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Speaker 1: Hello the Internet, and welcome to season seventy five, Episode

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Speaker 1: five of Jo Dai Lyes Eight Guys Season finale. Uh.

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Speaker 1: This is the podcast where we take a deep dive

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Speaker 1: into America's share consciousness. It's Friday, March twenty nine, two

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Speaker 1: thousand nineteen. My name is Jack O'Brien aka, I want

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Speaker 1: my Daily Jack Daily, Jeff Daily Jack. I want my

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Speaker 1: Daily Jack Daily, Jack Daily Jack, my olds Gravy Jack's

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Speaker 1: Glibe And it's courtesy of Trake Gang collabo with Hannah Sultis,

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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 Graay. You know, I want to

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Speaker 1: thank all. This is basic great Castle Spot Daily's Eight

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Speaker 1: Guys Dad. It's dope always by a tank, so I'm

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Speaker 1: not I'm ball even when I'm high. It's clear Miles

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Speaker 1: Gray runs this ship right here. Yeah. Wow, I soltis

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Speaker 1: handed for that one. You know, voices bad rash Bee

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Speaker 1: shout into Macy. Not related. Just for the record, Yeah, yeah,

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Speaker 1: a lot of people think we are well. That changes everything.

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Speaker 1: And you see Berkeley basketball player Ed Gray also yeah,

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Speaker 1: not related and the only reason you know people asked

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Speaker 1: by him he was in the same classic Jason game

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Speaker 1: What we Gotta Throw to be joined in her third

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Speaker 1: seat by the hilarious comedian and the host of the

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Speaker 1: They Tried to Bury This podcast, Mr tamer Katon, Kay,

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Speaker 1: what's up? Thank you guys, welcome back. That was a

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Speaker 1: pretty impressive Macy Gray, Thank you. She was no joke.

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Speaker 1: She was at the Haha Cafe not even a month ago,

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Speaker 1: and she went up and did a set. She did comedy. Oh,

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Speaker 1: she goes like this, she goes, she walks up to

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Speaker 1: the stage, she goes, listen, I just got two jokes,

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Speaker 1: and then her friend in the back goes, you got

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Speaker 1: full bitch. And she was so nice. She took pictures

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Speaker 1: of everybody. She was super sweet, pretty good. No, I

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Speaker 1: mean they were kind of like here, like kind of

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Speaker 1: like dad joke, you know, like not it was knock

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Speaker 1: knocking two dudes. But with her voice. Yeah, she's such

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Speaker 1: an interesting person and like just heard speaking is cool.

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Speaker 1: So it just deserves to be on a stage one

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Speaker 1: where totally. And she was there for like three hours.

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Speaker 1: She likes sat. She sat through two different shows. I

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Speaker 1: think she's researching comedy or something because she was she

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Speaker 1: was really into it. Interesting. She didn't do three hours

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Speaker 1: like she did two jokes to her and told her

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Speaker 1: friend to shut up about the other two for her

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Speaker 1: just calling her out. Tamara Willett, We're gonna get to

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Speaker 1: know you a little bit better in a moment. First,

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Speaker 1: we're gonna tell our listeners a few of the things

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Speaker 1: we're talking about today. We're going to kick things off

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Speaker 1: on a health and wellness tip, because robots can predict

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Speaker 1: when you're going to die, so don't go to the

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Speaker 1: doctor with startling accuracy. We're also gonna talk about how

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Speaker 1: the just firmament of reality is now tipped against us

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Speaker 1: because we are by default two pounds fatter then we

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Speaker 1: were in the eighties, just without eating the same number

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Speaker 1: of calories. We're gonna talk about how that's possible. Uh.

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Speaker 1: And then we're just gonna do a check in with

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Speaker 1: the Mueller Report, with the media's you know, reaction to it,

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Speaker 1: how we are dealing with that reaction all that ship.

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Speaker 1: We're gonna talk about Facebook banning white nationalism and how

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Speaker 1: that problem has been solved, and a controversy on the

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Speaker 1: Billboard country chart. But first, hammer, what is something from

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Speaker 1: your search history that's revealing about who you are? Okay?

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Speaker 1: So my most recent Internet search with I've become a

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Speaker 1: new fan of RuPaul's drag Race and I'm deep. I'm like,

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Speaker 1: I'm deep into the B sides And so I looked

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Speaker 1: up the history of She'd Done Already Done, had hers

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Speaker 1: is and it was really cool, Like RuPaul talked about

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Speaker 1: how like it was. They left a club in Atlanta

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Speaker 1: one night they went to Crystals, this chicken spot in Atlanta,

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Speaker 1: and some girl went to grab food and she goes,

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Speaker 1: huh uh, she done already done, had hers And now

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Speaker 1: it's a part of drag rays history. So it's like,

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Speaker 1: So I've been googling a lot of like RuPaul and

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Speaker 1: drag queen slang because I'm a big fan of our

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Speaker 1: slang comes from drag queens, right, so much, so much

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Speaker 1: comes from shade getting dragged, getting red. Like, there's so

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Speaker 1: much you have. I had no idea how much culture

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Speaker 1: was being impacted by drag culture. Yeah, I know. RuPaul

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Speaker 1: was like tight with the B fifty twos back in

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Speaker 1: back in the day. He was in the music video

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Speaker 1: They came out of the same scene in Athens, Georgia,

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Speaker 1: and r E M all those all those people were

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Speaker 1: hanging out together entire eighties. Uh, but yeah, RuPaul is incredible.

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Speaker 1: One of my favorite. There's like one B fifty twos

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Speaker 1: video I watch a lot on YouTube. It's them doing

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Speaker 1: private Idaho like live. I don't know why I love

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Speaker 1: because you're living in your own private ideal. Yeah, in

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Speaker 1: your own primated You're living in your own private Idaho.

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Speaker 1: That it sounded like a white person in doing an

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Speaker 1: impersonation of another white person. Yeah. Like the way they

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Speaker 1: pronounced And as a kid I loved just because Fred

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Speaker 1: isn't yeah way of speaking. Just as a kid, I

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Speaker 1: thought was so if you see a faded side at

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Speaker 1: the side of the road and overnunciation ship out of

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Speaker 1: those syllables, Yeah, sir, hitting the continent extra hard. Uh man. That.

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Speaker 1: By the way, the episode with Amy Miller on that

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Speaker 1: song on punch Jam is so fucking good. People should

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Speaker 1: go check that out. What is something you think is underrated? Uh?

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Speaker 1: Long Island Medium, I love that show. You are, like,

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Speaker 1: I'm a skeptic, big time skeptic. But there are not

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Speaker 1: that many great actors in Hugh Jersey, Long Island. In

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Speaker 1: Long Island, I mean sorry, you're right, yeahally actors, you're right,

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Speaker 1: But I was like there's she's got something. I don't

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Speaker 1: know what it Isn't seen her get utterly just stumped though.

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Speaker 1: Wasn't there like a thing where she someone tried to

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Speaker 1: corner her with some like like she was caught out

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Speaker 1: not fully medium? I mean there's a certain extent. I

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Speaker 1: mean I think a lot of it is good guesswork,

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Speaker 1: but I don't know, you know, I'm sure there's sometimes

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Speaker 1: when it's bullshit and you're just trying to You're like,

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Speaker 1: it's an awkward conversation essentially where you like promised to

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Speaker 1: do some ship that you couldn't pull off, but like

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Speaker 1: you don't want to disappoint the person. But then I'm

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Speaker 1: sure there maybe other times when I actually don't believe

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Speaker 1: in any of it, but like if if you did

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Speaker 1: believe in it, that that could still be an argument

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Speaker 1: that Yeah, sometimes the bullshit but I don't want to

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Speaker 1: believe it, and my brain does it, but my heart

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Speaker 1: keeps going, come on, yeah, you know yea, the producers man,

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Speaker 1: they got you. It's pretty, It's it's pretty compelling. I

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Speaker 1: love her hair. I mean I believe in her hair.

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Speaker 1: She's in her hair, but something's keeping that she evolved

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Speaker 1: her hair over the years. Yeah, her daughter became a hairstylist,

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Speaker 1: and her daughter's I think is so funny. She's like

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Speaker 1: just naturally weird and funny. She's on the show. She's

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Speaker 1: on the show. Yeah, and she's super funny and a medium. No,

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Speaker 1: she's just a regular girl who complains. She's like, I

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Speaker 1: just wanted to buy cupcakes, mom, and she's like she's

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Speaker 1: like and they're reading the cupcake cashiers like talking about

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Speaker 1: her dead brother, and she's like, I just wanted a cupcake.

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Speaker 1: Just need to eat these red velvet cupcakes. Want to

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Speaker 1: talk about his uncle. Yeah, but there's got to be

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Speaker 1: some sort of supernatural explanation for how high and just

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Speaker 1: consistently large her hair is. Yeah, she's impressive. Though. There's

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Speaker 1: something that she she does have a gift. Is it

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Speaker 1: speaking to the dead? I don't know, but there's a

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Speaker 1: level of like empathy and being able to read people

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Speaker 1: or read energy or Whatever's something that she does. Yeah,

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Speaker 1: and get the label. That's kind of impressive. Yeah. There's

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Speaker 1: like a whole world of sort of carnival Barker type

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Speaker 1: like tourist, trappy like entertainment people who like used to

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Speaker 1: you know, be a big deal in their little corner

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Speaker 1: of the world, like back in the day when people

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Speaker 1: would just like travel through a town and check it

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Speaker 1: out and then, uh, you know, we don't have a

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Speaker 1: record of those people. So we're we're going to be

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Speaker 1: the first culture that has a very thorough record of

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Speaker 1: our people who have that like ineffable gift. That's like, huh, yeah,

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Speaker 1: I guess they do have something. I can't really say

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Speaker 1: what it is. There's not a word for it. But uh,

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Speaker 1: and her nails and hair, her nails anyways, what is

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Speaker 1: something you huh like dreams? He's like brushing his Like, well,

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Speaker 1: I'm just pictured like I'm giving a lecture in the future,

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Speaker 1: like as a historian of this time, you know, but

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Speaker 1: you have the hair and the nails though, exactly, that's right.

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Speaker 1: What is something you think is overrated? Um? The phrase

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Speaker 1: get or done? Huh? Like I don't say what's up anymore? Right,

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Speaker 1: but get or done has been around in like country

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Speaker 1: culture for way too long. They keep using it. It's

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Speaker 1: not clever. The people that yell out get or done

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Speaker 1: are often people who are unemployed. What are you getting done?

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Speaker 1: You didn't get anything done? Alright? People make a lot

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Speaker 1: before we walked in the studio. He's all right, that's

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Speaker 1: how we open every every recording. That must be like

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Speaker 1: a colloquial phrase. It's I don't think Larry invented it.

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Speaker 1: I think Larry put a collar on it and made

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Speaker 1: it his at the Marine Corps is a Marine Corps thing.

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Speaker 1: That's what is claiming right now. And I agree that

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Speaker 1: the Marine Corps are passing fed. They should involve that

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Speaker 1: to That's like a if the Marine Corps is a

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Speaker 1: nationwide brand, that would be like a nationwide anchor person

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Speaker 1: using a regional slang. It's not right. Yeah, your outrage,

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Speaker 1: it's how upset? What is it about it? Like, let's

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Speaker 1: really unpack this. Is it the is it the culture

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Speaker 1: that it's coming from? Is it the phrasing itself that

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Speaker 1: rubs you the wrong way? Here's what I hate about it.

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Speaker 1: I think some of the hardest working people in the

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Speaker 1: world are immigrants, and I feel like the people who

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Speaker 1: embrace that get or done phrase or like talking about

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Speaker 1: hard work and it's like, no, you don't own hard work.

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Speaker 1: The people that you claim to hate those are the

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Speaker 1: people who really deserve that title. So I don't like

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Speaker 1: that because one it's a stupid phrase, and it's bullshit.

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Speaker 1: Like the people who say, don't embody that mentality, they're

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Speaker 1: not hard workers. They're people who are entitled interesting. Yeah yeah,

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Speaker 1: that was a much better uh way of explaining that

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Speaker 1: than I was expecting. That's really very, very smart. I

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Speaker 1: just don't like divisiveness at the end of the day

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Speaker 1: at all. Like, you know what, when I'm when I

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Speaker 1: visit the Middle East, I defend America. When I'm in America,

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Speaker 1: I defend the Middle East. I went to college in Europe,

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Speaker 1: and in Europe I defended America. America, I defend Europe.

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Speaker 1: I just don't like people hating other people based on

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Speaker 1: like bs stereotypes, even the one that I just used

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Speaker 1: to explain how much. Yeah, but I get it. Your

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Speaker 1: whole thing is, look, if you want get or done,

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Speaker 1: get or fucking done, get done exactly? Who use it cheaply?

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Speaker 1: It's like a homeless guy wearing a shirt saying billionaire

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Speaker 1: in the making. No, you're not, like, okay, just because

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Speaker 1: you drank a keg, you didn't get or done exactly.

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Speaker 1: I'm tired of people pointing to ship but never hitting

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Speaker 1: home runs. Don't pin it, don't point at the back

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Speaker 1: wall unless you got a back, You've got the wild

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Speaker 1: immigrant kid mentality right now. It's like my mom's just

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Speaker 1: like just celebrating already birthday. Yeah, what have you done

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Speaker 1: in your five years? Yeah? Yeah? What's what's this word pneumonia?

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Speaker 1: He's silent fall the uh? And finally, what does a myth?

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Speaker 1: What's something people think this? Oh? Man? So, I don't

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Speaker 1: know how this ended up path named, but I went

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Speaker 1: into this deep internet dive into like time travelers and

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Speaker 1: like the most authentic people are closest to to proving

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Speaker 1: that they're real. And there's a guy who goes by

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Speaker 1: the title of Citizen three thousand fourteen and he's from

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Speaker 1: the year three thousand fourteen, and I'm really getting into

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Speaker 1: the idea of time travelers and did Okay, I'm sorry,

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Speaker 1: go on. So I I think, uh, this myth of

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Speaker 1: Citizen fourteen is something that needs to be investigated more deeply. Wow.

