Missa me!  It's like jibaba I hope you are also being blessed That kids won't go back to it We live we could, they would So why Replace That's why we are here And that's why you're requesting That's why you're requesting Those songs on Facebook Sushi Good morning also Praise the Lord This is your service. My name is Miriam Asaba and I'm with DJ Knicks. Kama kawida tunakuleta walo asani wame leta mziki, wame tuwamziki lewiki. That kawiki lenyatu jahonana utunakuleta walo asani, they come share with us their story and their journey, how they were able to write this music and also to produce that music. Kama kawida today in studio we have the lovely, the very beautiful, the very humble, the very blessed, dot of the most high. He? Shani mutia dot of the most high. Pam. And you know Pam told me this name, this other name I'm like, hey Jesus, mugu wagu, praise the Lord. Say I'm like, hey, yo karimu nyume ulemi, hey, maitia, ebuti umbe jina hengine, umbe jina yo jina li tokao api, na yaa idipi, ako zanju yaa idisi nii, Pam. Yaa. Tumbe yo. So yaa idini, Pamela gasheri kajuju, bachewsani nii, Pamgat 2-5-4. Pamgat nii, kusho tentu Pamela gasheri. Pamgat? Yaa. So biya dani menyulishin doku pronaunzi. Hey Jesus. Hey. Ni kare kameru. Ni mixed pronouns. Kare ka? Kare kameru. Kare kameru. Kare kameru. Ina manisha tu kas chana kameru. Oh. Adi hukini faini vok, hukini ambi yag li na manisha yu vasu zada jwa. Kare kameru. Kare kameru. So you're like, mingsakia, hata ni mingsakia, so I know I'm not. I'm qualified. Kare kameru. Yaa. Kare kameru to the show. Thank you, thank you. It's looking all lovely. Thank you. Yes, yes. You also look good with it. I know. Ni Gracia Godz. I know. Pasu usipanga ni Gracia Godz. Ni Godz. Ni Godz. So very good. True. Hata is Pam. Isongi ako bairakamu zangu.  Me, as far as na izakumbu, katuni li kwa naimba. Like niliya zaku imbalini kwa mdogo sana. Wow. My first music, kwa indi kwa nili kwa nili kwa class 3. Kwa indi kwa? Niki mkura kwa niya nili kwa class 3. Niki mkura kimizana kwa na matahaya onze. So, so you know ma? Yes, yes, yes. You see, you know ma penyemen fukisha. Wow. Ni Godz. You started writing in class 3 and professionally, when did you begin singing? I started recording last year. Last year in July, that's when I released my first song. Okay. Yeah. Yeah. Yeah. So baraka ni sumiangapi? Ni appeali. Batch kuna zingene, though I was in a video. Oh, okay. So it's the first song ni nisa sa ubefagana? Ikona video. It's the second one in the video. The second one in the video. Yeah. And how is it, how was it, how was it producing this video? Ini challenges. Yeah. Nili indi aze? Ini kwa challenge kuba kwa first of all, like I'm not employed, bado ni kwa shulei, I'm a student. Sure. So I'm depending on the little money that I'm getting from my parents, ya po kekman, ya ma pesaya food. Wengi na kekula, 2 apa 3 kos mil, mi na seman, nita hata lunch, mihata saapa, mi saviya video. So that's how it is. Everything is about sacrifice. Sacrifice and challenges and you're able to overcome that. So tell us more about this baraka song. What inspired the song? What made you write that, specifically that message, ya baraka? Ya, the song is inspired by the book of Jeremiah 2911. Goda na sema, akuna good plans for us. Then nikiangalia society 8 una, waziz yuku wana liya, kuna wajani yuku wana uliza God, why have you left me? Zdu kuna student aniliya hana school fees. So this is a prayer, this song is a prayer. Mi pana kumbushatu God. Iso baraka zako God na zi itaji kwa sana. Zime kawiya na zi itaji. Zita fika. In due time. In due time. Do you have any other thing, any other project you're working on or do you have any, any artist you look up to? And you like to do a collab with? Ya, definitely. Especially Masima Sika. She's just my role model, not musically peke. Even in the life she's living, her personality, I just look up to her. And also Gadyan Angel. I love his vibe. Like aneza imbangoma ikubam bekama weni yut. Napia ikubless, you know. So inna connect. Ya, inna connect. Inna your spirit. Ya, inna. So, and also Paul Clement wa nani blesana nangomazake. And Markerina also. Nice. It was a game, game weni collabo yungi kwa ni Dadyan Angel Masima Sika. Markerina. Naki na empangu. And Paul Clement. Paul Clement, we prophesy. On JC circle. We prophesy that this collab will happen one day. Yes. Well, alaku, ya, kuna wale wa tu me sema. No, saying that you're still a student. How do people, colleagues wako sasa chuwa wali receive wana receiving ya geministri ya ako? As well as music is concerned. They're so proud. They're so proud cause wako like you know we know so many people with this such talent but wana kata wana sema. Ata ni malize shule mi bini pate job.  So they're so proud of me. Ata ni kikami intervi bedo wali na mbeni wa big up. What you akabete, big shout out to you guys. Oh, mwasa, mwasa. Nasa apia kuna wale specific people. Kuna w friends wachuo, maybe outside school pia kuna watu ameksikia ministry ya ako. Ya, you can shout them out pia. Ah, nyanze, currently I'm working with the studio in nature of Vinox. Inakwa ngapale unguwaro, place in nature kongo. Vinox records, thanks for always standing by me. Te, your camera is full. It's supporting my music. To me a baleta lago. My mom pia and Kajuju apodagorechi na ja na watch. My siblings joining at Chiana. Nwale wachuo adi like kukimba wa nakubakap. I do na feel, I'm not alone there.  So everyone wanyana ni support. Ata meru my home kuna kuna empainetua genix empire. They have they have held me down all this time. Meru yote, media houses yote, Y254. Thank you guys for having my back. Kari Musa. And I'm noticed kwaesong. Uya biga fumse moja kwaesong. Uzi ta kolabo ama Yeah, it's a kolabo. Anetua G-boy. Um ni meru like he's born in Meru but not geological Meru. So I had this song from a friend of his anetua Julie Manakochi. So ni kamauliza Julie. You know G-boy is a Meru and everything I say ma yes, so ni kamauliza. Nneza ni konekko at that time nili kwa na nata kamauliza at least aneza nishi kama konu. Do you know? Nili uliza, kwen kwa ni pia kolabo manze. It's not easy.  But G-boy came through nana mo appreciate sa na kwa kumik baraka where it is. Wow. Bless the Lord. Nneha, na umzikiya kwa tufna pataze. Ani kona YouTube page. Nna also social media. Nneza zemension zote. Kuna YouTube page Palm Guts 254. Instagram Palm Guts 254. Twitter Palm Guts 254. FB ni Palm Guts na pia ni kona fan page ni toa Palm Guts 254 music. Wow. Nice. That is nice. I can't waste to drop this jam sababu. Una na ventu maipuluk marambilita tuyo and we pray that na hupuase you guys you should receive this song with love what you did to go endapale your YouTube yaka social media yaka you can interact with Hamo and of course keep requesting the music hapa. And share. And share. And share. Message ya baraka yende wa tu. Yende wa tu. Sawa, sawa. Anyway, thank you so much, Pam. Ya karikamelu. Karikamelu. Karikamelu. Karikamelu. Thank you so much. There is aniliditai kama nikuwa shulek especially high school na primary kutulikwa like atuskiyangi wa meroa kihimba wa meroa jikuimba so mi ni kasi ma ni kengakwa industry tazimani ditambulishena kwenye metu waka. Which is very nice by the way. But do you know if we don't go to a kwangiwengi kwa industry and of course we pray that mugoratangilakufu wa milangos ma dirisha and every path ay lainisha sababu ya ministry yako tawfikepale for his glory. Thank you so much for coming. Thank you for having me. If you have new music, please do come back and God bless you so much. And for the very first time here on J.C.S.A.K.O


