What's going on guys welcome to a brand new sweet film podcast my name is Zach and my name is Cody and today We're discussing the highs and lows of the conjuring franchise because this weekend the scary-ass none looks to be coming out Hopefully it's scary. I'm not I don't have much hope for the film But I'm hoping it lives up to that potential what we're talking about the highs and lows the conjuring universe plus me and Cody have been wanting to talk about more video games on here So we're also gonna bring talking about the scariest video games. We've ever played But before we get into this we do have a great guest joining us and that is Ren from over at Ren Geekness. How are you doing, man? Hey guys, thank you so much for having me all the way across the pond as we just mentioned It's a great honor to be here I wanted to be on on the video with you guys for so long and I don't get the none this weekend But I still want to talk about it. Hey, it's still worse We'll talk about it then when you see the none you can tell us what you thought of it Or guys of course go so subscribe to him Which is link will be down in the bio and then you guys can see all his great movie reviews over there But um before we get into this I get to know I know how Ren's doing How are you doing Cody on this lovely morning in Arizona for me, but kind of afternoon for you? Yeah, no, it's it's going well We're still I'll say this. I love your background. I love your background. Oh, thank you. Yeah Deadpool and cable say hi But yeah, no man's fine man's good. It's uh, it's like 90 degrees with 70% humidity here So, uh, it's okay, but You know as far as the none is concerned with all this stuff and first of all Thanks everybody who showed up to the sweet film podcast and thanks to everybody who's seen the second episode of entertainment wars It's getting it's getting a lot of people to see it right now I believe we're at over a hundred people close to a hundred and fifty people who have seen it So thank you to everybody who's seen it so far. Thank you so much for showing up It really means a lot for all the support that you give us for the podcast and for all the projects that Zach and I do But as far as the none is concerned When it comes to this movie, I always put it into two categories I don't think it's gonna be as good as any of the Conjuring films However, for me, I think it's either gonna be this year's Annabelle Which we all know that movie was a complete another bus fire or it'll be this year's Annabelle creation And if it's just like Annabelle creation where it's just a fun Fun horror movie, I'll be okay with that. Yeah, I'm saying too, but I guess we'll talk more about the preview and preview than on a little bit So let's just start with the Conjuring universe. Let's get to the highs and lows This will be a great discussion and of course starting back in 2013 we're bringing into the Conjuring.  I'm like a huge war in fanatic.  We almost shit our pants So but with Ren being our guest Ren I want to hear your thoughts because you did tell me you have some unpopular opinions about this All right, so Conjuring one came out in 2013 as he said I didn't see this movie in theaters I was not interested the film did not look good to me And then as you said the buzz came out everyone was raving about this film And I was like this is strange, but I'm going to wait for the hype to die down So I waited and waited and it wasn't until like January of the year following that Then I watched the Conjuring for the first time. I bought it. I put the blu-ray on my PlayStation I watched and I was like that was fine That was an above No, not even above that was an average horror film I would have you seen it again since have you seen it again since?  I've Man of Steel. I have Wonder Woman It's an OCD thing the only franchise I haven't done any ends because I refuse to spend 20 bucks for each one is cars I have cars one and I have cars three Do I want cars too? No, but every time I go through my collection.  So what is your thoughts on the very first one? Oh, yeah No, I I love the first Conjuring movie. I have my first experience with it was It was like a year or two ago like I ran our first experience I think we're talking about like sex stories to the first time about sex Was third grade when I was going through a little anime book and I found a naked lady. Oh, you know, it's Well, we Tentacles we do have a Okay, this is too much. Yeah, I would say so if you guys want to hear more about sex and movies We also have a podcast episode for that So you should go check that out, but the condor I want to be in that one We'll make another one. We'll make another one right the first country movie. Yeah, I'm a porn. I Porno like a condoring spin-off porno.  Why isn't it demonic but yet?    We might get to monetize, but she was on her knees. I'll just put it there But go on Cody Okay, so I love the first Conjuring film I've seen it multiple times and And What I can say is like Ren I did not see the film of the theater, but I made the mistake I was lying in my bed. It was eight o'clock at night. I saw the Conjuring on Netflix And I decided to watch it wait wait wait hold up You just watched this didn't you like for the first time not that long ago Well when I say it was about like six to six to eight months ago I remember you texting me and I thought you'd already seen the film Okay, yeah, no, um, so Let's just say after watching that I probably didn't get to bed till 2 a.m. Because I was afraid to fall asleep in my bed I've seen it a few more times since then and I've you know I've seen all the rest of the other Conjuring films up until this point, so Yeah, I love the first Conjuring film. I think it's a brilliant movie. I think it's a great horror film So yeah, and that's why I think rent should revisit. I think of Ren revisit I think it might bump up for him because I've had those same things where I'll watch a film and then like years down The road I watched again. I'm like, oh that was not as bad. I don't remember what film that there's a horror Oh, um in city is so it actually the reverse effect when I first saw on city is to I Freakin thought it was dumbest thing in the world. That was horrible And I always used to think the first one was fantastic and then I dated this one girl who wanted to do a marathon of all them for the third one came out and I hate the first one now and I love the second one and I actually Be watched the second one like every couple months. I really like the second one Funny you should give those as examples because I I actually just watched the three in cities movies before the New one came out this year. Oh really you like them. Do you like them? I The first one I thought it was watchable.   I think he's fantastic. I actually have his Funko Pop somewhere over there He is I think he's one of the best directors working today hands down like Conjuring is perfect like top 10 Yeah I'm not saying like of all time, but top 10 working right now He's up there because I think his direction even with his like weaker films His direction is always strong like I don't think Dead Silence is a good movie But didn't he direct it? I'm pretty sure he directed that sound and I did and he's the direction It's pretty solid I'm insidious again. Those aren't the best and there's not solid saw the first saw Jesus That that was like a fantastic But guys, let's move on to 2014 Brilliant spin-off that came out called Annabelle do we have to So read from you saying that I'm guessing you don't like this. This isn't the real one. Oh, no, I thought it was so You thought I was off the right I was like that I didn't get up, but I did watch this one in theaters I didn't get up or anything. I did I never did that thing of being loud in the theater But I tried so hard for the entire runtime of the movie by the way to hold my laughs in Because I saw everybody be like Oh Can I say one thing? Let me get my pro. I think the basement seems great the basement seems great Awesome, that sequence is okay. Yeah. Yeah, I don't know if I just think it's great because I agree I'm not no, I agree with you on that one Let's be honest though. Is it only good because the rest of the movie sucked? probably I Don't I think it has it genuinely has its value Genuinely as its merits. Yeah, I don't know what happened with us impressive, but cool scene. Yeah. Yeah, I don't know What happened? I don't know people like to this movie John R. Lin net. I have no idea that is Okay, me neither.  Okay, the man went on to the right to wish upon guys. Oh my god. Yeah, let's not talk You know what? Here's the other thing if you notice James one had barely anything to do with the Annabelle movie Oh, yeah, I wonder why I wouldn't want anything to do with it either Yeah, no It's so bad. It's It's hard to believe that we go from something so expertly crafted such as the conjuring and then we get Annabelle which Okay, no no shame in saying it here since I just caught up with the the conjuring films in the past eight months, but The fact of the matter is this Annabelle is A horrendously done movie and halfway through the movie. I Almost fell asleep. I think I fell asleep for like a good 15 minutes of the movie See, I didn't see this film in the theaters because I didn't want to like I saw the reviews And I was like, yeah, I'm not seeing that and then I ended up renting it and Man It's I was just like this isn't even fucking none of it makes sense Sometimes no, no, but I will give it this if you watch This is a spoiler podcast for people have not seen the conjuring franchise other than none We none of us have seen the nun so we don't know what happens in none. Yeah I mean, we'll talk about animal creation a little bit more when we get there, but let me say this Annabelle creation enhances this film just a little bit not a lot, but it does make it a little bit more Understanding of what's yeah, it does. Yeah, so I will give the film That I think it was really smart and how it tied in because let's be honest when Annabelle creation ended I my mouth dropped my mouth dropped. Yeah I'll talk about that in a second. I think Annabelle we can just skip over talk this movie Oh before we move on from Annabelle I have a very interesting fact about Annabelle as we were talking about the director in The beginning I just found out that the man who directed Annabelle also directed Mortal Kombat annihilation Gentlemen your thoughts. So this man directed Annabelle Mortal Kombat annihilation, right?  I mean Cody. You've been saying this though lay Manel director of upgrade He is friends with James one if he does not do the Mortal Kombat reboot film. I am not watching it Yeah, and sorry, but it's Yeah, speaking of horror things Zach and I also agreed that if resin if James one actually does if he himself Directs a resident evil movie. We want lay Manel to take care of the action in the resident Well, he's producing the new resident evil that they're making so I have a feeling one really yeah He's producing it's supposed to be based off like the ones that we're doing right now So but I'm curious red. Did you see upgrade? Yeah, I just saw it actually. Okay. What do you think of the action? The action is great. I mean, I love the movie until literally the last two minutes see that's how me and Cody were and I mean All right, and if we're gonna talk and I called what was going to happen. Yeah, it's like 20 minutes in I knew The reveal was going to be it. Yeah Speaking of the action that was in upgrade There is there's the first action scene. I think for me is personally one of the most Like he has the job for Mortal Kombat right there But yeah, we're actually talking about a horror franchise and the next film to come out in the series was actually the Conjuring to two years later coincidence on that so Cody I'm let you take this one off. What do you think of the Conjuring to the Conjuring to Does something very rare when it comes to horror films It not only produced a horror sequel that was Interesting, but it also produced a horror sequel that was actually good and I think that's partially because James Wan was still on board and he still had his story he wanted to tell with the Warrens and The Conjuring to I think I don't necessarily think it's as good as the first one is But I do think that as far as a horror movie I think the scares are more terrifying than what they were in the first Yeah, but either way either way you slice it. I thoroughly loved the Conjuring to I think it's Well, well without a doubt it is one of the best horror sequels to come out in a long time because it's It's good and we all know that horror sequels generally are never good. It's rare that they ever are Okay, so I'm curious to hear your thoughts Ren. What did you think of the I Love Conjuring to Then the second then the first one damn I'm gonna be I adore the small house. I Adored the small house.   