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Speaker 1: Hello the Internet, and welcome to season sixty one, Episode

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Speaker 1: four up, the Daily Seitgeist podcast, where we take a

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Speaker 1: deep dive into America's share consciousness. He's in the headline

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Speaker 1: box office reports, TV ratings, what's trending on Google and

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Speaker 1: social media. It's Thursday, December two thousand eighteen. Happy birthday

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Speaker 1: to my little sister Caitlin. My name is Jack O'Brien,

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Speaker 1: a K. Your the Jack O'Brien. Ain't no one ever

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Speaker 1: gonna get away with Lyon. That is courtesy of Hannah Saultus,

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Speaker 1: and I'm thrilled to be joined as always by my

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Speaker 1: co host, Mr Miles Pray. I'm beginning to look a

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Speaker 1: up like Miles Gray. Everywhere I go. Jack O'Brien is

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Speaker 1: over there, Anna Hosnia in her chair and dicast. I'd

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Speaker 1: really like to get to know Wow Noel Duncan dunking

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Speaker 1: on him with that a K Noel Duncan. So she

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Speaker 1: just comes with it because she's named after the season.

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Speaker 1: This is her time. Yes, well, we are throwed to

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Speaker 1: be joined in our third seat by a guest we

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Speaker 1: surely would like to get to know a little bit better.

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Speaker 1: She's been on the show a number of times she

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Speaker 1: is a hilarious comedian. She is sorry, j what's I

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Speaker 1: don't have an ak a, but I would like to

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Speaker 1: start associating my name with a wolf towel. So if

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Speaker 1: you guys could introduce me again and I'll just or

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Speaker 1: I could introduce you. No no, no, no, no, no, okay,

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Speaker 1: all right, sorry do it, say sar, and we're throwed

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Speaker 1: to be joined by Sorry ju wolf pack where my

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Speaker 1: wolf pack at? And then you just got dude, I

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Speaker 1: got a bad bullet proof again, chunky Si, chunky bullet?

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Speaker 1: When are we When are you going to learn? It's

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Speaker 1: like candy corn every year? I'll be like, no, this

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Speaker 1: won't be different. Well, no, the butter and oil congeals

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Speaker 1: at the hob and it's the yeah they do before

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Speaker 1: I pulled them out the refrigerator and it didn't do this.

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Speaker 1: I'm I have problems and this is not the show.

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Speaker 1: But you gotta have a bulletproof hot or else you're

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Speaker 1: just having chunks of butter coffee, which is not bad.

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Speaker 1: But it's not what you upset. No, it's it's bad.

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Speaker 1: It's I haven't I haven't fully recovered from the memory

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Speaker 1: of drinking you had, like an existential crisis, like just

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Speaker 1: big chunks of cocon at all. Nah, it was very

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Speaker 1: like salty and not not a good mix. Well, sorry, Jim.

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Speaker 1: We're going to get to know you a little bit

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Speaker 1: better in a moment. But first we're going to tell

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Speaker 1: our listeners a couple of things we're talking about. Google

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Speaker 1: has come out with their most googled terms of two

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Speaker 1: thousand eighteen, and we're going to look at the most

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Speaker 1: googled foods of two thousand eighteen. While we're on the

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Speaker 1: subject of foods, we're going to talk about the fact

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Speaker 1: that Whole Foods has been poisoning us for years and

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Speaker 1: we didn't know. We're gonna do a quick preview check

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Speaker 1: out with the democratic field, see how everybody's feeling about

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Speaker 1: all them candidates. We're going to look at the tech

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Speaker 1: world's latest trip to Capitol Hill, some more fallout from

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Speaker 1: that Oval Office meeting, all of that, and plenty plenty more.

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Speaker 1: But first we like to ask our guest, what is

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Speaker 1: something from your search history that is revealing about who

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Speaker 1: you are? M A recent search history term of mine

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Speaker 1: was is vaping halal? I wanted to know and moms

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Speaker 1: are divided on the subject, but well, the general consensus is, no,

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Speaker 1: it is not halal. It is horronto vape because it's

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Speaker 1: an intoxicant. Right, you're vaping like nicotine or weed or whatever.

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Speaker 1: It's kind of okay if you are quitting smoking, it's

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Speaker 1: like okay, you know it's where it's like it's not halal,

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Speaker 1: but like nobody's gonna out first in Islam? Can you

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Speaker 1: tell you what hal Halal means? It's cool? Haram means

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Speaker 1: it's not cool, so so overrated, underrated but already under it. Yeah. Yeah,

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Speaker 1: vaping is like it's not okay because it's in toxic

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Speaker 1: and you're not supposed to You're not supposed to get

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Speaker 1: sucked up. We're not supposed to get suck up cigarettes.

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Speaker 1: You're not suposed get suck up on alcohol. You're not

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Speaker 1: supposed to get sucked up on weed. But like does

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Speaker 1: every Muslim not drink? No, you know, so like people

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Speaker 1: do it or whatever. But interesting, vaping while haram does

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Speaker 1: not break, which is when you when you wash before

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Speaker 1: you pray, there's like a special like a washing procedure

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Speaker 1: before you pray so you get real clean, but vaping

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Speaker 1: doesn't break, would do so like you can still like

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Speaker 1: you could wash your hands a bunch and then vape

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Speaker 1: and then pray to God. Pretty cool. But if you

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Speaker 1: fart that breaks will do it. Yeah. If you pass out,

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Speaker 1: that also breaks will do if you pass out. Yeah, weird,

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Speaker 1: weird set of rules. Really, there's a lot of really

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Speaker 1: good forums where people ask a mom's like what Mohammed

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Speaker 1: said about vaping. Yeah, well that's so interesting about farting,

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Speaker 1: but like about about like modern ship. You know, it's

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Speaker 1: it's always really good. And now is that in the

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Speaker 1: Koran about farting? Uh? Yeah, but not they don't they

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Speaker 1: say anything exiting the body? Okay, oh really so a belch. Also, well, yes,

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Speaker 1: there's like exhale, so that's fine. Yeah, I would say

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Speaker 1: digestive gases, building and expanding them, yes, passing wind, taking ship,

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Speaker 1: passing out, and uh, falling asleep, keep sleep, you fall

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Speaker 1: asleep a little. I think it's fine. It's all really like,

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Speaker 1: it's not. I'm not I'm not Muslim? Are you vaping?

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Speaker 1: Is what I was gonna ask? H No, Okay, my friend, well,

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Speaker 1: my my podcast co host with a podcast comst. Drew

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Speaker 1: Nutter is a big, big vape daddy, and he recently

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Speaker 1: got a new vape and he it looks like how

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Speaker 1: from the movie two thousand and one. It's very large

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Speaker 1: and white and it has buttons on it, you know.

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Speaker 1: So I was like, your vape looks like hell? And

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Speaker 1: then I was like, is vaping hell? Okay? Train and no,

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Speaker 1: it's it's not really, but um, you know, no one's

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Speaker 1: gonna kick you out for it. I mean, don't vape

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Speaker 1: at a space for tone? You know, do a little?

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Speaker 1: Does vape daddy like a fetish? Like are people into

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Speaker 1: vape Daddy's like that? That's a good Google searching for you,

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Speaker 1: all right, my search history leather with it, right. A

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Speaker 1: vape daddy is a man who vapes with confidence. I

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Speaker 1: let's say, you know, when you've got his daddy who vapes,

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Speaker 1: he's a day got it or or vatty? What is

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Speaker 1: something you think is overrated? So I I really I

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Speaker 1: heard recently and maybe we'll talk about this later to

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Speaker 1: about Jack Dorsey going to a vipasan meditation retreat for

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Speaker 1: like eight to ten days, and then he came back

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Speaker 1: and he was like, here's a graph of my heart

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Speaker 1: rate while I was meditating, because he was wearing his

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Speaker 1: ring that measures your heart rate you know, wearable tech

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Speaker 1: not creepy at all. You know, a lot of regulation

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Speaker 1: around it, no worries. Um, yeah he was. I think

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Speaker 1: knowing all your body measurements all the time is overrated.

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Speaker 1: I think you know, every like the Apple Health and

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Speaker 1: ship things that track you. They're kind of cool in

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Speaker 1: a way. It's like, yeah, it's cool, but um, really,

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Speaker 1: I don't think. I don't know if you need to

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Speaker 1: monitor yourself constantly if you're not ill, you know what

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Speaker 1: I mean, Like if you have if you have an

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Speaker 1: illness or chronic illness or trouble sleeping or something, it's

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Speaker 1: very good to like keep track of stuff and it

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Speaker 1: can help find out a lot of stuff about yourself.

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Speaker 1: But but overall, I think I don't want to know

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Speaker 1: Jack Dorsey's heart rate all the time. You know. I

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Speaker 1: think that's overrated. It's probably the most relevant, overrated I've

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Speaker 1: ever brought to the table because I don't think it's awful.

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Speaker 1: But I'm like, yeah, well, I think it's it's for people.

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Speaker 1: If you like that data, fine, but like, are we

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Speaker 1: are we going to live for fifty years longer? Because

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Speaker 1: I don't want Jack Dorsey to live for fifty years longer.

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Speaker 1: I want him to die at a normal time. Is

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Speaker 1: his hair all long and ship right now? To the photos?

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Speaker 1: I don't, I don't know. I didn't. Okay, I thought

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Speaker 1: I saw a photo him looking hippie look like in

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Speaker 1: ten days his hair just grew to like shoulder length

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Speaker 1: from the strength of his meditation. No, I think he's

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Speaker 1: all right. I just heard somebody say, like, well, I

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Speaker 1: actually think Jack Dorsey is a pretty thoughtful guy. Like

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Speaker 1: of all the tech people, like tech entrepreneurs and founders,

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Speaker 1: I think he's the most you know, woke and uh

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Speaker 1: he's into mindfulness. He just went on a retreat and

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Speaker 1: now this has totally erased all of that. Yeah, he

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Speaker 1: wore his Apple watch and his aura ring that measures

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Speaker 1: your sleep and stuff the whole time he was at

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Speaker 1: the meditation retreat, which was like it's like in an

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Speaker 1: ashram or something, you're not allowed he you know, you're

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Speaker 1: not allowed to have a cell phone. You're supposed to

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Speaker 1: be in silent meditation for like hours and hours a day.

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Speaker 1: And he was like, I'm gonna keep my Apple watching.

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Speaker 1: He's like, well, hold on, dude, I need to check

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Speaker 1: my mention. Yeah, he was like they were in airplane mode.

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Speaker 1: Like they were an airplane mode. That's how I knew

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Speaker 1: like I was really peaceful, because like my mentions were

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Speaker 1: blowing and my heart was just like fucking flat chill.

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Speaker 1: He looks like fucking Hugh Laurie playing a shitty version

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Speaker 1: of Jack Dorsey. I would love to see a movie

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Speaker 1: about Twitter starring like a fake beard. Yeah, he looks

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Speaker 1: like a pug Hugh Laurie. Al Right, well I like Laurie.

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Speaker 1: Oh yeah, shout out to him. And incredible, incredible actor.

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Speaker 1: He's Hugh Daddy d House. What is something you think

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Speaker 1: is underrated? You know, having any sort of privacy with

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Speaker 1: your information online totally underrated. If you're still into privacy,

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Speaker 1: move on. Everyone knows where you are all the time.

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Speaker 1: It's chill. Companies buying and selling your data. Get used

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Speaker 1: to it, you know what I mean, everyone's polly now.

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Speaker 1: Everyone's got each other's information. You know, if you've got

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Speaker 1: a smartphone, just accept that you have no privacy. An

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Speaker 1: have a tracking device, you have a tracking device, like

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Speaker 1: you know, this is a thing that like what how

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Speaker 1: long have Hippy's been saying this, like thirty years? You know,

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Speaker 1: with a GPS tracking device, I mean, yeah, it's true,

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Speaker 1: you know what I mean? What I don't it is

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Speaker 1: people that are learning now and very surprised that companies

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Speaker 1: that track their locations buy and sell that information because

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Speaker 1: it's like, what else did you think they were doing well?

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Speaker 1: Because I think a lot of people didn't have the

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Speaker 1: why did people abstract what the business model was? Right?

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Speaker 1: Because they just thought it was like, yeah, it's Google's free,

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Speaker 1: Gmail's free, yeah, because that's just like what it is,

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Speaker 1: Like it's free, and they don't be like, yeah, how

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Speaker 1: do you sustain free? And then the guys that run

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Speaker 1: it are billionaires. Where does where's the money coming? Thought

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Speaker 1: they were just rich people who are trying to do

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Speaker 1: me a solid in the email. I think that's really

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Speaker 1: what a lot of people. I think. I'm for real,

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Speaker 1: Like they're trying to help the world and me by

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Speaker 1: giving me an email service. Right. It wasn't until I

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Speaker 1: had people who are working for those companies like break

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Speaker 1: down for me how it worked. I was like, oh,

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Speaker 1: like all I used to pay a monthly fee and

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Speaker 1: that's why I got my ship. Now it's like you

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Speaker 1: got the sweet message boards? Yeah, Now they just lure

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Speaker 1: you in so they can be like because we just

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Speaker 1: want to package your data, and sometimes they ask you

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Speaker 1: if they can get your location, and sometimes they don't.

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Speaker 1: I kind of just assume they're always doing it because

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Speaker 1: they have the ability, you know, and there's like there's

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Speaker 1: many companies that track your location and don't ask you

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Speaker 1: even though that's like pretty illegal. But the problem is

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Speaker 1: none of this is illegal right now, Like it's really

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Speaker 1: all very above board because we don't have any regulation

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Speaker 1: about it because we're like, uh, well, as we'll talk

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Speaker 1: about later, a lot didn't exist, you know, like we

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Speaker 1: never had to deal with this anymore or before. Rather,

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Speaker 1: but there's a I know there's a senator I believe

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Speaker 1: from Oregon who's who's trying to introduce like a maybe

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Speaker 1: a bundle of bills or maybe just one bill about

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Speaker 1: um regulating up you know, personal data, and he's it's

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Speaker 1: in the works right now, Scott. Scott. Something I want

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Speaker 1: to say, Scott, there's some senators from from Oregon trying

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Speaker 1: to like because there just is no legislation about this

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Speaker 1: because it was never an issue before. And then obviously

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Speaker 1: tech hasn't in Tristan, keeping it very deregulated don't make

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Speaker 1: it hot for us. They spent a lot of money

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Speaker 1: lobbying for that exactly, focus on Cambridge analytic. Yeah, like,

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Speaker 1: you know, people, everyone, everyone knows Zuck is going to run.

