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Speaker 1: I follow this one guy who's in Iran. Who does

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Speaker 1: I'm not joking. The scary ish he's always almost falling

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Speaker 1: off a mountain is what his contract is the thing.

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Speaker 2: I am that suicidal, but I'm not that in shape,

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Speaker 2: do you know what I mean?

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Speaker 1: Like, I'm like, if it happens like another life, let

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Speaker 1: go and let God No. I was showing Anna because

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Speaker 1: I was like, can you like translate what this guy

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Speaker 1: is saying? And She's like, the guy just keeps time.

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Speaker 1: My heights about to fall off?

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Speaker 2: Yeah? I feel like that's all I'd be talking about too.

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Speaker 1: What falling off a mountain?

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Speaker 2: Yeah, if I was about to fall off mountain, I'd

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Speaker 2: be like, yeah about God, No, no I have I'm

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Speaker 2: really scared of heights And like watching this, it's like.

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Speaker 1: What's that song?

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Speaker 2: I don't I don't like it done?

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Speaker 1: Then okay, you know what?

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Speaker 2: You know what? I can fix him? You need something

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Speaker 2: to live for, baby, He's never This is a man

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Speaker 2: who's never been properly loved before.

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Speaker 1: Hi, Hello the Internet? All right? Cool? Most of shit

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Speaker 1: up there is ai slot, but this one isn't. Because

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Speaker 1: this is season four eleven, Episode five of the dailies.

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Speaker 1: I guys. The production of iHeartRadio. This is the production

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Speaker 1: or the podcast where we take a deep dive into

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Speaker 1: America's shared consciousness. It's Friday, Fank fuck, October twenty fourth,

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Speaker 1: twenty twenty five. You say, what day is that? It's

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Speaker 1: National Bologne Day, National Pharmacy Buyer Day. Is that just

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Speaker 1: a like a euphemism for somebody who buys pills and shit? Yeah,

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Speaker 1: I'm a farm. Oh maybe someone who buys them. Look,

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Speaker 1: I don't know anything about pharmaceuticals. It's also National Food Day,

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Speaker 1: so shout out foods, shoutout pharmacy. Shut out. I guess baloney.

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Speaker 1: I have had a You do.

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Speaker 2: Have to wrap pills in blooney to get me to

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Speaker 2: eat them, So I feel like it's pretty related.

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Speaker 1: I need some kind of formed meat products to ingest

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Speaker 1: any of my medication.

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Speaker 2: Yeah, yeah, you have to. I have to trick myself

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Speaker 2: into it. You know.

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Speaker 1: I put mayonnaise on my dog's pills. That's how I

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Speaker 1: get it.

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Speaker 2: If your dog white?

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Speaker 1: My dog, I know, But I got him from Stephen Miller,

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Speaker 1: famous person. Yeah, famous Mann's person, Stephen Miller. No, he's

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Speaker 1: the way because I tried putting like the dog food

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Speaker 1: in like the little pill pouch type things, and that's

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Speaker 1: so much work that if I just if there's just

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Speaker 1: a hint of flavor in the dog bowl on the pill,

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Speaker 1: the dogs eats everything up, so I just got to pull.

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Speaker 2: Why are you putting mayonnaise.

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Speaker 1: Because it comes it's like a neat bottles like spicy. Well,

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Speaker 1: he has elevated tastes. He only likes QP Japanese mannaise.

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Speaker 1: You know what, Yeah, that's how he gets out. Anyway,

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Speaker 1: my name is Miles Gray a k A.

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Speaker 3: I can't run one point five miles and I can't

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Speaker 3: push up any more. Want to be the man who

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Speaker 3: kidnaps with a smile, land kicks down neighbors dogs.

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Speaker 1: Fuck Ice now, anyway. That thank you to Smitty Werbin

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Speaker 1: Jaegerman Jensen on the discord. I think that might be

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Speaker 1: a first timer, but thank you for that one, obviously,

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Speaker 1: because all the ICE candidates are terribly out of shape

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Speaker 1: because the only thing that brought them there is their

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Speaker 1: hate of non white people. But anyway, that's something to consider.

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Speaker 1: If you're wanting to be Ice, you will have to

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Speaker 1: do push ups and run one point five miles. Anyway,

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Speaker 1: I am thrilled to be joined my my co host today,

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Speaker 1: My guest co host today. Look brilliant comedian, brilliant writer,

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Speaker 1: brilliant activist, brilliant host. You know they got facial recognition comedy.

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Speaker 1: You probably heard of it. They're a lover of animals.

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Speaker 1: Some might say the Saint Francis of our time. Please

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Speaker 1: welcome to the microphone.

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Speaker 2: Hello, Hello, Okay, First of all, stop making eyes so relatable.

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Speaker 2: I don't think I can run one point. How can

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Speaker 2: you do probably less than Dean Kine?

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Speaker 1: I don't know, you can probably do more than thirty

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Speaker 1: You have to do thirty two.

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Speaker 2: That's literally, that's it.

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Speaker 1: Yeah, that's something they can't get motherfuckers that can do

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Speaker 1: thirty two sit ups because again they have to scrape

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Speaker 1: the literal bottom of the porta potty to dig up

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Speaker 1: these pieces of shit who have enough fucking hate in

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Speaker 1: their heart and are ignorant enough to be like, yeah, good,

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Speaker 1: this is this is something I want to be part of.

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Speaker 1: For posterious.

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Speaker 2: We got to figure out how to combat them wearing masks.

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Speaker 2: We got to figure out I don't know, we need

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Speaker 2: some sort of iron man.

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Speaker 1: We need some sort of give me some like some

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Speaker 1: semblance of like laws or something. I feel like, I

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Speaker 1: think maybe that would that would solve the case. But

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Speaker 1: we'll see.

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Speaker 2: No, that doesn't seem right.

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Speaker 1: Well, more and more states are being like, well, we

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Speaker 1: can't arrest you if you're breaking our laws in our state.

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Speaker 2: They're saying about that.

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Speaker 1: Yeah, yeah, that's happening in Illinois. Pelosi said that may

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Speaker 1: be alienated.

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Speaker 2: Like IDF soldiers are around the world.

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Speaker 1: Oh yeah, trying to vacation in Thailand and stuff. I

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Speaker 1: always see it, yea, that where it's out of control. Anyway,

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Speaker 1: we are joined today in our third seed. Brilliant guest.

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Speaker 1: I consider this person one of the greats of where

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Speaker 1: of Los Angeles. Why because they come from the San

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Speaker 1: Fernando Valley. Because they know that the shit I've learned

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Speaker 1: about la from this person is unreal. I didn't know

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Speaker 1: that the fucking Laurel Canyan kinga pass. I don't know

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Speaker 1: these are all Pony Express routes. I guess we taught

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Speaker 1: me that, this guest, and I still think of that

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Speaker 1: to this day. You know them from their work, I

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Speaker 1: don't know girls of Hoodies night Call. I've got fuck

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Speaker 1: a Heidi World and now the upcoming Geno World very

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Speaker 1: close to my heart because I grew up fucking steps

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Speaker 1: away from the Vivid Video headquarters in I guess we

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Speaker 1: call that Studio city, Universal City, Los Angeles. Yeah, University.

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Speaker 1: I mean it's right across from the wonderful Yeah exactly,

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Speaker 1: exactly right across from the Nissan dealership that is no

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Speaker 1: more near the in and out Burger Weergulane. Maxwell was

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Speaker 1: photographed pre arrest. Let's just this is a very historical area.

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Speaker 1: Please welcome to the microphone, Molly Lambert.

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Speaker 2: Wait, Molly, how do you know all these la facts?

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Speaker 4: I just can't stop. I can't stop.

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Speaker 1: A journalist, I think journalists probably, I would that maybe

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Speaker 1: the journalism brought you to intersection with these facts. Maybe

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Speaker 1: are we just that kid who was just always like

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Speaker 1: spitting nerdy facts?

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Speaker 4: I gut school and a trivia accumulator.

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Speaker 1: How did you know about or when did you learn of,

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Speaker 1: like the Laurel Canyon, Koanga Pass, Coldwater Canyon thing being

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Speaker 1: the routes for the old horsemail.

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Speaker 4: Oh. I read like a thousand books about Laurel Canyon

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Speaker 4: at one point. Okay, this makes sense as part of

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Speaker 4: a larger reading a thousand books about the Manson family,

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Speaker 4: just to know.

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Speaker 2: Just to learn still get their Christmas cards. It's crazy family.

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Speaker 1: The Manson family just sent their card. Okay, So okay,

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Speaker 1: that's interesting. So these factors that you're talking about there

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Speaker 1: in books, Okay, I'm.

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Speaker 2: Gonna did a I make those? What is that?

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Speaker 1: Some do?

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Speaker 2: Some do?

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Speaker 1: Most of these are yeah, exactly, Molly Jenda World coming up. Fantastic,

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Speaker 1: fantastic series that I've not really been able to hear.

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Speaker 1: I'm only saying that because I've lended my voice to

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Speaker 1: it and seeing all the other amazing people that have

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Speaker 1: lended their voice to and I'm.

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Speaker 4: Like, I'm excited for you to hear it because you

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Speaker 4: are literally the first voice that is heard. No, yeah,

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Speaker 4: it's oh.

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Speaker 1: No, that's pressure now.

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Speaker 4: No, no, it's so funny. Miles Place, Kid Rock.

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Speaker 2: Place, Daniel day lewis ing that.

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Speaker 1: Channeling, channeling, channeling. Yeah, when's so? When's General World dropping?

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Speaker 4: October twenty seventh, Monday.

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Speaker 1: Monday, Load up your fucking iPods? Okay for this podcast?

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Speaker 1: Producer Bay right there, Bay also work and everybody's everybody

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Speaker 1: giving a hand on the show.

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Speaker 4: They worked on the show. She's in the show. Everybody's

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Speaker 4: in the show.

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Speaker 1: There we go, There we go. Well, Molly, we're gonna

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Speaker 1: get to know you a lot better in a moment.

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Speaker 1: But first, what are we talking about today? The final

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Speaker 1: New York mayor Old debate happened, and every time there's

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Speaker 1: a debate, Zoran Mumdani has absolutely fillayed, flombaye, grilled, deep fried,

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Speaker 1: and cooked Andrew Cuomo very casually, and this debate was

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Speaker 1: no exception. But then along with that, Andrew Cuomo decided

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Speaker 1: to play in ace up his sleeve in the form

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Speaker 1: of racist AI slop video campaign ad on Twitter. We'll

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Speaker 1: check that out because it's it's like, so it's so

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Speaker 1: racist that I feel like even modern day racists will

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Speaker 1: be like, I mean, come on, like this, it's not

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Speaker 1: like this exactly. This is like the nineteen eighties version

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Speaker 1: of racism. But that's where onemost add mentally.

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Speaker 4: So putting him in like the paddy wagon.

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Speaker 1: Yeah right, exactly right. I feel like the fucking the

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Speaker 1: cops from Cuckoo Crisp were about to show up for

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Speaker 1: those of you all remember those commercials like the old

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Speaker 1: fucking Bobby hats and shit that they wore, and then

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Speaker 1: also the Stranger Things fucking universe is coming to an end.

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Speaker 1: It's collapsing before our eyes. So we just want to

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Speaker 1: talk about that. The going away.

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Speaker 2: About Elevin's finally a diary.

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Speaker 1: Eleven is now forty one, Okay, good to see honey.

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Speaker 1: You look great? Uh? Is Marde to John bon Jovi's kid?

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Speaker 2: Right, that's I think so. And didn't they like adopt

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Speaker 2: a child or something?

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Speaker 1: They already adopted a child.

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Speaker 2: They were I don't know, I thought there was something about.

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Speaker 4: I think that's all true. I think when you're a

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Speaker 4: child actor, your speed run in life.

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Speaker 1: Yeah right, holy shit.

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Speaker 2: Yeah. And so she's twenty one, but she has she

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Speaker 2: does have the makeup of a forty year old.

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Speaker 1: So yeah, I mean she's the way those kids have aged.

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Speaker 1: I'm like, the fuck, how do they even keep telling

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Speaker 1: this story? They all are unrecognizable at this point, like

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Speaker 1: like legitimately, I think in their mid thirties. Now, if you.

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Speaker 4: Spend your childhood working, you should get the rest of

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Speaker 4: it off.

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Speaker 2: But yeah, like the the what's his face? From Game

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Speaker 2: of Thrones who was just like, I got evil villain face,

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Speaker 2: So I'm just gonna go to college for a while.

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Speaker 2: The little blonde king what's his name?

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Speaker 1: Jeffrey, the one who played Geoffrey.

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Speaker 2: Yeah, he just was like, I'm gonna take some time

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Speaker 2: off and go learn shit.

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Speaker 1: And I'm like, that's a UK shit, you know, because

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Speaker 1: people got there.

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Speaker 2: They're smarters.

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Speaker 1: Yeah.

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Speaker 4: I said about Emma Watson too. She was like, I

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Speaker 4: think I might just go back to school again, and

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Speaker 4: everybody was like, why does she keep going back to Just.

