{"id":8531,"date":"2023-12-20T16:29:30","date_gmt":"2023-12-20T16:29:30","guid":{"rendered":"https:\/\/dailyai.com\/?p=8531"},"modified":"2023-12-21T10:38:38","modified_gmt":"2023-12-21T10:38:38","slug":"ml-boosts-x-ray-diffraction-techniques-to-find-new-materials","status":"publish","type":"post","link":"https:\/\/dailyai.com\/de\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/","title":{"rendered":"ML verbessert R\u00f6ntgenbeugungstechniken zur Suche nach neuen Materialien"},"content":{"rendered":"<p><strong>Materialwissenschaftler versuchen st\u00e4ndig, neue Materialien mit bestimmten Eigenschaften zu finden, aber die experimentellen Daten, die sie durchforsten m\u00fcssen, sind \u00fcberw\u00e4ltigend. Wissenschaftler der University of Rochester haben maschinelles Lernen eingesetzt, um die Entdeckung neuer Materialien zu beschleunigen.<\/strong><\/p>\n<p>Kristalline Materialien haben eine geordnete, sich wiederholende Kristallgitterstruktur, eine regelm\u00e4\u00dfige, sich wiederholende Anordnung von Atomen, Ionen oder Molek\u00fclen. Die Anordnung dieser Kristallgitter ist es, die einem Material bestimmte Eigenschaften verleiht.<\/p>\n<p>Sie wollen ein Material, das hart ist, hohen Temperaturen standh\u00e4lt und leicht ist? Um das zu erreichen, muss man genau die richtige Gitterstruktur haben.<\/p>\n<p>Wenn Materialwissenschaftler eine kleine Menge eines neuen Materials synthetisieren, wollen sie wissen, welche Eigenschaften es haben wird, um zu entscheiden, ob es f\u00fcr eine bestimmte Anwendung geeignet ist oder nicht.<\/p>\n<p>Dazu verwenden sie ein Verfahren namens R\u00f6ntgenbeugung (XRD). Die Materialprobe wird normalerweise zu einem feinen Pulver gemahlen und dann mit R\u00f6ntgenstrahlen bestrahlt. Wenn die R\u00f6ntgenstrahlen auf die Atome im Material treffen, werden sie je nach der Anordnung der Atome in verschiedene Richtungen gebeugt.<\/p>\n<p>Die gebeugten R\u00f6ntgenstrahlen erzeugen ein Muster auf einem Detektor, das die Wissenschaftler analysieren m\u00fcssen, um auf die Eigenschaften des Materials zu schlie\u00dfen. Das Problem ist, dass die R\u00f6ntgendiffraktometrie eine riesige Menge an Daten erzeugt, die der Mensch nicht effektiv verarbeiten kann.<\/p>\n<h2>Automatisierung der Materialanalyse<\/h2>\n<p><a href=\"https:\/\/www.nature.com\/articles\/s41524-023-01164-8\" target=\"_blank\" rel=\"noopener\">Die Studie<\/a>unter der Leitung eines Doktoranden der Materialwissenschaften <a href=\"https:\/\/www.hajim.rochester.edu\/me\/sites\/abdolrahim\/people\/graduate-students\/jerardo-salgado\/index.html\" target=\"_blank\" rel=\"noopener\">Jerardo Salgado<\/a>entwickelte Deep-Learning-Modelle, um die Klassifizierung von Materialien anhand ihrer XRD-Muster zu automatisieren.<\/p>\n<p>Bei den verwendeten maschinellen Lernmodellen handelt es sich um Faltungsneuronale Netze (CNNs), eine Art neuronales Netz, das sich besonders gut f\u00fcr Bilderkennungs- und Klassifizierungsaufgaben eignet.<\/p>\n<p>Die Modelle wurden anhand eines gro\u00dfen Datensatzes synthetischer XRD-Muster trainiert, die eine breite Palette von Versuchsbedingungen und Materialtypen repr\u00e4sentieren.<\/p>\n<p>Projektleitung <a href=\"https:\/\/www.hajim.rochester.edu\/me\/people\/faculty\/abdolrahim_niaz\/index.html\" target=\"_blank\" rel=\"noopener\">Niaz Abdolrahim<\/a>Ein Professor f\u00fcr Maschinenbau an der University of Rochester sagte: \"In jedem dieser Bilder steckt eine Menge Materialwissenschaft und Physik, und jeden Tag werden in Einrichtungen und Labors auf der ganzen Welt Terabytes an Daten produziert.\"<\/p>\n<p>Abdolrahim erkl\u00e4rt die Vorteile des maschinellen Lernens in seinem Fachgebiet: \"Die Entwicklung eines guten Modells zur Analyse dieser Daten kann wirklich dazu beitragen, Materialinnovationen zu beschleunigen, Materialien unter extremen Bedingungen zu verstehen und Materialien f\u00fcr verschiedene technologische Anwendungen zu entwickeln.\"<\/p>\n<p>Der Einsatz von Modellen des maschinellen Lernens zur Filterung von XRD-Daten k\u00f6nnte die Entwicklung schnellerer Elektronik, besserer Batterien oder sogar von Alltagsgegenst\u00e4nden mit verbesserter Haltbarkeit, Funktionalit\u00e4t oder Nachhaltigkeit beschleunigen.