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Speaker 1: You know, Zack is going to run maybe four Like

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Speaker 1: we don't really know. But but that's why it's not

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Speaker 1: because he's so good at people and relating to people

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Speaker 1: and people, you know, he doesn't He's not gonna have

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Speaker 1: to do a lot of coke if he's going to

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Speaker 1: come off as a human in any kind of interaction.

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Speaker 1: He's like, I don't know, but even then, I can't

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Speaker 1: imagine what Gee, don't you imagine giving a speech? Yeah, so,

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Speaker 1: I mean he's already so anxious, Like God, I'm panicking

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Speaker 1: watching he's a programmer, Like he looks like a program.

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Speaker 1: Already sounds like a programmer and looks like a program. Yes,

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Speaker 1: but I agree. We we talked about this even yesterday

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Speaker 1: that you know, it's a twenty one billion dollar industry

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Speaker 1: right now already, the selling of your location. But at

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Speaker 1: the same time, they're not really connecting it to you personally.

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Speaker 1: It's just they're they're interested in the patterns. They're just

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Speaker 1: viewing you as a point of data basically, but like

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Speaker 1: you're a point of data that goes from one place

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Speaker 1: to another every you know what I mean, Like I

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Speaker 1: don't have like when I use Google Maps, you know,

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Speaker 1: how you have an option to set your home address,

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Speaker 1: Like I don't use that, you know, but I know

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Speaker 1: Google knows where I live because it's like where do

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Speaker 1: I go every night? You know? They know my fucking

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Speaker 1: address right exactly, and yeah they I'm more jealous than

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Speaker 1: anything because I want to know like all the ship

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Speaker 1: that they know about, like humans and how we actually

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Speaker 1: behave you should work for an advertising company. They do that.

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Speaker 1: They ping you when you go buy a billboard, like

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Speaker 1: if you have a certain kind of phone and a

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Speaker 1: GPS tracker um. Advertising companies that have a billboard will

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Speaker 1: be able to ping you and and see when you're

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Speaker 1: near the billboard, and then they can see where you

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Speaker 1: can go after that and how much later you buy

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Speaker 1: their product if you stay within a certain radius, and

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Speaker 1: they can see how it affects your travel patterns and

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Speaker 1: your shopping patterns, and like you know who wants that?

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Speaker 1: Yeah right, yeah, you guys want that. Do you think

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Speaker 1: that's cool? Do you think it's fine? Because I think

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Speaker 1: some people think it's fine, and I really don't I

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Speaker 1: feel like I'd rather have my privacy than arm companies

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Speaker 1: with more like aggressive data to sell me ship. Like,

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Speaker 1: I don't see where the benefit is for them to

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Speaker 1: know all of those because it makes it easier for

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Speaker 1: them to sell you. It makes the money then, But

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Speaker 1: it's a yeah, that's what I'm saying. Like, if it's

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Speaker 1: a binary chosen, I'm like, well, I don't know that privacy.

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Speaker 1: What's more important like the ability of a corporation to like,

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Speaker 1: you know, expand their profit or your ability to walk

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Speaker 1: down a street and not have a company know where

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Speaker 1: you're going right exactly. You know. Look, if you want

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Speaker 1: to sell me something, just put CARDI being a commercial. Yeah.

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Speaker 1: If you want to get a guy on the street

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Speaker 1: getting to give me a flyer, yeah, or one of

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Speaker 1: those with the arms that go crazy. I'm like, what's

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Speaker 1: old school advertising? That oil lube chain center. If I

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Speaker 1: could find a way show me a big wiggly guy

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Speaker 1: I can find a way to work in advertising and

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Speaker 1: kill myself, I would do it. But I just I

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Speaker 1: don't think there's a possible you'd be very rich and

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Speaker 1: dead right. Yeah, those are the problems. Off. Finally, what

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Speaker 1: is a myth? What's something people think it's true, you know,

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Speaker 1: to be false. Um, sometimes people say, oh, Riverdale, the

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Speaker 1: sexy archy show on the CW. That show is mere

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Speaker 1: trash and has no political overtones. Well, I say, those people,

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Speaker 1: I don't know what they're talking about, because I now

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Speaker 1: have a second podcast. That's right, I have a second

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Speaker 1: podcast and it's only about Riverdale and how it's communist Dale. Yeah,

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Speaker 1: I got that Twitter account. You got that account at

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Speaker 1: d S A underscore Riverdale. We post maybe but like

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Speaker 1: once a month. This is a low key broadcast, but

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Speaker 1: Riverdale's extremely woke. There's a lot of political themes in

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Speaker 1: Riverdale season one, season two, season three, season three, right

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Speaker 1: now crazy yeah, Oh, the whole thing is about how

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Speaker 1: the town of Riverdale is being taken over by this

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Speaker 1: rapacious capitalist High Room Lodge Veronica's dad and then like

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Speaker 1: jug Head represents the poor who are in a gang

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Speaker 1: and they're constantly getting like Riverdale gets gentrified. The south

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Speaker 1: side of Riverdale gets gentrified in season two because High

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Speaker 1: Room Lodge spoilers, spoilers spoilers, wants to build a private

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Speaker 1: prison there. They got a very clear perspective, and you know,

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Speaker 1: and then we also just like to talk about who's hot,

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Speaker 1: who's in that room. I mean, you know, some people

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Speaker 1: would like to meet h Yeah, and so we got

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Speaker 1: a little bit of got a little bit of lashback, backlash,

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Speaker 1: flashback about our show because um, people got mad at

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Speaker 1: us on Twitter for associating the sexualization of miners with

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Speaker 1: class struggle. Was a complaint that we got, which I

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Speaker 1: take seriously. But it's ridiculous because they're not miners. Um,

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Speaker 1: the actors themselves are not miners, They're not teens. The

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Speaker 1: show is not really about teens, you know. It's just

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Speaker 1: very weird when you're like, oh, they're they're in high school.

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Speaker 1: Well yeah, they're supposed to be in high school, and

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Speaker 1: like you never see them in class. And also, yeah,

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Speaker 1: all the actors are like in their twenties, so right,

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Speaker 1: I don't feel bad about it, um, but but some

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Speaker 1: people didn't for being too horny. Humor jokes were doing

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Speaker 1: for humor jokes and fun, but also like the show

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Speaker 1: is deeply sexual, Like have you ever seen Riverdale The

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Speaker 1: student has sex with the one of the teachers, and

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Speaker 1: the parents of like, you should just get out of town.

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Speaker 1: I'm sorry, that's how they handle cool. Yeah, it is

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Speaker 1: a hotbed, hotbed of uh, you know, sin and revolutionary

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Speaker 1: activity here we go. Are you saying that the community

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Speaker 1: like operates on socialist along socialist ideals or just that

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Speaker 1: they like hide socialist ideas in it. Some of the

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Speaker 1: main characters in the show explicitly fight for socialist ideals.

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Speaker 1: And also in season two, Archie becomes a fascist. It

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Speaker 1: starts like a terrorist group and then by the end

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Speaker 1: of the season he has a change of heart and

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Speaker 1: he becomes anti fashion But like, I still don't really Archie.

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Speaker 1: Archie goes to prison. He has an experience in prison

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Speaker 1: that makes him rethink his trust of the cops in

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Speaker 1: the system, just like alright, guys, let's talk about the

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Speaker 1: most googled foods of two thousand eighteen, and we have

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Speaker 1: brought in our special Keto correspondent to produce her on

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Speaker 1: a hosnie. Listen to that energy from that Keto dio

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Speaker 1: vibrating right now. She's hovering. But the reason we bring

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Speaker 1: her in is because when you look at the most

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Speaker 1: googled food of this year, five of the fucking entries

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Speaker 1: are keto recipes. So keto pancakes, keto cheesecake, keto chili,

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Speaker 1: keto brownies amongst the other Cheeto cookies and chet will

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Speaker 1: be better. But it's actually Keto cookies. Huh. But yeah,

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Speaker 1: I'm like, it just shows you the power, the strength

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Speaker 1: of the Keto crazy ket wave too. I am not,

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Speaker 1: but my roommate was Keto for a while and I

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Speaker 1: just threw osmosis it started eating a lot less bread. Yeah. Yeah,

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Speaker 1: Now I now I know what's keto and wood isn't,

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Speaker 1: and I know what it is. I'm not Keto. You

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Speaker 1: I didn't have a need or desire to lose quite

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Speaker 1: a large amount of weight. But yeah, it's making its

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Speaker 1: way through all our brains. And my dad was on

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Speaker 1: three different kinds of it this year. I tried it

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Speaker 1: for three do three dos three. Yeah. So you just

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Speaker 1: said that you had made Keto pancakes this weekend? Did

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Speaker 1: you not made Keto pancakes this weekend? I've made Keto cheesecake,

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Speaker 1: which I brought in and you guys all pretended to

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Speaker 1: like it. I did know they were delicious. Yeah, face,

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Speaker 1: you were on this podcast. It's so easy. I've made

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Speaker 1: Keto cookie, chocolate chip, Keto cookies. I've made keto um.

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Speaker 1: I use almond flour. Nice. I also use like coconut flour.

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Speaker 1: So this is like no carbs. Is that the Keto philosophy.

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Speaker 1: It's all fat, very little sugar. Yeah, very very fat,

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Speaker 1: moderate protein, low carb. But that Keto cheesecake was sweet?

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Speaker 1: What was what was so fruit? I use for the

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Speaker 1: Keto cheesecake. I used the Swerve sugar, which is like

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Speaker 1: fake sugar. It's it's it's the from taking the world.

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Speaker 1: You gotta go by, You gotta go spend most of

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Speaker 1: your life savings on this stuff because it's very expensive

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Speaker 1: and they only sell it at like health food stores. Right. Yeah,

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Speaker 1: I feel like Keto is expect I feel like this

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Speaker 1: is a good time. I need a race yead tucks

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Speaker 1: a loaf for Keto bread. Yeah, low car bread. Look,

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Speaker 1: it's not great, but it does the job of you

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Speaker 1: thinking you're eating bread. Yeah, it's just you need something

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Speaker 1: to put things. You toast your Keto bagels here in

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Speaker 1: the office, And sometimes I smell them and I'm like yeah,

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Speaker 1: and you're like someone using white out. The other things

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Speaker 1: on this list were very interesting too. I feel like

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Speaker 1: we're not treating ourselves very well as a species because

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Speaker 1: most of these are like when have we ever? Right?

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Speaker 1: But these are like, it's okay. So like romane lettuce.

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Speaker 1: You know that was because of the route, because that's

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Speaker 1: not what everybody needed a romane resturant, Right, how do

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Speaker 1: I cook romane letter CBD gummies so we're treating ourselves. Well,

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Speaker 1: they're everybody loved. But this was a year for CBD,

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Speaker 1: C boys, ABC CBD. Uh. The gummy thing is cool.

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Speaker 1: I like that. There's just a lot of vigano. I

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Speaker 1: always felt a little weird about eating gelatine. Yeah, I'm

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Speaker 1: not vegan, but like gelatine is a little rather it's

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Speaker 1: a bone goo. I'd rather not um. And now there's

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Speaker 1: vegan gummies everywhere, which I think is great. Oh yeah,

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Speaker 1: we've made a lot of advances and vegan sciences and

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Speaker 1: vegan edibles people who want to get that CBD wave.

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Speaker 1: And then other ones Neco wafers. I'm surprised because we

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Speaker 1: talked about how that ship should have just been thrown

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Speaker 1: on the fucking trash sheep. It's so bad, That's what

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Speaker 1: That's what I'm talking about. And then got Jan is

402
00:21:48,040 --> 00:21:54,880
Speaker 1: pretty good but underrated, Neco waivers, underrated, Nila wafers. Wafers

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Speaker 1: are like currency in my preschool I remember as the

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Speaker 1: kid which banana coin. Yeah, but the thing would go

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Speaker 1: to I wonder if that had to do. It's the

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Speaker 1: Korean spice paste, like the foundation for all, like Korean

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Speaker 1: spicy pepper paste. Yeah, and that was mentioned in that

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Speaker 1: woman's really tired obituary about her potato salad or whatever

409
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Speaker 1: the fun remember the woman she was like, millennials are

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Speaker 1: ruining mayonnaise. That's what it was like. And now people

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Speaker 1: want goach or jang or whatever. But I think this

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Speaker 1: was just a hot year for Korean fusionnaise old year. Yeah,

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Speaker 1: mayonnaise is number five hundred and seventies. Oh boy, Unicorn

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Speaker 1: cake was the number one searched thing, which that insta

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Speaker 1: it's just because that's it, Like it's cake with a

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Speaker 1: horn on it. No, no, it's rainbow cake, right, But

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Speaker 1: it's like, but it was all about the visual of

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Speaker 1: it rather than like this was a thing to eat.

419
00:22:50,680 --> 00:22:53,240
Speaker 1: Everyone's just obsessed with like you can make this little

420
00:22:53,280 --> 00:22:57,320
Speaker 1: cake look like unicorn uniform. Yeah. People want to eat

421
00:22:57,359 --> 00:23:00,720
Speaker 1: things that look good and don't taste good. I find Yeah,

422
00:23:01,119 --> 00:23:03,320
Speaker 1: all those all those like pastry instagrams, I'm like, you know,

423
00:23:03,400 --> 00:23:05,240
Speaker 1: this doesn't taste it's kind of dry because you've got

424
00:23:05,240 --> 00:23:06,680
Speaker 1: to make a real you have to make a thick

425
00:23:06,760 --> 00:23:08,800
Speaker 1: cakes to be very rigid, has to be very rich.

426
00:23:09,080 --> 00:23:12,720
Speaker 1: Not a fond fan either, Nope, nope, nope, nope nopeupa

427
00:23:12,840 --> 00:23:15,639
Speaker 1: for eating. Yeah, okay, so I see the inside of

428
00:23:15,680 --> 00:23:20,320
Speaker 1: the unicorn cake. Looks like a unicorn frap from Starbucks.

