{"id":1576,"date":"2020-01-30T20:10:40","date_gmt":"2020-01-30T20:10:40","guid":{"rendered":"https:\/\/www.danielparente.net\/en\/2020\/01\/30\/ai-powered-robots-will-be-the-next-big-work-revolution-in-warehouses\/"},"modified":"2020-01-30T20:10:40","modified_gmt":"2020-01-30T20:10:40","slug":"ai-powered-robots-will-be-the-next-big-work-revolution-in-warehouses","status":"publish","type":"post","link":"https:\/\/www.danielparente.net\/en\/2020\/01\/30\/ai-powered-robots-will-be-the-next-big-work-revolution-in-warehouses\/","title":{"rendered":"AI-powered robots will be the next big work revolution in warehouses"},"content":{"rendered":"<h3>Algorithmia AI Generated Summary<\/h3>\n<p> [ad_1]<br \/>\n<\/p>\n<div>\n<p id=\"cz8VBh\">Right now, in a warehouse not far from Berlin, a bright yellow robot is leaning over a conveyor, picking items out of crates with the assurance of a chicken pecking grain. \u201d<\/q><\/aside>\n<\/div>\n<p id=\"E5tlbF\">\u201cWe tested this robot for three or four months, and it can handle nearly everything we throw at it,\u201d Peter Puchwein, vice president of innovation at Knapp, the logistics company that installed the robot, tells <em>The Verge<\/em>. \u201d<\/p>\n<figure class=\"e-image\"><span class=\"e-image__inner\"><\/p>\n<p>    <span class=\"e-image__image \" data-original=\"https:\/\/cdn.\n\n<hr\/>\n<p> [ad_1]<br \/>\n<\/p>\n<div>\n<p id=\"cz8VBh\">Right now, in a warehouse not far from Berlin, a bright yellow robot is leaning over a conveyor, picking items out of crates with the assurance of a chicken pecking grain. <\/p>\n<p id=\"jtXFOJ\">The robot itself doesn\u2019t look that unusual, but what makes it special are its eyes and brain. With the help of a six-lens camera array and machine learning algorithms, it\u2019s able to grab and pack items that would confound other bots. And thanks to a neural network it will one day share with its fellows in warehouses around the world, anything it learns, they\u2019ll learn, too. Show this bot a product it\u2019s never seen before and it\u2019ll not only work out how to grasp it, but then feed that information back to its peers.<\/p>\n<div class=\"c-float-right\">\n<aside id=\"TDD2u0\"><q>\u201cWe want a very high number of these machines out there.\u201d<\/q><\/aside>\n<\/div>\n<p id=\"E5tlbF\">\u201cWe tested this robot for three or four months, and it can handle nearly everything we throw at it,\u201d Peter Puchwein, vice president of innovation at Knapp, the logistics company that installed the robot, tells <em>The Verge<\/em>. \u201cWe\u2019re really going to push these onto the market. We want a very high number of these machines out there.\u201d <\/p>\n<p id=\"V0ACat\">For the bot\u2019s creators, Californian AI and robotics startup Covariant, the installation in Germany is a big step forward, and one that shows the firm has made great strides with a challenge that\u2019s plagued engineers for decades: teaching robots to pick things up. <\/p>\n<p id=\"VEqLPd\">It sounds easy, but this is a task that\u2019s stumped some of the biggest research labs and tech companies. Google has run a <a href=\"https:\/\/www.theverge.com\/2016\/3\/9\/11186940\/google-robotic-arms-neural-network-hand-eye-coordination\" target=\"_blank\" rel=\"noopener\">stable of robot arms<\/a> in an attempt to learn how to reliably grasp things (employees jokingly call it \u201cthe arm pit\u201d), while Amazon holds an <a href=\"https:\/\/www.theverge.com\/2016\/7\/5\/12095788\/amazon-picking-robot-challenge-2016\" target=\"_blank\" rel=\"noopener\">annual competition<\/a> challenging