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Speaker 1: Hello the Internet, and welcome to this episode of the

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Speaker 1: Weekly Zeitgeist. Uh. These are some of our favorite segments

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Speaker 1: from this week, all edited together into one uh NonStop

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Speaker 1: infotainment laugh stravaganza. Uh yeah, So, without further ado, here

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Speaker 1: is the Weekly Zeitgeist. Real guys, we got a lot

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Speaker 1: of news to cover. Amar Rossa back. Reality TV continues

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Speaker 1: to define the zeitgeist, you guys, whether it's Kim Kardashian

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Speaker 1: saying someone isn't interesting to look at, or you know,

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Speaker 1: the President being a reality TV star and turning the

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Speaker 1: presidency into a reality show. Uh, and now we have

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Speaker 1: you know, somebody worked for him in the White House

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Speaker 1: who is only known because of her work on a

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Speaker 1: reality show, not success, just being as Kim Kardashian pointed,

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Speaker 1: interesting to look at. That is the most important trait

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Speaker 1: you can have. Uh. And I'm Rosa is definitely interesting

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Speaker 1: to look at. She's back and she's messy. Yes, she's

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Speaker 1: got a book coming out. She does, so we know what.

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Speaker 1: The playbook is a stirrup as much ship as possible

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Speaker 1: to get people talking about you and the book out

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Speaker 1: of off top of the White House. Like everything, and

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Speaker 1: there's a lie, there's nothing true. It like they were

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Speaker 1: very very clear that everything in there just basically slanderous

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Speaker 1: or whatever. But you know, she kicked off her pressed

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Speaker 1: her pretty impressively by leaking two recorded conversations she had

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Speaker 1: during her time there, and it was like being so messy.

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Speaker 1: She's like they're like, oh, I'm Rosa, do you have

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Speaker 1: more recordings? And she just looks and goes, oh, yes,

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Speaker 1: I do. And it's really treat like really acting like

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Speaker 1: a villain from it, like I'm back, Well, I'm ready

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Speaker 1: to fuck things up. I think I remember her original

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Speaker 1: season on The Apprentice, and that was sort of what

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Speaker 1: she did. She was just like, oh, I'm going to

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Speaker 1: be a villain, Like she just got it immediately. Like,

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Speaker 1: but this is with the government now, you know, like

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Speaker 1: you're taking her out of this medium that ultimately does

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Speaker 1: doesn't matter. I don't think her and Trump know they're

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Speaker 1: in the government and they're defense. They don't know. It's

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Speaker 1: a new set that they're working on, right right, it's

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Speaker 1: on a different set. Where are the cameras and um?

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Speaker 1: But yeah, it's this is what happens when you put

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Speaker 1: people like this in actual decision making capacities that affects

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Speaker 1: other people's lives. So, yeah, the first one she talks about,

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Speaker 1: you know, she had a recording of when Chief of

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Speaker 1: Staff John Kelly fired her, and it's a pretty long

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Speaker 1: clip that they have or whatever. But the thing that's

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Speaker 1: interesting about this one, aside from him just hearing, he's

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Speaker 1: basically sort of like does like a that kind of

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Speaker 1: jeezer up sort of being like, look, let's make this

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Speaker 1: as nice as possible because we don't want to make

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Speaker 1: things difficult for you after this. Yeah, like okay, all right,

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Speaker 1: I'll be cool. But what this apparently happened in the

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Speaker 1: fucking situation room. So she recorded conversation in one of

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Speaker 1: the most sensitive areas of the West Wing where you know,

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Speaker 1: that's where like Obama watched the bin Laden hit job

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Speaker 1: basically led yeah, whatever if they got but yeah, like

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Speaker 1: a lot of shame there by accident. It just shows

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Speaker 1: you this room where so many important things have happened.

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Speaker 1: You just can wander in there with your phone or whatever,

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Speaker 1: just make her recording whatever. So we found out that

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Speaker 1: she got fired and it was whatever. Then the second

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Speaker 1: clip that she dropped, I think it was either yesterday today,

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Speaker 1: was a phone call with her and Trump where he

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Speaker 1: acts so zero mg surprised that she was fired. So

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Speaker 1: apparently she was fired and she and the things. She's like,

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Speaker 1: does the president know about this? And Janka is like, look,

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Speaker 1: this is in a negotiable situation like it just like

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Speaker 1: you know, tough guyser. So that's your shame if something

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Speaker 1: happened to your reputation. Yeah, essentially specifically he said that, yeah,

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Speaker 1: sparkling reputation. Yeah, like an actual reality star villain. Villain.

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Speaker 1: This is the recording that she made when she talks

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Speaker 1: with the President Trump right after being fired. Morossa, what's

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Speaker 1: going on on the news that you're thinking about leaving?

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Speaker 1: What happened General Kelly? General Kelly came to me and

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Speaker 1: said that you guys wanted me to leave. No. I

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Speaker 1: nobody even told me about it. You know, they run

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Speaker 1: a big operation, but I didn't know it. I didn't

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Speaker 1: know that. I don't love a god, damn it. I mean, okay,

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Speaker 1: So you can look at that called on. You can

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Speaker 1: look at that one of two ways. One is that

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Speaker 1: he actually knows nothing about what's going on in his

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Speaker 1: own administration and General Kelly just calls all the shots,

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Speaker 1: which is likely. The other is that he totally knew,

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Speaker 1: and just because he doesn't, he's not really confrontational and

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Speaker 1: he wants to be able to be the good guy,

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Speaker 1: acting like all surprised about it, like he didn't even know, Like,

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Speaker 1: oh really, the god damn it goes goddamn it. Oh yeah,

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Speaker 1: you're so upset. That was one of the worst performances

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Speaker 1: I've ever seen, Like just as a liar, but that

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Speaker 1: was just not good. And he is, if nothing else,

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Speaker 1: a well practiced liar when he lets out much better

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Speaker 1: lives than that. Yeah, I think they are like certain

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Speaker 1: lives he's comfortable with or has convinced himself are true,

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Speaker 1: and this just didn't happen to be one of those.

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Speaker 1: Like he was like, Okay, she's fired, Okay, let me

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Speaker 1: get on the phone with her, and what's going on?

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Speaker 1: What am I reading about? Oh my god, damn it.

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Speaker 1: And then as we were laughing, you can hear him

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Speaker 1: say I don't love you leaving at all. Uh, that's

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Speaker 1: such a weird way to describe that. Host. So you'll

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Speaker 1: hire me back again? Okay, I gotta I gotta go

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Speaker 1: and hold on my big Max here. Yeah, I don't know. Look,

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Speaker 1: this sort of underlines the whole problem with this administration too,

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Speaker 1: is because now she's out and she's talking all this

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Speaker 1: ship Trump is on Twitter coming at her intelligence. You know,

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Speaker 1: typical playbook when it comes to people of color who

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Speaker 1: are have any opinion on the presidents, question their intelligence.

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Speaker 1: But you know, after that, the media, you know, rightfully

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Speaker 1: noticed what has always been obviously, like wall, not a

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Speaker 1: lot of people of color that are working at the

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Speaker 1: highest level in that White House administration. So on the

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Speaker 1: Sunday shows, Kelly and Conway was out there and I

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Speaker 1: think she's on I forget which which of the Sunday shows,

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Speaker 1: basically being asked a question, hey, can you name some

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Speaker 1: people of color that work with the president, And it

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Speaker 1: was a little you know, she didn't have many ideas,

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Speaker 1: and um, the Amorosa was the most prominent high level

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Speaker 1: African Americans serving in the West Wing on President Trump's staff.

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Speaker 1: Who now is that person who is the most prominent

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Speaker 1: high level advisor to the president on the West wing

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Speaker 1: staff right now? African American? Yes, I would say that, Well,

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Speaker 1: first of all, you're you're totally uh not covering the

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Speaker 1: fact that our Secretary of Housing and Urban Development and

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Speaker 1: world renowned I'm asking you about the White House staff.

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Speaker 1: I'm asking what the people the president is with every day.

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Speaker 1: He's that he's well, the President works as Secretary of

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Speaker 1: Carson every day. He's trying to break the back up

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Speaker 1: the White House staff right now. And you we have

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Speaker 1: Geron who's done a fabulous job and very involved with

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Speaker 1: He's been very involved with Jared Kushner and President Trump

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Speaker 1: on prison reform at the beginning. He's been there from

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Speaker 1: the beginning. He worked with am Rossa and others of us.

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Speaker 1: Does he have an office in the West wing? Killing

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Speaker 1: has an office on the in the e o P. Absolutely,

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Speaker 1: the Executive Office of the President. Yes, but but but

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Speaker 1: not in the West Wing. What does that say that

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Speaker 1: have not a single senior advisor in the West Wing

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Speaker 1: who's African American. I didn't say that there wasn't, but

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Speaker 1: hold on with me. There there are plenty of people.

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Speaker 1: If you're if you're if you're going by that and

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Speaker 1: not by the actions of the President, which you probably should,

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Speaker 1: then then you should look at the fact that we

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Speaker 1: have a number of different minorities and the fact is

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Speaker 1: that this president is doing well for all Americans. Yeah, okay,

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Speaker 1: m M, I mean, just look at all the people

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Speaker 1: he appoints to like judicial nominations that I think he

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Speaker 1: has a thing for white guys. I think it's easy

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Speaker 1: to say. Yeah, at first I thought I thought she

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Speaker 1: was making up Geron I'll way, oh, hell no, you

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Speaker 1: just made up There's a named jarn Smith who works

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Speaker 1: with Jared Kushner like as a executive aid. But who

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Speaker 1: knows and what real capacity that actually is. But you know, again,

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Speaker 1: it's not surprising when you look at just you know again,

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Speaker 1: if you if she's saying, look at the actions of

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Speaker 1: the president, well then I think that would also be

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Speaker 1: clear to me. Don't look at the actions of our

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Speaker 1: most right. So did you see him? Well, he had

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Speaker 1: all those bikers at the White House this weekend, and

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Speaker 1: the one dude had a patch that said I like

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Speaker 1: guns and titties, just prominently on his best parents. He

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Speaker 1: is not necessarily in that order, yeah, but it was,

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Speaker 1: but in that order. He's like he's got his arm

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Speaker 1: around these bikers and the dude one of the dudes patches,

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Speaker 1: He's like like, uh not that his bass is all

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Speaker 1: Harley Davidson writers. But didn't he do something like over

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Speaker 1: the weekend where he's like split He actually started talking

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Speaker 1: trash on Harley Davidson, right, because they're going to take

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Speaker 1: some of their operations overseas because of EU terror and

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Speaker 1: now Harley david the drivers like, well, do I like

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Speaker 1: my bike more? Yeah? Racist for a boycott. I mean

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Speaker 1: Trump is only at most would be president for eight

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Speaker 1: years total. Those Harley's though, this whole trademark that sound. Yeah,

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Speaker 1: you know, if you take care of it and get

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Speaker 1: their oil changed, if you can do that with a motorcycle,

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Speaker 1: then they'll they'll hold up for years. I wonder how many.