I fucking love I Love how he He makes basically the house the environment that the characters are in a character and Flatter then also did that with the nun the not the nun sorry the end of all creation and One also did that when insidious too, which is why I like it more than the first one as well See so this is where I'm at with Conjuring too. I thought it was fine. I didn't think it was like amazing I didn't think it was like I thought it was good. Like I thought it was good I definitely like the first one more. I Think my issue with the second one is it's way too long for me I think it's way too long for a horror film And I think there's something you could have cut out and another thing that does make me so again Like I said earlier. I'm a big warrants fan like I love all their stuff The true story of this is a lot of bullshit Like they embellish and I get it like they embellish a lot But I hated how much they went away from the first one They really did embellish a lot for the second one like the nuns never a real thing Annabelle's a true thing, but and the nun was never a real thing and There's so many you'd have to dig into like the actual stuff that goes on but I think for me. I Think the nun is a cool addition. I think it's awesome that it was reshoots. It was a reshot thing like Yeah, you didn't know that the crooked man originally the main villain and they went back and we shot it all to be the nun Yeah, cuz the twist caught me off guard. Yeah, so isn't that crazy how that works, but yeah I mean even crazier is that the fact that I mean in the narrative it works at least for me Oh, yeah It really works though the fact that I was shot was another and I even like the crooked man I know a lot of people do not like the crooked man in his CGI the CGI need to be touched up a fuck done But the crooked man, I thought he was cool for what he was, but I thought that old man That was creepy like this Remote I think that's the most freakiest scene is when she's at home alone because we've all been there We've all had that kind of stuff in the conjuring to me. I think delve deeper into these characters and delve deeper into this universe and that's why I'm still surprised that there is no announcement for a third one None what so I want they want to see if this none works cuz If it works out like the rest of the franchise has worked out for me I'm going to hate the first none and I'm going to like an eventual second the nun movie Oh, yeah, so if this first fail, they're going to announce a country a conjuring three before the nun to Yeah, yeah, I mean pretty bad for the nun I remember a little while ago There was talks of of a conjuring three and the more I think about it the concept that they had then I Just do you remember the idea? Yeah, it was about bringing werewolves into which is awesome Do that class that they do is seriously look at the Warren's werewolf case when you're done It is insane. Is it really and it's okay And it's very I don't know obviously if they embellish a lot of stuff But I think that's the right direction to go get away from the demon stuff go into that That's our actual true case that they dealt with and it is in Think about it if they if they mixed like American werewolf or what is American Brian got it the American werewolf in London that one if they build that psychological tension Within the conjuring universe. I think that'd be great I think that'd be awesome, and I think that's the best way to Bring them in you know what I mean Obviously they'll embellish it a bit and they'll probably actually make it like more of a werewolf, but I'm sorry But I would want that the only thing that worries me is the writer of the film That's the only thing that worries about me because the guy who's writing the third one he wrote The orphan Wrath of the Titan Okay, gosh wrap with it Conjuring to which okay, and he wrote Aquaman, so he's I think Wrath of the Titan is the one that scares me a little bit I like the orphan I did too. So that's why I'm like, okay. Okay. We'll see how Aquaman goes But yeah, he is he is writing the new Conjuring 3 so hopefully they get that in development soon But guys let's talk about 2017 because Annabelle creation comes out this year and I my experience with this movie was I had seen a trailer. I said it looked bad I am a big fan of David F. Sandberg after lights out and all of his short films I think the guys are genius. I cannot wait for shut lights out like literally I would love to sit down and talk with this guy I I'm such a big man. Do Dr. Sleep. No, that's a Mike Flanagan. This is Sandberg, man. Oh, wait separate guys. Oh Yeah, no, yeah, okay I'm gonna touch me man. I he makes me want to touch myself every time I watch one of his films and a real But Dude, I mean this guy is like he has such a good success trip I like lights out and then Annabelle creation. I just remember so I got an early screen of this I was sitting there.  It's not like I went home and I was scared like psychologically But in the moment, I was scared and I think about creation is fantastic I think it's one of the best films in the Conjuring universe I think it's probably the second best to be honest and I think it's probably the most fun. I Love all the little nods and none not in the picture. That's awesome I got a little Easter egg in there made me jump out of my seat the after-credits scene It this is how it should have been and again, like I said, it enhances the original Annabelle because When the ending comes about and you see that it's the original Annabelle my jaw dropped Because at first I didn't understand what was happening. I was like, wait, I'm confused. Those people look familiar What's going on? Oh my god. Oh my god. She woke up.  Did they always plan on this? Not until after the the first Annabelle failed, I think at least But for me, it's like the first Annabelle it never made sense with the cult it never made sense Yeah, so that's why it's like this one makes total sense now, but Brent tell me what you what's your thoughts about animal creation? Oh, man I had so much fun with with Annabelle creation. First of all, let's say I really like this movie But let me point out the the one big flaw because I actually already had a channel when this came out But I just chose not to review it for some reason Maybe I was feeling lazy and you can call the the scares in this movie. That's the weakest point of it But the atmosphere that Sanberg creates He just has these long takes steady cam shots. He walks around the house He makes you observe everything so you can see Where stuff is going to come in and because you understand that he does that on purpose You have so much fun with it You sit there just waiting and waiting and waiting and then it catches character X or character Y From the dark boom. I love that moment.  I wasn't a group of like eight people watching that movie We all were calling it but yet one person screamed and like Scratch my friends arms so much Bleeding after that I mean Holy cow, you know talking about this. I kind of want to sit down and watch Annabelle creation again But one of my favorite scenes from yeah, if you couldn't already tell I Really enjoyed Alan Bell creation. It was actually funny enough if you saw I thought it was smart I think it was the oh that was also When I saw the little little clip of it that they were showing a month beforehand and the month before Zach and I officially met But But Annabelle creation. I thought it was a fun movie. Yeah, there are a lot of horror cliches in Annabelle creation There's no deny, but one thing that it does is We finally got we actually got a great Conjuring prequel and a group and a really fun Annabelle film Which that's the best part and what I think it might be my favorite scene as far as horror is concerned is when the little The little orphan girl on crutches because if it's not a wheelchair, it's gonna be crutches But she goes inside she goes inside of Annabelle's room She doesn't know it's Annabelle's room Yeah, but then but then the place where Annabelle is kept opens up and you just see the doll sitting there that is In my opinion, there is no amount of of suspense or atmosphere Horror that is captured in the rest of the movie then in that one scene the way that was put together was so brilliant And one of my favorite things is looking at the behind-the-scenes stuff It's apparent that they may have used a lot of color correction because they did a lot of Daytime well, so it's funny. So if you guys haven't check out David of Samberg's a YouTube channel He actually goes to the death of how he does all the special effects He does a lot of the special effects himself So you know the when the body's like hanging and there's blood dripping on the floor Yeah, yeah, all that at home. That was post-production.  So he like that's why I really like this guy and I cannot wait to see what the guy does With Shazam I don't know if we'll get to do videos like that on Shazam since Shazam's like a more higher budgeted film But I just I love Annabelle creation all the subtle nods to the conjuring universes in there Everything is just so weaved in there perfectly in my opinion. It's not a perfect movie But it's a great horror fun film like it's a great film to sit people around and watch and enjoy and Yeah, it's a great Halloween movie. Yeah, so before we get talking about the nun I do want to talk about two of the other films that they are coming out within the conjuring universe are Obviously, we've already talked about the conjuring three With the werewolf, but I want to talk about the next Annabelle film Have you guys heard about the film at all because I'm gonna tell you That's what I was going to ask you like when we were talking about conjuring three I was about to ask and isn't there an Annabelle three announced or something because I'm not sure There isn't any they just announced that at Comic-Con this year or Scare-Con like that's that's okay now It's directed by Gary Doberman who is been the writer on almost every single thing in the conjuring universe And he also wrote and I'm pretty sure he wrote it Let me check. Oh, okay. I'm pretty sure you wrote every document Yes, he wrote it. He wrote both chapters of it. Nice. He's written everything pretty much like ever since the Annabelle he's written everything for the conjuring yours. Well, they have a great writer on board. That's for sure Yeah, so but he's also directing it first-time director Which I'm not as scared because James Wan is like I guess Actually like really hands-on with this next Annabelle film I certainly hope so and are you guys ready to hear what it's gonna be? What is it? James Wan specifically calls this next Annabelle film Nightmare at the museum because he compares the whole film tonight at the museum where it's all about Taking place in the future in the Warren's house With the with like the dolls and her bringing everything to life and it from what I understand Is that Ed Lorraine will be in the film, but they will not be a main part. It'll be the daughter Wow, okay, that sounds honestly Once again, that's the idea That's in it with the team they've got behind them I don't think it's gonna be a film that will encapsulate the magic that the first conjuring film did I just don't I don't think it'll be glad to go in a different direction though. That's why I really like that Yeah, I do think honestly, I do think this will be I do think that This will be another really fun Annabelle film. I mean, that's what I'm getting from the premise It sounds like it's gonna be a ton of fun Yeah, no, so