429
00:23:20,520 --> 00:23:26,240
Speaker 1: Oh god, it looks like Cashi sixty nine. It's like blue,

430
00:23:26,280 --> 00:23:29,720
Speaker 1: it's like candy colors blue and pink white, all that. Yeah,

431
00:23:30,040 --> 00:23:34,520
Speaker 1: so seen thing. Basically super producer on a Hosnier the

432
00:23:34,560 --> 00:23:37,000
Speaker 1: way to break the Internet, come up with a keto

433
00:23:37,160 --> 00:23:41,879
Speaker 1: unicorn cake. Oh shit, there would go. We're on the

434
00:23:41,880 --> 00:23:46,840
Speaker 1: same page. You can imagine. You just need to get

435
00:23:46,920 --> 00:23:50,199
Speaker 1: like you could make frosting from like Swerve confection or

436
00:23:50,200 --> 00:23:54,000
Speaker 1: Sugar Holy with food coloring, and then you can make

437
00:23:54,040 --> 00:23:56,680
Speaker 1: the cake out of either almond flour or coconut flour,

438
00:23:56,880 --> 00:23:58,359
Speaker 1: use the same recipe as a cake, but you just

439
00:23:58,400 --> 00:24:03,880
Speaker 1: replace those certain items with the replaceable with nuts. Guys.

440
00:24:03,960 --> 00:24:06,000
Speaker 1: Her eyes are closed as she says this, and she

441
00:24:06,080 --> 00:24:12,600
Speaker 1: was just running her fingers, like Max. Once you do

442
00:24:12,720 --> 00:24:15,560
Speaker 1: and start making enough Keto things, you immediately can see

443
00:24:15,560 --> 00:24:18,439
Speaker 1: how to make the very It's like the gift of

444
00:24:18,480 --> 00:24:21,119
Speaker 1: the woman seeing the math in the air, right, just

445
00:24:21,640 --> 00:24:26,040
Speaker 1: like ketoing, She's going onto a Keto fugue. And then

446
00:24:26,080 --> 00:24:28,920
Speaker 1: real quick, Whole Foods is poisoning you through those little

447
00:24:28,920 --> 00:24:34,720
Speaker 1: brown boxes that you put their hot bar food into. Yeah,

448
00:24:34,840 --> 00:24:40,000
Speaker 1: somebody did a test on all grocery chains in America

449
00:24:40,119 --> 00:24:43,399
Speaker 1: and said that Whole Foods ranked by far the worst

450
00:24:43,480 --> 00:24:47,640
Speaker 1: for chemicals it uses in packaging it's popular hot food bar.

451
00:24:48,200 --> 00:24:51,879
Speaker 1: They found high levels of fluorine or fluorine and five

452
00:24:52,000 --> 00:24:55,160
Speaker 1: of the seventeen items tested Whole Foods for which were

453
00:24:55,160 --> 00:24:57,520
Speaker 1: containers for its salad and hot food got to keep

454
00:24:57,560 --> 00:24:59,800
Speaker 1: those bodily essences. These are the ones that like the

455
00:25:00,160 --> 00:25:03,879
Speaker 1: super biodegradable, compostable little but I don't think so. No,

456
00:25:03,960 --> 00:25:05,399
Speaker 1: those are the ones that are cardboard but on the

457
00:25:05,440 --> 00:25:08,879
Speaker 1: inside it looks plastic. Yeah, I think I think that

458
00:25:09,000 --> 00:25:13,360
Speaker 1: that's what that plastic. So they're they're really not they're

459
00:25:13,400 --> 00:25:16,640
Speaker 1: not compostable and they're not really bidegradable because of that.

460
00:25:17,119 --> 00:25:20,280
Speaker 1: Fall for it again, yeh, I fail free it again.

461
00:25:20,640 --> 00:25:25,480
Speaker 1: Yeah might Sorry, that's not very digestible, Yeah, for real,

462
00:25:25,520 --> 00:25:27,080
Speaker 1: it doesn't. Second, my teeth. I'm glad to know that

463
00:25:27,200 --> 00:25:29,360
Speaker 1: is plastic and I should not eat that. Yeah, it's

464
00:25:29,440 --> 00:25:34,920
Speaker 1: It's really a crucible of the compostable packaging industry is that,

465
00:25:34,960 --> 00:25:38,320
Speaker 1: like everything that's compostable, when it gets hot, it falls apart.

466
00:25:38,720 --> 00:25:40,479
Speaker 1: So that's why I like the compostable cups you can

467
00:25:40,520 --> 00:25:43,119
Speaker 1: only put cold drinks in because for something to be compostable,

468
00:25:43,119 --> 00:25:45,360
Speaker 1: it has a breakdown, and the heat of a compost

469
00:25:45,359 --> 00:25:49,440
Speaker 1: pile helps it break down. Underrated composting, I'm I'm heavy

470
00:25:49,480 --> 00:25:52,520
Speaker 1: into it now. I got a big soil saver. Oh boy,

471
00:25:52,720 --> 00:25:54,680
Speaker 1: I love to talk about pH levels. I want to

472
00:25:54,680 --> 00:25:57,920
Speaker 1: get all the tools. When compost is going right, it

473
00:25:57,920 --> 00:25:59,600
Speaker 1: should be so hot that if you put your hand

474
00:25:59,600 --> 00:26:06,520
Speaker 1: in it, you in your hands, crazy and tropic breakdown. Yeah, alright,

475
00:26:08,600 --> 00:26:22,919
Speaker 1: to think about that and we'll be right back. And

476
00:26:23,000 --> 00:26:26,399
Speaker 1: we're back. And I wanted to take a quick moment

477
00:26:26,520 --> 00:26:33,399
Speaker 1: to look at the democratic field because specifically the betto

478
00:26:33,840 --> 00:26:37,159
Speaker 1: Verse Bernie debate that is now sort of bubbling to

479
00:26:37,320 --> 00:26:42,119
Speaker 1: the surface. Uh, some of the people on the Biden

480
00:26:42,880 --> 00:26:46,560
Speaker 1: it's bidal betto Burnie. I think people just have a

481
00:26:46,600 --> 00:26:50,240
Speaker 1: Biden is like a fixed like a known quantity and

482
00:26:50,280 --> 00:26:57,600
Speaker 1: then like mayonnaise, right, and then right betto is and

483
00:26:57,800 --> 00:27:00,720
Speaker 1: he is miracle whip right. Well, so, you know, I

484
00:27:00,840 --> 00:27:07,120
Speaker 1: heard somebody talking about how Bernie gets like harshly criticized for,

485
00:27:07,400 --> 00:27:10,919
Speaker 1: you know, not having very woke politics on race, and

486
00:27:10,960 --> 00:27:15,520
Speaker 1: I started doing like research into that, and it seems

487
00:27:15,600 --> 00:27:19,000
Speaker 1: like people don't really know where to come down on

488
00:27:19,080 --> 00:27:22,880
Speaker 1: Bernie and how he feels about race. Well, he's had gaffs,

489
00:27:22,960 --> 00:27:25,560
Speaker 1: right like so during on Super Tuesday when he got

490
00:27:25,600 --> 00:27:28,520
Speaker 1: blown out by Hillary, like, it was almost like there

491
00:27:28,560 --> 00:27:30,680
Speaker 1: was no effort to reach out to black women who

492
00:27:30,680 --> 00:27:33,040
Speaker 1: are if you're going to be a Democratic candidate, you

493
00:27:33,160 --> 00:27:35,480
Speaker 1: need that, And there was very little effort to court

494
00:27:35,560 --> 00:27:38,680
Speaker 1: that voting block. And he said said things here and there,

495
00:27:38,680 --> 00:27:41,440
Speaker 1: but you know, it's criminal justice. Things do address those

496
00:27:41,480 --> 00:27:44,080
Speaker 1: kinds of things. He's just not a very vocally like.

497
00:27:44,200 --> 00:27:46,400
Speaker 1: I think the issue is he doesn't say enough out

498
00:27:46,520 --> 00:27:49,639
Speaker 1: vocally that people go, oh, I see him vibing with

499
00:27:49,640 --> 00:27:51,640
Speaker 1: people of color. Now, in the last year he's done

500
00:27:51,640 --> 00:27:53,920
Speaker 1: a lot too, I think changed that. But I think

501
00:27:53,960 --> 00:27:56,400
Speaker 1: a lot of the criticism comes from I think sort

502
00:27:56,400 --> 00:27:58,720
Speaker 1: of the lack of interest and from Hillary to from

503
00:27:58,760 --> 00:28:03,119
Speaker 1: just trying to better understand the black vote. Kind of

504
00:28:03,160 --> 00:28:06,959
Speaker 1: the two the two ends of the spectrum on you know,

505
00:28:07,240 --> 00:28:10,919
Speaker 1: white Democrats trying to appeal to voters of color. Is

506
00:28:10,960 --> 00:28:12,720
Speaker 1: on the one hand, you know, you've got Bernie who

507
00:28:12,760 --> 00:28:15,119
Speaker 1: just doesn't really talk about it, but he talks about

508
00:28:15,240 --> 00:28:20,000
Speaker 1: policies that affect class, which is very influenced, like race

509
00:28:20,040 --> 00:28:22,639
Speaker 1: and class are are deeply intertwined. And then on the

510
00:28:22,680 --> 00:28:25,399
Speaker 1: other end of the spectrum, you've got Hillary Clinton telling

511
00:28:25,400 --> 00:28:29,359
Speaker 1: you that she's your robola, you know, which does that help?

512
00:28:30,240 --> 00:28:34,639
Speaker 1: I have hot sauce in my bag, swag so authentic,

513
00:28:35,000 --> 00:28:39,760
Speaker 1: got hot sauce in my part? What kind Texas pizza?

514
00:28:39,880 --> 00:28:43,320
Speaker 1: Come on, get that ship out? It's not crystal. I

515
00:28:43,320 --> 00:28:47,760
Speaker 1: had slaves in Arkansas? Yeah, did you? Yeah? I mean so.

516
00:28:48,320 --> 00:28:51,880
Speaker 1: Sanders in two thousand sixteen said something about like how

517
00:28:51,920 --> 00:28:56,440
Speaker 1: we need to move beyond identity politics to focus on class,

518
00:28:56,560 --> 00:29:02,000
Speaker 1: which I get very very nervous. Yeah, exactly. It's a

519
00:29:02,000 --> 00:29:05,120
Speaker 1: big it's a big debate right now. Yeah, because people

520
00:29:05,120 --> 00:29:08,320
Speaker 1: are talking about identity politics like it's meaningless, which I

521
00:29:08,320 --> 00:29:10,600
Speaker 1: think is upsetting. But at the same time, identity politics

522
00:29:10,600 --> 00:29:13,200
Speaker 1: are not the whole sum of all politics. I feel

523
00:29:13,200 --> 00:29:19,680
Speaker 1: like it's used by certain white like liberals to suggest that,

524
00:29:19,800 --> 00:29:24,080
Speaker 1: like it's basically their discomfort with focusing on racial issues,

525
00:29:25,360 --> 00:29:27,600
Speaker 1: for do you have to talk about being black all

526
00:29:27,640 --> 00:29:33,560
Speaker 1: the time. But meanwhile, like the entire platform is identity politics,

527
00:29:34,480 --> 00:29:38,160
Speaker 1: and just in the reverse, it's identifying yourself as white

528
00:29:38,240 --> 00:29:44,680
Speaker 1: and identifying people of color and the LGBTQ community as other.

529
00:29:44,960 --> 00:29:48,640
Speaker 1: And yeah, that is identity politics, but it doesn't get

530
00:29:48,680 --> 00:29:51,680
Speaker 1: identified as such. Right, Identity politics as terms are for

531
00:29:51,840 --> 00:29:55,400
Speaker 1: people with marginalized identities who won't shut up about it, right,

532
00:29:55,680 --> 00:29:58,880
Speaker 1: exactly better definition. Right. Yeah, So when you looked at

533
00:29:59,080 --> 00:30:01,520
Speaker 1: I think what that move on pole, that straw pole

534
00:30:01,560 --> 00:30:03,760
Speaker 1: is the thing that got everybody talking about sort of like, oh,

535
00:30:03,880 --> 00:30:06,720
Speaker 1: let's according to these people, it's just about people who

536
00:30:07,040 --> 00:30:09,680
Speaker 1: support for members if they ended up becoming, you know,

537
00:30:09,720 --> 00:30:14,640
Speaker 1: political candidates. Polling, the best of the Democrat percent was

538
00:30:14,840 --> 00:30:19,040
Speaker 1: someone else, don't know, slash other percent Betto fourteen point nine,

539
00:30:19,120 --> 00:30:23,640
Speaker 1: Biden thirteen point one, Bernie ten percent, Campbell Harris six

540
00:30:23,680 --> 00:30:25,800
Speaker 1: point four percent, Elizabeth Warren and then on and on

541
00:30:25,840 --> 00:30:28,240
Speaker 1: and on, and Corey Booker at the very bottom at

542
00:30:28,280 --> 00:30:32,320
Speaker 1: two point six. Yeah, I mean, good good luck to you, Corey.

543
00:30:32,800 --> 00:30:35,640
Speaker 1: Uh so I'm very curious to know what's going on

544
00:30:35,680 --> 00:30:38,280
Speaker 1: because we know Betto has been talking to Obama, He's

545
00:30:38,280 --> 00:30:42,000
Speaker 1: been talking to Al Sharpton, uh, and Andrew Gillim. That

546
00:30:42,080 --> 00:30:44,920
Speaker 1: Andrew Gillim thing is very interesting to me that they're talking,

547
00:30:45,240 --> 00:30:47,640
Speaker 1: what they're talking about, what he is trying to do.

548
00:30:47,720 --> 00:30:50,520
Speaker 1: If he's trying to position himself to be more aggressively

549
00:30:50,680 --> 00:30:53,480
Speaker 1: courting people of color as part of his voting block

550
00:30:53,600 --> 00:30:56,920
Speaker 1: or whatever potential cabinet, I mean, yeah, that would be

551
00:30:57,000 --> 00:30:59,480
Speaker 1: that would be interesting. But yeah, I don't know. It's uh, well,

552
00:31:00,200 --> 00:31:04,000
Speaker 1: we will see. I just know that Joe Biden come

553
00:31:04,040 --> 00:31:09,240
Speaker 1: on now, unless he just has a radical change where

554
00:31:09,280 --> 00:31:14,360
Speaker 1: he's like completely progressive and like updates his politics too.