Welcome into the fan duel. Hurry up. It's Maria Marino for fantasy sports network and Jim Sonnis of number fire is on hand. It's Super Bowl week. It's here Jim. And we have a single game slate available on fan duel just for the Super Bowl. 6 30 p.m. Eastern this Sunday on CBS, the Patriots and the Rams squaring off. I'm clearly very excited.  This segment right here will focus on the studs and we'll start with the stud Tom Brady himself. Yeah, with with with Super Bowl, it's kind of hard to not use Tom Brady and single game DFS. And I think in general my baseline assumption when it comes to a single game slate, the first question I ask is, do I want to use both quarterbacks? And I think when looking at this game, I kind of do. I like both Tom Brady and Jared golf. This game is indoors. It's projected to be pretty close with the Patriots, his two point favorites. And I think that both those things line up well for both these quarterbacks to do pretty well. So looking at Tom Brady specifically in the playoffs this year, he's had a lot of passing yards, 348 yards in the first game, 343 in the second just hasn't quite translated to fantasy points because the touchdowns have not broken his favor instead. They've mostly been rushing touchdowns and that's quite a hurt Tom Brady from a fantasy perspective, but that's not to say he can't get touchdowns. We saw him, you know, less than a month ago or about a month ago get four touchdowns against the Jets in a single game. He had three touchdowns against the Dolphins earlier than that back in December as well. So Brady can get touchdown luck on his side.  So I think it kind of comes down to the way you think the Patriots will attack this Rams defense. If you think they'll go at them with a heavy rushing attack, then I think that Sony Michelle makes a lot of sense. But my personal assumption is that they let Tom Brady do his thing because this game is indoors and projected to be pretty close. So I lean towards Tom Brady. I think that he's always a safe bet when it comes to Super Bowl DFS. So I think that he's very much worth that salary at $15,500 on FanDuel. Experience is certainly on his side. Tom Brady projected to reach over 19 fantasy points on FanDuel. Up next, the other quarterback. It's the, it's old school versus new school. And in the new school category, we got Jared Goff of the Rams. Once again, this game is projected to be close, but are you concerned at all about Goff, you know, this being his first time there? Yeah, I think that's always a legitimate concern because like if I were personally down there, I think I'd be pretty jittery. And I think that, you know, just like thinking about this from a baseline perspective, it would kind of make sense that they were nervous and obviously this Sean McVeigh's for Super Bowl two. So some concerns around that, but this, this coaching staff with Jim Fossil and Wade Phillips has a lot of experience, especially in these big games. So I still think the Rams will be prepared. And if they are prepared, this is a spot where Jared Goff could do pretty well. And I think that honestly between he and Brady, the guy with the highest true ceiling between these two guys might be Jared Goff. And the big reason for that is because Goff is throwing the ball down field more often. He has gone deep 21% of the time during the postseason, whereas Tom Brady has done so just 13% of the time. It's a pretty big deviation. And what that does is it gives Goff a lot of upside from a yardage perspective. Looking at this specific game last week, when they were in the in the conference championship, Goff couldn't hear because he was dealing with the crowd at the Super Dome. But I don't think that will be as big of an issue as they're down in Atlanta, Atlanta fans, probably not big fans of the Patriots. And in general, the Super Bowl is not going to be as engaged of a crowd as we have down in New Orleans, especially. So from that perspective, Goff should get an upgrade. I think that even, you know, we look at Goff since Cooper Kup got hurt. We kind of look at the fantasy scoring being down, but he did still score 24 points on FanDuel against the 49ers back in week 17. He's playing indoors. We've seen him play really well in domes this year, especially in those two games against the Saints. So I think that Jared Goff has pretty good upside. I think he'll be on fewer rosters than Tom Brady is on. So I think that's from a tournament perspective for this weekend. Jared Goff's a pretty fun play. I will use both in the same line up for short, because I think that there is enough value to do so. But I think that Jared Goff, maybe my preferred tournament option just because he should be on fewer rosters and has some pretty spicy upside. The two starting quarterbacks in this game really couldn't be more different as far as experience level and what they bring. But their projections are very comparable with Goff looking to reach about 18 and a half fantasy points on FanDuel and two touchdowns in the game. We'll see which one will have the better showing. I think it's going to be really close. But let's turn our attention to another stud. This one, um, maybe like fantasy MVP for most of the season, Todd Gurley of the Rams, except all you were hearing after the championship game was where was Todd Gurley? So should we be concerned? My bankroll was very concerned and was wondering where Todd Gurley was during the championship round as well, because it was it was it was not good. But I think when you look at the things that Todd Gurley has said, the things that Sean McVeigh has said, they've all said that it's not injury related. I don't think that Todd Gurley has still heard. It just seemed like he was rusty in that game and didn't play very well. So Sean McVeigh said, Hey, we're going to ride CJ Anderson. He's playing pretty well. But now Gurley has two weeks knock off that rust. And Sean McVeigh has come out and said, we're going to use Todd Gurley a lot in this game.  They'll be misleading. But Sean McVeigh to his credit before the division around said that CJ Anderson was in the game plan. And that was true. And now he's saying Todd Gurley is going to get a lot of run during the soup bowl. I'm inclined to believe Sean McVeigh. And as a result, I think that Gurley is going to have going to be on fewer rosters for this slate than he should be. We know what he can do as a receiver out of the back. I think that's kind of the main appeal in Todd Gurley. He's still gotten targets each of the past two games in the postseason, even with the injuries. And in that game against the Saints, when it was crunch time, Todd Gurley was on the field. You know, CJ Anderson got in there too, but Gurley was on the field when it did matter. And this entire game matters. So I think that Todd Gurley is still a player I want to use, even though I think there are legitimate reasons for concern. You could still talk yourself into CJ Anderson, because if you assume that he keeps the same role he had last week, he'd be an awesome player for DFS. But for me personally, I'm assuming the pendulum to swing further back towards Todd Gurley. That knee does not seem to be an issue based on what they have said about it publicly. So I'm inclined to believe them. And if Sean McVeigh says they will use Todd Gurley, but I want to use them as well. So far, no reason not to trust Sean McVeigh's word when it comes to game plan. Todd Gurley, I'm sure is also looking to have a huge bounce back. Up next, Julian Edelman of the Patriots. He is a stud for this single game Super Bowl slate. Tell me why. Yeah, I think that when you look at the two guys at the salary, it's Gurley and Edelman. I think that Gurley has the higher ceiling because if they use them the way he did during the regular season, the dude could just be a monster. He'd be a great MVP selection. But I think that Edelman is a safer selection by a pretty wide margin just because we don't really know what Gurley's role will be. And we absolutely know what role Edelman will have. That's been a pretty meaty one for Edelman ever since Josh Gordon left in the playoffs. Edelman has 26% of the Patriots targets. He has 33% of their deep targets and 20% of their red zone targets. Those are all really solid numbers and it's allowed him to score at least 12 Fandal points in now six straight games. Now you could look at Edelman's numbers and say, hey, you know, there's not a ton of upside here and he is pretty cost prohibitive on Fandals. Maybe you wouldn't want to use Edelman, but he has also had 20 and 13 points in the two playoff games. And that is without scoring a touchdown in either game. He has had a lot of red zone targets, so a touchdown is possible. So if you give him his seven receptions for 100 yards and give him a touchdown on top of that, there's a pretty good chance that Edelman could be the highest scoring player in this game. So I know the ceiling has not always been there for Edelman, but I think that he is still a pretty solid selection for your MVP slot. He has an awesome floor. The ceiling is pretty good too. So Edelman, I think is a safer play between these two guys in this $14,000 range on Fandal. And I think that if you're looking for safety, he does make a lot of sense. As far as how he's being used, Julian Edelman has had quite the run getting targeted 10 times or more in six out of his last seven games that includes the playoffs and therefore just goes on to emphasize your point about a great floor that you can feel good about. Now, how about James White of the Patriots? You also consider him to be a stud, a little bit less expensive, which is nice. What else can you tell me? Yeah, it's kind of like the Todd Gurley scenario where in