I wonder I Wonder if it could be like it. Have you guys seen Black Mirror the last season? I I'm gonna be honest last season. Yes last season. I watched. Yes Okay, so the episode the final episode of Black Museum with Shuri from Black Panther Yeah, I know what you're talking about. Yeah, so if it's that But like in a Annabelle in a Annabelle scenario, that would be insane if they go rated R, especially Oh, it'll be rated R. Almost every film in this franchise has been rated R. So Actually, I think every film in the franchise has been rated R. Yeah, I was actually surprised a little bit Yeah, I knew the first Annabelle was because I didn't think it was rated R Yeah, no, it's But as we've already stated that the first Annabelle movie is crap Yep, it is Okay, so do we want to start previewing the nun? The last thing I want to bring up is the crooked man. Are you guys wanting to see this film? Oh, if I tell now if I throw in that James Wan wrote the story for it. Will that make you excited? Yes, it makes me want to see it Not not excited because it's just a story not the screenplay But I am more confident because they at least have a solid or what I like to believe is a solid basis for it True true on that part, but I don't know I would need to I would need to hear what it is about actually not just crooked man and That doesn't that it's not enough for me. No, I I guarantee that none doesn't do good. They're not gonna make the crooked man Yeah, don't ask Those seriously they will go straight back the Connery three if none doesn't do good Yeah, I look at this film franchise and it's a billion dollar franchise, which is that's awesome That's awesome to see it's a billion dollar franchise, but so guys Let's preview the nun. I want each of us to just go through. What do we expect from it? What do we want from it and just make one wow prediction about the film? Ren I'm gonna have you start with us since again. You're our guest Okay, so I've only seen the first teaser. That's the only trailer there is That makes you feel better. Yeah, there's like nothing else for this film Which means they've already shown us everything cool Also, I've only seen each of the Connery movies even the ones I like once so What I want from the nun is for the twist to actually be that it is Mark Riley from Schmozno and Clyde. No, I'm kidding What I want from the nun is I want atmosphere I want us to go down into those Underground tunnels beneath the church which seemed to be in the trailer where it's all foggy and the The the actual nun not as in the cursed nun The actual nun is there and you see the nun behind her she looks and then there's another nun I thought that was very creative that caught me off guard I don't want the movie to be entirely like that. It feeds on the cliche and then turns it around and If I'm going to make a wild prediction I'm going to say the crooked man is in this film With a big role actually at least bigger than a cameo big role or do you think just a small role kind of how like the nun Was an Annabelle condition Okay, I wouldn't say not that big a role But I know I wouldn't say I would say it's much bigger than that. It's not a cameo. It's not just one scene He isn't he's actually important to this story. That's how I'll put it Okay Cody you what about you? Okay my wild prediction are not I'll get to that in a sec But what I want is the same thing is right now. I just want a fun because like I said, I don't think this is gonna be anything I Don't think this is gonna be anything as good as the as the Conjuring films. I I don't I am expecting a fun Atmospheric horror film and I think them playing in an old Romanian church building where you have all that religious Symbolism in a building that is just so so dark and so and so haunting. I something Atmospheric I think will be the best thing for this movie and Obviously it feels as though we're going to be getting good performance in here and my wild prediction I Think I think that the nun. I think it's going to tie into the first Conjuring film somehow. I'm not sure how The Vera from Miga, isn't her daughter in this to taisa from Miga I'm pretty I know she's in it, but I know they're relate. I don't know if it's her daughter or her sister or something No, she's a she is very very for Miga's daughter. Okay. Is she playing a younger version of her though? That's the thing. I'm like sister Irene. No, no, no, no, but she's not a younger version. Yeah, sister Okay, well, okay. How about this it's going to Okay, wait, she's the younger sister of her for Miga. Okay, it's obviously going to connect at some point. So Okay, I'll I'll scrap I'll say that But I mean, why would you get the younger version of her if it's not gonna connect to the first Conjuring film exactly So, all right, I guess my wild prediction is I think we're going to get a connection or a tie-in into Definitely into future films down the road, but I think we're going to get a tie-in. I Guess I'll go with what Rensing. I think we might have a tie-in with the crook and man in here So you guys want to hear something so Okay, I'm reading this right now one discuss the possibility for a nun sequel and what its storyline may cover I do not know I do know where it's potential if the nun works out where the nun Too could lead to and how that ties back to Lorraine's story that we've set up in the first two Conjuring's make it all Come full circle Okay, so this one wouldn't connect to Conjuring Okay But okay, now I'm reading so the director originally did not want to cast Taissa for me because they were related they changed his mind after seeing the audition Okay, so maybe they aren't related. Maybe they just you know what I mean. She got the role. You know what I mean audition that makes me that would make sense That would make sense it could just be like cuz I mean they're related. You know what I mean, like I don't know For me the nun, I just want a really good atmospheric film.  I'm just expecting a good Atmospheric film like Annabelle creation. Yes, and I'm also hoping for a good story.  I just don't want an Annabelle like literally just don't want a first Annabelle I want a like a decent horror film, but I should expect more of that from the Conjuring universe So that's what I'm hoping from the directors and new time director. He's only done a short film and I've heard it's pretty good. I haven't watched it. I heard like fix that gothic stuff Is it a short film? No, he's not a whole oh the whole feature Yeah Looks pretty good to be honest.  I think she's gonna be in the film she'll be in the movie some way shape or form and Even if it's her telling a flashback or it ends with the Conjuring to get tying into the Conjuring to Yeah, cuz the Conjuring to is also pretty well through the first one, right? Yes But it takes place after the Conjuring one, but it has flashbacks to the app But I'm also with you I wouldn't be surprised if the crooked man shows up because that's supposedly supposed to be the next one so it would make sense for it to go forward and Yeah, so I I think I'm looking forward to that but let's move on to our next thing before we get going guys and that is scariest video games you guys have ever played Cody I'm let you start and then okay. I'll go in that. I'll go and then we'll let Ryan go Well, it would make sense you start with me because okay, just the heads up for you guys listening and watching this is that I Well, that's not true. I just haven't played video games in a long time But as you guys may have known I went to see Zach over the summer in Arizona And he kind of got me back into video games and he touched me and he Well, guess what buddy? So did you? All right, but He introduced me to a little game called Resident Evil 7 biohazard and as far as terrifying games You guys know that the last of us is my favorite game of all time. I don't find it that scary I don't find it that scary of a game. I find it a brilliant game not a scary one Resident Evil 7 biohazard The first time I played it is one of the most terrifying Experiences I've ever had and it's because the game is so well developed and so well established that the horror inside the game It's very atmospheric. It's so It's so well put together and of course I really loved all the callbacks and stuff that they had to classic horror movies like Tex-Ex-Chains on massacre to evil dead to to So many things so that's my answer is Resident Evil 7 biohazard. Okay, you have any other fix at all? Oh Yeah, um back in the day They're not like, you know PS4 major in mainstream games But the the two ones I would pick are for honorable mentions are slender when it first came out I played that with some buddies of mine in high school Yeah, I played that with some buddies of mine in high school. That was terrifying But if we're gonna talk about PC games the other terrifying game is Amnesia that game is creepy That that's another experience to where it was pretty hard for me to get to sleep at night when I played it But those are my answers resident evil 7 biohazard slender and amnesia. Awesome.  I'm one of the few people that still own this damn game On their ps4 it's probably a 13 minute demo 13 20 minute demo of what Silent Hill was supposed to be This is easily one of the creepiest games ever played Atmospherically all that all of it's in there check out the demo on YouTube if you can check it out and watch it Until dawn a really brilliant wharf game. I thought it was really cool. You get to choose your own direction I think it was super scary, but the atmosphere again was there You already mentioned amnesia, so I'm not gonna talk about it dead space one and two is Amazing the first one is scarier, but the second one has some of the best horror stories.  I know another one that you mentioned when I was there you said that Yes, that's the one that you were talking about mention so outlast one I thought was very scary, but I thought it didn't it lacked in a very other departments outlast 2 Was more effective for me on every other department. I thought outlast 2 was just insane Especially since it takes place in Arizona. So maybe that's why I'm a little bit more scared of it, but Other than that I think the only other game I can really talk about is condemned I don't know if you guys have ever heard of this game.     I?  I killed everyone except one person Really, who did you keep alive? The blonde girl. Hey in pants here. Yeah, Cody. I really recommend this game. It's like only 10 bucks, dude Yeah, I'm sorry. It's 10 bucks. It's 10 bucks and it's like telltale, but a horror game Yeah, I'm gonna have to check it out. All righty What else what else was I going to mention? I think amnesia is also really good fear is really good Yeah, this one is not a horror film, but it can get scary at points And it's splatter house the one that Yeah, that's a really a really obscure one and Little nightmares. Have you guys played that?  