555
00:31:14,440 --> 00:31:17,120
Speaker 1: Got the rose emoji in his display name, right, which

556
00:31:17,160 --> 00:31:19,480
Speaker 1: I I just don't see happening. Like I think he

557
00:31:19,760 --> 00:31:22,960
Speaker 1: is the Joe Biden needs a pepper in his disapline,

558
00:31:23,760 --> 00:31:27,479
Speaker 1: too spicy. He's the choice for people who are like,

559
00:31:27,520 --> 00:31:30,640
Speaker 1: we just need to do Obama again the exact same thing.

560
00:31:30,720 --> 00:31:33,720
Speaker 1: Remember Obama, that was great, right, let's do it again,

561
00:31:33,760 --> 00:31:37,760
Speaker 1: but without the identity politics, right, yeah, yeah, exactly. It's

562
00:31:37,800 --> 00:31:41,120
Speaker 1: a very you know old Oh god, the thought of

563
00:31:41,200 --> 00:31:45,280
Speaker 1: Joe Biden running is just making me feel heavy, heavy

564
00:31:45,280 --> 00:31:47,840
Speaker 1: and board, yeah, and also worried because I feel like

565
00:31:47,960 --> 00:31:52,160
Speaker 1: enough don't who don't know, who aren't engaged enough politically

566
00:31:52,160 --> 00:31:53,920
Speaker 1: will be like, I don't see what the problem is

567
00:31:53,960 --> 00:31:55,880
Speaker 1: with Joe. But you remember when when Parks and Rack

568
00:31:55,960 --> 00:31:57,680
Speaker 1: had Joe Biden on a bunch of episodes, and like

569
00:31:57,720 --> 00:31:59,880
Speaker 1: the whole thing with Amy Poelard's character was that she

570
00:32:00,080 --> 00:32:03,200
Speaker 1: was like way into Joe Biden. Even then, I was like,

571
00:32:03,240 --> 00:32:05,239
Speaker 1: this isn't working for me, Like he does not have

572
00:32:05,280 --> 00:32:08,440
Speaker 1: a lot of charm as a as a states I

573
00:32:08,440 --> 00:32:11,760
Speaker 1: don't know the way he's intoxicating to white women, middle

574
00:32:11,800 --> 00:32:14,480
Speaker 1: age women. Remember that photo of him with the He's

575
00:32:14,480 --> 00:32:17,680
Speaker 1: got the biker's girlfriend on his lap and he's like

576
00:32:17,720 --> 00:32:20,280
Speaker 1: whispering in her ear and the two biker dudes are

577
00:32:20,320 --> 00:32:25,400
Speaker 1: like this motherfucker and she's like slick, motherfuck Yeah, And

578
00:32:25,440 --> 00:32:29,320
Speaker 1: I'm like, Joe Biden white women, but I just don't

579
00:32:29,320 --> 00:32:31,800
Speaker 1: see I don't see the appeal. I I probably couldn't

580
00:32:31,800 --> 00:32:33,840
Speaker 1: pick him out of a lineup. They had him on

581
00:32:33,880 --> 00:32:35,120
Speaker 1: the show, and I was like, I wonder if this

582
00:32:35,160 --> 00:32:38,160
Speaker 1: is the real Joe Biden. His smile will blind you them.

583
00:32:38,160 --> 00:32:40,960
Speaker 1: Ships are two of them. Teeth are so white, so white,

584
00:32:40,960 --> 00:32:45,760
Speaker 1: so large. Yeah, he is central casting president from a

585
00:32:45,880 --> 00:32:48,960
Speaker 1: nineties movie, like, yeah, just what a president looks like

586
00:32:49,040 --> 00:32:53,240
Speaker 1: in the nineties movie. He's not even an action movie president. Yeah,

587
00:32:53,840 --> 00:32:57,160
Speaker 1: he's like a movie about journalism president. Yeah, and that

588
00:32:57,240 --> 00:32:59,840
Speaker 1: president always ends up being the bad guy, like you,

589
00:33:00,000 --> 00:33:02,560
Speaker 1: and though it comes up in the whole time. Yeah,

590
00:33:02,600 --> 00:33:08,040
Speaker 1: I think like president from the robotcop universe but aspires

591
00:33:08,040 --> 00:33:10,200
Speaker 1: confidence in the populace, but then he's secretly building a

592
00:33:10,280 --> 00:33:14,040
Speaker 1: robot cop. Yeah, exactly. I feel like there's sort of

593
00:33:14,120 --> 00:33:17,760
Speaker 1: frustration from all sides, Like people on the far left

594
00:33:17,760 --> 00:33:22,000
Speaker 1: and like Democratic socialists are concerned that Bernie is being

595
00:33:22,000 --> 00:33:26,280
Speaker 1: criticized for his racial views, and then people who are

596
00:33:26,360 --> 00:33:30,440
Speaker 1: like more center left are concerned that people on the

597
00:33:30,480 --> 00:33:34,160
Speaker 1: far left are criticizing Bett. Oh, and I think we

598
00:33:34,240 --> 00:33:37,320
Speaker 1: need to just be okay with everybody being criticized until

599
00:33:37,360 --> 00:33:40,480
Speaker 1: we have a candidate, like just for the news to

600
00:33:40,720 --> 00:33:44,240
Speaker 1: take its course. Yeah. Why do people wanna perfect? I mean,

601
00:33:44,360 --> 00:33:47,280
Speaker 1: I guess why do people want a perfect candidate? But

602
00:33:48,680 --> 00:33:52,360
Speaker 1: why why do people keep expecting a perfect candidate, especially

603
00:33:52,480 --> 00:33:55,120
Speaker 1: in this system we have Yeah, you're not coming out

604
00:33:55,120 --> 00:33:59,200
Speaker 1: of here unscathed. It's a really interesting time I think

605
00:33:59,200 --> 00:34:02,000
Speaker 1: now and people are starting to talk about class now

606
00:34:02,280 --> 00:34:04,280
Speaker 1: and and a big part of that is Bernie. Bernie

607
00:34:04,320 --> 00:34:07,680
Speaker 1: was like really mainstreamed talking about the working class again

608
00:34:08,239 --> 00:34:10,560
Speaker 1: in a way that the Democrats really haven't for a

609
00:34:10,600 --> 00:34:12,879
Speaker 1: long time, and they certainly haven't explicitly for a long

610
00:34:12,920 --> 00:34:16,399
Speaker 1: time talked about raising up the working class, even using

611
00:34:16,520 --> 00:34:19,680
Speaker 1: using the terms working class families. But where does the

612
00:34:19,719 --> 00:34:22,760
Speaker 1: Democrats money come from. It doesn't come from working class families.

613
00:34:22,800 --> 00:34:25,200
Speaker 1: Maybe it did fifty years ago, but it doesn't anymore

614
00:34:25,320 --> 00:34:29,040
Speaker 1: because their policies have not really helped working class people.

615
00:34:29,160 --> 00:34:31,600
Speaker 1: I mean, everybody knows that the rich have gotten richer

616
00:34:31,600 --> 00:34:33,200
Speaker 1: and the poor have gotten poorer in the class gap

617
00:34:33,360 --> 00:34:36,160
Speaker 1: has just widen and widen and widened. So anything that

618
00:34:36,400 --> 00:34:38,279
Speaker 1: either party has been trying to do to help the

619
00:34:38,320 --> 00:34:42,359
Speaker 1: working classes obviously not fucking working. So but now we're

620
00:34:42,400 --> 00:34:45,920
Speaker 1: coming up on this weird sort of framing um and

621
00:34:46,160 --> 00:34:48,600
Speaker 1: and I do believe this is like it is being

622
00:34:48,640 --> 00:34:51,000
Speaker 1: framed as this in order to weaken it. UH, this

623
00:34:51,080 --> 00:34:55,040
Speaker 1: idea that class uh class politics and a class based

624
00:34:55,040 --> 00:34:59,080
Speaker 1: analysis of politics and economy are at odds with a

625
00:34:59,160 --> 00:35:01,759
Speaker 1: race based and now assists or with the gender based analysis,

626
00:35:01,880 --> 00:35:05,120
Speaker 1: the identity politics analysis, when in fact it's just another

627
00:35:05,200 --> 00:35:09,719
Speaker 1: factor and it's it's all intersectional. Yeah, absolutely, it's not

628
00:35:09,800 --> 00:35:12,239
Speaker 1: an either or thing. But they're being pitted against each other.

629
00:35:12,320 --> 00:35:14,439
Speaker 1: And this is something that honestly Republicans have been doing

630
00:35:14,960 --> 00:35:18,400
Speaker 1: since the thirties to you know, destroy any kind of

631
00:35:18,520 --> 00:35:21,560
Speaker 1: unionization of marginalized groups in the working class. And it's

632
00:35:21,600 --> 00:35:24,080
Speaker 1: just kind of the same thing over again. But it's

633
00:35:24,120 --> 00:35:27,040
Speaker 1: it's very weird to see, Well, the smoke bombing isn't

634
00:35:27,200 --> 00:35:29,120
Speaker 1: is slowly starting to not work as much as they

635
00:35:29,160 --> 00:35:31,280
Speaker 1: used to, like where they would obscure and be like okay,

636
00:35:31,320 --> 00:35:35,719
Speaker 1: now y'all fight. Yeah man, we were both poor. Yeah,

637
00:35:35,719 --> 00:35:38,080
Speaker 1: and it's been like so many years of them doing

638
00:35:38,160 --> 00:35:39,600
Speaker 1: this and we're like, wait a second, that didn't work,

639
00:35:39,640 --> 00:35:41,239
Speaker 1: and that didn't work, and that didn't work, and like

640
00:35:41,560 --> 00:35:44,040
Speaker 1: the only thing that worked was really radical ship that

641
00:35:44,120 --> 00:35:47,200
Speaker 1: then people got murdered by the FBI for when it

642
00:35:47,280 --> 00:35:49,319
Speaker 1: got too far. You know, they were like, okay, we'll

643
00:35:49,360 --> 00:35:52,959
Speaker 1: give we'll civil rights. Okay, fine, ship to the people died,

644
00:35:53,160 --> 00:35:57,120
Speaker 1: Fine you can vote now white people. Yeah, No, no, no, no, no, no,

645
00:35:57,680 --> 00:35:59,960
Speaker 1: time to kill Dr Martin Luther King Jr. Like, that's

646
00:36:00,080 --> 00:36:03,279
Speaker 1: the line is poor people teaming up. And that was

647
00:36:03,400 --> 00:36:06,840
Speaker 1: the thing that you know, made him very unpopular in

648
00:36:06,920 --> 00:36:09,560
Speaker 1: the lead up to his death with white America was

649
00:36:09,640 --> 00:36:12,480
Speaker 1: the idea of him that's that's too far, you know,

650
00:36:12,640 --> 00:36:16,040
Speaker 1: that's that's crossing the line. Yeah. And I think the media,

651
00:36:16,120 --> 00:36:20,919
Speaker 1: which black people, okay, poor people no, no, no, no, no. Yeah.

652
00:36:21,239 --> 00:36:23,920
Speaker 1: And I think the media is somewhat complicit in this.

653
00:36:24,120 --> 00:36:26,360
Speaker 1: I think, like we we've talked before about how the

654
00:36:26,480 --> 00:36:33,320
Speaker 1: Dean scream was somewhat Yeah, that that was that was

655
00:36:34,560 --> 00:36:37,360
Speaker 1: sort of fabricated by the media to be a like

656
00:36:37,520 --> 00:36:39,680
Speaker 1: he did scream like that, but it was because he

657
00:36:39,760 --> 00:36:42,279
Speaker 1: had no It sounded crazy because he had a noise

658
00:36:42,360 --> 00:36:46,200
Speaker 1: canceling microphone, and so it sounded crazy because it was crazy.

659
00:36:46,760 --> 00:36:48,279
Speaker 1: He cares, you know what I mean, that's the thing

660
00:36:48,560 --> 00:36:50,880
Speaker 1: they but they made it a point. I don't think

661
00:36:50,920 --> 00:36:55,600
Speaker 1: we even have to, you know, explain why he did it. Nobody. Yeah,

662
00:36:55,680 --> 00:36:59,480
Speaker 1: all of these things are like really inflated. Yes, And

663
00:37:00,080 --> 00:37:05,080
Speaker 1: I do think that the center media, the mainstream media,

664
00:37:05,280 --> 00:37:10,040
Speaker 1: takes takes it upon themselves to protect capitalism capitalism with

665
00:37:10,120 --> 00:37:15,279
Speaker 1: this idea of electability like well, Bernie Sanders just isn't electable. Yeah,

666
00:37:15,320 --> 00:37:17,240
Speaker 1: like people are too stupid to vote in their own interests.

667
00:37:17,880 --> 00:37:21,280
Speaker 1: Is really the wonder I wonder when the left left

668
00:37:21,360 --> 00:37:25,440
Speaker 1: media will turn on Alexandria Kazio Cortez. Though. What's the

669
00:37:25,520 --> 00:37:28,839
Speaker 1: left media? I mean, like the MSNBC's of the world

670
00:37:29,000 --> 00:37:31,440
Speaker 1: where they're sort of like you know they are, but

671
00:37:31,560 --> 00:37:34,400
Speaker 1: not not like in the way where they're full on trying.

672
00:37:34,520 --> 00:37:36,640
Speaker 1: I mean they buy into like the really stupid, vapid

673
00:37:36,719 --> 00:37:39,160
Speaker 1: headlines of like oh, she messed up this thing or whatever.

