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Speaker 1: Hello the Internet. I welcome to season fifteen, Episode one

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Speaker 1: of DS Daily Zeitgeist for January twenty second, two thousand

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Speaker 1: and eighteen. My name is Jack O'Brien, a K. Jack

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Speaker 1: hawk Down, and I'm joined by my co host, Mr

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Speaker 1: Miles Gray. Since your boy mona Lisa Miles, and would

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Speaker 1: the rare honor Amy Man or Mahan. I'm sorry if

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Speaker 1: I miss Bernouca your name. You hit us with two

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Speaker 1: A K s that we both used, So shouts to you,

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Speaker 1: Amy the double uh. And we're thrilled to be joined

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Speaker 1: in our third seat by the hilarious comedy writer Roger

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Speaker 1: to say. Hey, thanks for having me. Hey man, thanks

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Speaker 1: for thanks for being here. What's something from your search

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Speaker 1: history that is revealing about who you are as a

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Speaker 1: human being? Yesterday I searched for I did a Google

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Speaker 1: image search of Warren Harding Warren G. Harding because I

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Speaker 1: read this article that was talking about the worst presidents

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Speaker 1: of all time and it called him darkly handsome, So

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Speaker 1: I was like, well he was he? I didn't I mean,

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Speaker 1: I feel like, you know, JFK number one, maybe Barack

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Speaker 1: Obama number two all time? I don't know, So wasn't

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Speaker 1: he like an actor, like a model at first or

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Speaker 1: something like that. He might have been. I mean he was, yeah,

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Speaker 1: damn look at that. I was just Google image searched him.

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Speaker 1: And he looks like it was that muppet that was

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Speaker 1: like an old eagle. Yeah, he doesn't look look like

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Speaker 1: that muppet turned into a handsome man. Right, it's like

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Speaker 1: back in the day when just like old white men

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Speaker 1: were the sex symbols America. His eyebrows are here to

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Speaker 1: fucking that, they're not here. This is not a game.

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Speaker 1: Those eyebrows are vivid. Um. Sam Eagle is what warrensy

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Speaker 1: Harding looks like come to life. Um. Anyways, a very

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Speaker 1: attractive man. What's something you think is overrated? Oh? I

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Speaker 1: would say leather jackets. I feel like our way overrated. Really,

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Speaker 1: go on, go on, tell me more. I just feel

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Speaker 1: like people think leather jackets equal coolness and um oh right,

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Speaker 1: that that's like the that's the signal. It's like when

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Speaker 1: you're cool, you gotta leave the jackie. Yeah. And then

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Speaker 1: they're they're really heavy right there. Not that I don't

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Speaker 1: think they're that comfortable, but um, but I feel like

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Speaker 1: leather jackets or something that's overrated. Um, and uh I

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Speaker 1: feel like wine and Margarita's are two of the most

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Speaker 1: overrated I'll call every Yeah, I don't, I don't know.

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Speaker 1: I feel like wine basically tastes like grape juice to me.

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Speaker 1: I'm not saying I have a good sensitive power problem

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Speaker 1: grape juice. Yeah, and then somehow Margarita is It's just

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Speaker 1: like I don't have a slurpie. Do you not like tequila?

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Speaker 1: Is that Margarita? Yeah? Yeah, this man tequila something about it.

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Speaker 1: I just feel like people go nuts tequila. Well, yeah,

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Speaker 1: the blended ones, like especially when you go like like

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Speaker 1: Las Vegas and everyone's drinking like the obnoxious frozen drink

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Speaker 1: out of like a like a bomb shaped glass. Like yeah,

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Speaker 1: because I mean I'm not really a huge fan of

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Speaker 1: Margaret either. I wish you had said tequila just always

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Speaker 1: tastes like grape just taste well. It's funny also about

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Speaker 1: the leather jackets, Like, I feel like in the eighties

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Speaker 1: and nineties that was like that was that born out

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Speaker 1: of the idea that every cool character wore a leather jacket.

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Speaker 1: I think, well, I feel like it was James Dean

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Speaker 1: and then gave it to Fonzie, and Fonzie now is

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Speaker 1: a great actor, Henry Winkler, but he's not cool, not

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Speaker 1: five for or something. You know. It's like, oh, then

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Speaker 1: maybe Marlon Brando too. Brando. Yeah, they all had their moments.

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Speaker 1: And then, uh, I didn't one of the dudes in

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Speaker 1: Boy Mets World didn't you have a leather jacket too?

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Speaker 1: I don't remember. Yeah, probably the friend, like the cool

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Speaker 1: friend Sean shout out to my friend Nick. His dad

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Speaker 1: played Shawn's dad. Also another thing, the other side in

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Speaker 1: the movie Milk Money with Melanie Griffin, where the kids

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Speaker 1: save up money to go see a naked woman, so

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Speaker 1: they go to the city to try and higher prostitutes

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Speaker 1: to see a naked woman. I thought it was like

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Speaker 1: to marry their father. Well that's the initial reason why

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Speaker 1: they go meet her, and then they bring back like

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Speaker 1: she rules, yeah, let's have a day, and then like yeah,

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Speaker 1: Harris bade the dad. There's like this whole bet of

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Speaker 1: one of the kids getting the other kids leather jacket,

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Speaker 1: and like the second he went to school with the

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Speaker 1: leather jacket was like, oh ship, he got the leather jacket.

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Speaker 1: So I think that, yeah, there's a lot of misplaced

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Speaker 1: emphasis on the leather jacket. Yeah, just that it equals

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Speaker 1: awesomeness or something or bad boy two it or whatever

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Speaker 1: spoken like a real bad boy. Yeah you mentioned Brando.

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Speaker 1: I feel like the magnetism that Brando head is an

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Speaker 1: unparalleled thing we don't have access to apparently. Like they're

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Speaker 1: all these trends that I just thought were, you know,

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Speaker 1: standard trends, but they were all like Brando. Like the

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Speaker 1: way mobsters dress are all taken not from Brando and Godfather,

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Speaker 1: but like some other earlier movie like the Whole h

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Speaker 1: like same colored shirt and tie and suit was like

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Speaker 1: that that was initially pulled off by Brando. And like

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Speaker 1: there's all these different things that people just fucking loved

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Speaker 1: that guy. My mom is obsessed with fucking Marlon Brando.

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Speaker 1: But like it just because of his late career. Anybody

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Speaker 1: who was born like after the year well even like

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Speaker 1: the one where he was in yellow face like Teahouse

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Speaker 1: of August Moon or whatever, he literally in a Japanese

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Speaker 1: Mo's like love it. I'm like, like, you're really gone

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Speaker 1: over the deep end When this dude is mocking us

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Speaker 1: and you're like, yeah, he's handsome, I'm like damn, all right, Well,

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Speaker 1: but you don't each their own what's something you think

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Speaker 1: is underrated? Rush, I would go with um pairs, pairs.

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Speaker 1: I like this. I like apples, take all the thunder.

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Speaker 1: There's so many types of apples. There's maybe three types

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Speaker 1: of pears available to Ralph's or wherever, you know, and

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Speaker 1: I like app is fine, they're okay, But I just

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Speaker 1: feel like there's no pear sauce. There's no like you know,

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Speaker 1: there should be. You know what's good Kern's nectar, the

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Speaker 1: pear flavor. And I don't say a pair of juice

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Speaker 1: because it's juice. But I love pears in general because

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Speaker 1: also have you like you know, Asian pairs are like apples. Yeah,

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Speaker 1: when those are ripe and sweet, get the apples out

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Speaker 1: of here. That's how that's the guy. Yeah yeah, Bartlett

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Speaker 1: pears too. You know, I still I still ride for apples.

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Speaker 1: Really yeah? What's your best apple? Honey crisp? Okay? So

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Speaker 1: what you know we need to do is have a showdown,

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Speaker 1: throw down honey crisp apple versus like the Japanese na.

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Speaker 1: I like the Japanese pair, but I say it's my

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Speaker 1: favorite pair. No, no, no, I got far the crispiest

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Speaker 1: crunchest pair. But that it has nothing on the crispiest

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Speaker 1: crunchest apple, which is the honey crisp apple. Um. And

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Speaker 1: also I just don't like that country, like that part

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Speaker 1: of the world. I'm just not alright r I P.

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Speaker 1: You're mentioned all right. We're trying to take a sample

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Speaker 1: of the national share consciousness, what Americans are thinking about

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Speaker 1: talking about spiritually going through right now and the way

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Speaker 1: we like to open up his by asking our guest

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Speaker 1: what is a myth? What is something that most people

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Speaker 1: believe to be true that you know to be false? Rush, Well,

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Speaker 1: something I've done a lot of taking a lot of

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Speaker 1: personal interested in is whether or not shaving results in

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Speaker 1: a more thicker beard the more you shave. Because ever

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Speaker 1: heard that? Yeah? I thought it was true for the

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Speaker 1: longest time, but apparently it's completely untrue. Yeah, they say

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Speaker 1: that in Asia a lot too. Really, Yeah, like or

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Speaker 1: if you shave your head, your hair will go back thecker.

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Speaker 1: I've been doing that ship and it is not going back.

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Speaker 1: I believe this. This is a fucking myth, right, But

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Speaker 1: those they say that with babies too, Like I feel

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Speaker 1: like I heard like new parents being like, well, we

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Speaker 1: could shave the baby's head for the hair to come

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Speaker 1: back thicker. Yeah, like that might just be the baby

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Speaker 1: getting older, like growing more hair shape in the head. Yeah,

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Speaker 1: I bet it comes from just people having puberty mustaches

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Speaker 1: and then shaving them and the hair eventually becoming actual

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Speaker 1: facial hair, and then being like, see it got thicker.

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Speaker 1: It must have been my shaving that caused the thickness.

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Speaker 1: How did you first come across this myth? I thought

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Speaker 1: it was true, so I often would I have a

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Speaker 1: pretty strong beard or whatever, and would like take breaks

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Speaker 1: from shaving, And then I was like, well, let me

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Speaker 1: just actually see if this is true. Is there's something

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Speaker 1: some just some dude told me or whatever, you know,

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Speaker 1: I didn't hear it from like anybody who knows anything,

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Speaker 1: and it's apparently completely untrue. Yeah. I mean I still

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Speaker 1: don't understand the logic behind, like what the science behind

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Speaker 1: that would be if it were true. So it's hard

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Speaker 1: to believe, like, yeah, cutting your hair makes it grow,

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Speaker 1: like okay, but hey, look, if you if you guys

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Speaker 1: out there have a reason to make us believe that

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Speaker 1: we are wrong, I would love to know and then

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Speaker 1: give me that razor so I can reclaim some of

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Speaker 1: my hair. I think the people we need to talk

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Speaker 1: to about this. Are women who are like hair move

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Speaker 1: all experts and can tell you like how to remove

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Speaker 1: all hair anywhere. So uh, but yeah, because I had

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Speaker 1: always heard, uh, the women don't want to shave their

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Speaker 1: mustache because then it will grow back thicker and they'll

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Speaker 1: eventually look like ros And I, um, and did you

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Speaker 1: have any do you know have any insight to the

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Speaker 1: hair shaving debate, Like, leg hair grow back thicker? What's

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Speaker 1: the what's the consensus among women? Does shaving make hair

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Speaker 1: grow back thicker? Uh? In my experience, my leg hair

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Speaker 1: has grown back thicker. I have a little uh mustache

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Speaker 1: that I bleach. I don't shave it because my whole life,

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Speaker 1: my mom says if I shave, it will grow back

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Speaker 1: thicker and I will have an actual mustache. So I've

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Speaker 1: haven't tempted that. We haven't tested that one though we

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Speaker 1: could try it, but allow me so, I don't know.

