Host: How did you come to be an intern at MSR?<\/strong><\/p>\nWei Dai: It was a really good chance that last year in summer, Microsoft Research, the crypto group, actually, hosted one workshop for the standardization of homomorphic encryption. And they invited a lot of very famous scholars to Microsoft Research, the campus. And I actually,\u00a0 came with my advisor, and that\u2019s how I met Kristin, Kim and everyone in the group. And we introduced our work, everyone was thinking, \u201cOK, we never know, on GPU, it can be so fast.\u201d And Kristin got interested. She asked me, \u201cSo, would you like to do internship next year, summer?\u201d So, we scheduled it out and that\u2019s why I came here.<\/p>\n
Host: Well, give us a little overview of homomorphic encryption and what\u2019s its purpose is.<\/strong><\/p>\nWei Dai: Basically, it\u2019s not just any cipher or encryption scheme. It does not only do the encryption protector data, but also allow computation on the encrypted data, which was impossible before.<\/p>\n
Host: So, just to clarify, if I encrypt data and then I want to do something with it, as you say operate on it, traditionally, I\u2019ve had to unencrypt it be able to do something with it.<\/strong><\/p>\nWei Dai: Right. Yeah. With homomorphic encryption you don\u2019t have to decrypt the data, but you can perform computation, and whoever did the computation return you the result in an encrypted form. Where you are the one who owns the data, you are the only one that can decrypt the result.<\/p>\n
Host: So, you\u2019ve got the key. Nobody else gets the key to decrypt it.<\/strong><\/p>\nWei Dai: Yes.<\/p>\n
Host: To be able to operate on it, and then you can do this homomorphic encryption, operate on the data, get it back and then you can see what happened\u2026<\/strong><\/p>\nWei Dai: Yes, correct.<\/p>\n
Host: Tell us about the project that you\u2019re working on, maybe starting with the problem of the speed of homomorphic encryption to begin with?<\/strong><\/p>\nWei Dai: Ten years ago, people start building homomorphic encryption schemes mathematically, and also doing software or hardware implementations. At the beginning, the encrypted data are so large compared to clear data, and also the computation on encrypted data was so slow, Microsoft Research has started this library called the SEAL library, which is Simple Encrypted Arithmetic Library. So, the goal of building this library is to simplify how to use homomorphic encryption and push for more efficient computations. And for the past three years, the performance, the security, the user experience, everything has been improved by a lot. And they would like to see how can we accelerate the library on the GPU, on different hardware. And we also have another intern who is doing the implementation on FPGA. Which is, we are really trying all the hardware devices to see what we can get.<\/p>\n
Host: So, the speed-up of the runtime is what you\u2019re looking for?<\/strong><\/p>\nWei Dai: Yeah, exactly. The faster the better. And according to our experience, on a GPU, usually you can achieve at least 20 times speed up. And if the scheme is really well designed, you can reach two orders of magnitude, which is a hundred times. And on FPGA you can achieve something similar.<\/p>\n
Host: So, tell us about your library. This is a fairly unique, innovative thing that you\u2019ve been working on.<\/strong><\/p>\nWei Dai: Yeah, so suppose I am a data company. On the client side, I can provide them software to encrypt their data or doing decryption later. And the library itself also provides service for the data company who can design an application of machine learning or genomic data analysis. They provide the data analysis service to the clients in an encrypted form.<\/p>\n
Host: Sure.<\/strong><\/p>\nWei Dai: With the help of the SEAL library, everything can be simplified. They don\u2019t have to understand too much about the homomorphic encryption, they just know this is realizable and using our library will make your life much easier.<\/p>\n
Host: So how has that played out? I mean is this available yet, or is it still in the research phase, or where is it?<\/strong><\/p>\nWei Dai: So, the research never stops! So, what we do is we keep releasing new versions of the library. And the library is currently published under Microsoft license. And we do have a lot of clients in other groups who are using this library internally at Microsoft Research.<\/p>\n
Host: What do you hope to see in this area in the future?<\/strong><\/p>\nWei Dai: We do see a promising future in this area, because it is still fairly young, over nine or ten years so far.<\/p>\n
Host: Yeah.<\/strong><\/p>\nWei Dai: And now, because there are an urgent need for privacy protection, and there\u2019s regulations and laws making towards this direction, I think homomorphic encryption has a much brighter future.<\/p>\n
Host: Tell us about your advisor and the group you\u2019re working in, what have you learned from the people you\u2019re working with this summer?<\/strong><\/p>\nWei Dai: In our group, we have four \u2013 five full-time employees, and also we have five new interns this summer. So, mainly, I am the one who is working on GPU. We do have a lot of meetings together because different people have different opinions. And they might be able to see, for example, my colleagues, will see, what did I do wrong in these procedures somewhere. And they can correct me and give me another idea. It is very helpful.<\/p>\n