674
00:37:39,440 --> 00:37:41,279
Speaker 1: But you know, like on Fox, they're in full on

675
00:37:41,440 --> 00:37:43,839
Speaker 1: like terror mode I'm talking about when they're like they

676
00:37:43,920 --> 00:37:45,839
Speaker 1: tear her the funk down. Like now they're just started

677
00:37:45,920 --> 00:37:48,839
Speaker 1: being like, well she seems like a spirited young they're

678
00:37:48,880 --> 00:37:50,759
Speaker 1: more dismissive right now. I think it's going to be

679
00:37:50,760 --> 00:37:53,719
Speaker 1: when she starts implementing policy really and also if she

680
00:37:53,760 --> 00:37:57,560
Speaker 1: speaks it more about about Palestine. I think that's really

681
00:37:57,600 --> 00:37:59,520
Speaker 1: going to be because that's been what she's been torn

682
00:37:59,600 --> 00:38:02,399
Speaker 1: down for most on you know mainstream media. That's us

683
00:38:02,440 --> 00:38:05,400
Speaker 1: liberal um is you know, being being called anti Semitic

684
00:38:05,480 --> 00:38:08,359
Speaker 1: for for opposing Israel, right right. I think the one

685
00:38:08,440 --> 00:38:12,040
Speaker 1: good thing with her that will make it difficult for

686
00:38:12,080 --> 00:38:14,880
Speaker 1: them to tear down is she's got a Trump like

687
00:38:15,320 --> 00:38:18,120
Speaker 1: unflappable nous on Twitter, Like she's just like, you're not

688
00:38:18,160 --> 00:38:20,000
Speaker 1: fucking knocking me off my message home. She's like, I'm

689
00:38:20,040 --> 00:38:24,320
Speaker 1: a twenty nine year old Twitter literate millennial getting my

690
00:38:24,400 --> 00:38:27,000
Speaker 1: mention to see what happened. You want to quote tweet

691
00:38:27,040 --> 00:38:29,839
Speaker 1: me poorly, I'm going to do it for it. Yes,

692
00:38:30,080 --> 00:38:33,120
Speaker 1: I'm trying to thread this ship, all right. Speaking of

693
00:38:34,280 --> 00:38:38,440
Speaker 1: Congress being in the mainstream political elite being somewhat out

694
00:38:38,480 --> 00:38:44,160
Speaker 1: of touch with the realities of our world, the CEO

695
00:38:44,680 --> 00:38:48,920
Speaker 1: of Google visited The Hill on Tuesday, where he faced

696
00:38:49,440 --> 00:38:54,120
Speaker 1: a grilling. On the one hand, you know, hardline conservatives

697
00:38:54,200 --> 00:38:58,239
Speaker 1: were performing for the cameras with their uninformed questioning around

698
00:38:58,280 --> 00:39:01,640
Speaker 1: the conspiracy that Google is biased against conservative views and

699
00:39:01,760 --> 00:39:06,840
Speaker 1: like screens searches or conservative results. And then you had

700
00:39:06,920 --> 00:39:10,360
Speaker 1: Democrats pressing for answers on all the data mining and

701
00:39:10,520 --> 00:39:13,120
Speaker 1: just violations of privacy that we talked about a little

702
00:39:13,120 --> 00:39:17,080
Speaker 1: bit earlier, and the near monopoly they have, which is

703
00:39:17,600 --> 00:39:21,279
Speaker 1: very dangerous and should be the only focus of this.

704
00:39:22,000 --> 00:39:27,440
Speaker 1: But then there was also the dudes like Iowa Nazi

705
00:39:27,560 --> 00:39:32,399
Speaker 1: Steve King, who just clearly didn't understand technology and treat

706
00:39:32,440 --> 00:39:36,360
Speaker 1: it like when you go to an older relatives house

707
00:39:36,640 --> 00:39:38,480
Speaker 1: and they're like, here, let me show you this thing,

708
00:39:38,560 --> 00:39:41,360
Speaker 1: and it always turns into you being their tech support.

709
00:39:42,320 --> 00:39:46,080
Speaker 1: Your gee. My mom called me ten times yesterday because

710
00:39:46,160 --> 00:39:48,600
Speaker 1: the Uber app on her phone had disappeared. Yes, I

711
00:39:48,680 --> 00:39:51,400
Speaker 1: still don't know, like I think she deleted it by accident,

712
00:39:52,560 --> 00:39:55,040
Speaker 1: and then she said it's open or what I really

713
00:39:55,120 --> 00:39:56,359
Speaker 1: have No, I still have no idea what to put

714
00:39:56,400 --> 00:39:59,560
Speaker 1: it in a folder? She put it on the home

715
00:39:59,640 --> 00:40:03,640
Speaker 1: screens rags on another icon that the maniac for long pressing.

716
00:40:03,719 --> 00:40:09,960
Speaker 1: She's always like, do I want to Yeah, she goes,

717
00:40:09,960 --> 00:40:12,680
Speaker 1: it's wiggling. I don't know what to do. All right,

718
00:40:12,680 --> 00:40:17,680
Speaker 1: I'll come over anyways, let's here d Steve King's highly

719
00:40:17,719 --> 00:40:21,279
Speaker 1: informed questioning of the CEO of Google. I have a

720
00:40:21,440 --> 00:40:25,360
Speaker 1: seven year old granddaughter who picked up her phone before

721
00:40:25,440 --> 00:40:28,840
Speaker 1: the election, and she's playing a little game, kind of

722
00:40:28,880 --> 00:40:31,160
Speaker 1: game a kid would play, and up on their pops

723
00:40:31,160 --> 00:40:33,600
Speaker 1: a picture of her grandfather. And I'm not going to

724
00:40:33,680 --> 00:40:36,160
Speaker 1: say into the record what the kind of language was

725
00:40:36,280 --> 00:40:39,040
Speaker 1: used around that picture of her grandfather. But I would

726
00:40:39,040 --> 00:40:41,000
Speaker 1: ask you, how does that show up on a seven

727
00:40:41,080 --> 00:40:46,800
Speaker 1: year olds iPhone who's playing a kid's game? Congressman iPhone

728
00:40:46,880 --> 00:40:48,920
Speaker 1: is made by a different company, and so you know,

729
00:40:49,200 --> 00:40:51,680
Speaker 1: I mean it might have been an android. It's just

730
00:40:52,239 --> 00:40:54,880
Speaker 1: it was a hand me down to some guy. Uh,

731
00:40:55,800 --> 00:41:00,480
Speaker 1: you know, I guess I'm happy to paulled open on

732
00:41:00,840 --> 00:41:03,799
Speaker 1: the specifics. There may be an application which was being

733
00:41:03,920 --> 00:41:07,240
Speaker 1: used which had a notification, but I'm happy to understand

734
00:41:07,280 --> 00:41:10,520
Speaker 1: it better and classified for you. Okay, thank you for

735
00:41:10,560 --> 00:41:15,040
Speaker 1: your testimony. And it's just like, Okay, I thought I

736
00:41:15,040 --> 00:41:17,000
Speaker 1: would get him on that one. That guy has worked

737
00:41:17,120 --> 00:41:20,279
Speaker 1: in tech support. You can tell yeah, like yeah, he's

738
00:41:20,280 --> 00:41:22,719
Speaker 1: an engine. He's like okay, um, let's talk about this

739
00:41:22,800 --> 00:41:25,399
Speaker 1: later so you don't embarrass yourself. I understand your concern sir.

740
00:41:25,760 --> 00:41:27,920
Speaker 1: I have a lot of tickets though, and again the

741
00:41:27,960 --> 00:41:30,560
Speaker 1: whole thing of like how does my granddaughter finding out

742
00:41:30,680 --> 00:41:34,279
Speaker 1: I'm a racist nazi taint scab? Like? Like what did

743
00:41:34,360 --> 00:41:36,320
Speaker 1: it say? Was it like Steve King is a cocksucker?

744
00:41:36,480 --> 00:41:38,760
Speaker 1: Like what? Maybe? Unless it was like a want head headline,

745
00:41:38,800 --> 00:41:41,480
Speaker 1: I can't imagine any thing that had like an outright

746
00:41:41,560 --> 00:41:44,520
Speaker 1: aggressive ship. That would be like unless he really does

747
00:41:44,600 --> 00:41:46,560
Speaker 1: take offensive the fact that people do point out that

748
00:41:46,640 --> 00:41:49,480
Speaker 1: he's not think and he was like, how did I

749
00:41:49,560 --> 00:41:51,440
Speaker 1: mean not? Also like, why does your seven year old

750
00:41:51,520 --> 00:41:54,560
Speaker 1: have a smartphone? Man? Like, why do you use there's

751
00:41:54,600 --> 00:41:57,080
Speaker 1: kid protect because the parents can't be bothered to entertain

752
00:41:57,160 --> 00:41:59,239
Speaker 1: the kids? Or sorry, m might have been an and

753
00:41:59,400 --> 00:42:00,680
Speaker 1: or you don't even know if your kid has an

754
00:42:00,719 --> 00:42:04,040
Speaker 1: iPhone or an Android? Do what kind of grandpa are you? Right? Also,

755
00:42:04,120 --> 00:42:05,759
Speaker 1: it had to be a Nexus phone if he's gonna

756
00:42:05,760 --> 00:42:08,279
Speaker 1: answer directly as the head of Google, Okay, not just

757
00:42:08,360 --> 00:42:11,240
Speaker 1: some android, that's just the operating system. Okay, next, angry

758
00:42:11,280 --> 00:42:14,040
Speaker 1: tech support guy Miles come in, thank you. Next, But no,

759
00:42:14,400 --> 00:42:17,440
Speaker 1: that's other loss for the olds. By the way, I

760
00:42:17,520 --> 00:42:21,399
Speaker 1: didn't realize how old Steve King is. He's just like yeah.

761
00:42:22,239 --> 00:42:24,839
Speaker 1: A lot of people were just asking really weird things,

762
00:42:24,880 --> 00:42:27,760
Speaker 1: Like another Democrat was like, how come when you search idiot,

763
00:42:27,840 --> 00:42:31,560
Speaker 1: Trump's name comes up, and they're like, it's called gaming

764
00:42:31,600 --> 00:42:34,160
Speaker 1: the algorithm and read it and people just you know,

765
00:42:34,280 --> 00:42:36,880
Speaker 1: you upvote this ship enough you can just change out. Honestly,

766
00:42:37,000 --> 00:42:41,879
Speaker 1: terrifying how little every elected representative knows about basic Internet, yes,

767
00:42:42,080 --> 00:42:44,920
Speaker 1: you know, but the Steve King thing, I mean, clearly

768
00:42:45,840 --> 00:42:49,480
Speaker 1: his granddaughter was not playing some kids game. And then

769
00:42:49,800 --> 00:42:54,640
Speaker 1: a web page just spontaneously opened and criticized her grandfather.

770
00:42:55,160 --> 00:42:59,279
Speaker 1: She was googling her grandfather plus tain't scab, and she

771
00:43:00,080 --> 00:43:01,640
Speaker 1: up a page that said he was a taint scat

772
00:43:01,920 --> 00:43:03,360
Speaker 1: and he was like, wait, well, let me see what

773
00:43:03,440 --> 00:43:05,640
Speaker 1: you're looking at there, and then she made up a

774
00:43:05,719 --> 00:43:09,479
Speaker 1: lie about how like the phone made her do it. Um, yeah,

775
00:43:09,640 --> 00:43:12,719
Speaker 1: well you know they were they were really going all in.

776
00:43:12,840 --> 00:43:16,400
Speaker 1: They were pulling up all these like just debunked studies

777
00:43:16,440 --> 00:43:19,279
Speaker 1: about how like it favors the left or whatever. And

778
00:43:19,360 --> 00:43:21,319
Speaker 1: one person was like, how come when you searched other

779
00:43:21,400 --> 00:43:24,000
Speaker 1: Republican tax bill it talked about how it would it

780
00:43:24,160 --> 00:43:28,440
Speaker 1: was really unfavorable to working people in the media, But

781
00:43:28,560 --> 00:43:30,440
Speaker 1: that shows you their blind spot is like are they

782
00:43:30,560 --> 00:43:32,680
Speaker 1: so up there? I mean they must be so up

783
00:43:32,719 --> 00:43:36,600
Speaker 1: Their own asked too that they're like, I don't truth up.

784
00:43:36,680 --> 00:43:39,000
Speaker 1: Here's the thing they don't understand that Google is not

785
00:43:39,120 --> 00:43:43,520
Speaker 1: an objective search like Google is a search that points

786
00:43:43,560 --> 00:43:45,920
Speaker 1: you to the pages that are visited the most, and

787
00:43:45,960 --> 00:43:48,960
Speaker 1: then those pages exponentially get visited more and then their

788
00:43:49,000 --> 00:43:51,920
Speaker 1: number one in search results. Like, Google is not an objective.

789
00:43:52,120 --> 00:43:55,040
Speaker 1: The algorithm is not objective. It is not like neutral.

790
00:43:55,440 --> 00:43:58,680
Speaker 1: You get search results tailored to the search results you

791
00:43:58,800 --> 00:44:01,480
Speaker 1: click on. So if you search yourself, oh, Steve King,

792
00:44:01,520 --> 00:44:03,839
Speaker 1: I'm gonna name search Steve King. First thing that comes

793
00:44:03,880 --> 00:44:06,040
Speaker 1: up as Steve King is a fucking Nazi. You click

794
00:44:06,080 --> 00:44:08,280
Speaker 1: on that, You're like, who's calling me a nazi? Boom,

795
00:44:08,360 --> 00:44:11,160
Speaker 1: Google's gonna give you that. More so, like they're acting

796
00:44:11,239 --> 00:44:13,760
Speaker 1: like Google is this you know, like what I asked

797
00:44:13,840 --> 00:44:16,240
Speaker 1: God and God said my tax bill was back. Google's

798
00:44:16,280 --> 00:44:20,400
Speaker 1: not God. It's a product, right, Yeah, those questions were

799
00:44:20,440 --> 00:44:22,600
Speaker 1: so funny, though. There's another one about how they're just

800
00:44:22,719 --> 00:44:25,240
Speaker 1: like and this other bill, it was like lying about

801
00:44:25,320 --> 00:44:27,400
Speaker 1: this thing, and it's like it wasn't it was giving

802
00:44:27,440 --> 00:44:29,840
Speaker 1: you the analysis of like what trying to blow up

803
00:44:29,920 --> 00:44:31,920
Speaker 1: the Affordable Care Act was going to do, or what

804
00:44:32,280 --> 00:44:33,719
Speaker 1: these other things were going to do. And they're like,

805
00:44:34,280 --> 00:44:37,480
Speaker 1: it's just so I can't believe this information is so free. Right,

806
00:44:38,239 --> 00:44:40,040
Speaker 1: all right, we're gonna take another quick break. We'll be

807
00:44:40,200 --> 00:44:55,359
Speaker 1: right back, and we're back. And the fallout from yesterday's

808
00:44:55,440 --> 00:45:00,560
Speaker 1: immediately famous Oval Office meeting between Trump, Nancy Pelosi, and

809
00:45:00,640 --> 00:45:05,520
Speaker 1: Chuck Schumer continues, and apparently the president, you know, he

810
00:45:05,640 --> 00:45:08,160
Speaker 1: went in thinking he was going to ambush them, and

811
00:45:08,480 --> 00:45:12,040
Speaker 1: he came out apparently just throwing his papers to the

812
00:45:12,160 --> 00:45:17,239
Speaker 1: floor and complaining that he got ambushed. Um, it's my

813
00:45:17,360 --> 00:45:20,880
Speaker 1: favorite ship because he was he was like bragging out

814
00:45:20,920 --> 00:45:22,480
Speaker 1: I got the votes, and Nacy like, we'll pull up

815
00:45:22,520 --> 00:45:26,200
Speaker 1: with the votes. Then you don't got shit. Well that's

816
00:45:26,200 --> 00:45:28,719
Speaker 1: what I got. Ship back down, you pee sitting down now.