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Speaker 1: Um said leg hair did grow back thicker. Yes, leg

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Speaker 1: hair always grows back thicker. I don't know why, it's

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Speaker 1: just always in my experience. Could it just be that

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Speaker 1: your body is producing more leg hair as it could

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Speaker 1: just be that I have like dark middle eastern hair jeans.

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Speaker 1: So I have, that's what I get. Um, I've always

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Speaker 1: been told to thread, to just just thread any facial

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Speaker 1: hair thread. Don't shave thread, have it pulled out from

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Speaker 1: the root. Feel the pain. And for men who don't

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Speaker 1: know what threading is, it is it's like an old

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Speaker 1: fashioned technique of using two pieces like a like a

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Speaker 1: torture method. Yeah, it's like you wrap the thread around

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Speaker 1: your hands and you use the friction of the thread

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Speaker 1: hitting or like rubbing against each other to pull hair

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Speaker 1: out of your face. It's look beauty is pains. My

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Speaker 1: mom always told me that is some real ship. Well,

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Speaker 1: thank you, Anna. Uh So let's move on to the stories,

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Speaker 1: uh and what people are talking about in the zeitgeist.

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Speaker 1: So over the weekend, there was a women's march on

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Speaker 1: Saturday that the mainstream media didn't make too much of

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Speaker 1: a dent. In the mainstream media. Apparently the Sunday shows

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Speaker 1: didn't really cover it, maybe because it wasn't quite as

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Speaker 1: big as last year's and so, you know, they felt

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Speaker 1: like the you know, the media always needs to go

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Speaker 1: bigger and there has to be sort of an arc

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Speaker 1: to their story. But it's wild how little they actually

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Speaker 1: spoke about it, like NBC I Think I'll Meet the Press.

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Speaker 1: Chuck Todd Show had I think the longest discussion about it,

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Speaker 1: and it was twenty seconds. Like other people just had

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Speaker 1: like in the opening monologue about like yeah, and women

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Speaker 1: are marching or like or people just referencing the march.

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Speaker 1: But it wasn't like a topic that was actually discussed

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Speaker 1: on those shows, and those are kind of those A

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Speaker 1: lot of people get their news from those Sunday morning shows,

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Speaker 1: so it's a little odd that they did that. And

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Speaker 1: then you couple that with like the straight fuckory on

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Speaker 1: Fox or they're like trying to spend those marches as

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Speaker 1: being something anything other than people pushing back on like

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Speaker 1: what this new administration's agenda has been with women. Uh yeah,

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Speaker 1: wait did they really try and push that agenda? Yeah? There, Well,

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Speaker 1: I know Trump tweeted some shi it is like oh yeah,

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Speaker 1: records like yeah, and I think that I mean, I

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Speaker 1: think on Fox they were kind of like walking that

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Speaker 1: tight rope of being like is that was that a joke?

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Speaker 1: Or what how are we really talking and blah blah blah.

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Speaker 1: It wasn't like that's how they were covering it. If

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Speaker 1: they even covered it at all, but that did come

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Speaker 1: up once or twice. Yeah, sort of the sarcastic trolling

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Speaker 1: from Trump and and uh, the Trump administration's propaganda wing

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Speaker 1: Fox News, Uh is really tone deaf when you like

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Speaker 1: look at it next to that Halsey poem. The artist

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Speaker 1: Halsey like unleashed this. You know, it's like a five

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Speaker 1: minute long poem of just growing up amid sexual assault

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Speaker 1: and sexual uh abuse and just you know, I don't know,

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Speaker 1: it's it's pretty affecting. And then to to then go

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Speaker 1: over to Twitter and read Trump be like ha ha,

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Speaker 1: good good day, good weather for all these women to

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Speaker 1: get up right there, it's like, come on the Yeah, Yeah,

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Speaker 1: that Halsy poem was very moving. I was, I mean,

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Speaker 1: she's I haven't really listened to her music, but yeah,

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Speaker 1: I mean neither, but now I'm gonna force myself to

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Speaker 1: because it was pretty dope. Yeah, and it was big

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Speaker 1: everywhere too, because like what I think, uh l A

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Speaker 1: probably had the biggest showing of all of all the cities,

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Speaker 1: right right, think that a half million people came out. Yeah,

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Speaker 1: well I think the estimates where two fifty thousand we're

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Speaker 1: going to come and five thousand people showed up. So

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Speaker 1: I went down there with my wife and her friend

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Speaker 1: and our son and it was pretty cool. It was

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Speaker 1: it was just cool to be there among you know,

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Speaker 1: all that positive energy. Uh. There were some Trump supporters

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Speaker 1: standing there with like Trump flags and like don't tread

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Speaker 1: on the flags that they were like three blocks away

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Speaker 1: from where where any of the people who were marching where.

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Speaker 1: It was like really weird, and they were like surrounded

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Speaker 1: by police barricades, but it wasn't clear like what they

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Speaker 1: were being protected from or what they were being held

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Speaker 1: back from because nobody was around them. They were just

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Speaker 1: on the street corner that was like completely barren and

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Speaker 1: like waving their flight. Yeah over here, where are you

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Speaker 1: gonna see? Like literally nobody could see you. Um. There

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Speaker 1: any funny signs at the protests? Yeah, yeah, there were

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Speaker 1: some good ones. Most of the ones that I saw

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Speaker 1: were on Twitter. Um. Uh. There was the one of uh,

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Speaker 1: notice how few Nazis are at our march was a

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Speaker 1: strong one. Yeah, I think the lack of Nazis. Yeah,

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Speaker 1: I noticed the lack. Yeah. Yeah. There was some Harry

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Speaker 1: Potter one that was like Harry would have been dead

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Speaker 1: in the first book without her mind Earth like that. Uh,

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Speaker 1: that was just where do I even begin? Exhausted? Yeah, uh,

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Speaker 1: there's I hate crowds, but I hate Trump more, which

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Speaker 1: is solid. This march is about accountability. Seven percent of

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Speaker 1: white women voted for misogyny. Well heavy, heavy, Well that's

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Speaker 1: wild because I think it was in Vegas, the head

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Speaker 1: of Planned Parenthood, Cecili Richards, she kind of made mention

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Speaker 1: to that in her the Women's March for Power to

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Speaker 1: the polls, where she was kind of saying like, hey,

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Speaker 1: like white women need to do better, which is you know,

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Speaker 1: pretty significant considering the sort of Yeah, I think we

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Speaker 1: have a clip of it. We can just kind of

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Speaker 1: play one part of what she said. All across the country,

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Speaker 1: the Women's March inspired doctors and teachers and mothers to

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Speaker 1: become activists of organizers and yes, Canada's for office, and

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Speaker 1: from Virginia to Alabama until last week in Wisconsin, women

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Speaker 1: have beaten the odds to elect our own the office.

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Speaker 1: That's right, women of color, transgender women, rural and urban women.

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Speaker 1: And these victories we're lead and made possible by women

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Speaker 1: of color. So right, so why women listen up. We've

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Speaker 1: got to do better. We've got to do better. They

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Speaker 1: should drop the mic, got the funk off stage. Yeah,

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Speaker 1: it was just the amount of coverage. It's wild how

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Speaker 1: much if you are on Twitter or you have your

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Speaker 1: own way of getting news, how much we were hearing

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Speaker 1: about this. But yeah, that's what makes the sort of

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Speaker 1: a mission of talking about it from these other shows

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Speaker 1: a little odd because I get it last year that

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Speaker 1: I was technically I think the largest demonstration in the

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Speaker 1: history of the country. And I guess what because there

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Speaker 1: wasn't a superlative this time. It wasn't Or is this

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Speaker 1: like some kind of weird subtle backlash of like, well,

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Speaker 1: I guess we're done talking about this? Like are the

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Speaker 1: producers of these shows saying, like, we're okay, We've got

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Speaker 1: millions of people out here, you don't want to talk

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Speaker 1: about it? Come on, that was last week's story. What

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Speaker 1: are we talking about this week? Right? Um? There's also

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Speaker 1: my neck, my back, my pussy will grab back. I

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Speaker 1: like that. Uh. There was also this episode of Black

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Speaker 1: Mirror Sucks, which is pretty good one. Um. Yeah, and

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Speaker 1: there were some speeches by Scarlett Johansson who specifically called

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Speaker 1: out I think it was actually implicitly called out James

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Speaker 1: Franco uh and then her publicists confirmed. People were like,

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Speaker 1: you were talking about James Franco right. Her publicists like

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Speaker 1: yes officially uh and Viola Davis. So uh those were

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Speaker 1: some people who gave pretty powerful speeches that the one

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Speaker 1: in Los Angeles, I believe. Uh. So all in pretty

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Speaker 1: I don't know, exciting movement and exciting weekend that just

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Speaker 1: didn't translate to the mainstream media for some reason. All right,

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Speaker 1: we'll take a quick break. We'll be right back, and

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Speaker 1: we're back. Uh. So the Democrats, Uh, the government is

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Speaker 1: back open, thank god? Fuck holding my breath. Well, the

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Speaker 1: I r S sent me some ship over the weekend

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Speaker 1: and I was like, oh, hell yeah, the government shut down,

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Speaker 1: so I could I could let this slide come out.

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Speaker 1: The fucking Democrats make a deal keep the government going again,

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Speaker 1: well at least for three weeks up until February eight.