<\/p>\n<p>Forscher des <a href=\"https:\/\/cmap.rochester.edu\/\" target=\"_blank\" rel=\"noopener\">Zentrum f\u00fcr Materie bei atomarem Druck<\/a> haben ein besonderes Interesse an dieser Anwendung des maschinellen Lernens. Der Einsatz von XRD, w\u00e4hrend Materialien extremen Dr\u00fccken und Temperaturen ausgesetzt werden, wird den Wissenschaftlern nicht nur helfen, Wege zur Schaffung neuer Materialien zu finden, sondern auch etwas \u00fcber die Entstehung von Sternen und Planeten zu erfahren.<\/p>\n<p>Der Einsatz von KI zur Befreiung wissenschaftlicher K\u00f6pfe von der m\u00fchsamen Datenanalyse wird ihr kreatives Denken besser auf die Entwicklung der Materialien lenken, die unsere Zukunft gestalten werden.<\/p>","protected":false},"excerpt":{"rendered":"<p>Materialwissenschaftler versuchen st\u00e4ndig, neue Materialien mit bestimmten Eigenschaften zu finden, aber die experimentellen Daten, die sie durchforsten m\u00fcssen, sind \u00fcberw\u00e4ltigend. Wissenschaftler der University of Rochester nutzten maschinelles Lernen, um die Entdeckung neuer Materialien zu beschleunigen. Kristalline Materialien haben eine geordnete, sich wiederholende Kristallgitterstruktur, eine regelm\u00e4\u00dfige, sich wiederholende Anordnung von Atomen, Ionen oder Molek\u00fclen. Die Anordnung dieser Kristallgitter ist es, die einem Material bestimmte Eigenschaften verleiht. Sie wollen ein Material, das hart ist, hohen Temperaturen standh\u00e4lt und leicht ist? Um das zu erreichen, muss man genau die richtige Gitterstruktur haben. Wenn Materialwissenschaftler eine kleine Menge eines Materials synthetisieren<\/p>","protected":false},"author":6,"featured_media":8534,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[150,105],"class_list":["post-8531","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-ai-benefits","tag-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ML boosts X-ray diffraction techniques to find new materials | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/de\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ML boosts X-ray diffraction techniques to find new materials | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Material scientists are constantly trying to find new materials with specific properties but the experimental data they have to wade through is overwhelming. Scientists at the University of Rochester used machine learning to fast-track new materials discovery. Crystalline materials have a well-ordered, repeating crystal lattice structure, a regular, repeating arrangement of atoms, ions, or molecules. The arrangement of these crystal lattices is what gives a material specific properties. Want a material that\u2019s hard, handles high temperatures, and is lightweight? You\u2019ve got to get just the right lattice structure to make that happen. When material scientists synthesize a small amount of\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/de\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2023-12-20T16:29:30+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-12-21T10:38:38+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Eugene van der Watt\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:label1\" content=\"Verfasst von\" \/>\n\t<meta name=\"twitter:data1\" content=\"Eugene van der Watt\" \/>\n\t<meta name=\"twitter:label2\" content=\"Gesch\u00e4tzte Lesezeit\" \/>\n\t<meta name=\"twitter:data2\" content=\"3\u00a0Minuten\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/\"},\"author\":{\"name\":\"Eugene van der Watt\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/person\\\/7ce525c6d0c79838b7cc7cde96993cfa\"},\"headline\":\"ML boosts X-ray diffraction techniques to find new materials\",\"datePublished\":\"2023-12-20T16:29:30+00:00\",\"dateModified\":\"2023-12-21T10:38:38+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/\"},\"wordCount\":493,\"publisher\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/material-crystal-lattice.png\",\"keywords\":[\"AI benefits\",\"machine learning\"],\"articleSection\":[\"Industry\"],\"inLanguage\":\"de\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/\",\"url\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/\",\"name\":\"ML boosts X-ray diffraction techniques to find new materials | DailyAI\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/material-crystal-lattice.png\",\"datePublished\":\"2023-12-20T16:29:30+00:00\",\"dateModified\":\"2023-12-21T10:38:38+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#breadcrumb\"},\"inLanguage\":\"de\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#primaryimage\",\"url\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/material-crystal-lattice.png\",\"contentUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/12\\\/material-crystal-lattice.png\",\"width\":1792,\"height\":1024},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2023\\\/12\\\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/dailyai.com\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"ML boosts X-ray diffraction techniques to find new materials\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#website\",\"url\":\"https:\\\/\\\/dailyai.com\\\/\",\"name\":\"DailyAI\",\"description\":\"Your Daily Dose of AI News\",\"publisher\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/dailyai.com\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"de\"},{\"@type\":\"Organization\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\",\"name\":\"DailyAI\",\"url\":\"https:\\\/\\\/dailyai.com\\\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/logo\\\/image\\\/\",\"url\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/06\\\/Daily-Ai_TL_colour.png\",\"contentUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/06\\\/Daily-Ai_TL_colour.png\",\"width\":4501,\"height\":934,\"caption\":\"DailyAI\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/logo\\\/image\\\/\"},\"sameAs\":[\"https:\\\/\\\/x.com\\\/DailyAIOfficial\",\"https:\\\/\\\/www.linkedin.com\\\/company\\\/dailyaiofficial\\\/\",\"https:\\\/\\\/www.youtube.com\\\/@DailyAIOfficial\"]},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/person\\\/7ce525c6d0c79838b7cc7cde96993cfa\",\"name\":\"Eugene van der Watt\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"de\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/07\\\/Eugine_Profile_Picture-96x96.png\",\"url\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/07\\\/Eugine_Profile_Picture-96x96.png\",\"contentUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2023\\\/07\\\/Eugine_Profile_Picture-96x96.png\",\"caption\":\"Eugene van der Watt\"},\"description\":\"Eugene comes from an electronic engineering background and loves all things tech. When he takes a break from consuming AI news you'll find him at the snooker table.\",\"sameAs\":[\"www.linkedin.com\\\/in\\\/eugene-van-der-watt-16828119\"],\"url\":\"https:\\\/\\\/dailyai.com\\\/de\\\/author\\\/eugene\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"ML verbessert R\u00f6ntgenbeugungstechniken, um neue Materialien zu finden | DailyAI","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/dailyai.com\/de\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/","og_locale":"de_DE","og_type":"article","og_title":"ML boosts X-ray diffraction techniques to find new materials | DailyAI","og_description":"Material scientists are constantly trying to find new materials with specific properties but the experimental data they have to wade through is overwhelming. Scientists at the University of Rochester used machine learning to fast-track new materials discovery. Crystalline materials have a well-ordered, repeating crystal lattice structure, a regular, repeating arrangement of atoms, ions, or molecules. The arrangement of these crystal lattices is what gives a material specific properties. Want a material that\u2019s hard, handles high temperatures, and is lightweight? You\u2019ve got to get just the right lattice structure to make that happen. When material scientists synthesize a small amount of","og_url":"https:\/\/dailyai.com\/de\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/","og_site_name":"DailyAI","article_published_time":"2023-12-20T16:29:30+00:00","article_modified_time":"2023-12-21T10:38:38+00:00","og_image":[{"width":1792,"height":1024,"url":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png","type":"image\/png"}],"author":"Eugene van der Watt","twitter_card":"summary_large_image","twitter_creator":"@DailyAIOfficial","twitter_site":"@DailyAIOfficial","twitter_misc":{"Verfasst von":"Eugene van der Watt","Gesch\u00e4tzte Lesezeit":"3\u00a0Minuten"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"NewsArticle","@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#article","isPartOf":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/"},"author":{"name":"Eugene van der Watt","@id":"https:\/\/dailyai.com\/#\/schema\/person\/7ce525c6d0c79838b7cc7cde96993cfa"},"headline":"ML boosts X-ray diffraction techniques to find new