startups to stock shelves with robots in the hope of finding a machine good enough for its warehouses (it hasn\u2019t yet). <\/p>\n<p id=\"kuOcmg\">But Covariant claims its bots can do what others can\u2019t: work 24 hours a day, picking items without fuss. This doesn\u2019t mean that picking is a solved problem (Covariant\u2019s robots uses suction cups not robotic fingers, making the task easier) but it does unlock a lot of potential. This is particularly true in the world of warehouses and logistics, where experts say it\u2019s difficult to find human workers and they need all the robots they can get. <\/p>\n<div class=\"c-float-right\">\n<aside id=\"4GWsxl\"><q>\u201dOur customers don\u2019t trust short demo videos anymore.\u201d<\/q><\/aside>\n<\/div>\n<p id=\"T9xYzp\">Speaking to <em>The Verge<\/em>, Pieter Abbeel, Covariant co-founder and the director of the Berkeley Robot Learning Lab, compares the current market in robot pickers to that of self-driving cars: there\u2019s a lot of hype and flashy demos, but not enough real-world testing and ability.<\/p>\n<p id=\"RhoI7E\">\u201dOur customers don\u2019t trust short demo videos anymore,\u201d says Abbeel. \u201cThey know very well most of the difficulty is in consistency and reliability.\u201d<\/p>\n<p id=\"HmIgVk\">Puchwein of Knapp agrees, telling <em>The Verge<\/em>: \u201cThe typical thing for startups to do is to show some short, well edited videos. But as soon as you try to test the robots, they fail.\u201d<\/p>\n<figure class=\"e-image\"><span class=\"e-image__inner\"><\/p>\n<p>    <span class=\"e-image__image \" data-original=\"https:\/\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg\"><\/p>\n<picture class=\"c-picture\" data-cid=\"site\/picture_element-1580412388_6548_108232\" data-cdata=\"{&quot;asset_id&quot;:19653103,&quot;ratio&quot;:&quot;*&quot;}\"><source srcset=\"https:\/\/cdn.vox-cdn.com\/thumbor\/Hs6GMqxHmlhxw6rELBrTGtw7p4s=\/0x0:6447x4351\/320x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 320w, https:\/\/cdn.vox-cdn.com\/thumbor\/H_JU4PsiZHxuyVzS1vpQYflxNFg=\/0x0:6447x4351\/520x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 520w, https:\/\/cdn.vox-cdn.com\/thumbor\/yGguEYxM_gYbEAJy4D4eSmta1r4=\/0x0:6447x4351\/720x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 720w, https:\/\/cdn.vox-cdn.com\/thumbor\/72oZkbyOpJQHC_iskfARNuHFmmg=\/0x0:6447x4351\/920x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 920w, https:\/\/cdn.vox-cdn.com\/thumbor\/mLoZXltv0RYy7pWh0C8KIqQtdMM=\/0x0:6447x4351\/1120x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1120w, https:\/\/cdn.vox-cdn.com\/thumbor\/DCUQhvF8jX2TagnF1gsTY6NYf6Y=\/0x0:6447x4351\/1320x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1320w, https:\/\/cdn.vox-cdn.com\/thumbor\/siUj-twGE44nrcqY7hnbPkk2HFc=\/0x0:6447x4351\/1520x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1520w, https:\/\/cdn.vox-cdn.com\/thumbor\/d4Oj3xAwpDvwp9fW4vBZu9CHMzs=\/0x0:6447x4351\/1720x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1720w, https:\/\/cdn.vox-cdn.com\/thumbor\/WKtjYpUqUEHZoYUMgsBlkMOllgo=\/0x0:6447x4351\/1920x0\/filters:focal(0x0:6447x4351):format(webp):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1920w\" sizes=\"(min-width: 1221px) 846px, (min-width: 880px) calc(100vw - 334px), 100vw\" type=\"image\/webp\"><img decoding=\"async\" srcset=\"https:\/\/cdn.vox-cdn.com\/thumbor\/xhM0pia7p32J1XyZyjsD5vBLDr0=\/0x0:6447x4351\/320x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 320w, https:\/\/cdn.vox-cdn.com\/thumbor\/0wuprFtzGL6kgzQ0o3lwmA9_hVQ=\/0x0:6447x4351\/520x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 