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Speaker 1: Wrong with her because in books anyways, my life was

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Speaker 1: stunted by stardom and Hollywood productions. Probably I don't know that.

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Speaker 2: That's no get addicted to drugs and pop and dance

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Speaker 2: in front of the paparazzis.

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Speaker 1: Shave you ahead, you ahead have a crisis, have a crisis.

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Speaker 1: And also we're going to talk about Canada's Trump Kevin O'Leary,

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Speaker 1: mister wonderful, because I didn't know he was in Marty Supreme,

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Speaker 1: the new Safti Josh Saftie film, and the reason why

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Speaker 1: his cast is really funny. But also this guy, Look,

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Speaker 1: you put a shitty person in a film, they're gonna

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Speaker 1: say shitty things during the fucking promo tour for the film,

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Speaker 1: even if they're not formally part of the promotional tour.

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Speaker 1: So we'll get into that and maybe some other stories too,

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Speaker 1: while we're at it. But first, Molly Lambert, if I

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Speaker 1: may do the French pronunciation, what is something from your

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

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Speaker 4: Okay? Last night, this one, I'm ready. This time, I

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Speaker 4: heard somebody listen playing I heard somebody reading Frankenstein on

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Speaker 4: aloud a radio station. Yeah, on a college I can't

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Speaker 4: tell you the college radio station.

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Speaker 1: There way to get people to shadow noise pollution on

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Speaker 1: Thursday Nights, hosted by'm a boy Chris Candy.

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Speaker 4: Yeah, it's such a it's a great radio station, Kexley.

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Speaker 4: But yeah, they were just playing some recording of somebody

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Speaker 4: reading Frankenstein.

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Speaker 2: And I was locked the fuck in. I was like, yeah,

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Speaker 2: wow this rocks were searching.

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Speaker 4: I just was searching Frankenstein and reading all this stuff

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Speaker 4: about Mary Shelley writing Frankenstein when.

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Speaker 1: She was a teen.

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Speaker 4: She was a teen, Yeah, she wrote it when she

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Speaker 4: was eighteen.

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Speaker 1: Okay, Mary Shelley, God damn, I was.

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Speaker 2: Too busy, fucking.

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Speaker 1: Yeah I could have wrote that, but I was out.

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Speaker 2: Here them with real body parts, you know.

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Speaker 1: Tell me, dude, I say a lot of ladies with

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Speaker 1: they pitchforks out, you know what I mean? Because I

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Speaker 1: was doing them dirty.

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Speaker 4: Uh yeah, I was reading about Frankenstein, reading about some

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Speaker 4: of the real scientists the doctor Frankenstein was based off.

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Speaker 1: Of that were trying to like reanimate that bodies, and.

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Speaker 2: Yeah they were. They They're fucking crazy back then. Sorry,

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Speaker 2: go ahead, No, they were.

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Speaker 4: They were fucking crazy back then. They were doing a

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Speaker 4: lot of like like attaching electrodes to things and making

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Speaker 4: the things kind of like shake and seem like they

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Speaker 4: were coming to life. And that's where the idea.

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Speaker 2: Yes, it's because they were trying to figure out how

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Speaker 2: like nerves worked, probably.

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Speaker 1: But yeah, but like I think they probably accidentally figured

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Speaker 1: out how nerves work.

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Speaker 4: I think, you know, it was like it was really

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Speaker 4: like they were trying to do alchemy and they kept

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Speaker 4: accidentally like doing real science, right right, right, Yeah, So

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Speaker 4: like the guy who Frankenstein is allegedly based on, there's

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Speaker 4: like a castle Castle Frankenstein. He was like trying to

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Speaker 4: make the elixir of life that keeps you alive forever.

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Speaker 2: This was like the billionaires of their time who had

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Speaker 2: their own blood boys and stuff.

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Speaker 4: It was truly so techbro of its time. It was

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Speaker 4: just like, yeah, he's trying to make the elixir of life,

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Speaker 4: and then he was just scamming all these people, being like, yeah,

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Speaker 4: I made it right.

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Speaker 1: It's exactly where the others failed. I have succeeded. I

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Speaker 1: present to you soilent, my boys.

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Speaker 4: His name, his thing was that he boiled a bunch

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Speaker 4: of animal bones down to an elixir.

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Speaker 1: And then.

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Speaker 2: This is like white people discovering like Eastern medicine all

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Speaker 2: over again, these herbs. Isn't there like a new Frankenstein

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Speaker 2: coming out with oscarizing.

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Speaker 4: Yeah, there's a new Caramel do Toro for ye, where

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Speaker 4: Jacob Elordi.

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Speaker 1: Is the monster.

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Speaker 4: Okay, okay, Jacob I almost like Frankenstein's cool.

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Speaker 1: But Molly, it's alleged that Mary Shelley based Frankenstein off

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Speaker 1: a dude named Frankenstein who was doing wild experiments.

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Speaker 4: Yeah, his name wasn't Frankenstein. I think his name was Dippin'.

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Speaker 4: And it's like dipping the elixir.

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Speaker 1: Dippin' dots.

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Speaker 2: The ice cream.

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Speaker 1: It breaks dots.

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Speaker 4: But there's all this stuff too about Mary Shelley and

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Speaker 4: her husband and being like in a polycule eighteen hundreds

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Speaker 4: polycule dang mess.

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Speaker 2: I like, oh, that's why she was like looking at

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Speaker 2: body parts from different people. That's how she was getting down.

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Speaker 1: Oh she didn't even think about that. Fuck okay Mary Shelley, Okay,

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Speaker 1: wait who was reading it? Was the reading so good?

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Speaker 1: It was captivating or like you're like.

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Speaker 4: Oh yeah, there was a guy reading it who like

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Speaker 4: had a real guy reading Frankenstein Boye where he was like, oh,

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Speaker 4: my creature, it's come to life.

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Speaker 1: Oh so he was giving a little monster mash.

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Speaker 4: Yeah.

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Speaker 1: I went a little spooky, few, little spooky.

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Speaker 2: This is real healing my inner child by having someone

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Speaker 2: read me a book moment.

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Speaker 5: It was great.

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Speaker 4: I was like wow, books. And also I was stuck

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Speaker 4: in traffic, so again I was like, yeah, yeah.

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Speaker 2: Everything, books, everything, computer.

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Speaker 1: Speaking of college radio, are you fucking with the oak?

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Speaker 1: How sound?

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Speaker 4: What's that?

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Speaker 1: The Seasun radio station?

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Speaker 4: I don't know about it.

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Speaker 1: Matt Pinfield, Matt Pinfield has a show on there.

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Speaker 4: Oh my god, I've heard it by accident.

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Speaker 1: It's it's good being phenomenal. Yeah. I was like, see

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Speaker 1: Sun's radio stick.

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Speaker 2: This is how state phenomenal about it.

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Speaker 1: Just there. They've totally like it's like CACRW here. They're like,

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Speaker 1: we're not playing like the commercial hits. We're just curating

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Speaker 1: really good places. Oh wow, so like but it's great,

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Speaker 1: Like you'll get a great block of rock and you're like,

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Speaker 1: what the fuck?

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Speaker 2: Yeah, just a minute, it's kind Yeah, that's incredible.

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Speaker 1: Or just random stuff. Yeah, it's really really cool.

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Speaker 4: I was going back to the old school.

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Speaker 1: You got to you got to radio. So many people

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Speaker 1: got got at kcr W. Sorry this is like la

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Speaker 1: radio talk right now. But a lot of DJ's like

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Speaker 1: Jeremy Soul, A lot of people have been there for

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Speaker 1: a minute, We're let go, and that's that's that's sending

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Speaker 1: shock waves through the public radio community in Los Angeles.

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Speaker 4: Uh, Molly, was the only morning ever become a colectic? Now, well,

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Speaker 4: maybe that's why I got no Vina Carmel. And people

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Speaker 4: are mad at Novina Carmel for being or there, like

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Speaker 4: it's probably there's no Vena's taking up the money.

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Speaker 1: It's like, y'all, please don't be mad at.

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Speaker 2: This woman of color out right now for this drama.

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Speaker 1: Also, her dad is sly Stone, Mollie. What is something

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Speaker 1: you think is underrated?

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Speaker 4: How about a nice pair?

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Speaker 2: I love goal on Asian pair. People are all, you know,

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Speaker 2: like people are like apples, apples apples, But what about

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Speaker 2: the pair. It's good.

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Speaker 1: What kind you have? Like a bartlet?

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Speaker 4: Yeah, I like a bartlet, like a done you Oh yeah.

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Speaker 1: Wait, what's that is that? The crunchy Asian I like

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Speaker 1: crunchy Asian pairs.

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Speaker 2: I feel like people underrate pairs because they can get

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Speaker 2: soft and damage and apples. You can carry around more

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Speaker 2: easily because they have like a harder shell, if you will,

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00:17:40,200 --> 00:17:43,600
Speaker 2: the meat harder, harder meat, tougher meats. That's kind of

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Speaker 2: but if you can delicately carry your pair around and

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Speaker 2: bite into that cris crisp pear, so good.

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Speaker 1: Yeah, you've actually designed a carrying case for pairs. It's

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Speaker 1: like a PVC sort of tube. You put it in there.

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Speaker 2: It's one of those Yeah, it's like you know in

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Speaker 2: sixth grade when you had to make a parachute for

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Speaker 2: an egg.

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Speaker 1: I'm doing one for a pair. Sorry.

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Speaker 2: I did one for a pair, and I carried around

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Speaker 2: instead of a purse, and then in the middle of

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Speaker 2: a conversation, I just pull it out and crunch.

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Speaker 1: There's there's a Korean chicken place I went to and

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Speaker 1: like and their drink case. I had a bunch of

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Speaker 1: Korean drinks and one was a pear juice, a crunchy

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00:18:21,840 --> 00:18:24,160
Speaker 1: Asian pear juice, like not like a kurrns nectar pair,

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Speaker 1: which is also shout out Currs nectar. Even that's all

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Speaker 1: basically fucking sugar. But that fucking Korean pear juice drink.

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Speaker 1: Oh my god, it's transported me to my childhood because

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Speaker 1: like in Japan in the summers, like you fucking eat pears,

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Speaker 1: those crunchy pears and nonstuff.

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Speaker 2: Can I say something controversial? Go ahead, Asian fruit supremacy.

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Speaker 1: Tell them, tell them, tell them.

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Speaker 2: I'm sorry that shit is fresh as.

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Speaker 1: You don't even know about light cheese, you know what

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Speaker 1: I mean?

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Speaker 2: I don't know jackfruit, mango, everything's better.

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Speaker 4: Oh you go to the farmer's market and there's the

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Speaker 4: one guy with the good Asian fruit and vegetable. Yeah

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00:19:02,000 --> 00:19:03,680
Speaker 4: winter melon, yeah.

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00:19:03,680 --> 00:19:07,600
Speaker 1: Yeah, exactly so good, or like a momotato tomato, you

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00:19:07,680 --> 00:19:11,080
Speaker 1: know what I mean. There's all kinds of there's there's speech. Yeah,

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00:19:11,320 --> 00:19:16,320
Speaker 1: good god. Now I just want fruit, Molly. What's something

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00:19:16,359 --> 00:19:17,160
Speaker 1: you think is overrated?

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00:19:17,800 --> 00:19:17,960
Speaker 2: Uh?

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00:19:18,240 --> 00:19:23,080
Speaker 4: I think eggs. I realized I don't really care about eggs. Okay,

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00:19:23,280 --> 00:19:27,800
Speaker 4: the pair livestock, Yeah, you think I was going to

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00:19:27,880 --> 00:19:30,159
Speaker 4: go with another fruit or vegetable. But yes, what you

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Speaker 4: said egg one second ago, and then my brain went.

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Speaker 1: Egg because you don't miss eating them. I buy I

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00:19:36,720 --> 00:19:39,399
Speaker 1: buy eggs mostly because my kid will kind of eat them,

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00:19:39,480 --> 00:19:41,040
Speaker 1: and in my mind, I'm I was like, oh, yeah,

402
00:19:41,040 --> 00:19:43,040
Speaker 1: I'll probably cook up an egg. I fucking never do.

403
00:19:43,160 --> 00:19:45,960
Speaker 1: And then yeah, just soft boil them, eat them like

404
00:19:46,119 --> 00:19:46,400
Speaker 1: I buy.

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Speaker 2: I buy eggs as a financial investment with smart contracts.

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Speaker 1: Good.

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00:19:50,760 --> 00:19:54,960
Speaker 2: Yeah, because you're because they're so pricey and like, yeah

408
00:19:55,040 --> 00:19:59,480
Speaker 2: you invest now lating Yeah that six dozen you bought

409
00:19:59,600 --> 00:20:02,280
Speaker 2: on a few weeks, Yeah they're still here. It doesn't

410
00:20:02,280 --> 00:20:03,879
Speaker 2: smell really great, but you know what.

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Speaker 4: I think, it's like I like the yolk, but I

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Speaker 4: just I've never been like egg white.

