" class=\"blog-roadmap-item__title__num-block__arrow\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" \/ alt=\"\">\r\n            <\/div>\r\n            <span class=\"blog-roadmap-item__title__text-block\">Compare the new thing with the boring thing<\/span>\r\n        <\/div>\r\n        <div class=\"blog-roadmap-item__content\">\r\n            <p>If a pretrained model, AutoML system, or multimodal architecture is under consideration, test it against a simpler baseline under the same conditions. Same data, same metrics, same latency limits, same business objective.<\/p>\r\n            <p>If the complicated model wins by 0.3% and costs four times more to run, I\u2019d want a very good reason for keeping it.<\/p>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item\">\r\n        <div class=\"blog-roadmap-item__title\">\r\n            <div class=\"blog-roadmap-item__title__num-block\">\r\n                <span class=\"blog-roadmap-item__title__num-block__num\">04<\/span>\r\n                <img decoding=\"async\" class=\"blog-roadmap-item__title__num-block__arrow\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" \/ alt=\"\">\r\n            <\/div>\r\n            <span class=\"blog-roadmap-item__title__text-block\">Pilot it where failure is survivable<\/span>\r\n        <\/div>\r\n        <div class=\"blog-roadmap-item__content\">\r\n            <p>Use representative data and test the cases most likely to cause trouble: missing inputs, rare classes, unusual devices, weaker customer segments, peak loads. Decide in advance what would make you stop the pilot.<\/p>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item\">\r\n        <div class=\"blog-roadmap-item__title\">\r\n            <div class=\"blog-roadmap-item__title__num-block\">\r\n                <span class=\"blog-roadmap-item__title__num-block__num\">05<\/span>\r\n            <\/div>\r\n            <span class=\"blog-roadmap-item__title__text-block\">Give the model an owner after launch<\/span>\r\n        <\/div>\r\n        <div class=\"blog-roadmap-item__content\">\r\n            <p>Someone needs to watch drift, latency, cost, calibration, subgroup performance, and the business metric the model was supposed to improve. Also decide when to retrain it, roll it back, replace it, or simply switch it off.<\/p>\r\n            <p>And yes, sometimes the right conclusion is that the new ML trend doesn\u2019t improve enough to justify changing anything.<\/p>\r\n            <p>That counts as a successful evaluation too.<\/p>\r\n        <\/div>\r\n    <\/div>\r\n\r\n<\/div>\r\n\r\n<div class=\"blog-roadmap-mobile\">\r\n\r\n    <div class=\"blog-roadmap-item-mobile active\">\r\n\r\n        <div class=\"blog-roadmap-item-mobile__side-arrow-wrapper\">\r\n            <img decoding=\"async\" class=\"side-arrow--open\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/Line-404-2.svg\" alt=\"arrow-icon.\" \/>\r\n\r\n            <img decoding=\"async\" class=\"side-arrow--closed\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" alt=\"arrow-icon.\" \/>\r\n        <\/div>\r\n\r\n        <div class=\"blog-roadmap-item-mobile__main-wrapper\">\r\n            <div class=\"blog-roadmap-item-mobile__title\">\r\n                <span class=\"blog-roadmap-item-mobile__title__num\">01<\/span>\r\n                <span class=\"blog-roadmap-item-mobile__title__text\">Define what needs to improve<\/span>\r\n            <\/div>\r\n            <div class=\"blog-roadmap-item-mobile__content\">\r\n                <p>More accurate forecasts? Fewer false fraud alerts? Lower inference cost? Faster inspection? Pick the outcome first and keep the current process as a baseline.<\/p>\r\n            <\/div>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item-mobile\">\r\n\r\n        <div class=\"blog-roadmap-item-mobile__side-arrow-wrapper\">\r\n            <img decoding=\"async\" class=\"side-arrow--open\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/Line-404-2.svg\" alt=\"arrow-icon.\" \/>\r\n\r\n            <img decoding=\"async\" class=\"side-arrow--closed\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" alt=\"arrow-icon.\" \/>\r\n        <\/div>\r\n\r\n        <div class=\"blog-roadmap-item-mobile__main-wrapper\">\r\n            <div class=\"blog-roadmap-item-mobile__title\">\r\n                <span class=\"blog-roadmap-item-mobile__title__num\">02<\/span>\r\n                <span class=\"blog-roadmap-item-mobile__title__text\">Check whether the data can support it<\/span>\r\n            <\/div>\r\n            <div class=\"blog-roadmap-item-mobile__content\">\r\n                <p>Before comparing models, look at labels, missing values, access rights, class imbalance, coverage, and whether production data will resemble the data used for training. This is also where a lot of ML projects become less exciting very quickly.<\/p>\r\n            <\/div>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item-mobile\">\r\n\r\n        <div class=\"blog-roadmap-item-mobile__side-arrow-wrapper\">\r\n            <img decoding=\"async\" class=\"side-arrow--open\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/Line-404-2.svg\" alt=\"arrow-icon.\" \/>\r\n\r\n            <img decoding=\"async\" class=\"side-arrow--closed\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" alt=\"arrow-icon.\" \/>\r\n        <\/div>\r\n\r\n        <div class=\"blog-roadmap-item-mobile__main-wrapper\">\r\n            <div class=\"blog-roadmap-item-mobile__title\">\r\n                <span class=\"blog-roadmap-item-mobile__title__num\">03<\/span>\r\n                <span class=\"blog-roadmap-item-mobile__title__text\">Compare the new thing with the boring thing<\/span>\r\n            <\/div>\r\n            <div class=\"blog-roadmap-item-mobile__content\">\r\n                <p>If a pretrained model, AutoML system, or multimodal architecture is under consideration, test it against a simpler baseline under the same conditions. Same data, same metrics, same latency limits, same business objective.<\/p>\r\n                <p>If the complicated model wins by 0.3% and costs four times more to run, I\u2019d want a very good reason for keeping it.<\/p>\r\n            <\/div>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item-mobile\">\r\n\r\n        <div class=\"blog-roadmap-item-mobile__side-arrow-wrapper\">\r\n            <img decoding=\"async\" class=\"side-arrow--open\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/Line-404-2.svg\" alt=\"arrow-icon.\" \/>\r\n\r\n            <img decoding=\"async\" class=\"side-arrow--closed\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" alt=\"arrow-icon.\" \/>\r\n        <\/div>\r\n\r\n        <div class=\"blog-roadmap-item-mobile__main-wrapper\">\r\n            <div class=\"blog-roadmap-item-mobile__title\">\r\n                <span class=\"blog-roadmap-item-mobile__title__num\">04<\/span>\r\n                <span class=\"blog-roadmap-item-mobile__title__text\">Pilot it where failure is survivable<\/span>\r\n            <\/div>\r\n            <div class=\"blog-roadmap-item-mobile__content\">\r\n                <p>Use representative data and test the cases most likely to cause trouble: missing inputs, rare classes, unusual devices, weaker customer segments, peak loads. Decide in advance what would make you stop the pilot.<\/p>\r\n            <\/div>\r\n        <\/div>\r\n    <\/div>\r\n\r\n    <div class=\"blog-roadmap-item-mobile\">\r\n\r\n        <div class=\"blog-roadmap-item-mobile__side-arrow-wrapper\">\r\n            <img decoding=\"async\" class=\"side-arrow--open\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/Line-404-2.svg\" alt=\"arrow-icon.\" \/>\r\n\r\n            <img decoding=\"async\" class=\"side-arrow--closed\" src=\"https:\/\/i.ibb.co\/t4Px1j6\/Rectangle-784-2.png\" alt=\"arrow-icon.