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Speaker 1: So I don't know. This is kind of depends on

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Speaker 1: how far left you are, because people that are pretty

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Speaker 1: far left, like myself, uh, look at this and are like,

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Speaker 1: I think we just played ourselves because this they made

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Speaker 1: a deal to get this continuing resolution done. Uh. Because

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Speaker 1: Mitch McConnell said I intend to have a vote on

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Speaker 1: immigration on February nine, but I won't commit to any

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Speaker 1: specific legislation. And it was just a very kind of like, yeah,

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Speaker 1: well we'll vote on this. Well, we can bring a

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Speaker 1: vote on immigration, but that doesn't take into consideration like

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Speaker 1: the House or other things like that. And I know,

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Speaker 1: like people like um Dick Durban and stuff and their

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Speaker 1: Senate speeches are on the floor today. It seemed like

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Speaker 1: really optimistic, as if you know, Mitch McConnell had really

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Speaker 1: like come around and made them some kind of promises

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Speaker 1: that made them comfortable to make this deal. But the

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Speaker 1: other weird thing that makes that doesn't sit well with

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Speaker 1: me is like Susan Collins from Maine was like, hey,

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Speaker 1: you can trust Mitch McConnell. Meanwhile, this dude fucking played

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Speaker 1: her for her vote in the tax bill because she

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Speaker 1: was like, I need like Obamacare stabilization measures like put

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Speaker 1: into like a spending bill. Is like, yeah, yeah, you

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Speaker 1: get those, just vote on tax bill and that hasn't

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Speaker 1: happened at all. So I don't know this is I

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Speaker 1: think it's just terrible because we're playing with these dreamers

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Speaker 1: and people like we've already seen stories of people who

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Speaker 1: have lived here, like they're in their forties who were

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Speaker 1: brought here as kids, and they're getting deported, like ripped

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Speaker 1: from their families because we haven't sorted this out, and

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Speaker 1: it just it felt like a real moment where, you know,

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Speaker 1: the Democrats had a chance to stand up for these people,

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Speaker 1: and I think I think the optics kind of got

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Speaker 1: to them because it seemed like the polling was starting

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Speaker 1: to show that people were, like, you know, they weren't

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Speaker 1: as on message as Republicans. Kind Of to your point

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Speaker 1: on Friday, the Republicans kind of won the messaging war

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Speaker 1: in that it caused a group of moderates to kind

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Speaker 1: of cave and make a deal. Yeah. Well, it was

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Speaker 1: Susan Collins the one who was saying that the Democrats

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Speaker 1: were only holding out because some of them were going

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Speaker 1: to run for president in two thousand and twenty, and

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Speaker 1: they were trying to appeal to their base. Uh, it

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Speaker 1: might not have been hurt. It might have been Clara McCaskill,

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Speaker 1: for that's who was Clara mccaskell said that, And Yeah,

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Speaker 1: the messaging was just kind of all over the place

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Speaker 1: from the Democratic side. I think I think because Democrats

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Speaker 1: don't have their own Fox News all they have is

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Speaker 1: you know the Daly. Uh, they have crooked media, which

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Speaker 1: like probably most you know, democratic politicians are too old

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Speaker 1: to actually listen to or understand about. Yeah some dude.

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Speaker 1: But every time a politician comes on there, like my

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Speaker 1: daughter said that, you guys, it's like, come on that. Yeah.

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Speaker 1: Well they Democrats need to wake up because we're the

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Speaker 1: fucking people that if you want our vote, you got

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Speaker 1: to kind of come come with it. Yeah, I mean

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Speaker 1: Republicans can like all they do is watch Fox News,

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Speaker 1: internalize what Fox News is saying, and it's like this

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Speaker 1: feedback loop where everybody's on message. So yeah, we talked

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Speaker 1: about this on Friday. I'm just uh reiterating how right

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Speaker 1: I was. Um, I would say, it's a good time

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Speaker 1: to be the word stop gap. Definitely. It was all

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Speaker 1: over the place. Yeah, so they got McConnell to say

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Speaker 1: it is my intention as that is. Producer Nick Stunt

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Speaker 1: point out they couldn't even get an unequivocal, meaningless promise.

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Speaker 1: They just got like equivocating meaningless promise. Uh. That's like

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Speaker 1: you know when you make promises to people and like

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Speaker 1: they're like and you don't hold your end up. You're like, well,

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Speaker 1: I said that was my intention. Okay, you look back

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Speaker 1: at what I said. I didn't say I also promised

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Speaker 1: to totally hang out sometimes is my intention to stop

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Speaker 1: cheating on you. It is my intention after this. Yeah.

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Speaker 1: And also the thing that the Democrats are holding out

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Speaker 1: for for the Dreamers, um, I don't think they should

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Speaker 1: be in our cut now. Uh. It's basically just giving

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Speaker 1: them a path to citizenship, which is pretty I don't know,

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Speaker 1: it seems kind of weak. Uh. And it wasn't what

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Speaker 1: they were asking for in the first place. It's just

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Speaker 1: because the Republicans are better at messaging. They've slowly moved

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Speaker 1: everything towards you know, everything moves right because and also

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Speaker 1: because the Republicans control when they were pretty consistent with like, well,

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Speaker 1: these Democrats are fighting for illegal aliens before actual Americans

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Speaker 1: kind of thing, which is like absurd because again, anyway

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Speaker 1: we can I think most people already get that the

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Speaker 1: Republicans control all the branches of government and started this

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Speaker 1: whole mess in the first place, so hey, what are

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Speaker 1: we gonna do? Well? And also they're willing to Uh.

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Speaker 1: Chuck Schumer was saying, I think on Friday that he

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Speaker 1: was willing to fund Trump's wall. Yeah, he was, and

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Speaker 1: Trouble was like, na, still not good enough, motherfucker. Um

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Speaker 1: when he left and thinking that he was he did

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Speaker 1: have something that like it felt good, and then suddenly

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Speaker 1: he was like, actually not fam Yeah no. So he

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Speaker 1: met with Trump was like, all fund the wall, you

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Speaker 1: let dreamers have the possibility of staying in the country.

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Speaker 1: Great deal, good negotiating Democrats and Trump was like, yes, great,

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Speaker 1: That's what I wanted all along. And then of course,

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Speaker 1: you know John Kelly and Stephen Miller, uh getting and

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Speaker 1: they're like, no, ask for more, ask for more because uh,

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Speaker 1: John Kelly, we talked about a couple of months ago

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Speaker 1: when asked what the acceptable number of illegal immigrants coming

424
00:24:13,240 --> 00:24:17,040
Speaker 1: to coming across the border was. They were trying to decide,

425
00:24:17,480 --> 00:24:22,520
Speaker 1: you know, Obama administration had lowered it to you know,

426
00:24:22,720 --> 00:24:25,359
Speaker 1: two hundred thousand or a hundred fifty thousand. They were like,

427
00:24:25,760 --> 00:24:28,400
Speaker 1: you know, is it acceptable for us to get back

428
00:24:28,480 --> 00:24:30,960
Speaker 1: up to two hundred thousand. He was like, my acceptable

429
00:24:31,040 --> 00:24:34,280
Speaker 1: number is zero. Yeah. So that's the same dude who

430
00:24:34,320 --> 00:24:37,480
Speaker 1: was like slavery, we was a dope time for America. Uh,

431
00:24:37,680 --> 00:24:40,440
Speaker 1: We're not surprised, John Kelly. People kind of view him

432
00:24:40,480 --> 00:24:45,480
Speaker 1: as the you know, responsible parent, but he's actually incredible

433
00:24:45,600 --> 00:24:51,280
Speaker 1: racist immigration, like anti immigration hardliner who a couple of

434
00:24:51,280 --> 00:24:54,080
Speaker 1: that was Stephen Miller, Like in Trump's here, Like it's

435
00:24:54,080 --> 00:24:57,040
Speaker 1: wild because Trump is so impressionable that he'll be in

436
00:24:57,040 --> 00:24:59,120
Speaker 1: a meeting with one group of people and be like, yeah, okay,

437
00:24:59,119 --> 00:25:01,600
Speaker 1: that works, that works, and somebody just starts whisperings between

438
00:25:01,640 --> 00:25:03,800
Speaker 1: this other and he's like, oh yeah, like he I

439
00:25:03,840 --> 00:25:06,919
Speaker 1: mean like talk about utter lack of leadership like he

440
00:25:06,960 --> 00:25:10,359
Speaker 1: hasn't No, he has no judgment of his own. Also,

441
00:25:10,400 --> 00:25:13,240
Speaker 1: the Democrats are bad at metaphors. Chuck Schumer was saying,

442
00:25:13,440 --> 00:25:16,480
Speaker 1: negotiating with Trump is like trying to negotiate with Jello.

443
00:25:16,840 --> 00:25:20,320
Speaker 1: It's like, no, you're like trying to nail Jello down,

444
00:25:20,680 --> 00:25:23,680
Speaker 1: is what you're trying to say. But instead you've said

445
00:25:23,760 --> 00:25:28,320
Speaker 1: that it's like negotiating with Jello, which is an insane

446
00:25:28,400 --> 00:25:31,080
Speaker 1: metaphor that doesn't make any fucking sense. Can you just

447
00:25:31,119 --> 00:25:33,920
Speaker 1: show him talking to this is what I want? Right?

448
00:25:34,119 --> 00:25:38,520
Speaker 1: What do you say? As we all know from my experiences, Uh,

449
00:25:38,640 --> 00:25:41,359
Speaker 1: let's move on to better news. Guys, the super Bowl

450
00:25:41,400 --> 00:25:46,280
Speaker 1: is set or the Big Game. Don't say that's like,

451
00:25:46,400 --> 00:25:48,879
Speaker 1: do has anybody ever been sued for saying the super

452
00:25:48,880 --> 00:25:51,560
Speaker 1: Bowl on like a podcast? Oh yeah, I don't know,

453
00:25:51,640 --> 00:25:54,800
Speaker 1: but let's try it out. Super Bowl, super Bowl, super

454
00:25:54,800 --> 00:26:02,440
Speaker 1: Bow Bowl is set, super Bowl and Philadelphia Uh made it? Um? Yeah,

455
00:26:02,840 --> 00:26:08,400
Speaker 1: the stands were rowdy. The after party was rowdier. There's

456
00:26:08,400 --> 00:26:12,919
Speaker 1: a great video of a guy running after a train,

457
00:26:13,280 --> 00:26:16,919
Speaker 1: a train that he just missed, and just face planning

458
00:26:16,920 --> 00:26:21,200
Speaker 1: into a into a sign like it's it's literally out

459
00:26:21,200 --> 00:26:23,919
Speaker 1: of like a Fairly Brothers for a film. It's like

460
00:26:24,000 --> 00:26:27,280
Speaker 1: wait for me and it goes right to the steel beams.

461
00:26:27,800 --> 00:26:30,639
Speaker 1: If you, guys, I mean, these Eagles fans have been

462
00:26:30,720 --> 00:26:32,879
Speaker 1: nuts for you. He's been a story than the seventies

463
00:26:32,960 --> 00:26:38,280
Speaker 1: they boosted. Yeah, notorious right for having like the most

464
00:26:38,400 --> 00:26:42,119
Speaker 1: like aggressive fans, Like there's nothing worse than them hating

465
00:26:42,119 --> 00:26:45,640
Speaker 1: their own players. Right. Yeah, they booed Donovan McNabb when

466
00:26:45,640 --> 00:26:50,639
Speaker 1: he was drafted. He ended up being their best quarterback ever. Um,

467
00:26:50,680 --> 00:26:52,960
Speaker 1: there wasn't funny. Speaking of funny signs, some somebody in

468
00:26:53,000 --> 00:26:56,240
Speaker 1: the Eagles stand because they're playing Minnesota, had a funny

469
00:26:56,240 --> 00:27:04,640
Speaker 1: sign just just said Prince sucks. God damn. There were

470
00:27:04,680 --> 00:27:11,439
Speaker 1: signs up around the Colosseum or around where where the

471
00:27:11,440 --> 00:27:15,359
Speaker 1: game was being played, telling Vikings fans that after the

472
00:27:15,440 --> 00:27:18,200
Speaker 1: game take off they should take off their jersey when

473
00:27:18,280 --> 00:27:21,160
Speaker 1: leaving so they don't get like attacked and beat up.