the conference championship, we saw James White kind of get phased out. And I think that that could be concerning and could force you to use Rex Burkhead for this weekend. But I think there is a possible explanation for that because I mean, James White got a lot of work between that Los Angeles game and the game against the Chiefs. You know, he was heavily used. If it's possible, he was just gassed by the end of that game and needed a breather. Maybe he got hurt. I think that there were some rumblings around that too. So there's a possibility the late game usage for James White was not indicative of what we should expect during the Super Bowl. And I think that that's kind of where I wind up landing where I don't assume that White will be, you know, on the sidelines like he was at the end of that game. Personally, if I had to pick between James White and Rex Burkhead, I'm probably leaning White most of the time because there is always big usage well within his range of outcomes in the playoffs, even including that game against KC. White still has 26% of the Patriots targets. He has 27% of their Red Zone targets. And, you know, the Rams are pretty good against past catching backs, but we talked before about how Tom Brady isn't throwing the ball down feel very often. What that does is leads to really big usage for guys like James White and like Julian Edelman. So to me, I think that it does still make sense to go at a guy like James White. He's a little bit cheaper than Gurley, then Edelman, then Sonya Michelle. And I think that that does add to his appeal too if you don't want to go all the way down into the immense value plays for this game. So James White didn't have a big role in the conference championship, but I think based on a story you can tell yourself about his usage in that game, I think he's still very much in play for the Super Bowl Slate. I'll just say we know what kind of day James White had back in Super Bowl 51. Do I expect that much? No, but we know he's capable. So that always helps. Finally, a stud to consider for this single game Super Bowl Slate on the Rams. It's Robert Woods. Which receiver on the Rams, like when you're looking at them, why Robert Woods? Yeah, it's kind of hard to choose because there's a lot of reasons to like Brandon Cook's. I love Brandon Cook's the talent. Like the dude's just crazy fast. He makes offenses better. And in a perfect world, I'd use Brandon Cook's.  And I think if you're looking at a player they may take away, it could be Cook's or it could be Woods. But the thing that I like about Robert Woods is that he gets more targets and Brandon Cook's and he's a little bit cheaper than Brandon Cook's too. Woods is just $10,500, which I think given his target load is kind of a steal for this single game Slate because in the playoffs Woods has 28% of the Rams total targets. And the reason he hasn't really popped off is because not a lot of those targets have been downfield. You look at the cornerback play of this Patriots team, they've got really good guys on the outside. They can shut down pretty much anybody and that does, you know, work on slot receivers too. JC Jackson's been awesome and they could use other guys on Robert Woods and potentially shut him down. But I think given the salary that Robert Woods carries, given the volume he gets and given how much this Rams team may be forced to throw what they get behind, I think there are still enough things working in Robert Woods's favor where you can definitely use him. We'll talk about Josh Reynolds in the value section. I think that he may wind up being the safer guy when you consider his salary, but Robert Woods is getting too much volume to ignore when his salary is just $10,500. So to me, from choosing between Cook's and Woods, I love Brandon Cook's. The revenge game narrative is there too once again for him this week. But I think that I do prefer Woods and I'll take that $1,000 savings. Six receptions or more in five of his last six games that includes the post season, Robert Woods, definitely a great stud option for this Super Bowl slate. I'm so darn excited for the big game, but we got to take a break. And when we come back, Jim and I are going to talk about all the value DFS plays. So don't go anywhere. We're back on the fan duel. Hurry up, Maria Marino. Once again for fantasy sports network and number fires, Jim Sonnis continuing to preview the biggest of the big games, the Super Bowl, which is coming up this Sunday and the single game slate offered on fan duel.  Now it's time to go through the value plays. And you know, I got to say, Jim, a lot of people throughout the fantasy football season complained about kickers and the kicker spot. But with this format, using a kicker is not a bad idea to say the least. Let's start by talking about Greg Zerline. Yeah, you said using a kicker. I'm not opposed to using kickers. Well, here, Maria, because hey, we can use any position we want. Why not both? But starting with Greg Zerline, I think that we saw in the conference championships, what does dude can do when he is indoors? They call him legatron for reason. Like the dude is an absolute machine. He has scored at least 13 points in both playoff games so far this year. And in the regular season, he was just insanely consistent. He scored double digit fandal points in 10 of 18 games this year. Like that is unreal. They never scored fewer than seven fantasy points in a game. The only downside I see with Greg Zerline is his salary. He has $10,000. And, you know, that's not a lot. It's not a ton by any means. But if you decide to plug in both Jared Goff and Tom Brady, and someone like Todd Gurley, or Julian Adam, or Sonya Michelle, it's going to be really hard to afford Greg Zerline for that fourth slot. So basically what he requires you to do is use either just one quarterback or drop down for your third player to someone like Jean's White, Brandon Cooks, or Robert Woods. I am okay with doing that. So I'm going to use Greg Zerline in some lineups. But I think the only real drawback on him is that he doesn't necessarily fit with a Stars and Scrubs approach that I think I will use pretty often for this game. But if I have the salary to get to Greg Zerline at $10,000, the dude is automatic. He has a super high floor. His ceiling is pretty good too. So I think that Zerline makes a ton of sense for the Super Bowl slate, even though kickers in general may not be our best friends or fantasy. Definitely has the clutch gene after what we saw in that championship game and allowing the Rams to make it all the way to the Super Bowl. Now, another kicker, the other kicker, I should say, Steven Gostkowski. What do you think about him and, I mean, comparable as well in terms of price and the other projections? Absolutely. I think that with Gostkowski you get a $500 discount on Fandle, which is certainly attractive. And I also don't expect Gostkowski to be on as many rosters because if you look at the weekly output by both Greg Zerline and Gostkowski, it skews pretty heavily towards Greg Zerline. So if people do decide they want to use a kicker, they're probably going to use Greg Zerline more often than they use Steven Gostkowski. But for me personally, my preference at kicker will always be to use the guy on the team that wins the game. And right now the Patriots are two-point favorites. We've seen a lot of public bets go on them. And a lot of the money is on the Patriots as well. So smart people seem to think that the Patriots are going to win this game. And if they do, it would allow Steven Gostkowski to kick field goals late in this game. And it would imply that the Patriots score more points than the Rams do. Both those things line up well for a kicker. So I think that if you look at what the bookmakers are saying about this game, it says we should favor Steven Gostkowski over Greg Zerline despite what has happened throughout this regular season. Gostkowski has shown upside to, he scored 22 fan dual points in one game back against the cheester in the regular season. He had 14 against the bill. So I think that the upside is there for Gostkowski, the stability, you know, during the regular season was not there as much for him as it was for Zerline. But I still think there are enough factors in his favor to take Gostkowski, take the $500 savings and plug him in there at $9,500. I think the biggest thing about Steven Gostkowski that makes him appealing is this whole business as usual kind of kind of situation. He's been there six. Well, this will be a six time in the Super Bowl. So pretty crazy. Obviously, he's, um, he's no stranger to the moment. Let's move on and talk about a