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Speaker 1: I think they used to suck, but the time travelers

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Speaker 1: have absolutely stepped their game up. Their predictions are getting better.

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Speaker 1: I think the outfits are getting or sassy. I think

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Speaker 1: the planets that they're talking about where they came from,

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Speaker 1: and not just this guy, but also the guy that

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Speaker 1: talked about the Bavians on the Howard Stern Show, Riley Martin,

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Speaker 1: he talks familiar with his work. Well, he he sells these,

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Speaker 1: he'll he'll design like a symbol, like a Native American symbol.

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Speaker 1: He was an old black man, but he wore Native

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Speaker 1: American headband and then he would give you symbols, and

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Speaker 1: the symbols were like invitations onto the spaceship. Has anybody

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Speaker 1: ever taken him up on that? Well, he passed away,

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Speaker 1: but he was a lunatic man. He had a radio.

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Speaker 1: He passed away or did he? He? Well, just his

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Speaker 1: physical existence, his physical existence on the planet. He had

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Speaker 1: fourteen kids by aliens, but on Earth he only had

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Speaker 1: two sons. And during his radio show, he hated the

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Speaker 1: ad top so much so he just started peeing while

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Speaker 1: doing radio and you can hear him peeing into a bucket.

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Speaker 1: Oh no, he's amazing. So who thing is like time?

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Speaker 1: So from that point, the time Traveler brand has begun

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Speaker 1: to really become a little it's it's becoming it's more

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Speaker 1: sophisticated and simultaneously feels more organic. Like I'm starting talking

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Speaker 1: like in a straight line while peeing, because I think

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Speaker 1: that would be like, right, what do you mean? Yeah, Well,

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Speaker 1: because like I think your brain is not designed to

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Speaker 1: just be like talking Pete talking, It's like patting your

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Speaker 1: head and your stomach in a circle. Jack. In the

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Speaker 1: last five months on this show, the whole time, I'm

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Speaker 1: always blaming it on the dogs that people bringing to

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Speaker 1: the office. That's right. I'm like, damn Andy, Pete on

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Speaker 1: that my chair again, you do some One last question

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Speaker 1: about Citizen three thousand fourteen. I just want to take

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Speaker 1: a wild guest here. Did he step onto the scene

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Speaker 1: in two thousand fourteen? Because you're good, You're like the

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Speaker 1: magnum p I on the internet. How did you know

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Speaker 1: that he's just wait for real, he's yeah, a lot

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Speaker 1: of these time travelers are not great with math. Yeah,

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Speaker 1: but he's like, he's like two thousand, oh, this would

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Speaker 1: be trippy. I'm I'm I'm sitting in three thousand. He

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Speaker 1: did go pretty and a pretty even Stephen number. I

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Speaker 1: will tell you none of them talk about their technology, right,

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Speaker 1: they don't talk about but I will talk to you

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Speaker 1: about one quick thing is so one time I did

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Speaker 1: mushrooms while listening to Riley Martin, and then my friend

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Speaker 1: and I went for a walk and we were staring

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Speaker 1: at the Tower Records building I tell you about that,

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Speaker 1: and I stared at at my whole life, I've never

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Speaker 1: noticed anything, but there was an irregular pattern on the

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Speaker 1: blinking on the blinking light. And then when I was sober,

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Speaker 1: I looked it up and it actually spells Hollywood and Morse.

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Speaker 1: Oh yeah, I think we talked about this. I'm too much.

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Speaker 1: I just want to help you out, you know what

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Speaker 1: I mean. People think you're a one note guy. He's like,

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Speaker 1: you have Tamaron. We talk about time travel and looking

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Speaker 1: at the blinking light again, Well, they're all connecting now,

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Speaker 1: you know. It's like mushrooms time travelers. And these time

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Speaker 1: travelers are distinct from the ones who show up in

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Speaker 1: pictures from the past. And it's like Nicolas Cage was

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Speaker 1: in this picture from you. I think those were toe dips,

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Speaker 1: and now these are people getting in the jacuzzi with us. Interesting,

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Speaker 1: and that's the time travel. Those are toe dips. And

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Speaker 1: then and then before actual time travel, we'll use the

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Speaker 1: grossest metaphor mr Together. Pretty gross. And now we're going

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Speaker 1: full of jacus. Alright, guys, let's talk about AI the movie. No,

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Speaker 1: not the movie. I don't really have much to add them.

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Speaker 1: There is a AI that like is using machine learning

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Speaker 1: to basically predict when people are going to die. So

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Speaker 1: a group of scientists, I mean this makes sense if

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Speaker 1: you've ever done a life insurance policy. Like you know,

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Speaker 1: there's an entire industry that is just devoted and like

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Speaker 1: constantly updating its methods of trying to find out when

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Speaker 1: you will die, like most accurately, and they can make

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Speaker 1: a lot of money on like adapting, you know what,

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Speaker 1: how they evaluate the data that you give them. So

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Speaker 1: scientists in the UK took five hundred thousand people between

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Speaker 1: the year two thousand and six and two thousand sixteen

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Speaker 1: and fed a bunch of different variables that they were

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Speaker 1: able to get from those people into a bunch of

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Speaker 1: different systems, uh, and then ask those systems how likely

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Speaker 1: were those people to pass away from two thousand six

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Speaker 1: to two thousand sixteen, And this algorithm was able to

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Speaker 1: identify the people who would die with seventy six percent accuracy.

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Speaker 1: So and told him how many people died at the

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Speaker 1: end of that tenure. At the end of the tenure

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Speaker 1: sent it was fourteen thousand, five hundred people, which is

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Speaker 1: not which is just like, right, they die primarily answer

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Speaker 1: heart disease, respiratory diseases, and so it's it's really in

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Speaker 1: testing for a couple of reasons. First of all, that's

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Speaker 1: insanely like all the you know models that doctors and

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Speaker 1: UH insurance companies have been using up to this point

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Speaker 1: are usually below fifty accuracy, and so they got up

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Speaker 1: to seventy six percent. And they also said that the

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Speaker 1: the variables that the AI was able to determine, uh

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Speaker 1: like we're the most beneficial to determining if you were

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Speaker 1: gonna live or die were not the ones that the

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Speaker 1: other models emphasized. So the other models looked at age, gender,

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Speaker 1: smoking history, prior cancer diagnosis, and another one of the

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Speaker 1: other models looked at body fat percentage, waste circumference, the

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Speaker 1: amount of fruit and vegetables that people and skin tone,

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Speaker 1: and this AI determined that it was mostly useful to

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Speaker 1: know exposure to job related hazards, air pollution, alcohol intake,

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Speaker 1: and the use of certain medications. Yeah, those were those

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Speaker 1: are the top Wow, those are those from the traditional

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Speaker 1: models where they're like that's how Yeah, those are the

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Speaker 1: things that jumped out as like, the AI determined that

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Speaker 1: that would tell you how likely people were, did I

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Speaker 1: It's strange that the survey size was so massive, right,

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Speaker 1: I think they I think they picked a massive number

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Speaker 1: in order to make themselves look accurate. Right, Like, if

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Speaker 1: you told me, here's fifty people guests all their favorite colors,

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Speaker 1: I probably wouldn't get I probably wouldn't do that. Well.

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Speaker 1: But if you told me, here's five thousand people guess

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Speaker 1: their favorite color and I picked blue, right, I probably

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Speaker 1: have a much more impressive number. Yeah. But when you

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Speaker 1: have a set of data set that big, though, and

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Speaker 1: you can repeat it over like, what, so seventies of

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Speaker 1: fourteen thousand, that's pretty that's pretty good. But here's what

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Speaker 1: I mean. It's it's death is all like individual to us,

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Speaker 1: but then they do a sample size that's so big

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Speaker 1: that it's no longer about individuals, it's about a population. Yeah,

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Speaker 1: you know what I it's like, it's so bizarre. Yeah,

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Speaker 1: and who were these five thousand people that said, yeah,

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Speaker 1: I want to know when I'm going to die? They agree?

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Speaker 1: So no, they were just giving it was basically they

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Speaker 1: agreed to be part of a health study. Snartly. I

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Speaker 1: don't like Yeah, I mean, I don't think they were

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Speaker 1: identified or anything. They called him up, They're like, hey,

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Speaker 1: you did yet, Well you might want to get that

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Speaker 1: bucketless going, right. But I think that's where you look

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Speaker 1: at that seventy percent accuracy. I wonder how much just

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Speaker 1: sort of you know what insurance companies called acts of

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Speaker 1: God or something. Yeah, I mean one of the things

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Speaker 1: that was unexpectedly predictive was on the job hazards, Like

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Speaker 1: if you have a really dangerous job, if you're like

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Speaker 1: working in a construction in a construction place, like I'm

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Speaker 1: sure there are you know, you're exposing yourself to a

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Speaker 1: ton of different opportunities to have an act of God

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Speaker 1: or accident type thing or nailed. Then yeah. But I

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Speaker 1: mean while you're trying to shoot some cans like actuaries,

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Speaker 1: I do think this is going to be a place

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Speaker 1: that AI is going to stun us within our lifetime

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Speaker 1: because actuaries are just constantly iterating on this like that

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Speaker 1: is there's an entire huge, like very you know, wealthy

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Speaker 1: industry that is constantly churning trying to figure out better

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Speaker 1: methods for figuring out when we're going to die, or

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Speaker 1: you know, being able to predict how risky people are

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Speaker 1: different lifestyle choices are and so we'll I think, does

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Speaker 1: it say that, does it say who funded it? I

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Speaker 1: mean it's the insurance companies you. Uh well, it was

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Speaker 1: in the UK, I think, so, I think they tend

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Speaker 1: to have like better rules about stuff like that. But yeah,

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Speaker 1: so that's good. Also makes me feel better about my

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Speaker 1: fruit and vegetable intake. Was that they found that wasn't

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Speaker 1: that predictive of whether you're going to live or die? Yeah,

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Speaker 1: just you know, workplace hazards. Yeah. And then another study

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Speaker 1: that it's just interesting. It says that they looked at

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Speaker 1: I think thirty six thousand, four hundred Americans between ninety

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Speaker 1: one two thousand eight and the physical activity data of

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Speaker 1: fourteen thousand, four hundred and nineteen people between night and

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Speaker 1: two thousand and six. They grouped the data sets together

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Speaker 1: by the amount of food and activity age and b

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Speaker 1: m I, and they found that a given person in

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Speaker 1: two thousand and six eating the same amount of calories,

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Speaker 1: taking the same quantities of nutrients like protein and fat,

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Speaker 1: and exercising the same amount as a person of the

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Speaker 1: same age in would have a b m I that

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Speaker 1: was two point three points higher. In other words, people

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Speaker 1: are about ten percent heavier or fatter than people in

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Speaker 1: the eighties. Why uh So the theories are like they

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Speaker 1: were just like chemicals, like chemicals that we've been exposed to.

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Speaker 1: It seems like we're getting better at identifying those. They said.

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Speaker 1: Also it could be medications that were you know, we've

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Speaker 1: changed a lot the medications that we're taking um. And

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Speaker 1: then the microbiome is the thing that I think is

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Speaker 1: an underrated aspect of human health is you know, they're

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Speaker 1: doing things like poop transplants that really help people with

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Speaker 1: all sorts of diseases. And it sounds crazy, but like

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Speaker 1: a lot of our digestion and you know, the whole

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Speaker 1: machine of our body is determined by this entire bias

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Speaker 1: fhere that's living inside your gut. And it's a very

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Speaker 1: complicated thing that we haven't really studied that much. So

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Speaker 1: poop transplant. So when I go to a music festival

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Speaker 1: and I fish people ships out of the porta potty, no,

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Speaker 1: that's not that's what do we call that? A weird fit,

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Speaker 1: very train spot. But so I think what we need

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Speaker 1: is we need one of our time travelers to take

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Speaker 1: poops from the eighties, you bring them forward to and

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Speaker 1: then transplant the eighties poop into our poop and all good. Yes,

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Speaker 1: we can wave with the future, so to speak. All right,

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Speaker 1: we're gonna take a quick break, we'll be right back,

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Speaker 1: and we're back. And so we wanted to just do

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Speaker 1: a kind of leisurely check in with the Maller report.

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Speaker 1: We've learned it over three hundred pages, which is way

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Speaker 1: longer than the two sentences we have quoted in the

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Speaker 1: Bar summary. It's probably more than that, but but yeah,

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Speaker 1: there's a there's a whole lot we haven't read. But

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Speaker 1: in the meantime, people are continuing to, you know, deal

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Speaker 1: with the fallout of the Bar summary. The right has

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Speaker 1: repeatedly spiked the football Uh you know the Fox News

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Speaker 1: is and drudges of the world. Um oh, they're loving it.

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Speaker 1: They are Bob Bob wow there. I mean, if you look,

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Speaker 1: can also do how the coverage has changed. Like Daily Beast,

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Speaker 1: a few people were comparing it's like, that's weird. He

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Speaker 1: spent the last two years saying Mueller was a hack

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Speaker 1: and then now it's like, yo, this guy's the savior.

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Speaker 1: Just listen, there's just a quick mash up daily piece

424
00:25:14,000 --> 00:25:17,400
Speaker 1: put together. The tone changed very quickly, on Fox News.

425
00:25:17,640 --> 00:25:20,920
Speaker 1: Special counsel Robert Mueller's team is a pack of partisan hacks.

426
00:25:21,280 --> 00:25:24,360
Speaker 1: We can't trust anything coming out of the Mueller investigation.

427
00:25:24,640 --> 00:25:26,840
Speaker 1: Muller is not only out for blood, he's out to

428
00:25:26,880 --> 00:25:29,720
Speaker 1: save his own. But if you think you can trust

429
00:25:29,840 --> 00:25:33,480
Speaker 1: the upcoming Muller Report, think again. How are we supposed

430
00:25:33,520 --> 00:25:36,200
Speaker 1: to trust that Robert Muller. This investigation is on the

431
00:25:36,280 --> 00:25:38,000
Speaker 1: up and off. I'm proud that we were on the

432
00:25:38,080 --> 00:25:39,720
Speaker 1: right side of justice these last year and a half.

