Hi y'all, she was sitting yes, I have all my antlers because it is December and I just Feel like wearing some antlers. Okay so Yes, I have my Christmas tumbler Okay Spending the holidays if you're single how to spend the holidays if you're single, okay? because I know a lot of People are single and they start feeling bad this time of year. So I just want to tell y'all it's okay I remember when I was single during the holiday season. I had so much fun. I didn't even realize I was single You know why? Because all my friends were single my sister was single Well, some of the years And we just used to hang out and have fun go to movies go to dinner parties Christmas parties Clubs, this is when I was younger y'all and I would just not even think about being single because I would be having so much fun Meeting so many people. I will be dating because I wasn't really attached to anyone so I could go out on dates I could go walk around the mall for hours Try on stuff You know stuff like that and it was just I didn't get stuck in that moment thinking oh, I'm so single I'm so single. I'm so single. I Wish I had this I wish I had that party on me adjust this lighting because there we go so If you're starting to feel that holiday drag Go do something fun. Go get some champagne and invite your girlfriends over and have ladies night and watch movies Like if you're not a club person like you don't like going out Or if you don't have a lot of money to spend or you just not in a part of the city where you know stuff like that is available Have a girl's night in and do like You know Play truth or dare Get some good chick flicks Maybe Like a lot of women know how to do nails some know how to do hair Y'all could have like a spa hookup party and it's like one girl who knows how to do nails would do everyone's nails and One girl who knows how to do hair. Well, well, that's a lot of work, but Maybe she could like help someone do one of their hair So and then just you know trade secrets and say, you know what works for you What works for me because you would be surprised at how much you can learn from other women what works and what doesn't work Okay, and if you have it like that and you have some money that you can spare Like you could hire someone to come in and do like manicures and pedicures just for the little spa party And make it like a holiday theme spa party So you won't even be thinking about a man You'd be like so wrapped up in yourself and your friends and Looking cute and stuff like that and you'll start to feel a lot better about yourself And you won't even be feeling like you're lacking anything because you're really not You are you were born with everything that you need, you know We just feel like we need a partner because it's pushed so much in society, but really you don't really need a partner You just want to share your world with someone and you want to you know Be With someone who appreciates you who spoils you and all that kind of stuff But you really don't need a person, you know a lot of people just want a person and that's fine But if you're not in the place right now where you're going to have a boyfriend this season focus on your friends focus on yourself focus on your Beauty focus on you know fun things and These will be in your memory forever because if you ever do settle down and get me or you're gonna be Remembering back on the past and all the fun you had when you were single now if you can't do that then It's not gonna be any fun to sit there reminisce. We have nothing to reminisce about so make your single life fun Don't make it all about I need a man. Oh, I'm looking for a man.   It was like she had you know nice champagne food Music it was it was like It was cool.    Yeah, that's fine Everybody knows that but this time of year, let's just chill and relax and enjoy. I mean If you don't have a man by now, it's almost Christmas a you're probably not gonna get one cuz he's gonna save that money on his Chris on buying a Christmas gift or B, he's gonna come at you right after Christmas. You might get them for New Year's if you're lucky, okay? And I know a lot of the side chicks out there are being very neglected right now Don't lose hope y'all The holiday season is a lesson for side chicks It puts things into perspective as to why you don't want to be a side chick for the rest of your life Okay, because it's gonna be a lonely lonely holiday season year after year. Okay?   He spends holidays with his family Now I don't have anything against side chicks for real like I really don't I'm just saying y'all can't get mad when you Chose that lifestyle, you know, if you want to have the man for the main holiday Then get a man who's not going to ask you to be a side chick. Okay? I think most women have been a side chick once in their life, maybe I don't know I know I have once and I Didn't know I was and then I found out I was like Side chick. Oh, I'll get it. I guess I get it.   It was crazy. Okay. This is back before I met my husband So I was dating this guy and he was fun And I don't I don't know if he had a side chick. I think he did but I'm not sure I don't know if I Know I'm getting all these people confused. Okay Okay, I was dating this guy and I felt like I was a side chick because He was his family was really well off and he was like pot say And How much time do I have let me see I can tell the story. Okay. Yeah, he was fancy. Oh, he was fancy He was gorgeous. This is one of the guys you go for for the looks. Okay, this guy was like a male model Okay, and his family was rich I'm not gonna say what his family did because it might be too easy to figure out but Yeah, I think I was his side chick for a little a little second and it was around the holiday season, too And I was like, you know what I Don't think I can do this anymore. And we had just started dating, too. He was like, what do you mean? I was like, I Just don't feel like This is real. He's like, what do you mean? It's not real. I was like, I think I'm a side chick He looked at me crazy. I was like Because I I Just felt that I'm very intuitive and so it ended up being true. So I kind of dumped him and then He kept calling me and calling me and I was like, I didn't answer and I deleted them off of you know my phone and everything and It was it was so funny because you wouldn't expect a woman to dump someone that rich and that Attractive but I don't do side chicks stuff.   The wife gets the benefits. So I said bye-bye and Now fast forward what 15 years and I don't have to worry about any of that kind of stuff anymore But if I had stuck with him, who knows I might have never met my husband Would have never met my husband if I was stuck with being a side chick, okay? So y'all have to remember remember that so happy holidays to y'all throw y'all self-suffer party And Y'all have fun, you know, this is not the time of year to be down Okay, a lot of people suffer with depression this time of year.  So get some fresh air and just have fun y'all, okay? I'm gonna see y'all later and If y'all have any video ideas for topics or questions, please put them in the comments So I could try to answer them. I'm gonna be trying I'm going to be trying to answer more questions Since I have a lot of questions in my comments. I was gonna do like a whole video of just all questions and answers But those can get pretty long. So I'm just probably gonna try to cover two questions per video so if y'all can ask a Question I might do two per video Starting with the most wild question, okay, so I'll see y'all later. Bye


This is the SF Productions Podcast Network. That's Warner Brothers, folks! From the Pop Culture Bunker, I'm Mindy. And I'm Mark. You can check out our audio podcast, How I Got My Wife to Read Comics on iTunes, or on our website, SFPodcastNetwork.com. Now, we continue our history of the movie studios with Warner Brothers. There were actual Warner Brothers! Actually, Juan Scholaser, before their family name was anglicized after emigrating from what is now Poland, brothers Harry, Albert, and Sam, Jack would join later, went into the nascent movie theater business in 1903, chipping in for the cost of a projector and films that would be shown in Pennsylvania and Ohio mining towns. They spent $150 to present two films, Life of an American Fireman and The Great Train Robbery, using the profits from that, to form the Duquesne Amusement and Supply Company to distribute films. By World War I, they were producing their own films, opening their first studio in Hollywood in 1918. Sam and Jack produced the movies, while Harry and Albert handled the finances. Warner Brothers Pictures, Inc. was officially created in 1923. Their first star was a dog. Rintin Tin, a German Shepherd, brought back by an American soldier in World War I, starred in a long line of Warner Brothers films. Jack called the dog The Mortgage Lifter, for saving their finances. Daryl Ebsanik produced the films and would later become the Warner Brothers' top producer before moving to Fox. Meanwhile, Ernst Lubick gave Warner Brothers some credibility, if not a lot of money, doing sophisticated comedies such as The Marriage Circle, 1924. By the mid-20s, Warner Brothers was considered the largest of the independent studios, First National, Paramount, and MGM, were considered to be the big three. At Sam Warner's urging, Warner Brothers experimented with sound in films as early as 1926. They established Vitaphone, in partnership with General Western, for these productions. Don Juan, with John Barrymore, was the first to include music and effects tracks, but lost so much money, that Warner Brothers almost went under. They were forced to open what was an exclusive agreement for sound film with the other studios. Despite this, they soldiered on and produced The Jazz Singer with Ile Jolson in 1927, which included his singing tracks, but not sound dialogue. It was an enormous success, and was the death knell of the silent film era. It also was Sam Warner's time to end, as he died the night it premiered. Jack Warner took over production. Warner Brothers took the money generated from The Jazz Singer and pushed it into full sound films, such as Lights of New York, as well as a new studio in Burbank. They also bought out First National and multiple theater chains. Their first all color, all talking feature, was On With The Show in 1929, kicking off a series of color musicals. Brother Harry invested their money in music publishing, forming Warner Brothers' music. The Great Depression had an enormous impact on Warner Brothers, losing $8 million in 1931 and $14 million the next year. Warner Brothers and First National formally merged in order to save money, although the Justice Department required them to make First National pictures through 1938. So when you see credits of old movies on TCM, you might see references still to First National. They survived on the profits of Busby Berkeley musicals, such as Gold Diggers and 42nd Street, the classic