tight end. Rob Gronkowski of the Patriots. This is interesting to me because all season long it was the narrative has, has Grant kind of lost it. Is he not the top tier tight end that he's been in the past? What do you say to that? And how do you feel about him at this point in the season? Yeah, I think that narrative that you were discussing, Maria, really did accelerate down the stretch front of the season because yeah, in the last couple of games of the regular season and in the first game of the postseason, Gronk really did nothing. But last week, we kind of saw this big resurgence with Gronk where he got a lot of usage for this team. He led the Patriots with 11 targets in that game against Kansas City. Three of those targets were at least 16 yards downfield. One of them was in the red zone. And I think that, you know, when we look at that, that's pretty big usage and I don't want to ignore it just because of the way we've seen Gronk play this year. Like we don't want to overlook volume just because the player may not have that same edge that he used to have. One of the concerns I tend to have with Gronkowski in general is that we have this, you know, this narrative where Bill Belichick kind of keeps him in the garage to keep him healthy throughout the regular season and may not use him fully to keep him healthy. But there's nothing to keep him healthy for anymore. It's a Super Bowl, maybe his final game ever. So all bets are off with Rob Gronkowski at this point. They're going to let him unleash. And if Gronk still has anything left in the tank, we're going to see it on Sunday against this Rams team. Now, he's not the same person he was before. You know, the thoughts around Gronk were there for a reason, but his salary isn't there either. He is just $9,000 on Fandall. He had more than 100 receiving yards in a game just back in December. Like it wasn't that long ago against the Dolphins. He had more than 100 receiving yards. So I think he could go out on a high note. I think that Gronkowski had $9,000 fully worth that salary. If you can afford him as you go with your stars and scrubs type lineup, I think that Gronkowski makes a lot of sense. I know there are concerns and I think those concerns are legitimate, but I think that his salary accounts for that. And last week provided a kind of a blueprint for a big day from Gronk. You certainly like the trend when his most recent game in the AFC championship, he was targeted the most that he had been all season with 11. Now, how about Josh Reynolds as we continue to talk about value plays for this single game Super Bowl slate? What about him? Do you like? Yeah, with Reynolds, I think it's kind of the same discussion we had about Sandy Watkins two weeks ago for the conference championship, where we had this narrative around the Patriots where they're really good and they're really smart defensively. They can shut down your top two options just because they want to make you play left handed. And if they decide to do that this week, that's going to mean they could be shutting down guys like Brandon Cooks and Robert Woods, leaving Josh Reynolds a little bit softer coverage. And we did see Sandy Watkins do pretty well against that coverage last Sunday in the conference championship. So I think that that could lead to a lot of usage for Josh Reynolds. And on top of that, he's gotten usage in general so far in the playoffs. He has 17% of the Rams overall targets along with 25% of the deep targets. And this is a guy who did get red zone work during the regular season as well. After the Cooper Cup injury, this guy was like their main target inside the red zone. So Josh Reynolds saves you a lot of money. He is $8,500 at the same site, the same price as Philip Dorsett, who doesn't have nearly the same overall volume as Josh Reynolds has. So Reynolds saves you a lot of money. He gets you away from those top two cornerbacks of the Patriots. And I kind of think that the best assumption is that the Patriots dedicate those good assets and trying to slow down Robert Woods and Brandon Cooks. If they do that, Reynolds could beast out at $8,500. So I am fully willing to take those savings, plug in Josh Reynolds and hope the Patriots live up to their motto in shutting down an opposing team's best unit. He had seven or more targets and four of his last six games. Once again, just a trend you could feel good about and potentially a great option to find some value. Moving on, Chris Hogan of the Patriots. He's another value play salary, just $7,500. What else do you like about him? It's mostly just a salary. I'll be fully on about this, but you know, $7,500 can go a long way on a fan duel on this slate. When I want to pay for Brady, for golf, for girly, for Edelman and Michelle, I need to say somewhere. And what Chris Hogan gets me at $7,500 is a player I know will be on the field and I know will at least get some targets. And honestly, that's all I really need for this slate. Now, the debate for the Patriots is, do you want to use Chris Hogan or do you want to use Phillip Dorsett? Dorsett is $8,500 whereas Hogan is $75. Hogan has 13% of the team's targets in the playoffs, whereas Dorsett has 9%. And Hogan also does have 20% of the team's red zone targets. There's a decent chance he can score a touchdown. And if you get a touchdown at a Hogan on the single game slate, he's basically going to pay off no matter how many yards he winds up getting. So I think that when I'm trying to compare these lower salary Patriots receivers, I think I prefer Chris Hogan over Phillip Dorsett straight up, given, you know, that we know he will be on the field at all times and should get more targets overall. But when you give me $1,000 in savings to boot, I think that that pushes me further towards Hogan. So he's disappointing in general so far this year. And it is largely a salary based decision. But I think that there is a path to a good day for Chris Hogan. And that's enough for me to take a swing at him at $7,500. And in his defense, I'll say that in his last few games, he's been targeted considerably more than he was earlier in the season. And that just means he is trending in the right direction, which gives you a little bit more peace of mind, especially when you need that salary relief. Finally, one last value play to discuss. And I have a feeling it's going to be more of the same in terms of a lot to do with the price tag, which is quite low at six K. It's Gerald Everett. You are very much not wrong. Again, you read my mind here because the salary is so low at $6,000 for Gerald Everett. And I think that when I'm looking at the players available for this weekend, he's probably the lowest salary player that I want to use at $6,000. He does allow me to use those three big subs we were talking about before with Goff and Brady and then one other stud in that upper pricing register because Everett is $6,000. He is $500 cheaper than Tyler Higby. But in the conference championship, it was Everett who was on the field more often. He played 68% of the snaps. He ran 27 routes compared to 14 routes for Tyler Higby according to pro football focus. So Everett was getting more chances to catch passes and convert those into points. And he also benefits from the same narrative we discussed around Josh Reynolds, where the Patriots decide to shut down Brandon Cooks and Robert Woods. That's going to leave softer coverage for guys like Reynolds and like Gerald Everett. They're not going to be trying to shut down Gerald Everett when you got guys like Cooks, Woods and Todd Gurley on the field. If you plug in Gerald Everett, you kind of have a lot of flexibility on the top end. So I'm going to have quite a bit of him for this single game slate. I will also have some Tyler Higby because he is a guy that they have turned to in the red zone and is going to be on the field. So I think that you can use both Higby and Everett, but personally I prefer Everett. I'll take the $500 savings and take the guy who has been on the field more often of late.  Gerald Everett might be the guy that allows you to just fill whatever spot you need and without breaking the bank. Plus, as you said, could take advantage of the opportunity. Assuming most of the attention will be on some of his other teammates. Okay, so that's it. That's all the studs. That's all the values, courtesy of Jim Sonnis of Number Fire. Thanks for that. Thank you all for tuning in. I hope you're getting as excited as I am for Super Bowl Sunday. By the way, if you want more content, you can always go to fan duel.com slash the duel and click on videos or subscribe to our YouTube channel at the Fantasy Sports Network.