520w, https:\/\/cdn.vox-cdn.com\/thumbor\/JogBv3L6vtKDwXWPu6sVXEpVq0M=\/0x0:6447x4351\/720x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 720w, https:\/\/cdn.vox-cdn.com\/thumbor\/5Euuk2I35Sfk0GsrLk6D60xcKEU=\/0x0:6447x4351\/920x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 920w, https:\/\/cdn.vox-cdn.com\/thumbor\/OLFelcNZRBqLu7WvFRc9D4Hletg=\/0x0:6447x4351\/1120x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1120w, https:\/\/cdn.vox-cdn.com\/thumbor\/U6TZhzk0wTxcgpFhn6XNznSnds4=\/0x0:6447x4351\/1320x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1320w, https:\/\/cdn.vox-cdn.com\/thumbor\/iY8u6qie4OgXdLCZbfznOOhxkOM=\/0x0:6447x4351\/1520x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1520w, https:\/\/cdn.vox-cdn.com\/thumbor\/5EN5ONOhJ3CxZIKmofHcwxaZx48=\/0x0:6447x4351\/1720x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1720w, https:\/\/cdn.vox-cdn.com\/thumbor\/zB0si46uan1zSLbcNMqCepTqpN4=\/0x0:6447x4351\/1920x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg 1920w\" sizes=\"(min-width: 1221px) 846px, (min-width: 880px) calc(100vw - 334px), 100vw\" alt=\"\" data-upload-width=\"6447\" src=\"https:\/\/cdn.vox-cdn.com\/thumbor\/UiHTXSQ8FU_jlc3KgRgklRC0CpI=\/0x0:6447x4351\/1200x0\/filters:focal(0x0:6447x4351):no_upscale()\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653103\/Covariant_co_founders__L_R__Tianhao_Zhang__Rocky_Duan__Peter_Chen__Pieter_Abbeel.jpg\"\/><\/source><\/picture><\/span><\/p>\n<p>  <\/span><\/p>\n<p>    <span class=\"e-image__meta\"><figcaption><em>Covariant\u2019s four co-founders, from left to right: Tianhao Zhang, Rocky Duan, Peter Chen, Pieter Abbeel<\/em><\/figcaption><cite>Image: Covariant<\/cite><\/p>\n<p>    <\/span><\/p>\n<\/figure>\n<p id=\"7VcKJd\">A lot of this hype has been generated by the promise of machine learning. Today\u2019s industrial robots can pick with great speed and precision, but only if what they\u2019re grabbing is equally consistent: regular shapes with easy-to-grasp surfaces. That\u2019s fine in manufacturing, where a machine has to grab the same item over and over again, but terrible in retail logistics, where the objects being packed for shipping vary hugely in size and shape.<\/p>\n<p id=\"7Ja0HS\">Hardcoding a robot\u2019s every move, as with traditional programming, works great in the first scenario but terribly in the second. But if you use machine learning to feed a system data and let it generate its own rules on how to pick instead, it does much, much better. <\/p>\n<p id=\"ec91XS\">Covariant uses a variety of AI methods to train its robots, including reinforcement learning: a trial and error process where the robot has a set goal (\u201cmove object x to location y\u201d) and has to solve it itself. Much of this training is done in simulations, where the machines can take their time, often racking up thousands of hours of work. The result is what Abbeel calls \u201cthe Covariant Brain\u201d \u2014 a nickname for the neural network shared by the company\u2019s robots. <\/p>\n<div class=\"c-float-right\">\n<aside id=\"Bc6HEj\"><q>AI allows robots to pick objects without direct instruction<\/q><\/aside>\n<\/div>\n<p id=\"1z785C\">Covariant, which was <a href=\"https:\/\/www.theverge.com\/2017\/11\/10\/16627570\/robot-ai-grasping-grabbing-embodied-intelligence-startup\" target=\"_blank\" rel=\"noopener\">founded<\/a> in 2017 under the name Embodied Intelligence and comes out of stealth today, is certainly not the only firm applying these methods, though. Numerous startups like <a