\" \/>\r\n        <\/div>\r\n\r\n        <div class=\"blog-roadmap-item-mobile__main-wrapper\">\r\n            <div class=\"blog-roadmap-item-mobile__title\">\r\n                <span class=\"blog-roadmap-item-mobile__title__num\">05<\/span>\r\n                <span class=\"blog-roadmap-item-mobile__title__text\">Give the model an owner after launch<\/span>\r\n            <\/div>\r\n            <div class=\"blog-roadmap-item-mobile__content\">\r\n                <p>Someone needs to watch drift, latency, cost, calibration, subgroup performance, and the business metric the model was supposed to improve. Also decide when to retrain it, roll it back, replace it, or simply switch it off.<\/p>\r\n                <p>And yes, sometimes the right conclusion is that the new ML trend doesn\u2019t improve enough to justify changing anything.<\/p>\r\n                <p>That counts as a successful evaluation too.<\/p>\r\n            <\/div>\r\n        <\/div>\r\n    <\/div>\r\n    \r\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6c7a13a e-con-full e-flex e-con e-child\" data-id=\"6c7a13a\" data-element_type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-e6acc88 e-con-full e-flex e-con e-child\" data-id=\"e6acc88\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5a1539f elementor-widget elementor-widget-heading\" data-id=\"5a1539f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Machine learning applications and trends in practice: Innowise case studies<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b3f0640 elementor-widget elementor-widget-html\" data-id=\"b3f0640\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<style>\n    a.cases-link{\n        display: inline-block;\n        font-family: Sora;\n        font-weight: 600;\n        font-size: 18px;\n        line-height: 130%;\n        color: #191B1D;\n        padding-bottom: 8px;\n        text-decoration: none;\n        border-bottom: 1px solid #191B1D;\n    }\n    \n    a.cases-link:hover, a.cases-link:active{\n        color: #C63031;\n        border-color: #C63031;\n    }\n    \n    @media (max-width: 767px){\n        a.cases-link{\n            font-size: 16px;\n            padding-bottom: 6px;\n        }\n    }\n<\/style>\n<a href=\"\/cases\/\" class=\"cases-link\">All case studies<\/a>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8f3865d elementor-widget__width-inherit elementor-widget elementor-widget-shortcode\" data-id=\"8f3865d\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">    <div class=\"case-slider-v2-wrap case-slider-v2-wrap-blog\">\n        <div class=\"case-slider-v2\">\n            <div class=\"swiper\">\n                <div class=\"swiper-wrapper\">\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                                                        <a href=\"\/pt\/cases\/saude\/\" class=\"only\">Healthcare<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            AI dermatologist skin scanner app development                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            An AI app we built uses deep learning and image recognition to quickly assess skin conditions, giving preliminary diagnoses based on photos.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>30<\/b>\n                                                                                                <span>dermatological conditions supported<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ai-skin-scanner-app\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ai-skin-scanner-app\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                                        <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2025\/01\/ai-skin-scanner-app.jpg\" alt=\"AI dermatologist skin scanner app..\">\n                                        \n                <\/div>\n                            <\/div>\n            <\/div>\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                                                        <a href=\"\/pt\/cases\/saude\/\" class=\"only\">Healthcare<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            Building an AI remote patient monitoring system                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            We built a wound care app as part of the remote patient monitoring software and implemented an AI-driven analysis for accurate assessment.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>2-tier<\/b>\n                                                                                                <span>user role system<\/span>\n                                                            <\/div>\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>100%<\/b>\n                                                                                                <span>system compliance<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/remote-patient-monitoring-software\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/remote-patient-monitoring-software\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                                        <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2023\/10\/Remote-patient-monitoring-software-small-cover.jpg\" alt=\"Remote patient monitoring software..\">\n                                        \n                <\/div>\n                            <\/div>\n            <\/div>\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                            <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/10\/Medspa-logo.svg\" alt=\"MedSpa Network website redesign and rebuild.\">\n                                                                                        <a href=\"\/pt\/cases\/saude\/\" class=\"\">Healthcare<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            MedSpa Network website redesign and rebuild                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            Innowise rebuilt MedSpa Network\u2019s website on WordPress, giving its team control over day-to-day content updates.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>2<\/b>\n                                                                                                <span>months from kickoff to launch<\/span>\n                                                            <\/div>\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>3-5<\/b>\n                                                                                                <span>leads per week up from 1 per month<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/medspa-network-website-rebuild\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                                <div class=\"case-slider-v2-card-a\" role=\"button\" tabindex=\"0\">Client review<\/div>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/medspa-network-website-rebuild\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                                <div class=\"case-slider-v2-card-a\" role=\"button\" tabindex=\"0\">\n                            <img decoding=\"async\" src=\"\/wp-content\/uploads\/2026\/10\/icon.svg\" alt=\"Client review logo.\">\n                            Client review\n                            \n                        <\/div>\n                                            <\/div>\n                                        <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/10\/MedSpa-Network-Website-Redesign.png\" alt=\"MedSpa Network website redesign and rebuild.\">\n                                        \n                <\/div>\n                                <div class=\"case-slider-v2-pdf-source\" hidden>\n                        <div id=\"pdf_6af773f7a5943\" class=\"js-pdf-viewer\" data-pdf-url=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/10\/Referral-Letter_MedSpa-Network.pdf\"><\/div>\n    \n    <script>\n    (function() {\n        function waitForPDF(callback) {\n            if (typeof pdfjsLib !