474
00:27:21,400 --> 00:27:24,399
Speaker 1: They were like public service and apparently they were like

475
00:27:24,440 --> 00:27:28,399
Speaker 1: throwing stuff at Vikings fans as they walked into the

476
00:27:28,440 --> 00:27:32,120
Speaker 1: game and then they just like beat them mercilessly. So

477
00:27:32,359 --> 00:27:34,240
Speaker 1: were there like were they merciful and they're like, hey,

478
00:27:34,280 --> 00:27:36,560
Speaker 1: look you obviously took alice. We're not going to rob

479
00:27:36,640 --> 00:27:38,920
Speaker 1: you now. Yeah. I think they just took it out

480
00:27:38,920 --> 00:27:42,400
Speaker 1: on light poles. Apparently light poles are a big concerned

481
00:27:42,480 --> 00:27:46,600
Speaker 1: because the police took precautions, like as the game started

482
00:27:46,600 --> 00:27:49,159
Speaker 1: getting out of control and like this the Eagles were

483
00:27:49,240 --> 00:27:51,840
Speaker 1: up by a couple of touchdowns, the police started greasing

484
00:27:51,920 --> 00:27:56,080
Speaker 1: up street poles with fans of Friscoe. Uh oh. It

485
00:27:56,119 --> 00:27:58,520
Speaker 1: was apparently at least four hours before the game, and

486
00:27:59,119 --> 00:28:03,240
Speaker 1: like knowing that if the Eagles won, uh, everybody would

487
00:28:03,280 --> 00:28:05,600
Speaker 1: be trying to find that I love it. They're so

488
00:28:06,359 --> 00:28:08,639
Speaker 1: they're like, and do we have our seventy gallons of

489
00:28:08,720 --> 00:28:11,960
Speaker 1: Chris or if the case we win, yeah, we've got

490
00:28:11,960 --> 00:28:15,440
Speaker 1: a more on proof of the city. Yeah, yeah, exactly, man,

491
00:28:15,720 --> 00:28:18,439
Speaker 1: you know, good for the Eagles. I'm not Look, as

492
00:28:18,520 --> 00:28:20,440
Speaker 1: most people know, I'm not a huge NFL fan because

493
00:28:20,560 --> 00:28:23,359
Speaker 1: last time I've checked on the Eagles, do Staley was playing,

494
00:28:23,920 --> 00:28:26,360
Speaker 1: So that shows you were what you're I'm operating from

495
00:28:26,960 --> 00:28:28,719
Speaker 1: good to them. Shout out to the homie Chris too,

496
00:28:28,760 --> 00:28:30,399
Speaker 1: because I know that's his team, so you know we're

497
00:28:30,480 --> 00:28:33,359
Speaker 1: rooting for y'all. The Patriots also made it, which do

498
00:28:33,440 --> 00:28:35,919
Speaker 1: we even have to say the only good thing? It

499
00:28:36,000 --> 00:28:38,640
Speaker 1: was actually a really good game and they almost lost.

500
00:28:38,920 --> 00:28:44,600
Speaker 1: And I am a ashamed Patriots fan. Uh since you are? Yeah, yeah,

501
00:28:44,720 --> 00:28:48,760
Speaker 1: since back? You're back before when when they were like

502
00:28:48,800 --> 00:28:51,920
Speaker 1: the underdogs going up against like the unbeatable St. Louis

503
00:28:52,040 --> 00:28:55,960
Speaker 1: Ram's offense, and uh rookie Tom Brady came out of

504
00:28:55,960 --> 00:28:58,560
Speaker 1: nowhere to to beat them. Yeah. But I've been a

505
00:28:58,560 --> 00:29:00,440
Speaker 1: fan since I was in high school. I used to

506
00:29:00,480 --> 00:29:03,959
Speaker 1: go to Patriots games and watch fucking Drew Bledsoe when

507
00:29:04,000 --> 00:29:09,080
Speaker 1: they sucking Vinnie testiverdian ship. Yeah yeah, so uh yeah,

508
00:29:09,280 --> 00:29:11,480
Speaker 1: I didn't realize. You know, that's so funny because you

509
00:29:12,520 --> 00:29:14,440
Speaker 1: act like you're a neutral and then suddenly you're like

510
00:29:14,560 --> 00:29:18,160
Speaker 1: I'm an ashamed Patriots man. Wow, look at you. It's dark.

511
00:29:18,320 --> 00:29:22,120
Speaker 1: It's it's also Robert Kraft. Yeah, exactly know. But my

512
00:29:22,160 --> 00:29:24,360
Speaker 1: favorite story about him is how Putin fucking straight up

513
00:29:24,400 --> 00:29:27,479
Speaker 1: stole his Super Bowl rate. Right. He Putin asked like

514
00:29:27,600 --> 00:29:30,280
Speaker 1: to see his Super Bowl ring like a bully and

515
00:29:30,600 --> 00:29:33,800
Speaker 1: like third grade and let me see that and just

516
00:29:33,920 --> 00:29:37,280
Speaker 1: walked out and Craft was like, wait, where is he going? Right?

517
00:29:37,480 --> 00:29:40,320
Speaker 1: And apparently the KG you guys straight up like created

518
00:29:40,320 --> 00:29:42,440
Speaker 1: old like put a block up for him, like a

519
00:29:42,640 --> 00:29:46,240
Speaker 1: get out of here. Um, here are some things that

520
00:29:46,320 --> 00:29:47,800
Speaker 1: you could have heard if you were listening in on

521
00:29:47,920 --> 00:29:52,640
Speaker 1: the Philadelphia police uh scanner last night. Uh, this is

522
00:29:52,720 --> 00:29:56,760
Speaker 1: Sports Illustrated. The wait they were using they were the police, Yeah,

523
00:29:56,800 --> 00:30:00,120
Speaker 1: they're listening police scanner. Uh. Quote, we've got a guy

524
00:30:00,160 --> 00:30:02,880
Speaker 1: climbing a light pole, so that Chris did not work.

525
00:30:05,960 --> 00:30:11,800
Speaker 1: Then immediately like I'm gonna climb that ship. Uh there's

526
00:30:11,800 --> 00:30:13,960
Speaker 1: a guy running nude. He's carrying a green T shirt

527
00:30:14,000 --> 00:30:17,160
Speaker 1: and a pair of jeans, blackmail and cowboy hat, throwing

528
00:30:17,200 --> 00:30:21,400
Speaker 1: fireworks into the crowd. Uh. Police officers made a call

529
00:30:21,520 --> 00:30:25,120
Speaker 1: for a strike force team. Uh, we're going to get

530
00:30:25,160 --> 00:30:28,840
Speaker 1: people off the statue. Next he's standing on top of

531
00:30:28,880 --> 00:30:32,760
Speaker 1: the bus stand. We lost the intersection, like it's like

532
00:30:32,760 --> 00:30:38,800
Speaker 1: a military yeah, territory. Uh. There was a bus with

533
00:30:38,960 --> 00:30:43,000
Speaker 1: NFL personnel that was stuck in traffic like they couldn't

534
00:30:43,040 --> 00:30:46,280
Speaker 1: get out of the game because of just the citywide

535
00:30:46,360 --> 00:30:49,520
Speaker 1: riot happening. And the police said, we have a crowd

536
00:30:49,560 --> 00:30:53,600
Speaker 1: breaking out their windows. Nobody got hurt though, right, No,

537
00:30:53,720 --> 00:30:56,280
Speaker 1: I don't think so, other than that guy who face

538
00:30:56,320 --> 00:30:59,520
Speaker 1: planted into that. Yeah, that was that's worth that's worth

539
00:30:59,600 --> 00:31:03,480
Speaker 1: checking out. Um. Well that's good. Yeah. Yeah, I'm glad

540
00:31:03,760 --> 00:31:06,440
Speaker 1: that these things to be so cathartic for people. So

541
00:31:06,720 --> 00:31:09,760
Speaker 1: you know, you know, despite the cris go keep keep

542
00:31:09,760 --> 00:31:16,360
Speaker 1: ascending that pool, y'all right? Uh and all right, uh,

543
00:31:16,400 --> 00:31:19,440
Speaker 1: we're gonna move on to Amazon Go. The Store of

544
00:31:19,480 --> 00:31:24,280
Speaker 1: the Future has opened in Seattle. Um New York Times

545
00:31:24,320 --> 00:31:27,840
Speaker 1: Center reporter and you know they said that it is

546
00:31:28,520 --> 00:31:30,920
Speaker 1: it's sort of a game changer. So what this is

547
00:31:31,240 --> 00:31:36,080
Speaker 1: it is a store that has like cameras all over

548
00:31:36,120 --> 00:31:40,520
Speaker 1: the place. Uh, and you walk through the gates, they

549
00:31:40,560 --> 00:31:44,680
Speaker 1: identify you by you or Amazon account, and then you

550
00:31:44,800 --> 00:31:48,680
Speaker 1: just like put stuff in your bag off the shelves. Uh.

551
00:31:48,720 --> 00:31:53,160
Speaker 1: And walk out like your shoplifting, and because of the

552
00:31:53,200 --> 00:31:58,520
Speaker 1: cameras and presumably facial recognition technology, Uh, they know everything

553
00:31:58,800 --> 00:32:01,440
Speaker 1: you got. You just walk out and then five minutes

554
00:32:01,520 --> 00:32:04,040
Speaker 1: later you get a bill for everything you just walked

555
00:32:04,040 --> 00:32:07,280
Speaker 1: out with. Um M. And the New York Times reporter

556
00:32:07,400 --> 00:32:11,200
Speaker 1: even tried to shoplift. He like put his bag over

557
00:32:11,240 --> 00:32:15,080
Speaker 1: a thing and then like kind of surreptitiously put it

558
00:32:15,160 --> 00:32:17,840
Speaker 1: like away and then walked out with it in the bag.