433
00:25:39,840 --> 00:25:42,040
Speaker 1: I don't trust Muller. The Mueller report came back with

434
00:25:42,119 --> 00:25:46,160
Speaker 1: no collusion and no obstruction. You should ever trust Robert Mueller.

435
00:25:46,240 --> 00:25:49,280
Speaker 1: Mueller has proven he cannot be trusted. He clearly found

436
00:25:49,320 --> 00:25:52,960
Speaker 1: no collusion. Special Counsel Robert Muller's corrupt. How can you

437
00:25:53,080 --> 00:25:58,320
Speaker 1: ever trust the Mueller investigation? Robert Mueller's partisan, extremely biased, hyperpartisan.

438
00:25:58,400 --> 00:26:02,800
Speaker 1: Robert Mueller's team is hyperpartisan. Mueller's handpig millions are a

439
00:26:02,840 --> 00:26:07,000
Speaker 1: bunch of Trump hating, Hillary loving partisan hacks. Special Counsel

440
00:26:07,119 --> 00:26:09,960
Speaker 1: Robert Mueller and his partisan hacks. I just don't trust

441
00:26:10,040 --> 00:26:12,640
Speaker 1: Muller and his team. I'm not sure trust Muller's team

442
00:26:12,680 --> 00:26:17,160
Speaker 1: never had Muller's report on Russia election interference finds, as

443
00:26:17,280 --> 00:26:23,360
Speaker 1: we have been telling you, zero collusion. Yeah, yeah, yeah.

444
00:26:23,560 --> 00:26:27,320
Speaker 1: So it's funny, and I think there there are other

445
00:26:27,480 --> 00:26:31,879
Speaker 1: versions of that, with primarily MSNBC people, you know, saying

446
00:26:32,000 --> 00:26:35,280
Speaker 1: some wild over the top ship about like that we

447
00:26:35,480 --> 00:26:39,840
Speaker 1: now know with like perfect clarity that Trump conspired and

448
00:26:39,920 --> 00:26:42,400
Speaker 1: that his you know kids are going to be let

449
00:26:42,440 --> 00:26:45,560
Speaker 1: out of the White House and handcuffs and so a

450
00:26:45,640 --> 00:26:49,080
Speaker 1: lot of things have changed. I think on the extremes,

451
00:26:49,280 --> 00:26:52,959
Speaker 1: what's changed for you, Well, I personally don't think it's

452
00:26:53,040 --> 00:26:56,960
Speaker 1: useful to claim Trump is an idiot or to evaluate

453
00:26:57,119 --> 00:26:59,560
Speaker 1: him as one, whether he is or not. He has

454
00:26:59,680 --> 00:27:02,480
Speaker 1: like a certain genius and what he does, like the

455
00:27:03,040 --> 00:27:07,280
Speaker 1: the no collusion thing was just very shrewd. He redefined

456
00:27:07,680 --> 00:27:11,320
Speaker 1: the argument to what he knew would work for him

457
00:27:11,480 --> 00:27:16,600
Speaker 1: given the facts, and doing all of his bad stuff

458
00:27:16,680 --> 00:27:19,520
Speaker 1: out loud, like the obstruction of justice out loud was

459
00:27:20,160 --> 00:27:24,480
Speaker 1: also very shrewd, like he's gonna for whatever it's worth

460
00:27:24,840 --> 00:27:28,120
Speaker 1: and whether it's just complete instinct and like a broken brain.

461
00:27:28,480 --> 00:27:31,920
Speaker 1: But he is good at playing this particular version of

462
00:27:32,040 --> 00:27:35,600
Speaker 1: the media very well, and I feel like the media

463
00:27:35,920 --> 00:27:39,680
Speaker 1: got played very well by him or yeah or just yeah.

464
00:27:39,680 --> 00:27:43,280
Speaker 1: I think the hyper focus on the word collusion definitely.

465
00:27:43,320 --> 00:27:45,440
Speaker 1: I mean, I don't know if he's he does have

466
00:27:45,720 --> 00:27:49,960
Speaker 1: a instinct for sure on how to do it. Genius.

467
00:27:50,320 --> 00:27:53,560
Speaker 1: There's different kinds of genius. Yeah, would be the evil genius.

468
00:27:53,840 --> 00:27:57,080
Speaker 1: He's definitely the category of evil genius. I think, like

469
00:27:57,280 --> 00:28:00,720
Speaker 1: the Liberals have a tendency to have a better rolodex

470
00:28:00,840 --> 00:28:02,879
Speaker 1: of artists, and that's why you can see it when

471
00:28:02,920 --> 00:28:05,280
Speaker 1: we have a democratic president, when we've got really talented

472
00:28:05,359 --> 00:28:08,480
Speaker 1: artists that support and I think, uh, conservative parties have

473
00:28:08,560 --> 00:28:10,320
Speaker 1: a have a great pool of people who are great

474
00:28:10,320 --> 00:28:16,280
Speaker 1: at corruption. That's they're excellent at corruption. Liberals suck at it.

475
00:28:16,680 --> 00:28:19,119
Speaker 1: And and the fact that the Mole Report even had

476
00:28:19,160 --> 00:28:22,280
Speaker 1: to happen is a mark on this president. You know,

477
00:28:22,359 --> 00:28:25,119
Speaker 1: the fact that people did get arrested already, just because

478
00:28:25,880 --> 00:28:28,240
Speaker 1: you didn't get a grand slam doesn't mean that all

479
00:28:28,280 --> 00:28:30,600
Speaker 1: the other people around him that he claimed we're good

480
00:28:30,680 --> 00:28:34,720
Speaker 1: people were proven to be traitorous. To mention, he was

481
00:28:34,760 --> 00:28:40,360
Speaker 1: an unnamed, unindicted co conspirator and exactly, and again I

482
00:28:40,440 --> 00:28:42,720
Speaker 1: think it's even people are so quick to just take

483
00:28:42,800 --> 00:28:45,880
Speaker 1: the William Barr summary as what the actual Mola report is.

484
00:28:45,960 --> 00:28:48,040
Speaker 1: And I think that's people need to pump the brakes

485
00:28:48,080 --> 00:28:50,360
Speaker 1: on that and constantly be telling for people who just

486
00:28:50,640 --> 00:28:54,040
Speaker 1: sort of watched the news in a very like unengaged way,

487
00:28:54,440 --> 00:28:56,320
Speaker 1: to really remind people of that, because a lot of

488
00:28:56,360 --> 00:28:58,480
Speaker 1: people are just like reading the chirons and being like, oh,

489
00:28:58,600 --> 00:29:02,600
Speaker 1: maller report usan okay, okay, so there must be none.

490
00:29:02,920 --> 00:29:05,360
Speaker 1: They're watching it the way I think a lot of

491
00:29:05,400 --> 00:29:07,440
Speaker 1: people watch politics the way I used to watch cricket,

492
00:29:07,880 --> 00:29:09,960
Speaker 1: Like I didn't know anything about cricket. I don't really

493
00:29:10,160 --> 00:29:15,320
Speaker 1: cricket or see I don't know. And all he told

494
00:29:15,360 --> 00:29:18,520
Speaker 1: me was, this is our team. I'm not gonna explain

495
00:29:18,520 --> 00:29:20,320
Speaker 1: all the rules to you, but this is our team.

496
00:29:20,680 --> 00:29:22,920
Speaker 1: And anytime something happened, I didn't and even if I

497
00:29:23,000 --> 00:29:25,440
Speaker 1: didn't even understand it, I just want, oh, well, that's

498
00:29:25,480 --> 00:29:28,680
Speaker 1: our team, so I'm gonna root when something is positioned

499
00:29:28,800 --> 00:29:31,040
Speaker 1: is good for our team. Everyone on my sides cheering

500
00:29:31,120 --> 00:29:33,880
Speaker 1: right now, exactly. And I think that's what a lot

501
00:29:33,920 --> 00:29:35,800
Speaker 1: of these people are doing. That they've turned They've made

502
00:29:35,880 --> 00:29:38,320
Speaker 1: us tribal to the exact opposite of what this country

503
00:29:38,400 --> 00:29:40,760
Speaker 1: is about. The word united is the most critical word.

504
00:29:41,080 --> 00:29:43,040
Speaker 1: And that's the fact that he's dividing the country and

505
00:29:43,120 --> 00:29:47,440
Speaker 1: that and the Fox News displays news with it, they

506
00:29:47,480 --> 00:29:50,760
Speaker 1: display it. It's just it's so un American. Yes, I

507
00:29:50,800 --> 00:29:54,040
Speaker 1: would I would say, like, I won't be any less

508
00:29:54,040 --> 00:29:57,320
Speaker 1: suspicious of his administration. I won't be any less you know,

509
00:29:57,560 --> 00:30:02,640
Speaker 1: completely suspicious of Fox News as just a mouthpiece for

510
00:30:03,400 --> 00:30:07,160
Speaker 1: a very cynical point of view. Like Glenn Greenwald from

511
00:30:07,360 --> 00:30:11,480
Speaker 1: The Intercept, who's a leftist journalists, like he got a

512
00:30:11,560 --> 00:30:14,440
Speaker 1: lot of things right about the Maler report and was

513
00:30:14,600 --> 00:30:17,000
Speaker 1: like voicing a lot of concern about some of the

514
00:30:17,080 --> 00:30:19,880
Speaker 1: stories that were being reported and not corrected when they

515
00:30:19,960 --> 00:30:22,640
Speaker 1: turned out not to be true. But then he went

516
00:30:22,720 --> 00:30:26,000
Speaker 1: on Tucker Carlson the other day and with Tucker Carlson

517
00:30:26,200 --> 00:30:28,000
Speaker 1: was like, you guys got it right. They were just like,

518
00:30:28,320 --> 00:30:31,680
Speaker 1: you know, jerking each other off for fucking getting like

519
00:30:31,800 --> 00:30:34,800
Speaker 1: a couple parts of the story right. And it's just like, yeah,

520
00:30:34,960 --> 00:30:38,880
Speaker 1: like sometimes a broken system or like a broken clock

521
00:30:39,000 --> 00:30:40,760
Speaker 1: is going to be right twice a day, so to speak,

522
00:30:40,880 --> 00:30:44,800
Speaker 1: Like that's that's how Fox News was right on a

523
00:30:44,880 --> 00:30:47,360
Speaker 1: couple of the stories. But like to to go on

524
00:30:47,520 --> 00:30:51,360
Speaker 1: there and like congratulate them is like, I think inexcusable

525
00:30:51,480 --> 00:30:55,080
Speaker 1: for something who's like, uh, supposed to be trying to

526
00:30:56,080 --> 00:30:59,440
Speaker 1: you know, we're we're in a point in our history

527
00:30:59,520 --> 00:31:02,800
Speaker 1: where where at war over the truth and to go

528
00:31:02,920 --> 00:31:07,160
Speaker 1: on like the primary mouthpiece for you know, distorting our

529
00:31:07,240 --> 00:31:09,800
Speaker 1: reality and like congratulate them on getting a couple of

530
00:31:09,920 --> 00:31:15,160
Speaker 1: the details wrong is pretty inexcusable. Isn't Muller Republican? Yes?

531
00:31:15,560 --> 00:31:19,680
Speaker 1: And they kept saying he's hyper by but yeah, he's hyperpartisan. Again,

532
00:31:20,760 --> 00:31:23,120
Speaker 1: he's a Republican. I think that is Their art form

533
00:31:23,240 --> 00:31:26,560
Speaker 1: is like this in addition to corruption, is like knowing

534
00:31:26,640 --> 00:31:31,720
Speaker 1: how to play this person media game, like setting expectations,

535
00:31:31,880 --> 00:31:35,440
Speaker 1: like they they invented the thing where you portray the

536
00:31:35,520 --> 00:31:38,720
Speaker 1: person you're about to have a debate with as the

537
00:31:38,840 --> 00:31:42,360
Speaker 1: greatest or a tour since fucking well, I think that's

538
00:31:42,440 --> 00:31:45,080
Speaker 1: Trump surreal genius. How he plays the media is that

539
00:31:45,200 --> 00:31:47,640
Speaker 1: he owns one of the biggest networks, right, Yeah, that

540
00:31:47,720 --> 00:31:51,800
Speaker 1: helps whatever he says they repeat without question. Yeah, amplify that,

541
00:31:51,960 --> 00:31:55,440
Speaker 1: Yeah exactly that At one trend I'm seeing is that

542
00:31:56,000 --> 00:31:59,560
Speaker 1: the right is using the idea that there was no

543
00:31:59,680 --> 00:32:03,680
Speaker 1: evidence that the Trump administration colluded with Russia to a

544
00:32:03,800 --> 00:32:08,000
Speaker 1: degree that was criminal. They're apparently counterintelligence probes that are saying,

545
00:32:08,440 --> 00:32:13,040
Speaker 1: you know, that's a lesser bar for proving anything. You

546
00:32:13,120 --> 00:32:15,160
Speaker 1: don't need to like prove it in a criminal court

547
00:32:15,280 --> 00:32:19,800
Speaker 1: for it to be an intelligence situation. But I'm seeing

548
00:32:20,000 --> 00:32:23,280
Speaker 1: people on the right then acting like that means that

549
00:32:23,800 --> 00:32:28,400
Speaker 1: Russia didn't interfere in the election. They're basically using the

550
00:32:28,840 --> 00:32:32,920
Speaker 1: this wave of energy in the news cycle to then

551
00:32:33,000 --> 00:32:36,240
Speaker 1: be like and that's all that's pattent. Like in culture,

552
00:32:36,400 --> 00:32:39,600
Speaker 1: did a head a story on her website, which big

553
00:32:39,720 --> 00:32:43,120
Speaker 1: fan always first first sight that I check in the morning,

554
00:32:43,600 --> 00:32:48,280
Speaker 1: but she was, you know, listing all these MSNBC statements

555
00:32:48,400 --> 00:32:52,600
Speaker 1: that were, you know, now look crazy and so like

556
00:32:52,720 --> 00:32:56,680
Speaker 1: alongside ones where they're saying the Russia conspiracy to help

557
00:32:56,720 --> 00:32:59,480
Speaker 1: Donald Trump get elected was apparently wider, deeper, dirty, or

558
00:32:59,520 --> 00:33:02,800
Speaker 1: more sophist dedicated, more pervasive than we thought was like

559
00:33:03,000 --> 00:33:06,760
Speaker 1: right alongside ones where it says that Trump colluded and

560
00:33:06,840 --> 00:33:09,440
Speaker 1: it's like, no, those are one of those is true.