Let's Put on a Show film with ridiculous musical numbers. Eventually, the market for musicals abated, MGM would later take up the cause and Warner Brothers shifted to gangster films, Little Caesar, The Public Enemy, I Am a Fugitive from a Chain Gang, all from the pre-code era of films when there was little censorship of violence and sex in films. A studio fire in 1934 which saw the loss of 20 years of early films did not help the bottom line. Contracts, especially for silent stars, were dropped and a new era of stars came up. Cagney and Reggie Robinson, Barbara Stanwick, Humphrey Bogart. The petrified forest in 1936 was a huge hit, but the same year, an offer by Harry's daughter to buy the rights to Gone with the Wind was vetoed by Jack, who expected correctly that it would be an expensive production. The haste code caused another shift at Warner Brothers moving to historical dramas and swashbucklers with Errol Flynn, of course. By the latter part of the 30s, Warner Brothers started to lose its cluster as many of its stars balked at contracts and conditions as well as their treatment by Jack Warner. Cagney left to form his own company. Betty Davis tried to escape to the UK, but both would come back. A bright spot for WB began in 1930 where producer Leon Schlesinger sold the earliest WB cartoons to the studio. Harmon and Issing, Fritz Freeling, Tex Avery, Bob Plampett, Chuck Jones and Robert McKimson all were involved in Looney Tunes and Merry Melodies. Warner Brothers would later buy him out in 1944. The resulting company would continue making cartoons until 1969. Prior to WWII, the head of Warner Brothers German sales was murdered by the Nazis and the studio went all in on anti-Nazi and pro-war films. Casablanca, Yankee Doodle Dandy, 1942, This is the Army and Mission to Moscow, 1943 are representative of the era. In fact, they made war films even after public response turned on them. After the war, profits began to drop. Like most studios, WB got caught in the Supreme Court case that forced them to divest of their theater chains just as television began to eat at their revenues. The studio jumped into 3D but was never successful at it. Jack Warner temporarily closed the animation studio assuming it would be switched over to all 3D which never happened. Cinema scope films were made to combat the rise of TV such as The High and the Mighty which provided the studio with a profit in 1954. In 1956, Warner Brothers sold their pre-1950 film library to associated artists which would later be purchased by United Artists and even later by Turner Broadcasting which is how we have TCM today. As you'll see later Warner Brothers would get it all back. They also sold the company itself that year although it ended up being controlled by a syndicate which made Jack Warner its new president. In that same period, WB was the first studio to heavily invest in the new TV industry while the others avoided it like the plague. An agreement with ABC resulted in a lot of westerns, Maverick, Bronco, the Alaskans, and Private Eyes 77 Sons at Strip, Hawaiian Eye, Surfside Six. By the 1960s, Warner Brothers was diversifying. Their records division bought out Frank Sinatra's reprise records. Sinatra would end up as part owner of that division and the soundtrack to Warner Brothers' film My Fair Lady made them profitable. As the movie industry moved away from the classic studio system, Warner Brothers began running out their studios to independent productions. In 1966, Jack Warner sold the company to Canadian investors and the company became Warner Brothers Seven Arts. Only two years later was sold again this time to Kinney National Company which started as a parking concern. They had just expanded into entertainment buying out national periodical publications, a.k.a. DC Comics, in the Ashley Famous Talent Agency and Panavision. Due to issues in owning both a studio and a talent agency, plus a financial scandal involving their old parking business, the non-entertainment divisions were spun off and the remainder was renamed Warner Communications in 1972. Jack Warner had already moved on by that point and died the next year. As Paul Newman, Robert Redford, Barbara Streisand, and Clint Eastwood got Warner Brothers through this period and kept them profitable. Their record division continued to snap up competitors such as Electra and Atlantic. They also bought out a small company making a home video game system, Atari, and the Six Flags amusement parks. In 1973 Warner Brothers did a co-production, The Towering Inferno with 20th Century Fox. Both had burning skyscraper films based on different books in pre-production and decided wisely to go with a single film. This started a wave of profitable disaster films. Warner Brothers used their recent ownership of DC Comics to produce the Christopher Reeve Superman films and the Linda Carter Wonder Woman TV series and would later repeat that success with Batman. The 80s saw a retrenchment for Warner Brothers. Their huge profits from the Atari subsidiary reported a one-third of Warner Communications' total revenues at its peak crashed after the video gamer didn't invest in New Tech, lapped by Nintendo, pushing Warner's stock price from $60 to $20. The studio created a new company, the Burbank Studios, to co-own their actual lot with Columbia. Due to infighting, very little production was actually completed there. They would later buy out Lorimar, who owned the old MGM studio lot, which would then be sold again to Sony just a year later. That year, 1989, saw Warner merge with Time Incorporated. The resulting company would later be swallowed up by AOL at the height of the dot com boom. In 1995, WB started up their own TV network, the WB, partly as a response to Paramount's UPN. They would later merge those networks into the CW. Warner Brothers bought out Turner Broadcasting in 1996, which brought the film catalog they had sold in the 50s back into the fold. The studio would finally find a franchise outside of comic books when they acquired the Harry Potter books, with films starting in 2001 and Harry Potter and the Deathly Hallows Part 2, their highest-grossing worldwide film ever. The Dark Knight remains the largest US gross for the studio. In 2018, Time Warner, since renamed from AOL Time Warner, was gobbled up by AT&T and renamed Warner Media. All the various divisions were reorganized, while HBO, which came in as part of the Time Inc. merger, would become a major part of the upcoming HBO Max streaming service, along with all the content that WB brings to the party. Wow! Yeah, a tangled web here, making us getting all the way from the great train robbery at the turn of the 20th century, showing them in mining towns to this huge classes of a company bought out over and over and over, and one time by a company that made their money in parking lots. Well, what do you judge for parking these days? That day! All right, you can check out our radio podcast, how I got my way to read comics on iTunes or on our website, asifpodcastnetwork.com From the Pop Culture Bunker, I'm Mindy. And I'm Mark. Thanks for watching.


Hi everyone, Joe for jaspyscasebreaks.com coming at you with a 2020 Panini prism draft picks football four box Random college football team number 21 big things of these folks right here. So 23 spots everyone gets Three teams from the list below. So let's triple your names up one two three and They're all the college football teams right here. Let's roll it. Let's randomize it Six and a two eight times for each list one two three four five six seven And eight. I don't remember Tyler Ken down to Seth Scott after eight Me be able to look at cardboard connection.com look at the parallel and see what it's number two Six out of six. I'm not six out of two six and two eight times one two three four five six seven and eight so after eight times We've got Purdue down to The South Florida Bulls I think I've ever heard of that university All right, so I'm not gonna read off all these but it's just way too many But we'll slowly scroll through the list like this and then I will alphabetize by your first names in just a second So hang tight. All right, there you go. Now. Let's sort by column a So Barry, they're your teams Brett Chase Damon Eric Jason Jens John Kenneth Matthew Michael Phillip Scott Goodman Seth Scott and Warren Now while you're considering Trey actually if you're watching live, I'll drop this link to you Can view So there's a link in the chat if you can't open up Google sheets from whatever device you're watching Then then let me know and I can scroll down to your name and let you know what teams you have in the meantime Let's pop this fresh case open. This is 2020 right just pop this fresh case open And let's see which five boxes we're gonna do. All right, so let's make stacks of five There's one two three four five one two three four five One two three four Five Many boxes are in here.   You're gonna have to trust that it was to All right Let's mark these so we know they're just from the same case Why don't we why not just do 12 34? That's that sounds way too complicated for my small brain Adam set those there for now. We might be able to run back another one of these tonight Yeah, I still don't get that Adam Well like one and two is left side no no no god no that sounds like a nightmare and my brain is not big enough to comprehend that Or my other die went it's gone forever you guys Sorry old flamingo blue blue die to find more matching die at some point all right Let's go back to the list right here. Sorry back to the list right here any trades No, no trades Chase wants to get or Dfs wants to get Kentucky. I don't know if he's here DFS. What teams do you have? To offer in case he's listening Blue flamingo die. Where'd you go? I found it It's on the ground all back tomorrow.  