559
00:32:17,920 --> 00:32:20,880
Speaker 1: And uh they still they still charge. Now let me

560
00:32:20,880 --> 00:32:24,480
Speaker 1: get in there, right, I bet it. That's the you

561
00:32:24,520 --> 00:32:26,880
Speaker 1: know what it's calling all people who have a habit

562
00:32:26,920 --> 00:32:31,120
Speaker 1: of boosting ship. That's like the fucking boss level of

563
00:32:31,240 --> 00:32:32,840
Speaker 1: trying to push it from a store. If you can

564
00:32:32,920 --> 00:32:34,560
Speaker 1: fucking walk out of there with like a bottle of

565
00:32:34,600 --> 00:32:37,440
Speaker 1: coke or something down your pantent leg or however whatever

566
00:32:37,480 --> 00:32:40,480
Speaker 1: method you use, Uh always pant leg right, Yeah, is

567
00:32:40,520 --> 00:32:43,360
Speaker 1: there ever a better method than pant leg or like

568
00:32:43,400 --> 00:32:45,160
Speaker 1: I had the homie fucking walk out with the London

569
00:32:45,200 --> 00:32:47,560
Speaker 1: broil once, like full on piece of fucking meat like

570
00:32:47,640 --> 00:32:50,320
Speaker 1: a roast in his in his pants, like in the crotch.

571
00:32:51,360 --> 00:32:53,720
Speaker 1: He's a legend, And we still ate the food. Wow

572
00:32:53,880 --> 00:32:56,600
Speaker 1: that you ate a London broil that was crotch store

573
00:32:57,920 --> 00:33:00,520
Speaker 1: and the heat cooks off. Any of that pleases rink?

574
00:33:00,520 --> 00:33:03,920
Speaker 1: Why am I on? Try? Okay? I like that. Like

575
00:33:03,960 --> 00:33:06,800
Speaker 1: the first Amazon Ghost store opens in Los Angeles and

576
00:33:06,880 --> 00:33:11,080
Speaker 1: miles it's like the last scene of of Thomas Crown Affair,

577
00:33:11,160 --> 00:33:15,360
Speaker 1: like going with like five dudes and identical hats, like, yeah,

578
00:33:15,400 --> 00:33:18,560
Speaker 1: we all drop a drop a briefcase that like emmits smoke.

579
00:33:19,320 --> 00:33:22,760
Speaker 1: I have people like that mathematical distance between their eyes,

580
00:33:22,800 --> 00:33:24,760
Speaker 1: so like the friend and kind of get a jump

581
00:33:24,760 --> 00:33:27,120
Speaker 1: on the face scanning software wearing some class anyway, Yeah,

582
00:33:27,120 --> 00:33:30,520
Speaker 1: I look for that. But yeah, this this store is

583
00:33:30,800 --> 00:33:33,600
Speaker 1: interesting to me because a I feel like it's smart

584
00:33:33,760 --> 00:33:36,000
Speaker 1: and that you will walk in there and not really

585
00:33:36,000 --> 00:33:37,640
Speaker 1: have an idea of what you're buying or like what

586
00:33:37,640 --> 00:33:39,120
Speaker 1: you're gonna pay for it. And I feel like a

587
00:33:39,160 --> 00:33:40,800
Speaker 1: lot of people are gonna go their first trip to

588
00:33:40,840 --> 00:33:42,320
Speaker 1: the Amazon Ghost or they're gonna walk out and that

589
00:33:42,400 --> 00:33:43,840
Speaker 1: notice comes on there from like well I just spent

590
00:33:43,960 --> 00:33:46,920
Speaker 1: ninety eight dollars on a bunch of ship Because that

591
00:33:46,960 --> 00:33:49,320
Speaker 1: happens like the first time you get the Whole Food

592
00:33:49,360 --> 00:33:53,760
Speaker 1: Salad bar and you're like, yeah, they're like, I shouldn't

593
00:33:53,800 --> 00:33:57,959
Speaker 1: put all that beans and are heavy. H that is

594
00:33:59,000 --> 00:34:03,480
Speaker 1: classic Rookey miss yeah being never anything being based. Keep

595
00:34:03,480 --> 00:34:06,080
Speaker 1: it leafy, a little bit of protein, but yeah, yeah,

596
00:34:06,200 --> 00:34:09,480
Speaker 1: keep it leafy. That's a good way. But it is

597
00:34:10,080 --> 00:34:15,440
Speaker 1: because it's Amazon. It will have certain whole foods yea

598
00:34:15,719 --> 00:34:21,120
Speaker 1: food amenities, and there is a chef who's like off

599
00:34:21,160 --> 00:34:24,040
Speaker 1: on the side making like pre made foods for people.

600
00:34:24,760 --> 00:34:28,359
Speaker 1: So yeah, it is going to be that uh where

601
00:34:28,360 --> 00:34:31,400
Speaker 1: you get like some rice and like an entree and

602
00:34:31,480 --> 00:34:35,440
Speaker 1: it's like four dollars get a couple of scoops less

603
00:34:35,480 --> 00:34:38,080
Speaker 1: of that, right, and then realized how much that cost. Yeah,

604
00:34:38,239 --> 00:34:40,759
Speaker 1: And I've always been too ashamed to, like you were

605
00:34:40,760 --> 00:34:42,760
Speaker 1: talking about how this will be a game changer because

606
00:34:42,760 --> 00:34:45,279
Speaker 1: people will only find out once they've left. But I've

607
00:34:45,280 --> 00:34:48,200
Speaker 1: always been too ashamed to like put the stuff back.

608
00:34:48,520 --> 00:34:50,399
Speaker 1: I've just been like, yeah, I know that was the plan.

609
00:34:50,600 --> 00:34:55,200
Speaker 1: I meant to spend eight dollars, man, I'm shameless person, man,

610
00:34:55,239 --> 00:34:58,560
Speaker 1: when the funds are light. Yeah, I used to you know,

611
00:34:58,680 --> 00:34:59,960
Speaker 1: you used to be like, oh, I gotta take the

612
00:35:00,000 --> 00:35:02,239
Speaker 1: stuff back, like you know what. Put my arm down,

613
00:35:02,280 --> 00:35:05,759
Speaker 1: like everything past year, I don't want. Now let me

614
00:35:05,840 --> 00:35:09,839
Speaker 1: leave with like my Current's nectar. Current's Nectar is really

615
00:35:09,840 --> 00:35:11,840
Speaker 1: getting a lot of shout outs on this podcast. That

616
00:35:11,960 --> 00:35:14,359
Speaker 1: and Dominoes also shout out to people on Twitter who

617
00:35:14,400 --> 00:35:16,799
Speaker 1: are really trying to get us that Domino's endorsement TiAl

618
00:35:16,800 --> 00:35:21,440
Speaker 1: because you're really fucking praising the pizza gods anyway. But

619
00:35:21,480 --> 00:35:23,560
Speaker 1: the other thing I was interesting is like, you know,

620
00:35:23,760 --> 00:35:26,080
Speaker 1: a lot of people are kind of critical too, because clearly,

621
00:35:26,120 --> 00:35:28,880
Speaker 1: like this is the kind of story that humans don't

622
00:35:28,880 --> 00:35:31,480
Speaker 1: want because it requires like maybe four people to work

623
00:35:31,520 --> 00:35:34,719
Speaker 1: the entire thing. So that's like a precursor of like

624
00:35:34,800 --> 00:35:38,920
Speaker 1: the the robots took her jobs. H And also like

625
00:35:39,120 --> 00:35:41,120
Speaker 1: help about the people who are on food stamps? You know,

626
00:35:41,160 --> 00:35:44,080
Speaker 1: why can't you use that ship at Amazon go? You know?

627
00:35:44,160 --> 00:35:45,719
Speaker 1: And I think they're they are, I know, they are

628
00:35:46,040 --> 00:35:48,320
Speaker 1: like participating some kind of pilot program the u s

629
00:35:48,360 --> 00:35:51,719
Speaker 1: t a to to accept food stamps. But there's something

630
00:35:51,800 --> 00:35:54,680
Speaker 1: kind of very sort of classist about like, hey, do

631
00:35:54,680 --> 00:35:56,640
Speaker 1: you have a like smartphone with the ability to have

632
00:35:56,719 --> 00:35:58,120
Speaker 1: this app to walk through and do you have an

633
00:35:58,120 --> 00:36:00,640
Speaker 1: Amazon account? And blah blah blah. It's not like anybody

634
00:36:00,640 --> 00:36:04,239
Speaker 1: who's go in. Yeah, I know Amazon is evil. They're

635
00:36:04,280 --> 00:36:07,600
Speaker 1: going to just slowly take over the world. I was

636
00:36:07,640 --> 00:36:10,880
Speaker 1: just all a where an Amazon bookstore just opened up?

637
00:36:10,920 --> 00:36:13,799
Speaker 1: And it's all it is is Barnes and Noble but

638
00:36:13,880 --> 00:36:17,120
Speaker 1: connected to like your Amazon account essentially. Wait, where is

639
00:36:17,120 --> 00:36:19,439
Speaker 1: there an Amazon bookstore, like a physical one here? Yeah,

640
00:36:19,680 --> 00:36:25,080
Speaker 1: in the Century City mall of course. And uh I

641
00:36:25,120 --> 00:36:26,960
Speaker 1: went in. I was like, oh man, I missed these

642
00:36:26,960 --> 00:36:31,239
Speaker 1: bookstores that Amazon put out of here, Like Amazon's opening there.

643
00:36:31,440 --> 00:36:33,600
Speaker 1: But you pay. It's not like an Amazon Go model

644
00:36:33,640 --> 00:36:35,200
Speaker 1: where you just walk the funk out with no. No,

645
00:36:35,320 --> 00:36:39,560
Speaker 1: you have to pay somebody human. Yeah, we're gonna have

646
00:36:39,560 --> 00:36:41,640
Speaker 1: to start asking that now about new businesses like and

647
00:36:41,680 --> 00:36:45,160
Speaker 1: do they employ humans? And it's all it's all just

648
00:36:45,719 --> 00:36:48,520
Speaker 1: a way to get you to become an Amazon Prime

649
00:36:48,680 --> 00:36:51,600
Speaker 1: member because they like give you off in the story

650
00:36:51,840 --> 00:36:55,400
Speaker 1: if your prime come up, Prime member, if you come no,

651
00:36:55,520 --> 00:36:57,640
Speaker 1: I think it's actually a few if you Yeah, we

652
00:36:57,719 --> 00:37:00,000
Speaker 1: gotta When you just raised the price on that ship too,

653
00:37:00,680 --> 00:37:03,200
Speaker 1: Uh yeah, where did it go from like ten n

654
00:37:03,360 --> 00:37:05,239
Speaker 1: twelve and nine or something? I think it got up

655
00:37:05,280 --> 00:37:09,719
Speaker 1: to but they didn't change the annual one. So that's

656
00:37:09,719 --> 00:37:11,560
Speaker 1: how they get you. Yeah, and I mean this is

657
00:37:11,600 --> 00:37:16,000
Speaker 1: part of a broader trend of corporations sort of these

658
00:37:16,120 --> 00:37:21,200
Speaker 1: big main corporations like Google, Amazon, Apple, you know, sort

659
00:37:21,239 --> 00:37:27,000
Speaker 1: of taking over. Um, there's been a slight adjustment towards

660
00:37:27,120 --> 00:37:32,040
Speaker 1: people realizing that these companies are not your friends, and uh,

661
00:37:32,080 --> 00:37:35,200
Speaker 1: anything free that they're giving to you, they are doing