561
00:33:10,120 --> 00:33:16,080
Speaker 1: Trump was helped by Russians. The Russians explicitly, they just

562
00:33:16,280 --> 00:33:18,920
Speaker 1: can't they just can't prove that there was someone on

563
00:33:19,000 --> 00:33:22,200
Speaker 1: the Trump side of things co ordinating with the Russians

564
00:33:22,320 --> 00:33:25,280
Speaker 1: to help this. Did it on TV? You stood in

565
00:33:25,360 --> 00:33:27,640
Speaker 1: front of a TV camera and said, hey, Russia, get

566
00:33:27,720 --> 00:33:30,360
Speaker 1: those other emails for me, said in front of everybody.

567
00:33:30,480 --> 00:33:32,400
Speaker 1: And I think this is where it gets a little tricky, right,

568
00:33:32,400 --> 00:33:34,640
Speaker 1: because collusion isn't really something that has like a proper

569
00:33:34,800 --> 00:33:38,520
Speaker 1: legal definition, and by trying to chase that down, we're

570
00:33:38,520 --> 00:33:42,680
Speaker 1: already playing a flawed game. When Trump created Well here's

571
00:33:42,680 --> 00:33:44,800
Speaker 1: the other thing. Like, for any girl that's ever dated

572
00:33:44,800 --> 00:33:47,080
Speaker 1: a guy who's a cheater, and I think Trump is

573
00:33:47,200 --> 00:33:52,520
Speaker 1: a cheater, is part of his nationality. Yeah, But any

574
00:33:52,880 --> 00:33:55,080
Speaker 1: as any girl in any Time traveler will tell you,

575
00:33:56,000 --> 00:33:58,120
Speaker 1: the Muller report is not the end. It's the beginning.

576
00:33:58,560 --> 00:34:00,520
Speaker 1: Any girl that's ever caught a guy that she was

577
00:34:00,600 --> 00:34:02,960
Speaker 1: suspicious of him cheating on her, and if if it

578
00:34:03,160 --> 00:34:05,720
Speaker 1: if it was, if it merited in an investigation and

579
00:34:05,840 --> 00:34:07,719
Speaker 1: the guy got out of it, it was the beginning.

580
00:34:08,520 --> 00:34:11,920
Speaker 1: He was gonna get caught. The next thing, Ship's coming, right.

581
00:34:12,000 --> 00:34:14,000
Speaker 1: Every every talk show I've ever seen somebody go on

582
00:34:14,080 --> 00:34:17,600
Speaker 1: that says, I think my man is cheating. Dude was cheating, right, Well,

583
00:34:17,640 --> 00:34:19,239
Speaker 1: I don't know. I saw a couple more episodes, or

584
00:34:19,280 --> 00:34:20,799
Speaker 1: that there's a couple more, is there's a couple more

585
00:34:20,840 --> 00:34:28,040
Speaker 1: I'll give you that, I'll give you. It's always the

586
00:34:28,120 --> 00:34:31,880
Speaker 1: husband or boyfriend, always yeah, yeah, And I guess also

587
00:34:32,040 --> 00:34:35,239
Speaker 1: it's even hard to even say that anything is incorrect

588
00:34:35,680 --> 00:34:39,279
Speaker 1: because everything we do know amounts to a lot of

589
00:34:39,640 --> 00:34:43,920
Speaker 1: talk and back and forth and communication between the two sides,

590
00:34:44,400 --> 00:34:47,279
Speaker 1: just because it didn't reach the level of like criminal

591
00:34:48,040 --> 00:34:51,920
Speaker 1: you know, coordination or conspiracy is one thing versus you know,

592
00:34:52,040 --> 00:34:56,320
Speaker 1: like not having the laws to properly defined like that.

593
00:34:56,440 --> 00:34:59,600
Speaker 1: This behavior is like absolutely has no there's no room

594
00:34:59,680 --> 00:35:02,600
Speaker 1: for it in our system. That's a great distinction. Actually,

595
00:35:02,960 --> 00:35:04,719
Speaker 1: he he knows how to play the law. He knows

596
00:35:04,760 --> 00:35:06,480
Speaker 1: how to play with lawyers, and there are there are

597
00:35:06,600 --> 00:35:09,680
Speaker 1: legal mistakes that he found ways to prove that he

598
00:35:09,760 --> 00:35:14,440
Speaker 1: didn't break, but ethically, ethically he's broken all of them. Right,

599
00:35:14,440 --> 00:35:16,480
Speaker 1: and then again, just to talk about this momentum, right,

600
00:35:16,560 --> 00:35:20,000
Speaker 1: he he gets the bar Okay William Barr's the Mulla

601
00:35:20,080 --> 00:35:23,480
Speaker 1: Report and uses that to say, oh, I'm totally exonerated.

602
00:35:23,680 --> 00:35:27,000
Speaker 1: Everything's all good, and then goes full gear, like he

603
00:35:27,080 --> 00:35:29,080
Speaker 1: turns a ship up to ten about being like Okay,

604
00:35:29,160 --> 00:35:31,799
Speaker 1: now send memos out to newsrooms being liked, and these

605
00:35:31,840 --> 00:35:33,960
Speaker 1: people from ever talking again because they were caught lying.

606
00:35:34,120 --> 00:35:36,719
Speaker 1: That's not true, that's that's not even close to being

607
00:35:36,760 --> 00:35:39,600
Speaker 1: with the cases or uh, you know, having a rally

608
00:35:40,000 --> 00:35:42,680
Speaker 1: last night in Michigan to just basically be like, hey,

609
00:35:42,960 --> 00:35:46,440
Speaker 1: no collusion, like this is definitely energized the president of

610
00:35:46,600 --> 00:35:51,040
Speaker 1: very bizarre way. Whe're like, you can't that's good, of course, confident,

611
00:35:51,280 --> 00:35:54,080
Speaker 1: no right. And and again even with healthcare put out

612
00:35:54,120 --> 00:35:56,800
Speaker 1: the thing with dj saying, yeah, we're gonna defend this

613
00:35:57,080 --> 00:36:00,239
Speaker 1: ruling in Texas to the Supreme Court that Obamacare would

614
00:36:00,239 --> 00:36:03,960
Speaker 1: be completely just gutted. So the momentum taking him in

615
00:36:04,000 --> 00:36:06,120
Speaker 1: a weird way. And then you now have you know,

616
00:36:06,200 --> 00:36:10,239
Speaker 1: Republicans and the House Intelligence Committee telling Adam Shift to

617
00:36:10,280 --> 00:36:12,560
Speaker 1: resign because he was saying he's like there's a lot

618
00:36:12,600 --> 00:36:15,880
Speaker 1: of clear evidence that something was going on. And it

619
00:36:16,080 --> 00:36:19,200
Speaker 1: was really bizarre to see immediately how like all nine

620
00:36:19,239 --> 00:36:21,319
Speaker 1: Republicans on there just signed a letter being like, oh,

621
00:36:21,400 --> 00:36:24,080
Speaker 1: you need to resign for like lying, even though Devin

622
00:36:24,200 --> 00:36:28,880
Speaker 1: Nonez was doing the fucking most to actually obstruct this

623
00:36:29,040 --> 00:36:31,319
Speaker 1: investigation as much as he could. And then I mean,

624
00:36:31,400 --> 00:36:35,319
Speaker 1: so credits Adam what who told it who asked him

625
00:36:35,360 --> 00:36:38,200
Speaker 1: to resign? So all the Republicans. It was all the Republicans,

626
00:36:38,320 --> 00:36:42,880
Speaker 1: but it was Conway from Mike Conway from Texas who

627
00:36:43,000 --> 00:36:44,880
Speaker 1: was basically just say, we have no fa Like he

628
00:36:45,040 --> 00:36:46,600
Speaker 1: pulled up in the committee. I was like, we have

629
00:36:46,760 --> 00:36:50,640
Speaker 1: no faith. How many Democrats are on the committee? I'd

630
00:36:50,680 --> 00:36:54,319
Speaker 1: imagine nine also, and then he's got it. But now

631
00:36:54,400 --> 00:36:56,719
Speaker 1: that yeah, he's but now he's the chair because you

632
00:36:56,760 --> 00:36:59,440
Speaker 1: know the Democrats are in power. Um. So his rebuttal

633
00:36:59,480 --> 00:37:01,359
Speaker 1: to this was that she pretty good. Because they were

634
00:37:01,400 --> 00:37:03,680
Speaker 1: really trying to spin this as like when we were

635
00:37:03,760 --> 00:37:06,840
Speaker 1: running this committee, everything was done in good faith. We

636
00:37:06,920 --> 00:37:10,040
Speaker 1: were very honest. Devin Nounez wasn't getting stuff from the

637
00:37:10,080 --> 00:37:11,960
Speaker 1: White House and then pretending he did. You know what

638
00:37:12,040 --> 00:37:14,319
Speaker 1: I mean, there was there was so much bizarre ship

639
00:37:14,440 --> 00:37:16,239
Speaker 1: going on, and just because Adam shiff was like, no,

640
00:37:16,520 --> 00:37:19,160
Speaker 1: there's I smell shit and we have to keep going

641
00:37:19,480 --> 00:37:21,920
Speaker 1: and using this to be like anyone who even suspected

642
00:37:21,960 --> 00:37:26,400
Speaker 1: the president is an evil treasonists like fucking Trader um.

643
00:37:26,719 --> 00:37:28,800
Speaker 1: And I was trying to figure out what Russia to

644
00:37:28,880 --> 00:37:30,640
Speaker 1: turn it into Russia they're trying to turn it into

645
00:37:31,200 --> 00:37:33,560
Speaker 1: James Coley, in an interview with Lester Holt, was saying,

646
00:37:33,680 --> 00:37:39,200
Speaker 1: imagine if President Barack Obama was working with the Iranians

647
00:37:39,520 --> 00:37:43,160
Speaker 1: to possibly put together a better Iran nuclear deal, that

648
00:37:43,200 --> 00:37:45,440
Speaker 1: the arrange that would help the Iranians, and you had

649
00:37:45,640 --> 00:37:50,680
Speaker 1: his National Security advisor designate flirting with the ambassadors to

650
00:37:50,800 --> 00:37:53,960
Speaker 1: Iran lying to the FBI about it. If imagine if

651
00:37:54,040 --> 00:37:56,680
Speaker 1: Malia or somebody was trying to set a back channel

652
00:37:56,760 --> 00:37:59,440
Speaker 1: with Russia or the Iran and you're gonna tell me

653
00:37:59,480 --> 00:38:02,800
Speaker 1: the FBI shouldn't look into this. That's that's unheard of anyway.

654
00:38:02,800 --> 00:38:05,040
Speaker 1: I just want to play Adam Shift's sort of response

655
00:38:05,120 --> 00:38:07,560
Speaker 1: to Mike Conaway, because he was like, oh, really, like

656
00:38:07,680 --> 00:38:10,080
Speaker 1: you're you're trying to act like I'm acting dishonorable, and

657
00:38:10,280 --> 00:38:13,280
Speaker 1: this was his response. My colleagues may think it's okay

658
00:38:14,440 --> 00:38:18,440
Speaker 1: that the Russians offered dirt on a Democratic candidate for

659
00:38:18,520 --> 00:38:21,440
Speaker 1: president as part of what was described as the Russian

660
00:38:21,480 --> 00:38:24,640
Speaker 1: government's effort to help the Trump campaign. You might think

661
00:38:24,719 --> 00:38:29,880
Speaker 1: that's okay. My colleagues might think it's okay when that

662
00:38:30,040 --> 00:38:32,759
Speaker 1: was offered to the son of the president who had

663
00:38:32,760 --> 00:38:35,960
Speaker 1: a pivotal role in the campaign. That the president's son

664
00:38:36,040 --> 00:38:39,960
Speaker 1: did not call the FBI, He did not adamantly refuse

665
00:38:40,280 --> 00:38:44,120
Speaker 1: that foreign help. No, Instead, that son said that he

666
00:38:44,200 --> 00:38:48,040
Speaker 1: would love the help of the Russians. That Paul Manafoort,

667
00:38:48,080 --> 00:38:50,680
Speaker 1: the campaign share, someone with great experience and running campaigns,

668
00:38:51,520 --> 00:38:53,759
Speaker 1: also took that meeting. That the president's son in law

669
00:38:54,400 --> 00:38:57,480
Speaker 1: also took that meeting. That their only disappointment after that

670
00:38:57,560 --> 00:39:00,280
Speaker 1: meeting was that the dirt they received on Hillary Innton

671
00:39:00,440 --> 00:39:03,399
Speaker 1: wasn't better. That when it was discovered a year later

672
00:39:04,200 --> 00:39:06,840
Speaker 1: that they lied about that meeting, that the President is

673
00:39:06,880 --> 00:39:10,840
Speaker 1: reported to have helped dictate that lie, that the campaign

674
00:39:10,960 --> 00:39:15,920
Speaker 1: chairman of a presidential campaign would offer information about that

675
00:39:16,040 --> 00:39:19,360
Speaker 1: campaign to a Russian oligarch in exchange for money or

676
00:39:19,400 --> 00:39:22,640
Speaker 1: debt forgiveness, That that campaign chairman offered polling data to

677
00:39:22,760 --> 00:39:25,719
Speaker 1: someone linked to Russian intelligence, That the president himself called