817
00:45:29,960 --> 00:45:35,239
Speaker 1: So basically what happened exactly. Yeah, so one thing was

818
00:45:35,280 --> 00:45:39,800
Speaker 1: like he threw his ship, then he thank you exactly

819
00:45:40,000 --> 00:45:43,239
Speaker 1: you spit on your face. Then he basically went on

820
00:45:43,360 --> 00:45:46,440
Speaker 1: to complain about how that was such an embarrassment. He

821
00:45:46,640 --> 00:45:49,479
Speaker 1: was really piste off that Chuck Schumer wasn't even looking

822
00:45:49,520 --> 00:45:51,600
Speaker 1: at him while he was just making jokes to the press,

823
00:45:51,640 --> 00:45:53,719
Speaker 1: because Schumer was just sort of like going, what about

824
00:45:53,760 --> 00:45:57,239
Speaker 1: this asshole? That really got to fucking Trump to the

825
00:45:57,280 --> 00:45:59,600
Speaker 1: point that even like once the press left, like okay,

826
00:45:59,640 --> 00:46:01,840
Speaker 1: let's have a meeting, Like he couldn't he couldn't recover,

827
00:46:01,920 --> 00:46:06,000
Speaker 1: and he was like, yeah, I know when I'm being unrespected. Yeah, seriously,

828
00:46:06,400 --> 00:46:08,719
Speaker 1: and uh, One of the funniest things is like he

829
00:46:08,920 --> 00:46:12,279
Speaker 1: got really mad at Mike Pence. He felt that Mike

830
00:46:12,360 --> 00:46:14,719
Speaker 1: Pence when he powered down in front of everybody like that,

831
00:46:15,800 --> 00:46:18,879
Speaker 1: he was like, you burned me Pence. I think he's

832
00:46:18,960 --> 00:46:21,320
Speaker 1: right though. I think this is this is in keeping

833
00:46:21,560 --> 00:46:25,879
Speaker 1: with my theory that something happened with the revelations, either

834
00:46:25,960 --> 00:46:28,800
Speaker 1: that we know about or stuff we don't quite know

835
00:46:29,000 --> 00:46:31,160
Speaker 1: yet because of all the redactions, but with the Muller

836
00:46:31,200 --> 00:46:34,920
Speaker 1: investigation in the Southern District of New York investigation, like

837
00:46:35,200 --> 00:46:39,000
Speaker 1: last week's revelations that the Pence camp seems to have cooled.

838
00:46:40,440 --> 00:46:45,080
Speaker 1: Um and yeah, Mike Pence definitely like the memes around

839
00:46:45,520 --> 00:46:48,160
Speaker 1: what was going through his mind. We're we're a lot

840
00:46:48,239 --> 00:46:51,120
Speaker 1: of fun but also kind of unavoidable. When you look

841
00:46:51,160 --> 00:46:54,400
Speaker 1: at his performance, he just either choked or was like

842
00:46:54,440 --> 00:46:57,200
Speaker 1: I don't want anything. He almost looked like a spouse

843
00:46:57,440 --> 00:47:00,480
Speaker 1: of like an alcoholic who's like it inner and the

844
00:47:00,520 --> 00:47:03,680
Speaker 1: spouse is drunk and they're just like the thing, what

845
00:47:03,680 --> 00:47:06,440
Speaker 1: do you mean I can't take left over some mission buffet.

846
00:47:07,440 --> 00:47:10,120
Speaker 1: I paid for it. I'm gonna take it home. Where's

847
00:47:10,200 --> 00:47:12,920
Speaker 1: my food? We already ate? And then he where is it.

848
00:47:13,200 --> 00:47:15,719
Speaker 1: He was literally closing his eyes like fucking Luke Skywalker

849
00:47:15,760 --> 00:47:17,960
Speaker 1: in the last Star Wars movie, trying to like actually

850
00:47:18,080 --> 00:47:20,440
Speaker 1: project himself into another place, like please give me the

851
00:47:20,480 --> 00:47:25,600
Speaker 1: funk out of here, just visualizing Hawaii somewhere else. Yeah,

852
00:47:25,960 --> 00:47:28,520
Speaker 1: and then he said they set me up. But the

853
00:47:28,640 --> 00:47:30,799
Speaker 1: funny thing is in the Daily Beasts they report how

854
00:47:31,120 --> 00:47:33,880
Speaker 1: Trump initially this was supposed to be a no cameras,

855
00:47:34,080 --> 00:47:36,360
Speaker 1: behind closed door thing and at the zero hour was like,

856
00:47:36,440 --> 00:47:38,040
Speaker 1: you know what, let's bring the press in because I

857
00:47:38,080 --> 00:47:40,080
Speaker 1: think I'm gonna press him about the wall and see

858
00:47:40,080 --> 00:47:42,919
Speaker 1: how they handle it. And then got his big wind

859
00:47:43,000 --> 00:47:48,239
Speaker 1: coming up, just flipped like, you fucking idiot, you poor

860
00:47:48,400 --> 00:47:51,360
Speaker 1: poor idiots. You can't say no to those cameras for that,

861
00:47:51,480 --> 00:47:53,880
Speaker 1: and then just gets looks like a total ass, like

862
00:47:53,920 --> 00:47:56,560
Speaker 1: he's supposed to be Mr. Reality TV and he just

863
00:47:56,840 --> 00:47:59,880
Speaker 1: showed his ass so bad, and somehow then did the

864
00:48:00,120 --> 00:48:02,680
Speaker 1: worst thing you can do is be like, yeah, I'll

865
00:48:02,760 --> 00:48:06,000
Speaker 1: on the shut down. Yeah. At the same time, so

866
00:48:06,440 --> 00:48:09,160
Speaker 1: I did read an analysis of this on The Daily Beast,

867
00:48:09,239 --> 00:48:13,160
Speaker 1: which obviously is not a conservative place, where they somebody

868
00:48:13,239 --> 00:48:15,800
Speaker 1: was saying that they thought Trump actually won that in

869
00:48:16,080 --> 00:48:20,000
Speaker 1: his like weird version of reality, not just like he

870
00:48:20,120 --> 00:48:22,320
Speaker 1: believes he want it, but the people who he appeals

871
00:48:22,400 --> 00:48:25,279
Speaker 1: to would think he wanted. And the idea is that

872
00:48:26,160 --> 00:48:29,320
Speaker 1: while Nancy and Chuck we're trying to they were like,

873
00:48:29,440 --> 00:48:33,080
Speaker 1: let's talk behind closed doors because political decorum, he was like, no,

874
00:48:33,239 --> 00:48:36,080
Speaker 1: let's do it right here. And that does seem like,

875
00:48:36,920 --> 00:48:40,560
Speaker 1: I don't know, political decorum is popular with the mainstream media,

876
00:48:40,719 --> 00:48:43,480
Speaker 1: but for you know, the people who vote for Trump

877
00:48:43,560 --> 00:48:48,000
Speaker 1: and even just regular people, I feel like urging somebody

878
00:48:48,080 --> 00:48:51,160
Speaker 1: to do, like have the conversation behind closed doors as

879
00:48:51,200 --> 00:48:54,400
Speaker 1: an immediate like red flag. Right. Well, I think the

880
00:48:54,520 --> 00:48:57,279
Speaker 1: hit isn't necessarily like, I don't think he gains from

881
00:48:57,320 --> 00:48:58,839
Speaker 1: it being out in the open. I think the hit

882
00:48:58,920 --> 00:49:02,000
Speaker 1: he takes is from openly owning a shutdown if it

883
00:49:02,080 --> 00:49:04,920
Speaker 1: happens over the wall, right, And like that's the part

884
00:49:05,000 --> 00:49:06,520
Speaker 1: that isn't a good look because we're used to him

885
00:49:06,640 --> 00:49:09,759
Speaker 1: just having a hissy fit in public. Trump, I think,

886
00:49:09,800 --> 00:49:12,399
Speaker 1: like throughout the campaign has always been like, yeah, I'll

887
00:49:12,440 --> 00:49:15,080
Speaker 1: make Mexico pay for the wall. Yeah, I'll do it. Yeah.

888
00:49:15,360 --> 00:49:17,480
Speaker 1: You know, He's always that like, yeah, I'm gonna fucking

889
00:49:17,520 --> 00:49:19,480
Speaker 1: do it. I'm gonna do the thing is unthinkable. And

890
00:49:19,560 --> 00:49:22,000
Speaker 1: now that you know he got sort of confronted about

891
00:49:22,000 --> 00:49:23,719
Speaker 1: the shutdown, he was like, yeah, fuck it, you know,

892
00:49:23,840 --> 00:49:26,200
Speaker 1: I don't care. And then all his constituency was like,

893
00:49:26,320 --> 00:49:29,520
Speaker 1: we care. Yeah. At the same time, he's fighting for

894
00:49:29,600 --> 00:49:33,040
Speaker 1: a thing his constituents want or think they want, in

895
00:49:33,120 --> 00:49:36,120
Speaker 1: the wall, and he's willing to do an unpopular thing

896
00:49:36,160 --> 00:49:38,560
Speaker 1: to get it with the shutdown. Now, I think the

897
00:49:38,840 --> 00:49:40,880
Speaker 1: place that the l is really going to come is

898
00:49:41,000 --> 00:49:44,120
Speaker 1: when the shutdown actually happens. If he really does force

899
00:49:44,239 --> 00:49:47,920
Speaker 1: it and then it's a complete fucking disaster and he

900
00:49:48,000 --> 00:49:51,160
Speaker 1: still doesn't get his wall, then yeah, that's not going

901
00:49:51,200 --> 00:49:53,120
Speaker 1: to be a good look for him. Well, there was

902
00:49:53,160 --> 00:49:55,279
Speaker 1: a thing. I don't know if how real it was,

903
00:49:55,360 --> 00:49:57,960
Speaker 1: but there was some article saying that the wall was

904
00:49:58,040 --> 00:50:01,719
Speaker 1: just merely a mnemonic device for him to talk about immigration.

905
00:50:02,320 --> 00:50:05,160
Speaker 1: For sure, that it wasn't pnemon means, but okay, but yeah,

906
00:50:05,239 --> 00:50:07,720
Speaker 1: that's what they were. They needed it as like a concept,

907
00:50:07,719 --> 00:50:11,319
Speaker 1: as a nod to help the candidate, remember metaphor synic

908
00:50:11,400 --> 00:50:14,000
Speaker 1: to key New York, it's yeah, thank you so much.

909
00:50:14,160 --> 00:50:18,000
Speaker 1: It is a synectic. Yes, immigration, Well, you just got

910
00:50:18,040 --> 00:50:20,920
Speaker 1: an English major on your show. But holy sh it. Um.

911
00:50:21,440 --> 00:50:23,400
Speaker 1: So then yeah, and then essentially he just took it

912
00:50:23,480 --> 00:50:26,919
Speaker 1: literally and then his melted brain just turned it into

913
00:50:26,960 --> 00:50:28,719
Speaker 1: the thing that it's like, say the wall so they

914
00:50:28,760 --> 00:50:30,840
Speaker 1: know immigration. He's like, no, it's a literal wall that

915
00:50:30,880 --> 00:50:35,840
Speaker 1: I want it. Okay whatever. Um. But then but the

916
00:50:35,880 --> 00:50:37,440
Speaker 1: other thing is like you see, it's like he's like

917
00:50:37,520 --> 00:50:39,280
Speaker 1: someone's like, you gotta ask for her hand in marriage,

918
00:50:39,320 --> 00:50:44,040
Speaker 1: and he's literally like, I want your hand. I have

919
00:50:44,160 --> 00:50:46,360
Speaker 1: the hand. What I do now, Steve, I have the hand? No? No, no,

920
00:50:46,680 --> 00:50:52,040
Speaker 1: Jesus Okay. First of all, you're glad. Yeah. Well, the

921
00:50:52,400 --> 00:50:55,160
Speaker 1: Senator Kennedy from Louisiana, John Kennedy, he was like he

922
00:50:55,360 --> 00:50:57,120
Speaker 1: was basically saying, like if I were playing poker with

923
00:50:57,160 --> 00:50:58,960
Speaker 1: the president and he was across the table from me,

924
00:50:59,040 --> 00:51:00,960
Speaker 1: and he had demonstrated the face that he demonstrated in

925
00:51:01,040 --> 00:51:03,480
Speaker 1: that meeting, and I wasn't holding good cards, I'd fold

926
00:51:03,840 --> 00:51:06,120
Speaker 1: because I don't think he's bluffing. I think he's prepared

927
00:51:06,120 --> 00:51:07,840
Speaker 1: to shut down a really long way to say I

928
00:51:07,880 --> 00:51:09,960
Speaker 1: don't think he's bluffing. Yeah, but it's just sort of

929
00:51:10,000 --> 00:51:12,319
Speaker 1: like that you're starting to see. Also, the weird sort

930
00:51:12,360 --> 00:51:16,319
Speaker 1: of the sycophant comments steam in about like they're like, yeah,

931
00:51:16,440 --> 00:51:18,719
Speaker 1: he's digging in or whatever. It's like, yeah, I don't

932
00:51:18,760 --> 00:51:21,800
Speaker 1: think it's as clear cut a win as the media

933
00:51:21,920 --> 00:51:24,680
Speaker 1: has portrayed, or at least people who pay attention to

934
00:51:24,719 --> 00:51:26,440
Speaker 1: the media. I don't even I don't think it's a

935
00:51:26,600 --> 00:51:27,759
Speaker 1: I don't get me wrong, I don't think this is

936
00:51:27,800 --> 00:51:30,279
Speaker 1: a policy win in any way. This is nearly just

937
00:51:30,400 --> 00:51:33,879
Speaker 1: like a ship talking at lunch break win. His whole

938
00:51:33,920 --> 00:51:36,000
Speaker 1: campaign was I'm going to build a wall. And now

939
00:51:36,080 --> 00:51:38,160
Speaker 1: he's like, I'm building a wall, and all his constituents

940
00:51:38,200 --> 00:51:40,480
Speaker 1: are like great, and then every everyone voting for him

941
00:51:40,560 --> 00:51:41,960
Speaker 1: is like good. And he's like, I'm building a wall.