Host: So, it is group constructive criticism.<\/strong><\/p>\nWei Dai: Right, right.<\/p>\n
Host: Who is you advisor?<\/strong><\/p>\nWei Dai: So, Kim Laine, he is the one who makes this SEAL Library really useful right now, and ends up being used by many other groups. Like we have people working on machine learning, people working on compilers and everyone is curious about how we can use this? And they are trying to use it right now. Hopefully, we can come up with some joint work and end up in a product.<\/p>\n
Host: Yeah. So, when you came here, did you bring this project with you, the GPU speed-up scenario for homomorphic encryption?<\/strong><\/p>\nWei Dai: So, accelerating SEAL Library on GPU has been the plan by the Microsoft Research and also in our group. However, in this field, it requires some special skills, and not many people in this area have actually done GPU implementations. I am one of them, and I was lucky to have the best performance out of it. When I came here, they just told me, OK, you are specialized in this, please do this. Just\u2026<\/p>\n
Host: Ready, go. Um. Tell us a bit about the performance, like that you\u2019ve alluded to, that you had the best performance. What are we comparing that to?<\/strong><\/p>\nWei Dai: Traditionally, we were just comparing, suppose you have an algorithm. I implement it on a GPU and achieve, probably, more than hundred times speed-up compared to running it on the CPU. Even compared to the best CPU implementation, it could be a hundred times more. And now, this is not just a simple algorithm, it is a whole library, and even the algorithm itself is hard to implement. It involves a lot of research work because talking about how to do this computation is one thing. Actually adding two numbers on a computer is different!<\/p>\n
Host: Sure.<\/strong><\/p>\nWei Dai: And on different hardware is a new area. This summer, I have been working on accelerating SEAL. We are expecting more than 20 times at least. Hopefully, again, the faster the better!<\/p>\n
Host: What\u2019s next for you, Wei?<\/strong><\/p>\nWei Dai: This fall I will be focusing on finishing my PhD, and doing the dissertation and the defense. After that I would like to go in industry, and Microsoft Research, actually, is one of the best destinations for me, if I can come back.<\/p>\n
Host: Yeah. My bet is yes.<\/strong><\/p>\nWei Dai: Thanks, I hope.<\/p>\n
Host: So, but a career in research continues?<\/strong><\/p>\nWei Dai: Yeah. I feel this area is too promising to leave right now. I would like to stay in this area and continue my research. I think right now, internally, we have been doing something very meaningful and we do have some prototypes that is driven by homomorphic encryption, it shows a very good result. Not ideally practical, but good enough for you to consider using it.<\/p>\n
Host: Wei Dai, this podcast has been a very good result! Thanks for coming in and sharing this with us, it is so interesting.<\/strong><\/p>\nWei Dai: Thank you.<\/p>\n
(music plays)<\/strong><\/p>\nHost: Sara Beery may be the only MSR intern who was also a professional ballerina. But her passion now is using technology to help protect the environment. She joined researcher Dan Morris and spent her summer building AI models for motion-triggered cameras used in wildlife conservation.<\/strong><\/p>\nHost: Sara Beery, welcome to the podcast.<\/strong><\/p>\nSara Beery: Thank you.<\/p>\n
Host: You have a really\u2026 I say this to a lot of people, but you really do have an interesting, unique, unconventional path to this place. Tell us a bit about your personal story, and then we will get to the details of what you\u2019re doing later. But I want to hear about you.<\/strong><\/p>\nSara Beery: Like you said, I definitely had an unconventional path to tech. So, I grew up here in Seattle and I moved alone, at 16, to Atlanta to dance with the Atlanta Ballet. Ballet was my entire life. I absolutely loved it. I continued on from there to dance in San Francisco and New York City, actually all over the world, but actually while I was in Atlanta, I was living really close to Georgia Tech. And I was really broke, because I was a ballerina. And Georgia Tech would have these open talks that would have free food. And so, I started going to these talks and hearing about all this really amazing research basically, just as a ticket for free food. And I actually wasn\u2019t even sure I was supposed to be there. You\u2019re probably supposed to be a student, but I lived close enough, it was fine. And I, more and more, as I was hearing what people were doing, really started to think, like, \u201cOK, well, I can\u2019t do ballet forever and I always really loved school. Like, maybe I\u2019ll go back after ballet and become an engineer, so I can help solve these problems for people in the world.