It's so good. I never saw a single trailer for it I never saw anything about it. I saw the cover when it was for sale. I picked it up and it's amazing I love that check it out. What's it on? It's not a ps4. Yeah. Oh really what's it called little night and it's Yeah, little nightmares And it will remind you of it like in a real way. Oh I Know this game and it's on the switch. I might go buy it on the switch today All right Damn, I know I'm not sure what price it is right now, but it's you know, there's a Easter egg to it in it, isn't there? There's a big one. I'm pretty sure it's on YouTube. He's wearing a raincoat. So yeah All right, I'm down for that. You know what other game that kind of reminds me of is limbo. Do you guys remember that game limbo? Yes, I'm yeah, but I know what it is. It is a very dark game, but really cool But yeah, I really like that game And one other game I want to mention for horror games, which if no one's ever played this game It's called BioShock. If you don't know what BioShock is. Oh, yeah, see I love BioShock I loved one two and I loved infinite infinite it's my favorite, but one is still a horror game for me That is a horror game So it has four elements to it, but I think that's where we're gonna cut this off guys So again, thank you so much for watching the sweet film podcast and a journey into the highs and lows of the Conjuring universe As I'm sending everyone off I want everyone to tell and say what their favorite film in the Conjuring universe is so before we get going Right and where can they find you at man? And what is your favorite Conjuring film? My favorite Conjuring film is Conjuring 2. I think it's the highest Franchise as ever has gotten and will will be the highest one for a while Even after the nun and you guys can find me anywhere on Facebook Twitter Instagram and on YouTube Or I do movie reviews and I share some of my short films sometimes at Ren Geekness It's always the same name So you guys don't have to search very hard for it and I want to thank Zach and Cody for having me on I can't wait to hopefully come back on another episode and I'm going to be collabing with these gentlemen's on my own channel very very soon Awesome man, thank you so much I can't with the collaborate with you guys if you guys haven't me and Ren did an awesome Collaboration about what almost a year ago now talking about Star Wars attack of the clones That is the best rant if you ever want to hear something two men talking about how Anakin looks like a pedophile Get on yes, but Cody where can they find you out and what's your favorite film in the Conjuring universe? Okay Well first I find it funny that you say Anakin looks like a pedophile because remember Padme was like what 16 years older than That's true, that's true It's very creepy very wrong and attack of the clones needs to burn in a bus fire But guys my favorite film in the Conjuring universe is still the first one. I think the first one is brilliant I think it's a masterpiece of of horror of horror making But of course when I'm not here doing the sweet film podcast with Zach You guys can also find me with Zach hosting a little game show called entertainment wars episode 2 is up right now So you should go check that out and you can also check me on my own YouTube channel Just look for Cody Curtis up the YouTube search bar should be the first name that pops up You can also find me on social media on Facebook Instagram Twitter Snapchats and a little movie reactionary app called start us either search underscore Cody underscore Curtis or just Cody Curtis She'll be able to contact me on there. Let's get a conversation started awesome Thank you so much guys for joining us and before I get going You guys find me a sandwich on films down below or on this YouTube channel, of course at Zach Pope Also, let me tell you my favorite Conjuring film probably the Conjuring one But I'm gonna be a little bit different and say Annabelle creation. Just why not wow I like being weird, but I mean it's probably Conjuring, but I gotta mention I gotta give some love to Annabelle creation, but thank you so much Ren for joining us Cody Of course, thanks for being a great host with me and this is the sweet film podcast So of course until next time you guys all stay classy and have sweet rest of your day


With social media like Jonathan hates talks about this right specifically affects young women or girls The I think there's a lot of things have happened Number one obviously we have we've had economic issues a lot of the blue collar middle-class jobs are getting squeezed That doesn't it doesn't help that the the Fed is printing money through quantitative easing and our buying powers decreasing What's the point in making three times more money when the buying power is losing about? You know inflation 2% plus tax Plus products increasing on average. You're losing about 3.5 to 5% per year for purchasing power We'll probably still be nice for a lot of people to still have their wages going up It's a match that at least but I get what you're saying the Fed just needs to stop printing money and go back to Gold Reserve Yeah, you know our buying power needs to increase hence by Bitcoin Our sponsor today is brought to you by Satoshi Nakamoto by Bitcoin So as a multitude of factor you have social media which is causing mental crisis and young females like crazy Depression suicide. They're affected more like you give boys and Jonathan talks about this highly recommend reading his book the culling of the American mind You give boys internet cell phone, whatever Video games porn, right? They're not that psychologically affected per se right girls girls are the worst when it comes to social creatures girls women They're It's a hierarchical battle between females, right? How does how do I what's the first of all? It's what what's it in it for me second of all? How do I look? From the perception to my other females, right? So they're always comparing compare compare and they ridicule each other extremely, you know boys We have a different way of settling differences, right and it's done, right? I probably won't talk. I might man. I've been a million fights.  They're not physical per se At least majority let's say 99% so their thing is more chronic.   Yeah, like crazy man I get hit like almost once a day when like oh oops run a red and So like any tool the tools and Nate it doesn't have like sentient intelligence, right? Right, so you have these social media platforms, whatever you name it and it's not like us saying bye-bye social media. I think It can be used for good, right like look what we're doing right now a lot of good can come out of it However, I think we have to start a very young age of understanding There's a time and a place for things. There's a context for things and I think the education needs to start from an early age Of how to use these tools better, you know, that's one aspect of society that needs to change Second aspect of society that needs to change specifically relates to males young males Back in the day you can even view right now with hunters and certain hunters and gather even certain cultures They still have a right of way a passage where there is a psychological trigger Is a trigger of a boy turning into a man? It can be something so simple as a father passing his rifle or a father spending time in a you know Two-day camping trip where they go through an extreme Adventure or experience and the father gives the son something it can be even like whatever a sim a symbolic gift That moment there's a psychological trigger females they naturally By nature are given a psychological trigger They menstruate right we don't Right, and so you that's we see a lot of young angry men today They're still boys and men's bodies They've never they've never had that psychological evolution to have responsibility And it's a multitude of different factors, you know The father's not really in their life doesn't mean he's not there, but he's not part of a part of the family number two Number two you have the fact of And this Jonathan hate to talks about this is the advent of helicopter parents Right will make everything easy for you. So how does that benefit anybody anywhere? You want them to? It's like a puzzle learn the skill fail, you know feelings going to be very normal in life, right get back up learn Enjoy the process don't enjoy the incentive everybody wins now man. It's fun.  Give me a break. How's that training society to be better? Right, it's not it's not. No, it's not So, okay, so I guess unpack you to a certain degree the the social media thing I Do I guess I want to disagree to a certain I think I think it's rather just like it just is Social media is just a tool that's just there it might amplify some of the things well, obviously amplifies a ton of the things but But the relationships.  It's all everybody's depressed down stuff and it's like yeah, but do you think it's Do you think it the fact that you didn't notice oppression? Maybe the the fact that there is actually more depression Well, see that's that's like I grew up with no social media. I was probably the last generation. I'm maybe five So I'm 34 35 right And so I didn't get I didn't get like a smartphone until I was like Like 22 20 like I was past my high my you know teenage years.     You know what I mean You have all these psychological social pressures Building up in you and this happening subconsciously like I was never exposed to that ever I would just I wasn't aware of anybody else Doing anything I was just in the moment my whole generation. Well, you were aware of like Celebrities and stars and things. Yeah, but it wasn't 24-7.  Is that healthy? No, no, it's not healthy, but we I think we tend to do a lot of things in our teens and 20s that aren't healthy bro, bro And so that's a whole different thing where this I've done too much. I know me too way too much This the stuff I was doing at 16. I mean all I can say is I'm so glad people couldn't just take pictures and post it That's I'm so happy.  Oh God Imagine if you were looking at my bio today before like I don't even know if you should come on the show man It's crazy, right and so that's different, right that's totally different, but I Don't know I like So there's bad things to it, right again. It's gray all of this is but this idea that it's What created this sort of like depressed generation?  That's for sure Right, I mean and it existed as a thing But again this goes back to me where I was like we we are wealthier We're freer to do things we we we travel like people didn't travel the way we travel You know what I mean? Like it's just all the time like either like my daughter or her friends are just like We were in France. We were in Spain. We were in again. It's just so not a thing anymore I mean it when I was in grade nine It was like if somebody was ever going to like Winnipeg or Vancouver.  Not just like oh, wow, that's where you went for the weekend Yeah, of course cool. It that's that's different That's really different and it does give us this freedom. It allows us or enables us to To I mean not just contemplate things because obviously we're checking Instagram all the time We're not contemplating but it does I think as a society Give us more freedom to stop and so for me to stop as a parent and actually Give a shit about like how my daughter might be feeling or thinking which not that my parents didn't care Of course they did but they never stopped and asked like it just wasn't a thing and nobody nobody's like Maybe you should go see a therapist.  That's just how are you going and right? But I'm saying that I think that is afforded to me because of the Lifestyle that things around me have allowed me to live right the internet as it is being able to run a podcast and like Not have to work that much is is not a thing that happened 20 years ago. No, it's it's a it's a luxury beyond a luxury, right? It's like zero point zero zero zero one percent of the world right and but I mean to me that like so There's the grit and the loss of grit and that's terrible. That's a thing that we do need to sort of analyze But I do think that it's not all bad. I think that there's a lot of good things coming out of it I think Us hopefully is like a human race will come out better and will be more evolved in this process I think so like there's a buddha saying it is as it should be, you know like a plot like a passing cloud it comes and goes right you You know, it's like Like the butterfly effect you look back in hindsight and realize well if this if that didn't happen This wouldn't happen. So like dominoes