materials","datePublished":"2023-12-20T16:29:30+00:00","dateModified":"2023-12-21T10:38:38+00:00","mainEntityOfPage":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/"},"wordCount":493,"publisher":{"@id":"https:\/\/dailyai.com\/#organization"},"image":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#primaryimage"},"thumbnailUrl":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png","keywords":["AI benefits","machine learning"],"articleSection":["Industry"],"inLanguage":"de"},{"@type":"WebPage","@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/","url":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/","name":"ML verbessert R\u00f6ntgenbeugungstechniken, um neue Materialien zu finden | DailyAI","isPartOf":{"@id":"https:\/\/dailyai.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#primaryimage"},"image":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#primaryimage"},"thumbnailUrl":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png","datePublished":"2023-12-20T16:29:30+00:00","dateModified":"2023-12-21T10:38:38+00:00","breadcrumb":{"@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#breadcrumb"},"inLanguage":"de","potentialAction":[{"@type":"ReadAction","target":["https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/"]}]},{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#primaryimage","url":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png","contentUrl":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/12\/material-crystal-lattice.png","width":1792,"height":1024},{"@type":"BreadcrumbList","@id":"https:\/\/dailyai.com\/2023\/12\/ml-boosts-x-ray-diffraction-techniques-to-find-new-materials\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/dailyai.com\/"},{"@type":"ListItem","position":2,"name":"ML boosts X-ray diffraction techniques to find new materials"}]},{"@type":"WebSite","@id":"https:\/\/dailyai.com\/#website","url":"https:\/\/dailyai.com\/","name":"DailyAI","description":"Ihre t\u00e4gliche Dosis an AI-Nachrichten","publisher":{"@id":"https:\/\/dailyai.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/dailyai.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"de"},{"@type":"Organization","@id":"https:\/\/dailyai.com\/#organization","name":"DailyAI","url":"https:\/\/dailyai.com\/","logo":{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/dailyai.com\/#\/schema\/logo\/image\/","url":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/06\/Daily-Ai_TL_colour.png","contentUrl":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/06\/Daily-Ai_TL_colour.png","width":4501,"height":934,"caption":"DailyAI"},"image":{"@id":"https:\/\/dailyai.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/x.com\/DailyAIOfficial","https:\/\/www.linkedin.com\/company\/dailyaiofficial\/","https:\/\/www.youtube.com\/@DailyAIOfficial"]},{"@type":"Person","@id":"https:\/\/dailyai.com\/#\/schema\/person\/7ce525c6d0c79838b7cc7cde96993cfa","name":"Eugene van der Watt","image":{"@type":"ImageObject","inLanguage":"de","@id":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/07\/Eugine_Profile_Picture-96x96.png","url":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/07\/Eugine_Profile_Picture-96x96.png","contentUrl":"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/07\/Eugine_Profile_Picture-96x96.png","caption":"Eugene van der Watt"},"description":"Eugene kommt aus der Elektronikbranche und liebt alles, was mit Technik zu tun hat. Wenn er eine Pause vom Konsum von KI-Nachrichten einlegt, findet man ihn am Snookertisch.","sameAs":["www.linkedin.com\/in\/eugene-van-der-watt-16828119"],"url":"https:\/\/dailyai.com\/de\/author\/eugene\/"}]}},"_links":{"self":[{"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/posts\/8531","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/comments?post=8531"}],"version-history":[{"count":6,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/posts\/8531\/revisions"}],"predecessor-version":[{"id":8559,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/posts\/8531\/revisions\/8559"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/media\/8534"}],"wp:attachment":[{"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/media?parent=8531"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/categories?post=8531"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dailyai.com\/de\/wp-json\/wp\/v2\/tags?post=8531"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}