== 'undefined') {\n                callback();\n            } else {\n                setTimeout(function() { waitForPDF(callback); }, 100);\n            }\n        }\n        \n        waitForPDF(function() {\n            var container = document.getElementById('pdf_6af773f7a5943');\n            var pdfUrl = container.getAttribute('data-pdf-url');\n            \n            pdfjsLib.GlobalWorkerOptions.workerSrc = 'https:\/\/cdnjs.cloudflare.com\/ajax\/libs\/pdf.js\/2.16.105\/pdf.worker.min.js';\n            \n            pdfjsLib.getDocument(pdfUrl).promise.then(function(pdf) {\n                var renderPage = function(pageNum) {\n                    return pdf.getPage(pageNum).then(function(page) {\n                        var canvas = document.createElement('canvas');\n                        canvas.style.width = '100%';\n                        canvas.style.display = 'block';\n                        container.appendChild(canvas);\n\n                        var viewport = page.getViewport({ scale: 1.5 });\n                        canvas.width = viewport.width;\n                        canvas.height = viewport.height;\n\n                        return page.render({\n                            canvasContext: canvas.getContext('2d'),\n                            viewport: viewport\n                        }).promise;\n                    });\n                };\n\n                var chain = Promise.resolve();\n                for (var i = 1; i <= pdf.numPages; i++) {\n                    (function(pageNum) {\n                        chain = chain.then(function() {\n                            return renderPage(pageNum);\n                        });\n                    })(i);\n                }\n            });\n        });\n    })();\n    <\/script>\n                    <\/div>\n                            <\/div>\n            <\/div>\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                            <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/10\/TBCBank-logo.svg\" alt=\"AI bot for TBC Bank marketing campaign.\">\n                                                                                        <a href=\"\/pt\/cases\/ai\/\" class=\"\">AI<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            AI bot for TBC Bank marketing campaign                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            Innowise built a bilingual Telegram bot that generates AI selfies with TBC Bank&#039;s football-star brand ambassador.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>3,000<\/b>\n                                                                                                <span>users engaged<\/span>\n                                                            <\/div>\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>2<\/b>\n                                                                                                <span>languages supported<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ai-telegram-bot\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                                <div class=\"case-slider-v2-card-a\" role=\"button\" tabindex=\"0\">Client review<\/div>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ai-telegram-bot\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                    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class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                                                        <a href=\"\/pt\/cases\/ecommerce\/\" class=\"only\">E-commerce<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            Defining the product strategy for Bitlendex&#8217;s bitcoin lending platform                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            Innowise conducted a discovery phase for Bitlendex, helping the client transform an early-stage product concept into a validated business model and clearly defined MVP.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>1 month<\/b>\n                                                                                                <span>for a full discovery phase<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/product-discovery-for-bitcoin-lending-platform\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/product-discovery-for-bitcoin-lending-platform\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                                        <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/10\/Product-Discovery-for-Bitcoin-Lending-Platform-Innowise.png\" alt=\"Defining the product strategy for Bitlendex&#8217;s bitcoin lending platform.\">\n                                        \n                <\/div>\n                            <\/div>\n            <\/div>\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                        <div class=\"case-slider-v2-card-logo\">\n                                                            <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/09\/Bonnfinanz-logo-1.svg\" alt=\"Financial advisory system for Bonnfinanz.\">\n                                                                                        <a href=\"\/pt\/cases\/fintech\/\" class=\"\">FinTech<\/a>\n                                                    <\/div>\n                        <div class=\"case-slider-v2-card-title\">\n                            Financial advisory system for Bonnfinanz                        <\/div>\n                                                <div class=\"case-slider-v2-card-text\">\n                            Innowise helped Bonnfinanz to build a web-based advisory and administration system that supports mobile working and direct interaction with the client.                        <\/div>\n                                                                    <\/div>\n                    <div 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e-mobility platform by enhancing its billing, payment, transaction management, and reporting capabilities.                        <\/div>\n                                                                        <div class=\"case-slider-v2-card-n-blocks\">\n                                                        <div class=\"case-slider-v2-card-n-block\">\n                                                                <b>&gt;50%<\/b>\n                                                                                                <span>faster billing and payment processing<\/span>\n                                                            <\/div>\n                                                    <\/div>\n                                            <\/div>\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ev-charging-platform-modernization\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                <\/div>\n                <div class=\"case-slider-v2-card-right\">\n                    <div class=\"case-slider-v2-card-buttons\">\n                        <a href=\"https:\/\/innowise.com\/pt\/case\/ev-charging-platform-modernization\/\" class=\"case-slider-v2-card-button\">View case study<\/a>\n                                            <\/div>\n                                        <img decoding=\"async\" src=\"https:\/\/innowise.com\/wp-content\/uploads\/2026\/09\/image.jpg\" alt=\"EV charging platform with flexible billing.