Well schedules in the chat and Then whatever else fills and that 630 time slot will be able to do And we break until 10 o'clock Pacific tonight All right, good luck everybody. So there's the final print out right there I guess I'll set that one away over here. I think I have enough regular top loaders for the break I know if not Get some more There you go. So there are the four boxes that we picked from our 16 box case So we get there's another four in the store Ladies and gentlemen, I'm not sure if this is the best production idea See what they're trying to do, but this thing always slides in and the packs always rattle around. I like that. All right. Good luck auto a pack Five per box 20 per four box break Yeah, I can count and veteran commons don't ship, but everything else will There's Phillip Rivers that'll ship though. That's a silver right there. There's Tyler Johnson to 249 Jalen Régor is our first auto that'll be for Texas Christian University home of the horned frogs Kenneth are there a lot of horned frogs in that area. I'm not sure where they got that but There you have it The Odell Beckham, Jr. 299 Those aren't numbered, but they will ship and the next one is clave on chasing LSU this tiger goes to Brett Myers big rig 13 out of 9. I think you did Brett You did you just got that LSU autograph Another guy on LSU. Who is that guy? There's Jake Luton an Oregon State beaver That'll go to Warren 45 out of 75 There's Emmett Smith to 199 Trayvon digs Stefan's brother and Colby Parkinson a Stanford Cardinal Jason K. There's Leonard for net Kj Hamler to 149 and AJ Dylan a Boston College Eagle right Eagles right Eric J for the Eagles and all these all those cards right there. We'll We'll sleeve and top load before they go out Next box Good luck Baker Mayfield the viscous shinalt jr. Who I've heard people like to 149 and we got Denzel Mims From a Baylor that goes to John Williams and the Baylor Bears Deandre Hopkins to 199 to a Tagovaiola I've heard of him. He's pretty good Allegedly I guess we'll have to see Isaiah Simmons Clemson That'll go to Damon last spot mojo two out of 49 There's a Juan Barclay to 299 Shea Patterson to 49 and James Morgan to 199 With a blank college to it Penini got all the licenses except for this one This college held out for some reason Florida International Florida International that goes to Eric J. They're the Golden Panthers by the way Did you guys watch the horse competition and Allie Quigley's fake dog in her backyard? Did anyone else notice this? It's right. It's Did you see the fake dog? You see the Allie Quigley versus Chris Paul one day Watch the Allie Quigley versus Chris Paul one There's a dog In the like there's a statue of a dog in the background. I guess so then just buy a That died and she brought I mean may be all right So type the schedule in the chat folks There's Harris and Brian if your break just recently sold us not on the schedule yet I'll we'll get it on the schedule soon There's Harris so we went from Florida International to Florida Atlantic Florida at the at Florida Atlantic owls Yens with that one Steven Punk asking how many topless and soft sleeves Do we go through a week? I? Don't know a lot There's John Hightower For Boise State you should watch all of our breaks even punk and count 44 out of 149. All right two more boxes to go Go to Allie Quigley's dog. There it is. I think trip me out. I At first I was one and you know the camera quality on the SPN horse is Pretty bad for most of these players But at first I thought it was Allie Quigley's very well-behaved dog That was just like I was like I was amazed.  Yeah, someone mentioned that yesterday Mac. I mean I'll I'd have to chalk that up to There's Phillip Rivers 249 and There's Trish and Jackson to 75 I Would have to chalk that up to maybe Maybe that person lost lost its head with the bright lights And the TV cameras and look at this CD lamb I think this is the first one of these color bursts that I've seen Nice Tricky not yet. I think there will be though. Whoa. Whoa. Whoa USC does not represent California Represent spoiled Bratton LA maybe does not represent California Joann Johnson and Oregon duck quack quack quack for Yens QSE Cal CJ Henderson and Justin Herbert Eight out of 50. I can't wait for that sherbert contract that he's gonna get From an ice cream company. I love sherbert orange sherbert rainbow sherbet Sherbet sherbert Sherbet pineapple sherbert Get out Is that like the ones with the chunks of pineapple inside it's I It's me cool. Harman's I take I take a orange sherbet over Italian ice TJ Dallas Miami that'll be for Bienvenidos. I'm yummy. Don't Brett Meyers with Miami hurricanes. There you go. Well that last card Sanford. No, this is Miami and Oregon there We had two organs Oh, sorry, the color burst was Oklahoma. That's CD lamb from Oklahoma. That'll be for Barry Roberts. Oh, you That's Stanford One more box. I want to I want to get some some ride aid ride aid rainbow sherbet right now It's a perfect day for that. Does ride aid deliver contact-free delivery Someone look that up ride aid Hermosa Beach contact-free ice cream delivery Oklahoma gets the color burst Warren Oklahoma does say the wrong name. I did say the wrong name. You get it Warren Don't listen to me. It doesn't matter what I say The shipping team will look at this and we'll look at the list Barry Roberts is Oklahoma State Mr. Warren Lowe has The sooner there's Marquis Brown To 99 or whatever that was Jacob Eason and Josh Kelly Before the color burst, it's all out of order now I'll do I'll do a random. I'll do a recap There's Josh Kelly. No, that was that was my bad Warren It's the list is so far away the font is so tiny Derek Brown to I was busy. I was busy talking about sherbet. There is T. Higgins for Clemson That'll be for Damon But Jason K if it was Stanford, it'll go to you. You could also rewind I think but make sure you come back live Aaron Jones 290 there should our DVR function should still be available Jake from a state farm to 299 and Justin Mad Madbuke 10 out of 10 for the Aggies Texas A&M Philip Meagle with the Aggies Warren, are you a low or a low? Like a Brandon Lowe or a Nate Lowe Brandon Lowe for their Tampa Bay races. It's Lowe but There's Alvin Camara, but his teammate Nate Nathaniel says it's low Tyler Johnson to 199. I know loud doesn't sound right. You're like the hardware store low. Okay Lowe's Jimmy Johnson 48 home depot that was Who drove the Home Depot car? Why am I blanking on his name 74 out of 149? That guy that maybe killed the guy Remember when he almost killed the guy on a dirt track? I think it was an accident Kendrick before before the Tony Stewart It's the before the Tony Stewart company. It's excuse me Don't sue me Tony Stewart That Kendrick Rogers is an Aggie that will go to Philip quick little recap right there. Thanks everyone Nice color burst for Oklahoma Oh, this was you talking about were you talking about this? This was Syracuse Jason K.  We're still recording We're still recording we got a I got a shut down this video before Tony Stewart Slander and libel Joe for jasby's case breaks calm. Sorry Tony. We'll see you next time jasby's case breaks calm


All right, we are live. So hello, everyone, and welcome to the Google Summer of Code and Outreachy Project Showcase. Both these programs, for those of you who don't know, are run by Google and Software Freedom Consovency. And they are designed to introduce students to free and open source software projects from around the world. Wikimedia has been participating in these programs since many years in Google Summer of Code since 12 and Outreachy since five years. These runs that just got over earlier this month, we have 10 students from India, Israel, and United States who contributed code to different projects under the mentorship of 13 mentors. And out of these 10 students, we have seven students attending the showcase today, and they will be sharing with us more about their projects, what features they built this past summer, how it works, and much more. We are very proud of the contributions these students have made, and we are very happy they are here to share their accomplishments and learning with us. So before we dive into the details, I will give you a quick overview of logistics. Each student will tell us who they are, where they are joining us from today, what project they worked on, and then details about their project. And after we are done with this, there will be time for question and answers. For those of you who are watching us live, if you have any questions, you can ask us on IRC channel Wikimedia office. OK, so let's get started. Let's start with whoever is in the slide first. I will quickly do a screen share here. So we have Ella on the slide first. Ella, are you ready to present? Yes, thank you. OK, hello, everybody. My name is Ella. I'm from Israel. I took the feature that called, remind me of this article in X days. And it's supported in notification of reminder for the user per his request, of course. It's a very exciting feature. It's end-to-end feature. It touches from the database through the server to the UI. It was very interesting feature to work on. Basically, we've created a new component in the Echo extension that it's a delayed event, actually. And the new, of course, several APIs for this feature. I can move to the next slide, please. Yes, thank you very much. And we can see. I think I need to present it to everyone. That way, we will see the screen share. OK, awesome. OK, so by enabling the feature, we can see right near the read, edit, view history tabs, we have a new tab that called, right now, it called remind me. And if you're in any page on Wikimedia, you can click on the remind me tab. You get the pop-up that says, please input comment. It's an optional comment, of course, just for the user to connect its reminder for its thoughts in the moment. The user can then click on the when or date input and then choose any of a future date in resolution of seconds, as you can see. And for the user convenience, of course, there are the most popular future time frames, which are tomorrow, next week, and next month. So the user chooses the time and then creating the reminder. And then when the time and when the future time is come, so a notification is generated in the user notification. The notification is triggered with a cron job, the crons in very short intervals. And it's a very exciting feature. Cool. Thank you so much, Ella, for sharing about your work. OK, so next we have Feroz. Hi, everyone. I'm joining from New Delhi, and I am GSOC 2017 participant. And I was working on a project for introducing a hierarchy type to an extension, cargo extension. So first let me introduce you about what cargo is. Cargo is an extension that allows you to store data in your wiki from templates and from info boxes within your templates so that you can query it easily. And it allows you to have some easy build queries for maps, for locations, for several other types that are easy to use and are very informative, in a sense, specific to some type. For example, cargo gives you a place near to a specific coordinate in a range of five kilometer or some x kilometer. So such type of ability cargo gives you. So my task was about adding a hierarchy type. So hierarchies are, as you know, like we have several categories, and then they can be another class, and within that another class. And the aim was to allow generic categories, generate hierarchy types, and allow query within that. So I'll discuss what features are added. Can you switch the slide please? Yeah. So here are a few of the features that I added. I also added in page forms extension. Page forms is like another extension that allows you to easy addition of data into the wiki and really good GUI for adding information into the wiki. So the cargo and page forms work together. Cargo can also work with semantic media extension. But in this project, I have tried to incorporate cargo with page form for the hierarchy feature. So somehow support for hierarchy. And I have added two new querying features within and holds within. I'll tell you