662
00:37:35,239 --> 00:37:39,960
Speaker 1: that by selling off information about you to advertisers. But

663
00:37:40,080 --> 00:37:44,160
Speaker 1: for instance, there is a tech experiment happening in Toronto

664
00:37:45,080 --> 00:37:48,960
Speaker 1: where one of the alphabet companies, one of Google's corporate siblings,

665
00:37:49,840 --> 00:37:53,920
Speaker 1: is trying to plan a futuristic metropolis that is just

666
00:37:54,080 --> 00:37:58,359
Speaker 1: straight out of the movie RoboCop. Like it's yeah, so

667
00:37:58,440 --> 00:38:02,920
Speaker 1: it's called Keyside, and it's like a real derelict rundown

668
00:38:03,000 --> 00:38:07,120
Speaker 1: part of Toronto, and it'll be laden with sensors and

669
00:38:07,280 --> 00:38:10,799
Speaker 1: cameras tracking everyone who lives, works, or merely passes through

670
00:38:10,840 --> 00:38:16,319
Speaker 1: the area. And uh sidewalk is the Google affiliate calls

671
00:38:16,360 --> 00:38:20,879
Speaker 1: it the marriage of technology and urbanism. But yeah, I mean,

672
00:38:20,880 --> 00:38:24,040
Speaker 1: we've talked before about how crazy the world is going

673
00:38:24,080 --> 00:38:27,920
Speaker 1: to be once there's facial recognition scanners everywhere, Like crime

674
00:38:28,040 --> 00:38:31,200
Speaker 1: will be over, which seems like a good thing, but

675
00:38:31,560 --> 00:38:33,680
Speaker 1: companies will always know where you are. So you know,

676
00:38:33,719 --> 00:38:36,239
Speaker 1: what we should do now is invest in masks that

677
00:38:36,320 --> 00:38:39,320
Speaker 1: you can wear that obscure your face from facial scanning

678
00:38:39,360 --> 00:38:40,839
Speaker 1: so you can do dirt out there. You could buy

679
00:38:40,920 --> 00:38:42,719
Speaker 1: you know, do whatever you gotta do in the dark

680
00:38:42,719 --> 00:38:45,800
Speaker 1: part of town with no shame. I don't know. I

681
00:38:45,840 --> 00:38:48,040
Speaker 1: think that's like, I think that's the secondary pirate market

682
00:38:48,080 --> 00:38:50,440
Speaker 1: to like protect people from all the spatial recognition software

683
00:38:50,480 --> 00:38:55,120
Speaker 1: is like facial obscuring like devices or whatever. It's worth

684
00:38:55,239 --> 00:38:59,160
Speaker 1: kind of checking out how countries like Germany and Italy

685
00:38:59,239 --> 00:39:03,000
Speaker 1: are a reacting too. Uh, some of these bigger tech companies,

686
00:39:03,040 --> 00:39:05,799
Speaker 1: they're kind of giving them a much harder time over there,

687
00:39:06,080 --> 00:39:09,400
Speaker 1: Um because they're more suspicious of these things they have

688
00:39:09,520 --> 00:39:14,960
Speaker 1: us of like how how absolute power works and yeah,

689
00:39:15,239 --> 00:39:17,400
Speaker 1: because yeah, it'll leaves like seeing Apple for their like

690
00:39:17,480 --> 00:39:21,640
Speaker 1: sort of planned obsolescens scheme with iPhones. Uh, and wait,

691
00:39:21,680 --> 00:39:23,120
Speaker 1: what's going on with Germany? Are they doing the same

692
00:39:23,120 --> 00:39:28,480
Speaker 1: thing over Facebook and hate speech on Facebook? They're basically

693
00:39:28,520 --> 00:39:32,080
Speaker 1: making it so that it's illegal for Facebook to keep

694
00:39:32,680 --> 00:39:37,520
Speaker 1: something up on Facebook for very long if it's alive,

695
00:39:37,719 --> 00:39:41,920
Speaker 1: that is, you know, in some way promoting heat right. Um,

696
00:39:42,000 --> 00:39:46,839
Speaker 1: and uh, Apple so this is more of a personal thing,

697
00:39:47,560 --> 00:39:51,040
Speaker 1: but Apple has continued to you know, we talked about

698
00:39:51,680 --> 00:39:53,920
Speaker 1: I think a couple of months ago about how we

699
00:39:53,920 --> 00:39:59,279
Speaker 1: were all doing the latest iOS update to eleven and

700
00:39:59,440 --> 00:40:03,000
Speaker 1: our phone said started running slow. Um, you know we

701
00:40:03,040 --> 00:40:08,200
Speaker 1: had sixes or fives or you know, a seven. And

702
00:40:08,840 --> 00:40:13,920
Speaker 1: since that time, it's not like Apple fixed that incompatibility. Uh,

703
00:40:14,080 --> 00:40:15,919
Speaker 1: you know, since that time, there's been a big news

704
00:40:15,920 --> 00:40:20,040
Speaker 1: story about how Apple was slowing down older phones. Uh,

705
00:40:20,080 --> 00:40:24,239
Speaker 1: in order to people suspected encourage people to you know,

706
00:40:24,440 --> 00:40:28,400
Speaker 1: upgrade their phones. Apple said it was to you know,

707
00:40:28,920 --> 00:40:33,640
Speaker 1: protect people's batteries on older phones. But also have you

708
00:40:33,640 --> 00:40:37,000
Speaker 1: guys ever heard Tim Cook speak? I mean, it's an

709
00:40:37,000 --> 00:40:39,680
Speaker 1: interview with him. He's just like he sounds like kind

710
00:40:39,719 --> 00:40:44,240
Speaker 1: of a southern he He doesn't sound like a powerful scene.

711
00:40:45,360 --> 00:40:47,719
Speaker 1: Yeah he sounds he doesn't even sound like a nerd. Yeah,

712
00:40:47,719 --> 00:40:52,600
Speaker 1: he just sounds like an unassuming kind of dummy. Uh.

713
00:40:52,719 --> 00:40:56,520
Speaker 1: But anyways, he was he was just completely you know what,

714
00:40:57,040 --> 00:41:00,200
Speaker 1: and we were so shocked that people were upset by this.

715
00:41:00,440 --> 00:41:04,720
Speaker 1: But uh, justin yeah, just an update on the whole

716
00:41:04,960 --> 00:41:09,080
Speaker 1: force obsolescence thing. Here at the Daily zeit Geist, I

717
00:41:09,120 --> 00:41:11,840
Speaker 1: had to upgrade my phone because it broke because of

718
00:41:11,880 --> 00:41:15,400
Speaker 1: the io S, update miles and upgrade my ship. It

719
00:41:15,480 --> 00:41:19,680
Speaker 1: was on my phone was virtually like unusable. Yeah, Sophie,

720
00:41:20,040 --> 00:41:23,200
Speaker 1: same deal. Our project manager just over the weekend, her

721
00:41:23,239 --> 00:41:26,320
Speaker 1: phone just stopped working and she went to the Verizon

722
00:41:26,400 --> 00:41:28,920
Speaker 1: store and the person at Verizon was like, oh, yeah, no,

723
00:41:29,000 --> 00:41:32,480
Speaker 1: Apple knows they're doing this, and like basically came clean

724
00:41:32,560 --> 00:41:35,600
Speaker 1: about like the stuff that Apple probably doesn't want them

725
00:41:35,640 --> 00:41:40,320
Speaker 1: to say. Uh so yeah, that's still happening. Um, and

726
00:41:40,560 --> 00:41:43,719
Speaker 1: you know, these are the companies that, uh we we've

727
00:41:43,760 --> 00:41:46,080
Speaker 1: put a lot of trust in. Yeah, they have my

728
00:41:46,120 --> 00:41:48,680
Speaker 1: goddamn face information, right, I mean I know they say

729
00:41:48,680 --> 00:41:54,920
Speaker 1: they don't store that or whatever, but I can't trust it. Um. Yeah,

730
00:41:55,040 --> 00:41:58,480
Speaker 1: the you know there there's that Google app that matches

731
00:41:58,520 --> 00:42:05,000
Speaker 1: your face to a painting and uh, you did it right? Yes?

732
00:42:05,000 --> 00:42:08,240
Speaker 1: I was Martin Luther the King. Uh really Yeah that's awesome.

733
00:42:09,040 --> 00:42:15,960
Speaker 1: I was a random eighteen hundreds woman and and also

734
00:42:16,000 --> 00:42:19,560
Speaker 1: a dude who like really looked like an unflattering version

735
00:42:19,560 --> 00:42:24,200
Speaker 1: of me, but like his eyes were like the same. Yeah,

736
00:42:24,200 --> 00:42:26,759
Speaker 1: it just it just looked very similar. But um that

737
00:42:27,000 --> 00:42:31,080
Speaker 1: those that specific app is illegal in like Texas and

738
00:42:31,160 --> 00:42:35,880
Speaker 1: one other country for one other state because because of

739
00:42:35,920 --> 00:42:39,160
Speaker 1: facial recognition. Yeah, it can't be for like they said

740
00:42:39,200 --> 00:42:42,360
Speaker 1: it was unspecific reasons or whatever, because they didn't clearly

741
00:42:42,360 --> 00:42:45,000
Speaker 1: define what they were doing with that information. So yeah,

742
00:42:45,200 --> 00:42:48,600
Speaker 1: so uh shout out to Texas. At the very least,

743
00:42:48,600 --> 00:42:51,239
Speaker 1: we're headed for the future of Minority Report, where like

744
00:42:51,440 --> 00:42:56,280
Speaker 1: ads are just beamed directly into our phases, um, based

745
00:42:56,320 --> 00:42:59,640
Speaker 1: on our purchase. Like that was the thing that Minority

746
00:42:59,680 --> 00:43:02,479
Speaker 1: Report got wrong, is that it was beaming the same

747
00:43:02,560 --> 00:43:05,080
Speaker 1: add to everybody. And that's not gonna be happening. They're

748
00:43:05,080 --> 00:43:09,360
Speaker 1: gonna be talking specifically. It won't be automated like Miles

749
00:43:09,480 --> 00:43:14,360
Speaker 1: by Mercedes Benz. These are the new Nike shoes, Kern's

750
00:43:14,440 --> 00:43:18,360
Speaker 1: nectar flavors, and blood wraps. So those are all the

751
00:43:18,440 --> 00:43:20,160
Speaker 1: things that I'm on my way to the store now

752
00:43:20,360 --> 00:43:25,160
Speaker 1: right exactly. Um. And finally, in a bit of good

753
00:43:25,160 --> 00:43:29,480
Speaker 1: news for the little guy, Amazon has announced its list

754
00:43:30,120 --> 00:43:34,200
Speaker 1: of the you know finalists for its h Q two.