678
00:39:25,760 --> 00:39:28,960
Speaker 1: on Russia to hack his opponents emails at the president's

679
00:39:28,960 --> 00:39:32,920
Speaker 1: son in law sought to establish a secret back channel

680
00:39:32,960 --> 00:39:35,840
Speaker 1: of communications, and he goes on, this is all facts,

681
00:39:35,880 --> 00:39:37,960
Speaker 1: he's saying. These are not denial. These are all things

682
00:39:38,040 --> 00:39:40,240
Speaker 1: that are out here in public. People have played guilty

683
00:39:40,280 --> 00:39:42,239
Speaker 1: to this ship, right, And that's the thing that I

684
00:39:42,280 --> 00:39:45,560
Speaker 1: think is bad faith with the even the leftist journalists

685
00:39:45,640 --> 00:39:47,560
Speaker 1: like calling out the media and being like all of

686
00:39:47,680 --> 00:39:51,400
Speaker 1: the Russia's our generations w M D S. It's like, no,

687
00:39:51,560 --> 00:39:55,160
Speaker 1: they really uncovered some very shady ship. The mainstream media

688
00:39:55,719 --> 00:39:58,080
Speaker 1: did do some good reporting, and to act like the

689
00:39:58,200 --> 00:40:01,920
Speaker 1: whole thing was overblown just because because the MSNBC did

690
00:40:02,160 --> 00:40:04,920
Speaker 1: like funk up and like go crazy over it, doesn't

691
00:40:05,400 --> 00:40:07,840
Speaker 1: that's not the direction we should be taking it. And

692
00:40:08,000 --> 00:40:10,560
Speaker 1: like this self reproach and I mean, even if you

693
00:40:10,600 --> 00:40:12,239
Speaker 1: want to slightly defend what they were trying to do

694
00:40:12,320 --> 00:40:14,840
Speaker 1: on MSNBC, like they were looking at a set of

695
00:40:14,920 --> 00:40:17,920
Speaker 1: facts and respond like or a lot of journalistic reporting

696
00:40:17,960 --> 00:40:20,279
Speaker 1: too of things like this and saying this looks so

697
00:40:20,480 --> 00:40:22,839
Speaker 1: fucking bad. I think, yeah, maybe at times they went

698
00:40:22,920 --> 00:40:24,440
Speaker 1: from just sort of being like this looks bad to

699
00:40:24,520 --> 00:40:26,520
Speaker 1: like this is what the whole fucking thing is without

700
00:40:26,600 --> 00:40:30,480
Speaker 1: fully knowing. Uh. But again I think even so just

701
00:40:30,680 --> 00:40:32,200
Speaker 1: to some of what Adam Stifts said at the end,

702
00:40:32,200 --> 00:40:34,080
Speaker 1: he said, you know, he listed all that ship, and

703
00:40:34,160 --> 00:40:35,640
Speaker 1: he's like you might think that's all okay. And this

704
00:40:35,680 --> 00:40:36,960
Speaker 1: is a quote from him. He said, you might just

705
00:40:37,040 --> 00:40:39,239
Speaker 1: say that's what you need to do to win, But

706
00:40:39,400 --> 00:40:41,719
Speaker 1: I don't think it's okay. I think it's immoral. I

707
00:40:41,760 --> 00:40:44,680
Speaker 1: think it's unethical, I think it's unpatriotic. And yes, I

708
00:40:44,760 --> 00:40:48,560
Speaker 1: think it's corrupt and evidence of collusion. So you know,

709
00:40:48,719 --> 00:40:51,120
Speaker 1: like they can are they have no response to that,

710
00:40:51,239 --> 00:40:53,879
Speaker 1: because they all saw that with their own eyes. It's

711
00:40:53,920 --> 00:40:55,440
Speaker 1: just now a matter of like, well, how much do

712
00:40:55,560 --> 00:40:58,600
Speaker 1: we want to you know, forgive that because we're we're

713
00:40:58,640 --> 00:41:01,759
Speaker 1: in the same jersey. Right. A point that's being made

714
00:41:02,400 --> 00:41:04,840
Speaker 1: a little bit in sort of the background of this

715
00:41:05,320 --> 00:41:07,759
Speaker 1: one version of the story that's out there in the

716
00:41:08,000 --> 00:41:12,000
Speaker 1: forefront that is like no collusion Trump has vindicated is

717
00:41:12,400 --> 00:41:15,920
Speaker 1: this point that there are kind of two standards of

718
00:41:16,360 --> 00:41:19,480
Speaker 1: what the various people investigating the two thousand and sixteen

719
00:41:19,520 --> 00:41:23,000
Speaker 1: election are trying to live up to. Mueller was trying

720
00:41:23,040 --> 00:41:26,800
Speaker 1: to live up to the highest possible standard, which is,

721
00:41:26,920 --> 00:41:30,800
Speaker 1: can you win a criminal court case like will this

722
00:41:30,920 --> 00:41:34,239
Speaker 1: stand up and and prove beyond reasonable doubt that there

723
00:41:34,320 --> 00:41:38,000
Speaker 1: is a criminal conspiracy. Now, there's also the level of

724
00:41:38,160 --> 00:41:42,800
Speaker 1: counter intelligence that's like the CIA gathering intelligence trying to

725
00:41:42,880 --> 00:41:45,759
Speaker 1: find out what's actually going on in real time and

726
00:41:46,120 --> 00:41:49,960
Speaker 1: you know, establish their best guests at you know, what

727
00:41:50,800 --> 00:41:55,560
Speaker 1: we can put together based on the information that we're

728
00:41:55,680 --> 00:42:00,480
Speaker 1: able to find out using objective investigation. And people are

729
00:42:00,600 --> 00:42:06,200
Speaker 1: saying that there are still counterintelligence like investigations happening into

730
00:42:06,320 --> 00:42:09,600
Speaker 1: the two thousand sixteen election, into the question where that

731
00:42:09,760 --> 00:42:14,279
Speaker 1: Mueller ultimately concluded was kind of a nonstarter from a

732
00:42:14,360 --> 00:42:21,120
Speaker 1: criminal perspective. But this guy, uh, Frank fig Louzy, who

733
00:42:21,239 --> 00:42:24,440
Speaker 1: is a former assistant director for counterintelligence at the FBI,

734
00:42:25,400 --> 00:42:27,960
Speaker 1: was like, we never thought that Mueller would bring a

735
00:42:28,080 --> 00:42:32,120
Speaker 1: conspiracy charge, and focusing on the absence of criminal indictments

736
00:42:32,200 --> 00:42:36,680
Speaker 1: for conspiracy doesn't really do anything if all we do

737
00:42:36,840 --> 00:42:41,359
Speaker 1: is apply criminal standards to investigative findings. Were missing the point.

738
00:42:41,920 --> 00:42:44,960
Speaker 1: This thing started as a counter intelligence investigation, and it

739
00:42:45,080 --> 00:42:49,080
Speaker 1: needs to end as a counter intelligence investigation. Yeah, I'll

740
00:42:49,120 --> 00:42:52,640
Speaker 1: tell you one thing. Three pages is suspiciously short. Yeah,

741
00:42:53,000 --> 00:42:55,759
Speaker 1: that's right. After all this time, even if it would

742
00:42:55,760 --> 00:42:57,959
Speaker 1: have said three thousand pages, I would have still thought

743
00:42:58,000 --> 00:43:00,920
Speaker 1: that sounded need to be like home that's brought down

744
00:43:01,000 --> 00:43:02,719
Speaker 1: like on a forklift. Well, yeah, I mean all the

745
00:43:02,800 --> 00:43:04,640
Speaker 1: time that they've spent on it, and and the way

746
00:43:04,760 --> 00:43:07,279
Speaker 1: the Mueller. I mean, the quote that I've heard most

747
00:43:07,320 --> 00:43:09,399
Speaker 1: often about Mueller is, uh, you know, when they ask

748
00:43:09,520 --> 00:43:11,200
Speaker 1: Abraham Lincoln, what would you do if you have two

749
00:43:11,200 --> 00:43:13,200
Speaker 1: hours of chopped down tree, he said, I'd spend the

750
00:43:13,239 --> 00:43:15,919
Speaker 1: first hour and a half sharpen the axe. And that's

751
00:43:15,960 --> 00:43:18,439
Speaker 1: what Mueller was. Mueller was like associated with that quote.

752
00:43:18,480 --> 00:43:21,719
Speaker 1: He he is a detailed person. He spends a lot

753
00:43:21,760 --> 00:43:23,600
Speaker 1: of time. He won't go after a case that he

754
00:43:23,640 --> 00:43:26,520
Speaker 1: doesn't know he can win. Like it just sounds really

755
00:43:27,080 --> 00:43:31,279
Speaker 1: really suspicious. Yeah, well, I'm looking forward to get my

756
00:43:31,360 --> 00:43:33,400
Speaker 1: hands on a copy. I don't think it's the end.

757
00:43:34,200 --> 00:43:35,719
Speaker 1: I think it's the beginning. I mean, yeah, with the

758
00:43:35,800 --> 00:43:39,360
Speaker 1: in terms of length, I don't know if that necessarily

759
00:43:39,440 --> 00:43:41,759
Speaker 1: indicates one thing or never. I think the most suspicious

760
00:43:41,800 --> 00:43:44,440
Speaker 1: thing on its surface is basically that William Barr was

761
00:43:44,480 --> 00:43:48,680
Speaker 1: allowed to basically poison the well summary before the actual

762
00:43:48,719 --> 00:43:51,040
Speaker 1: report came out. I think that is by far the

763
00:43:51,080 --> 00:43:55,040
Speaker 1: most aggressive in your face, like sums up right, and

764
00:43:55,160 --> 00:43:58,640
Speaker 1: it might be there might be some lies in his summary, Yeah,

765
00:43:58,760 --> 00:44:00,320
Speaker 1: you know, and I think that's why, you know, a

766
00:44:00,400 --> 00:44:02,680
Speaker 1: lot of the leadership on the Democratic side is you know,

767
00:44:02,800 --> 00:44:05,320
Speaker 1: they're saying, we gotta drag somebody up here to explain this,

768
00:44:05,520 --> 00:44:08,040
Speaker 1: whether it's William Barr, Robert Mueller, like they need to.

769
00:44:08,160 --> 00:44:10,520
Speaker 1: You know, we'll do something on the record talking. We

770
00:44:10,600 --> 00:44:13,279
Speaker 1: can do some closed door stuff, but you know, the

771
00:44:13,440 --> 00:44:17,640
Speaker 1: explanation as it stands is not sufficient. Yeah. The way

772
00:44:17,680 --> 00:44:20,120
Speaker 1: that these people play with lies, it's almost like when

773
00:44:20,120 --> 00:44:21,440
Speaker 1: you're a kid and your mom finds a joint in

774
00:44:21,440 --> 00:44:23,120
Speaker 1: your pocket and go, it's not mine, mom, it's this

775
00:44:23,239 --> 00:44:25,200
Speaker 1: other guys, and your mom wants to believe it, so

776
00:44:25,320 --> 00:44:27,759
Speaker 1: she believes it. And it makes me wonder if the

777
00:44:28,280 --> 00:44:30,520
Speaker 1: the energy and the speed that they went out with

778
00:44:30,600 --> 00:44:34,000
Speaker 1: their conclusions was because they knew that a truth might

779
00:44:34,040 --> 00:44:36,279
Speaker 1: be coming out that is going to damage them, so

780
00:44:36,360 --> 00:44:38,319
Speaker 1: that they said, let's feed a lie that feels better

781
00:44:38,680 --> 00:44:42,480
Speaker 1: so that when the truth comes out people will resist it. Yeah,

782
00:44:43,000 --> 00:44:47,680
Speaker 1: well just tell mus your joint, you know. Yeah, that's

783
00:44:47,719 --> 00:44:51,880
Speaker 1: the solution. I mean, that is kind of what Trump proved.

784
00:44:51,960 --> 00:44:56,480
Speaker 1: He is just openly He's like that. I was doing

785
00:44:56,520 --> 00:45:01,720
Speaker 1: a lot of baby is not a cry and threatened

786
00:45:01,760 --> 00:45:06,200
Speaker 1: witnesses on Twitter. Um, all right, we're gonna take another

787
00:45:06,320 --> 00:45:18,959
Speaker 1: quick break and we'll be right back, and we're back,

788
00:45:19,760 --> 00:45:23,959
Speaker 1: and there is a controversy on the country charts, which

789
00:45:24,080 --> 00:45:28,320
Speaker 1: we're always staying on top of. Uh No, But for

790
00:45:28,400 --> 00:45:32,239
Speaker 1: the first time, a song that I might actually listen

791
00:45:32,320 --> 00:45:35,879
Speaker 1: to was climbing the country charts. Uh called Old Town Road.

792
00:45:36,239 --> 00:45:39,080
Speaker 1: Old Town Road by Little Nasax. And when I saw

793
00:45:39,160 --> 00:45:41,960
Speaker 1: this name trending, I was like, what did Naz's son do?

794
00:45:42,840 --> 00:45:44,719
Speaker 1: I did not know who the funk Little nos X

795
00:45:44,840 --> 00:45:48,799
Speaker 1: is because I am an elder, but apparently this song

796
00:45:49,000 --> 00:45:51,160
Speaker 1: was blowing the funk up and it did a very

797
00:45:51,239 --> 00:45:54,120
Speaker 1: I mean this guy, he's a really young artist rapper,

798
00:45:54,680 --> 00:45:57,440
Speaker 1: and this song Old Town Road charted like simultaneously on

799
00:45:57,480 --> 00:46:00,440
Speaker 1: the Billboard Hot one Hot Country Songs and Hot R

800
00:46:00,520 --> 00:46:02,480
Speaker 1: and B and hip hop songs. When you play just

801
00:46:02,640 --> 00:46:04,879
Speaker 1: a little bit, so you get an idea of where

802
00:46:04,960 --> 00:46:16,880
Speaker 1: this sign, where this sort of the vibe is. Yeah, okay,

803
00:46:17,280 --> 00:46:20,399
Speaker 1: it sounds good with little little banjo picking, little guitar

804
00:46:20,480 --> 00:46:23,439
Speaker 1: picking in the back. Oh, but you're ready for this part?