href=\"https:\/\/www.theverge.com\/2017\/10\/24\/16526248\/kindred-warehouse-robot-the-gap-pilot-program\" target=\"_blank\" rel=\"noopener\">Kindred<\/a> and <a href=\"https:\/\/techcrunch.com\/2019\/04\/08\/righthand-robotics-debuts-a-new-pick-and-place-system\/\" target=\"_blank\" rel=\"noopener\">RightHand Robotics<\/a> use similar fusions of machine learning and robotics. But Covariant is bullish that its robots are better than anyone else\u2019s. <\/p>\n<p id=\"PKnVzK\">\u201cReal world deployments are about extreme consistency and reliability,\u201d says Abbeel. In the warehouse in Germany, Covariant claims its machines can pick and pack some 10,000 different items with accuracy greater than 99 percent \u2014 an impressive figure. <\/p>\n<p id=\"6gAb7c\">Puchwein agrees, and he would know. He\u2019s got 16 years of experience in the industry, including working for Knapp, one of the largest builders of automated warehouses worldwide. It installed 2,000 systems last year with a turnover of more than \u20ac1 billion.<\/p>\n<p id=\"4xBGOa\">Puchwein says the company\u2019s engineers traveled around the world to find the best picking robots and eventually settled on Covariant\u2019s, which it installs as a nonexclusive partner. \u201cNon-AI robots can pick around 10 percent of the products used by our customers, but the AI robot can pick around 95 to 99 percent,\u201d says Puchwein. \u201cIt\u2019s a huge difference.\u201d<\/p>\n<p id=\"WqmQVo\">Puchwein isn\u2019t the only one on board, either. As it comes out of stealth today, Covariant has announced a raft of private backers, including some of the most high-profile names in AI research. They include Google\u2019s head of AI, Jeff Dean; Facebook\u2019s head of AI research, Yann LeCun, and one of the \u201c<a href=\"https:\/\/www.theverge.com\/2019\/3\/27\/18280665\/ai-godfathers-turing-award-2018-yoshua-bengio-geoffrey-hinton-yann-lecun\" target=\"_blank\" rel=\"noopener\">godfathers of AI<\/a>,\u201d Geoffrey Hinton. As Abbeel says, the involvement of these individuals is as much about lending their \u201creputation\u201d as anything else. \u201cInvestors aren\u2019t just about the money they bring to the table,\u201d he says.<\/p>\n<figure class=\"e-image\"><span class=\"e-image__inner\"><\/p>\n<p>    <span class=\"e-image__image \" data-original=\"https:\/\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653120\/covariant_picking_robot.gif\"><\/p>\n<p><img decoding=\"async\" class=\"c-dynamic-image \" alt=\"\" data-chorus-optimize-field=\"main_image\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAUEBAAAACwAAAAAAQABAAACAkQBADs\" data-cid=\"site\/dynamic_size_image-1580412388_4774_108233\" data-cdata=\"{&quot;asset_id&quot;:19653120,&quot;ratio&quot;:&quot;*&quot;}\"\/><noscript><img decoding=\"async\" alt=\"\" src=\"https:\/\/cdn.vox-cdn.com\/uploads\/chorus_asset\/file\/19653120\/covariant_picking_robot.gif\"\/><\/noscript><\/p>\n<p>    <\/span><\/p>\n<p>  <\/span><\/p>\n<p>    <span class=\"e-image__meta\"><figcaption><em>Covariant\u2019s picking robot at work in an Obeta warehouse in Germany<\/em>. <\/figcaption><cite>Image: Covariant<\/cite><\/p>\n<p>    <\/span><\/p>\n<\/figure>\n<p id=\"Y8jsFi\">For all the confidence, investor and otherwise, Covariant\u2019s operation is incredibly small right now. It has just a handful of robots in operation full time, in America and abroad, in the apparel, pharmaceutical, and electronics industries. <\/p>\n<p id=\"7o13pj\">In Germany, Covariant\u2019s picking robot (there\u2019s just one for now) is packing electronics components for a firm named Obeta, but the company says it\u2019s eager for more robots to compensate for a staff shortage \u2014 a situation common in logistics. <\/p>\n<div class=\"c-float-right\">\n<aside id=\"rai3IO\"><q>\u201cIt\u2019s very hard to find people to do this sort of work.