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Speaker 1: It's like you don't wait, hold on, hold on, wait, wait,

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00:20:12,440 --> 00:20:14,800
Speaker 1: you don't you like that's the opposite of what people say.

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00:20:14,880 --> 00:20:17,600
Speaker 1: I don't know white, I don't I get the yolk

416
00:20:17,680 --> 00:20:19,879
Speaker 1: if you're doing I'm like runny or whatever. But like

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00:20:20,080 --> 00:20:21,119
Speaker 1: in a boiled egg.

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Speaker 4: Too, yea, even in a boiled egg, yok' is a

419
00:20:22,800 --> 00:20:23,760
Speaker 4: good part yellow.

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Speaker 2: That's like the to me, that's the I haven't had

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00:20:26,760 --> 00:20:29,440
Speaker 2: eggs in a while, but that's like the most chalky part.

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00:20:29,920 --> 00:20:32,280
Speaker 4: I like, I don't like how the white is like

423
00:20:32,560 --> 00:20:38,960
Speaker 4: runny or like gummy. Oh wow, interesting, it's like anything.

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Speaker 1: Okay, so Victor, actually, yeah, baby, let's find another guest

425
00:20:44,920 --> 00:20:45,600
Speaker 1: we're looking for.

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00:20:46,320 --> 00:20:51,560
Speaker 2: We're looking for the pure white, the part none of this.

427
00:20:53,200 --> 00:20:58,399
Speaker 1: Color yellow supremacy. I'm hearing on this show there's a

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00:20:58,480 --> 00:21:00,720
Speaker 1: Japanese Wait, BASI said, there's a jack. But these white

429
00:21:00,720 --> 00:21:02,040
Speaker 1: egg bait. Come on Mike really quickly.

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Speaker 4: We'll say.

431
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Speaker 1: You know what is good.

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00:21:03,720 --> 00:21:07,480
Speaker 4: It is the ta egg. That's a good egg. Oh yes,

433
00:21:07,840 --> 00:21:09,400
Speaker 4: eggs so good.

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00:21:09,560 --> 00:21:13,200
Speaker 2: But these white eggs they feed them, I think just

435
00:21:13,520 --> 00:21:17,240
Speaker 2: rice or something. It's called The brand is called Coma.

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00:21:18,840 --> 00:21:22,040
Speaker 1: Means rice. Okay, yeah, yep, yeah, yeah, oh shi it

437
00:21:22,119 --> 00:21:23,080
Speaker 1: really the yolks are.

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00:21:25,040 --> 00:21:25,560
Speaker 4: I'm looking?

439
00:21:26,359 --> 00:21:30,720
Speaker 1: Nah see oh white white is all weird?

440
00:21:31,280 --> 00:21:34,879
Speaker 2: Wow that does feel weird. I don't know, I don't know.

441
00:21:35,560 --> 00:21:38,080
Speaker 1: No, I don't like this. I don't like it.

442
00:21:38,480 --> 00:21:40,200
Speaker 2: I don't like the white rice too.

443
00:21:40,320 --> 00:21:41,320
Speaker 4: It is just like that's.

444
00:21:43,680 --> 00:21:51,879
Speaker 1: Yea, oh my god? Yeah, holy, okay, well great, a

445
00:21:51,960 --> 00:21:56,320
Speaker 1: new egg for racists has dropped courtesy of Japan, wouldn't

446
00:21:56,359 --> 00:21:58,960
Speaker 1: you know it? All right, we will take a quick

447
00:21:59,000 --> 00:22:01,920
Speaker 1: break and we'll be right back to talk about I

448
00:22:01,960 --> 00:22:14,920
Speaker 1: guess some more racism, I guess right after this, and

449
00:22:15,359 --> 00:22:20,560
Speaker 1: we're back. A lot of a lot of consequential races

450
00:22:20,760 --> 00:22:24,560
Speaker 1: happening across the country. We've got Prop fifty coming up

451
00:22:24,680 --> 00:22:28,919
Speaker 1: in California to try and battle all the racist jerrymandering

452
00:22:28,920 --> 00:22:31,600
Speaker 1: that's happening because North Carolina just they just carved up

453
00:22:31,600 --> 00:22:34,120
Speaker 1: their maps and created a new Republican seat. So it's

454
00:22:34,119 --> 00:22:36,240
Speaker 1: a bit of an arms race in terms of jerrymandering.

455
00:22:36,600 --> 00:22:40,320
Speaker 1: We also have Gubernatoil races, mayoral races, and which we'll

456
00:22:40,400 --> 00:22:42,560
Speaker 1: touch on too, because I've had Zegang reached out to

457
00:22:42,600 --> 00:22:44,080
Speaker 1: be like talk about this race. I'm like, ye, we

458
00:22:44,240 --> 00:22:47,120
Speaker 1: absolutely should. But one that's very much been in front

459
00:22:47,119 --> 00:22:48,520
Speaker 1: of mine, at least for this show has been the

460
00:22:48,560 --> 00:22:51,800
Speaker 1: New York mayoral race. And there was the I believe

461
00:22:51,840 --> 00:22:56,240
Speaker 1: the final debate happened before the election, and again, like

462
00:22:56,320 --> 00:22:59,840
Speaker 1: I said up top, this was another opportunity for the

463
00:23:00,400 --> 00:23:04,600
Speaker 1: to just fucking just describe Andrew Cuomo to his face

464
00:23:04,680 --> 00:23:06,960
Speaker 1: as an insult, and it's one of the most effective

465
00:23:07,000 --> 00:23:09,520
Speaker 1: attacks you can do on a debate stage. But yeah,

466
00:23:09,560 --> 00:23:12,000
Speaker 1: I think the thing that was most talked about again

467
00:23:12,280 --> 00:23:15,840
Speaker 1: was Mom Donnie bringing up the multiple sexual harassment allegations

468
00:23:15,960 --> 00:23:19,920
Speaker 1: against Cuomo and even talking about how one of the

469
00:23:20,000 --> 00:23:22,879
Speaker 1: people that has accused him was in the audience. I

470
00:23:22,920 --> 00:23:26,119
Speaker 1: will just play I'm just gonna play this clip because

471
00:23:26,200 --> 00:23:29,159
Speaker 1: in its entirety it's an absolute It's I don't know,

472
00:23:29,320 --> 00:23:34,240
Speaker 1: a broiled basted raised here. He is just saying, Hey,

473
00:23:34,320 --> 00:23:36,200
Speaker 1: what's up with you? Bro? Let me talk about you

474
00:23:36,280 --> 00:23:36,680
Speaker 1: real quick.

475
00:23:36,720 --> 00:23:42,040
Speaker 6: Andrew Cuomo, Mister Cuomo, in twenty twenty one, thirteen different

476
00:23:42,080 --> 00:23:44,639
Speaker 6: women who worked in your administration in credibly accused you

477
00:23:45,160 --> 00:23:49,560
Speaker 6: of sexual harassment. Since then, you have spent more than

478
00:23:49,640 --> 00:23:53,959
Speaker 6: twenty million dollars in taxpayer funds to defend yourself. All

479
00:23:54,880 --> 00:23:58,920
Speaker 6: I'm describe it resigations entirely. What could he possibly be?

480
00:23:59,000 --> 00:24:01,479
Speaker 6: Writ again, You've even go so far as to legally

481
00:24:01,600 --> 00:24:06,880
Speaker 6: go after one of those women. Charlotte Bennett is here

482
00:24:07,000 --> 00:24:11,679
Speaker 6: in the audience this evening. You seek to access her

483
00:24:11,800 --> 00:24:13,720
Speaker 6: private gynecological records.

484
00:24:15,000 --> 00:24:16,280
Speaker 2: She cannot speak.

485
00:24:16,000 --> 00:24:20,840
Speaker 6: Up for herself because you lodged a defamation case against her. I, however,

486
00:24:21,000 --> 00:24:24,120
Speaker 6: can speak What do you say to the thirteen women

487
00:24:24,160 --> 00:24:25,160
Speaker 6: that you sexually harassed?

488
00:24:27,840 --> 00:24:30,920
Speaker 2: Dude? And then he kind of like his mind like skips.

489
00:24:31,160 --> 00:24:34,879
Speaker 1: He's like, but I mean telling you that, he's like

490
00:24:35,000 --> 00:24:38,159
Speaker 1: he's hanging his head as he's describing all this. I'll

491
00:24:38,320 --> 00:24:41,160
Speaker 1: let's let Andrew Cuomo give his answer because I'm sure

492
00:24:41,200 --> 00:24:47,640
Speaker 1: it will be a poignant That's not a good sign

493
00:24:47,720 --> 00:24:51,760
Speaker 1: if you're Andrew Cloma. If you if you want to

494
00:24:51,800 --> 00:24:54,960
Speaker 1: be in government, then you have to be serious and mature.

495
00:24:56,080 --> 00:24:58,879
Speaker 1: That's what you would say to the women you sexually harassed.

496
00:25:01,160 --> 00:25:03,879
Speaker 1: Because she's doing a wind up.

497
00:25:03,960 --> 00:25:05,760
Speaker 4: But like, so that's crazy.

498
00:25:06,359 --> 00:25:06,520
Speaker 2: Yeah.

499
00:25:06,600 --> 00:25:08,639
Speaker 4: I didn't watch this yet, and I didn't know it

500
00:25:08,920 --> 00:25:11,040
Speaker 4: had become like good wrestling.

501
00:25:11,560 --> 00:25:17,439
Speaker 2: It's got some bangers, also some good racism, like Curtis

502
00:25:17,800 --> 00:25:21,920
Speaker 2: Sila asked, saying that Zoron advocated for Global GHA.

503
00:25:22,480 --> 00:25:25,640
Speaker 4: Yeah, well they're out all the catchphrases.

504
00:25:25,800 --> 00:25:31,160
Speaker 2: Yeah yeah, yeah, he's But also, I yeah, I love Curtis.

505
00:25:31,720 --> 00:25:34,840
Speaker 2: He's a typical. He's like it's like it's like a

506
00:25:35,280 --> 00:25:39,080
Speaker 2: caricature of New York. It's like it's like he's like, hey,

507
00:25:39,200 --> 00:25:41,440
Speaker 2: I'm walking here like that guy.

508
00:25:41,840 --> 00:25:44,359
Speaker 1: When him and Cuomo start arguing, I was saying, like,

509
00:25:44,480 --> 00:25:47,000
Speaker 1: I feel like I'm like a bus terminal in like Manhattan.

510
00:25:47,080 --> 00:25:49,879
Speaker 2: Do you know that ar Do you know that clip

511
00:25:49,960 --> 00:25:52,520
Speaker 2: that went viral of like two guys like not fighting,

512
00:25:52,600 --> 00:25:54,639
Speaker 2: but like flipping each other off on the street. Do

513
00:25:54,720 --> 00:25:56,440
Speaker 2: you remember that? That's them.

514
00:25:57,960 --> 00:26:02,040
Speaker 1: Almost getting down but yeah, yeah, so fuck you, hey,

515
00:26:02,320 --> 00:26:05,560
Speaker 1: fuck you. So Cuomo said, yeah, you need to be

516
00:26:05,680 --> 00:26:08,879
Speaker 1: serious and mature, and I guess his version of that

517
00:26:09,359 --> 00:26:12,200
Speaker 1: was too. So while this was happening, while the debate

518
00:26:12,320 --> 00:26:17,160
Speaker 1: was happening, twenty minutes into it, Cuomo's official account tweeted

519
00:26:17,200 --> 00:26:22,199
Speaker 1: this AI generated video about the quote criminals for zoron

520
00:26:22,320 --> 00:26:26,240
Speaker 1: Mumdani and the criminals in this video are just a

521
00:26:26,359 --> 00:26:30,000
Speaker 1: bunch of racist stereotypes, like a black pimp that looked

522
00:26:30,040 --> 00:26:33,560
Speaker 1: like fucking Huggy Bear from Starsky and Hutch Like not like.

523
00:26:33,600 --> 00:26:36,800
Speaker 2: You're like what well, because it was AI generated, so

524
00:26:36,840 --> 00:26:39,479
Speaker 2: it was based on like all of these fucking awful

525
00:26:39,600 --> 00:26:42,159
Speaker 2: tropes and whatever racist shit you plug in.

526
00:26:42,480 --> 00:26:44,560
Speaker 4: Yeah, the actor, you guys say that meme that was

527
00:26:44,680 --> 00:26:48,119
Speaker 4: like shout out to AI for proving the existence of

528
00:26:48,200 --> 00:26:50,840
Speaker 4: a soul by showing us what stuff without.