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Speaker 1: I don't know what other bike would you ride? A

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Speaker 1: fucking Yamaha baby, that's too foreign? Yeah, that's too foreign,

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Speaker 1: like a Royal Enfield to English to European. I don't

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Speaker 1: know anyway. I don't know about motorcycles, that's all I

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Speaker 1: thought you would. Jack. You strike me as a big

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Speaker 1: hog guy with the wild handlebars like it's great airs

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Speaker 1: you out? Yeah, rad one to work every day. That's

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Speaker 1: actually a bird scooter whatever, Tomato Harley bird scooter. I

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Speaker 1: don't know about you, guys. I was refreshing my phone

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Speaker 1: pretty regularly yesterday waiting for, you know, all hell to

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Speaker 1: break loose on the Unite the right to rally in Washington,

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Speaker 1: d C. They decided to have it right across the

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Speaker 1: street from the White House. I don't know how they

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Speaker 1: figured they'd get away with that with this president of ours, who's,

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Speaker 1: as you can tell just looking at his behaviors and

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Speaker 1: his actions, if not his hiring practices, he's the least

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Speaker 1: racist person ever. But so, you know, the idea, I

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Speaker 1: think they had permitted for four hundred uh neo Nazis

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Speaker 1: and skinheads and white Nationals. No, no, not not officially,

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Speaker 1: We're not allowed with them. Right when you put the

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Speaker 1: speaker list too, they were new Nazis. Uh so they

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Speaker 1: were expecting four hundred uh and they drew was it for?

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Speaker 1: It was about two dozen people, maybe a little more

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Speaker 1: two hundred or two uh yeah, so it was between

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Speaker 1: two dozen and forty that they actually had come out

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Speaker 1: to you know, I think people last year after uh

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Speaker 1: you know, they all showed up in their white shirts

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Speaker 1: and uh no masks, which was really the most surprising

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Speaker 1: part of their decision. Their their decor at the Unite

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Speaker 1: the Right rally of the first one, they were just

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Speaker 1: like this is cool now right, everyone were all the right,

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Speaker 1: and then a bunch of them got fired on my

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Speaker 1: communities as being hateful racists and uh now that apparently

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Speaker 1: did people. People weren't fond of of how that went down,

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Speaker 1: that nobody showed up completely tanked. I mean not that

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Speaker 1: like there was any stock or social cachet with being

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Speaker 1: a white nationalist, but like people were definitely like, yo,

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Speaker 1: I can't be out here like that, Like I'm not

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Speaker 1: that down with it. I mean, because I think he

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Speaker 1: could only find about thirty people who are that ignorant

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Speaker 1: and shameless to go out and be like, yeah, we're

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Speaker 1: sucking here for the Unite the Right to uh the

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Speaker 1: counter esters. However, they came on the thousands, So you know,

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Speaker 1: it's very clear that I think, you know, one is

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Speaker 1: less meaningful, let's say, less sexy to the general public.

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Speaker 1: But I think Jason Kessler man, he's had a lot

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Speaker 1: of problems too, because the other thing that this whole

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Speaker 1: failure of the Unite the Right rally shows is there

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Speaker 1: there's a lot of fracturing going on in this whole

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Speaker 1: right community where like they don't know how who to follow,

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Speaker 1: who actually is the leader. Half of them are getting

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Speaker 1: scrubbed off of Twitter and things like that, so it's

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Speaker 1: become a very fractured, and Jason Kessler like he's burned

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Speaker 1: a lot of bridges in the neo Nazi community because

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Speaker 1: there are people like on a gap they're like, you know,

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Speaker 1: chat site that they can talk shit on. They're all

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Speaker 1: being like, no, this guy has no manpower. No one

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Speaker 1: follows him anymore, Like I advise you to not go.

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Speaker 1: It's gonna be dangerous. Uh. And you know, he's also

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Speaker 1: like he hasn't been able to fundraise, like on any

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Speaker 1: kind of website that makes it easier to collect funds

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Speaker 1: from people, so he's basically limited to like cash and

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Speaker 1: check donations, so he's has less and less organizing power.

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Speaker 1: And so it was kind of like on Right Wing Watch,

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Speaker 1: our boy Jared Holt was always saying, like, this is

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Speaker 1: probably gonna be a flop just from the onset, based

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Speaker 1: on how nobody's really like with each other on the

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Speaker 1: same side anymore compared to last year, because Keler is

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Speaker 1: the guy who organized the UH last Yearott. Yeah, I

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Speaker 1: mean that's the problem with your movement being fully obsessed

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Speaker 1: with categorizing people and hating them, Like you're going to

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Speaker 1: have some divisions that open up, and some of those

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Speaker 1: people aren't going to be fully on board with your

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Speaker 1: type of white nationalism. Um. Yeah, one one of the

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Speaker 1: white nationalists or neo Nazis was mad because Jason Kessler

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Speaker 1: had like a non white person working like at a

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Speaker 1: higher level with him, and he's like not to mention that,

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Speaker 1: like there's not even all white people in his organization. Yeah.

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Speaker 1: So something I didn't realize. Richard Spencer, who likes to

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Speaker 1: focus his brand of white nationalism and white supremacy on

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Speaker 1: claiming that it's like all about European culture and like

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Speaker 1: different people coming from European nations and having something special.

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Speaker 1: I didn't realize that over the past year he has

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Speaker 1: been banned from like most European countries. Yeah, he can't

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Speaker 1: get not allowed to go there. A lot of the

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Speaker 1: people can't. Yeah, people are kind of running away from

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Speaker 1: this movement. That's how fractured it is. By the way,

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Speaker 1: is that so few people want to join the movement

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Speaker 1: that they have to hire minority to fill these white positions. Right,

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Speaker 1: Like not even this job as a movie Black Klansman

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Speaker 1: shows right of that they just got it's you know.

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Speaker 1: The other aspect of this is, you know, last year

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Speaker 1: they had a lot of like paramilits. They militias like

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Speaker 1: pull up at the unite the right thing like oath

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Speaker 1: keepers and stuff like that to you know, protect them.

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Speaker 1: And you could see like that site was pretty out

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Speaker 1: there when you saw all these dudes in this tactical

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Speaker 1: gear and being like, yeah, we're aligned with this group.

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Speaker 1: But because of that fought out those militias that you

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Speaker 1: have even like pulled away from kind of being out

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Speaker 1: there because the optics like aren't really helping them. And

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Speaker 1: I was reading this piece, which which is kind of interesting,

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Speaker 1: is like how the militias have kind of lost their

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Speaker 1: way now that Trump is president because even with like

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Speaker 1: Bush two and Clinton and Obama, they were able to

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Speaker 1: like have this like it's this like neo globalist, you know,

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Speaker 1: conspiracy to bleed America dry and blah blah blah, and

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Speaker 1: like so we gotta be ready and like so when

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Speaker 1: Trump was running, they were all like, yeah, this is

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Speaker 1: our guy, this is our guy. And a lot of

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Speaker 1: analysts were like, if Hillary Clinton wins, I think we

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Speaker 1: need to really be prepared for what the fallout was

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Speaker 1: gonna look like with these militias and things like that.

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Speaker 1: But then he won, and now they're kind of like

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Speaker 1: have an identity crisis because they're like, wait, our guy

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Speaker 1: is in power, so what do we yet? Yeah, and

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Speaker 1: like and they were started tracking like first it was

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Speaker 1: anti fuck because then it was easy to be like,

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Speaker 1: oh yeah, okay, we're diametrically opposed. And then that kind

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Speaker 1: of fell off, so then it was immigrants, then Muslims,

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Speaker 1: and now the new thing is they're just obsessed with

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Speaker 1: the civil war, like that's the next thing that they've

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Speaker 1: given themselves, like, well, okay, we're gonna be ready for this,

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Speaker 1: like libs verse conservatives race war. Drudge was trying to

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Speaker 1: popularize the whole anti anti thing yesterday because like a

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Speaker 1: lot of the top headlines were like it's getting ugly

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Speaker 1: out there, and then it would be like a video

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Speaker 1: of Antifa like pushing a camera away or something like um,

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Speaker 1: and then a lot of places we're writing that ship up,

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Speaker 1: like in the coverage of this like of open white

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Speaker 1: supremacy in this country, they're getting mad at like Antifa

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Speaker 1: for clashing with like other Like when you saw, like

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Speaker 1: importantly a few weeks ago, the police definitely from what

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Speaker 1: I saw, like what the reporting was, they seemed to

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Speaker 1: be much more aggressive with like the counter protesters and

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Speaker 1: they were with like the white nationalists, and a lot

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Speaker 1: of the coverage is more focused on what they're doing,

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Speaker 1: rather than these white nationalists who are out here, you know,

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Speaker 1: spreading all this hatred. So the coverage of it was

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Speaker 1: a little odd to me too, from some place, not everybody,

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Speaker 1: but yeah, and I mean I think there's also a

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Speaker 1: sense in which they overplayed their hand a little bit.

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Speaker 1: Like I mean, there there are people who are invigorated

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Speaker 1: by Trump's you know, election and feeling like, okay, now

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Speaker 1: I can you know, let my racist inner thoughts and

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Speaker 1: feelings out into the open. And they did that last year,

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Speaker 1: and they sort of overplayed their hand, and you know

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Speaker 1: a lot of them got hired from their jobs, and uh,

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Speaker 1: you know there. I think there's also like when when

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Speaker 1: you watch that Vice documentary last year with that guy

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Speaker 1: was like we got all the guns and we got

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Speaker 1: all this and like, you know, just talking with his

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Speaker 1: chest out like he was about to go whoop some mess.

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Speaker 1: And I was very you know, angry and seemed sure

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Speaker 1: of himself. And then the next video we saw of him,

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Speaker 1: he was weeping and being like I'm so scared, Please

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Speaker 1: don't hurt me about the cops because he got in

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Speaker 1: trouble for being openly violent. I just feel like when

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Speaker 1: your movement is about violence and a very very limited worldview,

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Speaker 1: you're not going to have very stable leadership a lot

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Speaker 1: of the time. And there's another guy who was very

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Speaker 1: I forget where the article was, but it was a

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Speaker 1: guy who wrote for you know, a mainstream outlet who

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Speaker 1: used this right wing kind of mainstay as a source.

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Speaker 1: And over the past year that's sourced disappeared because he

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Speaker 1: actually stabbed his father to death. Like, was that the

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Speaker 1: guy in Oregon? Yeah? Or Washington, Washington Northwest? Right? Yeah.

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Speaker 1: So it's like, you know a lot of these people

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Speaker 1: who were big personalities and who were you know, out

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Speaker 1: there pushing this point of view, they don't last long

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Speaker 1: in the public eye for any number of reasons. When

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Speaker 1: it just shows you that they're rallying, Like the thing

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Speaker 1: that brings them together is literal hatred and violence. That's

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Speaker 1: not Most people are pretty chill, you know, they're not

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Speaker 1: wired like you know, you'll you'll have people who are

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Speaker 1: very angry, and you can get those people. But that's

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Speaker 1: but you look at the counter protesters, they are they

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Speaker 1: rally around the idea of of inclusion and unity and

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Speaker 1: like empathy. That's a that's a much more broader audience

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Speaker 1: for them then, like, hey man, you fucking hate immigrantsmen

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Speaker 1: and beat some people? Right? Oh no, Like really I'm

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Speaker 1: not that Like I'd rather just you know, shame some racists.

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Speaker 1: It's harder, it's harder to get behind that point of

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Speaker 1: view now more than ever, because you can't burn all

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Speaker 1: the books like in in you know, there's still the internet,

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Speaker 1: and like eventually, like the internet can be bad if

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Speaker 1: you just get in to like one small group where

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Speaker 1: everybody's talking crazy, but like eventually you can go out

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Speaker 1: and do your own research and uh doesn't look good.