755
00:43:34,640 --> 00:43:37,319
Speaker 1: This was great because all the small cities were gave

756
00:43:37,360 --> 00:43:40,640
Speaker 1: him opportunities like maybe we can have right. Frisco, Texas

757
00:43:40,719 --> 00:43:44,840
Speaker 1: put together one of the more impressive like recruiting videos

758
00:43:44,880 --> 00:43:48,160
Speaker 1: that they, you know, put on YouTube, like hey, Amazon,

759
00:43:48,320 --> 00:43:52,200
Speaker 1: come to Frisco, Texas. It's an up and coming city. Uh.

760
00:43:52,239 --> 00:43:56,759
Speaker 1: And so their list of twenty of the finalists is

761
00:43:56,800 --> 00:43:59,600
Speaker 1: basically a list of the twenty biggest cities in America.

762
00:43:59,680 --> 00:44:02,799
Speaker 1: For the part, it's like, Um, New York. Have you

763
00:44:02,840 --> 00:44:04,840
Speaker 1: heard of this place? You guys, it might be a

764
00:44:04,880 --> 00:44:10,160
Speaker 1: cool place to have New York City, Um, Washington, d C, Chicago. Uh.

765
00:44:10,239 --> 00:44:12,640
Speaker 1: It had like all the big ones and then you

766
00:44:12,680 --> 00:44:18,759
Speaker 1: know the smallest ones. I think we're Raleigh and Columbus, Ohio.

767
00:44:19,719 --> 00:44:23,720
Speaker 1: And besides that, it was all, you know, the biggest

768
00:44:23,719 --> 00:44:29,120
Speaker 1: places that you would expect a huge company to put

769
00:44:29,160 --> 00:44:32,680
Speaker 1: their business. They also threw Toronto in there, which is

770
00:44:32,719 --> 00:44:35,080
Speaker 1: one of the biggest cities in America, just happened to

771
00:44:35,120 --> 00:44:39,799
Speaker 1: be Canadian. Other cities you might have heard of, like

772
00:44:39,960 --> 00:44:45,120
Speaker 1: Los Angeles, Miami. Oh yeah, is that is that the

773
00:44:45,120 --> 00:44:49,680
Speaker 1: one in Florida? Yeah? Yes, it is actually no Ohio? No, yes,

774
00:44:49,719 --> 00:44:54,040
Speaker 1: my Florida, Austin, Dallas, Denver, Nashville. Like the only I

775
00:44:54,040 --> 00:44:56,919
Speaker 1: guess big emissions like San Francisco isn't on there, right,

776
00:44:56,960 --> 00:45:00,480
Speaker 1: but but we obviously know why. Uh So yeah. Yeah,

777
00:45:00,600 --> 00:45:03,279
Speaker 1: and uh, if you do end up getting the headquarters

778
00:45:03,320 --> 00:45:06,560
Speaker 1: in your town, you can look forward to basically paying

779
00:45:06,680 --> 00:45:10,680
Speaker 1: Amazon tax money with your tax dollars, because that's uh,

780
00:45:11,080 --> 00:45:14,520
Speaker 1: basically all these cities are competing to give Amazon enormous

781
00:45:14,560 --> 00:45:17,279
Speaker 1: tax breaks. And also, like not to mention like the

782
00:45:17,360 --> 00:45:20,440
Speaker 1: housing problems that come with having like these like giant

783
00:45:20,480 --> 00:45:23,919
Speaker 1: companies there. Like I don't seattle like property, Like there's

784
00:45:23,960 --> 00:45:27,000
Speaker 1: not much access to affordable housing because of like the

785
00:45:27,040 --> 00:45:30,279
Speaker 1: injection of all this these tech companies and stuff. But

786
00:45:30,360 --> 00:45:31,959
Speaker 1: I mean this is kind of what we can hope

787
00:45:31,960 --> 00:45:35,520
Speaker 1: for in this uh landscape where it's like these companies

788
00:45:35,640 --> 00:45:41,759
Speaker 1: and Walmart are basically you know, dropping into small communities

789
00:45:41,800 --> 00:45:46,239
Speaker 1: across America and just like vacuuming out all the resources

790
00:45:46,320 --> 00:45:50,040
Speaker 1: to wherever their corporate headquarters is. Uh, you know, we

791
00:45:50,560 --> 00:45:53,160
Speaker 1: can at least hope that we get to be near

792
00:45:53,239 --> 00:45:56,279
Speaker 1: one of those corporate headquarters at some point. Is sort

793
00:45:56,280 --> 00:46:00,480
Speaker 1: of let it trickled down on us. Uh that that's

794
00:46:00,480 --> 00:46:02,839
Speaker 1: always worked right in the past, what I understand. Yes,

795
00:46:03,480 --> 00:46:07,040
Speaker 1: on the other hand, Amazon Prime now has anger management

796
00:46:07,080 --> 00:46:16,160
Speaker 1: on its video serviced. I love that movie. All Right,

797
00:46:16,200 --> 00:46:18,960
Speaker 1: We're gonna take another quick break and we'll be right back.

798
00:46:27,600 --> 00:46:30,279
Speaker 1: And we're back, uh and we'll running along time. We

799
00:46:30,320 --> 00:46:33,160
Speaker 1: just wanted to check in with the American box office

800
00:46:33,360 --> 00:46:38,520
Speaker 1: to see what is hitting with the uh national shared

801
00:46:38,520 --> 00:46:43,280
Speaker 1: consciousness of ours. Uh. And The Greatest Showman is apparently

802
00:46:43,320 --> 00:46:47,360
Speaker 1: a big hit, which is you know, the musical starring

803
00:46:47,440 --> 00:46:52,320
Speaker 1: Hugh Jackman about P. T. Barnum got bad reviews. Uh,

804
00:46:52,640 --> 00:46:56,520
Speaker 1: but when you look on you know, top searches on

805
00:46:56,800 --> 00:47:01,399
Speaker 1: Google or you know, top searches in iTunes, a lot

806
00:47:01,440 --> 00:47:05,040
Speaker 1: of the searches are for songs from this musical, so

807
00:47:05,200 --> 00:47:09,240
Speaker 1: apparently it has catchy tunes. I know. They're even like screenings,

808
00:47:09,600 --> 00:47:12,040
Speaker 1: sing along screenings. I heard on the radio they were

809
00:47:12,040 --> 00:47:15,160
Speaker 1: doing ads for and I was like, that seems a

810
00:47:15,200 --> 00:47:18,719
Speaker 1: little bit a little overenthusiastic, like you already doing the

811
00:47:18,840 --> 00:47:21,880
Speaker 1: sing along screenings. But I guess there must be some

812
00:47:21,960 --> 00:47:24,160
Speaker 1: kind of market for it. Doesn't like I can't imagine

813
00:47:24,200 --> 00:47:25,960
Speaker 1: that they're just like, you know what, just do it,

814
00:47:26,080 --> 00:47:29,239
Speaker 1: we'll see who shows up. Uh. It is kind of

815
00:47:29,280 --> 00:47:34,760
Speaker 1: crazy that in this current atmosphere, a movie about P. T. Barnum,

816
00:47:34,800 --> 00:47:39,080
Speaker 1: who was like the best exploitative person of all time

817
00:47:39,160 --> 00:47:44,000
Speaker 1: to animals and other races of people. Uh that like

818
00:47:44,080 --> 00:47:46,839
Speaker 1: it would be hitting hard. Uh, people should go listen

819
00:47:46,880 --> 00:47:53,560
Speaker 1: to the Dollarp the podcasts by Dad Anthony and Gareth Reynolds. Uh,

820
00:47:53,960 --> 00:47:55,680
Speaker 1: it's like a history podcast. And I have a great

821
00:47:55,719 --> 00:48:00,239
Speaker 1: episode about Pete Barnum um and just what a what

822
00:48:00,360 --> 00:48:02,319
Speaker 1: a monster he is. Hey, but if you just spin

823
00:48:02,400 --> 00:48:06,439
Speaker 1: it with like singalongs and ship, yeah you don't. Yeah,

824
00:48:06,640 --> 00:48:08,680
Speaker 1: it's like it's easy to show like the fun part

825
00:48:08,719 --> 00:48:11,600
Speaker 1: of p. T. Barnome ignore what maybe these other people

826
00:48:11,640 --> 00:48:14,799
Speaker 1: who were like working for him were experiencing. In twenty years,

827
00:48:14,800 --> 00:48:18,520
Speaker 1: there's gonna be a Trump musical about like a great

828
00:48:19,440 --> 00:48:21,480
Speaker 1: because the economy was so good to look well, the

829
00:48:21,520 --> 00:48:23,480
Speaker 1: economy seems like they got through it. It was a

830
00:48:23,480 --> 00:48:28,560
Speaker 1: fun time for everyone, right. Um. And of course I

831
00:48:28,600 --> 00:48:31,000
Speaker 1: would be remiss if I were not to mention that

832
00:48:31,120 --> 00:48:36,560
Speaker 1: Jumanji has just been dominating ever since it came out.

833
00:48:36,640 --> 00:48:40,600
Speaker 1: It has been number one. There's three consecutive weekends it

834
00:48:40,640 --> 00:48:44,320
Speaker 1: has been number one. It has now made three seventeen

835
00:48:44,400 --> 00:48:50,600
Speaker 1: million dollars, which surprises anybody who didn't realize that The

836
00:48:50,719 --> 00:48:55,040
Speaker 1: Rock and Kevin Hart were in it and everything they

837
00:48:55,080 --> 00:48:59,000
Speaker 1: do is just amazing. I know, people who I was

838
00:48:59,000 --> 00:49:01,399
Speaker 1: talking to somebody last or I think this weekend, who

839
00:49:01,480 --> 00:49:03,560
Speaker 1: was like, whenever they're in the movie, I will always

840
00:49:03,560 --> 00:49:06,600
Speaker 1: just go see it. Yeah, Like there are people who

841
00:49:06,640 --> 00:49:10,360
Speaker 1: it's funny like their their movie going habits are purely

842
00:49:10,400 --> 00:49:12,640
Speaker 1: based on the cast, and like I would see every

843
00:49:12,719 --> 00:49:14,640
Speaker 1: Rock movie. I would see every Rock and Kevin Hart movie.

844
00:49:14,640 --> 00:49:16,560
Speaker 1: I would say with Kevin Hart movie, yeah, I don't know.