529
00:26:50,640 --> 00:26:53,840
Speaker 1: It looks like, yeah, amazing, no for real because you

530
00:26:53,960 --> 00:26:57,080
Speaker 1: can see it immediately. But again, then there's like a

531
00:26:57,200 --> 00:26:59,960
Speaker 1: black man in like a Kafia shoplifting. I'm like, Wow,

532
00:27:00,080 --> 00:27:02,480
Speaker 1: you're really layering this one on thick like you're getting

533
00:27:02,520 --> 00:27:05,360
Speaker 1: you're doing multiple attacks with just this dude. I'll play

534
00:27:05,359 --> 00:27:08,560
Speaker 1: a little bit of it because it's it's so it's

535
00:27:08,640 --> 00:27:12,080
Speaker 1: just so fucking bad, not just from it, like obviously

536
00:27:12,400 --> 00:27:15,560
Speaker 1: the messaging is filed, but the fucking it starts off

537
00:27:15,640 --> 00:27:18,640
Speaker 1: with Zaron eating rice with his hands, which I think

538
00:27:18,640 --> 00:27:20,040
Speaker 1: for anybody who's you know, who.

539
00:27:19,960 --> 00:27:22,440
Speaker 2: Would fucking what kind of culture would do that?

540
00:27:23,040 --> 00:27:24,960
Speaker 1: Who would why would they?

541
00:27:25,800 --> 00:27:27,720
Speaker 2: Why would they do that?

542
00:27:28,200 --> 00:27:32,760
Speaker 1: Yeah, again, very fucking just like top level xenophobic attack

543
00:27:33,440 --> 00:27:36,800
Speaker 1: Becau you know who this is obviously geared towards. Because

544
00:27:36,800 --> 00:27:38,439
Speaker 1: again I think Quom was just like, I don't know, man,

545
00:27:38,520 --> 00:27:40,800
Speaker 1: the racists, I don't care, Like even if we're ideologically

546
00:27:40,880 --> 00:27:44,480
Speaker 1: not in line politically maybe on xenophobia, wheel I feel

547
00:27:44,560 --> 00:27:47,159
Speaker 1: like he is like he doesn't give a shit. No, no,

548
00:27:47,280 --> 00:27:49,640
Speaker 1: I mean, it's pure desperation. I think just now maybe

549
00:27:49,680 --> 00:27:52,879
Speaker 1: he was like, ah, we'll get we'll gradually turn up

550
00:27:52,920 --> 00:27:55,159
Speaker 1: the racism and then we'll get to an eleven by

551
00:27:55,160 --> 00:27:55,480
Speaker 1: the day.

552
00:27:56,119 --> 00:27:58,560
Speaker 2: You know, brother, We're getting right there right now.

553
00:28:00,320 --> 00:28:02,840
Speaker 1: So here's here's a bit of the ad because it's

554
00:28:04,000 --> 00:28:04,840
Speaker 1: have either of you seen it?

555
00:28:05,280 --> 00:28:05,480
Speaker 2: Yes?

556
00:28:05,920 --> 00:28:07,760
Speaker 1: Yeah, okay, just so people.

557
00:28:07,560 --> 00:28:12,960
Speaker 2: Can you aioron like freaks me the fuck out, mam.

558
00:28:13,040 --> 00:28:13,960
Speaker 1: Donnie isn't crazy.

559
00:28:14,200 --> 00:28:16,600
Speaker 2: He's just trying to even the play in field, you know.

560
00:28:16,680 --> 00:28:19,840
Speaker 1: Give everyone a fair shot. Sure he said multiple times

561
00:28:19,880 --> 00:28:21,639
Speaker 1: we need to defund the police, but that was just

562
00:28:21,720 --> 00:28:24,040
Speaker 1: a metaphor. And yes he did say crime like I'm

563
00:28:24,080 --> 00:28:25,520
Speaker 1: pretty sure that had to have been off of like

564
00:28:25,560 --> 00:28:27,440
Speaker 1: a black spilitation film because it looked like that was

565
00:28:27,480 --> 00:28:31,840
Speaker 1: shot in panavision or like that was like the film quality. Okay,

566
00:28:31,880 --> 00:28:34,440
Speaker 1: so go on. These are all the people, Uh there's

567
00:28:34,560 --> 00:28:39,360
Speaker 1: white men, white ladies, men who are saying very scary. Yeah,

568
00:28:39,360 --> 00:28:42,000
Speaker 1: who's saying he's all good? Crime is okay. The whole

569
00:28:42,040 --> 00:28:43,520
Speaker 1: point of this thing is to be like, look at

570
00:28:43,520 --> 00:28:46,400
Speaker 1: all these criminals that want zoron Mumdani. These are the

571
00:28:46,440 --> 00:28:49,120
Speaker 1: people who will benefit from his mayoral election.

572
00:28:49,400 --> 00:28:52,680
Speaker 2: Time is a social construct, but that was also a metaphor.

573
00:28:53,000 --> 00:28:57,880
Speaker 7: His main backer, the democratic socialist ideas are common sense

574
00:28:58,240 --> 00:28:58,640
Speaker 7: such a.

575
00:28:58,840 --> 00:29:04,680
Speaker 1: See criminalizing this demeanors like shoplifting. So this guy, as

576
00:29:04,720 --> 00:29:06,479
Speaker 1: soon as he says that, he puts a like an

577
00:29:06,600 --> 00:29:08,880
Speaker 1: N ninety five mask on and then a kafir around

578
00:29:08,920 --> 00:29:13,240
Speaker 1: his neck because all shoplifters are a propost Indian third degree.

579
00:29:13,120 --> 00:29:18,040
Speaker 6: Flifting is hamas trespassing prostitution.

580
00:29:18,920 --> 00:29:21,480
Speaker 1: This guy's opens up a van full of and drug

581
00:29:21,760 --> 00:29:26,680
Speaker 1: driving with plans to decriminalize all drugs. Ma'am, Donnie will

582
00:29:26,680 --> 00:29:30,719
Speaker 1: be a job creator for drug deal drug dealers. Instead

583
00:29:30,720 --> 00:29:32,840
Speaker 1: of helping us homeless get off the streets and into

584
00:29:32,880 --> 00:29:35,280
Speaker 1: the mental health facilities we need, he wants to give

585
00:29:35,320 --> 00:29:38,160
Speaker 1: us safe injection sites to do crack. Okay, I don't

586
00:29:38,160 --> 00:29:40,560
Speaker 1: know if you do crack at a safe injection site,

587
00:29:40,680 --> 00:29:43,120
Speaker 1: but okay, uh, I.

588
00:29:43,160 --> 00:29:45,160
Speaker 2: Mean you don't because that's what I've been doing.

589
00:29:46,160 --> 00:29:49,280
Speaker 1: But like this thing is such just slopped together.

590
00:29:49,800 --> 00:29:52,520
Speaker 2: But also it should be fucking illegal to use your

591
00:29:52,600 --> 00:29:57,520
Speaker 2: opponent's uh likeness. Likeness. Yeah, with him saying shit, he

592
00:29:57,600 --> 00:30:01,560
Speaker 2: didn't say has an Ai figure, that's fucking crazy.

593
00:30:02,080 --> 00:30:05,440
Speaker 1: I think this is the the ad went down almost

594
00:30:05,440 --> 00:30:08,880
Speaker 1: as quickly as it went up here. What the fuck? Yeah? No, truly,

595
00:30:09,040 --> 00:30:11,920
Speaker 1: I mean this is just but that is like it clearly.

596
00:30:11,680 --> 00:30:15,560
Speaker 4: Shows he's scared because Zoron was like, you are hiding.

597
00:30:15,320 --> 00:30:18,640
Speaker 1: A child, right, exactly, and I don't know if that

598
00:30:18,760 --> 00:30:20,480
Speaker 1: really helped. Let me see, let's see how.

599
00:30:20,440 --> 00:30:24,680
Speaker 2: The wa wait he he draked him? What happened?

600
00:30:25,160 --> 00:30:28,560
Speaker 4: No, yeah, just that he like like said something like

601
00:30:29,160 --> 00:30:29,920
Speaker 4: come on stage.

602
00:30:30,080 --> 00:30:36,080
Speaker 1: Yeah, depending on who's pulling you look at it's not

603
00:30:36,480 --> 00:30:40,960
Speaker 1: looking good right now. The sum he's up by eight points,

604
00:30:41,040 --> 00:30:43,760
Speaker 1: others he's up as many as twenty four points on

605
00:30:43,880 --> 00:30:48,840
Speaker 1: a Fox News Yeah yeah yeah. So again, I'm not

606
00:30:48,960 --> 00:30:52,520
Speaker 1: sure if these like bad faith racist attacks work because again,

607
00:30:52,680 --> 00:30:54,520
Speaker 1: they tried all this stuff. Like like, if you think

608
00:30:54,520 --> 00:30:57,520
Speaker 1: about this ad, they were doing every single thing that

609
00:30:57,760 --> 00:30:59,880
Speaker 1: like the establishment tries to do to anyone to be

610
00:31:00,400 --> 00:31:05,160
Speaker 1: they're Muslim, they're socialists, they want you know what I mean.

611
00:31:05,240 --> 00:31:08,480
Speaker 2: Like, it's so fucking weird. They're doing this in New York,

612
00:31:08,600 --> 00:31:12,040
Speaker 2: one of the most diverse cities on the fucking planet. Like,

613
00:31:12,760 --> 00:31:15,880
Speaker 2: and you're saying that you're speaking for New Yorkers, You're

614
00:31:15,920 --> 00:31:18,600
Speaker 2: saying that you're speaking for that population of people who

615
00:31:18,880 --> 00:31:21,720
Speaker 2: even compared to La where we don't even interact on

616
00:31:21,800 --> 00:31:24,720
Speaker 2: the subway, and like neighborhoods are segregated and stuff, like

617
00:31:24,840 --> 00:31:26,959
Speaker 2: sure they're segregation and stuff in New York, but it's

618
00:31:27,000 --> 00:31:29,440
Speaker 2: so dense you interact with people and they become more

619
00:31:29,520 --> 00:31:31,720
Speaker 2: human to you no matter what, you know what I mean.

620
00:31:31,960 --> 00:31:35,400
Speaker 2: And so it's like it's nuts that he's like driving

621
00:31:35,560 --> 00:31:39,280
Speaker 2: into the city in his fucking giant suv and and

622
00:31:39,400 --> 00:31:42,760
Speaker 2: then being like, I know what, this city would love racism.

623
00:31:43,120 --> 00:31:43,840
Speaker 1: Well all these.

624
00:31:43,760 --> 00:31:47,720
Speaker 4: People too, It's like the eighties are still happening for them. Yeah,

625
00:31:48,240 --> 00:31:50,720
Speaker 4: that's like. Also, like when Trump talks about la you

626
00:31:50,800 --> 00:31:55,440
Speaker 4: can tell he's like, right, building these skyscrapers downtown or whatever.

627
00:31:55,640 --> 00:31:58,280
Speaker 4: It's like time is not passed for him.

628
00:31:58,360 --> 00:32:02,280
Speaker 7: He's like, you remember the old sub in California RTD buses?

629
00:32:03,240 --> 00:32:06,360
Speaker 7: What the fuck dude, you're talking about the Rapid Transit

630
00:32:06,480 --> 00:32:08,800
Speaker 7: District buses? God have you've thought about that?

631
00:32:08,880 --> 00:32:12,320
Speaker 1: Shi in ages? Uh that logo is kind of wild though,

632
00:32:12,640 --> 00:32:16,680
Speaker 1: Uh yeah, I don't know. I mean, I'm assuming this

633
00:32:16,800 --> 00:32:18,200
Speaker 1: is going to end how we all think it is,

634
00:32:18,320 --> 00:32:20,600
Speaker 1: with mom Donnie winning and then we'll go from there.

635
00:32:20,680 --> 00:32:27,120
Speaker 2: But I'm honestly like, like I'm worried. Like, obviously Islamophobia

636
00:32:27,320 --> 00:32:30,360
Speaker 2: is rampant in this country's and it has been for

637
00:32:30,480 --> 00:32:35,320
Speaker 2: a long time, but I'm I'm not I'm not worried

638
00:32:35,320 --> 00:32:39,080
Speaker 2: about the race. I'm worried about, like the people that

639
00:32:39,800 --> 00:32:43,480
Speaker 2: Cuomo and all of these attack ads and the global

640
00:32:43,560 --> 00:32:48,920
Speaker 2: spot actual are inciting, yeah, against Zorn because political violence

641
00:32:49,080 --> 00:32:57,320
Speaker 2: is becoming more prominent in the Yeah, because there's so

642
00:32:57,440 --> 00:32:58,160
Speaker 2: much Antifa.

643
00:32:58,680 --> 00:32:59,960
Speaker 1: Yeah, yeah, i mean they're all over.

644
00:33:00,080 --> 00:33:04,240
Speaker 2: But yeah, that's like anytime they come after like progressives

645
00:33:04,320 --> 00:33:07,960
Speaker 2: or leftist candidates. I'm less worried about the policy and

646
00:33:08,080 --> 00:33:11,360
Speaker 2: political leins because like, clearly the people want what he's saying,

647
00:33:11,800 --> 00:33:15,000
Speaker 2: and I'm more worried about like the instances of violence

648
00:33:15,120 --> 00:33:17,920
Speaker 2: that the Yeah, that these fucking crazy people in site.

649
00:33:18,240 --> 00:33:20,920
Speaker 1: Right, because rhetorically, when everything is just like and all

650
00:33:21,000 --> 00:33:25,280
Speaker 1: these people are violent or whatever, you know, again, you're.