in a moment. And I have added a drill down interface for specifically hierarchies and added some pages for some fields entries in page form extension for hierarchy support with the cargo extension. So let's see one of the pages. Can you change the slide? Yeah. Thank you. Yeah. So this is one of the page in the page forms, special create class. This page allows you to create a template and a class and a form to take input form for the template. So here you can see allowed values and hierarchy. So the interface has not been changed pretty much. But I have added this text area and all the stuff to give a hierarchy structure. So from here, you can easily give hierarchies in the form of stars, specifying the levels. So I don't know if you can see the stars, count the stars, asterisks. One asterisk means the first level, the root level. And then as the stars increase, you are going deeper into the level and you can specify that. So this is how you can allow creating a hierarchy field. Please change the slide. So what's the advantage of it? Obviously, the queries that I have added allows you to see how many people are having specific mentions of specific value. Suppose the last field, you created a field like main ingredient in your template. And you have following values, roots, apples, mangoes, and so on, like hierarchy. And now you want to query how many dishes or how many vegetables have root vegetables mentioned in them. And that should also include carrots or turnips or any other values within the root vegetables. So there is a sample query that you can run into your wiki page. And it will give you a nice result in the form of table if you specify the table. So you can see it on the next slide. Please change the slide. Yeah, so here's the sample data. So it is the result for the above query that you ran. So in this way, you can get the results of the queries. So this is just a query for fields having single values. You can similarly run queries for fields having several values. While discussing, it looks the same. But on the back end side, there have been different implementations due to different architecture for saving such data. Hi, Rose, your time is up. Yeah, so that's the last feature if you can give me a few seconds. Next one, yeah. So here is the drill down. You can see the whole mentions of those fields in each and every slide and in each and every page with their accounts. So basically, these are the few major things which I have added on. And that's it. OK, thank you for those. Thank you. Next, we have Amrit. Hello, everyone. I'm Amrit and I'm from Kochi. So the project I've been working in on is the general improvement of improvement and enhancement of WikiSource and an extension called ProofreadPage. So those who are familiar with WikiSource might as well know what ProofreadPage is. For those who aren't, ProofreadPage is an extension that helps in the validation of a text or something that is uploaded to WikiSource. And it allows easy rendering of texts in several ways without duplicating its data. So the tasks I have undertaken is the first one is a creation of an auto-validate privilege. Now, one issue with validation is that not the same person cannot Proofread and validate the same page. So for people running on small Wikis, they need to call in a third person who might not be related to the thing that he's doing in order to validate the page he has Proofread. So with the creation of this auto-validate privilege, the admins, the admins of the small Wikis can themselves Proofread as well as validate the page. So this makes the process a lot more easier and much more simplified. Now, the second one is the conversion of index pages editing form to object-oriented JavaScript. Now, the advantage of object-oriented JavaScript is that the code is much more readable than what was previously written, and the interface looks much better. So what I've done is generally the porting of the pages editing form, that is an index. Those who are familiar with Wikisodes might know this because index is basically like the index of a book. So what all do you need in an index of a book? Those are there in the web interface. So I have converted that from PHP to OJS. And my third task is the migration of Proofread Zoom feature to OJS. It's a similar thing, but then this is a little more of a bigger task. And the job was to convert the code which was originally written and implemented in jQuery to OJS. So you can see the Zoom feature while zooming into an image that is being pinned in with a book when you upload a book to a Wikisodes. And then you Proofread it and validate it. You also add an image with it. So in order to zoom into that image, a widget was used. Now, this widget was originally written in jQuery. So once converting this to OJS makes the code much more readable and easier to access. So these were the tasks that I had done during my DSOP project. And I have planned to keep the presentation pretty small as I guess this can be viewed throughout the Wikisodes and it's widely implemented in the media Wikisodes. Thank you. Shrishji Omurit. Next, we have Sonali. Sonali, are you ready? Hello. Yeah. So hello, everyone. I'm Sonali, and I'm joining from Jaipur, India. I participated in Outroochie round 14. And my project was about documenting how Zatero translators are developed. So can we have the screen share? OK, so basically, we have a service called Cytoid that allows users to add citation to Wikipedia's. And it has made it very easy for people to add citations through URLs and DOIs. Pretty easy because of the UI earlier, it was through adding code in the source. And this service uses Zatero translators. Zatero is a force reference management system. These translators basically scrape websites and get their data and save them as JavaScript object. And that is used by Cytoid. So the link is provided where you can see what the documentation covers. Can we switch to the next slide? So I'll just cover what all the documentation has. First, we go about knowing what Zatero translators are. And then for the people who would like to learn how to write translators through an example and skip all the tutorial, I have created a page that has a translator for Wikipedia blog. And then there is a section that covers all the concepts that are needed before you jump into writing code. And then we have all the methods that are basically used to write a translator. These are more or less static. There's this template that is used in all of the translators. Next, moving ahead, we have a detailed explanation of a translator for mediawiki.org. This documentation was basically prepared because the current documentation that we have was pretty old and did not have all the updates. During the internship period, Zatero released its new version, Zatero 5.0. So this documentation has all the updates, how to develop on Docker, and how to do development through translation server. Because for Cytoid, it is very important that a translator runs on translation server. Whereas the previously available documentations only explain how to develop through scaffold, which is an integrated development environment provided by Zatero community. So the documentation, for the first time, has how to test and write and check the code on the translation server. Further, we have how these translators can be deployed and how to get them merged first in the Zatero community and then in the Wikimedia mirror of Zatero. And most of the translators that we have, as of now, cover English language. And not much coverage is there. It's not available for other languages. So it will be great if people make use of this documentation, develop translators, and expand the coverage of the content that we have. So, yeah. Thank you. Thank you, Sonali. Next, we have Siddharth. Yeah, hi. Can you hear me? Yes, we can hear you. So I'm Siddharth. I'm joining from IT Delhi. And my GSOC project was about making a tool. And this web tool is capable of uploading images from the repositories of GLAMs to Wikimedia Commons. Now, GLAM stands for Gallery, Library, Archives, and Museum, for example, the Amsterdam Museum. So what happens is that these large galleries sometimes have a lot of images to be uploaded to Wikimedia Commons. And as you know that anybody, any comments user can do so. So with my tool, any comments user will be able to upload images, either a single image or multiple images at a time. So let's go to the slides. Yeah, so this is, as I already said, next slide. So right now we are supporting two GLAMs, National Archive and Amsterdam Museum. And the main challenging thing in the tool was to make the tool scalable. And this tool can be extended to any number of GLAMs. So we are expecting to extend it to other GLAMs. And there is a page which I have shown here where anybody can suggest new GLAMs. Next page, next slide. Yeah, so it has a number of features. For example, suppose you are a Wikimedia Commons user, so you will be able to use this tool. So you'll have to log in using your Wikimedia Commons credentials for that we have used authentication token, this protocol called auth. And it has a very simple interface which we will show in the next slides. And the main idea is that, suppose when you are uploading an image, so this image need to have certain metadata which the Wikimedia Commons expects. And these metadata are formed by our tool and the user does not do anything regarding manually entering this metadata. And we will prevent uploading of duplicate images. Suppose we were trying to upload an image which is already there in Wikimedia Commons who our tool will report that. And our tool is capable of uploading multiple images at a time and it can associate images with multiple categories. We will see all in the next slides what this is. So let's go to the next slide. So this is the homepage. The tool is hosted in Wikimedia Foundation Labs. It's called GLAM to Commons. So first thing you have to do is you have to log in using your Wikimedia Commons. And you will see the supported GLAMs list here which contains the link to the repositories you can serve through the images and upload. Let's go to the next slide. So once you click on the login button, you will be asked to log in. If you don't have a Wikimedia Commons account, you can join and log in. Let's go to the next slide. And then you have to allow certain rights to the tool. It will ask you to allow the right to interact with pages and interact with media. And after you allow that, you are inside the tool. Let's go to the next slide. Yes, so this is our tool. It has three main buttons, Home, Help, and the Wikimedia Foundation link, Homepage link. The Home button is where we'll have all the action. Help button has the instructions which you will see in a little while. So once you are logged in, the first thing you'll do is it will choose a GLAM from the dropdown, choose GLAM. Let's go to the next slide. Once you have chosen, suppose, National