{"id":7980,"date":"2024-08-21T14:13:51","date_gmt":"2024-08-21T14:13:51","guid":{"rendered":"https:\/\/sites.hslu.ch\/werkstatt\/?p=7980"},"modified":"2025-08-21T07:37:48","modified_gmt":"2025-08-21T07:37:48","slug":"fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024","status":"publish","type":"post","link":"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/","title":{"rendered":"+FO Artificial Intelligence \u2013 Creative Practices and Critical Perspectives 2024"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_section el_class=&#187;dkw-section-lead&#187;][vc_row][vc_column width=&#187;2\/3&#8243; offset=&#187;vc_col-sm-offset-2&#8243;][vc_column_text css=&#187;&#187;]+FO Artificial Intelligence \u2013 Creative Practices and Critical Perspectives[\/vc_column_text][\/vc_column][\/vc_row][\/vc_section][vc_section el_class=&#187;dkw-section-content&#187;][vc_row][vc_column width=&#187;1\/3&#8243; el_class=&#187;dkw-col-toc&#187; offset=&#187;vc_col-lg-3&#8243;][vc_column_text]<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<span class=\"ez-toc-title-toggle\"><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#How_algorithms_learn_to_see_and_to_create_images\" >How algorithms learn to see and to create images<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Nicolas_Maleve\" >Nicolas Malev\u00e9<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Practical_Introduction_to_AI_Tools\" >Practical Introduction to AI Tools<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Guillaume_Massol\" >Guillaume Massol<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Doing_Critical_Technical_Art_Practice\" >Doing Critical Technical Art Practice<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Winnie_Soon\" >Winnie Soon<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Train_your_own_Model\" >Train your own Model<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Thomas_Knuesel_and_Alexandra_Pfammatter\" >Thomas Kn\u00fcsel and Alexandra Pfammatter<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Selfstudy\" >Selfstudy<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Presentation\" >Presentation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/sites.hslu.ch\/werkstatt\/fo-artificial-intelligence-creative-practices-and-critical-perspectives-2024\/#Open_Studio\" >Open Studio<\/a><\/li><\/ul><\/nav><\/div>\n[\/vc_column_text][\/vc_column][vc_column width=&#187;2\/3&#8243; el_class=&#187;dkw-col-content&#187; offset=&#187;vc_col-lg-6&#8243;][vc_column_text css=&#187;&#187;]<\/p>\n<h3><span class=\"ez-toc-section\" id=\"How_algorithms_learn_to_see_and_to_create_images\"><\/span>How algorithms learn to see and to create images<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<h4><span class=\"ez-toc-section\" id=\"Nicolas_Maleve\"><\/span>Nicolas Malev\u00e9<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p><strong>2.+ 3. September | <\/strong><strong>9:15 ~ 12:00 \/ 13:00 ~17:00 | physical<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-4200\" src=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2022\/08\/zero-degree-confidence.png\" alt=\"\" width=\"500\" height=\"332\" \/><\/p>\n<p>Every day, images are published by millions on the Internet. And these constitute only a fraction of all the images that are produced and archived. Computer Vision algorithms are designed to make sense of this sheer mass of visual content. They play a central role in the management of image traffic on the networks, as well as in the preparation of diagnosis in medicine or in analysing never ending footage of surveillance imagery. Algorithms also generates new images (eg. Dall-e, Midjourney, Stable Diffusion). From deep fakes that can map one&#8217;s face to a famous actor video or politician to deep dreams where machine algorithms produce their own hallucinated version of the world, the visual techniques powered by artificial intelligence have largely infiltrated film production and even traditional software such as Adobe Photoshop. This evolution has lead to spectacular results and in return has received a lot of coverage<\/p>\n<p>What is less discussed publicly is how machines acquire the ability to interpret and generate images. Machine learning algorithms learn what is an image and what it represents from series of examples selected by humans.\u00a0 To teach machines how to see, computer scientists curate visual datasets. These datasets can be understood as large collections of photographs. State of the art\u00a0 datasets contain billions of items. These last years have seen a proliferation of datasets. From animals to computer parts, mangas to clothing, the visual world is collected and classified at an extraordinary scale.<\/p>\n<p>In this workshop, we will explore these large collections of photographs, how they are assembled, where they come from, how they can become objects of inquiry or material for creation. We will also explore what it means to look at those extraordinary amount of images, to classify them and to curate them. We will playfully learn the importance of images, and in particular photographs, for teaching computers how to see. We will experience what kind of vision and speed correspond to the model of vision used by algorithms. And we will delve in prompt-engineering to push generative AI outside of its comfort zone. This will allow us to ask new questions about the evolution of the technology that constitute a key component of our visual practices as artists and citizens.