651
00:33:25,160 --> 00:33:28,680
Speaker 4: Trying to get a civil war going. That's all we've

652
00:33:28,680 --> 00:33:32,960
Speaker 4: been doing this year, is like trying to get somebody

653
00:33:33,080 --> 00:33:35,640
Speaker 4: to kick it off, and the left will fall for it.

654
00:33:35,760 --> 00:33:38,080
Speaker 4: So they're just like, maybe maybe our side can do it.

655
00:33:38,600 --> 00:33:38,840
Speaker 1: Yeah.

656
00:33:38,920 --> 00:33:42,120
Speaker 2: And also, like the part that scared me the most

657
00:33:42,240 --> 00:33:45,160
Speaker 2: was him speaking in the fucking ad like there are

658
00:33:45,240 --> 00:33:47,760
Speaker 2: people where they will believe that, you know what I mean,

659
00:33:47,920 --> 00:33:50,600
Speaker 2: they will believe that he said that. And also this

660
00:33:50,800 --> 00:33:52,960
Speaker 2: is a dude who's like in the streets all the

661
00:33:53,040 --> 00:33:56,120
Speaker 2: time is actually accessible.

662
00:33:56,160 --> 00:33:58,360
Speaker 1: I'm like, yeah, yep, yep. I can only imagine what

663
00:33:58,600 --> 00:34:03,760
Speaker 1: his election and you know, ascendants into the office will

664
00:34:03,800 --> 00:34:05,800
Speaker 1: actually do and what the rhetoric looks like at that

665
00:34:05,880 --> 00:34:08,040
Speaker 1: point when he if he's elected.

666
00:34:08,280 --> 00:34:10,360
Speaker 4: Like I did see what The New York Times opinion

667
00:34:10,480 --> 00:34:15,279
Speaker 4: section ran another incredible opinion piece today. Oh god, we

668
00:34:15,400 --> 00:34:20,400
Speaker 4: editorial board, democrats need to move to the center's Oh.

669
00:34:20,360 --> 00:34:25,040
Speaker 1: Yeah, yeah, some good question mark. Yeah, that's where the

670
00:34:25,160 --> 00:34:25,799
Speaker 1: votes are at.

671
00:34:26,239 --> 00:34:27,920
Speaker 4: It was funny because even the people in the comments

672
00:34:27,960 --> 00:34:30,160
Speaker 4: were like, bro, yeah.

673
00:34:30,320 --> 00:34:33,640
Speaker 1: Shut up. They're like, it says you the person who's like,

674
00:34:34,080 --> 00:34:37,640
Speaker 1: hasn't fucking know nothing on the line here by existing

675
00:34:37,680 --> 00:34:41,560
Speaker 1: in this country. Okay, let's move on. Also, just because

676
00:34:41,960 --> 00:34:45,840
Speaker 1: Stranger Things is finally coming to an end, What the

677
00:34:46,000 --> 00:34:49,040
Speaker 1: last time we had fucking was it fucking three years ago?

678
00:34:49,080 --> 00:34:51,640
Speaker 1: I feel like it was twenty twenty two. I already

679
00:34:51,760 --> 00:34:54,040
Speaker 1: this happens every time Stranger Things comes out. I forget

680
00:34:54,120 --> 00:34:56,239
Speaker 1: what the fuck even happened last season? And then I

681
00:34:56,320 --> 00:34:57,960
Speaker 1: start watching it and I'm like, I don't know, I

682
00:34:57,960 --> 00:34:59,200
Speaker 1: don't know what's going on. What happened?

683
00:34:59,800 --> 00:34:59,840
Speaker 6: What?

684
00:35:00,200 --> 00:35:00,520
Speaker 1: What is this?

685
00:35:00,719 --> 00:35:03,520
Speaker 2: I think it it feels like when someone posts like

686
00:35:03,600 --> 00:35:06,320
Speaker 2: a picture of a celebrity and they're in black and

687
00:35:06,320 --> 00:35:07,879
Speaker 2: white and you're like, oh my god, are they dead?

688
00:35:08,280 --> 00:35:10,280
Speaker 2: And then you're like, oh no, it's just another season.

689
00:35:10,600 --> 00:35:12,800
Speaker 1: Just a cool yeah, just a cool just a cool photo.

690
00:35:13,239 --> 00:35:17,160
Speaker 1: But yeah, Now, like I said, these we've we've aged

691
00:35:17,200 --> 00:35:20,120
Speaker 1: along with the cast. The first chunk of this season

692
00:35:20,200 --> 00:35:24,040
Speaker 1: comes out in November, and then more episodes Christmas Day,

693
00:35:24,160 --> 00:35:27,800
Speaker 1: and then a series finale on New Year's Eve, because

694
00:35:27,920 --> 00:35:31,000
Speaker 1: everyone is going to clear out their fucking New Year's

695
00:35:31,040 --> 00:35:33,279
Speaker 1: Eve calendar to see what happens. I know plenty of

696
00:35:33,320 --> 00:35:35,759
Speaker 1: people probably will, but I couldn't think of something on

697
00:35:35,840 --> 00:35:38,480
Speaker 1: what I'd want to do less. But there were reports

698
00:35:38,520 --> 00:35:41,000
Speaker 1: that like the show's creators wanted like the Duffer Brothers,

699
00:35:41,040 --> 00:35:43,880
Speaker 1: they wanted to put the finale in movie theaters.

700
00:35:43,960 --> 00:35:44,680
Speaker 4: I think they're doing it.

701
00:35:45,160 --> 00:35:47,160
Speaker 1: They are. I think they are now, right because at

702
00:35:47,239 --> 00:35:51,000
Speaker 1: first Netflix was like, nah, nah, we're not doing it.

703
00:35:51,160 --> 00:35:53,600
Speaker 1: We're not doing it, and everyone was like, uh, you

704
00:35:53,840 --> 00:35:56,759
Speaker 1: just put K pop Demon Hunters in the theaters and

705
00:35:56,880 --> 00:35:58,200
Speaker 1: it did really well. What do you what do you

706
00:35:58,280 --> 00:36:00,839
Speaker 1: mean you don't You're not doing it? Now now they've

707
00:36:00,880 --> 00:36:02,640
Speaker 1: come back around and by like, oh, yeah, we gotta

708
00:36:02,640 --> 00:36:04,480
Speaker 1: probably make a little money on that. We'll probably make

709
00:36:04,520 --> 00:36:06,080
Speaker 1: a little money in that. So now it's for just

710
00:36:06,200 --> 00:36:09,799
Speaker 1: two days, December thirty first, and I guess New Year's Day.

711
00:36:10,719 --> 00:36:12,759
Speaker 1: So it doesn't mean you're gonna see it before anyone else,

712
00:36:12,840 --> 00:36:16,239
Speaker 1: but like, that's that's what they're doing. This is the

713
00:36:16,320 --> 00:36:20,400
Speaker 1: part that's really interesting to meet. So Ted Sarandos, Sarandos,

714
00:36:20,480 --> 00:36:23,600
Speaker 1: however you want to say it. Sarandon, the head of Netflix.

715
00:36:24,200 --> 00:36:26,600
Speaker 1: He was like, again, he's been sort of like at

716
00:36:26,640 --> 00:36:28,400
Speaker 1: the head of like being like, well, I don't know

717
00:36:28,440 --> 00:36:31,279
Speaker 1: about the theatrical release. Earlier, he was quoted by saying,

718
00:36:31,360 --> 00:36:34,279
Speaker 1: quote that driving folks to a theater is just not

719
00:36:34,440 --> 00:36:37,600
Speaker 1: our business, and he's called movie theaters an outdated concept.

720
00:36:37,760 --> 00:36:40,360
Speaker 1: This is his full quote. He said, we're in a

721
00:36:40,440 --> 00:36:43,040
Speaker 1: period of transition. Folks grew up thinking I want to

722
00:36:43,080 --> 00:36:46,759
Speaker 1: make movies on a gigantic screen and have strangers watch them,

723
00:36:47,040 --> 00:36:48,920
Speaker 1: and to have them play in the theater for two

724
00:36:49,000 --> 00:36:51,840
Speaker 1: months and people cry and sold out shows. It's an

725
00:36:51,880 --> 00:36:52,920
Speaker 1: outdated concept.

726
00:36:54,080 --> 00:36:57,239
Speaker 2: I truly think people who do this thing where they

727
00:36:57,520 --> 00:37:00,880
Speaker 2: like eliminate third what is it called third spaces or whatever,

728
00:37:01,080 --> 00:37:04,320
Speaker 2: or places where community can gather and like interact and

729
00:37:04,400 --> 00:37:06,600
Speaker 2: have a shared experience or like some of the most

730
00:37:06,680 --> 00:37:12,000
Speaker 2: evil people, because that's like what really ruins the strength

731
00:37:12,400 --> 00:37:15,200
Speaker 2: of our populace is like banding together. And I think

732
00:37:15,320 --> 00:37:17,520
Speaker 2: and I fucking know they know that all they care

733
00:37:17,560 --> 00:37:21,120
Speaker 2: about is engaging us on devices and keeping our attention

734
00:37:21,480 --> 00:37:24,920
Speaker 2: and not like communing with each other, And I like,

735
00:37:25,200 --> 00:37:28,200
Speaker 2: legit think it's evil, Like I think it's bad.

736
00:37:28,560 --> 00:37:31,400
Speaker 4: I do think that the AI slot problem has gotten

737
00:37:31,480 --> 00:37:35,120
Speaker 4: so bad that I'm now optimistically thinking people will get

738
00:37:35,160 --> 00:37:38,719
Speaker 4: offline and go back to reality because I do think

739
00:37:38,760 --> 00:37:41,000
Speaker 4: it's also just like there's a limit of how much

740
00:37:41,160 --> 00:37:42,319
Speaker 4: entertainment you can take.

741
00:37:42,880 --> 00:37:45,560
Speaker 2: Yeah, I mean, isn't like jen Alpha doing that where

742
00:37:45,560 --> 00:37:47,960
Speaker 2: they're like not on social media as much because they're

743
00:37:48,080 --> 00:37:51,480
Speaker 2: like rediscovering touching grass as a generation.

744
00:37:51,920 --> 00:37:54,520
Speaker 4: They're also going outside and building a treehouse.

745
00:37:54,960 --> 00:37:58,080
Speaker 2: Yeah, what is that in the sky the sun?

746
00:37:58,840 --> 00:38:03,920
Speaker 1: I was just a Jason Propaganda petties Hed had a

747
00:38:03,960 --> 00:38:06,960
Speaker 1: poetry reading yesterday I went to and his his new

748
00:38:07,000 --> 00:38:10,279
Speaker 1: album is called I Think the Beautiful Endlings. And but

749
00:38:10,520 --> 00:38:13,440
Speaker 1: then endling is like a group of a species that

750
00:38:13,640 --> 00:38:17,160
Speaker 1: is the last one to exist before extinction, and he

751
00:38:17,480 --> 00:38:19,440
Speaker 1: was bringing up he's like, you know, and we think

752
00:38:19,440 --> 00:38:21,640
Speaker 1: about this all the time, but like millennials really are

753
00:38:21,719 --> 00:38:24,480
Speaker 1: the last people who knew the pre Internet world, like

754
00:38:24,640 --> 00:38:27,560
Speaker 1: fully knew the pre Internet world. No, that's true.

755
00:38:27,920 --> 00:38:31,440
Speaker 4: Yeah, you're like digital digital migrants, not digital natives.

756
00:38:31,800 --> 00:38:33,680
Speaker 1: Yeah. Right, when I think about that, I'm like, god,

757
00:38:34,400 --> 00:38:36,960
Speaker 1: damn no. And it's so true, Like they do want

758
00:38:37,000 --> 00:38:39,919
Speaker 1: everybody to just they want their version of Wally where

759
00:38:40,360 --> 00:38:42,600
Speaker 1: you're just you put your goggles on and look at

760
00:38:42,640 --> 00:38:44,719
Speaker 1: these images. The thing about A I was also reading

761
00:38:44,760 --> 00:38:47,360
Speaker 1: recently was a lot of the data people are like,

762
00:38:47,880 --> 00:38:51,000
Speaker 1: you know, like this thing hoovers up data very quickly,

763
00:38:51,120 --> 00:38:54,040
Speaker 1: and we're gonna run out of high quality data to

764
00:38:54,200 --> 00:38:57,400
Speaker 1: train the ai AI on by like some point in

765
00:38:57,440 --> 00:39:00,319
Speaker 1: twenty twenty six or something. And they're like saying, at

766
00:39:00,360 --> 00:39:04,200
Speaker 1: that point, it will then just begin training on other bullshits.

767
00:39:04,239 --> 00:39:08,080
Speaker 1: I think there, Yeah, yeah, no, one, I don't think

768
00:39:08,160 --> 00:39:14,440
Speaker 1: the Alabama of the Internet just in breathing. Yeah, just

769
00:39:14,719 --> 00:39:20,080
Speaker 1: a terrible AI centipede human centipede just feeding on itself.