What do you think about where Bitcoin interfaces with the rest of the financial networks, specifically in the form of ETFs and things like that? Right now there's one ETF out there that was predicted to be more and trading at a significant premium meeting, but more ETFs aren't coming into existence with Bitcoin. Yes, so what's happening with the interface between Bitcoin and the traditional financial system and why are there not more ETFs? There's only one at the moment that has come into existence, I assume you mean GBTC, and is trading at a significant premium, and what happens? Why haven't there been more? Well, it's because Bitcoin is sufficiently alien that it can't be swallowed by the traditional financial system. They really have no idea how to handle it. It doesn't conform to any of the expectations. The entire financial system is an edifice of counteracting controls, counterparties, risk management layers, and checks and balances. All of which assume custody and oversight and control, of which Bitcoin expresses none. So how do you take something that is this alien and put it in this type of environment? This is exactly like asking, it's the early 1900s, and the automobile is out. Why are not more pony express routes being replaced by automobiles? There's no roads. And they've built a series of stations that have lots of hay, which can't be used for the automobile. So everything they have doesn't work with what is new. That is basically the issue. Bitcoin is quite capable of having an ETF. ETFs are quite incapable of encompassing Bitcoin into the current regulatory system at the moment. They're finding it very difficult to swallow. And that is a feature, not a bug. I hope they choke on it.


Next talk is Fabio talking about deep learning on Hopsadoop. So everyone, I'm Fabio. I work for a company called Logical Clocks. We have a startup in Stockholm. And we are the leading company behind the Hopsadoop platform. And today we are going to show you how you scale deep learning workloads on our platform basically. So a bit of step back, the project was a couple of years back with OpsFS. OpsFS is basically a fork of Apache HFS. The difference between OpsFS and the main difference between OpsFS and Apache HFS is that we took the metadata of the file system, which in HFS are stored in the name node, and we put them in a distributed in-memory database. And this allows us to scale both in terms of like space and like files we can store and in terms of throughput. Just to be clear, this is not like some random vendor numbers. These are like research with recognition both from academia and the industry. So on top of that, so on top of the file system, and actually we also have a fork of YAM, which is like the Doop Resource Manager and Custom Manager. We fork it because right now YAM doesn't support like scheduling of GPUs. It's coming in a couple of next reads. And we do have it in Ops YAM. On top of like Opsadoop, on top of OpsFS and Ops YAM, we build like an entire platform and you can find basically everything, all the software that you will expect from a big data platform. But we also want to provide deep learning solutions. So we also have the support for TensorFlow. On top of that, we have, well, Jupyter and Zeppelin to write your code. And the whole platform is organized basically in projects. And you can think about like data projects. So you have like users can collaborate on multiple projects, multiple projects can have data shared like across different projects and so on and so forth. Everything is just like a recipe so you can build your own applications on top of Opsadoop. And we just released the 0.3 version so you can go and check it out. I will have a link at the end of the slides. So as I said, we want to provide like deep learning solutions. And when it comes to deep learning, Python is basically the winner. We allow people to run deep learnings on Opsadoop by using Codel repositories. Basically, each project is on Codel environment. It's like users can install on their project whatever libraries they want. And then they will be able to like use those libraries from Spark and from TensorFlow. And we see later that these two are quite connected. Besides that, we develop our own Python library that surprise us called Opsa Python library. And the thing that this library does a bunch of stuff, the main thing is that it allows you to like do hyperparameters searching for your models and manage the TensorFlow lifecycle. I will show an example later how you can do that. Now, you have a platform. You have all the tools. You have maybe some good ideas. And we develop this thing as a PhD student working real-time and getting this tool done. It's basically data. The idea of data is that you organize your clusters, your Ops cluster in a peer-to-peer network, and they can basically exchange that set with each other. And the idea is that if you, let's say you have like your new like image recognition network and you want to try out, you can go on the network, grab ImageNet, and then you are good to go and you can, you know, start training and see how good is your network. Or on the other hand, if you have like a cool data set or you did like a cool experiment, you can like register your data set with the network and then people can start using it and start doing more experiments basically. The next thing about this is that your protocol is based on UDP and the idea is that we don't want to impact like production traffic going on your cluster. The tool listens for like traffic in the network. If it is empty, then start transferring the data set.   What you can do is doing, you can do like hyperparameters searching in parallel with the ops Python library. The idea is the following. You take your TensorFlow model and you put it into this function. You define some like additional values of saying, okay, I want to test this learning rates, I want to test this dropout values. This is actually optional. You can say, in this case, you say, okay, let's try like a grid and so let's try 001, 045, 005, 045 and so on and so forth like in the grid manner. And then you import this TF launcher which comes down with the ops library and you say launch this model with this grid and what this basically does is the following. It uses Spark to go to Yarn and request like six different executors in this case and will launch your TensorFlow model and run your TensorFlow model for you on the cluster. The next thing is that Spark is now aware of like that can go to Yarn and ask for GPUs. So your model, like your experiments can have it run on one or multiple GPUs basically. Besides that TensorFlow launcher will actually launch it for you like a TensorFlow bot which basically for those of you who don't know what TensorFlow is, it's basically like a nice visualization UI where you can basically track like how your experiments are going. So on the end of the execution, you will probably see and so let's say you were tracking the accuracy of the model, you will be able to see which of these combination of hyperparameters gives you back like the best accuracy basically. Now you have your model, you have data and so on. Now you want to like really like, scale out for instance of like you want to go like distributed training and train on the full size dataset. Now when it comes to distributed TensorFlow, distributed TensorFlow is actually designed to be used with like the cluster manager. You have to start all the processes, you have each process which where all the other processes are and so on and so forth. So you either want to use Kubernetes, Mesos or in our case as we are in the Doop world we use Yarn again and we exploit basically the same fact that we were doing before with TensorFlow Lancer and we use Spark to actually distribute the code, allocate the resources and start the process for you basically. We use a tool actually open source by Yahoo. It's called TensorFlow on Spark. The idea is that Spark is used to, as I said, request the resources from Yarn. It's used to start the processes and it's used also to distribute your code to all the work as basically. We actually fork the TensorFlow on Spark, mainly because again Ops Yarn supports exclusive GPU allocations. So you basically like this TensorFlow, no, our version of TensorFlow on Spark can request GPUs basically for you. And there is another like a minor improvement, but minor, not really minor. The idea is that parameter servers which are effectively a Spark executor will not get the GPU because they don't need it. So it's like a waste of resources basically. And again, TensorFlow on Spark will manage for you the tensorboard basically. This is how basically you run everything. Again, you wrap all your models inside this training function. Inside training function you call this tfnode such as the server.  