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Speaker 1: Uh there. There's also Stephen Miller's uncle just published an

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Speaker 1: article where it's almost surprising how basic it was. He

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Speaker 1: was just like, hey, so our great grandfather came here

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Speaker 1: because of you know, there were anti Semitic programs and like,

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Speaker 1: uh he was trying to escape like just horrible treatment

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Speaker 1: in his home country, and he came through Ellis Island

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Speaker 1: and then he like worked and paid for his you know,

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Speaker 1: to pay your great grandfather to like come over and

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Speaker 1: it's basically chained migration. He's like, so, how are you

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Speaker 1: going to It's just like this ideology that these groups

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Speaker 1: and that like you're Stephen Miller's of the world kind

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Speaker 1: of a spouse is just like so transparently, just like

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Speaker 1: it doesn't hold up on scrutiny that I don't know,

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Speaker 1: it seems like every time they just get put down

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Speaker 1: or you know, every time someone points out the insanity

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Speaker 1: of their argument, it's like, yeah, that's pretty obvious, turns

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Speaker 1: out and that whole letter is it's like he's just

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Speaker 1: like I'm ashamed to him. He knows better, like he

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Speaker 1: and like the thing that was really to that point

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Speaker 1: is like he points out that Stephen Miller is well

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Speaker 1: aware of their family's history, like coming from like a

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Speaker 1: stettle in what is now Belarus like to coming here

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Speaker 1: and the articles almost like, my man, how the funk

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Speaker 1: are you even thinking like this knowing our family's history

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Speaker 1: like that, this is this exact kind of policy that

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Speaker 1: could have gotten you know, our ancestors killed and we

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Speaker 1: wouldn't even be here. You wouldn't even be at Santa

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Speaker 1: Monica High School being like I think the janitors need

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Speaker 1: to speak English. Anybody with me? Uh, And that's why

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Speaker 1: I'm running for student president, which is like one of

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Speaker 1: his speeches that he made. She's a legendary YouTube clip

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Speaker 1: him in high school. Yeah, I mean the cowardice of

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Speaker 1: like getting over the wall from like a danger and

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Speaker 1: like pulling the ladder up behind you is Yeah, it's

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Speaker 1: just obvious. It's like, yeah, man, that's not a good look. Um.

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Speaker 1: And I don't think they ever cared that it would

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Speaker 1: be a good look, you know, or even thought that.

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Speaker 1: Like that's like the most infuriating part of all of this.

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Speaker 1: It's like, yeah, he doesn't care, like he knows that

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Speaker 1: his family comes from a long line of immigrants. He

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Speaker 1: doesn't care, like he pulled the rope back, you know

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Speaker 1: what I mean. Like this is just what's going to

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Speaker 1: keep happening. And when he gets called like oh yeah,

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Speaker 1: by the way, what you do is illogical, it's like, yeah,

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Speaker 1: obviously it's illogical. None of it is logical. Hate is

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Speaker 1: not logical. It's just all self serving things. And I

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Speaker 1: don't think this will like, oh, Stephen Miller is not

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Speaker 1: a great guy. Holy shit, right, thank you uncle Miller. Um. Yeah,

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Speaker 1: I think most people who come to America, like you know,

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Speaker 1: when you ask all these people, I think pretty much

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Speaker 1: everyone has a backstory about oh yeah, they came here

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Speaker 1: for a better opportunity at some point, even if you're

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Speaker 1: one of these daughters of the Revolution type people like,

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Speaker 1: there are people still coming here because they're like, oh

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Speaker 1: I'm not feeling this place. I'm coming here and this

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Speaker 1: will this will offer me the opportunity. But it's easy

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Speaker 1: to forget that. I think the only person who came

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Speaker 1: to America and just to not escape anything bad was

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Speaker 1: Prince Akim in coming to America because he was just

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Speaker 1: looking for Shorty. Right, thank you king shit, yes, fuck

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Speaker 1: you too. All Right, we're gonna take a quick break.

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Speaker 1: We'll be right back, and we're back. All right, guys,

426
00:22:44,160 --> 00:22:46,040
Speaker 1: let's get into the stories of the day. The man

427
00:22:46,040 --> 00:22:49,080
Speaker 1: of defense has rested. They have dropped the mic. They

428
00:22:49,080 --> 00:22:53,040
Speaker 1: were like done and done. I think we've made our point.

429
00:22:53,080 --> 00:22:55,680
Speaker 1: I think it goes like this. The prosecution rest then

430
00:22:55,720 --> 00:22:58,240
Speaker 1: the is like, okay, now what will the defense be

431
00:22:58,320 --> 00:23:04,960
Speaker 1: presenting in case we're good? Yeah, so there's two weeks

432
00:23:04,960 --> 00:23:08,560
Speaker 1: of prosecution calling witnesses who testified that man of Fort

433
00:23:08,840 --> 00:23:12,960
Speaker 1: did like all the money crimes basically and did them

434
00:23:12,960 --> 00:23:17,359
Speaker 1: like flamboyantly, like he thought people couldn't see him like

435
00:23:17,440 --> 00:23:20,080
Speaker 1: he was invisible. And there were a couple of weird

436
00:23:20,160 --> 00:23:24,080
Speaker 1: like courtroom shenanigans that we don't totally understand just yet.

437
00:23:24,160 --> 00:23:26,880
Speaker 1: Like there was a recess that was like a full

438
00:23:26,960 --> 00:23:30,200
Speaker 1: day recess that nobody really knows why it happened, a

439
00:23:30,200 --> 00:23:33,000
Speaker 1: lot of behind closed doors meetings with the judge and

440
00:23:33,240 --> 00:23:36,959
Speaker 1: defense and prosecution, and then the defense requested that the

441
00:23:36,960 --> 00:23:40,440
Speaker 1: case be dismissed and the judge was like no, but

442
00:23:40,480 --> 00:23:42,680
Speaker 1: like there's a reason the defense thought that they could

443
00:23:42,680 --> 00:23:46,679
Speaker 1: get away with that. Uh. And then apparently that was

444
00:23:47,000 --> 00:23:49,360
Speaker 1: their whole idea because then they were like, Okay, now

445
00:23:49,760 --> 00:23:54,240
Speaker 1: present your first witness, and they were like we rest, yeah,

446
00:23:54,680 --> 00:23:57,359
Speaker 1: you'd present your first witness. I don't know what's gonna

447
00:23:57,359 --> 00:24:00,040
Speaker 1: happen if that means, like, you know, a lot of

448
00:24:00,119 --> 00:24:03,600
Speaker 1: the speculation has been some kind of issue with the jury,

449
00:24:03,840 --> 00:24:07,560
Speaker 1: whether it was a juror overhearing something or speaking to someone,

450
00:24:07,840 --> 00:24:11,000
Speaker 1: or if there is a you know, a huge Donald

451
00:24:11,000 --> 00:24:13,920
Speaker 1: Trump's a border who's just willing to stay locked in

452
00:24:13,960 --> 00:24:16,600
Speaker 1: their position and have a hung jury. I don't know, Like,

453
00:24:16,640 --> 00:24:19,600
Speaker 1: if it's a juror who overheard any of the news

454
00:24:19,680 --> 00:24:22,760
Speaker 1: for the past two years, maybe he's anti maniport. I

455
00:24:22,800 --> 00:24:27,560
Speaker 1: don't know. Uh, it seems crazy that we have to

456
00:24:27,880 --> 00:24:32,439
Speaker 1: have a trial where people would be completely impartial. But um,

457
00:24:32,480 --> 00:24:37,119
Speaker 1: because of you know, this touch is literally every aspect

458
00:24:37,200 --> 00:24:40,600
Speaker 1: of of our country. H Robert, you just did a

459
00:24:40,640 --> 00:24:43,960
Speaker 1: Maniford episode a two podcast Behind the Bastards. You did

460
00:24:44,080 --> 00:24:47,480
Speaker 1: to Maniford episodes. Uh so, first of all, explain to

461
00:24:47,520 --> 00:24:49,600
Speaker 1: our listeners what Behind the Bastards is. For people who

462
00:24:49,600 --> 00:24:51,680
Speaker 1: don't listen, I mean, our tagline is we we tell

463
00:24:51,720 --> 00:24:53,639
Speaker 1: you everything you don't know about the very worst people

464
00:24:53,640 --> 00:24:56,080
Speaker 1: in all of history. And and Paul Manaford is definitely

465
00:24:56,080 --> 00:24:58,040
Speaker 1: one of those. What I say in the podcast, and

466
00:24:58,040 --> 00:24:59,720
Speaker 1: what I truly believe is that his work for Donald

467
00:24:59,760 --> 00:25:02,360
Speaker 1: Trump is probably the least objectionable thing he's ever done.

468
00:25:03,600 --> 00:25:06,760
Speaker 1: That his whole career was built on. He he's the

469
00:25:06,760 --> 00:25:09,640
Speaker 1: guy who helped invent the modern concept of lobbying. There

470
00:25:09,640 --> 00:25:11,560
Speaker 1: were I think a couple of hundred lobbyists in the

471
00:25:11,720 --> 00:25:14,240
Speaker 1: entire United States when Paul Manafort started his firm, and

472
00:25:14,280 --> 00:25:16,399
Speaker 1: he is like, you know, in the late nineties, he

473
00:25:16,400 --> 00:25:19,119
Speaker 1: started getting jokes on like the Simpsons about how you know,

474
00:25:19,160 --> 00:25:22,200
Speaker 1: all politicians are the same. Let Democrat and Republican. They're

475
00:25:22,240 --> 00:25:25,240
Speaker 1: they're the same person, they support the same ideologies. A

476
00:25:25,280 --> 00:25:26,840
Speaker 1: lot of that is due to the fact that the

477
00:25:26,880 --> 00:25:29,720
Speaker 1: lobbying firm that Manafort started with Roger Stone and a

478
00:25:29,760 --> 00:25:34,399
Speaker 1: guy whose last name was Black, would regularly represent both

479
00:25:34,440 --> 00:25:37,760
Speaker 1: sides of elections because they're a big part of their

480
00:25:37,760 --> 00:25:39,800
Speaker 1: goal was they would help They were the first company

481
00:25:39,840 --> 00:25:43,679
Speaker 1: to put lobbying under and like campaign advice and whatnot

482
00:25:43,680 --> 00:25:46,320
Speaker 1: campaign management under the same roof, so they would help

483
00:25:46,440 --> 00:25:49,359
Speaker 1: both sides of an election in a contested district, and

484
00:25:49,400 --> 00:25:52,159
Speaker 1: the no matter who won, they could then lobby to

485
00:25:52,280 --> 00:25:56,560
Speaker 1: that person with whatever corporations were backing them. Um so

486
00:25:56,720 --> 00:26:01,399
Speaker 1: there at least partially responsible for everything bad that people

487
00:26:01,400 --> 00:26:04,439
Speaker 1: hate about politics right now. Yeah, within a decade of

488
00:26:04,480 --> 00:26:07,159
Speaker 1: the establishment of Paul Manafort's firm, they went from a

489
00:26:07,200 --> 00:26:09,200
Speaker 1: situation where there were maybe a couple of hundred lobbyists

490
00:26:09,200 --> 00:26:10,959
Speaker 1: in the entire country to a situation where there were

491
00:26:10,960 --> 00:26:13,240
Speaker 1: more than ten thousand lobbyists. They have a lot to

492
00:26:13,240 --> 00:26:17,399
Speaker 1: do with that, and Paul Manafort quickly stopped working in

493
00:26:17,440 --> 00:26:19,600
Speaker 1: the US as much and started working for a variety

494
00:26:19,600 --> 00:26:22,520
Speaker 1: of dictators and terrorists all over the world. UM and

495
00:26:22,560 --> 00:26:25,159
Speaker 1: that's who he spent most of his career representing the

496
00:26:25,280 --> 00:26:27,439
Speaker 1: name of the lobby that he invented was called the

497
00:26:27,440 --> 00:26:31,320
Speaker 1: Torturer's Lobby. Like that, he's that kind of guy. Now, oh, yeah,

498
00:26:31,359 --> 00:26:33,760
Speaker 1: you did a human rights violations. Well, we're gonna rehab

499
00:26:33,800 --> 00:26:35,960
Speaker 1: your imagine. You're gonna put a suit on and we'll

500
00:26:36,000 --> 00:26:37,680
Speaker 1: present you to people in d C. And they'll think

501
00:26:37,720 --> 00:26:42,720
Speaker 1: you're a legit person. Um. Now, your show's also great

502
00:26:42,880 --> 00:26:46,520
Speaker 1: for you know, giving us weird personal details like that

503
00:26:46,600 --> 00:26:50,520
Speaker 1: Hitler was a fanboy of Westerns and that totally informed

504
00:26:50,640 --> 00:26:54,440
Speaker 1: his like military decisions, and that Saddam was a romance novelist.