770
00:39:20,520 --> 00:39:22,520
Speaker 1: But yeah, I mean, like that's another huge issue where

771
00:39:22,520 --> 00:39:25,880
Speaker 1: it's almost like it's I don't think I've seen a

772
00:39:25,920 --> 00:39:27,799
Speaker 1: few people sort of positive this, but it's like it's

773
00:39:28,000 --> 00:39:30,400
Speaker 1: you know, for AI to be anything they wanted to be, Like,

774
00:39:30,520 --> 00:39:34,400
Speaker 1: you also have to actually, human creativity has to be sustained.

775
00:39:34,480 --> 00:39:38,160
Speaker 1: Human innovation has to be sustained, because this isn't creating

776
00:39:38,320 --> 00:39:43,040
Speaker 1: new stuff. It's just training on things that exist. And yeah, yeah,

777
00:39:43,080 --> 00:39:45,040
Speaker 1: we got to get back in the lab. Hook some

778
00:39:45,160 --> 00:39:47,719
Speaker 1: electrodes up to a front. I'll get back in the lab.

779
00:39:48,520 --> 00:39:51,879
Speaker 2: Yeah, just give me a few seconds. Okay, I'm walking over.

780
00:39:55,520 --> 00:40:00,400
Speaker 1: Yeah, I don't know if that's you noticed he looks

781
00:40:00,440 --> 00:40:03,719
Speaker 1: I mean he looks like a character from like night

782
00:40:03,840 --> 00:40:06,840
Speaker 1: Court or some shit. Yeah, it's like, here comes courteously

783
00:40:07,000 --> 00:40:09,680
Speaker 1: with a vigilante racist Again he's like, I look what

784
00:40:09,760 --> 00:40:13,360
Speaker 1: I brought in. Nice fucking beret. I know it was

785
00:40:13,440 --> 00:40:13,839
Speaker 1: so great.

786
00:40:14,640 --> 00:40:17,320
Speaker 2: Maybe I'll go for him as or as him for Halloween.

787
00:40:18,160 --> 00:40:20,920
Speaker 1: Oh yeah, could be you got a Halloween costume?

788
00:40:21,440 --> 00:40:24,000
Speaker 4: No, I'm just gonna be like, do you have you

789
00:40:24,040 --> 00:40:24,800
Speaker 4: got any ideas?

790
00:40:24,960 --> 00:40:26,239
Speaker 1: Do you do costumes every year?

791
00:40:27,960 --> 00:40:28,280
Speaker 4: Really?

792
00:40:28,640 --> 00:40:28,839
Speaker 1: Yeah?

793
00:40:28,880 --> 00:40:33,160
Speaker 4: I have a strong, hard rule that's like you don't

794
00:40:33,200 --> 00:40:34,759
Speaker 4: you have to not have to explain it?

795
00:40:35,400 --> 00:40:39,200
Speaker 2: Yeah, Yeah, I'm the opposite where I'm like it's so obscure.

796
00:40:39,239 --> 00:40:41,440
Speaker 2: I'm like, can you guess? Can you guess what it is?

797
00:40:41,760 --> 00:40:43,160
Speaker 2: I've been aligned too much.

798
00:40:43,360 --> 00:40:46,440
Speaker 4: And he's like, dude, you know what I might do

799
00:40:46,560 --> 00:40:48,239
Speaker 4: though that everyone just keeps telling me to do is

800
00:40:48,320 --> 00:40:49,160
Speaker 4: be chapel roone.

801
00:40:49,760 --> 00:40:54,319
Speaker 1: Oh yeah sure, easy, yeah yeah, like yallow pony. Yeah,

802
00:40:54,360 --> 00:40:56,000
Speaker 1: but you got you got all the clothing. I mean,

803
00:40:56,040 --> 00:40:57,520
Speaker 1: that's that's some don't I don't know.

804
00:40:58,239 --> 00:41:01,040
Speaker 4: She looks like me, it's not no, but you don't.

805
00:41:01,120 --> 00:41:05,680
Speaker 1: You don't do the makeup something on stage, you know

806
00:41:05,719 --> 00:41:07,880
Speaker 1: what I mean? Stage A little fun.

807
00:41:07,800 --> 00:41:10,080
Speaker 4: Part, a little taxi cab costume or something.

808
00:41:10,400 --> 00:41:12,680
Speaker 1: Yeah, yeah, yeah, I might. I was thinking of just

809
00:41:12,680 --> 00:41:14,960
Speaker 1: because there's little energy just being Leonardo DiCaprio in one

810
00:41:14,960 --> 00:41:15,600
Speaker 1: battle after.

811
00:41:15,440 --> 00:41:19,759
Speaker 2: Another, there's going to be like a lot of costumes,

812
00:41:20,040 --> 00:41:20,360
Speaker 2: like I know.

813
00:41:20,440 --> 00:41:21,600
Speaker 1: And then I was like, this is going to be

814
00:41:21,719 --> 00:41:24,960
Speaker 1: every fucking yeah, person I hates costume.

815
00:41:25,239 --> 00:41:29,800
Speaker 2: You should be the creepy colonel. Oh yeah, Sean Penn's

816
00:41:29,840 --> 00:41:31,200
Speaker 2: character and then you can walk all funny.

817
00:41:31,520 --> 00:41:34,640
Speaker 1: Oh yeah, just be fucking he was. I think he

818
00:41:34,760 --> 00:41:37,120
Speaker 1: was auditioning to play r f K in an upcoming film.

819
00:41:37,880 --> 00:41:41,400
Speaker 4: Literally, I was like, they're just they're the same shade.

820
00:41:41,560 --> 00:41:44,920
Speaker 1: Yeah exactly, they're the same. What are you going to be?

821
00:41:46,120 --> 00:41:51,520
Speaker 2: I don't know, honestly. I also I miss like some

822
00:41:51,680 --> 00:41:54,719
Speaker 2: Halloween parties, but it's also the Volley, So I'm going

823
00:41:54,800 --> 00:41:57,520
Speaker 2: to like a queer the Volley on Saturday, so that

824
00:41:57,640 --> 00:42:01,200
Speaker 2: might be my instead of Halloween. I'm like the stuff

825
00:42:02,320 --> 00:42:04,480
Speaker 2: that was queer Indian.

826
00:42:08,440 --> 00:42:11,560
Speaker 1: Somebody just goes up to go, hey, great costume queer Indian.

827
00:42:11,640 --> 00:42:17,600
Speaker 1: Right Yeah, yeah, cool, you got a roommate. Yeah right,

828
00:42:19,320 --> 00:42:21,200
Speaker 1: someone says that to you on November fifth.

829
00:42:21,800 --> 00:42:25,560
Speaker 4: Yeah, yeah, we'll I'll get masks and kefias and go

830
00:42:25,719 --> 00:42:28,239
Speaker 4: as the shoplifter from the Cuomo AI ad.

831
00:42:28,520 --> 00:42:29,480
Speaker 1: Oh shit, my.

832
00:42:29,600 --> 00:42:31,800
Speaker 2: God, I'm going to be the drunk lady, the drunk

833
00:42:32,400 --> 00:42:34,000
Speaker 2: fifties mom that's driving.

834
00:42:34,280 --> 00:42:36,640
Speaker 1: Yeah yeah, I'll actually just put a suit on and

835
00:42:36,680 --> 00:42:38,840
Speaker 1: I'll eat rice out of a bowl with my hands. Okay,

836
00:42:39,040 --> 00:42:42,120
Speaker 1: and people will know that I'm an AI slapped racist

837
00:42:42,160 --> 00:42:45,480
Speaker 1: propaganda video. Okay, let's take another break and we come back.

838
00:42:46,160 --> 00:42:48,800
Speaker 1: Let's talk a little bit more about some film, because

839
00:42:48,880 --> 00:42:52,479
Speaker 1: Josh Saftie's Marty Supreme just it's getting a lot of talk,

840
00:42:52,600 --> 00:42:55,160
Speaker 1: but more so because I want to talk about Kevin O'Leary,

841
00:42:55,239 --> 00:43:09,239
Speaker 1: who fucking sucks. Right after this and we're back. So

842
00:43:09,480 --> 00:43:12,680
Speaker 1: one of the pretty highly anticipated films of this year

843
00:43:12,840 --> 00:43:19,120
Speaker 1: is Josh Saftie's Marty Supreme with Tim Atay Challamee Guicho,

844
00:43:19,880 --> 00:43:22,680
Speaker 1: whose daughter Apple we talked about this earlier this week. Apple,

845
00:43:22,800 --> 00:43:25,560
Speaker 1: we got our first look at Apple, Martin singing.

846
00:43:25,400 --> 00:43:27,759
Speaker 2: I would have named her Pair, but yeah, I would

847
00:43:27,800 --> 00:43:28,080
Speaker 2: have too.

848
00:43:28,760 --> 00:43:31,880
Speaker 1: God. Pair would have been worse actually than Apple somehow,

849
00:43:32,239 --> 00:43:33,920
Speaker 1: because Apple's already a fucked up name.

850
00:43:33,920 --> 00:43:34,200
Speaker 2: I don't know.

851
00:43:34,280 --> 00:43:36,600
Speaker 4: I heard they named her Apple because of Steve Jobs,

852
00:43:36,640 --> 00:43:38,000
Speaker 4: which makes it maybe the worst.

853
00:43:38,640 --> 00:43:40,080
Speaker 1: That was my I was joking like that. I was like,

854
00:43:40,160 --> 00:43:42,000
Speaker 1: she could really lean into this and get a deal,

855
00:43:42,160 --> 00:43:44,880
Speaker 1: you know what I mean? With Tim Cook or Apple Onia.

856
00:43:44,960 --> 00:43:47,160
Speaker 1: I don't know what the fuck it is anyway. I

857
00:43:47,200 --> 00:43:49,400
Speaker 1: think Tyler the creator is also in it too, or

858
00:43:49,520 --> 00:43:52,560
Speaker 1: now sorry Tyler Okonma because he's you know, he's an

859
00:43:52,560 --> 00:43:56,960
Speaker 1: actor now, yes, yes, yes, but anyway, when so, people

860
00:43:57,120 --> 00:43:59,680
Speaker 1: showed like we're watching the trailer, specifically a lot of

861
00:43:59,719 --> 00:44:03,200
Speaker 1: Candi people because they are very very aware of Kevin O'Leary,

862
00:44:03,320 --> 00:44:07,000
Speaker 1: mister Wonderful from Shark Tank's ass Wholeness. People were like,

863
00:44:07,080 --> 00:44:09,440
Speaker 1: what the fuck is this guy doing in this movie?

864
00:44:10,080 --> 00:44:12,680
Speaker 1: And again, this guy is known as like Canada's Trump,

865
00:44:12,840 --> 00:44:14,839
Speaker 1: we know him in the US as the shark tank guy.

866
00:44:14,920 --> 00:44:18,640
Speaker 1: That's Maga basically always doing something to try and defend Trump,

867
00:44:18,800 --> 00:44:21,960
Speaker 1: like even if it's the grossest defense, which we'll get to.

868
00:44:22,520 --> 00:44:24,879
Speaker 1: But just a side note, like he really did try

869
00:44:25,000 --> 00:44:27,560
Speaker 1: to try, Like he tried his hand in politics in Canada,

870
00:44:27,880 --> 00:44:30,120
Speaker 1: and then he had to sue the Canadian government to

871
00:44:30,280 --> 00:44:34,920
Speaker 1: change campaign finance laws to quote, to remove a specific

872
00:44:34,960 --> 00:44:38,000
Speaker 1: thing on limits on political donations in Canada because he

873
00:44:38,120 --> 00:44:41,239
Speaker 1: wanted to pay off his own campaign debt that he

874
00:44:41,360 --> 00:44:44,680
Speaker 1: ran up. And he's like, I can I do this myself?

875
00:44:44,840 --> 00:44:47,359
Speaker 1: It didn't work, Oh my god. But like recently, right

876
00:44:47,719 --> 00:44:50,680
Speaker 1: in July, he was on CNN. The Epstein files were

877
00:44:50,719 --> 00:44:53,279
Speaker 1: stirling around as a topic and during the interview he

878
00:44:53,360 --> 00:44:55,760
Speaker 1: said it's not a big deal anyway because it doesn't

879
00:44:55,800 --> 00:44:59,280
Speaker 1: affect the American economy. He said, quote, the average American

880
00:44:59,440 --> 00:45:01,719
Speaker 1: awake for eighteen hours a day. How many minutes do

881
00:45:01,760 --> 00:45:03,960
Speaker 1: you think they spent they spend worrying about this stuff.

882
00:45:04,280 --> 00:45:07,320
Speaker 1: Maybe they were raped, maybe they weren't. Nobody gives a poop.

883
00:45:07,400 --> 00:45:10,719
Speaker 1: Nobody gives a poop poop poop, worst case scenario. All

884
00:45:10,800 --> 00:45:13,080
Speaker 1: this stuff's true, does that in any way affect the

885
00:45:13,120 --> 00:45:17,520
Speaker 1: American economy? Yikes? Oh, dot com slash, what the fuck

886
00:45:17,560 --> 00:45:19,200
Speaker 1: are you talking about? Yeah?