Am I a parameter server? And then you take action basically. And then you call this tfcluster. You basically give you the Spark context. You have to give like the training function, the number of executors, and the number of parameter servers you want. If you go on this link, like there is an official guy from Yahoo telling you how you can transform like normal TensorFlow code, normal distributed TensorFlow code to the TensorFlow on Spark. Now, the problem is that when you are scaling out the system like you are training with a lot of GPUs, thank you, the parameter server architecture doesn't really scale because especially if you have like large model, like VGC 16, which I think the weights are like 500 megabytes, something like that, network comes from bottleneck. Every worker, every GPU has to communicate with the parameter server at the end of each iteration. So you really can't scale, basically. These are experiments done by Uber. Uber wrote this tool called AuroBot. And the idea of AuroBot is the following. They actually built on top of like work done at Baidu. And the idea is that you don't have like a centralized architecture, but you organize your workers in a ring, basically. It's, again, it's data parallelism, so each worker gets his own batch of data you want to train. And the idea is that when the work is done, the updated gradients are distributed to all the workers using the all-reduce algorithm. Just a quick recap of all the reduced algorithm works, basically. You have like these three GPUs, I'd say, and you have like your gradients, let's say, and you divide it in three batches, because you have three GPUs. And the idea is the following. Sincuesly, you view GPU 1 submits to GPU 2, GPU 2 submits to GPU 3, GPU 3 submits to GPU 1 again. You do that twice. And at the end of the first round, the first like the first two rounds, you will have like one GPU that has like each GPU as one of the chunks of the gradients that it has to transmit in the final state. You do another two iterations, and you have every GPU as the updated gradients for the next iteration, basically. But as I said, this is like a synchronous protocol. So before the next iteration, all the transmissions has to be completed. And this means that you want to have as homogeneous as possible GPUs and as homogeneous as possible a network. So let's say you have like 10 links and you have like nine InfinityBand and one Ethernet. Then you are based in InfinityBand because all the workers will wait until the transfer between the two worker connect through Ethernet are finished. One optimization you can have in this system is the following. So if you have like a neural network and you are doing like the computing the arrows, basically, the gradients updates for the last or the external, so to say. External layers are available much earlier than actually the gradients updates for the first layers. So you can stop transmitting the gradients updates for the last layers before actually having computed the gradients for the first layers. So you can get more performance, basically. So this is how you use it. There is like a full support for auto-use on Opsadoop, basically. The idea is the following. You write a Jupyter notebook, including all your code. Again, you have to do some minor modifications to your code. One thing is you have to feed your optimizer into this over-distributed optimizer. And you have to tell each worker the position in the ring. So he knows to which other worker to send the gradients from which worker will receive the gradients. You wrap everything in a notebook, so to say. And then from another notebook you call this auto-use launch spark and you give the notebook path. And this, again, will transform your notebook in a Python program, execute and train, and we show you the TensorFlow logging, basically. I do have, like, a quick demo of the old platform. Alex, how do I have left? Okay. Which one is there? No, no, no. Do you know what's... Yeah, I know. There are like four of them. No, this one. Oh, we can open another one. Can you just put it together? Yeah. It's in full screen, right? Ah, okay. So this is our, like, we have, like, a production cluster with the platform installed. And what you can do, for instance, is, like, you create a new project. Let's call, like... And the idea is that, well, we don't need hype. We don't need this one, this one, and this one. Can I go out to the full screen? Yes. Control-mines. Yeah, okay. Awesome. So now we can, for instance, look for that.  For instance, we can look for... How do... Okay. Quick draw. For instance, this is, like... Okay, this is only 200 gigabytes. We can add this dataset to our project. This is going to be fast. Like, this is going to be immediate, just because the data is on the same cluster, so you don't have, like, the transfer to do. But if you were on a different cluster and you were going to this data service, you will be able to see the progress of the transferring, basically. So once you have your data there, what you can do is you go into the Jupyter Notebooks. You say, let's do this TensorFlow. You say, well, I'm going to do, like, six part of the experiments. Each... Each executor for Spark will have one GPU, a bunch of memory, and you can start. So the first thing you want to do, maybe it's, like, doing... The data, for instance, in the QuickDraw experiment, it's basically a JSON entries. And the thing is, what you want to have is that, as you're using TensorFlow, you're using maybe expensive GPUs.  So what you can do is, basically, if you're using Spark, in this case, I'm using Spark, I'm, like, converting these JSONs, basically, into some... into actually, like, a dataset of TF records. So it's really... It's ready for actually training. Then we can go to the... We can go to this one, which is basically the... the API parameter searching. So as I said, again, down here, I'll say, okay, define a dictionary of possible parameters that you want to test. These parameters are then provided with your training function. Then you say, okay, these are the model parameters, and you can test with different dropout values and different learning rate. We can actually round this notebook. It will take a while to get up. So the TensorFlow is basically... This one. This one is the TensorFlow and Spark notebook. We have, like, here, we have, like, auto-ingested data. You are reading the TensorFlow... You're reading the TF records' assets. These are, like, the dataset APIs, which are really cool from TensorFlow. This is the model. And then down here, we have the... basically, the... the color I was talking to you before, saying, okay, tell me if I am a server or not. You can now say, okay, just wait for it. Otherwise, start the process and start training. Here is me, not really super a pro in writing TensorFlow code. It's really ugly, but let's say... Let's just keep here. And this is, like, how are you basically running? Yeah, this hotel basically comes out from the ops library. Say, okay, this is, like, the number of executor you ask, and this is the number of parameter server you ask for. And you start the training, basically. Say, okay, this is the number of executor again. This is, say, okay, I want... I want you to start TensorFlow for me... TensorFlow for me. And this is the input mode. You will find, like, more documentation. And finally, we have, like, the... notebook. Again, same color before. Network ingestion of the data. Here is the one... Here is the thing I was telling you. You have to specify, basically, in which position each worker is, basically, saying, okay, this is my local rank, so to say. This is a notebook to actually, like, that contains all the information and all the... I'll say, the code itself. And then you have these notebooks that actually launches the old train. And potentially, we can see... Yeah, you can see here, like, for instance, these six experiments that I launched before for doing upper-parameter searching, TensorFlow is up and he's showing, like, some graphs, basically. So I have to wrap up. Yeah. So that's it from my side. As I said, we released the 0.3 version of the platform. You can go on this link and get, like, a background machine, like a virtual box machine so you can try it out. We have documentation for everything I said on this link. Please start us on GitHub if you want and follow us on Twitter. Thank you. Thank you, Fabio. Time for questions. Thank you for the presentation. How are the tools that scales with the number of GPUs? Come again? How are the tools scales with the number of GPUs? Do we get a... This one, this is the AuroBot thing. Yeah, it's AuroBot that's managed the... Yeah, the idea, if you look back to this one, the orange is the normal parameters of architecture for TensorFlow and the light blue and the dark blue are AuroBots. The light blue is using TCP. The dark one is actually... like, the darker blue is using a DMA. Okay, thank you. Any other questions? Going once. Yes. Thanks for the presentation. Would it be suitable to use this kind of approach to run a single machine with multiple GPUs on it? Or would you advise to use it more to run multiple machines? Okay, we are actually using... I have like one single machine, for instance, with like 10 GPU usage and running AuroBot. But yes, you can potentially scale to multiple machines. I think there was a paper, I think in June, from Facebook, they were like using training of ImageNet to around, I think, less than an hour. I don't remember exactly the time and they were using the same approach, I think over 256 workers, so 256 GPUs spread at this point on multiple machines, basically. Okay, thanks. One more? No? Okay. Thank you, Fabio.