\u201d And I have always been really passionate, specifically, about environmental sustainability and conservation. Probably some of that comes from just growing up in the beautiful Pacific Northwest. I got this idea in my head that I, you know, after I retired from ballet, I was going to go study to be a green energy engineer. I retired actually kind of early for a ballerina, but a big part of that was because I had this dream to do something else as well. And so, I went back to school. I went to Seattle U. Studied electrical engineering. And along the way, found out that I actually loved math. And this was astonishing for me, because I absolutely hated math growing up! It was something I never felt good at. And I was in really high-level math classes in school. You know, I took calculus in high school, even before I graduated early, but I thought I was really bad at it. And I wasn\u2019t. I am actually quite good at math. But it took until college, and until I had teachers who really encouraged me, for me to even think that was an opportunity for me. I thought I was really going to struggle with the math classes. And instead, with the right teachers, and with the right encouragement, I totally thrived. So, I added a math degree. Along the way, found out that actually, I was really passionate about research, and so I ended up, now I\u2019m in a PhD program at Caltech, doing computer vision research, and specifically focused on environmental sustainability and conservation.<\/p>\n
Host: So where are you in that process right now?<\/strong><\/p>\nSara Beery: So, I just finished my second year. I will be starting my third year in the fall.<\/p>\n
Host: All right, so talk about your path here, as an intern, at Microsoft Research this summer.<\/strong><\/p>\nSara Beery: So, as I said, I have been really passionate about environmental sustainability from the time I was a child. And when I actually decided to go to Caltech, I worked with Pietro Perona, who is an absolutely amazing advisor. One of the reasons I decided to work for his lab, is that he has shown this real commitment to projects that are helping the world, or helping people, and that was something that was really important to me. After I finished my first year, I was looking for projects that would really further this goal. And I had previously done research with camera traps, which are this really interesting way that technology has been assisting people who study wildlife conservation. So, instead of having to do fieldwork, or a catch-and-release type study, which is quite invasive, to monitor animal populations, behavior, the density, like what the effects of climate change and urbanization are. They\u2019re able to just put cameras out in the field. They\u2019re motion- or heat-sensored cameras. Really the bottleneck there is just sorting the images. So these people\u2026<\/p>\n
Host: Wow.<\/strong><\/p>\nSara Beery: \u2026go through, they put out hundreds of cameras. They do a large-scale study, and then they spend hundreds and hundreds of hours just sorting the photos by what they see. I was at Caltech, trying to figure out what project I wanted to start with, and this group from the National Park Service and the U.S. Geological Survey reached out to Pietro and they said, \u201cYou know, we\u2019re really interested in trying to find a way to use computer vision to automatically go through this process of detecting animals, classifying their species and, long-term, maybe even doing individual identification. And I was like, \u201cActually I have a lot of experience with camera trap photos already and that sounds great.\u201d So, I started building models for them and curating their data set. And then I went to Grace Hopper last year, and at Grace Hopper, I just so happened to stop by the Microsoft booth and I was talking to Ossie Roycroft and you know I was like, \u201cI don\u2019t really need an internship. I am not really sure that it works with my PhD, but I was curious if you know what\u2019s going on at Microsoft Research at the intersection of AI and environmental sustainability.\u201d And she was like, \u201cOh, you should reach out to Lucas Joppa,\u201d who at the time was the head of this Nature + Computing group that was exactly what I was looking for. Like, somewhere where you could do AI for environmental sustainability.<\/p>\n
Host: Yeah.<\/strong><\/p>\nSara Beery: I reached out to him, and he was like, \u201cActually we\u2019re\u2026 you know, it\u2019s not been announced yet, but we\u2019re going to start this huge new program at Microsoft called AI for Earth (opens in new tab)<\/span><\/a>.\u201d And it was really serendipitous for me, but it\u2019s also so inspiring to see that Microsoft has made this commitment. So, this is a company-wide initiative to basically sit at the intersection of sustainability and AI. Hearing about that really encouraged me to say, \u201cOK, yeah, no, I am happy to come work for you.\u201d<\/p>\nHost: \u201cI\u2019ll be your intern!\u201d<\/strong><\/p>\nSara Beery: \u201cI\u2019ll help build your tools, you know.\u201d And actually it\u2019s kind of perfect because in academia, I can build lots of models, but I\u2019m not a team of software engineers.<\/p>\n