887
00:45:19,480 --> 00:45:23,720
Speaker 2: So, wait, can I say a real life analogous moment

888
00:45:23,760 --> 00:45:24,600
Speaker 2: that I had with someone?

889
00:45:25,040 --> 00:45:26,600
Speaker 1: Yeh, wait, what do you mean?

890
00:45:27,160 --> 00:45:30,280
Speaker 2: Okay? I like this, well, okay, So I was working

891
00:45:30,480 --> 00:45:34,560
Speaker 2: with this comic and I heard accusations about him, and

892
00:45:34,719 --> 00:45:36,879
Speaker 2: so I called him up and I was like, dude,

893
00:45:36,920 --> 00:45:40,600
Speaker 2: what the fuck? And he was like getting like sweaty,

894
00:45:40,719 --> 00:45:42,960
Speaker 2: defending himself and all this shit. And then and then

895
00:45:43,000 --> 00:45:46,680
Speaker 2: he spirals and he goes even if even if it

896
00:45:46,920 --> 00:45:48,960
Speaker 2: was true, like what, you wouldn't want to work with me?

897
00:45:49,160 --> 00:45:53,520
Speaker 1: And I was like, yeah, what yeah, dude, like exactly.

898
00:45:54,120 --> 00:45:57,720
Speaker 2: It's crazy how people they're like separate the sexual assaulter

899
00:45:58,000 --> 00:45:59,560
Speaker 2: from like the rest of the shit.

900
00:45:59,760 --> 00:46:00,600
Speaker 1: Yeah, that they do.

901
00:46:01,200 --> 00:46:04,239
Speaker 2: I was like, that's the fucking point, dude, No, I

902
00:46:04,280 --> 00:46:04,919
Speaker 2: wouldn't want.

903
00:46:04,840 --> 00:46:07,040
Speaker 4: To work that's also a tell they did it.

904
00:46:08,160 --> 00:46:12,000
Speaker 1: After that, I was like, by you're telling you're telling

905
00:46:12,120 --> 00:46:14,719
Speaker 1: me the person credibly accused you don't want to work

906
00:46:14,760 --> 00:46:14,960
Speaker 1: with me.

907
00:46:15,880 --> 00:46:19,000
Speaker 4: You're like this is my last day on kill Tony. Yeah,

908
00:46:21,840 --> 00:46:23,000
Speaker 4: I'm never coming back.

909
00:46:22,880 --> 00:46:25,759
Speaker 1: To never coming back. You lost to me anyway. So

910
00:46:26,239 --> 00:46:30,720
Speaker 1: there's also like his wife caused a fatal boat crash.

911
00:46:30,920 --> 00:46:32,960
Speaker 1: I was reading about where they were.

912
00:46:33,960 --> 00:46:36,040
Speaker 2: That she's the drunk driver in the AI.

913
00:46:36,920 --> 00:46:39,320
Speaker 1: She was actually the desert. She was the d D.

914
00:46:39,920 --> 00:46:42,799
Speaker 1: She was the d D with her husband and another person.

915
00:46:43,160 --> 00:46:45,320
Speaker 1: They smashed into a boat on a lake that was

916
00:46:45,400 --> 00:46:48,680
Speaker 1: like stargazing, and their defense was well, their lights were

917
00:46:48,719 --> 00:46:50,880
Speaker 1: off because they were stargazing. Even though we hit them

918
00:46:50,880 --> 00:46:54,400
Speaker 1: at an incredible speed and killed them, the charges were

919
00:46:54,480 --> 00:46:56,480
Speaker 1: dropped and she skated on that.

920
00:46:56,719 --> 00:46:59,680
Speaker 2: So just just a lot of are you feeling a

921
00:46:59,719 --> 00:47:03,120
Speaker 2: lot of empathy for a bad driver because I am one?

922
00:47:04,000 --> 00:47:06,800
Speaker 2: But beyond that, the whole killing somebody.

923
00:47:07,040 --> 00:47:10,359
Speaker 1: Yea Christ, that's a different level. Getting honked at because

924
00:47:10,400 --> 00:47:12,520
Speaker 1: you're on your phone because you didn't go when the

925
00:47:12,600 --> 00:47:13,840
Speaker 1: light turned green for fresh.

926
00:47:16,800 --> 00:47:20,439
Speaker 2: They were star gazing. It's like the middle of the day, I'm.

927
00:47:20,440 --> 00:47:25,120
Speaker 1: Driving, that's what It's just Hollywood Boulevard. They're stargazing. So anyway,

928
00:47:25,719 --> 00:47:27,239
Speaker 1: this is what happens. So people are like, why the

929
00:47:27,400 --> 00:47:30,400
Speaker 1: fuck is Kevin O'Leary in this movie? He said, this

930
00:47:30,480 --> 00:47:33,719
Speaker 1: is what Safti told him, quote, We're looking for a

931
00:47:33,800 --> 00:47:35,360
Speaker 1: real asshole and you're it.

932
00:47:35,880 --> 00:47:37,440
Speaker 2: That is so funny.

933
00:47:37,600 --> 00:47:41,160
Speaker 1: And another interviews after confirmed this explain that quote, we

934
00:47:41,280 --> 00:47:44,560
Speaker 1: needed someone who you did not like and did not

935
00:47:44,880 --> 00:47:47,640
Speaker 1: like in a deep, unconscious way, and we looked at

936
00:47:47,680 --> 00:47:50,279
Speaker 1: a lot of real businessmen and people who have no

937
00:47:50,520 --> 00:47:53,680
Speaker 1: history of being on camera. But then we found him

938
00:47:53,920 --> 00:47:55,400
Speaker 1: and this is the thing he is, like, it's so

939
00:47:55,560 --> 00:47:57,680
Speaker 1: what's so fun about him is that you enjoy watching

940
00:47:57,760 --> 00:48:00,480
Speaker 1: him be a dick kind of Maybe.

941
00:48:01,160 --> 00:48:05,080
Speaker 2: Then that gives him more stuff, you know what I mean.

942
00:48:05,320 --> 00:48:08,680
Speaker 1: Like, I'm just like, I give the perception of a

943
00:48:08,840 --> 00:48:10,600
Speaker 1: character like you see it and you med to go

944
00:48:10,719 --> 00:48:13,359
Speaker 1: fuck this guy, Fuck this guy, fuck this guy. Like sure,

945
00:48:13,920 --> 00:48:16,799
Speaker 1: I get that you can probably achieve that in many

946
00:48:16,880 --> 00:48:20,080
Speaker 1: other ways. But okay, fine, but here's the thing now

947
00:48:20,200 --> 00:48:22,279
Speaker 1: that the film, like there's a lot of people know

948
00:48:22,600 --> 00:48:25,000
Speaker 1: earlier reason the film, and like there's press going out.

949
00:48:25,760 --> 00:48:29,000
Speaker 1: He's been just using this opportunity of him being in

950
00:48:29,120 --> 00:48:31,560
Speaker 1: a film, despite never being in a movie before, just

951
00:48:31,600 --> 00:48:35,640
Speaker 1: start giving pointers to the film industry about AI, which

952
00:48:35,680 --> 00:48:38,719
Speaker 1: he is very invested in. So he he was on

953
00:48:38,920 --> 00:48:42,200
Speaker 1: like the hills World of Travel podcast, and which he

954
00:48:42,239 --> 00:48:45,040
Speaker 1: said basically was like Marty Supreme, like should have used

955
00:48:45,080 --> 00:48:48,600
Speaker 1: AI extras instead of humans. Oh yeah, this is what

956
00:48:48,719 --> 00:48:50,839
Speaker 1: he said. I just want to this is a well

957
00:48:51,239 --> 00:48:53,680
Speaker 1: you might recognize something about this quote because he's really

958
00:48:53,719 --> 00:48:56,600
Speaker 1: into this number for some reason. Quote almost every scene

959
00:48:56,640 --> 00:48:59,480
Speaker 1: had as many as one hundred and fifty extras. Now,

960
00:48:59,560 --> 00:49:04,640
Speaker 1: these people have to stay awake for eighteen hours. You

961
00:49:04,880 --> 00:49:06,680
Speaker 1: just said that about who. No one gives a shit

962
00:49:06,719 --> 00:49:08,640
Speaker 1: about the FS. This is like his weird perception of

963
00:49:08,719 --> 00:49:11,600
Speaker 1: working people. It's like they're up for eighteen hours, they

964
00:49:11,640 --> 00:49:13,440
Speaker 1: don't know what's going on, so he goes they have

965
00:49:13,520 --> 00:49:17,160
Speaker 1: to stay awake for eighteen hours. Usually it's twelve based

966
00:49:17,160 --> 00:49:20,160
Speaker 1: on the laws. Be completely dressed in the background, and

967
00:49:20,200 --> 00:49:23,120
Speaker 1: they're not necessarily in the movie, but they're necessary to

968
00:49:23,239 --> 00:49:25,840
Speaker 1: be there moving around. And yet it costs millions of

969
00:49:25,920 --> 00:49:29,480
Speaker 1: dollars to do that. Why couldn't you simply put AI

970
00:49:29,640 --> 00:49:32,320
Speaker 1: agents in their place because they're not the main actors,

971
00:49:32,560 --> 00:49:35,200
Speaker 1: they're only in the story. Visually, you could save millions

972
00:49:35,239 --> 00:49:38,160
Speaker 1: of dollars so more movies could be made. The same

973
00:49:38,239 --> 00:49:41,719
Speaker 1: director instead of spending ninety million or whatever he spent,

974
00:49:41,880 --> 00:49:45,520
Speaker 1: could have spent thirty five million and made two movies you,

975
00:49:45,719 --> 00:49:49,680
Speaker 1: I'm sorry, is the budget for background actors fifty five

976
00:49:49,880 --> 00:49:50,800
Speaker 1: million dollars?

977
00:49:50,920 --> 00:49:52,719
Speaker 2: Because what duction get paid for?

978
00:49:54,080 --> 00:49:56,120
Speaker 1: Know, that's what we get paid by George Soros to

979
00:49:56,200 --> 00:49:58,920
Speaker 1: take to the streets, you know what I mean? But

980
00:49:59,120 --> 00:49:59,600
Speaker 1: get this work.

981
00:50:02,360 --> 00:50:05,360
Speaker 2: And I said, and then I said, let my. I

982
00:50:05,400 --> 00:50:07,479
Speaker 2: don't know why. It's the same accent. And then I said,

983
00:50:07,560 --> 00:50:10,520
Speaker 2: let my. Let my bitch wife be AI because then

984
00:50:10,560 --> 00:50:13,320
Speaker 2: she would nag me all the time, and now she

985
00:50:13,600 --> 00:50:16,760
Speaker 2: just beat boops around. And it's so it's so efficient

986
00:50:16,840 --> 00:50:19,720
Speaker 2: and so costly, and I haven't seen my children in years.

987
00:50:19,920 --> 00:50:23,520
Speaker 1: What a fucking this? He goes on. Okay, I'd argue

988
00:50:23,640 --> 00:50:25,759
Speaker 1: for the sake of the art, you should allow it

989
00:50:25,880 --> 00:50:26,640
Speaker 1: in certain cases.

990
00:50:26,719 --> 00:50:27,759
Speaker 2: For the sake of the art.

991
00:50:28,000 --> 00:50:32,160
Speaker 1: AI extra is a really good case because you can't

992
00:50:32,239 --> 00:50:35,399
Speaker 1: tell the difference. You just put one hundred nor weld

993
00:50:35,520 --> 00:50:41,120
Speaker 1: tillies in there and you're good. Norweld tillies go.

994
00:50:44,760 --> 00:50:45,120
Speaker 4: Scamp.

995
00:50:45,320 --> 00:50:50,359
Speaker 1: Yeah, a pr it's not a real thing. I mean

996
00:50:50,440 --> 00:50:53,640
Speaker 1: when like, especially when the creator was like, oh, we're

997
00:50:53,680 --> 00:50:56,799
Speaker 1: getting calls from agencies, No you're not, then name them

998
00:50:56,960 --> 00:50:59,239
Speaker 1: and she couldn't you're like, of course because this, and

999
00:50:59,360 --> 00:51:02,640
Speaker 1: everyone's just in with that headline breathlessly, as if any

1000
00:51:02,800 --> 00:51:06,560
Speaker 1: legitimate talent agency was asking about an algorithm. For get

1001
00:51:06,600 --> 00:51:09,000
Speaker 1: the fuck out of here, anyway. This is what he

1002
00:51:09,000 --> 00:51:13,560
Speaker 1: goes on to talk about, Norweal Tilly nor Well Tillies quote,

1003
00:51:13,600 --> 00:51:16,480
Speaker 1: she's one hundred percent AI. She doesn't exist, but she's

1004
00:51:16,520 --> 00:51:19,799
Speaker 1: a great actress. She can come in any age you want.

1005
00:51:20,160 --> 00:51:22,759
Speaker 1: She doesn't need to eat, so she works twenty four

1006
00:51:22,880 --> 00:51:25,799
Speaker 1: hours a day. The Union is going out of their mind.