Hello everybody, I'm Evo Rabbit. We're here on a snowy track here in a set of Corsa to do some real drive Versa all the drive drifting make sure you guys follow me on all social media which found description box below. I Realize that was in gear. Let's get to it So it's either come on and do some snow drifting I will leave the link for the track down in the description box below We're here in the night runners s14 first and then we'll go into an all-wheel drive car And see what the difference is Definitely all the drive drifting is not my forte. So probably will be better real drive.  Oh Yeah, definitely slippery Probably should not be able to be in fourth gear with this but oh You can see the snow building up on the front tire. Oh, yeah, that's slippery We got this though trying to Thought we were gonna try and wall run that snow berm People can't work away out there.  Oh Yeah, I think I need to see if there's any online sessions with this This track or make myself an online session because you can just run some nice deep lines on these snow banks I don't even really need a handbrake on that. She's a way of the car Why I probably shouldn't stay in third For this little boggy Probably could have adjusted the ratio, but Close that snow berm That's a little run on that It's so weird because the front is so light. Oh What's all rotated the front is still light in the snow. There are other parts of this track It looks like there might be no no. All right. We got to do a snowman tab at some point today The definitely a real drive is very slow and Surprisingly very controllable with this car. I'm not sure What the actual Grip level is on this track, but we're digging into that snow berm. Do you think we don't have a rear bumper? Because otherwise it would have already been gone So not sure what the grip level is on this track, but I'll leave the link down in the description box below for the track Yep, there's definitely some loss of grip there in the front We're gonna pull out some Subaru to see if we can't do some all-wheel drive slides Probably not gonna involve which is gonna be involving a lot more In-out steering discipline, but I'm actually very surprised how well we're all running this S14 Rippin red line what gives a little too low But we're getting there now snowman tap.  Oh boy. I can already tell this is gonna be a little bit interesting. Let's see. Oh Yeah, there's gonna be a lot of turning into the drifts, so we're gonna full set you can let me know down in the comments which You prefer obviously, it's probably be the real oh, yeah. Oh, man. Oh Definitely not as smooth on a zero steer Actually surprisingly not doing as bad as I thought you are kind of bounce a red line. No, oh Pick up the back Playing forward to save itself there So I'm not sure really what the grip levels this has no grip You can tell we're doing a lot of Back and forth with the wheel That is all-wheel-drive. This is like every Subaru owners fantasy when the First snowfall hits and now one of those I probably shouldn't have pulled a handbrake on that it probably should have just gone up there Yeah, it's a lot of turn in with all-wheel-drive Yep. This thing does not really want to get sideways. I mean, I guess it's testament to The brew performance in this note. Nope. Well, oh geez. Oh my gosh. So I'm definitely obviously better drifting in Rural drive than I am all-wheel-drive Because do you really consider this drifting or just power sliding? But I think we're kind of getting a hang of it now kind of just turn into it Use the brace a little bit. Oh We're gonna slide to the berm So let me note down to the guidance which one you obviously prefer probably gonna be the real drive But go in all the dry slides kind of fun Maybe we should pull out a rally car that might have snow tires and see how that car does. Oh I think I may have a really close no tears. Let's check. Oh Hi crowd So this car just has rally tires. Oh, it's so sliding. Oh, no Yep, sliding this car's rally tires, but I don't know how it's gonna help us Other than making it really grippy Actually, maybe it's just grippier No off the wall Really turn in slide. I mean that that was kind of that was kind of cool. Nope I mean, we're someone getting it. No, we're not Oh snow berm pick it up So what do you guys do here on set of course a little snow fun having a little fun On the new snow track like I said, I'll leave the link down the description box below. You can get this track on Boston. Oh Make sure you follow me on all social media knowledge found in the description box below as always that thing guys are coming back. I'm watching We've all rabbit I'll see you guys on the track. Oh, I think we got it. No. Yep. Yeah, we got that one our transition Nope off track


Good morning. Good afternoon. Good evening and welcome to the very special mini series that we are doing here with the call for code for racial justice team. I'm Chris short host for the most of red hat live streaming and I am joined by some of my friends over at IBM. To talk about the project take two. Demi, please introduce the topic of discussion today, please. Thank you so much. Thanks again for having us here again, Chris. Always a pleasure having or being here on your show. So today I have the take two team here with me as well and we're going to get a little bit into what take two is pretty soon. Before we get started, I just want to give a, you know, a quick intro to anyone who's not familiar with call for code for racial justice. If you've not been tuning into this OpenShift TV series, just want to give you just like an overview of what call for code for racial justice is, and what call for code is. So call for code for racial justice is a component of call for code. And we'll get into that shortly. Just again, just our speakers who are going to be speaking today, Joanna, Naoki, Anna and Nagma will be talking pretty soon. Just after I give this intro on call for code. And we have a few additional members team members here as well. So many people have been participating in this project. From the beginning and there are some of them are still currently working on it and this list is continuing to grow. So if you see us in a few months, the list will be even longer than this. We have lots of people joining the community and participating as you as you'll see, we also have a lot of different roles that are available for people to contribute to as part of take two as well. So getting back to call for code call for code is essentially one of the world's largest tech for good initiative of its kind so essentially we have a global challenge every year where developers and non developers can come together and design projects that are solving specific social issues. So we've done a lot of different topics. So we've done natural disasters, climate change, COVID-19. And in 2020 we had a spot challenge for racial justice. And out of the spot challenge racial justice emerge call for code for racial justice. And now we have seven offerings that are related to this so call for code for racial justice. Emerge in 2020 as you might know, there are a lot of things happening in the US specifically around race relations and there was a bit of a like a social and racial reckoning. In regards to the killings of specific unarmed black citizens in the United States so IBMers within who are interested in doing something about this issue. They came together and they decided to do a spot challenge around a call for code so essentially they wanted to do something with them they could feel like they were giving back and contributing to eliminating systemic racism. So, out of that emerge these three pillars, police and judicial reform and accountability, diverse representation and policy and legislation reform. So during that time, we were able to create solutions and create projects that aim to address each of these issues. And actually, funny enough, I had the pleasure of working with diverse representation at the time. I was supporting that pillar so I worked with another product manager Ian, who was leading take take two at the time, and a few other projects so. And we'll talk a little bit more about take two shortly but these were the three main pillars that we had as a part of call for code for racial justice. And just a timeline like it's only been a little over a year at this point, since the launch of call for racial justice so was launched last year in Juneteenth in June of 2020 with a spot challenge. We had a lot of different participants who were involved. 500 volunteers globally we had distinguished engineers master inventors. As I mentioned we created seven open source solutions. And now we have a backlog of about 20 solution solution building blocks that can be used for creating other open source projects. And then we launched call for code for racial justice and externalize five of these solutions with the Linux foundation. And we're able to externalize an additional two of them of in this year, and we have a really wide variety of things within our tech stack so if you're interested in Python, you're a front end developer back end developer the different ways for you to get involved with our solutions here today and today as I mentioned before we're talking about take two. So I'll let the team take it away to tell you a little bit more about their work. Thanks, Demi. So I'll take us off. So, like Demi mentioned, when we were presented with the call for code for racial justice challenge. The problem statement that our team wanted to focus on was that bias can be learned and perpetuated in different ways, not through societal beliefs and misrepresentation ignorance. And ultimately this can lead to inequitable outcomes and a lot of times what happens is that this is something that's unconscious that people don't even realize that they are doing or perpetuating. And so we thought that this would be an interesting problem to tackle and look into deeper and see what we could do to help. If you go to the next slide, Demi. So, in particularly, we wanted to take a look at language right so I love this statement by our very own Dale Davis Jones and Humphrey from IBM, that words really they shape our worldview, how we regard others, and how we make others feel and so language is just such a powerful part of society, culture, everything that we do. And so we saw that there was this opportunity that we as a team could potentially address this, the issues that could be perpetuated via language, racially bias and mitigate it. And so, after the murder of George Floyd, you know there was a lot of scrutiny that was being said in the media, how it was being said, why there was a racial bias persistent in it, and there's lots of educational opportunities. And, you know, people were just really sharing this wealth of knowledge and background as to where the stereotypes were kind of being perpetuated, and, you know, pointing out social media posts news articles. And if you think about it, we're really all exposed to media news, fake news on an hourly, like basis. And so it's inherent in everything that we read and we want to be able to mitigate the perpetuation of these hurtful ideas of biases. And our team, we actually came together because we were often humbled by those who are sharing the background and the use of certain words and phrases and we thought I need to even educate ourselves and bring awareness to question our own biases in any content that we've created or or consumed. And so, you know, all the headlines that you're seeing kind of highlight that other companies and organizations that people were all kind of thinking about this. And so, some of you may be aware of these, these movements that have been happening for the removal of racially bias or insensitive language from different products, services, etc. And so, you know, we think it's just so powerful to understand the background and the words of the phrases that we choose to say, as well as continue to say. And so we really operated under the premise that awareness is key, and that we believe that bringing awareness to one language is racially biased and why would help mitigate content, content that is being created from people just not realizing or knowing that what they're saying is consistent racial bias, and therefore it can minimize bias that's perpetuating via the content that they're creating, and then ultimately reduce the offensive and harmful content that's out there. Yeah, so did you guys notice any or we've seen any work that talks about maybe the other different strata of types of biases, like in terms of, you know, for instance, like what someone says in social media versus a news publication just in terms of the effect that it might have, or in the context or the construct of that, or is there anything that you guys know about how that might differ from different in different contexts essentially. So, from what at least what I think I noticed was that I felt like in social media, there was a lot of like people emulating things that they thought were funny, like just out of like humor. And I think they didn't, they were, they thought it was lighthearted and it wasn't really offensive, but people were taking offense