805
00:46:28,280 --> 00:46:33,719
Speaker 1: Is my black boos blacks rotting on? Anyway. It's an

806
00:46:33,760 --> 00:46:36,759
Speaker 1: interesting point though, because it's almost like he's being um

807
00:46:37,080 --> 00:46:41,120
Speaker 1: satirical about country music. But then and then, but Republican

808
00:46:41,160 --> 00:46:44,080
Speaker 1: parties don't seem to understand satire. That's why Stephen Colbert

809
00:46:44,640 --> 00:46:47,800
Speaker 1: what was like loved by both sides, because the concernatives

810
00:46:47,800 --> 00:46:50,359
Speaker 1: didn't realize that he was making fun of them, right right,

811
00:46:51,600 --> 00:46:54,759
Speaker 1: So that song, yes, I would say, yeah, there's some

812
00:46:54,920 --> 00:46:58,560
Speaker 1: cowboy imagery in there, got some some instruments, some textures

813
00:46:58,640 --> 00:47:01,360
Speaker 1: that are our country. And then enters the trap rhythm,

814
00:47:01,440 --> 00:47:03,560
Speaker 1: well eight oh eight drum kit, a little snarech, a

815
00:47:03,600 --> 00:47:07,560
Speaker 1: little high hats, chains and things like that. But apparently

816
00:47:08,000 --> 00:47:11,480
Speaker 1: that wasn't good enough because the billboards, the people who

817
00:47:11,520 --> 00:47:14,160
Speaker 1: are on the billboard charts were like, we're gonna pull it,

818
00:47:14,320 --> 00:47:16,239
Speaker 1: and this is what they said. Upon further review, is

819
00:47:16,280 --> 00:47:18,360
Speaker 1: determined that Old Town Road by Little nos X is

820
00:47:18,400 --> 00:47:21,960
Speaker 1: not currently merit inclusion on Billboards country charts. When determining genres,

821
00:47:21,960 --> 00:47:24,560
Speaker 1: a few factors are examined, but first and foremost is

822
00:47:24,680 --> 00:47:28,400
Speaker 1: musical composition. While Old Town Road incorporates references to country

823
00:47:28,440 --> 00:47:31,080
Speaker 1: and cowboy imagery, it does not embrace enough elements of

824
00:47:31,120 --> 00:47:34,799
Speaker 1: today's country music to chart in its current version. That's ridiculous, now,

825
00:47:35,120 --> 00:47:38,759
Speaker 1: that's ridiculous. I have some theories as to why. Of course,

826
00:47:38,840 --> 00:47:42,160
Speaker 1: because black crossover artists especially in the country. I think

827
00:47:42,239 --> 00:47:44,640
Speaker 1: they did not like that. And I think also when

828
00:47:44,640 --> 00:47:47,719
Speaker 1: you also look at country music, here's the thing. The

829
00:47:48,000 --> 00:47:51,440
Speaker 1: label calls it sort of this country trap thing. On iTunes,

830
00:47:51,520 --> 00:47:53,640
Speaker 1: it was under country. I'm sure they submitted it like that,

831
00:47:54,080 --> 00:47:56,359
Speaker 1: and even other country artists are kind of like, yeah,

832
00:47:56,400 --> 00:47:58,520
Speaker 1: that's got some country vibe to it, like let it rock.

833
00:47:58,680 --> 00:48:00,960
Speaker 1: Yet they found a way to say this is not

834
00:48:01,160 --> 00:48:04,000
Speaker 1: country enough. Stupid, And I don't know what exactly the

835
00:48:04,040 --> 00:48:06,480
Speaker 1: standard is because I can play you a song by

836
00:48:06,600 --> 00:48:09,719
Speaker 1: b B Rexa and Florida Georgia Line that is number

837
00:48:09,760 --> 00:48:12,239
Speaker 1: three on the country charts, and I mean, listen to this,

838
00:48:14,880 --> 00:48:20,840
Speaker 1: Oh yeah, I know the song where your Country? I mean,

839
00:48:20,880 --> 00:48:25,160
Speaker 1: I love Johnny Cat, So to me, this sounds like

840
00:48:25,440 --> 00:48:27,320
Speaker 1: something straight pop, you know what I mean. It's like

841
00:48:27,400 --> 00:48:30,360
Speaker 1: an Ariana Grande type peeple. But I guess because of

842
00:48:30,400 --> 00:48:33,359
Speaker 1: the draw or the singing style, that's enough to meet

843
00:48:33,360 --> 00:48:36,640
Speaker 1: the country standard, because I'll go, I'll please skip around

844
00:48:36,680 --> 00:48:38,320
Speaker 1: this thing. So let's get to the skin color of

845
00:48:38,320 --> 00:48:40,920
Speaker 1: the one here in the same big bass, I'm here

846
00:48:40,920 --> 00:48:45,080
Speaker 1: in the same high hats here, you know hats. But

847
00:48:45,239 --> 00:48:49,960
Speaker 1: that's number three. That song should be are the artists white.

848
00:48:50,680 --> 00:48:53,520
Speaker 1: I don't know what bb Rexa's actual ethnicity is, but

849
00:48:53,680 --> 00:48:57,480
Speaker 1: I mean Florida, Georgia line. Again, they're not Little nas X.

850
00:48:58,200 --> 00:48:59,919
Speaker 1: And I think that's really the thing. I think because

851
00:49:00,040 --> 00:49:02,400
Speaker 1: it's aggressively like I think people were looking at it.

852
00:49:02,440 --> 00:49:06,800
Speaker 1: I don't know who were the outrage coming culturally, black culture,

853
00:49:07,800 --> 00:49:10,080
Speaker 1: country and how do we define that? And also like

854
00:49:10,160 --> 00:49:12,560
Speaker 1: when you think a lot of country songs I've heard

855
00:49:12,600 --> 00:49:15,680
Speaker 1: recently have that hip hop like like rhythm to it,

856
00:49:15,960 --> 00:49:17,800
Speaker 1: well you know what else it is? It's almost like

857
00:49:18,760 --> 00:49:20,560
Speaker 1: you like a girl who likes you until you find

858
00:49:20,600 --> 00:49:22,840
Speaker 1: out she likes other people. Then she's not special anymore,

859
00:49:23,239 --> 00:49:25,800
Speaker 1: you know what I mean. And it's like these companies,

860
00:49:25,920 --> 00:49:29,040
Speaker 1: these corporations and these platforms make brands by keeping us divided.

861
00:49:29,280 --> 00:49:31,520
Speaker 1: What Little nas X did was something that was beautiful.

862
00:49:31,840 --> 00:49:34,279
Speaker 1: He turned America into a fusion restaurant, and all of

863
00:49:34,400 --> 00:49:36,680
Speaker 1: us had had pieces of ourselves in that song. That's

864
00:49:36,680 --> 00:49:39,000
Speaker 1: a beautiful thing. It's funny too when you think there

865
00:49:39,000 --> 00:49:40,759
Speaker 1: are a lot of tweets and that song was blowing up.

866
00:49:40,800 --> 00:49:42,920
Speaker 1: People were like, I hate like tweets are doing like

867
00:49:42,960 --> 00:49:45,040
Speaker 1: I hate country, and then they put But when Old

868
00:49:45,080 --> 00:49:46,800
Speaker 1: Town Road comes on and then like a video of

869
00:49:46,840 --> 00:49:49,359
Speaker 1: them losing their ship. It's a thing where it made.

870
00:49:49,680 --> 00:49:52,560
Speaker 1: It's it's actually crossing over, and it's allowing people from

871
00:49:52,680 --> 00:49:55,400
Speaker 1: two genres. Like if you're into hip hop, that's I

872
00:49:55,480 --> 00:49:57,440
Speaker 1: kind of fun with this banjo ship. And I'm sure

873
00:49:57,440 --> 00:49:59,719
Speaker 1: their country will be like, oh, these rhythms are okay. Yeah,

874
00:49:59,800 --> 00:50:02,839
Speaker 1: what wrong with somebody reminding us that we're all the same. Well,

875
00:50:02,880 --> 00:50:04,880
Speaker 1: it's wrong with that, I think, you know, I just

876
00:50:05,200 --> 00:50:08,000
Speaker 1: why can't they just let let him cross over? You know,

877
00:50:08,080 --> 00:50:10,239
Speaker 1: there was Cowboy Troy. There was that was a guy

878
00:50:10,239 --> 00:50:12,440
Speaker 1: who's doing hip hop and that was that seemed to

879
00:50:12,480 --> 00:50:15,000
Speaker 1: be fine enough, but I guess it because he wasn't,

880
00:50:15,239 --> 00:50:18,400
Speaker 1: you know, signaling enough or showing enough of the uh

881
00:50:18,640 --> 00:50:21,920
Speaker 1: touch points are textures esthetically musically that they're like, no, no, no,

882
00:50:22,040 --> 00:50:24,040
Speaker 1: this is this is more hip hop. Well like love

883
00:50:24,120 --> 00:50:25,920
Speaker 1: and inclusion and all of us thinking were the same

884
00:50:26,040 --> 00:50:28,600
Speaker 1: is not good for business. It's not. And that's why

885
00:50:28,640 --> 00:50:30,480
Speaker 1: they want to keep us divided and keep us separated

886
00:50:30,480 --> 00:50:32,399
Speaker 1: and separate our cultures so they can make more money

887
00:50:32,480 --> 00:50:37,560
Speaker 1: off us. Citizen three. Yeah, So I mean I'm not

888
00:50:37,680 --> 00:50:40,520
Speaker 1: sure what I'm the one thing they were clear on

889
00:50:40,640 --> 00:50:42,920
Speaker 1: because Rolling Stone reached out like what what then was

890
00:50:42,960 --> 00:50:45,960
Speaker 1: that about? It has nothing to do with race, Like,

891
00:50:46,080 --> 00:50:50,040
Speaker 1: I'm sorry, we're just calling Yeah, I thought I left

892
00:50:50,080 --> 00:50:52,640
Speaker 1: my wallet up there. What I thought. The article was

893
00:50:52,680 --> 00:50:55,800
Speaker 1: titled I'm not racist, but not racist. But this just

894
00:50:55,880 --> 00:50:59,640
Speaker 1: doesn't have enough country elements that I've decided unbelievable. But

895
00:50:59,760 --> 00:51:02,279
Speaker 1: you know what a little noaacs keep doing your thing

896
00:51:02,280 --> 00:51:05,160
Speaker 1: because old Town Road. I mean, this is definitely good

897
00:51:05,280 --> 00:51:08,760
Speaker 1: for the song because I haven't heard that ship before

898
00:51:08,880 --> 00:51:11,520
Speaker 1: this controversy. When it was one of those songs that

899
00:51:11,600 --> 00:51:13,719
Speaker 1: was like cooking on social media like TikTok there was

900
00:51:13,719 --> 00:51:15,320
Speaker 1: like a ye hot challenge people are doing and that

901
00:51:15,400 --> 00:51:17,640
Speaker 1: I've just been so busy. I haven't been on TikTok. Yeah,

902
00:51:17,640 --> 00:51:21,239
Speaker 1: I know, I know. It's just take your posting is

903
00:51:21,360 --> 00:51:23,200
Speaker 1: not what it used to be doing. Oh man, don't

904
00:51:23,239 --> 00:51:25,520
Speaker 1: say that, I know because you used to. You're gonna

905
00:51:25,520 --> 00:51:29,200
Speaker 1: get Yah, You're gonna get my fans really piste off

906
00:51:30,000 --> 00:51:34,560
Speaker 1: on TikTok do and all that hit the folks. Are

907
00:51:34,600 --> 00:51:38,880
Speaker 1: you on TikTok? No? I know, I don't know what

908
00:51:39,040 --> 00:51:43,680
Speaker 1: TikTok are going to get you an account. Though. Alright,

909
00:51:44,040 --> 00:51:48,520
Speaker 1: let's let's add another hero to the board. Alongside Little Nasax,

910
00:51:49,120 --> 00:51:52,719
Speaker 1: we have the person who is suing t g I

911
00:51:52,880 --> 00:51:59,200
Speaker 1: Fridays for their potato skin potato chips chips. I don't

912
00:51:59,200 --> 00:52:01,239
Speaker 1: know if y'all have seen these, right, It's a t

913
00:52:01,400 --> 00:52:06,280
Speaker 1: G I Friday's chip bag and it's Friday's skins chips.

914
00:52:06,800 --> 00:52:08,919
Speaker 1: Everyone's seen him, especially if you're hot, you get high,

915
00:52:08,920 --> 00:52:10,920
Speaker 1: you've definitely seen them because you bought them because you

916
00:52:11,040 --> 00:52:13,919
Speaker 1: thought maybe this could be like a potato skin. Well

917
00:52:14,400 --> 00:52:18,280
Speaker 1: tell that to Salange Tronko So of the Bronx, because

918
00:52:18,600 --> 00:52:22,560
Speaker 1: she is fucking taking TJ Fridays to motherfucking court. She

919
00:52:22,719 --> 00:52:26,720
Speaker 1: because she's basically saying that, look, this is not actually

920
00:52:26,920 --> 00:52:29,480
Speaker 1: a potato skin. It's laid potato skins. But this is

921
00:52:29,560 --> 00:52:32,560
Speaker 1: just a quote mishmash of potato flakes and potato starch.