Well, some of you reason like cultural relatives tell relatives already sometimes you'll say things like well That's what that culture does. It's not what we do. So but since it's that culture It's okay that they're doing it that way On the other hand, sometimes you reason completely opposite of a cultural relative is sometimes you just say look It doesn't matter if the culture is doing that. It's simply wrong and Yeah, there there are cases I mean lots of cases of oppression for example So cultural relativism is kind of be kind of a mixed bag and sometimes it seems helpful to us and sometimes it doesn't so in this chapter Rachel's takes a pretty hard look at cultural relativism And he ultimately he's going to say that cultural relativism fails Overall, but he wants to say there are also just a couple of things that we can learn from cultural relativism So to begin this examination of cultural relativism We're gonna look at the Rachel's takes a look at the five main claims that cultural relativists tend to make now the first claim When you see this what it's kind of obvious, right? You just need to look out into the world to see if it's true And yeah, there is a lot of differences between cultures the second claim of culture relativism is pretty much the crux of it and this is this idea that That the culture is what determines what is right or wrong If you want to know what's right or wrong just simply look to what the culture says and if the culture If you try to say something contrary to the culture within you butters or you or try to act contradicted culture then you are doing something wrong Another claim about the cultural relativists is that you that there is no objective standard then for all of morality Since what is moral just depends upon what the culture says what there's you know There's no culture that encompasses all cultures. Okay, so there's just so there is no objective standard by which to By which to make any moral judgments. You just have to rely on the culture Kind of a similar to that then is that there's no way to judge a moral culture. Okay All right, there's no way to judge a culture especially within one's own context, right? It would be at best arrogant for say, I don't know the United States to criticize, you know American culture to criticize You know the practice in Japan of bowing we're greeting somebody that that's kind of a motivating idea behind it The next claim is kind of curious you might wonder about this It's a it's the claim for tolerance So so the cultural relativists is saying look, you know, since we can't judge all the cultures We ought to be tolerant of other cultures. We ought not to you know, it's kind of the opposite of arrogance All right, now you wonder might wonder whether that claim is supposed to be made within the American culture or With it or whether it's supposed to be made outside of all cultures and a lot turns on that depending on how you do it So these are the five main claims of cultural relativism So one very interesting project That we can do is to look at how these five claims of cultural relativism are supposed to be related to each other Because so far what we have and I'm not saying it's impossible What we what we have is not really an argument for all five claims, right? This is kind of stated Well one wonders, you know, is one supposed to prove the other is You know one supposed are all the other four supposed to come from the other from one Stuff like this So one way to go about looking at this is to see a lot of cultural relativists It is are going to argue that the first claim implies the second All right, this is what's called the cultural differences argument. Okay, so the idea is well Look, there's there's a great variety of differences in moral cultures. Okay You don't have to look very far to see where this is true anywhere from manners to some of the extreme cases of life and death That Rachel's mentions in the book So one way to One way to argue there say look since there's this difference in the cultures It follows that whatever is whatever the culture says is moral just is what's moral That difference in culture means different moral codes, right? Sorry differences in more moral Differences in cultures and moral codes means that there's different moralities. There's actual different Claims to morality depending upon when and where you are so to take kind of a look at this we're gonna put it again into a numbered propositional form and The first premise is the obvious one is the ones you don't have to look very far to find out whether It's true, and that's the that's the claim that there are that there are cultural differences Now it's the second premise that's really doing most of the work It's the conditional if there's a difference in cultures, then there's Then there's no then whatever is more just depends upon the culture and this conclusion follows Once again using our good friend modus ponens So like I said the first premise probably isn't the one you want to go after it's just pretty obvious It's the second premise that Rachel's disagrees with and he does this in a kind of an interesting way, and it's a very Real observation here the observations look cultures differ on a lot of different topics. Yeah And you know today culture at least in the West cultures are really consistent as far as mathematics But that didn't used to be the case That for a while there was a really heated argument about whether there's the number zero And different cultures had different points of view Cultures have taken different stances and approaches to making scientific claims. Okay History right depending upon which culture you're looking at you're going to get a very different account of history Now since there's this difference Amongst cultures in these other fields You know we might say well why isn't Why don't we make the claim that well history just depends upon when and where you are or the math just depends upon when Where you are our science. We're not at all tempted to do that So why is it that we're now all of a sudden tempted to do that with morality? And yeah, we could push the point even further. Okay, you know if we're gonna point to this difference in cultures As a reason to say well, then there's this difference in morality Well as a matter of fact cultures don't really agree upon cultural relativism Okay, sure some cultures do all right We saw some examples in the text, but most cultures are really sure that their morality applies to everybody else as well Okay, so it if we're going to say well since there's this difference in the cultures then others There's this different morality. Well, there's differences about whether the second premise of cultural relativism is true So that only depends upon winning where you are well if that's true that most of the cultures on the planet deny that premise and They really strongly believe in some kind of absolute moral truth that applies to everybody So that's perhaps one way to start looking at it Ultimately, you know Rachel's concludes is that the first premise does not imply the second premise sure There's differences of cultures, but that doesn't mean there's now a difference in truth You know you just of course we're we can further discuss this in class, but so far You know so far that this reasoning is pretty good, right if you're gonna say that since there's this difference in morality a Difference in moral beliefs across cultures. Therefore, this is difference of morality. You've got to explain why morality is a special case When we don't have that when we don't we don't apply it to science, math, and history another way to look at cultural relativism is to see how it's related to You know how it implies or how it impacts what you already believe So one thing about culture relativism is You know since we have this claim that what is moral just depends upon what the culture says Then it has kind of the odd conclusion that Whatever the culture says is right, but that means that there's nothing wrong ever in a culture There's nothing wrong ever in a culture and you don't think this is true You think there are cultures that have done some things that are really obviously wrong There are cultures that oppress people Okay, the third Reich is one of the most popular examples to point to it was a culture Okay, it was a very different set of beliefs that a group of people had they had practices the whole spiel But they did some really really horrible things now according to that culture It was just fine But that's wrong. It was really wrong the things that they did so if you If you say that there's if you subscribe to some version of culture relativism, right that whatever the culture does is Right, then there's absolutely nothing that the culture does that's wrong and Again that you know this has this impact regarding Whether you can judge that culture. I hope you say you can judge the third Reich, right? I really really do and it was wrong so You already think that there's something that the cultures can improve right well if they can improve Then whatever the culture says that it's not it's not sure that whatever the culture says is right there's This next implication Consequence is really kind of related to the first right just as you know if we say that there's no way that We that you know Excuse me if we buy the claim that culture relativism says that whatever culture says is right Then not only is it the case that no in every culture is doing anything right anything what the culture says to do Well, that's right. Well, that also applies to our culture if we If we say as the culture, you know if we buy the culture relativist line then whatever our culture does is right That means that our culture should never change Okay, and you really think that's wrong. I guarantee you think that's wrong because that means for instance That anybody who tries to change the culture Is doing something wrong now that means that Martin Luther King Rosa Park These people were wrong Were mistaken and what they were doing they were acting contrary to the culture and if culture relativism is right Then they were not Not trying to advance progress. They were trying to be revolutionaries they're trying to overthrow what was right and We don't want to say that we quite obviously and rightfully believe that Martin Luther King and Rosa Parks were doing the right thing And I think yeah, I think that you agree with this. I think you agree with this So with with those claims of culture relativism well, you have a choice either you give a culture relativism Or you give it the idea of more progress And I really hope you give up culture relativism and you keep the idea of more progress So the last claim we're really going to look at here is this idea of tolerance now. I Think tolerance is a good thing. I hope you think tolerance is a good thing In fact, you know tolerance Is something that we should aspire to when you probably ought