505
00:26:54,480 --> 00:26:57,840
Speaker 1: Is there like a surprising personal detail about Manafort that

506
00:26:58,560 --> 00:27:02,639
Speaker 1: you particularly liked? Uh? When he started working with Ukraine's

507
00:27:02,720 --> 00:27:06,200
Speaker 1: want to be dictator, Victor Ynukovich, Yanukovich had just lost

508
00:27:06,280 --> 00:27:08,359
Speaker 1: an election for president. It was Manafort who helped and

509
00:27:08,400 --> 00:27:10,840
Speaker 1: get elected a few years later, and his advice to

510
00:27:11,040 --> 00:27:14,359
Speaker 1: Yanukovich was to basically dress an act exactly like Paul Manafort.

511
00:27:14,640 --> 00:27:17,680
Speaker 1: They got identical suits tailored together. He made Ynukovich start

512
00:27:17,720 --> 00:27:19,639
Speaker 1: doing his hair the same way Manafort did. Like that

513
00:27:19,720 --> 00:27:22,000
Speaker 1: was that we helped this guy into power. Was like

514
00:27:22,200 --> 00:27:26,400
Speaker 1: be like me, dress exactly like me, victor you don't

515
00:27:26,400 --> 00:27:28,760
Speaker 1: have my swage right, that's what will put you in

516
00:27:28,840 --> 00:27:33,040
Speaker 1: It apparently worked right for a while. It's like twins

517
00:27:34,320 --> 00:27:38,600
Speaker 1: def Con. The top Hacker conference took place over the

518
00:27:38,600 --> 00:27:44,000
Speaker 1: weekend in Vegas, UH, and they demonstrated what they're capable

519
00:27:44,080 --> 00:27:46,920
Speaker 1: of in terms of hacking. There are a few highlights

520
00:27:47,480 --> 00:27:50,119
Speaker 1: that will point out that there was first a group

521
00:27:50,240 --> 00:27:53,320
Speaker 1: that hacked an Amazon Echo UH and they were basically

522
00:27:53,400 --> 00:27:56,359
Speaker 1: they strung together like multiple bugs and like a second

523
00:27:56,400 --> 00:27:59,760
Speaker 1: gen echo that could basically allow hagard a stream audio

524
00:27:59,800 --> 00:28:02,560
Speaker 1: from a microphone remotely, so just kind of listening on you.

525
00:28:02,600 --> 00:28:04,920
Speaker 1: But a lot of the you know this can The

526
00:28:04,960 --> 00:28:07,320
Speaker 1: deaf Con two is also meant for hackers to point

527
00:28:07,320 --> 00:28:10,360
Speaker 1: out these vulnerabilities and then help these companies be like, hey,

528
00:28:10,480 --> 00:28:12,960
Speaker 1: you need to sort this out. So the group of

529
00:28:13,000 --> 00:28:17,199
Speaker 1: who had found this vulnerability, they've already told Amazon about it,

530
00:28:17,240 --> 00:28:19,480
Speaker 1: so you don't have to full on worry about this

531
00:28:19,560 --> 00:28:21,880
Speaker 1: and start putting your echo inside of like a sound

532
00:28:21,920 --> 00:28:25,080
Speaker 1: proof box or anything like that. It also requires pretty

533
00:28:25,119 --> 00:28:29,199
Speaker 1: sophisticated access to like your WiFi network. UH. So I

534
00:28:29,240 --> 00:28:31,639
Speaker 1: think you'll be all right, but it was just interesting

535
00:28:31,720 --> 00:28:33,560
Speaker 1: enough to know, Yeah, the thing that you thought can

536
00:28:33,600 --> 00:28:37,920
Speaker 1: happen can happen without them addressing that. And then last

537
00:28:38,000 --> 00:28:41,040
Speaker 1: year that the deaf Con conference got a huge press

538
00:28:41,120 --> 00:28:43,440
Speaker 1: buzz because they did a lot of work with voting

539
00:28:43,480 --> 00:28:45,960
Speaker 1: machines uh, and they showed how you could just hop

540
00:28:45,960 --> 00:28:48,200
Speaker 1: in that thing and just mess with the vote tylers

541
00:28:48,280 --> 00:28:50,760
Speaker 1: or whatever. And this year, thank god, they must have

542
00:28:50,800 --> 00:28:54,200
Speaker 1: fixed that. They did. They did, They totally worked that out.

543
00:28:54,240 --> 00:28:57,960
Speaker 1: But except this year they supped the anti and again

544
00:28:58,000 --> 00:28:59,640
Speaker 1: it was no different. They took a lot of the

545
00:28:59,680 --> 00:29:02,000
Speaker 1: machine is that a lot of states use when they're

546
00:29:02,080 --> 00:29:04,880
Speaker 1: using electronic voting. Uh. They were able to upload their

547
00:29:04,880 --> 00:29:08,200
Speaker 1: own malicious software. They could change vote talies and one

548
00:29:08,240 --> 00:29:11,280
Speaker 1: of them even just pulled like the hot fire. What's

549
00:29:11,360 --> 00:29:13,120
Speaker 1: that that one gift with the duode just going with

550
00:29:13,160 --> 00:29:15,360
Speaker 1: his hands on his cheeks like this, he had that

551
00:29:15,400 --> 00:29:17,600
Speaker 1: gift just play on the screen, because you can do anything.

552
00:29:17,880 --> 00:29:21,040
Speaker 1: But the real fun part about this one is they

553
00:29:21,080 --> 00:29:24,280
Speaker 1: also had forty children between the ages of six and

554
00:29:24,400 --> 00:29:29,719
Speaker 1: seventeen attempt to infiltrate replicas of these election board websites

555
00:29:30,000 --> 00:29:33,080
Speaker 1: for several swing swing states. And so what they did

556
00:29:33,080 --> 00:29:35,400
Speaker 1: was just built out like the exact architecture of these

557
00:29:35,400 --> 00:29:37,600
Speaker 1: websites and just said, have added kids. If you know,

558
00:29:37,680 --> 00:29:43,080
Speaker 1: like young aspiring hackers, do your worst. Uh. And let's

559
00:29:43,120 --> 00:29:47,680
Speaker 1: just say the kids are all right at hacking, because

560
00:29:47,760 --> 00:29:50,200
Speaker 1: we are fucked. They were able to some of these

561
00:29:50,280 --> 00:29:53,360
Speaker 1: kids were able to exploit vulnerabilities that they were able

562
00:29:53,400 --> 00:29:57,680
Speaker 1: to tamper with vote tabulations, change the names of candidates. Uh.

563
00:29:57,720 --> 00:30:00,480
Speaker 1: And one eleven year old reportedly hacked to a mock

564
00:30:00,600 --> 00:30:03,560
Speaker 1: up of the Florida's Secretary of State's website and change

565
00:30:03,600 --> 00:30:08,200
Speaker 1: the voting results within ten minutes. But election officials were like, hey, hey,

566
00:30:08,240 --> 00:30:11,080
Speaker 1: I'm not really impressed by that. Most elections are done

567
00:30:11,080 --> 00:30:13,760
Speaker 1: in what four or five minutes? Yeah, exactly. And they're like,

568
00:30:13,800 --> 00:30:16,240
Speaker 1: you know, the environment is completely different, Yeah, because of

569
00:30:16,480 --> 00:30:19,400
Speaker 1: a noisy conference hall is much different than the empty

570
00:30:19,400 --> 00:30:24,120
Speaker 1: gymnasiums being overseen by octogenarians asking you when where do

571
00:30:24,160 --> 00:30:29,040
Speaker 1: you live? Yeah. So, you know, again, if the kids

572
00:30:29,040 --> 00:30:31,960
Speaker 1: are if it's that easy for you know, younger people

573
00:30:32,040 --> 00:30:34,080
Speaker 1: with just sort of the basic skills to do it,

574
00:30:34,360 --> 00:30:37,040
Speaker 1: I think maybe we should be looking into this a

575
00:30:37,080 --> 00:30:39,680
Speaker 1: little bit more rather than you know, passing the blame

576
00:30:39,680 --> 00:30:41,280
Speaker 1: and be like, oh, well, this is this, you know,

577
00:30:41,320 --> 00:30:43,400
Speaker 1: I'm not I'm not worried. We're not really impressed by this.

578
00:30:43,600 --> 00:30:46,400
Speaker 1: It's scary because the details of this, like they in

579
00:30:46,520 --> 00:30:49,400
Speaker 1: some of the hecks they change the candidates names and

580
00:30:49,440 --> 00:30:51,520
Speaker 1: like the things they changed it to are like Bob

581
00:30:51,640 --> 00:30:54,800
Speaker 1: the Builder and Richard Nixon's head. So it's like a

582
00:30:54,880 --> 00:30:58,840
Speaker 1: mixture of like juvenile sensibilities and right, they're like, so

583
00:30:59,200 --> 00:31:02,600
Speaker 1: in the future, wrong are able to just yeah, destroy

584
00:31:02,720 --> 00:31:04,600
Speaker 1: this thing. I follow a lot of these people on Twitter,

585
00:31:04,640 --> 00:31:06,160
Speaker 1: a lot of folks who are at Defcon, a lot

586
00:31:06,160 --> 00:31:08,000
Speaker 1: of hackers, because I don't understand that at all. So

587
00:31:08,040 --> 00:31:09,360
Speaker 1: I just try to listen to what the people who

588
00:31:09,400 --> 00:31:11,160
Speaker 1: do say. And there was a big thread of people

589
00:31:11,200 --> 00:31:13,760
Speaker 1: who do security for these things and who actually have

590
00:31:13,840 --> 00:31:16,240
Speaker 1: been part of coding voting machines for like Dibald and stuff,

591
00:31:16,280 --> 00:31:19,040
Speaker 1: saying this is the only field of coders you will

592
00:31:19,040 --> 00:31:21,480
Speaker 1: find this for. None of us think electronic voting is

593
00:31:21,520 --> 00:31:24,440
Speaker 1: a good idea. None of the people responsible for securing

594
00:31:24,480 --> 00:31:26,880
Speaker 1: electronic voting machines think that it's a good idea to

595
00:31:26,960 --> 00:31:30,320
Speaker 1: vote electronically, because they're just not secure and you can't

596
00:31:30,320 --> 00:31:34,000
Speaker 1: really point to hard evidence like a paper receipt or something,

597
00:31:34,120 --> 00:31:35,640
Speaker 1: or like you know how we have in California, like

598
00:31:35,720 --> 00:31:40,440
Speaker 1: the ink the inked up voting card we get. So yeah,

599
00:31:41,160 --> 00:31:46,400
Speaker 1: they also hacked police body cameras, voicemail. The Internet of

600
00:31:46,440 --> 00:31:49,400
Speaker 1: Things is horrifically secure. The body camera was wild because

601
00:31:49,440 --> 00:31:52,360
Speaker 1: they're you know, people, hackers were able to remotely download

602
00:31:52,400 --> 00:31:54,640
Speaker 1: the footage, edit it, and then re upload it. And

603
00:31:54,680 --> 00:31:57,120
Speaker 1: they weren't like it was untraceable, like you wouldn't have

604
00:31:57,160 --> 00:31:59,840
Speaker 1: known that someone had just switched out of video filing there.