Archive, so you will get to see a little description about National Archive. And then you will see what are the kind of sample URLs, so you'll be able to go to the sample URL and search, serve through the images of their collection and then provide the sample URL or unique ID for a single image upload. So we are right now considering a single image upload. To upload a single image, you'll have to provide this unique URL or unique ID as you can see here. And then, for example, I was looking at an image of Rajiv Gandhi from a Prime Minister of India. So I have added categories, Prime Minister of India and Rajiv Gandhi. And now we click on the upload or see image calorie button. And let's go to the next slide. So if that image is not there in the Wikimedia Commons repository, so in that case, it will be successfully uploaded and you will get to see a link of that image in the Wikimedia Commons. Once you click on the link, you'll get to see that. Let's go to the next slide. If it is already there in the Wikimedia Commons repository, we will report that a duplicate exists at the following location. Yeah, let's go to the next slide. If your image ID is invalid, incorrect. If you're given a wrong image ID, we will report that. Let's go to the next slide. And this is, once you click on the link to in the Wikimedia Commons, you'll get to see that the image has been uploaded with the metadata, as you can see, a lot of the metadata has been added by a tool. Let's go to the next slide. So this is multiple images at a time. So here, what we'll do is that we'll ask the user to provide a search string. Based on the search string, we will show him a gallery of images. For example, I wanted to see what are the images in National Archive Adir, that has Gandhi as one of the search string. Let's go to the next slide. So once you click on upload or see image gallery, you'll get to see the images which are related to Gandhi. And then you can choose, and there are checkboxes with respect to every image.  Let's go to the next slide. And let's go to the next slide. Yeah, so non-duplicated images, let's go back.  Let's move. And then you will have a link where you will get to see the new images uploaded, and these are the images which we have uploaded, Gandhi-related images in Wikimedia Commons. Let's move. This is a simple how to use the tool instructions. So you log into Wikimedia Commons, you choose the glam from the dropdown. If you want to upload a single image, you provide the URL or unikari. If you do not know no problem, you can just enter a search term and based on the search term, we will form an image gallery for you and you can choose the images you want to upload and click upload and those images will get uploaded. And if you make any mistakes and those mistakes will be, those exceptions will be caught by the tool and you will get to see appropriate messages. So this is what I did for my GISA project. Thank you. Thanks, Siddharth. Next, we have Sejal. Hi, everyone, I'm Sejal Khatri. I'm joining from Pune, India and my GISA project was to enhance the usability of the Wikimedia programs and events dashboard. So for all of you who don't know, Wikimedia Education Dashboard is Wikimedia Education Foundation's platform for helping people get started with editing articles on Wikipedia and helping professors run assignments wherein their students edit Wikipedia. So the dashboard code runs mainly on two projects which is Wikimedia Education Foundation Dashboard Project and the global version of that is Wikimedia Programs and Events Dashboard. So I worked on Wikimedia Programs and Events Dashboard because the previous use case, which was limited to higher education in the United States and Canada, that dashboard was pretty, it's running pretty well and then we moved on to the global version of the dashboard which is Programs and Events Dashboard which is not perfect yet. It has many programs, many kinds of programs including editathons, education programs and many such Wikimedia events which can be handled. The scope, there are many improvements to be made. So my GISA project was not limited, it was quite open and I had to figure out, I had to do many user testing sessions to find out what's going wrong and then work on that. So can we move on to the next slide? For the first part of my internship, I did some code refining for the user contribution stats and successfully made them available on the user profile pages. So I was working on this since the community bonding period of GSOC to add on some visualizations for user contribution stats and during the first part of my internship, I was successful in refining that and then getting it merged and deployed. Can we move on to the next slide? So I was using Vega, it's a visualization grammar. Using that, I generated these two visualizations. On the left side is visualization for the programs taught by a particular instructor. So as you can see, the programs taught by an instructor are distributed over the time scale which makes it easier for them to understand the impact they have had. And on the next, on the second screenshot, you have the number of editors taught by the instructors or the editors who are handling, guiding those editors on that program. So you could see that instructor, that particular instructor has taught 32 editors and he could see that he had impact on 32 new editors. And so that's the main agenda of the dashboard, to inspire people to contribute more so as to see the impact they are having. Can you move on to the next slide? And then comes the second part of my internship. This was the part where I was having conducting user testing sessions from people all across the globe and then interacting with them, helping them with their frustrations because some people didn't know how to use a particular function or how something is supposed to be done and then understanding and helping them. These are some of the issues that I resolved during which I discovered and then resolved. There was some very critical issues that were discovered and can we move on to the next slide? So yeah, the third and the final part of my internship. I was, there's a screenshot, which you can see the dashboard on a mobile device. It is not well organized and the nav bar you can see is not quite usable. So I walked on making it usable and then refining the UI. Can we move on to the next slide? So this is the outcome of what I did. The first screenshot on the left is I, we decided to add a hamburger menu instead of, because previously you saw that all the elements on the nav bar were distorted and cluttered and that's why we decided to add a hamburger menu and you could see the current layout. So during this I faced a few problems. It was not quite easy. This took a lot of time. The previous dashboard code was written in Hamill, the UI and then we had to like shift to React for using React JS. It's a React hamburger menu. It's a library provided. And then other problems which I faced like this and universal language translator. It's in jQuery and whenever React in jQuery you have to add in some other code. They don't go hand in hand. So I walked on that. And that's the fourth part. This is it as you can see. And the fourth part was me attending Wikimedia. There I met my mentors and further had discussion about how to document this and we decided to put on a proper like we have to document all the user testing sessions I had. Currently I have a raw document of what all the problems they are facing and Jonathan Morgan, my design mentor he helped me to with how the official documentation is done and I met my mentor, the other mentor, Sage Ross and it was an amazing experience. That's from it, that's from my side. Thank you, Sage. I don't see any questions coming on IRC. So I want to ask if anyone present in the room want to ask a question? Do you have any questions for one another? Hi, Sonali. Hello. Yeah, hello. Yeah. So you have walked on the Zotero translator, right? Yes. Yeah. I thought that it was really interesting to work on the project and as you said that this is probably going to help improve the number of contents in different languages other than English, right? Yeah. Yes. So even though in a few minutes I didn't understand the whole of it, I understood bits and pieces. So let's say, so is this a translator you have made or is this just documentation part you have done? So basically translators are like files that scrape web pages and these are used by people who do researches to save content, keep a summary of it. So while documenting the process, I had to create translators because you need to know what you're documenting about before you start writing about it. So I made some nearly 10 translators. It's very easy to learn first. If you learn, it's very easy to speed it up. So I developed translators and then I documented how someone else can do it. And there were many missing pieces in the existing documentation that I used. So the main motive was to make it perfect. So that is a really easy way. So I guess natural language processing was heavily involved, is that so? No, it was basically about working with the HTML code of the websites. It had nothing to do with NLP. It was about the HTML identifying the nodes in the structure of the websites and picking information from that. So just working with JavaScript, HTML and DOM. Okay, thank you. Okay, thanks for the question. Siddharth, I have a question for you. Yeah. I was wondering since your tool, it's out there, have you done any pilots already with people who are associated with these clans? And if so, have you discovered anything cool that you would like to share with us? Yeah, I think from the beginning itself when I made the prototype tool, we had communicated with the Wikimedia representative of the National Archive Clan and he has spoke very highly about the app. And he said that the workflow was very simple and it has made the work a lot easier for them. And there is a page we have maintained where we can see the number of uploads every day that's happening. And it's pretty impressive, I like that. And someone has suggested to include a clam, a French clam. And in France, most of the documentation is French so we're a little bit struck, but we'll start with that. And I wanted to ask you whether you could help me to get in touch with some of the Indian clams so that we can also add our history and upload images from our history to Wikimedia quickly and easily. If you are in contact with anyone. That would be cool. I can't think of any organizations that I know but definitely they can find something out. Yeah, so I'm pretty interested in making this too large and support more and more clams. Cool. Anyone else wants to ask anything? So we have Kirtanam missing, I think so. Yeah, Kirtanam is missing. And Meetham. So finished pretty much before time. Okay, then thank you everyone for joining and stopping the broadcast now. Thank you. Thank you.