942
00:51:41,960 --> 00:51:43,320
Speaker 1: And they're like, we're going to shut down the government.

943
00:51:43,320 --> 00:51:45,080
Speaker 1: And he was like, I care, I'm building a wall. Yeah.

944
00:51:45,160 --> 00:51:47,040
Speaker 1: You know, he's like, you're going to shut down the government.

945
00:51:47,080 --> 00:51:50,120
Speaker 1: He's like, I'm going to shut down just repeat said

946
00:51:51,280 --> 00:51:54,680
Speaker 1: and taxpayers are gonna shut down the government down. Mexico

947
00:51:54,800 --> 00:51:57,040
Speaker 1: is not paying for it, no, but I think apparently

948
00:51:57,080 --> 00:51:59,719
Speaker 1: after the camera's left, he insisted that Mexico was still

949
00:51:59,719 --> 00:52:02,439
Speaker 1: paying for us to Nancy, yeah, I'm excited to see

950
00:52:02,440 --> 00:52:04,600
Speaker 1: how Mexican's new president is going to deal with this

951
00:52:04,800 --> 00:52:09,600
Speaker 1: because he's am low baby Manuel Lopez Opera Door. I

952
00:52:09,640 --> 00:52:11,840
Speaker 1: don't think, Yeah, he's he might just be like I

953
00:52:11,920 --> 00:52:13,840
Speaker 1: don't know, I don't know her. He is like, I

954
00:52:13,880 --> 00:52:16,279
Speaker 1: don't know her. He's he's pretty lefty. Yeah, he's he's like,

955
00:52:16,360 --> 00:52:19,520
Speaker 1: we're not paying for this. Um. I hope things improve

956
00:52:19,560 --> 00:52:23,880
Speaker 1: in to Juanna for those caravans, Yeah, Jesus, because now

957
00:52:23,920 --> 00:52:26,239
Speaker 1: they're trying to look for for money to like go back.

958
00:52:26,400 --> 00:52:29,640
Speaker 1: Essentially too. A lot of them were deported, were taken back,

959
00:52:29,840 --> 00:52:31,719
Speaker 1: and then the ones that are remaining they just have like,

960
00:52:32,040 --> 00:52:34,759
Speaker 1: you know, no financials, they have no financial recourse, they

961
00:52:34,760 --> 00:52:36,319
Speaker 1: have no resources. A lot of people in the city

962
00:52:36,360 --> 00:52:38,520
Speaker 1: don't want them there. You know. There are also racist

963
00:52:38,560 --> 00:52:40,880
Speaker 1: people in Mexico, you know, and they're like fun condorans

964
00:52:40,960 --> 00:52:43,879
Speaker 1: or whatever. So yeah, they're in a really fucked up spot.

965
00:52:43,880 --> 00:52:45,400
Speaker 1: And a lot of them are the people that are

966
00:52:45,480 --> 00:52:48,040
Speaker 1: left or people that like have kids and and are

967
00:52:48,080 --> 00:52:50,399
Speaker 1: taking care of kids, and you know, to go back

968
00:52:50,719 --> 00:52:53,239
Speaker 1: is a lot worse. They're waiting for asylum. There's people

969
00:52:53,280 --> 00:52:55,120
Speaker 1: are just getting sick. You know. This is what happens

970
00:52:55,160 --> 00:52:57,880
Speaker 1: when large groups of people live on the street for

971
00:52:57,920 --> 00:53:01,279
Speaker 1: a while, people start getting really fucking sick. That's why

972
00:53:01,320 --> 00:53:03,680
Speaker 1: we have Typhus in l A. Now there's typus. Now

973
00:53:03,760 --> 00:53:08,560
Speaker 1: there's Typus on skin row. Mm hmmm, that's not good. Well,

974
00:53:09,320 --> 00:53:17,680
Speaker 1: speaking of not good, yes, low energy Michael Cohen h

975
00:53:18,200 --> 00:53:21,839
Speaker 1: is going to prison. Yeah. My prediction he will join

976
00:53:21,880 --> 00:53:26,279
Speaker 1: the Nartagnio gang in prison to survive. Uh yeah, I mean,

977
00:53:26,360 --> 00:53:28,840
Speaker 1: there's nothing really new. He basically went up to the

978
00:53:28,960 --> 00:53:33,040
Speaker 1: judge and was like, hey, I cooperated and also my

979
00:53:33,520 --> 00:53:36,239
Speaker 1: his quote was my blind loyalty to President Trump led

980
00:53:36,320 --> 00:53:39,880
Speaker 1: me to the darkness. But the judge was like, no,

981
00:53:40,360 --> 00:53:42,840
Speaker 1: I'm sorry, you get three years. I don't care. Like

982
00:53:43,000 --> 00:53:45,560
Speaker 1: Robert Mueller, he was like, well, he cooperated enough, we'll

983
00:53:45,600 --> 00:53:48,160
Speaker 1: recommend you to six months. But we're the Southern District

984
00:53:48,200 --> 00:53:50,560
Speaker 1: of New York and their dealings with him, they're like, yo,

985
00:53:50,640 --> 00:53:53,120
Speaker 1: this man was not easy to work with. He wasn't

986
00:53:53,160 --> 00:53:56,600
Speaker 1: being forthcoming with answers, and he sucked around and he

987
00:53:56,680 --> 00:53:59,440
Speaker 1: found out. So he's gonna do a little three year stretch.

988
00:53:59,640 --> 00:54:03,960
Speaker 1: Some Aller recommended that he be treated with leniency, but

989
00:54:04,120 --> 00:54:06,720
Speaker 1: then the Southern District of New York was like Nahu

990
00:54:06,920 --> 00:54:09,399
Speaker 1: that because he pitched off all the like New York

991
00:54:09,480 --> 00:54:11,840
Speaker 1: state crimes to him, Molly kept it to like, everything

992
00:54:11,880 --> 00:54:13,840
Speaker 1: I want to know about Russia, please tell me. And

993
00:54:13,920 --> 00:54:15,359
Speaker 1: that's the thing. We still don't know what he said

994
00:54:15,360 --> 00:54:17,719
Speaker 1: about what he told Robert Mueller, so it's not fair

995
00:54:17,800 --> 00:54:20,239
Speaker 1: to assess what exactly he knows or doesn't know. But

996
00:54:20,320 --> 00:54:22,759
Speaker 1: apparently when it came to his like financial crimes in

997
00:54:22,840 --> 00:54:26,560
Speaker 1: New York, he was sort of like, so, yeah, that's

998
00:54:26,560 --> 00:54:28,840
Speaker 1: what you get. You're gonna do three years, uh and

999
00:54:29,160 --> 00:54:32,160
Speaker 1: go go to jail now, yeah. Uh. And then also

1000
00:54:32,680 --> 00:54:36,160
Speaker 1: Mike Flynn, he also filed some paperwork before his sentencing

1001
00:54:36,320 --> 00:54:38,680
Speaker 1: basically outlining why he feels like he should do no

1002
00:54:38,840 --> 00:54:42,279
Speaker 1: time because he was a decorated service member of the

1003
00:54:42,440 --> 00:54:46,400
Speaker 1: Armed Forces, and he was very forthcoming with Robert Mueller.

1004
00:54:46,840 --> 00:54:49,200
Speaker 1: But the only thing that's really new about this thing

1005
00:54:49,360 --> 00:54:52,240
Speaker 1: that we found out was he his lawyers are arguing

1006
00:54:52,360 --> 00:54:55,400
Speaker 1: that when the FBI agents came to interview him the

1007
00:54:55,480 --> 00:54:57,200
Speaker 1: first time, when they're like, just so you know, we

1008
00:54:57,280 --> 00:55:00,000
Speaker 1: have you on tape talking to uh, like Russian ambassador

1009
00:55:00,080 --> 00:55:02,480
Speaker 1: is about sanctions, and he was like, oh, he played

1010
00:55:02,480 --> 00:55:05,080
Speaker 1: stupid about it. He was saying that the FBI agents

1011
00:55:05,120 --> 00:55:07,000
Speaker 1: didn't warn him that it was a crime to lie

1012
00:55:07,040 --> 00:55:09,440
Speaker 1: to the FBI, so that's so he can't really be

1013
00:55:09,520 --> 00:55:12,800
Speaker 1: held liable for that. He literally pulled the I'm sorry,

1014
00:55:13,000 --> 00:55:17,320
Speaker 1: I didn't know I couldn't do that to the guy

1015
00:55:17,840 --> 00:55:19,359
Speaker 1: because he's like, well, they came in on some real

1016
00:55:19,440 --> 00:55:22,279
Speaker 1: like are you telling me that I can't? I can't

1017
00:55:22,320 --> 00:55:24,600
Speaker 1: want to. I can't. Oh, you're in so much trouble

1018
00:55:25,800 --> 00:55:28,480
Speaker 1: and that is privileged in a nut show for you

1019
00:55:28,600 --> 00:55:31,520
Speaker 1: when you're like, well, they didn't tell me, didn't know,

1020
00:55:32,360 --> 00:55:34,520
Speaker 1: I didn't know the laws apply to me. See, that's

1021
00:55:34,560 --> 00:55:37,200
Speaker 1: what the rules were. What the heck isn't that the

1022
00:55:37,280 --> 00:55:39,319
Speaker 1: Dave chappellevit or I'm sorry, I didn't know I can

1023
00:55:39,360 --> 00:55:41,719
Speaker 1: do that. Yeah, the speating things like trying with his

1024
00:55:41,800 --> 00:55:45,200
Speaker 1: white friend, my friend gets out of a ticket by

1025
00:55:45,280 --> 00:55:47,440
Speaker 1: saying sorry, I didn't know I couldn't do that, and

1026
00:55:47,520 --> 00:55:49,880
Speaker 1: what they all fucked up to smoking weed like not

1027
00:55:52,680 --> 00:55:58,840
Speaker 1: the pup. That's amazing. But what Mike Flynn did is

1028
00:55:59,800 --> 00:56:03,320
Speaker 1: so so bad, Like what what he actually did was

1029
00:56:03,719 --> 00:56:08,880
Speaker 1: not just lying, but he undermined the sitting US president

1030
00:56:09,280 --> 00:56:12,600
Speaker 1: by going around him speaking to an enemy man, he

1031
00:56:12,640 --> 00:56:15,799
Speaker 1: didn't know he couldn't do that, but like it's such

1032
00:56:15,880 --> 00:56:19,000
Speaker 1: a huge crime. I was listening to this just kind

1033
00:56:19,040 --> 00:56:22,480
Speaker 1: of straightforward review of everything that he did from these

1034
00:56:22,560 --> 00:56:25,759
Speaker 1: like national security experts, and they were just like so

1035
00:56:26,640 --> 00:56:29,279
Speaker 1: just like out of breath, just talking about like how

1036
00:56:29,800 --> 00:56:33,000
Speaker 1: insane what he did is, like like and that he's

1037
00:56:33,000 --> 00:56:34,719
Speaker 1: going to get off with like not that big of

1038
00:56:34,800 --> 00:56:38,719
Speaker 1: a sentence like he should. Like it's essentially treason. It's

1039
00:56:39,120 --> 00:56:41,440
Speaker 1: the worst thing you can do as somebody who was

1040
00:56:41,480 --> 00:56:45,360
Speaker 1: supposed to be upholding like national security and like working

1041
00:56:46,000 --> 00:56:50,120
Speaker 1: like swearing to protect the American people and swearing to

1042
00:56:50,520 --> 00:56:55,040
Speaker 1: help America before anyone or your own self interest. And

1043
00:56:55,160 --> 00:56:57,840
Speaker 1: he was just like, nah, I'm gonna I'm gonna go

1044
00:56:58,080 --> 00:57:00,480
Speaker 1: talk to Russia and like secretly to deal with them

1045
00:57:00,480 --> 00:57:02,760
Speaker 1: and then lie about it. It's almost as if public

1046
00:57:02,840 --> 00:57:05,280
Speaker 1: servants are not actually in it to help the public.