605
00:32:00,480 --> 00:32:05,280
Speaker 1: So that's cool. Hey, that's pretty cool. Hey, so what

606
00:32:05,320 --> 00:32:07,720
Speaker 1: else they know? They're able to live stream footage, so

607
00:32:07,760 --> 00:32:10,480
Speaker 1: they're saying, you know, criminals could just basically tap into

608
00:32:10,480 --> 00:32:12,719
Speaker 1: a feed and be like, okay, that's where you are. Okay,

609
00:32:12,760 --> 00:32:15,160
Speaker 1: that's pretty cool. It's one of those things. It's it's

610
00:32:15,160 --> 00:32:17,760
Speaker 1: weird because like in the nineties, um, it's it's sort

611
00:32:17,760 --> 00:32:19,440
Speaker 1: of similar to what happened with gaming in the nineties,

612
00:32:19,440 --> 00:32:21,520
Speaker 1: where there were all these pundits like screaming about how

613
00:32:21,600 --> 00:32:24,240
Speaker 1: dangerous video games were and it was bullshit. And so

614
00:32:24,320 --> 00:32:26,240
Speaker 1: now when people try to point to like, no, there's

615
00:32:26,280 --> 00:32:28,360
Speaker 1: actually some some things we need to be concerned about

616
00:32:28,400 --> 00:32:31,240
Speaker 1: psychologically of what like violent video games due to people.

617
00:32:31,640 --> 00:32:34,000
Speaker 1: That doesn't get any traction because we were so used

618
00:32:34,040 --> 00:32:37,000
Speaker 1: to like being bullshit, it being bullshit. It's the same

619
00:32:37,000 --> 00:32:38,920
Speaker 1: thing with hackers. Were so used to movies in nine

620
00:32:39,680 --> 00:32:42,040
Speaker 1: where people were hacking cars and stuff, and it was like,

621
00:32:42,320 --> 00:32:45,040
Speaker 1: that's not possible, but now it is. But now we

622
00:32:45,120 --> 00:32:49,800
Speaker 1: have autonomous cars, they can be hacked, remotely started, remotely stopped,

623
00:32:50,200 --> 00:32:53,720
Speaker 1: whatever you mean. So are like our reflex to reject

624
00:32:53,800 --> 00:32:56,480
Speaker 1: that as a possibility is out of sync with the

625
00:32:56,520 --> 00:33:00,320
Speaker 1: reality of the voicemail one was really interesting thing though,

626
00:33:00,360 --> 00:33:03,520
Speaker 1: because I never thought of how that works. But so

627
00:33:03,560 --> 00:33:04,959
Speaker 1: what they were saying is like, you know, a lot

628
00:33:05,000 --> 00:33:08,160
Speaker 1: of our mobile carriers they were just terrible at securing

629
00:33:08,240 --> 00:33:11,760
Speaker 1: voicemail because we're still using like four digit pins. Most

630
00:33:11,800 --> 00:33:13,800
Speaker 1: people don't even know what their pin is because you

631
00:33:13,840 --> 00:33:15,920
Speaker 1: can just dial it straight from your phone now and

632
00:33:15,960 --> 00:33:19,479
Speaker 1: it's usually just the last four it'll default to being

633
00:33:19,520 --> 00:33:22,880
Speaker 1: the last four digits of your phone number. Uh So yeah,

634
00:33:23,080 --> 00:33:25,360
Speaker 1: So then basically what hackers can do they can just

635
00:33:25,400 --> 00:33:28,720
Speaker 1: brute force access your ship. Because there's also no limit

636
00:33:28,800 --> 00:33:31,400
Speaker 1: of the number of like incorrect passwords you enter. It

637
00:33:31,560 --> 00:33:34,240
Speaker 1: just locks it down so you can just have at it. Uh.

638
00:33:34,240 --> 00:33:36,480
Speaker 1: And then once they do that, they can get into

639
00:33:36,520 --> 00:33:40,120
Speaker 1: your voicemail system. They can request like like WhatsApps, send

640
00:33:40,520 --> 00:33:43,320
Speaker 1: like you know, the targets code via a phone call,

641
00:33:43,560 --> 00:33:45,480
Speaker 1: and if they don't pick it up and goes to voicemail,

642
00:33:45,520 --> 00:33:47,680
Speaker 1: then they can access the voicemail, get the code and

643
00:33:47,720 --> 00:33:50,600
Speaker 1: then put your ship like you know, log into your PayPal, eBay,

644
00:33:50,640 --> 00:33:53,640
Speaker 1: other ship just by using this like voicemail hack. So

645
00:33:54,120 --> 00:33:58,320
Speaker 1: that's another cool, pretty cool thing that's going well. Fortunately

646
00:33:58,440 --> 00:34:01,400
Speaker 1: we have our top lines at the top of the

647
00:34:01,480 --> 00:34:07,080
Speaker 1: government just sort of locking everything down as they actually

648
00:34:07,160 --> 00:34:09,959
Speaker 1: just pull a bunch of funding from from that. Yes,

649
00:34:11,600 --> 00:34:14,640
Speaker 1: you guys, crazy rich Asians. I think opened last night

650
00:34:14,920 --> 00:34:17,960
Speaker 1: and you know is opening over the course of this

651
00:34:18,040 --> 00:34:24,320
Speaker 1: coming weekend. It's getting really solid reviews. Um, I'm excited.

652
00:34:24,360 --> 00:34:27,439
Speaker 1: Constance was the lead. I feel like her performance as

653
00:34:27,480 --> 00:34:31,400
Speaker 1: the mom on Fresh off the Boat is uh. I

654
00:34:31,400 --> 00:34:33,399
Speaker 1: don't know, it reminds me of like what a lot

655
00:34:33,480 --> 00:34:36,560
Speaker 1: of Asian Americans I know say they love and respect

656
00:34:36,560 --> 00:34:40,560
Speaker 1: about their own moms. She's like unapologetic and strong and

657
00:34:40,880 --> 00:34:42,520
Speaker 1: I don't know, I read one person talk about the

658
00:34:42,560 --> 00:34:46,280
Speaker 1: moment and the crazy Rich Asians trailer where she laughs

659
00:34:46,320 --> 00:34:48,760
Speaker 1: and she like laughs hard and loud and like doesn't

660
00:34:48,800 --> 00:34:51,560
Speaker 1: cover her mouth, and they were like that act is

661
00:34:51,840 --> 00:34:55,120
Speaker 1: not normal for an Asian character in a you know,

662
00:34:55,200 --> 00:34:59,840
Speaker 1: Western movie. I've seen it tonight. Yeah, we'll see what

663
00:35:00,040 --> 00:35:03,400
Speaker 1: still last night? How was it? It was fine? Yeah,

664
00:35:03,520 --> 00:35:05,799
Speaker 1: that's what I'm That's what I'm thinking too. I think

665
00:35:05,920 --> 00:35:09,440
Speaker 1: it's more about the representation than the film itself. But

666
00:35:10,200 --> 00:35:14,360
Speaker 1: it was m yeah, yeah, I mean like something about

667
00:35:14,400 --> 00:35:17,680
Speaker 1: like where I am in my media consumption. But I'm

668
00:35:17,719 --> 00:35:19,839
Speaker 1: just like, oh, this is nice that like now we're

669
00:35:19,880 --> 00:35:23,480
Speaker 1: doing like a rom com with a majority Asian casts

670
00:35:23,480 --> 00:35:27,440
Speaker 1: are like entirely Asian casts. Um, but it's like it

671
00:35:27,560 --> 00:35:30,279
Speaker 1: still felt like weird. I don't know how to explain it. Like,

672
00:35:30,360 --> 00:35:32,080
Speaker 1: so I went with my brother, my younger brother. I

673
00:35:32,080 --> 00:35:33,600
Speaker 1: have two younger I went with one of them and

674
00:35:33,600 --> 00:35:36,440
Speaker 1: with my partner, and my youngest brother was like, man,

675
00:35:36,480 --> 00:35:39,080
Speaker 1: I've never seen so like such white Asian people before

676
00:35:39,080 --> 00:35:42,000
Speaker 1: in my life. Like they're all Asian, but like because

677
00:35:42,040 --> 00:35:43,880
Speaker 1: in the film a lot of them had gone to

678
00:35:43,960 --> 00:35:47,120
Speaker 1: like prep school in the UK theoretically, so they all

679
00:35:47,160 --> 00:35:50,560
Speaker 1: have English accents. Besides the Constance Wu and her mom character,

680
00:35:51,320 --> 00:35:55,200
Speaker 1: so they're all like these colonized Asians speaking like the

681
00:35:55,280 --> 00:35:58,920
Speaker 1: Queen's English, um. And I mean it was fun and all,

682
00:35:58,920 --> 00:36:02,000
Speaker 1: but because I had read so many like hype tweets beforehand,

683
00:36:02,360 --> 00:36:05,040
Speaker 1: where Asians were like dying over it, there, like I

684
00:36:05,120 --> 00:36:07,960
Speaker 1: cried like five minutes in and I couldn't stop crying,

685
00:36:07,960 --> 00:36:11,879
Speaker 1: and I was like really, I mean like I'm yes,

686
00:36:12,000 --> 00:36:14,279
Speaker 1: and I was super cry and I just wasn't like

687
00:36:14,480 --> 00:36:15,920
Speaker 1: feeling in on that level. I don't know if it's

688
00:36:15,920 --> 00:36:18,560
Speaker 1: because I went in with some other feelings, but I

689
00:36:18,640 --> 00:36:22,040
Speaker 1: definitely understand representation matters because that's like a first step

690
00:36:22,040 --> 00:36:25,920
Speaker 1: towards you know, wider acceptance except etcetera or whatever. And

691
00:36:25,960 --> 00:36:27,520
Speaker 1: I'm not trying to say that this movie needs to

692
00:36:27,520 --> 00:36:29,000
Speaker 1: do a lot of work because it's just this one movie.