845
00:49:17,280 --> 00:49:20,400
Speaker 1: Did you have good ratings? Reviews? Do you want? You know? Really,

846
00:49:20,680 --> 00:49:23,120
Speaker 1: it's like in the fifties on Running Tomatoes. I'm not

847
00:49:23,120 --> 00:49:26,480
Speaker 1: sure metacritic. Um, I guess I'll wait for that one

848
00:49:26,840 --> 00:49:30,360
Speaker 1: for an airplane ride. Yeah, or twelve Strong. That was

849
00:49:30,400 --> 00:49:34,759
Speaker 1: the second place movie, right, that's just like Horses in

850
00:49:34,800 --> 00:49:39,080
Speaker 1: Iraq or Some Soldiers Afghanistan. It was based on a

851
00:49:39,160 --> 00:49:46,640
Speaker 1: book called Horse Soldiers. Horse Soldiers. Well, I'll be um,

852
00:49:46,719 --> 00:49:51,360
Speaker 1: but yeah. It was about a mission in Afghanistan immediately

853
00:49:51,400 --> 00:49:56,640
Speaker 1: after nine eleven where it was like Americans have to

854
00:49:56,680 --> 00:50:00,560
Speaker 1: stop the Taliban in order to prevent I think one

855
00:50:00,600 --> 00:50:02,719
Speaker 1: of the quotes from the trailer is like, if if

856
00:50:02,760 --> 00:50:06,200
Speaker 1: we don't win this battle, like every Tuesday will be

857
00:50:06,200 --> 00:50:11,040
Speaker 1: another nine eleven. Uh, you'll be begging for more nine

858
00:50:11,080 --> 00:50:14,719
Speaker 1: elevens that's how bad things will be, uh if I

859
00:50:14,719 --> 00:50:17,320
Speaker 1: think I'm over exaggerating that a little bit. But basically

860
00:50:17,400 --> 00:50:22,000
Speaker 1: the idea is like this is the battle too, uh

861
00:50:22,200 --> 00:50:27,839
Speaker 1: stop nine eleven from Uh, I don't know that a

862
00:50:27,960 --> 00:50:30,200
Speaker 1: very important detail to me. I'm like, I feel like

863
00:50:30,239 --> 00:50:32,520
Speaker 1: we're spending a lot of money on our military hardware

864
00:50:32,719 --> 00:50:34,839
Speaker 1: just for these duds to be riding the horses back.

865
00:50:34,840 --> 00:50:37,120
Speaker 1: Do these horses have fucking robot legs or shoot lasers

866
00:50:37,120 --> 00:50:39,560
Speaker 1: out their head? They're just regular fucking horses. Maybe Chris

867
00:50:39,560 --> 00:50:45,080
Speaker 1: Hemsworth is going undercover as a villager and like an Afghanistan,

868
00:50:45,400 --> 00:50:47,839
Speaker 1: an Afghan village, and it's like this is the only

869
00:50:47,840 --> 00:50:50,680
Speaker 1: way we'll be able to move without drawing suspicion will

870
00:50:50,719 --> 00:50:56,000
Speaker 1: be obvious targets. Um. But anyways, that that's doing well

871
00:50:56,800 --> 00:50:59,360
Speaker 1: because people want to know the story of how America

872
00:50:59,480 --> 00:51:03,319
Speaker 1: won the war in Afghanistan on horses. I think all

873
00:51:03,320 --> 00:51:05,360
Speaker 1: of them have animals, right, I guess all three of

874
00:51:05,400 --> 00:51:10,240
Speaker 1: these right, Oh yeah, animal movies and Paddington too. Dang

875
00:51:10,320 --> 00:51:15,399
Speaker 1: yeah yeah. Paddington two is getting critical acclaim like it's

876
00:51:15,440 --> 00:51:18,759
Speaker 1: like the front runner for the best picture of the year.

877
00:51:19,480 --> 00:51:22,799
Speaker 1: Well maybe it should be Yeah, more more talking animals. Yes,

878
00:51:23,760 --> 00:51:26,360
Speaker 1: all right, that's gonna do it for us for today.

879
00:51:26,520 --> 00:51:29,359
Speaker 1: Rog that's been a blast having you, mankee, for having me.

880
00:51:29,440 --> 00:51:33,600
Speaker 1: Where can people find you? Probably the best place is

881
00:51:33,640 --> 00:51:41,200
Speaker 1: just a Twitter at underscore Roger de sigh underscore first, Yeah, awesome,

882
00:51:41,440 --> 00:51:44,399
Speaker 1: someone took the original one. Yeah, yeah, now I've got

883
00:51:44,400 --> 00:51:48,000
Speaker 1: the scarlet underscore. Who's so, who's the guy sitting on

884
00:51:48,040 --> 00:51:50,279
Speaker 1: your handle? I don't know. I think I looked it

885
00:51:50,360 --> 00:51:55,640
Speaker 1: up years ago, and scarlet I can't remember. So it's

886
00:51:55,920 --> 00:51:59,440
Speaker 1: it's always funny, like typically people who should have the handle,

887
00:51:59,480 --> 00:52:03,960
Speaker 1: like the you know, unsullied handle. Uh, it's always someone

888
00:52:04,000 --> 00:52:06,359
Speaker 1: who doesn't use it at all, like it's mind block.

889
00:52:06,400 --> 00:52:07,880
Speaker 1: I've never see anyone who's like, yeah, you know what,

890
00:52:07,920 --> 00:52:09,800
Speaker 1: they actually have a pretty big following, and I'm pretty

891
00:52:09,800 --> 00:52:14,200
Speaker 1: sure this guy had like thirty four followers, like no tweets. Yeah,

892
00:52:14,239 --> 00:52:17,719
Speaker 1: it's a struggle, man, Miles, Where can people find you?

893
00:52:17,719 --> 00:52:19,560
Speaker 1: You can find me not at Miles Gray because some

894
00:52:19,600 --> 00:52:21,920
Speaker 1: other motherfucker has that handle, So if you really want

895
00:52:21,960 --> 00:52:23,879
Speaker 1: to find me on Twitter and Instagram, you can find

896
00:52:23,880 --> 00:52:27,759
Speaker 1: me at miles of Gray. Miles of I thought they

897
00:52:27,760 --> 00:52:31,040
Speaker 1: felt like a night's name or like a nobleman. Um,

898
00:52:31,120 --> 00:52:35,479
Speaker 1: you can follow me at Jack Underscore O'Brien because Jack

899
00:52:35,560 --> 00:52:41,800
Speaker 1: O'Brien has tweeted twice, both on September two, two thousand eight. Uh,

900
00:52:41,840 --> 00:52:45,040
Speaker 1: and it was is this thing on? First was follow

901
00:52:45,120 --> 00:52:51,960
Speaker 1: ap bio, second was second tweet was homework follow a

902
00:52:52,120 --> 00:52:54,600
Speaker 1: p bio Like that's an account, like, hey, you should

903
00:52:54,600 --> 00:52:57,279
Speaker 1: follow ap bio. I don't know it's it's there's also

904
00:52:57,440 --> 00:53:01,879
Speaker 1: no spacing, so it's just follow bio like as if

905
00:53:01,880 --> 00:53:04,360
Speaker 1: it's one word. And then the second tweet is homework.

906
00:53:04,600 --> 00:53:09,719
Speaker 1: So uh but he has five followers to see what

907
00:53:09,800 --> 00:53:11,560
Speaker 1: he was at high school student who was like, I'm

908
00:53:11,560 --> 00:53:13,600
Speaker 1: gonna try this Twitter thing out, man. Yes, people just

909
00:53:13,600 --> 00:53:19,600
Speaker 1: talk about like whatever's happening. Um, and he is following

910
00:53:20,360 --> 00:53:25,000
Speaker 1: one person. Let's see who he's following ap bio at

911
00:53:25,040 --> 00:53:29,480
Speaker 1: ap bio. Are we surprised Mr Anthes Washburn, who presumably

912
00:53:29,640 --> 00:53:34,040
Speaker 1: the teacher of ap bio. Uh so, yeah, follow followed

913
00:53:34,560 --> 00:53:38,360
Speaker 1: Jack O'Brien and Jack Underscore O'Brien. Try this dude to

914
00:53:38,360 --> 00:53:40,560
Speaker 1: follow would be great if like he has like suddenly

915
00:53:40,680 --> 00:53:45,000
Speaker 1: was like, oh, I've got like three followers. It's crazy Uh,

916
00:53:45,160 --> 00:53:48,600
Speaker 1: and yeah, you can follow us the show, The Daily

917
00:53:48,680 --> 00:53:52,760
Speaker 1: Zeitgeist at daily Zeitgeist on Twitter. We're at the Daily

918
00:53:52,840 --> 00:53:56,160
Speaker 1: Zeitgeist on Instagram that we have a Facebook fan page.

919
00:53:56,239 --> 00:53:59,600
Speaker 1: Just search daily Zeitgeist you will find it. And we

920
00:53:59,719 --> 00:54:02,600
Speaker 1: have a website daily zy dot com where you can

921
00:54:02,640 --> 00:54:06,120
Speaker 1: find our episodes and footnote foot or we link off

922
00:54:06,160 --> 00:54:09,480
Speaker 1: to all the articles and other source material that we

923
00:54:09,640 --> 00:54:14,239
Speaker 1: used to research this episode. Uh, and that's gonna do

924
00:54:14,280 --> 00:54:17,640
Speaker 1: it for today's episode, Miles, any music that we're riding

925
00:54:17,640 --> 00:54:20,520
Speaker 1: out on or you know, Uh, I think today Anna,

926
00:54:20,840 --> 00:54:24,879
Speaker 1: we'll have a suggestion for us. Yeah, I recently heard

927
00:54:24,920 --> 00:54:27,880
Speaker 1: this song. It's by Japanese Breakfast and it's a cover

928
00:54:28,080 --> 00:54:35,360
Speaker 1: of California Dreaming by Mamas and Papa's and it's truly beautiful. Really, Okay,

929
00:54:35,560 --> 00:54:36,960
Speaker 1: I thought you were looking at me straight in my

930
00:54:36,960 --> 00:54:40,160
Speaker 1: eye because I'm from California and I'm Japanese. It felt right.

931
00:54:40,239 --> 00:54:42,680
Speaker 1: I recommended this, but you don't. For you, thank you

932
00:54:42,719 --> 00:54:45,120
Speaker 1: so much. You don't eat breakfast and we're trying to

933
00:54:45,160 --> 00:54:50,040
Speaker 1: get you to start. Yeah, my energy level, you're low, sugar.

934
00:54:50,600 --> 00:54:54,000
Speaker 1: Blood sugar has really a change. Okay, you said you

935
00:54:54,000 --> 00:54:58,279
Speaker 1: wouldn't do this on. All right, that's gonna do it.

936
00:54:58,400 --> 00:55:00,880
Speaker 1: We will be back tomorrow because it the daily podcast.

937
00:55:01,080 --> 00:55:21,480
Speaker 1: Talk to you guys then and skies. I'm oh stay,

938
00:55:26,320 --> 00:55:44,240
Speaker 1: I'd be safe and world. It follows in cafunic I'm

939
00:55:44,239 --> 00:56:03,360
Speaker 1: such a stay stop into a chick. Oh not so

940
00:56:06,800 --> 00:56:16,959
Speaker 1: you will teach you. At the call to Susta califun

941
00:56:20,120 --> 00:57:16,520
Speaker 1: I'm suchosay almos two stars, go star. I hope too.

942
00:57:19,080 --> 00:57:32,240
Speaker 1: I can't leave to call function. I'm such amusing, I'm

943
00:57:32,320 --> 00:57:37,800
Speaker 1: so too amazed to me. It's Scholas Day.