versus I think news articles were more so like, I don't know if they recognize that the way that they were describing different populations was, was just different and harmful for like people who are in the black population versus like how they were describing crime, for example. I felt like in social media that it was more coming from like a humorous standpoint versus like in the media, I don't know like for some reason, just the way that they were describing was, was not humorous but just different. I don't know if anyone else has anything to say on that. Comment briefly on that. So I think it would be an interesting thing, you know, to consider a machine learning part of the solution, if it can take advantage of that sort of, you know, broad contextual information to boost the accuracy of bias detection. But maybe I'll say more about that. Okay, cool. Looking forward to your section. All right. So moving on. Okay, so we initially began with the idea to build a tool that would detect bias and content. But we quickly realized that at the time at least there was no publicly available data set for us to leverage. And so, you know, this kind of made sense. Language is incredibly subjective. And while it is more straightforward to identify some overt forms of racial bias, it's a lot harder to capture the more subtle form. So kind of speak to what we just talked about within like the different contexts like social media versus like news articles, gaming chat rooms. And so, you know, this is really where our Chrome extension, our browser extension came into play. We wanted to see if there could be a way to maybe crowdsource this data via trusted contributors. And so we wanted to our goal was to really provide a trusted community of members with a tool to flag content that they were seeing consisted of racial bias and provide a mechanism for them to explain why something was racial bias racially consisted of racial bias. And so this would feed into our machine learning model, which Naomi will go into further detail on. And ultimately would serve as a data to help our machine learning model classify when phrases or expressions within certain context, maybe racially bias. And ultimately, this would then feed into our API, which Johanna will go into a little bit more detail that we wanted users to be able to leverage to check their content to see if it consists of racial bias and therefore be able to feel empowered to know and then make a decision as to whether they wanted to continue using that language or maybe there was a different way to get across the point that they were trying to make. And to be clear, we understand that this is an extremely complicated task that's dependent on context, you know, we don't really know what the ground truth is here. But we do think that we have a great starting point, at least for these different concepts and ideas. And so that's kind of that's kind of an overview of our solution. Very cool. Yeah, you said you had a Chrome extension with trusted people using it. How did you make that happen. Right. Like, are you going to get into that. If I'm asking too early just tell me. No, I can I can definitely, or, you know, others please jump in but so something actually something that we came across was we wanted to balance giving power to the community to flag content while also recognizing that there are bad actors and that that we need to make sure that they're credible people marking this and that people have the correct or, you know, the background to be able to understand when something is racially biased and so that's that's the reason why we're calling out trusted leaders. And so we are still kind of in the process of identifying what that looks like or who that is and our small team of original challenge. You know, when we were just started off it was a challenge that we're not sure if we're even the people to make that determination. We kind of want to talk to experts to help facilitate that and understand what that looks like but that's just a little bit of background on that. Thank you. So I will pass it over now to Johanna to talk a little bit about our solution architecture. Thanks. So hopefully everyone can hear me. So my name is Joe and I worked as a developer on this really fun project. So the solution at the moment and it's it's definitely not the final the final solution. But it's basically built up of three components and our repos are split into three to match the components that go along with this architecture. Just now I mentioned one of the issues we found at the beginning was not having a data set that that contain that more subtle form of racial bias. So it's very easy to find toxic language data sets or racial slur data sets they do exist. And we can bring those into our solution. And we have to use those to sort of for training and things like that training our models. What we found more difficult to find was things like. And like when I was talking about news articles that might be more heavily making it look like young black males are more heavily engaged in crime than the rest of the population. It's more difficult to to identify and there's not that many data sets that that that kind of contain that information. And so we so we decided okay let's create something so that someone could privately if they're browsing because people were already doing it on Instagram on Twitter they were already picking out a piece of content from someone's website or from the news and saying hey you know this is not okay. And this is why so we thought if we could give them the mechanism where they can actually do that via a private tool so it's it's not something that anyone else can see it's just privately highlighted. They go into their browser they can be on any any web page they want they highlight the word or a whole sentence or paragraph whatever it is. And that data is then via the API posted into a database a backend database now in our github kind of get up and running example that databases a couch DB instance. The overall plan for the project long term is for the community to own the data set via some sort of organization who are kind of impartial. We obviously someone who's kind of neutral ground for something like set you know to to kind of because it it would it would basically be like this is the definition of racial bias. Some people might interpret it that way so it needs to be kind of owned by the community. API then calls out also to them the machine learning model. So if someone so basically at the moment we have just a very simple text editor which we'd also like to turn into a Chrome extension. At the moment what happens is on the client side they can actually type content so if they're thinking of writing an article or posting something social media they can type what they want in the text editor. It makes a call out to our machine learning model which then will highlight any parts of that text or sentence that it feels might contain what doesn't feel that it finds might contain racial bias. And then it will actually explain why it thinks that it's very clever machine learning model why it's suggesting that you might want to reword. We've also talked about offering alternative words and two things that people are using and this could be anything from social media posts all the way to. To code that someone's creating online. So I'll just share my screen and then I'll show very quickly how it works. Hopefully it hasn't logged me out. So just to recap we've got three GitHub repos this is the repo for the API. And in here you'll find everything the information about what what we collect from the Chrome extension so. The categories that we define so I'll go into that when I show it and then a getting started guide on how to get up and running. And today it is not running on OpenShift but we have run it on OpenShift. When we were building the solution as part of the code this is just running on my on my normal machine but you can run it in a in a cloud native environment. We've got the. So this is the web API. We've also got the data science repo. And then we've got a repo for the Chrome extension. So the way it works is we've got this API running. When when you get the solution up and running and there's a number of different endpoints and they're used for various things and that's all explained in the docs but basically. You can get the marks that are in the database. You can post to the database which is what happens when if you post the mark that's what happens when someone selects and text in the Chrome extension. What I'll do is I'll just show the Chrome extension. So in order to be impartial at this moment I've just got an article about lettuce because I. I don't want to say what I think is racially biased or not. But basically the user can toggle on the cursor once they're logged in. And this will allow them to choose any words or phrases. So if I thought addition was a racially biased term. Oh, I've done that wrong. It's a bit slow. Just reload it's gone a bit slow. I'm sure you streaming video has nothing to do with it. Okay, let's just pick another one. Okay, and then your user once they've highlighted they'll be presented with six categories which is our initial idea was to have a category of racial bias we've also discussed just having a kind of Boolean so yes or no it does or it doesn't. We're still kind of, I'd say figuring this one out. But essentially the user can select. They can also. Again it might just be really slow, but they can also change a category if they want so if I had selected stereotyping I can change it. I can also delete a mark which will, which will basically and it calls all those endpoints that I showed earlier in the API. What then happens is so that's basically the Chrome extension and you can see that it needs some UI design work because it's extremely basic and actually what was quite cool about this is we use an already existing just general highlighter tool that existed for browsers. And we just took the, it was just like a highlighter tool that highlights stuff in yellow, yellow pen, and we use that open source project, and then kind of made it our own in order to suit this project which was a really nice way of using something that's already out there in the source world and kind of modifying it to our own kind of needs. So, before you leave that page, I'll just carry this a little bit more about the Chrome extension. So, I guess it's kind of disappeared but it has something about copying what happens when you do that. Copy all. Yeah, I guess remove all. What is copy? Yeah, so I think copy will take all the all the text that you've highlighted and you can probably paste it somewhere else like in a text editor if you wanted to something like that and removal will just remove all of your. All of your marks that you've made. There's lots of work to do on this Chrome extension. So, I think that there's a lot if you look in the Chrome extension repo you'll find a whole host of issues that some of us have raised that need to be worked on. Nice so I'm curious here is it like for centuries and human the highlights is it tell you what the racial biases are just told you that's highlighted. So at the moment it just tells you what's highlighted. Obviously because this is this is the side where people are capturing that data so it wouldn't know what the racial bias is yet. And we want to add like a space where they can not only highlight but then fill in some information about why they've highlighted it, and that information could then be used by the machine learning model as well. That's all stuff that we kind of haven't got around to. Okay, but it's a good idea. So, on the other side of the kind of API is is our text editor. And for now I don't have it hooked up to a machine learning model I just have it hooked up straight to the database I'm using but the general idea is I type in a sentence in the text editor. And it makes a call out to the machine learning model and it would say, you know, you've got this word, and we found out that we think it's a racial slur. And here's, here's the definition of what that is, and here's any additional information which might be things like you could, you could use this word instead. And