693
00:36:29,040 --> 00:36:30,920
Speaker 1: And I think the problem is that, like there hasn't

694
00:36:30,920 --> 00:36:32,600
Speaker 1: been movies like this, but in a way, there have

695
00:36:32,719 --> 00:36:35,680
Speaker 1: been movies like this, right, like the The Namesake, which

696
00:36:35,680 --> 00:36:38,520
Speaker 1: is about a South Indian family or South Asian families

697
00:36:38,520 --> 00:36:40,960
Speaker 1: who were Indian um. And then there was like Better

698
00:36:41,000 --> 00:36:43,400
Speaker 1: Like Tomorrow, which is about bunch of like suburban like

699
00:36:43,480 --> 00:36:46,319
Speaker 1: mostly male East Asian kids, but like there have been

700
00:36:46,320 --> 00:36:49,160
Speaker 1: movies where they were like a majority Asian casts. But

701
00:36:49,360 --> 00:36:52,000
Speaker 1: there's something about this movie and how like it's like

702
00:36:52,080 --> 00:36:55,719
Speaker 1: so capitalistic, and how it's being upheld in this very

703
00:36:55,719 --> 00:36:57,960
Speaker 1: specific way that like kind of fun that I just

704
00:36:58,000 --> 00:37:00,799
Speaker 1: don't I don't know, I'm not I'm not vibing with it,

705
00:37:01,040 --> 00:37:04,480
Speaker 1: and I feel bad. Yeah, well, no, that's how I was,

706
00:37:04,800 --> 00:37:06,200
Speaker 1: you know, because I feel like a lot of people

707
00:37:06,600 --> 00:37:09,799
Speaker 1: from Singapore were definitely vibing because they're like a lot

708
00:37:09,800 --> 00:37:12,160
Speaker 1: of the cultural touch points were very relevant to people

709
00:37:12,160 --> 00:37:15,480
Speaker 1: in Singapore. And I think I'm excited that we're looking

710
00:37:15,480 --> 00:37:17,640
Speaker 1: at a film like this that's got an Asian cast

711
00:37:17,719 --> 00:37:19,680
Speaker 1: and we're moving in that direction. But yeah, I think

712
00:37:19,880 --> 00:37:21,680
Speaker 1: it has to be a first step to then begin

713
00:37:21,719 --> 00:37:25,759
Speaker 1: telling I think spreading the diversity of stories out a

714
00:37:25,840 --> 00:37:27,880
Speaker 1: bit too from here. I think the first one, uh,

715
00:37:28,480 --> 00:37:30,040
Speaker 1: it shouldn't be too bad, but we'll see. I'm gonna

716
00:37:30,040 --> 00:37:32,759
Speaker 1: see it tonight. I didn't grow up crazy rich, so

717
00:37:33,200 --> 00:37:35,879
Speaker 1: I hope from that standpoint it's not too abstract. But

718
00:37:36,000 --> 00:37:38,040
Speaker 1: I think at the very least, it's nice to see

719
00:37:38,200 --> 00:37:41,480
Speaker 1: familiar faces on the screen kids Before that, I hope feeling.

720
00:37:41,680 --> 00:37:43,359
Speaker 1: I was just like, man, of all the feelings that

721
00:37:43,400 --> 00:37:45,279
Speaker 1: I've been feeling after watching that, I just feel so

722
00:37:45,400 --> 00:37:50,319
Speaker 1: fucking poor my overwhelming feeling. I'm like, I feel so poor,

723
00:37:50,360 --> 00:37:52,879
Speaker 1: and I feel like I don't have a strong jawline,

724
00:37:53,040 --> 00:37:55,200
Speaker 1: Like my face isn't right because like the Asians and

725
00:37:55,200 --> 00:37:58,080
Speaker 1: this one also look a very specific way, like the men,

726
00:37:58,160 --> 00:38:00,800
Speaker 1: oh my god, Like people are all like women, especially

727
00:38:00,800 --> 00:38:03,000
Speaker 1: movies are like man, the female gaze in this film

728
00:38:03,080 --> 00:38:05,719
Speaker 1: is like so extraordinary. But I'm like, so what, it's

729
00:38:05,760 --> 00:38:10,120
Speaker 1: just like some packs, Like I don't six packs. You know,

730
00:38:10,800 --> 00:38:12,960
Speaker 1: I get it, But it's also like, well, what is this?

731
00:38:13,560 --> 00:38:16,359
Speaker 1: Why are we so into things that we criticize when

732
00:38:16,360 --> 00:38:18,440
Speaker 1: it's like white folks, you know what I'm saying, But

733
00:38:18,520 --> 00:38:21,960
Speaker 1: then like when it's just because it's like being embodied

734
00:38:21,960 --> 00:38:24,480
Speaker 1: by Asian folks and we're like all for it. I mean,

735
00:38:24,640 --> 00:38:26,640
Speaker 1: I want this movie to do well. I wanted to

736
00:38:26,680 --> 00:38:28,719
Speaker 1: like funk up the box office. I heard that it's

737
00:38:28,760 --> 00:38:30,879
Speaker 1: like it's gonna do great, and I wanted to do well.

738
00:38:31,200 --> 00:38:34,759
Speaker 1: But I'm just kind of underwhelmed. I mean it, by

739
00:38:34,840 --> 00:38:38,080
Speaker 1: its nature, the whole accomplishment here is that it is

740
00:38:38,440 --> 00:38:40,960
Speaker 1: a mainstream movie that is going to get wide release,

741
00:38:41,120 --> 00:38:47,120
Speaker 1: and inherently mainstream movies have certain things, certain things that

742
00:38:47,160 --> 00:38:50,120
Speaker 1: go along with them, like that every character is good

743
00:38:50,120 --> 00:38:55,040
Speaker 1: looking and usually like wealthy and uh yeah, like better

744
00:38:55,120 --> 00:38:57,080
Speaker 1: Like Tomorrow is a really good movie. But you know,

745
00:38:57,239 --> 00:39:00,279
Speaker 1: I don't know too many people who saw it, but

746
00:39:00,440 --> 00:39:02,520
Speaker 1: the director of that has gone on to have like

747
00:39:02,600 --> 00:39:05,120
Speaker 1: a huge, amazing career. Well, you're gonna love my film

748
00:39:05,120 --> 00:39:09,640
Speaker 1: that's coming out called Ugly Broke Biracial People. It's gonna

749
00:39:09,640 --> 00:39:13,399
Speaker 1: it's it's gonna resonate with people. Alright, guys, let's talk

750
00:39:13,400 --> 00:39:16,240
Speaker 1: Elon Musk. So a New York Times article came out

751
00:39:16,560 --> 00:39:21,280
Speaker 1: last night. Uh it was an interview with him where he,

752
00:39:22,120 --> 00:39:24,160
Speaker 1: you know, just seems like he's at the end of

753
00:39:24,200 --> 00:39:27,880
Speaker 1: his wits. Uh. He is feeling sorry for himself that

754
00:39:27,960 --> 00:39:29,960
Speaker 1: he didn't get to hang out with his friends on

755
00:39:30,000 --> 00:39:35,160
Speaker 1: his forty seventh birthday, which who still celebrates then thirthday?

756
00:39:35,160 --> 00:39:37,680
Speaker 1: But he's he's like, you know, I just spent it

757
00:39:37,840 --> 00:39:40,719
Speaker 1: in the in the lab, like working, I didn't get

758
00:39:40,719 --> 00:39:42,720
Speaker 1: to see anyone, and then like has to stop himself

759
00:39:42,760 --> 00:39:45,600
Speaker 1: because he's about to break down crying. But a live

760
00:39:45,640 --> 00:39:50,600
Speaker 1: interview Yeah, well, you don't see it. It's like a description, right,

761
00:39:50,680 --> 00:39:54,920
Speaker 1: it's a piece of journalism, written journalism. But you know,

762
00:39:55,120 --> 00:39:57,360
Speaker 1: he just really seems like he's at the end of

763
00:39:57,400 --> 00:40:02,080
Speaker 1: his wits. His lifestyle. I'll by his account, it's like

764
00:40:02,120 --> 00:40:04,359
Speaker 1: all about the job, and it's just like he's been

765
00:40:04,400 --> 00:40:09,400
Speaker 1: working a d twenty hour weeks. And that might be true.

766
00:40:09,480 --> 00:40:13,480
Speaker 1: I mean, he definitely presumably works a lot, but it's

767
00:40:13,520 --> 00:40:17,560
Speaker 1: all like his account is also woven throughout The New

768
00:40:17,600 --> 00:40:21,000
Speaker 1: York Times talking about the fact that the board at

769
00:40:21,480 --> 00:40:25,920
Speaker 1: Tesla is investigating whether he's like tweeting and altered states

770
00:40:25,960 --> 00:40:29,720
Speaker 1: of consciousness. Uh. They mentioned the drug ambien and also

771
00:40:29,800 --> 00:40:33,680
Speaker 1: the fact that he has been known to use recreational drugs.

772
00:40:33,800 --> 00:40:37,760
Speaker 1: And so there was a thing that happened like last weekend,

773
00:40:37,920 --> 00:40:42,920
Speaker 1: I think where this week fast and he's been doing

774
00:40:42,960 --> 00:40:45,000
Speaker 1: a lot of the last teams like when he's cooled.

775
00:40:45,000 --> 00:40:47,640
Speaker 1: That guy a pedophile, right, he called a guy pedophile.

776
00:40:47,719 --> 00:40:50,200
Speaker 1: They mentioned that They mentioned the fact that he tweeted

777
00:40:50,239 --> 00:40:53,440
Speaker 1: without consulting with his board, that he's thinking about taking

778
00:40:53,480 --> 00:40:56,880
Speaker 1: Tesla private and had secured the funds for it, which

779
00:40:57,200 --> 00:40:59,880
Speaker 1: shifted the market. Right. I think the sec will probably

780
00:41:00,080 --> 00:41:02,000
Speaker 1: want to say something about that, and which he hadn't,

781
00:41:02,000 --> 00:41:05,320
Speaker 1: so it was like an illegal tweet. But Azelia Banks,

782
00:41:05,840 --> 00:41:08,560
Speaker 1: she's a rapper for people who don't know, and she

783
00:41:08,880 --> 00:41:11,040
Speaker 1: has been working on her second album for a long time,

784
00:41:11,160 --> 00:41:15,359
Speaker 1: and she's working with Grimes, Elon Musk's girlfriend, and she

785
00:41:16,120 --> 00:41:20,640
Speaker 1: was tweeting or posting on Instagram that she had been

786
00:41:20,680 --> 00:41:24,280
Speaker 1: basically holed up in Elon Musk's house for like days,

787
00:41:24,960 --> 00:41:28,160
Speaker 1: and she was like, yeah, I'm waiting for Grimes. She

788
00:41:28,239 --> 00:41:30,799
Speaker 1: invited me out here to La to stay at Elon

789
00:41:30,840 --> 00:41:33,880
Speaker 1: Mu's place to put the finishing touches on our album,

790
00:41:34,160 --> 00:41:37,480
Speaker 1: and she just like never showed up. And here's what

791
00:41:37,560 --> 00:41:40,080
Speaker 1: she tweeted. She wrote that staying at his house was

792
00:41:40,160 --> 00:41:43,520
Speaker 1: like a real life episode of get Out and she said, well,

793
00:41:43,640 --> 00:41:46,840
Speaker 1: I waited around all weekend while Grimes coddled her boyfriend

794
00:41:46,880 --> 00:41:50,000
Speaker 1: for being too stupid to know not to go on Twitter.