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Practical_Introduction_to_AI_Tools\"><\/span>Practical Introduction to AI Tools<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<h4><span class=\"ez-toc-section\" id=\"Guillaume_Massol\"><\/span>Guillaume Massol<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p><strong>4.+ 5. September | 9:15 ~ 12:00 \/ 13:00 ~17:00 | physical<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-5728\" src=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-1000x997.png\" alt=\"\" width=\"1000\" height=\"997\" srcset=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-1000x997.png 1000w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-250x250.png 250w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-768x766.png 768w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-1536x1532.png 1536w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-848x846.png 848w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-1140x1137.png 1140w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-1170x1167.png 1170w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640-600x598.png 600w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2021\/07\/Bildschirmfoto-2023-08-31-um-16.40.51-e1693925318640.png 1598w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/>In the second workshop we will familiarise ourselves with how machine learning works in practice. After a short introduction, you will have the opportunity to try out different ML models and their different applications with an AI toolkit. Once you are familiar with the tools, you will start to work out your own individual machine learning experiments.<\/p>\n<p>External Links:<\/p>\n<p><a href=\"https:\/\/blog.massol.me\/author\/guillaume\/\">https:\/\/blog.massol.me\/author\/guillaume\/<\/a><br \/>\n<a href=\"https:\/\/github.com\/gu-ma\">https:\/\/github.com\/gu-ma<\/a><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Doing_Critical_Technical_Art_Practice\"><\/span><span class=\"s1\">Doing Critical Technical Art Practice<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<h4><span class=\"ez-toc-section\" id=\"Winnie_Soon\"><\/span>Winnie Soon<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p><strong>5. September | <\/strong><strong>17:00 ~ 18:15 | o<\/strong><strong>nline<\/strong><\/p>\n<p class=\"p1\"><span class=\"s1\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-7969\" src=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1000x667.jpg\" alt=\"\" width=\"1000\" height=\"667\" srcset=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1000x667.jpg 1000w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-768x512.jpg 768w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1536x1024.jpg 1536w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-2048x1366.jpg 2048w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-848x565.jpg 848w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1140x760.jpg 1140w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1170x780.jpg 1170w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-1920x1280.jpg 1920w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/08\/WinnieSoon-600x400.jpg 600w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/>This talk delves into how Machine Learning (ML) and Natural Language Processing (NLP) can be explored as modes of inquiry through the lens of critical technical art practice. Moving beyond their predictive functions, I employ these technologies in my artistic work to raise new questions and possibilities for understanding and reimagining our relationship with artificial intelligence.<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">By engaging with data(sets), code and algorithms, I investigate the intersection between coding and thinking. Inspired by scholars such as Wendy Hui Kyong Chun and Philip Agre, I emphasise &#171;doing thinking&#187;\u2014a process where technical skills and critical inquiry converge for practice-based research.<\/span><\/p>\n<p>More Infos:<\/p>\n<p><a href=\"https:\/\/sites.hslu.ch\/werkstatt\/winnie-soon\/\">https:\/\/sites.hslu.ch\/werkstatt\/winnie-soon\/<\/a><\/p>\n<p>External Link:<\/p>\n<p><a href=\"http:\/\/www.siusoon.net\/\">http:\/\/www.siusoon.net<\/a><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Train_your_own_Model\"><\/span>Train your own Model<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<h4><span class=\"ez-toc-section\" id=\"Thomas_Knuesel_and_Alexandra_Pfammatter\"><\/span>Thomas Kn\u00fcsel and Alexandra Pfammatter<span class=\"ez-toc-section-end\"><\/span><\/h4>\n<p><strong>6. + 9. September | 9:15 ~ 12:00 \/ 13:00 ~17:00 | physical<\/strong><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-7759\" src=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1000x778.png\" alt=\"\" width=\"1000\" height=\"778\" srcset=\"https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1000x778.png 