I'm going to be speaking about a decidability result for a subclass of alternating automaton trees and infinite trees but I will spend most of my time introducing the model and talking about the restriction and intuitions and context. I will just mention the I will formulate the result in one of the last slides. So this is joint work with Jacques Dupac from University of Lausanne and Alessandro Facchini who was in Warsaw when we worked on this and now is in Amsterdam. So let me just start from probably for most of you it's it's known but I will recall it anyway. So my model of automata is alternating automaton infinite trees. I'm using the parity condition. I will just point out that the form of transition function I'm using is it just follows. It takes state and and letter and it gives a positive Boolean combinations of first direction and state. Okay so it's something like this. You either go right in the state Q1 or you go right in the state Q2 and sorry and and you either go in the right in the state Q2 or left in the state Q3. This function rank is used to define accepting runs or accepting place. I will talk a little bit about that in a second. It's essential the essential parameter of this model of automata is the number of ranks that you're using. It's not just the number but also whether you start from an odd or even rank. Okay so this measure that's used for expressing how complex your acceptance condition is called index and it consists of the minimal rank used and the maximal rank used. Now let me recall the how such an automaton work. So basically a computation of such an automaton is a game that's played by two players Box and Diamond. So the player starts in the root of the tree in the initial state and then if the root has label A then we replace the initial state with the Boolean combination given by the transition function and now the players make their choices depending on the on the outermost operator. So if the Boolean combination is a disjunction then Diamond chooses whether he wants phi 1 or phi 2 and this phi i replaces phi and if it's a conjunction it's Box who chooses. Now finally you go down to a single pair direction and state and this pair tells you okay so it's zero Q so you go left so to the left child in the state Q. If it's one Q you move right in the state Q and Diamond wins such a play if the sequence if in the sequence of ranks so this is defined by the sequence of states that are visited okay so if in this sequence the the maximal rank that was seen infinitely often is even then Diamond wins okay if it's otherwise then Box wins and we say the tree is accepted by this automaton if Diamond has a winning strategy for it. Now I would like you to think of the following very very simple operation so imagine you have two automata and you fix the state QS and you look at its occurrence in some transition okay now I'll do the following thing I will substitute this state QS with the initial state of the second automaton okay so the very very simple operation so you could see that on the picture as follows you have these two automata you fix one state and occurrence of this state in the transition and then you just move this single you modify this single arrow instead of pointing to this green state it now points to the initial state of the other automaton. Now it's a kind of obvious observation but if I take a different automaton B prime that is equivalent to B what I get is again an equivalent automaton right so changing a subcomponent of the automaton to an equivalent one doesn't change the semantics of the whole automaton right yeah so basically if the language is recognized by B and C are the same then after substituting B and C I again get the same language but what if I look at Corser equivalence relations so let's first look at the one at the bottom so I will say that two languages are equivalent if the minimal index of automata A prime such that A prime recognizes L of A is the same as the minimal index of automata B prime recognizing B then they are equivalent okay so you look at the smallest index of the automaton recognizing the language this puts the language in an equivalence class and you look at this equivalence relation now the other relation is much more fine-grained you demand that there exists two continuous functions f and g such that the inverse image of L of A is L of B and the inverse image of L of B is L of A what do I mean by continuous function so you can you can equip the space of infinite trees with natural metric counter like so if you know this then then is good if you don't know this then just think of the following characterization I will say that a function is continuous if I can determine say nth level of the output after knowing some fixed number of levels of the input okay so you ask me what is the seventh level of your tree and I say if you give me 17 first levels of the input I will give you the output okay so that's a continuous function it by by no means it has to be computable okay it's just an abstract construct now so why are these important they constitute two measures of complexity of an omega regular language you can sort in a way languages using those relations so basically a language is said to be more complex in the topological sense if it can be reduced to the other so if there exists a function from a such that the inverse image of B is a then I say that a is simpler than B and for for the index equivalence relation basically the higher the index the more you can recognize yeah so these are two quite widely studied complexity measures for for languages of infinite objects not just trees also words I listed several papers this is obviously not not all that was done in this area but I just listed the ones that was influenced by most so let's focus for a second on this index hierarchy so if one tries to understand complexity of omega languages state of trees what one often wants to do is to describe the two hierarchies so kind of understand which languages are more complex than than others in terms of those hierarchies and also try to describe the whole hierarchy so in a way one can think that if one understands the structure of this hierarchy one has a kind of classification of languages so it's not precise we abstract from some aspects but we kind of understand the structure in a way so the typical questions one asks is well the description of the hierarchy and if possible an effective description so I want to have an effective characterization of every level of the hierarchy like this the index hierarchy comes in different flavors because it depends on which kind of a tomata you're using so you can ask about deterministic index that will mean the smallest index of a deterministic automaton recognizing a language or non-terministic or alternating weak alternating etc sometimes this the answer would be infinity or impossible yes if you give if you take a language that is not weakly recognizable and you ask about weak alternating index then the answer might be no chance yeah so this yes as I said that the the classes form a hierarchy the shape is like this so basically if you if you take a say class of languages recognized by 0 to a tomata so the ones that only use ranks 0 1 2 and you take the complement then you can you take the the complement the complements of the languages then you you get the class of languages recognized by my one through a tomata a question to ask is whether this so that two questions the first one is whether the hierarchy is strict and if so then and what is the minimal index needed to recognize a given language yes so that's the typical decidability question and for in general if you take alternating three automata the strictness question was answered positively some time ago I guess the first proof would be Julian Bradfields and that concrete examples of languages that cannot be recognized by by automata with with small index so this is an example for so this is the language called w 1 3 and it's an example of a language that is recognized by 1 3 automaton but not by a 0 2 automaton so not by the dual one yeah so let me just quickly explain the language so you look at the trees that are labeled with the purse so each letter is a per it contains of a box or a diamond and a number yeah 1 2 3 now on such a tree you can play the same game that I explained while defining the semantics of the automata right so the player the players start in the roots and in the root you see it's a diamond right so it's the diamond who makes the choice he goes left or right then say he says go right I'm sorry go from your point of view is go left yeah so so he goes to this node with a three again it's it's a it's a diamond node so he makes his choice again he goes to two let's say two on the right so now it's box's choice so box chooses the way and this way they produce again in the sequence of numbers and again we say the diamond wins if the highest rank seems to be often the highest number often is is even so it can be proved using a topological argument that quite a simple one beta based on on on Banach principle that such a language cannot be recognized by by a 0 to automaton so this is settled then the second question would be to defy to decide the second question would be to decide the the index this we don't know we know it for a subclass of so for a class of deterministic languages so language recognized by deterministic automata what I mean by deterministic is that basically each transition is a conjunction of two pairs zero something and one something so in other words the existential player the diamond player has no choice and box only chooses whether he wants to go left or right but there is no choice about the state yes so so this case was sold but in some sense this case is very easy because the real the real difficult part in in deciding properties of automata is non-determinism or alternation so we're trying to come up with with a class that would capture enough alternation to be non-trivial but at the same time that would have decidable properties for instance the index problem would be soluble or the wedge hierarchy problem so yeah so the general problem remains open now you might ask okay so so I want to solve this problem why did I start from substitutions so what why would substitutions help so so imagine that we have this property suppose that if I take two languages B and C S or two automata B and C such that the language is recognized our wedge equivalent suppose it means that when I substitute the obtained languages are also equivalent how does that help now it turns out that if you have this property you can somehow compute the equivalence class by bottom up evaluation so you can treat strongly connected components of automata as operations on languages on equivalence classes not just languages yeah so what I mean by this is that to each wedge equivalence class you assign a certain canonical automaton that will be it's like a name of this class okay and now you start from the bottom you look at the at the graph or a tree of strongly connected components of the automaton and you start from the bottom you look at the leaf components well those you have to analyze by hand there is no other chance right so you evaluate them you find the canonical representations for them and then you you move up you look at the at the component one level higher you look at the canonical representation of its children and if you understand the operation that stands behind this component again you can evaluate I'm sorry right so you just move up up and finally you get the representation the canonical representation of the whole automaton yeah so that's what we would like to have unfortunately if you take the class of the whole class of alternating two automata you don't have this property why well the answer is very simple because that theoretical union of languages doesn't have this property let's look at a very simple example it's going to be a word example but you'll get the the taste of what's going on so look at the following three languages the first one is just the language of infinite words such that one or two repeats infinitely often the second one is similar only now we require that to repeat infinitely often again one doesn't repeat at all but that doesn't really matter and the third language is just the set of words such that from some point some point on you only see zeros yeah now the first two languages it's quite obvious that they're equivalent because the continuous reductions are actually letter-to-letter so if you want to reduce the the first language is a second language you simply map zeros to zeros once and twos to twos and this is this is obviously a reduction in the sense I described previously and vice versa if you want to reduce the second language to the first language you just take the identity mapping and this is going to be okay so the first language is identical and also if you look at them like directly you see that they are in fact sort of the same language yeah just in disguise now the thing is that if you add to them this third language of words that are finally that finally stabilize at zero then what you get in the first case is just the set of all possible words this is as simple as it can be yeah in the topological sense and also in the sense of the index or anything you want now in the second case you get the language of words over the alphabet one sorry zero one two such that they satisfy the parity condition so that the highest index repeating highest