\u201d<\/q><\/aside>\n<\/div>\n<p id=\"1lSjBT\">For all the talk of robots taking human jobs, there just aren\u2019t enough humans to do some jobs. One recent industry report <a href=\"https:\/\/ciltuk.org.uk\/News\/Latest-News\/ArtMID\/6887\/ArticleID\/22813\/Logistics-sector-facing-severe-skills-shortage-in-next-five-years-CILT-finds\" target=\"_blank\" rel=\"noopener\">suggests<\/a> 54 percent of logistics companies face staff shortages in the next five years, with warehouse workers among the most in-demand positions. Low wages, long hours, and boring working conditions are cited as contributing factors, as is a falling <a href=\"https:\/\/www.logisticsmgmt.com\/article\/is_there_an_answer_to_the_labor_shortage\" target=\"_blank\" rel=\"noopener\">unemployment rate<\/a> (in the US at least). <\/p>\n<p id=\"7lQVgw\">\u201cIt\u2019s very hard to find people to do this sort of work,\u201d Michael Pultke of Obeta tells <em>The Verg<\/em>e through a translator. He says Obeta relies on migrant workers to staff the company\u2019s warehouses, and that the situation is the same across Europe. \u201cThe future is more robots.\u201d<\/p>\n<p id=\"6plBJi\">And what about the employees that Covariant\u2019s robots now operate alongside \u2014 do they mind the change? According to Pultke, they don\u2019t see it as a threat, but an opportunity to learn how to maintain the robots and get a better type of job. \u201cMachines should do the base work, which is stupid and simple,\u201d says Pultke. \u201cPeople should look after the machines.\u201d <\/p>\n<\/div>\n<p>[ad_2]<br \/>\n<br \/><a href=\"https:\/\/www.theverge.com\/2020\/1\/29\/21083313\/robot-picking-warehouses-logistics-ai-covariant-stealth\" target=\"_blank\" rel=\"noopener\">Original article by  James Vincent  <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Algorithmia AI Generated Summary [ad_1] Right now, in a warehouse not far from Berlin, a bright yellow robot is leaning over a conveyor, picking items out of crates with the assurance of a chicken pecking grain. \u201d \u201cWe tested this robot for three or four months, and it can handle nearly everything we throw at [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1577,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","jetpack_post_was_ever_published":false},"categories":[84],"tags":[],"class_list":["post-1576","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-robotics"],"blocksy_meta":[],"jetpack_featured_media_url":"https:\/\/e928cfdc7rs.exactdn.com\/info\/uploads\/sites\/3\/2020\/01\/AI-powered-robots-will-be-the-next-big-work-revolution-in-scaled.jpg?strip=all","jetpack_shortlink":"https:\/\/wp.me\/p2TFCd-pq","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts\/1576","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/comments?post=1576"}],"version-history":[{"count":0,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/posts\/1576\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/media\/1577"}],"wp:attachment":[{"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/media?parent=1576"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/categories?post=1576"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.danielparente.net\/en\/wp-json\/wp\/v2\/tags?post=1576"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}