Host: No.<\/strong><\/p>\nSara Beery: So, if I build a tool, it\u2019s kind of difficult to actually get it to where it\u2019s widespread and easily accessible for the people the tool was meant for.<\/p>\n
Host: Right.<\/strong><\/p>\nSara Beery: And AI for Earth is this awesome bridge between that. It gives people like me the opportunity to build models, build tools, that can use cutting edge computer vision algorithms to work with this complicated data, and then you actually are able to use this team of software engineers, who are building APIs and building tools and dealing with the user interface. And you know, hopefully, by the end of the summer, we\u2019ll have actual tools that scientists can use to actually start sorting their data.<\/p>\n
Host: Tell us about the project then, specifically, that you\u2019re working on as an intern here.<\/strong><\/p>\nSara Beery: What I am specifically focusing on is I\u2019m taking these camera trap images and I am training detectors, which are able to look at an image and not only tell if there is an animal in the image but actually localize the animal. You are able to train models that work astonishingly well on camera traps, as long as you are using them at exactly the camera locations you\u2019ve trained them on. But, if we want these tools to be something that\u2019s actually really beneficial to the entire ecology community, biology community, where they are using these camera traps to do their research, we need to make sure that, if you are starting up in a new region, or even in a region we\u2019ve dealt with before, but it\u2019s a completely new set of cameras, that these models will be able to work for you as quickly as possible.<\/p>\n
Host: Yeah.<\/strong><\/p>\nSara Beery: And so, what I\u2019m doing is, I am working on trying to train detectors that are able to generalize well to these new areas and these new regions. So, I don\u2019t know if you\u2019ve heard of Zooniverse, but Zooniverse is this big citizen science platform for scientists to get crowd-sourced data annotations. And forty percent of their projects are camera trap projects. And the largest one is this project called Snapshot Serengeti, where these cameras have been out continuously for ten years in Africa. And I was talking to this woman who has been working with many different camera trap groups all over the world. And I asked her, \u201cWhat\u2019s your estimate, like, back of the napkin, let\u2019s do a calculation, how many active camera traps do you think there are in the world right now, running?\u201d And she was like, thought about it for a second and said, \u201cAt least 500,000, maybe a million.\u201d<\/p>\n
Host: Wow.<\/strong><\/p>\nSara Beery: That\u2019s amazing.<\/p>\n
Host: That\u2019s great.<\/strong><\/p>\nSara Beery: If you think about how cheap cameras are. Some of these cameras are like a hundred dollars. Think about how well you could monitor the effect of a new science policy on your wild animal population if you had the real-time ability to put out a camera and just track everything you saw and just stream that data and you could actually build sort of a global-scale population density map for all these different animal species.<\/p>\n
Host: Wow.<\/strong><\/p>\nSara Beery: I don\u2019t think it\u2019s going to happen soon, but I think it\u2019s definitely going to happen, and I am hoping my work can contribute to that.<\/p>\n
Host: Tell us about your advisor and the group you\u2019re in. The people that you\u2019re working with. What have you learned, what\u2019s been your experience?<\/strong><\/p>\nSara Beery: So, my direct boss is Dan Morris. He is gung-ho passionate about saving animals and he has been a really valuable resource for me, just in terms of learning what it takes to build a tool that people can use. He has a lot of intuition about sort of how to navigate the politics of a large company, and how to increase visibility, and how to basically make sure that people care about what you\u2019re doing so that it actually gets done.<\/p>\n
Host: Yeah.<\/strong><\/p>\nSara Beery: And that\u2019s something that I hadn\u2019t really had to think about as much before, right? I mean, I have an NSF Fellowship, so I basically have the ability to work on what I care about. But I don\u2019t have to convince anyone else to care about it. Yet. But now I am realizing, actually, how important that is. I think the ability to share your passions with others, and to really make it super-clear like, why you\u2019re passionate and get other people excited about it too? It\u2019s probably like the best way to make things happen.<\/p>\n
Host: Yeah, that\u2019s a skill that you will want in the future. What\u2019s next for you Sara?<\/strong><\/p>\nSara Beery: Well, I am going to work my butt off for the rest of this internship. Hopefully take advantage, as much as possible, of the resources I have here. I am going back to Caltech right when I finish. Being in a PhD is\u2026 it\u2019s a long haul, but it\u2019s exciting. And it\u2019s kind of the first time in my life that I haven\u2019t had to be thinking immediately about like, what does the future hold? And I\u2019m pretty sure that if I just keep working in areas I really care about, that I\u2019ll be able to find a way to continue to do that after I finish my PhD.<\/p>\n