795
00:41:50,080 --> 00:41:52,480
Speaker 1: Well on acid. Then she had the nerve to go

796
00:41:52,520 --> 00:41:55,239
Speaker 1: ghost and booked me a first class flight through Rocket Nation,

797
00:41:55,560 --> 00:41:58,480
Speaker 1: so basically sent her out of l A. So that

798
00:41:58,719 --> 00:42:01,680
Speaker 1: it's an interesting This wouldn't happen if he had a

799
00:42:01,719 --> 00:42:04,439
Speaker 1: woman in his own age. This is a problem this

800
00:42:04,480 --> 00:42:07,040
Speaker 1: is you know, a woman own age. If I if

801
00:42:07,040 --> 00:42:08,799
Speaker 1: he had a grown woman, she'd take his phone and

802
00:42:08,800 --> 00:42:11,040
Speaker 1: be like, leave twitter alone. This isn't for you. We're

803
00:42:11,080 --> 00:42:13,799
Speaker 1: too old for this. And you're on acid, and you're

804
00:42:13,800 --> 00:42:15,759
Speaker 1: on acid and you need to chill and take a nap,

805
00:42:15,760 --> 00:42:17,640
Speaker 1: and she put into bed. But this is a problem

806
00:42:17,640 --> 00:42:19,239
Speaker 1: with these older men that like, I don't know what's

807
00:42:19,280 --> 00:42:21,600
Speaker 1: going on. I've lost group of reality. Like, yeah, you're

808
00:42:21,640 --> 00:42:24,759
Speaker 1: forty seven and you're with someone half your age and

809
00:42:24,840 --> 00:42:27,799
Speaker 1: she's young, and she's just excited, Like get a real

810
00:42:27,880 --> 00:42:30,839
Speaker 1: one and chill. He had a real one. He had

811
00:42:30,880 --> 00:42:34,319
Speaker 1: a wife who was I think around his age and

812
00:42:34,520 --> 00:42:38,880
Speaker 1: who he has children with, who wrote an article about

813
00:42:38,920 --> 00:42:42,319
Speaker 1: how he treated her like a You don't say a

814
00:42:42,360 --> 00:42:46,759
Speaker 1: guy from an African mining family with treating people like property.

815
00:42:47,120 --> 00:42:50,799
Speaker 1: He said on multiple occasions that if she were an employee,

816
00:42:50,840 --> 00:42:53,880
Speaker 1: he would fire her throughout the course of their marriage.

817
00:42:54,280 --> 00:42:58,520
Speaker 1: Who hasn't said that to their part? Anyways, I'm gonna

818
00:42:58,520 --> 00:43:04,080
Speaker 1: call hr your mother, She'll sort this out. You come

819
00:43:04,120 --> 00:43:07,120
Speaker 1: get your son. He's talking crazy again, Okay, put him

820
00:43:07,160 --> 00:43:10,759
Speaker 1: on the phone. He's dead. But young women will put

821
00:43:10,800 --> 00:43:13,000
Speaker 1: up with that ship. The old guys they know, they

822
00:43:13,040 --> 00:43:15,399
Speaker 1: know that there's only so much. Yeah, because if you're

823
00:43:15,440 --> 00:43:17,440
Speaker 1: not at a at a certain level of maturity, you're

824
00:43:17,480 --> 00:43:19,839
Speaker 1: gonna sort of match the partner or something. So if

825
00:43:19,840 --> 00:43:22,480
Speaker 1: it's someone young, rambunctious and just being like, yeah, let's

826
00:43:22,880 --> 00:43:25,160
Speaker 1: let's fry up, let's fry up, to think about what

827
00:43:25,160 --> 00:43:26,759
Speaker 1: you part with in your twenty Like if I was

828
00:43:26,760 --> 00:43:28,759
Speaker 1: twenty and a guy was just like okay, I'd be

829
00:43:28,800 --> 00:43:31,719
Speaker 1: like great, And now I'm like, no, you gotta be this,

830
00:43:31,760 --> 00:43:33,920
Speaker 1: you gotta do this, have your ship together, Like your

831
00:43:33,960 --> 00:43:38,759
Speaker 1: list of demands is more our expectations are I'm right

832
00:43:38,760 --> 00:43:40,359
Speaker 1: a least. So it's good. Then you meet someone else

833
00:43:40,520 --> 00:43:43,719
Speaker 1: and you match each other's expectations. But it's like, yeah,

834
00:43:43,760 --> 00:43:46,440
Speaker 1: we're going to take a quick break and we'll be

835
00:43:46,560 --> 00:43:59,120
Speaker 1: right back, and we're back. Speaking of surprises. The Meg

836
00:43:59,520 --> 00:44:02,040
Speaker 1: So I follow The Meg exactly. I mean, I know

837
00:44:02,040 --> 00:44:05,680
Speaker 1: it's a movie. What what is about. It's about a

838
00:44:05,680 --> 00:44:09,520
Speaker 1: an extinct species of shark that was like basically a

839
00:44:09,719 --> 00:44:14,320
Speaker 1: giant great white, except more deadly and like more angry

840
00:44:14,400 --> 00:44:18,239
Speaker 1: and better at killing. It's called the Megalodon is the

841
00:44:18,400 --> 00:44:21,759
Speaker 1: full name for it. Uh, And if you were obsessed

842
00:44:21,800 --> 00:44:23,960
Speaker 1: with sharks like I was when I was a kid.

843
00:44:24,680 --> 00:44:28,640
Speaker 1: It's like, you know, just this mythical creature that's like

844
00:44:29,000 --> 00:44:32,000
Speaker 1: in terms of scale, it's like to a great white shark.

845
00:44:32,080 --> 00:44:37,279
Speaker 1: With a great white shark is to a salmon. Yes, yeah, yeah, exactly. Wait,

846
00:44:37,320 --> 00:44:39,480
Speaker 1: this already happened that there was like Mega Shark Verse,

847
00:44:39,560 --> 00:44:43,160
Speaker 1: Giant Octopus. There's been a lot of movies Mega Shark Verse, Crocosaurus.

848
00:44:43,560 --> 00:44:47,160
Speaker 1: I'm trying to like puzzle through this because so I

849
00:44:47,200 --> 00:44:50,480
Speaker 1: I pay attention to the box office. They're usually like

850
00:44:50,880 --> 00:44:53,720
Speaker 1: on Friday, they will put out their box office prediction,

851
00:44:53,840 --> 00:44:57,120
Speaker 1: like these box office analysts, and they'll usually be between

852
00:44:57,160 --> 00:45:00,319
Speaker 1: like five and ten percent. Like sometimes they're just like

853
00:45:00,440 --> 00:45:03,520
Speaker 1: right on point, being able to predict exactly what something's

854
00:45:03,560 --> 00:45:06,719
Speaker 1: gonna make. The Meg came out this weekend. It doubled

855
00:45:06,920 --> 00:45:11,000
Speaker 1: what box Office Mojo was predicting. It pulled in a

856
00:45:11,080 --> 00:45:15,280
Speaker 1: hundred and forty six point nine million dollars globally. Nobody

857
00:45:15,440 --> 00:45:21,560
Speaker 1: really oh yeah, oh yeah, it destroyed Solo. It's uh,

858
00:45:21,880 --> 00:45:26,160
Speaker 1: it might be more than Solos made Disney. Yeah, But

859
00:45:26,480 --> 00:45:29,520
Speaker 1: so I'm trying to figure out, like what about this

860
00:45:29,640 --> 00:45:33,200
Speaker 1: connected so much with people? I'm thinking there's something about

861
00:45:33,719 --> 00:45:36,319
Speaker 1: so there's been shark movies since Jaws. There was Deep

862
00:45:36,320 --> 00:45:40,680
Speaker 1: Blue cy Uh, there are shittier shark movies like, uh,

863
00:45:41,320 --> 00:45:44,840
Speaker 1: you know, Sharknado and stuff like that. But I wonder

864
00:45:44,880 --> 00:45:48,719
Speaker 1: if there's something to it being a singular like there's

865
00:45:48,719 --> 00:45:52,319
Speaker 1: been sharks movies like where they're multiple sharks, but not

866
00:45:52,520 --> 00:45:55,799
Speaker 1: a like singular shark movie. And I think there's like

867
00:45:55,880 --> 00:46:00,400
Speaker 1: something about one giant man eating shark that makes I

868
00:46:00,440 --> 00:46:02,279
Speaker 1: don't know, that appeals to us a little bit more.

869
00:46:02,400 --> 00:46:03,839
Speaker 1: I also, I mean, Jack, you and I have been

870
00:46:03,880 --> 00:46:05,839
Speaker 1: making content for people on the Internet for a very

871
00:46:05,880 --> 00:46:08,279
Speaker 1: long time, and we've noticed that it's definitely cyclical what

872
00:46:08,320 --> 00:46:10,640
Speaker 1: people are interested in. When we were both at Cracked

873
00:46:10,640 --> 00:46:12,319
Speaker 1: in the early years have Cracked, some of our most

874
00:46:12,360 --> 00:46:16,120
Speaker 1: successful articles were lists of weird prehistoric animals and monsters

875
00:46:16,120 --> 00:46:18,399
Speaker 1: and in stars that were scary, and then for years

876
00:46:18,400 --> 00:46:20,360
Speaker 1: you couldn't get people to read that stuff. And maybe

877
00:46:20,360 --> 00:46:22,640
Speaker 1: it's just that that ship swung back around and people

878
00:46:22,640 --> 00:46:25,960
Speaker 1: are interested again. Yeah, I mean, I yeah, they're that.

879
00:46:26,080 --> 00:46:29,480
Speaker 1: I think that's definitely true. I think people have always

880
00:46:29,520 --> 00:46:32,680
Speaker 1: been interested in big prehistoric creatures. I think what happened

881
00:46:32,680 --> 00:46:36,840
Speaker 1: at Cracked was that we created a type of article

882
00:46:37,120 --> 00:46:39,640
Speaker 1: that we were the only ones doing it, and then

883
00:46:39,880 --> 00:46:43,240
Speaker 1: BuzzFeed and a bunch of other websites like basically saw

884
00:46:43,280 --> 00:46:46,520
Speaker 1: that those articles were popular, and yeah, the list of

885
00:46:47,120 --> 00:46:49,759
Speaker 1: well and they like flooded the internet with articles that

886
00:46:49,840 --> 00:46:53,320
Speaker 1: were indistinguishable from hours. They weren't quite as good as ours,

887
00:46:53,320 --> 00:46:56,120
Speaker 1: but they were like easy to confuse with it, and

888
00:46:56,160 --> 00:46:58,640
Speaker 1: when you're on the Internet, you can't tell the difference.