that is pretty much it. I've obviously got my database running in the background but this is sort of not that interesting because like I said, we really want this to be a community own data set, and not something that one person just spins up on their own. There could be scenarios where companies want to use their own data for a specific reason so I know IBM, they have a set list of words that they would like that people should not use. We have done a project with an IBM where where before they post content onto their IBM developer website, they use our tool to scan the content of the of the new of the kind of article, and flag any words that were not appropriate to use, and then send a message back to the developer who wrote it and so you need to, you need to maybe reread the content and maybe change some of these things. So, so we have, we have, we have deployed it within IBM on like a trial project. And yeah, that's about it. I don't know if there's anything else. I think there's one more slide that I probably need to talk to you after before no key. Which is about data authentication so that obviously no key will go into data authentication from a machine learning perspective but there's some things that we've identified that we would potentially do to mitigate malicious actors or yeah or unreliable data. One thing I forgot to say is that the data is the user is obviously authenticated before they use the Chrome extension. They're up using one of IBM, the IBM app ID service. Initially we had the idea that we would ideally want anyone to be able to contribute but I think the way it's moving now I think it's probably was the wrong, the wrong choice. However, there could still be bad actors, even if you've gone through a very rigorous process. So, and also we want to kind of build up some consensus around the data that we get. So we've, we haven't implemented this yet but these are kind of some mock-ups of the kind of thing we want to do and this is very typical of something like what Google Translate does just asking the user while they're highlighting text, and then pop up to say, you know, click on the words that you feel like are racial slurs so that maybe this data is already in the database but we just want to verify it and try and build up that credibility. Same for maybe serving them a sentence and saying, you know, which, which category of these do you feel is most appropriate just so we can kind of build that that verification into into the process. So it could help with that, like many things in in in UI in the UI space. And so I will now hand over to Noki who will talk more about machine learning. Awesome. Okay, thanks, Joe. Next slide please. Yeah, so this is sort of a one slide depiction of our roadmap, if you will, or kind of vision, cautiously optimistic vision of where we want to go in the machine learning component. There's essentially a list of different versions of machine learning component of with with increasing sophistication, I guess, and starting from the left version zero will be sort of a normal machine learning version where you do in the database or dictionary version one is is a classical version where you can train a classifier that can detect what sort of specials or maybe long, you know, expressions and sentences and paragraphs are biased or not from labeled data. Version two is is the most next, you know, sophistication of that where you leverage the cutting edge deep learning technology to do this in sequential context. And the version one has been implemented in the repo and there's ongoing work on version two. But the rest of the versions actually are not implemented yet. Because it's in the future tense. Version three, we call the AIX what explainable AI model is a variation of the previous two, where it not only can flag a whole, you know, paragraph or whatever as bias can also point to specific or expression within it that are responsible for that, you know, bias or not judgment. Version four is one that tries to address the markers credibility question that Joe was, you know, talking about another mechanism to address, where we try to learn the credibility of the markers in a crowdsourcing context, and and use that information to build better and better machine learning models. Version five is an extension of that where you use that credibility information to actually actively choose and seek labeled data from the markers that are more credible, and about the questions that they, you know, the model models, we want to know about. So that's just sort of the summary. And in the next couple of charts, I will go into a little more detail about two of these versions, version one, sorry, yeah, version one and version four. Next slide please. Yeah, so just a question here before we move on. Can you explain just for the general audience, what is meant by broad context versus sequential context. Yeah, so maybe I shouldn't say broad but it in context so in in Joe's demo, she happened to be picking, you know, words to label, but in general you could just label a whole context like a paragraph. So this is trying to basically that the version one is going to classify whole, you know, paragraphs, or whatever into bias versus non bias and sequential means it really is paying detailed attention to the sequential context of, you know, in a sentence structure and that that's something that we need deep learning technology for. I mean, hard in my understanding or lack there of machine learning in general like how hard is it to train these models, right like this has to be a very challenging model to train I feel like. Yeah, yeah, good question. I think maybe I will say more about what we have done concretely and I think it will come out. It's not done by any done or complete we have a lot more to do so. So this one is the first version that we have implemented and it's using relatively classic machine learning classification on the technology like support vector machine and I base classifier combined with what we call bag words presentation of texts. So the picture on the right is sort of illustrating how this works, sentences coming as data, and they're labeled in this case, for simplicity biased or unbiased. And then these sentences or longer, transforming to something representation for the bag of words, she's essentially a vector of frequencies of many many words. So these sentences are mapped into very high dimensional numerical vector space, like, you know, not necessarily zeroes and ones but often zeroes and ones.  So what we do on a bunch of training data, label training. And once you have that classifier or the model, you can apply it on a new sentence or paragraph in this example. It's a master replica, which is also transformed to bag words and then the classifier is applied to that, and it comes up with the judgment or biased or unbiased. So that's how it works. And it's been implemented using scikit learn library and that you can find it in our report. So that's our first version. If there's a question I'd like to move to the next one, if you can go to the next slide. Just want there's one question check, could this solution be used for other languages, or is that something that's a map. That's a good. That's a good point that one of the advantages of, you know, machine learning based natural language type methods is that you train it with data so if you train it with English, they will learn about German. And one thing to know, I think our solution right now is primarily is English and also US, I think we're very, we've been kind of US centric and so that's definitely something on that we've been trying to, you know, consider moving forward. Considering different cultures, different languages and all of that though. Yeah, yeah, yeah, there's a lot more that you should and you can do about them. It doesn't all come, you know, automatically, but right, but it's basically extendable. So version four that we call ensemble consensus learning. This is our vision as an or an attempt to address the issue of there being unreliable markers or even adversarial markers in in crowdsourcing context. So the reasons that Joe stated, we believe that cross crowdsourcing is very important, and that's the way to go. But it's also challenging if you're collecting data from, you know, thousands of anonymous or people from all over, you may not necessarily have all the reliable people. But how can you, you know, how can you try to detect that and and learn from or leverage that information. Here's this here's an idea. We leverage a general idea called ensemble. That's a notion where you have a number of many potentially many machine learning models or methods. And and basically you make judgment using the ensemble. That means as shown in the question on the top, basically doing average. You do like a weighted voting by all of the machine learners in your ensemble and make a sort of an average judgment. So that's one thing about ensemble. The other thing about ensemble learning is that you can also learn the credibility of those models by updating their weights credibility weights, and you do that by this second equation where basically it's cutting up the weight of a model that makes a mistake. So every every time it makes a mistake compared to the ground truth label, it cuts, for example, cuts the weight by half. So it actually you can show that it quickly learns and zooms into to the good set of models. So this is the general idea of our ensemble learning, but we apply this in our context and there are a couple of things that we need to do. The first is that for those models, we don't really want to have just the markers if you have 1000 markers and train a model for each marker, you don't have enough data to form a single marker to create a good model. So we instead create many many models, but you train each one with data from a subset auditory subset of the markets. So that's sort of how it's depicted in picture. And then you serve you feed random subset of them, the all of the markers into different models, you can have hundreds of models. So that's one way that one way that differs from the general ensemble learning. The other difference is that we don't really know the ground truth for the same for the very reason that some of the markers are actually unreliable. So how do we know when to learn that one of the models made a mistake. So that's where we use the consensus, meaning the rated average prediction of the current ensemble you treat as as if it was the ground truth. And then you, you penalize those models that deviate from that. So that's what we call it ensemble consensus learning. Now, so with some assumptions about the reasonableness of the ensemble, you can show that you can hope to show that this also will quickly converge and and will quickly zoom into those models that are built with credible subsets of credible markers. So this is a, this is an idea that we would like to take forward, but sort of abstract. So if you can go to the next slide, I would like in the next couple slides, I'd like to show some concrete work that we have done. So much of this was done by Pritika, who can be presenting with us today. But what we did was, rather than sort of, you know, doing all this in abstract, we wanted to do it in concretely. So this dataset for the JITSO dataset from the Kaggle competition. It's a decent dataset about racial bias expressions. The dataset has 1.8 million observations, but it's not just about race or not just about, you know, black or Asian. As it's shown in the histogram on the left, there are many different kinds of biases that are present in the data. But by and large, you know, building machine learning models to learn these biases. So that's, that's a similar kind of modeling exercise, you know, irrespective of the exact type of, you know, bias we're talking about. So this is a very useful dataset. Another interesting thing is if you look at, so there is a column in the data, which stands for severely toxic or not. Well now we're using that as the, you know, target to predict. So we're trying to judge whether something is toxic or not. Interestingly, the sentences in data, if you look at the presence of obvious, obviously offensive terms like the F word or