to learn how to apply more in our lives now a lot of people Want to be cultural relativists because they're inspired by tolerance and I get the motivation or really do but as we seen culture relativism doesn't really imply tolerance it implies this idea that we're right nobody else is and You know kind of on top of that Just as a matter of fact, I don't really know of many cultures that are especially tolerant Every Culture has it's kind of dark history as far as this is concerned And you know really no no cultures innocent as far as far as I mean just think of your most outrageous example of one Group oppressing another trust me. It's happened. Okay. It's happened So, you know, this is kind of an important claim. Remember I Said that, you know, we you know earlier when I was talking about this fifth claim you got to wonder if that Claim to tolerance is made within our culture or made outside the culture Well, if the claim to tolerance is made within our culture Then you know the idea trying to be a culture relativist then you shouldn't be tolerant because our culture in fact just isn't that tolerant we You know, we make some pretty harsh claims Sometimes and I'm not even just talking about racial inequalities. Of course, that's there, right? We are definitely not at all Favorable towards any kind of socialism, right? We do not like socialism in any way shape or form Where there are plenty of cultures that either in the past or currently Prefer socialism. I think that's the way to go So as a matter of fact, we're just not that tolerant all right So so that claim to tolerance really can't be made within our culture So the question is what is it made regardless of what culture you're in and That's probably the way to go if you're claiming tolerance and you want to say That's you know tolerance is a value should have regardless what culture you're in well, then you are not a culture relativist Because now you're appealing to some kind of value independent of the culture So if you want to be tolerant if you want to argue for tolerance You probably want to argue from some sort of Objectivist moral viewer or some objective moral viewer absolute moral viewer. This is going to be true regardless of what a culture says So this is an interesting problem for cultural relativism They want to be tolerant, but it doesn't look like they can claim any way to be tolerant that doesn't disagree with cultural relativism Finally the last thing we're going to look at is Well the first claim of cultural relativism is that there's this difference among cultures and that's true Right, you don't have to look very long to find out That there's differences in moral codes. However There's also quite a lot of similarity What what is meant by this is that there are principles that are there saying there are values that are the same But they're expressed differently from culture to culture. So every culture In some way shape or form values family. All right, or it's a principle that family is very important and you look after family Okay You an American culture expresses this one way You see you see it expressed differently in other cultures. So other cultures for instance The family is very important and decisions about your future are made within that family Okay For the sake of the family because family is all you got families. How you you stick together Every culture has some notion of what's polite Okay, but what counts as polite differs from both culture to culture. Okay, and the states You know if I'm going to greet a friend, you know shaking hands is acceptable If there's a good friend giving a hug is acceptable Whereas in other cultures For instance Japan you bow. Okay, and there's even rules regarding that whether you make eye contact or not How low you bow depending upon who the other person is so there's there are differences in how values are expressed But the values themselves tend to be really consistent across cultures So the point that Rachel's is making here is there's not as much difference, right? It's not just really nearly It's not just you know completely dissimilar moral codes across the planet. No, there's a lot of similarity in moral codes So all in all cultural relativism Can't succeed it can't succeed according to its own reasons it disagrees with itself So that could be a significant problem for cultural relativism now Rachel's Wants to be careful here, right? He he's a little Unclear as to exactly what he means. I mean he wants to say something like there's still some good things about cultural relativism And he's right, right? So that this idea of Tolerance, okay, that's a very good thing and we should strive to keep that now as we said with with tolerance You're gonna probably have to point to some kind of objective moral theory in order to show the tolerance is moral Or maybe it's it's one of the values or principles There's got to be more of a story there Rachel says that there are two things that we could also learn from cultural relativism and the first is that the culture is not the definitive word on what is moral and Yeah, that's that's true I mean this is a lesson that we get from looking at cultural relativism and seeing how you know it kind of fails because Cultural relativism says no the culture is the definitive word well we've seen that You know this doesn't cohere with what we already think is true that there is such a thing as more progress so Then you know the cautionary tale here is when we're trying to figure out what is moral You know culture might be a source of evidence, but it's not going to be definitive It's not probably going to be the predominant. It's not going to be the decisive factor at least in most cases as to what's moral Another lesson to learn is to keep an open mind okay, so the idea here is That you yourself are in a culture Okay, you're a product of a culture and your culture has told you that some things are moral some things aren't moral And it's not to say that the your culture is automatically mistaken, right? We're not we're not saying that but on the other hand You ought to realize that Your culture is not impeccable or infallible Okay So when you're thinking about what's moral sure consult your culture But don't immediately disregard anything because it's contrary to your culture, especially when you're dealing with other cultures There are lots of things we can learn that cultures can learn from each other I'm a big fan of saying that Every culture has perfected something right? Japan perfected raw fish The Countries in the the southern part of North America Central America in the northern part of Southern America a lot of the Latin Latin America countries right there. They perfected the casual man's dresser. I'm a huge fan of Gua Vedas Yeah, so yeah, there's definitely something that each culture can learn from each other. Yes, specifically How more reasoning is going to apply in different cases, especially in cases of life and death So we learn these lessons from cultural relativism No, it's so much because they're consistent with cultural relativism But because we find that these things are more important than some of the claims that most that cultural relative cultural relativism makes


I'm really excited to be joined here today to announce details of the province's work in expanding campsite opportunities around BC. I'm happy to tell you that more than 350 new campsites in BC parks and recreation sites will be completed in time for this upcoming camping season. The last two camping seasons have seen a tremendous increase in demand for campsites in most regions of British Columbia. So the provincial campsite expansion that we are learning about today begins to address the need for more overnight sites to accommodate our future visitors' requirements. These investments will benefit British Columbians and our visitors to our province, whether you're seeking adventure in the BC back country and or just simply enjoying the pleasures of camping in provincial parks or recreation sites across the province. BC offers spectacular wilderness close to home and many people want to enjoy that experience by camping in our provincial parks and recreation areas. This campsite expansion is helping provide more camping opportunities where the demand is greatest and by investing in new campsites in British Columbia we're helping support a strong and secure park system for future generations to enjoy.


NATO Preparing for Confrontation with Russia for 15 Years NATO is ready to confront an increasingly aggressive Russia, said chair of the NATO Military Committee, Admiral Rob Bauer. NATO has been preparing for a conflict with Russia since the beginning, 14 years before the start of the war in Ukraine. Our military plans against Russia reach 4,500 pages. The Admiral noted, Bauer also mentioned the Russia-Georgia war in 2008 and the Russia-Ukraine war in 2014. There has been a partnership between NATO and Russia for more than 15 years. Then everything changed. He said that Allies prepared regional plans for containment and protection against the Russian Federation and terrorist group as the two main threats of the alliance. According to the Admiral, the regional plans include what needs to be done to restrain and protect against these two adversaries, these two threats. Bauer also mentioned that earlier at the NATO summit in Madrid, leaders had decided to increase combat groups on the Eastern flank. In addition to the existing four groups in Poland and the Baltic nations, four more were formed in Slovakia, Hungary, Romania and Bulgaria. He told about the decision to increase the rapid reaction force to 300,000 military personnel capable of deployment within the first 30 days. According to him, such a number of servicemen should be sufficient for NATO in case of the onset of a major conflict with Russia. Additionally, he noted the need to increase industrial production capacity, which would require significant investments. As Bauer stated, Russia's full-scale military aggression against Ukraine demonstrated the need for NATO to improve integrated air and missile defence.


This exercise by Q's got presets for heart race mode and fitness that allows the user to easily dial into different workout routines Similarly a good VR experience has presets as well take for example when you set up your VR headset guardian floor height and boundaries Now there's a lot of accessibility plug-ins out there that try to accommodate for different conditions for example blindness Seizures ADHD, etc. But keep in mind these out-of-the-box solutions won't fit every use case a good accessibility Setup allows users to dial in the individual controls to suit their experience best Your experience should be able to remember those settings for each user whatever customizations you build in you support Well, it's better to have a limited but high functioning feature set than a bunch of frustrating features that aren't supported