Host: And what would you see yourself doing in the future?<\/strong><\/p>\nSara Beery: I don\u2019t know! If Microsoft keeps funding AI for Earth, maybe I will work here! I would love to continue to find ways to bring AI algorithms and bring the skills that I\u2019m gaining at Caltech to play in areas where you can make a huge impact where they traditionally don\u2019t have access.<\/p>\n
Host: And hopefully you won\u2019t need to look for places that have free food\u2026<\/strong><\/p>\nSara Beery: (laughs) Yeah! Though I will say, I think being really poor at least once in your life is very good for you because you are not afraid of it anymore.<\/p>\n
Host: I hear you. What\u2019s harder, ballet or high-tech research?<\/strong><\/p>\nSara Beery: Ballet. (laughs) In some ways, you know, doing research somewhere like Caltech can be insanely difficult, but I don\u2019t wake up in pain every day. And I gotta say, it feels pretty good to be able to like, get out of bed and not feel like an 80-year-old.<\/p>\n
Host: Do you still dance?<\/strong><\/p>\nSara Beery: I do. Caltech has a ballet club. So I um\u2026<\/p>\n
Host: A club? Nice.<\/strong><\/p>\nSara Beery: Yes, the Caltech Ballet Club. I take classes on Sundays on a wood floor in the gym. It\u2019s uh\u2026 (laughs) it\u2019s, but it\u2019s nice to just keep my toes in.<\/p>\n
Host: Literally.<\/strong><\/p>\nSara Beery: Literally. (laughs)<\/p>\n
Host: Sara Beery, it\u2019s been so delightful talking to you. Thank you for coming in today.<\/strong><\/p>\nSara Beery: Yeah. Thank you so much. This has been really fun.<\/p>\n
(music plays)<\/strong><\/p>\nIf you\u2019re interested in applying for an internship at Microsoft Research, visit Careers.Microsoft.com (opens in new tab)<\/span><\/a><\/strong><\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":"
Episode 42, September 19, 2018 – On today\u2019s podcast, you\u2019ll hear the stories of three of these interns, each of whom came to Microsoft Research from a different field, with a different story and a different perspective, but all of whom share MSR\u2019s passion for finding innovative solutions to the world\u2019s toughest challenges.<\/p>\n","protected":false},"author":37074,"featured_media":505652,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"msr-url-field":"https:\/\/player.blubrry.com\/id\/37820970\/","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"categories":[240054],"tags":[195969,195970,240852],"research-area":[13556,198583,13554,13558],"msr-region":[],"msr-event-type":[],"msr-locale":[268875],"msr-post-option":[],"msr-impact-theme":[],"msr-promo-type":[],"msr-podcast-series":[],"class_list":["post-505649","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-msr-podcast","tag-internships","tag-internships-at-microsoft-research","tag-podcast","msr-research-area-artificial-intelligence","msr-research-area-ecology-environment","msr-research-area-human-computer-interaction","msr-research-area-security-privacy-cryptography","msr-locale-en_us"],"msr_event_details":{"start":"","end":"","location":""},"podcast_url":"https:\/\/player.blubrry.com\/id\/37820970\/","podcast_episode":"","msr_research_lab":[],"msr_impact_theme":[],"related-publications":[],"related-downloads":[],"related-videos":[],"related-academic-programs":[],"related-groups":[],"related-projects":[],"related-events":[],"related-researchers":[],"msr_type":"Post","featured_image_thumbnail":"","byline":"","formattedDate":"September 19, 2018","formattedExcerpt":"Episode 42, September 19, 2018 - On today\u2019s podcast, you\u2019ll hear the stories of three of these interns, each of whom came to Microsoft Research from a different field, with a different story and a different perspective, but all of whom share MSR\u2019s passion for…","locale":{"slug":"en_us","name":"English","native":"","english":"English"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/505649"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/37074"}],"replies":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/comments?post=505649"}],"version-history":[{"count":13,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/505649\/revisions"}],"predecessor-version":[{"id":664845,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/posts\/505649\/revisions\/664845"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/505652"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=505649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/categories?post=505649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/tags?post=505649"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=505649"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=505649"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=505649"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=505649"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=505649"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=505649"},{"taxonomy":"msr-promo-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-promo-type?post=505649"},{"taxonomy":"msr-podcast-series","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-podcast-series?post=505649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}