number repeating infinitely often is two so this language is in many senses like in the topological sense it's much more difficult but also in the sense of the index if you take a deterministic word automata then this can be recognized by zero two automaton but not but by say one three automaton okay so there is huge difference between those two languages so there is no chance we can we can get this property for for all automata so we need to find we need to find a class such that this property would work of course one can imagine many different approaches many different ways of solving the problem but we kind of thought that this approach is is elegant so we tried to figure out what is the richest class such that we can use this approach and get the result and the answer is actually very simple so since the problem is caused by union you just have to get rid of union yep you have to make sure that your automaton doesn't contain union anywhere but the thing is that the union can be hidden somewhere yeah so the way you do it the way you get rid of union entirely is you say you exclude certain kind of transitions so basically you say that a transition is dangerous we call it ambiguous if it contains two occurrences of the same direction so that means that in some computation the game can reach two places in the same to two places in the tree in two different states that's what it means so this is bad this induces this lets us encode somehow union or if you get conjunction there it's it's it's intersection which is equally dangerous so we can prove the following theorem if if you take a class of automata such that well it's over a fixed alphabet with at least two letters it's just one letter there is not much to to do you you assume that it's closed under substitution because this is the operation that you need to compute to evaluate your automaton and it contains trivial automata that reject everything and accept everything then such a class is a preserved the equivalence the wedge equivalence under substitutions if no automaton has an ambiguous transition if you don't have ambiguous transitions then it's your so here's here's a proof but I would skip it if you don't have ambiguous transitions then your transitions look like this so basically you're either this is like a deterministic transition in a way and this is something I would call a code deterministic transition so it's existential player who makes the choice diamond player but again he can only choose whether he goes left or right but he cannot choose the state so this is the class of automata that we're working on it's not that weak in fact because for instance it can it captures all the languages that show strictness of the index hierarchy yeah so it's quite powerful it has enough that non-demonism to make it interesting at least for us and what we focused in this paper so this is the main result in fact I said I said it's going to be at the very last slide so we focused on weak game automata so automata that don't have ambiguous transitions and also they they are they have weak acceptance condition so that means that whenever you have a whenever you can reach Q from Q prime and Q prime from Q then the ranks of these two states are the same so for such a tomata we managed to to show that so the picture is like this so here are the deterministic automata for which we know how to decide things and on the right you get the the weak game automata for which we didn't know anything but now we do so we managed to to show that for every weak game automaton you can find a wedge equivalent automaton of a very special kind so the special kind is is obtained by by using several very very simple constructions so you can look at such a canonical automaton as if it were a term that you construct with these operations so this automaton it can be effectively constructed the canonical one and also it has the same weak index yeah so I will show you that the operations don't try to analyze them probably from the back rows you cannot even see them but the point of this slide is just to show that there is finally many of them not that many in fact and they are quite simple so the most complicated one it requires three states now the AB and LM they just stand for other components of the automata yes so that's where you put other automata so it's like an operation on first of languages for first of automata and for those operations you can show you can analyze how they operate on equivalence classes and there is a mathematical way of describing what they do to wedge equivalence classes again don't try to read this even there are formulae that that explain how how the operations act on equivalence classes and this way since the operations are are effective we can decide the wedge hierarchy and the Boral hierarchy and what about the index hierarchy well since the automata preserved since the simplification it preserved the index and also we could prove that weak index in the case of this WGA recognizable languages so weak game languages the index is the same as the position in the Boral hierarchy so basically the two hierarchies they coincide so this also gives a decidability result for for the weak index problem okay and that's it basically it now the biggest question that that I could ask at the end what is what happens if you remove this weakness condition so our conjecture is that the method should still work it will require lots of computation but we will try to do it just for fun I suppose the challenges are that well there is no Boral hierarchy beyond the weak languages languages become non-Boral so you move into the area of set theory where things behave strangely you don't have it in the axiom and and lots of different things can happen instead of Boral classes we can look at we can look at languages that are reducible to our game languages yep so the languages I was describing in the argument about the strictness of the hierarchy and then this gives kind of a skeleton and around this skeleton you could try to build the hierarchy it's going to be difficult but but it might give some further insight into the structure of automata yeah so this is our aim for future thank you


My name is Toby and I work for a company called Pytop. I don't know if you guys have heard of it before but just in case not we're trying to develop these these technology and this learning programs that gets the next generation of people into making and building so that is both on the hardware side on the software side as well as the actual learning learning material that's provided and therefore really what we're prioritizing ahead of everything else is preparing the next generation for this this very new job market which is a little scary which we'll be kind of touching on in this talk and so yes what I'll be kind of covering off predominantly is actually the skills that you'll be needing in preparation as a product manager for this this future workplace what I what we refer to as the fourth industrial revolution and you will notice that a lot of these skills that I'm covering off are actually soft skills and they're transferable which is important for adapting for jobs that actually as it stands right now don't even exist okay so before I go into the skills before I kind of talk around fourth industrial revolution I want to talk a little bit I want to take it back to the job market let's say a thousand years ago it was a very very different time and the fact is obviously they had a huge amount of issues a huge amount of problems with plague with famine with empires crumbling but fundamentally the basic features of the society stayed strong depending on the cost level you were involved in you worked in the army you were maybe a farmer you were maybe a weaver so you were given a specific set of skills and because of the life expectancy was so short back then you had those skills that would usually last for that for that whole lifetime and you know that's it's an interesting shift change to now where we have this sort of new world and these these whole new issues that have come through and right now it's really difficult for us to even predict what the future holds so we need to you know already we need to start thinking on things like as you can see some of the problems that are kicking in with climate change with population growth but also some exciting things as well like the increase in life expectancy and with the increase in life expectancy we've got the big the big big change which is this technology which is also affecting this increase in life expectancy and this this sort of new technological wave is going to be full scale in the next decade or two you know what we've been referring to is automation and these we know already are taking people's jobs very really and so we've already got to start looking at preparing ourselves for this fourth industrial revolution when all of these jobs all of these menial tasks that can potentially be done better by machines will be will be taken by machines and you know I'm going to be talking about this in particular from my own professional standpoint so in pi top I spent a huge amount of time in the classroom and I'm a little horrified sometimes when I'm in the classroom because of how much they prioritize this standardization standard form of educational system which prioritizes measurements and prioritizes content as the main focus and and they do that because that goes back to the industrialization that goes back to the industrial age when at that stage they needed to develop people very specifically for to help for this exponent exponential growth this exponential change and they needed to make sure that they had workers and they needed to make sure that they had office people doing these specific similar jobs over and over again and back then as well the content played such an important part because of the fact that there wasn't a huge amount content was incredibly scarce back then but now it's very different and not only was the information scarce back then but the information that was provided was more than likely censored which is the whole other thing and now we've got this time where we've got this huge influx of information you can spend lifetimes just scrolling through the internet on free online courses on you know everything from Wikipedia to TED Talks you guys all know it and with this we don't therefore need to teach kids or we don't need to teach us any more information because we have all that information online actually what we need to start learning now is how to synthesize that information and how to do something with that information and that's something I'll be kind of covering off a little bit you know in this in this in this time now is what that means for a product manager on how to synthesize this information you know and I'm sure you guys have probably seen this one before um but it's the age old quote of forcing everyone into doing exactly the same test and that is literally what's going on in the classroom which is which is horrifying it means that a lot of incredibly gifted students are not being given the opportunity to flourish and so now we've got to start looking at prioritizing some of these soft skills and deprioritizing some of these predetermined slightly harder skills and unfortunately there's a number of companies a number of products out there in the market who who do look at this standardized model because that's the way that they can very easily scale their opportunity they know that if they just integrate into education then they can just scale as is already going on but we need to with with this sort of with these sort of products unfortunately what we're doing for ourselves and for the students out there in this world is we are developing people who will compete against robots rather than working with them so not even robots machines so and that's not just an issue with students the reason I'm bringing that up that's an issue for all of us right now as well but you know it's not all doom and gloom don't worry I'm sorry I've kind of obviously gone a little bit down on the negative on the negative side but the only reason I'm saying all of that is to give a little bit of context because right now we've got to start adapting to this sort of changing well we've got to start preparing for these new jobs that don't even necessarily exist and that's why we've got to right now work on prioritizing these transferable skills that can work in a multitude of different sectors you know at the moment the the number of robots are at the highest unprecedented number in history and yet in 2018 there was a report on unemployment which said that the numbers were the lowest they've been in 38 years just dropped down 5.2 percent so even though there's this huge amount going on in the machine age or in the fourth industrial soon to be the fourth industrial revolution we can still adapt and evolve to work in unison with this new technological revolution rather than seeing ourselves as competing against it and so with with that in mind I think the most important part of what I want to talk to you guys about today is working on actually developing these sort of transferable skills that can quite nicely fit into a variety of different sectors up until quite recently well even now in the educational system the most important part was these pre-determined skills you know you must know c++ you must know a foreign language but we all know that the computers or technology the way it's evolving the