\">\n                                        \n                <\/div>\n                            <\/div>\n            <\/div>\n                            <div class=\"swiper-slide\">\n            <div class=\"case-slider-v2-card\">\n                <div class=\"case-slider-v2-card-left\">\n                    <div class=\"case-slider-v2-card-left-cont\">\n                    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           line-height: 135%;\n            color:#2E2E2E;\n        }\n        .case-slider-v2-card-buttons{\n            display:flex;\n            justify-content:space-between;\n            align-items:center;\n            margin-top:auto;\n        }\n        .case-slider-v2-card-button,.swiper-slide .case-slider-v2-card-button{\n            background: #C63031;\n            padding:14px 28px;\n            font-family: Karla;\n            font-weight: 400;\n            font-size: 18px;\n            line-height: 150%;\n            color:#FFFFFF;\n            text-decoration:none!important;\n        }\n        .case-slider-v2-card-button:hover,.swiper-slide .case-slider-v2-card-button:hover{\n            background: #D13B3B;\n            color:#FFFFFF!important;\n        }\n        .swiper-slide:hover .case-slider-v2-card-button{\n            color:#FFFFFF!important;\n        }\n        .case-slider-v2-card-a{\n            font-family: Karla;\n            font-weight: 600;\n            font-size: 16px;\n            line-height: 150%;\n            color:#2E2E2E;\n            border-bottom:1px solid#2E2E2E;\n            cursor:pointer;\n        }\n        .case-slider-v2-card-a img{\n            display:none;\n        }\n        .case-slider-v2-card-a:hover{\n            color:#C63031;\n            border-color:#C63031;\n        }\n        .case-slider-v2-card-right{\n            width:458px;\n\t\t\tmin-width:458px;\n            overflow:hidden;\n\t\t\tborder: 1px solid #E8E8E8;\n        }\n        .case-slider-v2-card-right > img{\n            width:100%;\n\t\t\theight:100%;\n\t\t\tdisplay:block;\n            object-fit:cover;\n            transition:0.5s;\n        }\n        .case-slider-v2-card:hover .case-slider-v2-card-right > img{\n            transform:scale(1.1);\n        }\n        .swiper-pagination-counter{\n            font-family: Karla;\n            font-weight: 400;\n            font-size: 22px;\n            line-height: 100%;\n            color:#2E2E2E;\n        }\n        .case-slider-v2-nav{\n            display:none;\n            background:none;\n            border:none;\n            padding:0;\n            cursor:pointer;\n            line-height:0;\n            outline:none;\n            box-shadow:none;\n            -webkit-tap-highlight-color:transparent;\n        }\n        .case-slider-v2 .case-slider-v2-nav:hover,\n        .case-slider-v2 .case-slider-v2-nav:focus,\n        .case-slider-v2 .case-slider-v2-nav:focus-visible,\n        .case-slider-v2 .case-slider-v2-nav:active{\n            outline:none;\n            box-shadow:none;\n            border:none;\n            background:none;\n        }\n        .case-slider-v2-nav.swiper-button-disabled path{\n            stroke:#C1C1C1;\n        }\n\n        .case-slider-v2-card-right .case-slider-v2-card-buttons{\n            display:none;\n        }\n\n        @media(max-width:1024px){\n            .case-slider-v2-card,.case-slider-v2-wrap-blog .case-slider-v2-card{\n                padding:40px;\n            }\n            .case-slider-v2 .swiper-pagination-cont {\n                margin-top:40px;\n            }\n            .case-slider-v2-card-buttons{\n                display:none;\n            }\n            .case-slider-v2 .swiper-pagination-bullet{\n                width:50px;\n            }\n        }\n        @media(max-width:900px){\n            .case-slider-v2-card{\n                display:flex;\n                gap:40px;\n                flex-direction:column;\n                justify-content: space-between;\n            }\n            .case-slider-v2-card-left{\n                width:100%;\n                min-width:0;\n                min-height:0;\n                height:auto;\n            }\n            .case-slider-v2-card-right{\n                width:100%;\n                min-width:0;\n                min-height:0;\n                height:auto;\n                max-height:300px;\n            }\n            .case-slider-v2-card-left{\n                gap:30px;\n            }\n            .case-slider-v2-card-logo{\n                margin-bottom:20px;\n            }\n            .case-slider-v2-card-right .case-slider-v2-card-buttons{\n                display:flex;\n                margin-bottom:40px;\n                gap:40px;\n                justify-content:flex-start;\n            }\n        }\n        @media(max-width:767px){\n            .case-slider-v2-card,.case-slider-v2-wrap-blog .case-slider-v2-card{\n                padding: 24px 20px;\n            }\n            .case-slider-v2-card-logo{\n                margin-bottom:20px;\n                gap:12px;\n                min-height:30px;\n            }\n            .case-slider-v2-card-logo > img{\n                height:30px;\n            }\n            .case-slider-v2-card-logo > a{\n                padding-left:12px;\n                font-size:12px;\n            }\n            .case-slider-v2-card-title{\n                font-size:18px;\n                margin-bottom:16px;\n            }\n            .case-slider-v2-card-text{\n                font-size:14px;\n                margin-bottom:16px;\n            }\n            .case-slider-v2-card-n-block b{\n                margin-bottom:2px;\n                font-size:30px;\n            }\n            .case-slider-v2-card-n-block span{\n                font-size:12px;\n            }\n            .case-slider-v2-card-n-blocks{\n                gap:20px;\n            }\n            .case-slider-v2-card{\n                gap:20px;\n            }\n            .case-slider-v2-card-right{\n                display:flex;\n                flex-direction:column;\n                position:relative;\n            }\n            .case-slider-v2-card-buttons{\n                display:none;\n            }\n            .case-slider-v2-card-right .case-slider-v2-card-buttons{\n                display:block;\n                order:2;\n                margin-bottom:0;\n            }\n            .case-slider-v2-card-button{\n                display:block;\n                width:100%;\n                font-size:16px;\n                text-align:center;\n                padding: 12px 24px;\n            }\n            .case-slider-v2-card-a{\n                border:0;\n                text-align:center;\n                font-size:14px;\n                font-weight:400;\n                position:absolute;\n                top:0;\n                right:0;\n                background:#FBFBFD;\n                padding:5px 8px;\n                display:flex;\n                gap:4px;\n                align-items:center;\n            }\n            .case-slider-v2-card-a img{\n                display:block;\n                width:18px;\n                height:13px;\n            }\n            .case-slider-v2-card-right > img {\n                height: 180px;\n                object-fit: cover;\n            }\n            .case-slider-v2 .swiper-pagination-counter{\n                font-size:18px;\n            }\n            \n\n            .case-slider-v2 .swiper-pagination{\n                display:none;\n            }\n            .case-slider-v2 .swiper-pagination-cont{\n                display:flex;\n                align-items:center;\n                gap:12px;\n                width:100%;\n                transform:none;\n                margin-top:20px;\n            }\n            .case-slider-v2 .swiper-pagination-counter{\n                position:static;\n                transform:none;\n            }\n            .case-slider-v2-nav{\n                display:flex;\n                align-items:center;\n                justify-content:center;\n            }\n        }\n                .case-slider-v2-wrap-blog .case-slider-v2{\n            overflow:hidden;\n        }\n        .case-slider-v2-wrap-blog .swiper-pagination{\n            display:none;\n        }\n        .case-slider-v2-wrap-blog .swiper-pagination-cont{\n            display:flex;\n            align-items:center;\n            gap:10px;\n            width:100%;\n            transform:none;\n            margin-top:40px;\n        }\n        .case-slider-v2-wrap-blog .swiper-pagination-counter{\n            position:static;\n            transform:none;\n            font-size:22px;\n        }\n        .case-slider-v2-wrap-blog .case-slider-v2-nav{\n            display:flex;\n            align-items:center;\n            justify-content:center;\n        }\n        @media(max-width:768px){\n            .case-slider-v2-wrap-blog .swiper-pagination-cont{\n                margin-top:20px;\n            }\n            .case-slider-v2-wrap-blog .swiper-pagination-counter{\n                font-size:18px;\n            }\n        }\n                .case-slider-v2-popup-pdf{\n            display:none;\n            width:100vw;\n            height:100vh;\n            justify-content:center;\n            padding-top:150px;\n            position:fixed;\n            top:0;\n            left:0;\n            background:#0000009c;\n            z-index:10000;\n        }\n        .case-slider-v2-popup-pdf.is-open{\n            display:flex;\n        }\n        .case-slider-v2-popup-pdf-cont{\n            max-width:680px;\n            width:95%;\n            background:#fff;\n            padding:40px;\n            height:calc(100vh - 200px);\n            position:relative;\n            z-index:10;\n        }\n        .case-slider-v2-popup-pdf-frame{\n            overflow-y:auto;\n            overflow-x:hidden;\n            height:100%;\n            scrollbar-width:thin;\n            scrollbar-color:#888 transparent;\n        }\n        .case-slider-v2-popup-pdf-frame::-webkit-scrollbar{\n            width:6px;\n            background:transparent;\n        }\n        .case-slider-v2-popup-pdf-frame::-webkit-scrollbar-thumb{\n            background:#888;\n            border-radius:3px;\n        }\n        .case-slider-v2-popup-pdf-close{\n            position:absolute;\n            top:14px;\n            right:14px;\n            cursor:pointer;\n        }\n        .case-slider-v2-popup-pdf-frame canvas{\n            width:100%;\n            display:block;\n        }\n\n    <\/style>\n    \n    <\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4bb4657 e-con-full e-flex e-con e-child\" data-id=\"4bb4657\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a2a3e81 elementor-widget elementor-widget-heading\" data-id=\"a2a3e81\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Conclusion<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-146283e translation-block elementor-widget elementor-widget-text-editor\" data-id=\"146283e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In <span id=\"current-year\">2026<\/span>, more of the work is going into reusable models, better representations, smaller inference footprints, monitoring, calibration, and figuring out what happens once a model meets data that wasn\u2019t in the training set.<\/p><p>That\u2019s probably the useful shift to keep in mind. A newer approach is only better if it fits the problem, the data, the infrastructure, and the way the model will be used. If an older model performs just as well and is easier to run, keep the older model. If a foundation model saves weeks of training, use it. If neither survives a proper pilot, move on.<\/p><p>The trend itself is never the reason.<\/p><p>If you\u2019re evaluating which ML approaches make sense for a real product or workflow, <a href=\"\/ai\/machine-learning\/consulting\/\">our machine learning consulting team<\/a> can help with architecture, model selection, validation, and deployment.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7745742 e-con-full e-flex e-con e-child\" data-id=\"7745742\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6a53559 elementor-widget elementor-widget-heading\" data-id=\"6a53559\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">FAQ<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0be39d6 e-con-full e-flex e-con e-child\" data-id=\"0be39d6\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e4bf461 faq elementor-widget elementor-widget-n-accordion\" data-id=\"e4bf461\" data-element_type=\"widget\" data-settings=\"{&quot;default_state&quot;:&quot;all_collapsed&quot;,&quot;max_items_expended&quot;:&quot;one&quot;,&quot;n_accordion_animation_duration&quot;:{&quot;unit&quot;:&quot;ms&quot;,&quot;size&quot;:400,&quot;sizes&quot;:[]}}\" data-widget_type=\"nested-accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"e-n-accordion\" aria-label=\"Accordion. Open links with Enter or Space, close with Escape, and navigate with Arrow Keys\">\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2390\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"1\" tabindex=\"0\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2390\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> What is machine learning? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2390\" class=\"elementor-element elementor-element-940483b e-con-full e-flex e-con e-child\" data-id=\"940483b\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e14ff51 elementor-widget elementor-widget-html\" data-id=\"e14ff51\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n<p>\n    Machine learning (ML)  is a branch of AI where models learn patterns from data and use them to make predictions or decisions without every rule being written manually.\n\n<\/p>\n<p>\nIn practice, that can mean predicting demand, detecting fraud, estimating risk, recommending products, spotting defects, or forecasting when equipment is likely to fail.\n<\/p>\n\n<\/div> \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2391\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"2\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2391\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> How does machine learning differ from AI and deep learning? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2391\" class=\"elementor-element elementor-element-34a047b e-con-full e-flex e-con e-child\" data-id=\"34a047b\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e008181 elementor-widget elementor-widget-html\" data-id=\"e008181\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\n<div class='content'>\n <p>AI is the broad category. Machine learning is one way of building AI systems by learning from data. Deep learning is a subset of machine learning based on neural networks with many layers.<\/p>\n <p>So the relationship is fairly simple: deep learning sits inside machine learning, and machine learning sits inside AI.<\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2392\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"3\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2392\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> Are traditional ML models still relevant in <span id=\"current-year\">2026<\/span>? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2392\" class=\"elementor-element elementor-element-9161412 e-flex e-con-boxed e-con e-child\" data-id=\"9161412\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-bff55df elementor-widget elementor-widget-html\" data-id=\"bff55df\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n <p>Very much so.<\/p>  \n <p>Gradient boosting, random forests, logistic regression, and other established methods are still strong choices for many structured-data problems. They can be faster, cheaper, and easier to explain than newer deep-learning approaches.<\/p>\n <p>A model doesn\u2019t become obsolete because a more fashionable one exists.<\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2393\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"4\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2393\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> What challenges can slow the adoption of emerging ML technologies? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2393\" class=\"elementor-element elementor-element-9971a1c e-flex e-con-boxed e-con e-child\" data-id=\"9971a1c\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a7794a8 elementor-widget elementor-widget-html\" data-id=\"a7794a8\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n <p>Usually the boring ones: poor data quality, missing labels, weak infrastructure, unclear ownership, privacy restrictions, integration problems, and not enough people who understand both the model and the business process around it.\n<\/p>   \n<p>\n  There\u2019s another one too: sometimes the proposed ML system doesn\u2019t improve the existing process enough to justify the work.  \n<\/p>\n<p>\n    That\u2019s worth finding out early.\n<\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2394\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"5\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2394\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> What can AutoML automate, and where is human expertise still needed? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2394\" class=\"elementor-element elementor-element-a9dbc23 e-flex e-con-boxed e-con e-child\" data-id=\"a9dbc23\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3f4eb4d elementor-widget elementor-widget-html\" data-id=\"3f4eb4d\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n <p>\n    AutoML can handle parts of model selection, hyperparameter tuning, feature processing, ensembling, and experimentation.\n <\/p>   \n <p>\n     Humans still need to decide what the model should predict, whether the data makes sense, which errors matter most, how success should be measured, and whether the final system is safe and useful enough to deploy.\n <\/p>\n <p>\n     AutoML can run experiments. It can\u2019t decide whether the experiment was worth running.\n <\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2395\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"6\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2395\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> When should businesses run ML models on-device rather than in the cloud? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2395\" class=\"elementor-element elementor-element-829c32f e-flex e-con-boxed e-con e-child\" data-id=\"829c32f\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dc76206 elementor-widget elementor-widget-html\" data-id=\"dc76206\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n <p>\n On-device ML makes sense when latency matters, connectivity is unreliable, bandwidth is limited, or sensitive data should stay local.\n <\/p>  \n <p>\n   The trade-off is hardware. Smaller devices have tighter limits on memory, compute, and energy, so models usually need compression or other optimization before they can run there comfortably.  \n <\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-2396\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"7\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-2396\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> Is quantum machine learning ready for business use? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"40\" height=\"40\" fill=\"none\"><path fill=\"#C63031\" d=\"M19 8h2v24h-2z\"><\/path><path fill=\"#C63031\" d=\"M8 21v-2h24v2z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-2396\" class=\"elementor-element elementor-element-d7756b1 e-flex e-con-boxed e-con e-child\" data-id=\"d7756b1\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b291a8d elementor-widget elementor-widget-html\" data-id=\"b291a8d\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class='content'>\n <p>\n     For most companies, no.\n <\/p> \n <p>\n    Quantum machine learning is still largely a research topic. There are experiments around optimization, quantum kernels, and hybrid quantum-classical models, but conventional ML remains far more practical for normal production systems in <span id=\"current-year\">2026<\/span>. \n <\/p>\n <p>\n     If someone is proposing quantum ML for a routine forecasting problem today, I\u2019d ask what exactly the regular model failed to do first.\n <\/p>\n<\/div> \n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<script type=\"application\/ld+json\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"What is machine learning?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Machine learning (ML)  is a branch of AI where models learn patterns from data and use them to make predictions or decisions without every rule being written manually.\\n\\n\\n\\nIn practice, that can mean predicting demand, detecting fraud, estimating risk, recommending products, spotting defects, or forecasting when equipment is likely to fail.\"}},{\"@type\":\"Question\",\"name\":\"How does machine learning differ from AI and deep learning?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"AI is the broad category. 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index = -1;\n        for (let i = 0; i < headerElements.length; i++) {\n          if (headerElements[i].getBoundingClientRect().top <= marker) index = i;\n        }\n        if (index === currentIndex) return;\n        currentIndex = index;\n        tocLinks.forEach((item, i) => {\n          item.classList.toggle(\"active\", i === index);\n          item.classList.toggle(\"pre-active\", i < index);\n        });\n      };\n\n      let ticking = false;\n      const requestUpdate = () => {\n        if (ticking) return;\n        ticking = true;\n        requestAnimationFrame(() => {\n          updateActive();\n          ticking = false;\n        });\n      };\n\n      updateActive();\n      window.addEventListener(\"scroll\", requestUpdate, { passive: true });\n      window.addEventListener(\"resize\", requestUpdate);\n    };\n\n    if (document.readyState === \"loading\") {\n      document.addEventListener(\"DOMContentLoaded\", boot);\n    } else {\n      boot();\n    }\n  })();\n<\/script>\r\n\r\n<style>\r\n    .table-content-container {\r\n        max-width: 300px;\r\n        width: 100%;\r\n        flex-shrink: 0;\r\n    }\r\n\r\n    .table-content-container .elementor-widget-wrap {\r\n        margin: 0 !important;\r\n        padding: 0 !important;\r\n    }\r\n\r\n    @media (max-width: 1279px) {\r\n        .table-content-container {\r\n            display: none !important;\r\n        }\r\n    }\r\n\r\n    .toc-wrapper {\r\n        display: flex;\r\n        flex-direction: column;\r\n        row-gap: 30px;\r\n        font-family: \"Karla\";\r\n        box-sizing: border-box;\r\n        max-height: 436px;\r\n        flex: 1;\r\n    }\r\n    .ddcv {\r\n        flex-basis: 100%;\r\n        flex-grow: 1;\r\n        flex-shrink: 1;\r\n        overflow-y: auto;\r\n    }\r\n\r\n    .toc-wrapper {\r\n        overflow-y: auto;\r\n    }\r\n\r\n    .toc-wrapper::-webkit-scrollbar,\r\n    .ddcv::-webkit-scrollbar {\r\n        position: absolute !important;\r\n        width: 4px !important;\r\n        background-color: #f5f5f7 !important;\r\n    }\r\n\r\n    .toc-wrapper::-webkit-scrollbar-thumb,\r\n    .ddcv::-webkit-scrollbar-thumb {\r\n        position: absolute !important;\r\n        background-color: #999999 !important;\r\n        border-radius: 4px !important;\r\n    }\r\n\r\n    .toc-wrapper .toc {\r\n        scrollbar-width: 4px !important;\r\n        scrollbar-color: auto !important;\r\n    }\r\n\r\n    h4.toc-title {\r\n        margin: 0;\r\n        font-family: Karla;\r\n        font-size: 22px;\r\n        line-height: 28px;\r\n        font-weight: 700;\r\n    }\r\n\r\n    @media screen and (max-width: 1279px) {\r\n        .ddcv {\r\n            margin-top: 0px;\r\n            position: absolute;\r\n            top: 0px;\r\n            