the N word, you can see this monotonic increase in toxicity as a function of the frequency of those terms. If you look at some more, for example, like big or dog, it's not that that simple. So there's a lot more that you need to do to learn, rather than just counting frequencies of, you know, these bits. If you can go to the next slide. This slide is summarizing the results we have obtained thus far with this data with the first version that I talked about support vector machine version. There's a bit of an extension that we did call TFIDF that's kind of variation of the bag of words. We're trying to detail on that one. But so far, we've obtained the accuracy figure is around 80%. It's not satisfactory. So this sort of in part answers your question press that it is a challenging problem and we do need to leverage, you know, more sophisticated cutting edge methods to improve. But it's, it's, it's not a bad start. We, you know, awesome. Yeah. Yeah. And there's some this sort of spells out the steps of this involved in this modeling like cleaning up the text or removing stoppers. And dealing with the embossed data by down sampling the non toxic data and up sampling or the toxic ones and so forth. And, and we use SGD is a method for training support vector machine models, and we're using a specific, you know, version of the parameters with that. If you can go to the next slide. There's some takeaway from from this exercise. We've done both support vector machine and knife base. And as you can see, my base is getting about 75% accuracy. So even with this kind of classical machine learning technologies, some are better than others and and you know, you can hope to keep improving. Deep learning, for example, I think will improve significantly one of the indications that the model as of now is still not satisfactory. Is this is the fact that it's a little bit technical but the optimal loss function of the model is something for the modified who bear loss, which means that there are outliers in the data with, which means also that with the present in the data in the sentences. It's not enough to be making reasonable classification for for some of those ones. And so we expect that, you know, maybe it's a sequential context or maybe it's some other kind of contextual information that that's lacking in the data. That you would need to be able to make better judgment of those. So those are some takeaway lessons. Another comment is that this data comes with, as I mentioned these different kinds of discrimination like against Asian or against black wiper, we're not necessarily trying to predict those lack those categories but they could be useful as features because the type of offensive expressions might depend on those categories and it could be helpful in defining the models. Another thing is that this data is it comes with the marker ID column. So you do know which are which sentences or which examples come from a particular marker, even though we don't know their identities. So we could actually try to do this version for the ensemble consensus learning where you're trying to learn the credibility of markers. That's something we haven't done, but this data set actually is rich enough for us to do something like that. But eventually we want to move to crowd sourcing where you can choose to collect more information, maybe demographic and other kinds of contextual information about the markers and so forth and also do selective, you know, sampling of all the active learning. That's not really possible with the existing data set. So we are, you know, I'm supposed to move to the crowd sourcing mode. Sorry, I ran out kind of long but this is it for the machine learning component. Are there any other questions? Yeah, I had some questions. Can you talk a little bit of just about the computation is required for this, especially if you're moving to deep learning so how can someone, how easy is it for someone to do this locally on their computer. What do you guys thought about that? Yeah, so for the classic machine learning models that we've done, I mean that it's easy to do like on my laptop and training takes maybe, you know, seconds. So that's not a problem. But deep learning, if you really, I think maybe at this level it wasn't that bad. I'd love to check with Ritika. She probably did it on her own laptop but as this data sizing increases and you want to train, you know, for a longer period of time and so forth, you may want to leverage GPUs and you know, going to a higher, more capable setup but I think you could also do that with cloud clusters. Okay. It doesn't have to be IBM cloud but IBM cloud would provide such capabilities and you can seamlessly train these models with no particular difficulty problem. Nice. And what's the volume of data that you think you might need in terms of crowd sourcing? So like just a call to action to the community. How much more data do you guys think you need for your next phase? I don't know. It's difficult to say how much. I mean this data set has 1.8 million which is decent amount but it doesn't, it's not restricted to the type of racial bias that we're interested in. That's less. But with crowd sourcing, we have the ability to select the markers and select the data that we want so that would reduce the amount of data that we need. But generally, I mean hundreds of thousands would be. Okay. Good to know. I actually have a question. So I know we've talked about context and you know where we're kind of flagging and I know in our solution we've talked about like including where the data is coming from or like what platform we're on. Did you see that that was a field in the Kaggle data set? That's a good question. I doubt it. I haven't checked thoroughly but I'm doubting it. Yes, that's an example of the type of digital information we would like to collect. And sorry, maybe I can jump in there as well. So obviously we've built into capture where data comes from but I think to Demi's point about how much data do we need. I don't know what no key thoughts are but even when we've collected enough to train an initial machine learning model, I think racial bias is something that what is racially bias changes over time. So it's something that we'd want to keep updating and keep iteratively improving over time, also so that we can understand how definition of racial bias might have changed over time, depending on political events, different types of situations that unfold. So I think it's something that we obviously we need an initial set of data but we want to keep that process going and improving and things like that. Yeah, that's important that we models are dynamic and able to adapt to changes in society. Okay, maybe we should move on to the next segment. Yes, so here are some of the immediate applications of takes to that we're working towards a text based content like social media platforms blogs. But there's also future applications that we would like to take that we'd like to have take to be a part of such as in the gaming industry and of course in other languages. And we're also actually working with different partners to realize and co create a vision to grow take to even further. So here I would just like to highlight where we are headed. We have kicked off our community meetings and these are some of the things we're focusing on right now, finding a home for our data updating the US of API browser extension, as well as the training model models. Next slide. And so here's where we need your help. As you saw we have set up the foundation for take to but even with the current functionality, along with a great team of contributors that continues to grow we're still looking for people that can help. This is a complex project, a complex problem we're seeking to solve. And excuse me, a complex problem we're seeking to solve. And so any contributions we can get would be really appreciated, we want to make it as impactful as it can be. So we are looking for various, various varied skillset. And there's many ways to contribute. We're looking for data hosting data scientists designers, a full range. So if you are interested, if you know of anyone else who may be interested, please check out the links that were provided in the chat, as well as listed on the next slide. And the links tell you how to get started where you can find all of our repositories and all the information you need to contribute. Thanks, Demi, go ahead to discuss the next slide. So if I could, sorry, could I just pause it? And yeah, I just wanted to say that, you know, and I listed off a bunch of the different kinds of health that we need. And just wanted to call out that while, you know, we talked a lot about like the technicalities of our solution. But I think we also wanted to call out that because it's a socio-technical solution, we really also need people who are experts in like linguistics and, you know, political science and media and all of that.  So technical, social, whatever it is, I think we're really kind of looking for all kinds of people in a broad, diverse community to help out. So I think that's kind of beautiful and also awesome about take two. And so just wanted to call that out. That's great. That's very awesome. So yeah, just in relation to that, we do have some opportunities for you to get involved. As I'll put in this next few slides, you can join our Slack community. You can also join us for Hacktoberfest. So we're joining Hacktoberfest, which is a month long celebration of open source contributions in October from October 1 through the 31st, and we'll be participating with call for code for racial justice, all of our projects. We participate in including take two during this celebration. So we'll be having a kickoff event on October 6, if I can Eastern, you can watch it, you can register for the event at ibm.biz slash Hacktober CC, that is case sensitive, or you can watch the replay if you're not able to catch it live there. It'll be on that same link. So and for here, you'll be able to find out more about how you can contribute to our projects, exactly how to get involved in Hacktoberfest, and just learn a lot more, whether you're technical or non technical about ways you can contribute to all of our projects going forward. And this is a last call to action here. We'd like for you to join our community. There's definitely a lot of work to be done with take two. So we'd like for you to join us. And if you would like to be a part of a community can do so by joining us through our registration page, which is ibm.biz slash OS TV 0928, which is today's date when we're filming this. And with that, you'll be able to join us on the call for code slack channel. And once you get there, they're like going to be a million slack channel. So the thing to it's important to know is that you want to join the racial justice take two channel as well as the racial justice general channel as well. And with that, thank you for joining us today. It's been really awesome having us to being here and talking to you guys about take two. Yes. This is awesome. Thank you so much for the work you're doing. Thank you so much for bringing this project to the channel. And thank you so much for sharing your work with us. It's very much needed work and I'm passionate about it. So thank you very much for doing that. Any, any other points you want to make just thoughts before we get off the air here. Other than, you know, all the stuff I dropped in chat and links and such. I think just thank you again for having us and letting us share our story and we're looking forward. Hopefully people can join us on in our project and the journey and wherever we're headed and so, yeah, thank you. That's a good growing community and it's really nice to see this effort, you know, for and so you're welcome everyone to join. Yeah, it's cool to see when we all started like as a challenge to where it's gone and where we're sort of headed. So, you know, back last June to where we're at right now is really, really awesome. It's quite an achievement and just a little over a year. I mean, it's very impressive work. Thank you. Thank you. Awesome. So thank you all for joining. Thank you audience for watching and stay safe out there folks and we'll see you soon. Bye.