1047
00:57:06,000 --> 00:57:07,480
Speaker 1: Some of them are, but the ones that make it

1048
00:57:07,560 --> 00:57:10,040
Speaker 1: to the top apparently especially. I mean, I think it

1049
00:57:10,120 --> 00:57:12,440
Speaker 1: all depends on what your end game is as a person. Right,

1050
00:57:12,560 --> 00:57:14,480
Speaker 1: you can look at that and be like I'm down

1051
00:57:14,560 --> 00:57:17,560
Speaker 1: for some influence peddling for check and other people are

1052
00:57:17,640 --> 00:57:20,960
Speaker 1: actually selfless servants. I work hard, I go home to

1053
00:57:21,080 --> 00:57:22,680
Speaker 1: my house at the end of the day. I peddle

1054
00:57:22,760 --> 00:57:25,880
Speaker 1: some influence. But also, you know what, why the funds

1055
00:57:25,880 --> 00:57:30,400
Speaker 1: shouldn't I drive my bach, you know what I mean? Yeah,

1056
00:57:30,600 --> 00:57:33,120
Speaker 1: thank you so much. But yeah, so we'll see what

1057
00:57:33,200 --> 00:57:37,640
Speaker 1: happens to him. Because also, you know those sentencing memos

1058
00:57:37,800 --> 00:57:40,400
Speaker 1: or when like when the prosecutors are like, yeah, maybe

1059
00:57:40,480 --> 00:57:42,960
Speaker 1: this is the recommendations, the judge doesn't necessarily have to

1060
00:57:43,240 --> 00:57:45,720
Speaker 1: adhere to that. The judge can look at everything be like, Okay,

1061
00:57:45,760 --> 00:57:47,720
Speaker 1: that's what you think, but I think you should be this.

1062
00:57:48,200 --> 00:57:50,640
Speaker 1: But usually but they do have to sort of explain

1063
00:57:50,720 --> 00:57:52,920
Speaker 1: why that works. But it doesn't always necessarily mean what

1064
00:57:53,080 --> 00:57:54,720
Speaker 1: they recommend is what's going to happen. I think that

1065
00:57:54,800 --> 00:57:58,360
Speaker 1: kind of sucks. What that like, that system, the system

1066
00:57:58,360 --> 00:58:00,840
Speaker 1: of a judge getting to decide over I mean, isn't

1067
00:58:00,880 --> 00:58:03,000
Speaker 1: the point of our jury of peers that they're the

1068
00:58:03,040 --> 00:58:05,000
Speaker 1: ones that get to decide well for sentencing, I think

1069
00:58:05,000 --> 00:58:07,600
Speaker 1: you know what I'm just saying, Like, ideologically, it doesn't

1070
00:58:07,600 --> 00:58:09,160
Speaker 1: make a ton of sense to me. Yeah, you know,

1071
00:58:09,280 --> 00:58:12,320
Speaker 1: depending on if this person did actually give something of

1072
00:58:12,480 --> 00:58:16,120
Speaker 1: value to further the cause of the justice system, then yeah,

1073
00:58:16,160 --> 00:58:18,840
Speaker 1: we can figure out way to level that out. But yeah,

1074
00:58:19,600 --> 00:58:23,280
Speaker 1: and then just also going on in this investigation. We

1075
00:58:23,440 --> 00:58:27,360
Speaker 1: mentioned before that Maria Betina is going to cooperate, but

1076
00:58:27,800 --> 00:58:30,920
Speaker 1: just the details of what she had access to. So

1077
00:58:31,040 --> 00:58:35,120
Speaker 1: there's this dude, Paul Ericson, who's a GOP operative, and

1078
00:58:36,320 --> 00:58:38,320
Speaker 1: it was like the dude she was like sleeping with. Yeah,

1079
00:58:38,400 --> 00:58:42,160
Speaker 1: she was sleeping there. Uh and he was like an

1080
00:58:42,280 --> 00:58:46,440
Speaker 1: n r A spokesperson, a GOP operative. And one of

1081
00:58:46,560 --> 00:58:49,720
Speaker 1: the pieces of information that came out through investigating her

1082
00:58:49,960 --> 00:58:54,640
Speaker 1: was an email from Paula Ericsson saying basically him just

1083
00:58:54,720 --> 00:58:59,000
Speaker 1: bragging about doing covert agent stuff. I'm just gonna read

1084
00:58:59,320 --> 00:59:04,080
Speaker 1: the email. Unrelated to specific presidential campaigns, Ericson wrote in

1085
00:59:04,320 --> 00:59:07,080
Speaker 1: October two thousand sixteen email to an acquaintance that was

1086
00:59:07,200 --> 00:59:09,960
Speaker 1: later obtained by the FBI, I've been involved in securing

1087
00:59:10,120 --> 00:59:13,800
Speaker 1: a very private line of communication between the Kremlin and

1088
00:59:14,120 --> 00:59:20,200
Speaker 1: key unnamed political party leaders through of all conduits, the

1089
00:59:21,480 --> 00:59:27,200
Speaker 1: redacted unnamed gun rights organization. Uh, he Republican leaders, through

1090
00:59:27,600 --> 00:59:29,280
Speaker 1: of all conduits, the n r A. I think that's

1091
00:59:29,320 --> 00:59:31,800
Speaker 1: how if we're gonna do mad lives again, like do

1092
00:59:31,960 --> 00:59:35,120
Speaker 1: old people not understand how the internet works. No, they

1093
00:59:35,200 --> 00:59:37,040
Speaker 1: really don't know. He was like, I'm going to write

1094
00:59:37,080 --> 00:59:41,000
Speaker 1: an email about very private things. I've been named them.

1095
00:59:41,600 --> 00:59:46,960
Speaker 1: These people were so bad at spine. There was a

1096
00:59:47,320 --> 00:59:49,680
Speaker 1: telling about the note they found and they found I

1097
00:59:49,800 --> 00:59:52,560
Speaker 1: rated his house, So they rated his house and what

1098
00:59:52,720 --> 00:59:55,800
Speaker 1: one of the things was the Kremlin was trying to

1099
00:59:55,840 --> 00:59:58,760
Speaker 1: get to him via a number of different ways, Maria

1100
00:59:58,800 --> 01:00:03,480
Speaker 1: Boutina and also find out a job offer, because when

1101
01:00:03,520 --> 01:00:06,120
Speaker 1: they rated his house, he had just a post it

1102
01:00:06,240 --> 01:00:10,400
Speaker 1: note with the question written how to respond to FSB

1103
01:00:10,640 --> 01:00:18,400
Speaker 1: offer of employment question marks? Yeah right, that's the Russian

1104
01:00:18,440 --> 01:00:20,440
Speaker 1: equivalent of the CIA. That's what you would see on

1105
01:00:20,560 --> 01:00:23,080
Speaker 1: the wall of an establishing shot when you're like, you're

1106
01:00:23,080 --> 01:00:25,880
Speaker 1: in the character's house. What's he dealing with? Now? What

1107
01:00:26,040 --> 01:00:30,600
Speaker 1: offers of employment from International Secret Agency? Yeah? I mean

1108
01:00:30,680 --> 01:00:32,320
Speaker 1: it's like it might as well have been a handwritten

1109
01:00:32,360 --> 01:00:34,360
Speaker 1: note that it's like, want to do treason with me?

1110
01:00:34,680 --> 01:00:37,440
Speaker 1: Yes or no? Check out box signed FSB, which is

1111
01:00:37,480 --> 01:00:39,680
Speaker 1: the Russian version of the C. I A yes, so

1112
01:00:40,360 --> 01:00:44,040
Speaker 1: M I don't know. It's I mean, everyone's so stupid,

1113
01:00:44,320 --> 01:00:46,520
Speaker 1: you know. I think Russian style Americans were smarter than

1114
01:00:46,560 --> 01:00:49,800
Speaker 1: they were and Americans. I think they're realizing these people

1115
01:00:49,840 --> 01:00:52,960
Speaker 1: are fucking numbers ship right well, especially when you're greedy.

1116
01:00:53,240 --> 01:00:56,560
Speaker 1: I mean, yeah, they happens. They were like, hey, um,

1117
01:00:56,640 --> 01:00:58,240
Speaker 1: you want to collude with us on some stuff, you

1118
01:00:58,240 --> 01:01:01,760
Speaker 1: want to do some cool down down, And then the

1119
01:01:01,800 --> 01:01:03,600
Speaker 1: Americans sucked it up so bad that I think the

1120
01:01:03,680 --> 01:01:06,000
Speaker 1: Russians are now like I wish I'd never cool there, Like,

1121
01:01:06,200 --> 01:01:09,439
Speaker 1: all right, hey, what's up? Snapchat game? Doing a poll

1122
01:01:09,520 --> 01:01:11,640
Speaker 1: real quick? Should I collude to the Russia? Just voting

1123
01:01:11,720 --> 01:01:13,520
Speaker 1: my poll right now? Let me know? All right, Paul

1124
01:01:13,640 --> 01:01:15,640
Speaker 1: ericson out. You can tweet at me on the Snapchat

1125
01:01:16,760 --> 01:01:20,120
Speaker 1: is cool to like and subscribe. Also, sorry, June, it's

1126
01:01:20,160 --> 01:01:23,200
Speaker 1: been a pleasure having you. Where can people find you?

1127
01:01:23,360 --> 01:01:27,040
Speaker 1: People can find me on Instagram or venmo at atsr

1128
01:01:27,160 --> 01:01:29,160
Speaker 1: June h u y s a r A j u

1129
01:01:29,440 --> 01:01:35,200
Speaker 1: n e and on YouTube. At means TV means TV.

1130
01:01:35,640 --> 01:01:38,160
Speaker 1: That is a new channel that I am involved with.

1131
01:01:38,800 --> 01:01:40,400
Speaker 1: What are you doing there? We can talk about that

1132
01:01:40,440 --> 01:01:42,360
Speaker 1: more next time I'm on I'll have some stuff. I'm

1133
01:01:42,440 --> 01:01:44,320
Speaker 1: directing some stuff and writing some stuff, and I'll have

1134
01:01:44,440 --> 01:01:47,000
Speaker 1: some videos in the next next few months. Fantastic. Yeah,

1135
01:01:47,120 --> 01:01:48,880
Speaker 1: I'll come on and plug that. We'll plug that then.

1136
01:01:49,360 --> 01:01:51,800
Speaker 1: Hell yeah. Oh and is there a tweet you've been enjoying?

1137
01:01:52,320 --> 01:01:54,640
Speaker 1: Oh no, I'm not on Twitter anymore. Um, what's the

1138
01:01:54,680 --> 01:01:56,440
Speaker 1: Instagram post you like? Um? You know what I like

1139
01:01:56,520 --> 01:02:00,600
Speaker 1: on Instagram is um goku weed smoke. Smoke is is

1140
01:02:00,640 --> 01:02:03,200
Speaker 1: a follower of mine who's supposed to enjoy goku in

1141
01:02:03,320 --> 01:02:06,080
Speaker 1: his memes. Uh no, it's just a person's account. I

1142
01:02:06,080 --> 01:02:10,080
Speaker 1: don't know, man, I'm not social media. A good smoke,

1143
01:02:10,120 --> 01:02:12,880
Speaker 1: he's got a sick pluget smoke. Thanks for watching my

1144
01:02:12,960 --> 01:02:17,200
Speaker 1: Instagram stories, Miles. Where can people find you? Twitter? Instagram

1145
01:02:17,280 --> 01:02:19,760
Speaker 1: at Miles of Gray. Two tweets I like. One is

1146
01:02:19,760 --> 01:02:22,800
Speaker 1: from Traymon traypon Free says it seems like everybody getting

1147
01:02:22,840 --> 01:02:28,120
Speaker 1: locked up but her. And another one is just a

1148
01:02:28,240 --> 01:02:31,840
Speaker 1: photo from Jesse kraw. It's a photo of ray Leota

1149
01:02:31,880 --> 01:02:34,000
Speaker 1: on the Today Show with like Hoda and Cathie Lee

1150
01:02:34,080 --> 01:02:36,560
Speaker 1: all over him, and it says ray Leota King of

1151
01:02:36,640 --> 01:02:40,000
Speaker 1: the Wine Moms. But the way they are up on him,

1152
01:02:40,680 --> 01:02:43,680
Speaker 1: it looks like yeah, like it's I don't know, it

1153
01:02:43,720 --> 01:02:48,120
Speaker 1: looks like you walked in the wrong Bernie Manquet. You

1154
01:02:48,160 --> 01:02:51,480
Speaker 1: can follow me on Twitter at Jack Underscore, O'Brian uh

1155
01:02:51,680 --> 01:02:58,080
Speaker 1: tweet I enjoyed. Brandy Jensen tweeted two thousand seventeen sassy

1156
01:02:58,160 --> 01:03:01,200
Speaker 1: brands who dunk on people? Two thousand eighteen, the brands

1157
01:03:01,240 --> 01:03:04,560
Speaker 1: are anxious and depressed now two thousand nineteen brands started

1158
01:03:04,560 --> 01:03:08,320
Speaker 1: asking for feet picks, and then she tweeted me sure

1159
01:03:08,400 --> 01:03:12,840
Speaker 1: wish they would bring back spicy chicken nuggets. Wendy's step

1160
01:03:12,920 --> 01:03:19,680
Speaker 1: up my balls and we'll talk. You can find us

1161
01:03:19,760 --> 01:03:22,520
Speaker 1: on Twitter at Daily Zekegeist. Were at the Daily Zigeist

1162
01:03:22,600 --> 01:03:25,360
Speaker 1: on Instagram. We have Facebook fan page and a website,

1163
01:03:25,400 --> 01:03:27,880
Speaker 1: Dailies I guys dot com. We post our episodes and

1164
01:03:28,080 --> 01:03:30,640
Speaker 1: our foot don't We link off to the information that

1165
01:03:30,680 --> 01:03:34,240
Speaker 1: we talked about in today's episode and there a get

1166
01:03:34,320 --> 01:03:36,720
Speaker 1: gil as well as the song we ride out on miles.

1167
01:03:36,800 --> 01:03:40,040
Speaker 1: What's that going to be? So this is a track

1168
01:03:40,280 --> 01:03:46,120
Speaker 1: from Sam Gendal called Pure Imagination in parentheticals low five

1169
01:03:46,520 --> 01:03:48,600
Speaker 1: uh and this again. You know, we're trying to get

1170
01:03:48,600 --> 01:03:50,400
Speaker 1: our shoulders moving, We're trying to get our bodies moving.

1171
01:03:50,480 --> 01:03:53,480
Speaker 1: The weekend is approaching, so let's get loose and join

1172
01:03:53,600 --> 01:03:57,000
Speaker 1: in and don't drink the juice, alright, we're gonna ride

1173
01:03:57,000 --> 01:03:59,760
Speaker 1: out on that. We will be back tomorrow because of

1174
01:03:59,840 --> 01:04:30,720
Speaker 1: the seism to to, told to to, told to