922
00:52:33,200 --> 00:52:36,279
Speaker 1: And in her suit, she states that she purchased the

923
00:52:36,320 --> 00:52:38,840
Speaker 1: bag of the TJ Friday sour cream and onion potato

924
00:52:38,920 --> 00:52:42,240
Speaker 1: skins from a bodega for but claims that she wouldn't

925
00:52:42,239 --> 00:52:44,840
Speaker 1: have done so had she known the product didn't contain

926
00:52:44,960 --> 00:52:48,520
Speaker 1: real potato skins. So why doesn't somebody just give her

927
00:52:48,520 --> 00:52:51,479
Speaker 1: two dollars. I know, the dude at the bodega should

928
00:52:51,480 --> 00:52:53,800
Speaker 1: have just given her refund. That's great, but you know what,

929
00:52:53,920 --> 00:52:56,440
Speaker 1: but good for her for calling them out like too

930
00:52:56,480 --> 00:53:00,320
Speaker 1: many people take liberties with the population companies take liberty.

931
00:53:00,400 --> 00:53:02,279
Speaker 1: Is good for her for saying this isn't right, that's

932
00:53:02,320 --> 00:53:04,000
Speaker 1: not true. I'm gonna go all the way. And I

933
00:53:04,440 --> 00:53:06,520
Speaker 1: really feel this in my heart though, because I did

934
00:53:06,600 --> 00:53:10,719
Speaker 1: the same ship like in college high as fuck, being like,

935
00:53:10,880 --> 00:53:13,759
Speaker 1: oh yeah, this just sounds good like potato skins, and

936
00:53:13,800 --> 00:53:16,040
Speaker 1: they're like, it's like it really is. Like how like

937
00:53:16,160 --> 00:53:18,880
Speaker 1: a Pringles chip is. It's not like a lazer. You

938
00:53:18,880 --> 00:53:21,000
Speaker 1: can kind of like, oh that's from potatoes. Oh you

939
00:53:21,120 --> 00:53:24,760
Speaker 1: compressed potato whatever, like they said, miss mashed potato flakes.

940
00:53:24,800 --> 00:53:28,719
Speaker 1: It's like a catfish by a chip. Yeah, you're not

941
00:53:28,760 --> 00:53:32,080
Speaker 1: a potato skin. So you know, do you solange? I mean,

942
00:53:32,160 --> 00:53:34,600
Speaker 1: do they have pictures of the actual T G I

943
00:53:34,680 --> 00:53:39,279
Speaker 1: Friday potato skins on the bag, because that that would

944
00:53:39,320 --> 00:53:42,560
Speaker 1: be a well, that would be completely off base. I

945
00:53:42,600 --> 00:53:44,200
Speaker 1: think that's where they're probably you know, they're doing that

946
00:53:44,280 --> 00:53:47,759
Speaker 1: little gray area walking the line collusion thing, just being

947
00:53:47,840 --> 00:53:50,680
Speaker 1: like we'll put potato skins on the text. But you

948
00:53:50,719 --> 00:53:53,680
Speaker 1: look at the chips. They're satisfied. They look satisfy. I mean,

949
00:53:53,719 --> 00:53:57,959
Speaker 1: they just look like they're like elongated potato chips. Yeah,

950
00:53:58,080 --> 00:54:00,239
Speaker 1: I mean, look, Tamra, chill, look at that. That's not

951
00:54:00,280 --> 00:54:02,960
Speaker 1: a potato skin. That's not a potato skin at all.

952
00:54:03,160 --> 00:54:07,320
Speaker 1: But the word it really evokes an experience. Yeah, you know,

953
00:54:07,920 --> 00:54:10,800
Speaker 1: it's like close your eyes and pretend to think about

954
00:54:10,840 --> 00:54:14,319
Speaker 1: our potato skins as you consume these subpar potato chick

955
00:54:14,360 --> 00:54:16,800
Speaker 1: and put this potato starch. That's like me call myself

956
00:54:16,920 --> 00:54:21,560
Speaker 1: Afro Tamar and the girls like you're bald Man. That's

957
00:54:21,600 --> 00:54:24,120
Speaker 1: just a name. It's a state of mind. It's a

958
00:54:24,120 --> 00:54:28,120
Speaker 1: state of mind. Alright, guys, let's talk about the Jordan's

959
00:54:28,160 --> 00:54:33,040
Speaker 1: peel controversy. It's over for him. It's over for him. Yeah,

960
00:54:33,280 --> 00:54:38,160
Speaker 1: I mean what I mean, Look, you do so you

961
00:54:38,560 --> 00:54:41,759
Speaker 1: put two movies out that fucking cement your place as

962
00:54:41,840 --> 00:54:44,680
Speaker 1: a powerhouse in Hollywood. And then he had to go.

963
00:54:45,200 --> 00:54:47,480
Speaker 1: I think he's talking to Ian Roberts or something at UCB.

964
00:54:47,600 --> 00:54:50,520
Speaker 1: There's this discussion and this is the quote that fired

965
00:54:50,600 --> 00:54:53,759
Speaker 1: up the culture war machine. He said, quote, I don't

966
00:54:53,800 --> 00:54:55,719
Speaker 1: see myself casting a white dude as the lead in

967
00:54:55,800 --> 00:54:58,120
Speaker 1: my movie. Not that I don't like white dudes, he said,

968
00:54:58,239 --> 00:55:01,560
Speaker 1: nodding over to his moderator, Pal Roberts. Uh, but I've

969
00:55:01,600 --> 00:55:04,359
Speaker 1: seen that movie already. Uh. And then then the crowd

970
00:55:04,520 --> 00:55:06,880
Speaker 1: erupted blah blah blah um. He said, it really is

971
00:55:06,960 --> 00:55:09,040
Speaker 1: one of the best greatest pieces of this story is

972
00:55:09,080 --> 00:55:13,080
Speaker 1: feeling like we are in this time. A renaissance has happened, improved,

973
00:55:13,320 --> 00:55:17,239
Speaker 1: the myths about representation in the industry are false, and

974
00:55:17,360 --> 00:55:20,239
Speaker 1: so people are like, but people just take weight. I

975
00:55:20,320 --> 00:55:24,319
Speaker 1: don't see myself casting so he's anti white and he's

976
00:55:24,480 --> 00:55:27,759
Speaker 1: just all okay, even though his mom's okay, we'll hold on.

977
00:55:28,200 --> 00:55:29,759
Speaker 1: We don't know for sure. I don't know what I

978
00:55:29,920 --> 00:55:35,400
Speaker 1: see as a black man say anything about white women.

979
00:55:35,600 --> 00:55:39,239
Speaker 1: He's just saying there are a white men in lead

980
00:55:39,360 --> 00:55:42,719
Speaker 1: and men as leading films are overrepresented. That is his

981
00:55:43,080 --> 00:55:46,800
Speaker 1: prerogative as a fucking director now, uh, and that he

982
00:55:46,840 --> 00:55:48,560
Speaker 1: can make the films that he wants. And I'm sorry

983
00:55:48,600 --> 00:55:52,359
Speaker 1: that he's taking representation seriously and saying, yeah, I want

984
00:55:52,400 --> 00:55:55,279
Speaker 1: something that is more indicative of the world I want

985
00:55:55,320 --> 00:55:57,759
Speaker 1: to see, or the world I see um and again

986
00:55:58,400 --> 00:56:00,200
Speaker 1: right as an artist, the people were like a again

987
00:56:00,280 --> 00:56:02,600
Speaker 1: you know, you know the comments were so predictable, like

988
00:56:02,760 --> 00:56:04,840
Speaker 1: what do you just guess just sort of based on

989
00:56:04,880 --> 00:56:07,560
Speaker 1: the logic the right uses when things like this come out.

990
00:56:07,880 --> 00:56:09,560
Speaker 1: And I'll tell you if it's an actual tweet, because

991
00:56:09,560 --> 00:56:13,040
Speaker 1: there if you imagine if Clint Eastwood said that he

992
00:56:13,120 --> 00:56:16,720
Speaker 1: would never cast a black guy. Literally, can you imagine

993
00:56:16,760 --> 00:56:19,480
Speaker 1: if Brad Pitt said he would never I don't I

994
00:56:19,520 --> 00:56:22,240
Speaker 1: don't even know why. This person doesn't know this person.

995
00:56:22,560 --> 00:56:27,320
Speaker 1: This person just has no couldn't even be the director,

996
00:56:29,840 --> 00:56:33,480
Speaker 1: the only other guy. And then someone goes, oh, well,

997
00:56:33,520 --> 00:56:37,319
Speaker 1: I guess his films aren't for me, then they won't.

998
00:56:37,360 --> 00:56:39,799
Speaker 1: He won't need another one of my daughters. That is fine.

999
00:56:39,880 --> 00:56:43,200
Speaker 1: You guys have been boycotting like woke movies that are

1000
00:56:43,440 --> 00:56:46,120
Speaker 1: care about representation for the past five years, and they've

1001
00:56:46,160 --> 00:56:50,440
Speaker 1: been the biggest fucking hits. The angry conservative outrage seal

1002
00:56:50,480 --> 00:56:55,560
Speaker 1: of approval is guaranteed success doing good things for these brands.

1003
00:56:55,600 --> 00:56:59,160
Speaker 1: But I honestly think like this is this is just

1004
00:56:59,280 --> 00:57:02,080
Speaker 1: one of those things, like it's going to look so weird.

1005
00:57:02,239 --> 00:57:05,080
Speaker 1: It already looks so weird to me when we were

1006
00:57:05,120 --> 00:57:07,360
Speaker 1: doing our live show where we did the Zeitgeist of

1007
00:57:08,280 --> 00:57:10,080
Speaker 1: and we looked back at the movies and it's just

1008
00:57:10,239 --> 00:57:12,680
Speaker 1: all white dudes in the lead roles, and it's like,

1009
00:57:12,920 --> 00:57:15,560
Speaker 1: what the like, that's weird, Like that doesn't make sense.

1010
00:57:15,680 --> 00:57:19,680
Speaker 1: That's not representative, Like it's a inefficiency when it comes

1011
00:57:19,760 --> 00:57:22,600
Speaker 1: to the business because you're only telling stories that are

1012
00:57:22,680 --> 00:57:26,120
Speaker 1: about a very specific like that, it just doesn't it's

1013
00:57:26,160 --> 00:57:29,680
Speaker 1: going to look weirder and weirder that nobody else was

1014
00:57:29,800 --> 00:57:34,320
Speaker 1: saying this before. And now, I mean while in black

1015
00:57:34,320 --> 00:57:38,120
Speaker 1: people have movies like The Wood or like Life like

1016
00:57:38,360 --> 00:57:41,920
Speaker 1: a movie the Best Man, I think we're and then

1017
00:57:42,000 --> 00:57:43,919
Speaker 1: make it real. No one's saying like make it fake,

1018
00:57:44,040 --> 00:57:47,000
Speaker 1: Like I don't like those commercials were uh, a black

1019
00:57:47,120 --> 00:57:48,640
Speaker 1: dude and an Asian dude and a white dude. Hey,

1020
00:57:48,680 --> 00:57:53,000
Speaker 1: I'm like that's doesn't happen in real life. Like maybe,

1021
00:57:55,080 --> 00:57:56,920
Speaker 1: but you know me, like make it what's wrong with

1022
00:57:57,000 --> 00:57:58,840
Speaker 1: making it feel more real? Make it more or it's

1023
00:57:58,880 --> 00:58:01,040
Speaker 1: just not that it's not real, right that you know,

1024
00:58:01,160 --> 00:58:03,160
Speaker 1: people of diverse background is going to hang out. But

1025
00:58:03,280 --> 00:58:05,959
Speaker 1: like there is a world where there are many people

1026
00:58:06,040 --> 00:58:09,960
Speaker 1: of a certain ethnicity whose friend group is homogeneous, like

1027
00:58:10,880 --> 00:58:13,600
Speaker 1: because that's just in the neighborhood you grew up, that happens.

1028
00:58:13,640 --> 00:58:16,000
Speaker 1: That happened. And clearly by looking at films with that

1029
00:58:16,080 --> 00:58:19,480
Speaker 1: are mostly white dominated gasts, that reality exists for those filmmakers.

1030
00:58:19,840 --> 00:58:22,040
Speaker 1: And I mean, we're better when we're mixed. That's why

1031
00:58:22,120 --> 00:58:25,040
Speaker 1: ports cities have always been so successful in history and

1032
00:58:25,520 --> 00:58:28,520
Speaker 1: created different kinds of revolutions, because when we mix ethnicities,

1033
00:58:28,560 --> 00:58:31,480
Speaker 1: we tell better stories. We we we make better products.

1034
00:58:31,560 --> 00:58:33,800
Speaker 1: It's it's like DNA and thoughts are the same. If

1035
00:58:33,840 --> 00:58:35,520
Speaker 1: he just make the same ones all the time, it

1036
00:58:35,840 --> 00:58:38,480
Speaker 1: doesn't come out as strong. Come up with pug ideas

1037
00:58:38,760 --> 00:58:45,200
Speaker 1: that yo, man, pugs are brilliant dogs. They can't breathe, man,

1038
00:58:45,360 --> 00:58:48,080
Speaker 1: they can't breathe. You think if you read a pugs brain,

1039
00:58:48,120 --> 00:58:50,440
Speaker 1: they would be like, yo, take me out, kill me.

1040
00:58:53,280 --> 00:58:56,560
Speaker 1: They create a dog dog translation just to hear that, like,

1041
00:58:56,640 --> 00:58:59,360
Speaker 1: oh my god, you just don't want to hear what

1042
00:59:00,640 --> 00:59:08,360
Speaker 1: thisating on my own nose. When they sneeze, it goes

1043
00:59:08,400 --> 00:59:12,960
Speaker 1: back inside their old mouth. The bulldogs too, like when

1044
00:59:13,000 --> 00:59:15,040
Speaker 1: you see bull man, I remember my shout out to

1045
00:59:15,200 --> 00:59:18,640
Speaker 1: my friends dog bulldog rufio r I p uh The

1046
00:59:18,800 --> 00:59:22,000
Speaker 1: breathing on that dog gave me anxiety where I could

1047
00:59:22,000 --> 00:59:24,120
Speaker 1: be like not high around the dog, Like can't listen

1048
00:59:24,120 --> 00:59:27,000
Speaker 1: to breathing right now. Their life expectancy is like so

1049
00:59:27,640 --> 00:59:31,320
Speaker 1: is it? Oh yeah, it's terrible man, because there's such

1050
00:59:31,400 --> 00:59:33,720
Speaker 1: cool dogs. All right, Well, you know mud gang, right,

1051
00:59:34,600 --> 00:59:37,400
Speaker 1: bring all the MutS out, that's right. Well, tamer has

1052
00:59:37,480 --> 00:59:39,960
Speaker 1: been a pleasure having. Thank you guys. It's always fun

1053
00:59:40,040 --> 00:59:42,520
Speaker 1: hanging out with you guys and getting educated and laughing.