left: 50%;\r\n            transform: translate(50%, 0);\r\n        }\r\n    }\r\n\r\n    @media screen and (max-width: 767px) {\r\n        .ddcv {\r\n            display: none;\r\n        }\r\n    }\r\n\r\n    .toc ul {\r\n        list-style: none;\r\n        font-family: \"Karla\";\r\n        font-size: 16px;\r\n        line-height: 22px;\r\n        padding: 0px;\r\n        border-left: 1px solid #717171;\r\n    }\r\n\r\n    .toc li {\r\n        margin-left: -1px;\r\n        margin-top: 0;\r\n        padding: 16px 16px 16px 20px;\r\n        font-size: 18px;\r\n        line-height: 22px;\r\n        color: #717171;\r\n        border-left: 2px solid transparent;\r\n    }\r\n\r\n    .toc ul li a {\r\n        display: block;\r\n        width: 100%;\r\n        color: inherit;\r\n        text-decoration: none !important;\r\n    }\r\n\r\n    .toc ul .active {\r\n        color: #2e2e2e;\r\n        border-left: 2px solid #c63031;\r\n    }\r\n\r\n    .toc ul .pre-active {\r\n        border-left: 2px solid #c63031;\r\n    }\r\n<\/style>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-5718541 e-con-full elementor-hidden-tablet elementor-hidden-mobile e-flex e-con e-child\" data-id=\"5718541\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t<div class=\"elementor-element elementor-element-caa2474 e-con-full e-flex e-con e-child\" data-id=\"caa2474\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-7d61a7a elementor-widget-tablet__width-inherit elementor-widget__width-initial max100 elementor-widget elementor-widget-heading\" data-id=\"7d61a7a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Put ML to work<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-12ddde7 e-con-full e-flex e-con e-child\" data-id=\"12ddde7\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6b79093 elementor-absolute elementor-widget-mobile__width-inherit transform elementor-widget elementor-widget-html\" data-id=\"6b79093\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"wave-container\"><\/div>\r\n\r\n<style>\r\n  .wave-container {\r\n    width: 400px;\r\n    height: 400px;\r\n  }\r\n\r\n  @media(max-width: 767px) {\r\n    .wave-container {\r\n      width: 100%;\r\n      height: 100%;\r\n    }\r\n  }\r\n\r\n\r\n  .wave {\r\n    position: absolute;\r\n    border: 1px solid rgba(210, 184, 214, 1);\r\n    border-radius: 50%;\r\n    animation: drop 16s infinite;\r\n    top: 50%;\r\n    left: 50%;\r\n    transform: translate(-50%, -50%);\r\n    box-sizing: border-box;\r\n  }\r\n\r\n  @keyframes drop {\r\n    0% {\r\n      width: 0px;\r\n      height: 0px;\r\n      border: 1px solid rgba(210, 184, 214, 1);\r\n    }\r\n\r\n    100% {\r\n      width: 400px;\r\n      height: 400px;\r\n      border: 1px solid rgba(210, 184, 214, 0);\r\n    }\r\n  }\r\n<\/style>\r\n\r\n<script>\r\n\r\n  document.addEventListener('DOMContentLoaded', () => {\r\n    function createWaves(numberOfWaves) {\r\n      const waveContainers = document.querySelectorAll('.wave-container');\r\n\r\n      waveContainers.forEach((waveContainer) => {\r\n        for (let i = 0; i < numberOfWaves; i++) {\r\n          const wave = document.createElement('div');\r\n          wave.classList.add('wave');\r\n\r\n          wave.style.animationDelay = `${i * 0.8}s`;\r\n\r\n          waveContainer.appendChild(wave);\r\n        }\r\n      });\r\n    }\r\n\r\n    createWaves(10)\r\n  });\r\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-14de066 elementor-align-left elementor-widget__width-initial elementor-widget-mobile__width-inherit cta-btn elementor-widget elementor-widget-button\" data-id=\"14de066\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"#contact-form\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Talk to us<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-eab1d6c e-flex e-con-boxed e-con e-parent\" data-id=\"eab1d6c\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-87ab0d5 elementor-widget elementor-widget-shortcode\" data-id=\"87ab0d5\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f100240-o1\" lang=\"en-US\" dir=\"ltr\" data-wpcf7-id=\"100240\">\n<div class=\"screen-reader-response\"><p role=\"status\" aria-live=\"polite\" aria-atomic=\"true\"><\/p> <ul><\/ul><\/div>\n<form action=\"\/pt\/wp-json\/wp\/v2\/posts\/202814#wpcf7-f100240-o1\" method=\"post\" class=\"wpcf7-form init\" aria-label=\"Contact form\" enctype=\"multipart\/form-data\" novalidate=\"novalidate\" data-status=\"init\">\n<fieldset class=\"hidden-fields-container\"><input type=\"hidden\" name=\"_wpcf7\" value=\"100240\" \/><input type=\"hidden\" name=\"_wpcf7_version\" value=\"6.1.6\" \/><input type=\"hidden\" name=\"_wpcf7_locale\" value=\"en_US\" \/><input type=\"hidden\" name=\"_wpcf7_unit_tag\" value=\"wpcf7-f100240-o1\" \/><input type=\"hidden\" name=\"_wpcf7_container_post\" value=\"0\" \/><input type=\"hidden\" name=\"_wpcf7_posted_data_hash\" value=\"\" \/><input type=\"hidden\" name=\"_wpcf7_recaptcha_response\" value=\"\" \/>\n<\/fieldset>\n<style>\n.mailToContact br:nth-child(2){\ndisplay:none;\n}\n#form-templates .contact__info {\n  background-color: #f4f4f4;\n  padding: 70px 44px 70px 50px;\n  position: relative;\n  max-width: 540px;\n  width: 100%;\nborder: 1px solid #AEB1B7;\n}\n\n#form-templates .contact__info-background {\n  z-index: -1;\n  position: absolute;\n  top: 20px;\n  left: 20px;\n  width: 100%;\n  height: 100%;\n  border: 1px dashed #ef4557;\n}\n\n\n#form-templates .new-container{\ndisplay: flex;\njustify-content: space-between;\nflex-wrap: wrap;\n}\n\n\n#form-templates{\npadding: 100px 15px 100px 15px;        \n}\n\n#form-templates .contact__info-heading {\n  font-family: 'Sora' !important;\n  font-style: normal !important;\n  font-weight: 400 !important;\n  font-size: 36px !important;\n  line-height: 46px !important;\n  color: #2E2E2E !important;\n   margin-bottom: 60px !important;\n\n}\n\n\n#form-templates .message label{\ncolor: #585858 !important;   \n}\n\n.elementor-widget-container.form-template h2,.elementor-widget-container.form-template h1{\n font-size: 60px !important;\n  line-height: 70px !important;\n  font-family: \"Sora\", Sans-serif;\n  font-weight: 400;\n  margin: 0;  \n  margin-bottom: 20px;\n}\n\n\n\n\n.elementor-widget-container.form-template p{\n  font-family: \"Karla\", Sans-serif;\n  font-size: 22px;\n  font-weight: 400;\n  line-height: 28px;\n  color: var( --e-global-color-primary );\n  max-width: 700px;\n  margin: 0; \n  margin-bottom: 40px;\n} \n  \n\n\n.new-container #spinner{\nwidth: 50%;\nmax-width: 700px;\n}\n\n\n#form-templates .new-container #spinner div.contact-us__wrapper:nth-child(6){\ngap:30px; \n    \n}\n\n.contact-us__wrapper .pp a{\n  text-decoration: underline;\n}\n.contact-us__wrapper .pp a:hover{\n  color:#C63031;\n}\n.contact-us__wrapper .pp a:active{\n  color: #D13B3B;\n}\n\n#form-templates .contact__info-heading {\n  margin-bottom: 67px;\n  font-size: 36px;\n  font-family: karla;\n  color:  #2E2E2E;\n\n  line-height: 49px;\n}\n\n#form-templates .contact__info-steps {\n  display: flex;\n  flex-direction: column;\n  max-width: 425x;\n  row-gap: 20px;\n  border-left: 1px solid #2e2e2e;\n}\n\n#form-templates .contact__info-block {\n  position: relative;\n  padding-left: 45px;\n}\n\n#form-templates .contact__info-block:last-child {\n  box-shadow: -1px 0 0 1px #f4f4f4;\n}\n\n#form-templates .contact__info-step {\n  position: absolute;\n  border: 1px solid #2e2e2e;\n  width: 40px;\n  height: 40px;\n  display: flex;\n  align-items: center;\n  justify-content: center;\n  border-radius: 20px;\n  left: -20px;\n  top: -8px;\n  background-color: #F4F4F4;\n  color:  #2E2E2E;\n\nfont-family: Karla;\nfont-weight: 700;\nfont-size: 18px;\nline-height: 28px;\n\n}\n\n.elementor-widget-global .contact__info-step {\n        color:  #2E2E2E;\n}\n\n#form-templates .contact__info-text {\n  margin: 0;\n  font-size: 16px;\n  line-height: 26px;\n  color: #2E2E2E;\n  font-family: karla;\n\n  width: 100%;\n}\n\n\n#form-templates .contact-us__send{\nflex-shrink: 0;\nmargin-top:0;\n}\n\n\n\n@media screen and (max-width: 1279px) {\n    .new-container #spinner{\n        width: 100%;\n        max-width:100%;\n        margin-bottom:40px;\n    }\n    \n\n    .new-container .contact__info {\n        max-width: 700px !important;\n    }\n    \n}\n\n\n@media screen and (max-width: 1279px) {\n#form-templates{\npadding: 60px 15px 70px 15px;     \n}\n}\n\n\n\n@media screen and (max-width: 767px) {\n\n#form-templates .new-container #spinner div.contact-us__wrapper:nth-child(6){\ngap:20px; \n \n}\n\n\n  #form-templates .contact__info {\n    padding: 20px 20px 40px 40px;\n    margin: 0 auto;\n  }\n\n\n#form-templates{\npadding: 40px 15px 50px 15px;  \n    \n}\n\n  \n   .new-container #spinner{\n       \n    margin-bottom:30px;   \n   }\n   \n   \n   .elementor-widget-container #form-templates .form-template h2,.elementor-widget-container.form-template h1{\n   font-size: 32px !important;\n    line-height: 42px !important;    \n   }\n   \n   \n   .elementor-widget-container #form-templates .form-template p{\n       \n    font-size: 16px;\n    line-height: 20px;  \n    margin-bottom: 30px !important;\n \n       \n   }\n   \n   #form-templates .contact__info-heading{\n   font-size: 24px !important;\n    line-height: 49px !important;    \n       \n   }\n   \n\n.mailToContact{\nmargin-top: 10px !important;        \n}\n\n   \n\n  #form-templates .contact__info-heading {\n    font-size: 24px;\n    margin-bottom: 37px;\n  }\n\n  #form-templates .contact__info-background {\n    top: 10px;\n    left: 10px;\n  }\n\n  #form-templates .contact__info-text {\n    font-size: 12px;\n    line-height: 20px;\n  }\n  \n  \n  #form-templates .contact__info-heading {\n   margin-bottom: 35px !important;\n\n}\n\n}\n\n@media (max-width: 767px) {\n    .mailToContact {\n        max-width: 100%;\n    }\n    .contact-us__wrapper .pp {\nfont-size: 12px !important;\nline-height: 140%;\nmargin-bottom: 0 !important;\n\n}\n}\n<\/style>\n\n<script>\nwindow.addEventListener('hashchange',function(e){if(window.history.pushState){window.history.pushState('','\/',window.location.pathname)}else{window.location.hash=''}})\n<\/script>\n\n\n<div id=\"form-templates\">\n<div class=\"elementor-widget-container form-template\">\n<a name=\"contact-form\"><\/a>\n<h2>Contact us<\/h2>\n<p><a id=\"calendlylink\" style=\"\">Book a call<\/a> or fill out the form below and we\u2019ll get back to you once we\u2019ve processed your request.<\/p>\n<\/div>\n\n<div class=\"new-container\">\n\n\n<div class=\"contact-us__main\" id=\"spinner\" data-no-defer=\"1\">\n\n<div class=\"contact-us__wrapper\">\n\n<div class=\"name\">\n<label>Name<\/label>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"field_name\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required contact-us__name\" id=\"contact-name\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Name*\" value=\"\" type=\"text\" name=\"field_name\" \/><\/span>\n<\/div>\n\n<div class=\"company\">\n<label>Company<\/label>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"company\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required contact-us__company\" id=\"contact-company\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Company*\" value=\"\" type=\"text\" name=\"company\" \/><\/span>\n<\/div>\n\n<\/div>\n\n<div class=\"contact-us__wrapper\">\n\n<div class=\"email\">\n<label>Email<\/label>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"email\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-email wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-email contact-us__email\" id=\"contact-email\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Corporate email*\" value=\"\" type=\"email\" name=\"email\" \/><\/span>\n<\/div>\n\n<div class=\"phone\">\n<label>Phone<\/label>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"tel\"><input size=\"40\" maxlength=\"400\" class=\"wpcf7-form-control wpcf7-tel wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-tel contact-us__phone\" id=\"contact-phone\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Phone*\" value=\"\" type=\"tel\" name=\"tel\" \/><\/span>\n<\/div>\n\n<\/div>\n<div class=\"contact-us__wrapper subj\">\n<span class=\"wpcf7-form-control-wrap\" data-name=\"your-recipient\"><select class=\"wpcf7-form-control wpcf7-select\" id=\"form-field-subj_js\" aria-invalid=\"false\" name=\"your-recipient\"><option value=\"\">Subject*<\/option><option value=\"IT staff augmentation\">IT staff augmentation<\/option><option value=\"Turnkey product development\">Turnkey product development<\/option><option value=\"Support and enhancement\">Support and enhancement<\/option><option value=\"Careers\">Careers<\/option><option value=\"Other\">Other<\/option><\/select><\/span>\n\n<span class=\"wpcf7-form-control-wrap\" data-name=\"form-field-budget_js\"><select  class=\"wpcf7-form-control wpcf7-select\" id=\"form-field-budget_js\" aria-invalid=\"false\" name=\"form-field-budget_js\" aria-label=\"Project budget\"><option value=\"\">Project budget<\/option><option value=\"Under $15K\">Under $15K<\/option><option value=\"$15K-$30K\">$15K-$30K<\/option><option value=\"$30K-$100K\">$30K-$100K<\/option><option value=\"$100K-$250K\">$100K-$250K<\/option><option value=\"$250K-$500K\">$250K-$500K<\/option><option value=\"More than $500K\">More than $500K<\/option><\/select><\/span>\n\n<\/div>\n\n\n<div class=\"message\">\n<label>Message<\/label>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"message\"><textarea cols=\"40\" rows=\"1\" maxlength=\"2000\" class=\"wpcf7-form-control wpcf7-textarea wpcf7-validates-as-required contact-us__message\" id=\"contact-message\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Describe your needs in detail*\" name=\"message\"><\/textarea><\/span>\n<\/div>\n\n<div class=\"atvoice-wrap\">\n\n<div class=\"voice-wrap\">\n<span id=\"voice-mut\" class=\"voicetext\">Send us a voice message<\/span>\n         <div class=\"qc_voice_audio_wrapper\">\n            <div class=\"qc_voice_audio_container\">\n                <div class=\"qc_voice_audio_upload_main\" id=\"qc_audio_main\">\n                    <a class=\"qc_audio_record_button\" id=\"qc_audio_record\" href=\"#\" aria-label=\"Record an audio message\">\n                        <span class=\"dashicons dashicons-microphone\"><\/span> \u00a0<\/a> \n                <\/div>\n\n                <div class=\"qc_voice_audio_recorder\" id=\"qc_audio_recorder\" style=\"display:none\">\n\n                <\/div>\n                <div class=\"qc_voice_audio_display\" id=\"qc_audio_display\"  style=\"display:none\">\n                    <audio id=\"qc-audio\" controls src=\"\"><\/audio>\n                    <span title=\"Remove and back to main upload screen.\" class=\"qc_audio_remove_button dashicons dashicons-trash\"><\/span>\n                <\/div>\n            <\/div>\n            <input type=\"hidden\" value=\"\" name=\"qcwpvoicemessage\" id=\"qc_audio_url\" \/>\n        <\/div>\n        \n<\/div>\n\n\n<div class=\"attach-wrap\">\n<span class=\"voicetext\">Attach documents<\/span>\n\n<div class='attachment'>\n\n<div class=\"downloaded\">\n<span><\/span>\n<div class=\"deleteFile\"><\/div>\n<\/div>\n\n<div class=\"attachmentButton\" onclick=\"(function cl(e){if(e.target.nodeName == 'DIV'){e.target.parentNode.children[1].children[0].click(); }})(arguments[0]);\">\n\n<div class=\"innerText\">Upload file<\/div>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"att-files\"><input size=\"40\" class=\"wpcf7-form-control wpcf7-file\" accept=\".jpg,.png,.jpeg,.pdf\" aria-invalid=\"false\" type=\"file\" name=\"att-files\" \/><\/span>\n\n<div class=\"tip\" onclick=\"event.stopPropagation()\">\n<p>You can attach 1 file up to 2MB. 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