889
00:46:59,640 --> 00:47:03,080
Speaker 1: For these fifteen teen celebs have taken a turn from

890
00:47:03,080 --> 00:47:08,719
Speaker 1: thee out a terrible version. But I but to your

891
00:47:08,719 --> 00:47:11,400
Speaker 1: point about like the cyclical nature of things, One thing

892
00:47:11,440 --> 00:47:13,759
Speaker 1: we did notice in their early days, and I think

893
00:47:13,840 --> 00:47:18,319
Speaker 1: up until the end at Cracked, was that robots were

894
00:47:18,360 --> 00:47:21,600
Speaker 1: no longer scary to people. Like in the eighties, they

895
00:47:21,600 --> 00:47:24,280
Speaker 1: were like a thing that the whole world was terrified

896
00:47:24,320 --> 00:47:27,760
Speaker 1: of and there were all these movie franchises and batteries

897
00:47:27,760 --> 00:47:30,839
Speaker 1: not included. Yeah, and then like starting in about two

898
00:47:30,880 --> 00:47:33,839
Speaker 1: thousand eight two thousand nine, we just like couldn't get

899
00:47:33,880 --> 00:47:36,799
Speaker 1: people to read about robots in any way unless it

900
00:47:36,880 --> 00:47:39,719
Speaker 1: was like this, robots fucking cool, and does the thing

901
00:47:39,760 --> 00:47:41,920
Speaker 1: that's going to solve a problem that you have? We

902
00:47:42,000 --> 00:47:44,839
Speaker 1: had at least exactly one article about drones that got

903
00:47:44,880 --> 00:47:46,759
Speaker 1: decent traffic, and then no one wanted to read about

904
00:47:46,840 --> 00:47:50,200
Speaker 1: drone war anymore. Right, that's right. Um. I wonder if

905
00:47:50,239 --> 00:47:51,640
Speaker 1: some of it might also be though, Like, right now,

906
00:47:51,680 --> 00:47:53,680
Speaker 1: you've got a bunch of very it's a very political

907
00:47:53,680 --> 00:47:55,120
Speaker 1: time in the country, and you've got a lot of

908
00:47:55,239 --> 00:47:58,400
Speaker 1: very political movies Black Kkke Klansmen or however we're supposed

909
00:47:58,400 --> 00:48:01,239
Speaker 1: to pronounce its clansmen, sorry to the you. Um, and

910
00:48:01,440 --> 00:48:04,279
Speaker 1: like a lot of political stuff that's dropped recently, and

911
00:48:04,280 --> 00:48:05,960
Speaker 1: maybe people were like, oh, it's just a movie about

912
00:48:05,960 --> 00:48:09,600
Speaker 1: a big as shark. That seems like it'll be I

913
00:48:09,640 --> 00:48:12,120
Speaker 1: just I don't want to think about the that is what.

914
00:48:12,320 --> 00:48:16,360
Speaker 1: It's so broad. Yeah, and completely it's basically shark. It

915
00:48:16,480 --> 00:48:19,040
Speaker 1: distills Shark Weeks, the energy of Shark Week and puts

916
00:48:19,080 --> 00:48:21,400
Speaker 1: it into a movie that like they also engineered to

917
00:48:21,440 --> 00:48:25,839
Speaker 1: be accessible to China and America. Uh and I think

918
00:48:25,880 --> 00:48:29,000
Speaker 1: because put up million in America, it put up fifty

919
00:48:29,000 --> 00:48:32,080
Speaker 1: million in China, Right that rarely because really when you

920
00:48:32,080 --> 00:48:35,640
Speaker 1: get that on screen duo of Jayson's Stipen and lead

921
00:48:35,680 --> 00:48:38,239
Speaker 1: Bing Bing, I mean, you know that's his money. In

922
00:48:38,280 --> 00:48:41,120
Speaker 1: the register, Bling Bling. But with these two, I think

923
00:48:41,160 --> 00:48:43,400
Speaker 1: it's just because it's so uh, it's just easy to

924
00:48:43,440 --> 00:48:47,759
Speaker 1: understand big ash shark motherfucker's are scared of humans can

925
00:48:47,880 --> 00:48:50,279
Speaker 1: understand the appeal of That's not like Star Wars, where

926
00:48:50,280 --> 00:48:52,279
Speaker 1: there's a lot of cultural things as to whether or

927
00:48:52,320 --> 00:48:54,640
Speaker 1: not you shared. It's very interesting. Oh yeah, big shark

928
00:48:54,680 --> 00:48:58,239
Speaker 1: attacking people. I'm scared of sharks. I've swam, like right,

929
00:48:58,280 --> 00:49:00,480
Speaker 1: and I think yeah, because like the shallows are forty

930
00:49:00,520 --> 00:49:03,680
Speaker 1: seven ms down, those are a little more nuanced for films,

931
00:49:03,719 --> 00:49:05,919
Speaker 1: and they're multiple sharks. I'm telling you that has something

932
00:49:05,960 --> 00:49:08,120
Speaker 1: to do with it. One of the shallows was just one, right,

933
00:49:08,400 --> 00:49:09,879
Speaker 1: was it just it was just it is that lady

934
00:49:09,880 --> 00:49:12,160
Speaker 1: who goes out swimming gets the ship bitten out of her,

935
00:49:12,200 --> 00:49:14,720
Speaker 1: and that was a pretty fun I enjoyed that. They're intense.

936
00:49:14,760 --> 00:49:16,040
Speaker 1: But yeah, I think with this one, you can just

937
00:49:16,080 --> 00:49:18,480
Speaker 1: look at a shot where like one shark is size

938
00:49:18,520 --> 00:49:21,879
Speaker 1: of like nine people and you're like, oh, yeah, yeah, yeah, yeah,

939
00:49:21,880 --> 00:49:24,239
Speaker 1: that's shot in the trailer of like there's a bunch

940
00:49:24,280 --> 00:49:26,320
Speaker 1: of people swimming and you see the shark's mouth in

941
00:49:26,360 --> 00:49:28,719
Speaker 1: the water and big as all. You're like, Okay, I

942
00:49:28,800 --> 00:49:32,720
Speaker 1: want people. Yeah. Yeah, it's like a rolling emeric movie

943
00:49:32,800 --> 00:49:37,000
Speaker 1: but with a shark. Yeah exactly. Um so yeah, maybe

944
00:49:37,040 --> 00:49:39,879
Speaker 1: we're just or maybe I was overthinking it and it's

945
00:49:39,920 --> 00:49:41,560
Speaker 1: just like, yeah, it's a rolling memeric movie with the

946
00:49:41,600 --> 00:49:44,000
Speaker 1: giant shark. Yeah. Well, I guess that's how much we're

947
00:49:44,040 --> 00:49:47,000
Speaker 1: dumbing things down. Where she were like, surely people's tastes

948
00:49:47,040 --> 00:49:49,080
Speaker 1: have to be a little more refined than some like

949
00:49:49,120 --> 00:49:51,759
Speaker 1: such an aggressively beef movie or whatever. But at the

950
00:49:51,840 --> 00:49:53,400
Speaker 1: end of the day, you just want to see some

951
00:49:53,440 --> 00:49:56,720
Speaker 1: motherfucker's getting by sharks eating by sharks. Uh. Super produce

952
00:49:56,760 --> 00:49:59,960
Speaker 1: around a Hosnie is writing a question to me Team

953
00:50:00,080 --> 00:50:03,200
Speaker 1: Field trip, which yes, yeah, I think that's a good

954
00:50:04,040 --> 00:50:05,880
Speaker 1: to go hunt down the megludon that lives in the

955
00:50:05,880 --> 00:50:11,040
Speaker 1: Marianna's trench, right, but we we hijack James Cameron submarine

956
00:50:11,160 --> 00:50:13,440
Speaker 1: and write it down there with a bunch of shotguns

957
00:50:13,440 --> 00:50:15,680
Speaker 1: and take out that damn fish. Hell yeah, or why

958
00:50:15,719 --> 00:50:20,000
Speaker 1: don't you get meg tattoos or that either? I thought

959
00:50:20,040 --> 00:50:24,400
Speaker 1: that's what she meant by Team Fieldtom tattoos. I'm just

960
00:50:24,400 --> 00:50:27,440
Speaker 1: get a big shark on my throat. But I mean

961
00:50:27,480 --> 00:50:30,680
Speaker 1: the first the first Jaws as a B movie executed

962
00:50:30,719 --> 00:50:35,279
Speaker 1: by like a hitchcocky and great director, and the first

963
00:50:35,360 --> 00:50:38,480
Speaker 1: Jurassic Park. I'd say the same thing. And even though

964
00:50:38,520 --> 00:50:41,399
Speaker 1: the first Jurassic Park has the Raptors, that still has

965
00:50:41,760 --> 00:50:47,520
Speaker 1: this like the t Rex is like the singular uh

966
00:50:47,760 --> 00:50:50,960
Speaker 1: monster that's like lurking out there that you're constantly aware of.

967
00:50:51,280 --> 00:50:53,640
Speaker 1: It's not just like a bunch of different Have you

968
00:50:53,680 --> 00:50:57,000
Speaker 1: seen what the projections are for this weekend. They think

969
00:50:57,040 --> 00:51:00,360
Speaker 1: it's gonna double. They think the Mega is gonna I

970
00:51:00,360 --> 00:51:03,240
Speaker 1: can see that because it's it's a superation. Yeah, something

971
00:51:03,320 --> 00:51:05,840
Speaker 1: is a surprise. People start piling on another thing in

972
00:51:05,920 --> 00:51:08,239
Speaker 1: one of these articles are meaning that an analyst did

973
00:51:08,280 --> 00:51:10,279
Speaker 1: point out was sort of like it comes at the

974
00:51:10,440 --> 00:51:14,640
Speaker 1: right time where all the traditional tent pole movies in

975
00:51:14,640 --> 00:51:17,920
Speaker 1: the summer have already happened. People are right about to

976
00:51:17,960 --> 00:51:20,680
Speaker 1: go to school, so you get your last hurrah in

977
00:51:21,320 --> 00:51:23,279
Speaker 1: and it's like nothing to we like you did not

978
00:51:23,400 --> 00:51:25,279
Speaker 1: really have to wrap your head around it. So they're

979
00:51:25,320 --> 00:51:28,600
Speaker 1: kind of found like a good lull. I think Crazy

980
00:51:28,680 --> 00:51:30,640
Speaker 1: rich Asans is going to do well this weekend too,

981
00:51:30,920 --> 00:51:32,520
Speaker 1: Let's hope. So yeah, I think so, I hope that

982
00:51:32,640 --> 00:51:36,080
Speaker 1: next year is nine or fifty movies about sharks in

983
00:51:36,160 --> 00:51:40,319
Speaker 1: fifty movies with Ken Jong character, And it could be

984
00:51:40,320 --> 00:51:42,960
Speaker 1: the sharks just kind of are a great metaphor for

985
00:51:43,000 --> 00:51:45,480
Speaker 1: the time we live in now, where like we're innocent

986
00:51:45,520 --> 00:51:48,319
Speaker 1: people and there are just a few disgusting sharks out

987
00:51:48,360 --> 00:51:52,280
Speaker 1: there wanting to do the rest. Yeah, I mean they're sharks.

988
00:51:52,320 --> 00:51:55,719
Speaker 1: Clearly represents Donald Trump, but I didn't say I'm I'm

989
00:51:55,760 --> 00:52:00,840
Speaker 1: at Spectrum Cable. Okay, um, because they do not. I

990
00:52:01,000 --> 00:52:04,879
Speaker 1: got work. All right, that's gonna do it for this

991
00:52:04,960 --> 00:52:08,800
Speaker 1: week's weekly Zeite. Guys, please like and review the show.

992
00:52:09,440 --> 00:52:13,240
Speaker 1: If you like the show, uh means the world of Miles.

993
00:52:13,360 --> 00:52:17,799
Speaker 1: He needs your validation, folks. I hope you're having a

994
00:52:17,840 --> 00:52:52,320
Speaker 1: great weekend and I will talk to him Monday. By