1054
00:59:43,080 --> 00:59:46,560
Speaker 1: Where can people find you? Uh, tamer Kittan dot com

1055
00:59:46,720 --> 00:59:49,680
Speaker 1: is the best place for upcoming shows. I'm actually starting

1056
00:59:49,760 --> 00:59:52,320
Speaker 1: to feature for Ismo. He's a friend of mine, he's

1057
00:59:52,320 --> 00:59:55,480
Speaker 1: a comic. We're doing a mini tour together June six

1058
00:59:55,560 --> 00:59:58,920
Speaker 1: through nine at the Levity Live and Oxnard and otherwise

1059
00:59:59,120 --> 01:00:02,440
Speaker 1: at tamer cat on Instagram, at tamer Kittan everywhere everything

1060
01:00:02,520 --> 01:00:06,840
Speaker 1: else awesome. And is there a tweet you've been enjoying? Um? Yeah,

1061
01:00:06,920 --> 01:00:10,880
Speaker 1: there's one that I saw yesterday that said religion is

1062
01:00:11,000 --> 01:00:15,000
Speaker 1: like tide pods. It was invented to make us live

1063
01:00:15,080 --> 01:00:17,840
Speaker 1: less dirty, but then the dumbest people started swallowing it

1064
01:00:17,960 --> 01:00:22,320
Speaker 1: whole and then death started happening. Wow, that's really I

1065
01:00:22,440 --> 01:00:27,840
Speaker 1: like it was me, man, I have an only child.

1066
01:00:27,920 --> 01:00:32,360
Speaker 1: So I quoted my own tweeting, great tweet, thank you.

1067
01:00:32,720 --> 01:00:36,680
Speaker 1: I like how you kept that like under cover. I

1068
01:00:36,760 --> 01:00:39,520
Speaker 1: felt ashamed to quick it was good and who was that?

1069
01:00:39,680 --> 01:00:41,240
Speaker 1: And then you have to attribute it to someone else.

1070
01:00:41,280 --> 01:00:46,400
Speaker 1: You're like, um, not Tamar, And then you call them

1071
01:00:46,440 --> 01:00:48,600
Speaker 1: and you're like, yo, man, I want to buck you.

1072
01:00:50,240 --> 01:00:52,280
Speaker 1: I feel so guilty, Like if my own tweet, could

1073
01:00:52,320 --> 01:00:55,640
Speaker 1: you start start using this on stage? Uh, it's a

1074
01:00:55,760 --> 01:00:58,760
Speaker 1: great joke, but I just wrote for you. Uh no,

1075
01:00:58,960 --> 01:01:02,720
Speaker 1: that's good, own it man? And that on Also, I

1076
01:01:02,920 --> 01:01:05,120
Speaker 1: co host a podcast with my mom called they Tried

1077
01:01:05,160 --> 01:01:08,320
Speaker 1: to Bury Us and uh yeah, please follow and and

1078
01:01:08,560 --> 01:01:12,000
Speaker 1: it basically we interview a different uh immigrant every week.

1079
01:01:12,200 --> 01:01:15,440
Speaker 1: So they're all American origin stories and they're really positive

1080
01:01:15,480 --> 01:01:17,560
Speaker 1: and up and inspiring and it makes you remember why

1081
01:01:17,600 --> 01:01:20,640
Speaker 1: this country is so great. What's the full quote of

1082
01:01:20,720 --> 01:01:22,920
Speaker 1: they tried to bury us? The full quote is they

1083
01:01:23,000 --> 01:01:25,880
Speaker 1: tried to bury us. They didn't know we were sides, yeah,

1084
01:01:26,120 --> 01:01:28,440
Speaker 1: which I really really it's a something our our Mexican

1085
01:01:28,480 --> 01:01:30,040
Speaker 1: neighbor who told me when I came home with two

1086
01:01:30,080 --> 01:01:33,479
Speaker 1: black eyes one time, that two black guy, two black

1087
01:01:33,560 --> 01:01:38,520
Speaker 1: eyes to black. What happened someone that big? It's kind

1088
01:01:38,520 --> 01:01:40,360
Speaker 1: of a sad story. My dad. My dad was a

1089
01:01:40,440 --> 01:01:43,920
Speaker 1: boxer and uh, he had reflexes, you know, and so

1090
01:01:44,200 --> 01:01:45,480
Speaker 1: I scared him one time and he hit me in

1091
01:01:45,520 --> 01:01:48,000
Speaker 1: the face and I got a black eye. But both

1092
01:01:48,000 --> 01:01:50,320
Speaker 1: of my parents had to work, so I was embarrassed

1093
01:01:50,400 --> 01:01:52,400
Speaker 1: because my eye kept getting more black. So I went

1094
01:01:52,440 --> 01:01:54,360
Speaker 1: to my mom's bathroom and put makeup on my eye

1095
01:01:54,640 --> 01:01:56,800
Speaker 1: so there's foundation. And then when I got to school,

1096
01:01:56,800 --> 01:01:59,720
Speaker 1: I didn't do a good job. Sweated out. Yeah, these

1097
01:01:59,800 --> 01:02:02,000
Speaker 1: kids like he's wearing makeup? What a hubbo? And then

1098
01:02:02,040 --> 01:02:05,000
Speaker 1: they touched me and the other Oh, no, give you

1099
01:02:05,080 --> 01:02:07,120
Speaker 1: one to match that one. I went over with two

1100
01:02:07,160 --> 01:02:09,920
Speaker 1: black eyes. The next my Mexican neighbors like, hey man,

1101
01:02:09,960 --> 01:02:13,400
Speaker 1: what happened to damn? I told him the story, and

1102
01:02:13,480 --> 01:02:15,920
Speaker 1: he sat me down and started telling me. He's like,

1103
01:02:16,360 --> 01:02:18,000
Speaker 1: all the things that people make fun of you for,

1104
01:02:18,160 --> 01:02:20,520
Speaker 1: they're going to respect later and you have to remember

1105
01:02:20,600 --> 01:02:22,840
Speaker 1: this is making you stronger. And then he shared and

1106
01:02:22,880 --> 01:02:25,080
Speaker 1: then he pointed to this thing on his garage ball

1107
01:02:25,520 --> 01:02:27,120
Speaker 1: and said, they tried to bury us. They didn't know

1108
01:02:27,160 --> 01:02:32,840
Speaker 1: we were sides that why is neighbor he was definitely

1109
01:02:32,880 --> 01:02:34,520
Speaker 1: if that was in a movie, that would be like

1110
01:02:34,640 --> 01:02:41,120
Speaker 1: considered to like appropriating or like to uh stereotypical, like

1111
01:02:41,280 --> 01:02:49,479
Speaker 1: the y know, Tamer's character have to be white in them. Yeah,

1112
01:02:50,240 --> 01:03:01,400
Speaker 1: he's like, damn for what happened, Jared. Uh Miles, that

1113
01:03:01,480 --> 01:03:07,200
Speaker 1: almost sundated. He'son sorry, um damn fool um. So this

1114
01:03:07,360 --> 01:03:09,520
Speaker 1: next tweet, Uh, let's see. You can find me on

1115
01:03:09,560 --> 01:03:12,280
Speaker 1: Twitter and Instagram at Miles of Gray tweet I like

1116
01:03:12,480 --> 01:03:14,440
Speaker 1: a couple once from use of roach at use of

1117
01:03:14,520 --> 01:03:16,320
Speaker 1: roach is My favorite part of Los Angeles is seeing

1118
01:03:16,320 --> 01:03:20,560
Speaker 1: famous people drive regular ass cars. It's adorable because yeah, man,

1119
01:03:21,240 --> 01:03:22,760
Speaker 1: that's a that's a wave out here in l A.

1120
01:03:22,840 --> 01:03:25,520
Speaker 1: I always think I'm seeing famous people in regular cars,

1121
01:03:25,560 --> 01:03:28,000
Speaker 1: but then I like, look closer, it's not them. I mean,

1122
01:03:28,040 --> 01:03:30,439
Speaker 1: I don't want to blow someone spot up, but there's

1123
01:03:30,480 --> 01:03:32,480
Speaker 1: a very famous community who has been driving the same

1124
01:03:32,520 --> 01:03:35,000
Speaker 1: super roof fucking station wagon all over town. And you

1125
01:03:35,040 --> 01:03:38,240
Speaker 1: would never you'd be like, is that him? And Yeah,

1126
01:03:39,360 --> 01:03:41,040
Speaker 1: when I was a kid with shy he I think

1127
01:03:41,080 --> 01:03:43,920
Speaker 1: to this to this day for Bodego Boys fans out

1128
01:03:43,920 --> 01:03:46,800
Speaker 1: of here, he drives like a shitty pickup truck, A

1129
01:03:46,880 --> 01:03:49,200
Speaker 1: lot of people just do the hide and plain sight thing,

1130
01:03:49,400 --> 01:03:51,080
Speaker 1: you know what I mean? Like, No, that's cool. I

1131
01:03:51,200 --> 01:03:54,000
Speaker 1: like it. I respect it. Um and let me see.

1132
01:03:54,000 --> 01:03:57,160
Speaker 1: Another one I have is from Blair Saki. Blair Saki

1133
01:03:57,720 --> 01:04:00,200
Speaker 1: past guests. She says, the single most embarrassing moment of

1134
01:04:00,280 --> 01:04:02,040
Speaker 1: my life was when I was at a twelve step

1135
01:04:02,120 --> 01:04:05,360
Speaker 1: meeting and accidentally ended my share with banks. I've been Blair.

1136
01:04:10,040 --> 01:04:16,440
Speaker 1: That's amazing, so funny. Ufs also a former guest. Yes, yes, yes,

1137
01:04:16,560 --> 01:04:21,200
Speaker 1: yes yes. Uh. Some tweets I've been enjoying hoppers at

1138
01:04:21,320 --> 01:04:25,640
Speaker 1: Frog Avalanche tweeted me as Luke Skywalker puts one leg

1139
01:04:25,720 --> 01:04:28,800
Speaker 1: out of the tonton because it's too hot, which I

1140
01:04:28,960 --> 01:04:35,520
Speaker 1: just identified with as a sleeper. Uh, Maggie mull this

1141
01:04:35,720 --> 01:04:38,280
Speaker 1: is just a top notche dead joke. I refer to

1142
01:04:38,400 --> 01:04:41,400
Speaker 1: testicles as wankas because they're in between a willie and

1143
01:04:41,440 --> 01:04:46,800
Speaker 1: a chocolate factory. Uh. And then at Bird Butterer tweeted,

1144
01:04:47,560 --> 01:04:50,560
Speaker 1: give me the teat boys, I'm still a full. I

1145
01:04:50,720 --> 01:04:57,880
Speaker 1: want to drink milk from an areole. I can't you. Hey, yeah,

1146
01:04:58,200 --> 01:05:05,720
Speaker 1: angry wet fats country. That's country. So you can find

1147
01:05:05,760 --> 01:05:08,080
Speaker 1: me on Twitter at jack underscore, Oh Brian. You can

1148
01:05:08,120 --> 01:05:10,760
Speaker 1: find us on Twitter at Daily Zeitgeist. Were at the

1149
01:05:10,960 --> 01:05:13,080
Speaker 1: Daily z i Geist on Instagram. We have a Facebook

1150
01:05:13,120 --> 01:05:15,960
Speaker 1: pampage and a website Dailies that guys dot com by

1151
01:05:16,120 --> 01:05:19,400
Speaker 1: post our episodes in our pope to the information that

1152
01:05:19,440 --> 01:05:22,320
Speaker 1: we talked about today's episode as well as the song

1153
01:05:22,560 --> 01:05:25,680
Speaker 1: we right out on what second to be today? Actually,

1154
01:05:25,680 --> 01:05:27,440
Speaker 1: you know what, let's just go out on little nasax

1155
01:05:27,560 --> 01:05:30,560
Speaker 1: because just let go on your brain a little bit. Yeah,

1156
01:05:30,960 --> 01:05:32,840
Speaker 1: look and if that is fun, and look if that,

1157
01:05:33,040 --> 01:05:34,800
Speaker 1: if that infects your brain a little bit, maybe get

1158
01:05:34,800 --> 01:05:37,120
Speaker 1: into some country and if you were a person and

1159
01:05:37,200 --> 01:05:39,200
Speaker 1: you're like hip up, try out some hip hop. I'd

1160
01:05:39,240 --> 01:05:42,160
Speaker 1: like to try it all. Try it all, guys, do

1161
01:05:42,320 --> 01:05:45,720
Speaker 1: it all. All right, that's gonna do it for this week.

1162
01:05:45,960 --> 01:05:48,760
Speaker 1: We will be back on Monday. I have a great weekend.

1163
01:05:48,920 --> 01:05:59,560
Speaker 1: You guys pick right like, can't no more? I got

1164
01:05:59,640 --> 01:06:03,760
Speaker 1: the She's in the black horstock is attached and he's

1165
01:06:03,840 --> 01:06:07,480
Speaker 1: Maddy Black, Gotto Boost is black and mash rideing on

1166
01:06:07,600 --> 01:06:10,960
Speaker 1: the horse. You can't whip your horse. I've been in

1167
01:06:11,080 --> 01:06:13,840
Speaker 1: the valley. You ain't been about that forest. Now you

1168
01:06:13,960 --> 01:06:20,880
Speaker 1: can't Nobody fell me nothing you can't tell me. You

1169
01:06:21,000 --> 01:06:25,320
Speaker 1: can't nobody tell me nothing. You can't