way it's advancing they're going to be better than us doing all of this stuff we can already see that google translation you know so we we shouldn't look at like I said before we shouldn't look at competing we should be looking at developing skills that work in unison with this incredible technology that's evolving and changing and that's why we need to start looking at these soft skills these what we refer to as 21st 21st century competency skills and these skills are particularly pertinent for product managers which is why I brought them up and you know I don't mean this lightly but I do think that a product manager is a role for the 21st century because it's one of those roles that is prepared to adapt and evolve even if there's an unknown future around it any company that you go to every single time it's going to be very different dependent on the business needs of what they require from that specific product manager and so they're very prepared for turbulence and for adaptability and that's why why I'm bringing up these transferable skills and why I'm bringing up the fact that product managers such an important part for this 21st century is I want for now for you guys to understand at least while I'm looking out when I'm involved in the hiring process and when I'm looking for candidates I'm looking for people who can actually adapt and evolve to these sort of scenarios with these sort of transferable skills and you know these are the skills that we're also actually teaching students right now in the classroom we're trying to um and you know these these general purpose or soft skills as I've referred to before we've just found electrify the students a lot more and also allow them to really become their own self rather than the standardized model that has been taught taught from them from the very beginning that they are supposed to be without further ado kind of kicking off with what are the four C's based around the 21st century competencies dictated earlier on in the in the century by the UN and so one is critical thinking now critical thinking is I would say one of the most important parts of a product manager's role because you're inundated with information every single day there's a huge influx coming from all different departments and not only that but you have conflicting reports you have corrupted data you have all of this you also have red herrings that send you in the wrong wrong direction and it's very important as a product manager that you can quite clearly show how you can deal with this influx of information and constantly test it and based around that give feedback while also asking the correct targeted questions being able to always challenge the assumptions that you've set up and off the back of that actually have this basis this useful data to work from and with this useful data you can then develop a market driven product or a market driven solution that your market actually wants rather than based around all this sort of analysis is going on and you can then really chart the course or the direction that your product goes using this sort of useful data rather than this this sort of corrupted data that's why critical thinking is so important and you know this can also cover off a number of areas personally in the areas that I work is you know everything from when you're developing feature details to prototyping for early prototypes maybe working with the industrial design team to developing user flows and you're constantly given all of this information you have to constantly make trade-offs all the time because you know there's nothing worse when a department hears you say no but you've got to do that at this role because your priority is navigating that ship for that product into the in the correct direction that's your number one priority and you know right the way down to the product backlog which I'm sure all of you work or have known a lot of to managing the sprints and all of this what we work with internally which I'll cover off in a little bit is this sort of design thinking methodology and that's how that all nicely fits together for us critical critical thinking is obviously incredible incredibly important but collaboration is another one of those soft skills that's fundamental for a product manager to prepare for this this this sort of coming time and in particular with these soft skills you want I mean with this soft skill you want to make sure that you are constantly leveraging experts both internally and externally to make sure that you get the best result out of the product at pi top we have some of the best learning team you know ex director of learning from apple and we're being able to use and refine that information to make sure the learning framework and the product is developed precisely but if I just relied on that bit of information then we would have a product which wasn't customer centered that would be a product that was developed purely with the learning ethos in mind and so that's why it's important like I mentioned before to always make trade offs with the decisions listen to leverage all the different experts take in that data and then critically analyze the data based around that and then yeah so it's very important to curate that and then also another thing is this encouraging peer participation now this is particularly important at pi top on the software development side so I work across the hardware software and the learning it's a it's a bit of a beast it's a very very wide remit but it's you know it's startups for you and on the software side we've got on the operating system side they work on this thing called PED programming which is a really clever way of introducing someone who's never ever used the code base before to understand how the company works and in particular how that particular environment works and what they'll do they'll be someone who'll be doing the code more than likely the new recruit and then there'll be someone overhead navigating and constantly giving feedback to make sure and reviewing that code so that's also an incredibly important part is always collaborating and that works in any different departments then that feeds into communication I'm going to be talking a little bit around both the internal communication and then external so I think again maybe you guys have seen this this this chart before but there's a big you're as a product manager you're the glue between all of these different beliefs that's what the product is from sales to ops to qa to customer service to marketing every single one of them has this different interpretation of what they think is the best product and that's your role is to synthesize as mentioned before all that information down and to make sure that all of them adhere to your product vision based around the data that you've been able to critically critically analyze before so always listen to everything that they say in particular the sales teams are very important voice for the customer but make sure that no one opinion is taken too much too much more heavily than the rest you need to make sure that everything is taken on board before you make decisions around the product and then also externally and this this is incredibly important is empathizing with the customer so with every single product that I've worked on that I've developed at the very beginning you work on developing this value proposition and before you do anything around that you've got to start understanding how the customer is you've got to start empathizing with the customer's plight and how you do that is both through qualitative quantitative research and working both internally and externally to get that data then grinding that down into something which you can use to define what the market is after so once you've empathized with the customer you can then start defining what that product is that they're looking for and then you take it to the next stage where you start actually ideating and throwing stuff against the wall and seeing what kind of sticks and I think the most important thing of all of this is then rapid prototypes and testing and a constant feedback loop with this rapid prototypes and testing at pi top both on the hardware on the software side we had about nine or ten stages like full-on stages but pretty much through each of those stages in the sort of double diamond through each of those stages we made sure that we also had rough and ready low-fi rough and ready high-five designs to actually make sure that we constantly had the customer's voice involved in every single step in the process and that is such an important thing that is sometimes looked over especially for younger companies because all they want to do is you'll have a founder who's got a belief in what they think is the perfect product and they know exactly what what the customer wants but that's why again like I mentioned in point one with the critical thinking you've your role is to sometimes say no and to analyze that data and to show them why they need to look elsewhere and that's why rapid prototype rapid feedback is such an important part of this and you know on another note this sort of emotional intelligence bit is another thing that uniquely stands us away from this technology this machine age being able to communicate between between us so yeah then if we move on to the next point which is creativity so there's a number of different bits in creativity I think the what I found in my my my career in creativity is the fact I've had to be very adaptable to chaos very very quickly and that can be down to pivoting of business that can be down to rapid need of fundraising that can be down to a whole host of different things but a product managers role is to be able to creatively interpret what's going on and develop a solution based around that and that's both on the situation and on the product requirement side as well and we are also at the moment trying to develop learning curriculum and learning framework for students to actually start getting them thinking like this as well because at the moment and you guys will all remember this as well it's very instructional it's very step by step recipes for schools but what we want to encourage more and more is interpretive learning and give them a problem-based challenge and see what they come up with because that's where some of the most exciting kind of stuff comes from depending on what avenue they want to go and also on top of that you've got the play aspect and that's just the most most important bit for us is is the play side is always enjoying what you're doing from when you're doing a competitor research to learn early designs always having play enthused in any department that's involved in that right the way up to when you actually start mixing and remixing the product as well and you know we've got this we've got this thing where on our product we see it as three stages for the for the learning you've got this discovery stage where a kid goes out and they're just like i'm going to digest as much information as i can i don't know everything i'm going to digest as much as i can and then they go to control stage it's like i'm stop digesting i'm going to start taking ownership of what i'm doing and then they hit the next stage after that which is transference which is when okay so i've done all that i've got all this knowledge but i've also got all my contextual knowledge around that and i'm going to transfer that into something special and that for us is when the magic really happens in the product in that transference stage where we've done the discovery of doing the competitor research started to control develop the early designs the early prototypes taking them out and then based around the mixed interpretation of data on different customers on both internals and externals we've been able to start remixing and reinterpreting what our product looks like i would love to be able to show you how much our product evolved the one that launched in january but it looked to begin with like a green a green screen with a little fat back on the back when it first started just like a little lump on the back and it went right the way to this this beautiful thing we created the end and what the purpose was at the beginning was completely different to what we developed at the end and that's another important aspect in what you're working on is you've got to be agile you've got to take in this data and then be able to readjust based around this data in an agile way i guess what i'm trying to get at throughout all this talk is really the most important thing of everything else is that you're not competing in any way for tech you're not competing against technology for jobs if you start looking at how important these soft skills are for you and in fact if you start deprioritizing some of the hard skills that are being taught then you can actually help thrive and grow in this sort of this this sort of new time and you know with this sort of coming forth industrial revolution i think it's really exciting time for product development product management and product development as it is as we are going to be the people who are going to be building the infrastructure with great teams to ensure that we all thrive and adapt and reinvent in this sort of coming time in this coming wave and so therefore i think what's most important in all of this is for now you've you've got to start also thinking of developing products that can help us shape this new and exciting world so thank you