1000w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-768x597.png 768w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1536x1195.png 1536w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-2048x1593.png 2048w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-848x660.png 848w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1140x887.png 1140w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1170x910.png 1170w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-1920x1493.png 1920w, https:\/\/sites.hslu.ch\/werkstatt\/wp-content\/uploads\/sites\/13\/2024\/06\/PilatusRainbow-600x467.png 600w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/p>\n<p>In this workshop we will show you how to work with generative AI and train your own AI models. We will look at how generative AI works and explore different ways to control the output of generative AI models. In a second step, we will try to build a dataset to train your own image generator to generate your own style, a specific object or a specific character in different variations.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Selfstudy\"><\/span>Selfstudy<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>10. &#8211; 11. September | 9:15 ~ 12:00 \/ 13:00 ~17:00\u00a0<\/strong><\/p>\n<p><strong>12. September | 09:15 ~ 12:00<\/strong><\/p>\n<p>Time to do your own research or experiments, be curious &#8211; feel free to ask for help if you need advice.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Presentation\"><\/span>Presentation<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>12. September | 13:00 ~17:00\u00a0<\/strong><\/p>\n<p>a very short and brief presentation (max. 15 min per person) of your own research \/ work of the past Days.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Open_Studio\"><\/span>Open Studio<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><strong>13. September | 09:00 ~ 12:00<\/strong><\/p>\n<p>Miniexhibition Setup<\/p>\n<p><strong>13. September | 12:00 ~ 14:00<\/strong><\/p>\n<p>Studiovisit in the other + Focus Modules[\/vc_column_text][\/vc_column][vc_column width=&#187;1\/3&#8243; el_class=&#187;dkw-col-micro&#187; offset=&#187;vc_col-lg-3&#8243;][\/vc_column][\/vc_row][\/vc_section][vc_section el_class=&#187;dkw-dontprint&#187;][vc_row disable_element=&#187;yes&#187;][vc_column][vc_column_text]\u2014 \u2014 \u2014 INFO: In beiden nachfolgenden Post Grids die passenden Recipies und die passenden Talks\u00a0 ausw\u00e4hlen \u2014 \u2014 \u2014<br \/>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text]<\/p>\n<h2>Passende Tools<\/h2>\n<p>[\/vc_column_text][vc_basic_grid post_type=&#187;ids&#187; element_width=&#187;2&#8243; gap=&#187;10&#8243; item=&#187;517&#8243; css=&#187;&#187; grid_id=&#187;vc_gid:1743071456415-e2f443a4-bda1-7&#8243; include=&#187;5625, 6097, 6220, 7730, 7852&#8243;][\/vc_column][\/vc_row][\/vc_section][vc_section el_class=&#187;dkw-dontprint&#187;][vc_row][vc_column][vc_column_text]<\/p>\n<h2>Passende Talks<\/h2>\n<p>[\/vc_column_text][vc_basic_grid post_type=&#187;ids&#187; element_width=&#187;2&#8243; gap=&#187;10&#8243; item=&#187;517&#8243; css=&#187;&#187; grid_id=&#187;vc_gid:1743071456415-8d679e27-9a77-9&#8243; include=&#187;7968, 4219, 5606, 930, 2975&#8243;][\/vc_column][\/vc_row][\/vc_section]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_section el_class=&#187;dkw-section-lead&#187;][vc_row][vc_column width=&#187;2\/3&#8243; offset=&#187;vc_col-sm-offset-2&#8243;][vc_column_text css=&#187;&#187;]+FO Artificial Intelligence \u2013 Creative Practices and Critical Perspectives[\/vc_column_text][\/vc_column][\/vc_row][\/vc_section][vc_section el_class=&#187;dkw-section-content&#187;][vc_row][vc_column width=&#187;1\/3&#8243; el_class=&#187;dkw-col-toc&#187; offset=&#187;vc_col-lg-3&#8243;][vc_column_text][\/vc_column_text][\/vc_column][vc_column width=&#187;2\/3&#8243; el_class=&#187;dkw-col-content&#187; offset=&#187;vc_col-lg-6&#8243;][vc_column_text css=&#187;&#187;] How algorithms learn [&hellip;]<\/p>\n","protected":false},"author":50,"featured_media":4200,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[15,12],"tags":[],"class_list":["post-7980","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-mediadock","category-pastevents"],"acf":[],"_links":{"self":[{"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/posts\/7980","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/users\/50"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/comments?post=7980"}],"version-history":[{"count":27,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/posts\/7980\/revisions"}],"predecessor-version":[{"id":9794,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/posts\/7980\/revisions\/9794"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/media\/4200"}],"wp:attachment":[{"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/media?parent=7980"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/categories?post=7980"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.hslu.ch\/werkstatt\/wp-json\/wp\/v2\/tags?post=7980"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}