1007
00:51:27,200 --> 00:51:31,839
Speaker 1: Huh huh, And everyone just like roasted his ass.

1008
00:51:32,280 --> 00:51:34,000
Speaker 2: What does he do? I don't understand what he does?

1009
00:51:34,520 --> 00:51:35,400
Speaker 1: Just an entrepreneur.

1010
00:51:35,760 --> 00:51:37,680
Speaker 4: Yeah, he goes on shark Tank and it's like, I

1011
00:51:37,840 --> 00:51:39,440
Speaker 4: hate your stupid fucking idea.

1012
00:51:40,040 --> 00:51:44,560
Speaker 2: Yeah he's okay, I'm listening. Yeah, I also love doing that.

1013
00:51:45,480 --> 00:51:51,680
Speaker 1: He co founded soft Key Software Products and then Thy Brothers. Yeah,

1014
00:51:51,960 --> 00:51:57,600
Speaker 1: Betty soft Key, the soft Key Brothers. But yeah, this

1015
00:51:57,760 --> 00:52:01,680
Speaker 1: is where he's at now, just preaching the Norwell Tilly gospel.

1016
00:52:02,200 --> 00:52:04,759
Speaker 1: One person pointed out, I think rightfully, we shouldn't be

1017
00:52:04,760 --> 00:52:07,600
Speaker 1: paying attention to the quote technological and aesthetic wisdom of

1018
00:52:07,640 --> 00:52:11,120
Speaker 1: a guy who wears fucking two wristwatches simultaneously to keep

1019
00:52:11,160 --> 00:52:13,160
Speaker 1: track of different time zones. I don't know if you

1020
00:52:13,200 --> 00:52:16,120
Speaker 1: know this about him. He wears dueling wrist watches.

1021
00:52:17,000 --> 00:52:19,520
Speaker 2: You know why wait on either on both hands or

1022
00:52:19,520 --> 00:52:20,440
Speaker 2: on right one hand.

1023
00:52:20,480 --> 00:52:23,320
Speaker 1: Right wrist, left wrist. There is a wristwatch on it

1024
00:52:23,520 --> 00:52:27,439
Speaker 1: because it helps him keep track of New York time

1025
00:52:27,880 --> 00:52:28,959
Speaker 1: and do buy time.

1026
00:52:30,000 --> 00:52:32,680
Speaker 2: Okay, but if you had an AI watch, it could

1027
00:52:32,719 --> 00:52:35,280
Speaker 2: do the math for you. Yeah, and then you wouldn't

1028
00:52:35,320 --> 00:52:36,440
Speaker 2: have to look at things.

1029
00:52:36,680 --> 00:52:39,160
Speaker 1: I mean there's fancy rich guy watches that have multiple

1030
00:52:39,239 --> 00:52:43,920
Speaker 1: time zones and you think, yeah, this conundrum decades ago.

1031
00:52:44,640 --> 00:52:47,280
Speaker 2: But you're so fun. They are all living in the eighties.

1032
00:52:47,480 --> 00:52:49,399
Speaker 4: Yeah, that's what he's like, gotta have my watches from

1033
00:52:49,400 --> 00:52:50,360
Speaker 4: my different time zones.

1034
00:52:50,600 --> 00:52:53,960
Speaker 1: Look like such an asshole, two wrist watches like that.

1035
00:52:54,080 --> 00:52:56,360
Speaker 4: He's definitely not a fax machine on Oh.

1036
00:52:57,680 --> 00:52:59,400
Speaker 1: He hasn't like built into his limo. He's like, you

1037
00:52:59,440 --> 00:53:02,719
Speaker 1: see what that is, affect simile. I've got really cool,

1038
00:53:02,840 --> 00:53:03,239
Speaker 1: really cool.

1039
00:53:03,280 --> 00:53:05,160
Speaker 4: Wait, is that why it's called a fax machine?

1040
00:53:05,280 --> 00:53:05,520
Speaker 1: Yeah?

1041
00:53:06,239 --> 00:53:06,479
Speaker 2: Whoa.

1042
00:53:07,719 --> 00:53:14,320
Speaker 1: Look, we got a tribute between Alive's science brain and

1043
00:53:14,440 --> 00:53:18,759
Speaker 1: other general intelligence. My truly knowledge of the trivial and

1044
00:53:18,880 --> 00:53:20,520
Speaker 1: Molly's use of books.

1045
00:53:20,920 --> 00:53:27,360
Speaker 4: I think my general intelligence, my g I huh, we

1046
00:53:27,480 --> 00:53:29,600
Speaker 4: could crush a trivial pursuit tournament.

1047
00:53:29,680 --> 00:53:32,080
Speaker 1: I think, oh yeah, yeah, yeah, I think, I think.

1048
00:53:32,160 --> 00:53:34,360
Speaker 1: I think. So anyone wants to challenge just let us know.

1049
00:53:34,440 --> 00:53:37,600
Speaker 1: But you know, please, we're gonna get challenged by Tilly

1050
00:53:37,680 --> 00:53:39,920
Speaker 1: Norwood Norwell. Tilly.

1051
00:53:40,560 --> 00:53:45,279
Speaker 2: That's like chryl Lee, Ralph's character and Abbot Elementary, just mixing.

1052
00:53:45,080 --> 00:53:48,960
Speaker 1: Up all these celebraies. Norwell Tilly. It's like that's not

1053
00:53:49,120 --> 00:53:52,680
Speaker 1: even a name. You would I'd imagine say Tilly nor Well,

1054
00:53:53,480 --> 00:53:56,000
Speaker 1: but Norwell like even to get it reverse. Oh what

1055
00:53:56,120 --> 00:53:58,640
Speaker 1: a beautiful, beautiful girl, that nor Well.

1056
00:53:59,239 --> 00:54:00,920
Speaker 4: We're gonna crush sure in trivia.

1057
00:54:01,480 --> 00:54:03,840
Speaker 1: Yeah. So right now, the thing with the AI that

1058
00:54:03,880 --> 00:54:05,640
Speaker 1: earlier is trying to do, he's trying to build quote,

1059
00:54:05,680 --> 00:54:10,080
Speaker 1: the world's largest artificial intelligence data center in Alberta, Canada.

1060
00:54:10,440 --> 00:54:13,480
Speaker 1: And to add insult to injury, he's putting this thing

1061
00:54:13,680 --> 00:54:17,280
Speaker 1: called Wonder Valley on the traditional territory of the Sturgeon

1062
00:54:17,400 --> 00:54:21,680
Speaker 1: Lake Cree Nation. So you want to desecrate indigenous land

1063
00:54:21,960 --> 00:54:27,360
Speaker 1: with your capitalist, fucking hell site this He's on the

1064
00:54:27,440 --> 00:54:29,240
Speaker 1: right side of everything. Kevin O'Leary.

1065
00:54:29,600 --> 00:54:34,640
Speaker 2: I am calling the louver histers. We need you. Okay,

1066
00:54:34,800 --> 00:54:37,719
Speaker 2: we have another mission. Should you choose to accept, Okay,

1067
00:54:38,640 --> 00:54:40,160
Speaker 2: destroy this project.

1068
00:54:40,719 --> 00:54:43,520
Speaker 1: It might be easy, but use but you must, and

1069
00:54:43,960 --> 00:54:46,480
Speaker 1: you must use the help of Norwal Tilly because we

1070
00:54:46,560 --> 00:54:48,160
Speaker 1: have to bring it down from the inside. That's the

1071
00:54:48,239 --> 00:54:49,800
Speaker 1: only way it can happen. It's the only way we

1072
00:54:49,840 --> 00:54:52,920
Speaker 1: can happen. But anyway, I'm a lot of people are

1073
00:54:53,080 --> 00:54:55,160
Speaker 1: talking a lot about the film, while you're much more

1074
00:54:55,239 --> 00:54:58,840
Speaker 1: in tune with the film industry. Are people people pretty excited.

1075
00:54:58,840 --> 00:55:00,560
Speaker 1: I feel like this is one that people they're excited.

1076
00:55:00,680 --> 00:55:01,920
Speaker 2: I think it looks terrible.

1077
00:55:02,360 --> 00:55:03,719
Speaker 1: Oh yeah, I haven't seen any trailer before.

1078
00:55:03,719 --> 00:55:05,800
Speaker 4: I just get it looks like like a Wes Anderson,

1079
00:55:06,040 --> 00:55:09,439
Speaker 4: like really Pong Champ. But that's cool.

1080
00:55:09,920 --> 00:55:15,839
Speaker 1: Mmmmmm. Well, I know I might see it, because I mean,

1081
00:55:16,080 --> 00:55:18,480
Speaker 1: in truth, I might see every movie ever. I think

1082
00:55:18,480 --> 00:55:20,120
Speaker 1: that's a that's a true statement, even if.

1083
00:55:20,160 --> 00:55:22,280
Speaker 4: Well, I can say with complete confidence I will.

1084
00:55:22,200 --> 00:55:22,719
Speaker 2: Never see it.

1085
00:55:22,960 --> 00:55:24,480
Speaker 1: What's a movie I should see this year?

1086
00:55:24,840 --> 00:55:27,239
Speaker 4: I know you're totally asking the wrong person. I don't

1087
00:55:27,280 --> 00:55:28,120
Speaker 4: see movies at all.

1088
00:55:28,560 --> 00:55:31,040
Speaker 1: Well, you write, but you talk enough to people that know. Yeah,

1089
00:55:31,520 --> 00:55:33,440
Speaker 1: read books, no, I have.

1090
00:55:33,560 --> 00:55:36,360
Speaker 4: Like producer Victor, tell me what happens in movies that

1091
00:55:36,680 --> 00:55:37,319
Speaker 4: I haven't seen.

1092
00:55:38,239 --> 00:55:38,960
Speaker 2: Have you seen them?

1093
00:55:39,200 --> 00:55:40,720
Speaker 4: Getting of Eddington?

1094
00:55:41,160 --> 00:55:47,279
Speaker 2: No, it is good, Like the the plot isn't like

1095
00:55:47,960 --> 00:55:52,360
Speaker 2: crazy twists or anything, but the acting and the characters

1096
00:55:52,560 --> 00:55:55,520
Speaker 2: are like really good. I really love the actors in it.

1097
00:55:55,640 --> 00:55:58,040
Speaker 2: I think it's really that's that made me stay.

1098
00:55:58,400 --> 00:56:00,120
Speaker 4: I think the last movie I saw is the at

1099
00:56:00,239 --> 00:56:03,239
Speaker 4: Art was m Night Shyamalan's Trap. It was so good

1100
00:56:03,280 --> 00:56:04,200
Speaker 4: and it was so good.

1101
00:56:04,400 --> 00:56:07,600
Speaker 2: It was so good. I was obsessed. It was like

1102
00:56:07,800 --> 00:56:11,520
Speaker 2: it was it was at the level of acting of color. No,

1103
00:56:13,080 --> 00:56:17,040
Speaker 2: it was so good that yeah, yes, all check it out.

1104
00:56:17,320 --> 00:56:19,719
Speaker 2: We need Josh Hartnett in a lot of things. He

1105
00:56:19,920 --> 00:56:20,520
Speaker 2: was great in it.

1106
00:56:20,680 --> 00:56:23,560
Speaker 4: He was great m Night Shyamalon's daughter, who played a

1107
00:56:23,600 --> 00:56:24,520
Speaker 4: fictional pop star.

1108
00:56:25,200 --> 00:56:28,880
Speaker 2: Oh wait no, but she's like a real That was

1109
00:56:29,000 --> 00:56:31,960
Speaker 2: like the movie to like premiere, like it was solely

1110
00:56:32,000 --> 00:56:35,480
Speaker 2: a commercial for her music. Like yeah, that was fully

1111
00:56:35,600 --> 00:56:38,839
Speaker 2: for like a promotional thing for her so that her

1112
00:56:38,920 --> 00:56:42,919
Speaker 2: music could be highlighted and then she could supposedly act

1113
00:56:43,000 --> 00:56:43,400
Speaker 2: in between.

1114
00:56:43,640 --> 00:56:46,120
Speaker 1: That's that look, that's he said. Being a good dad,

1115
00:56:46,600 --> 00:56:51,319
Speaker 1: Josh hartnetto dad, Well, yeah, it was a good movie

1116
00:56:51,320 --> 00:56:52,239
Speaker 1: about being a good dad.

1117
00:56:52,280 --> 00:56:52,920
Speaker 2: You should watch it.

1118
00:56:53,280 --> 00:56:55,680
Speaker 1: True, great, great, great? What you're saying it's so bad

1119
00:56:55,719 --> 00:56:56,160
Speaker 1: it's good.

1120
00:56:56,760 --> 00:56:59,920
Speaker 2: Yeah, yeah, it's I just think it's regularly good kind.

1121
00:56:59,800 --> 00:57:02,560
Speaker 1: Of oh wow, okay, okay, okay, yeah, because like Shyamalan has,

1122
00:57:02,880 --> 00:57:03,680
Speaker 1: it's a movie.

1123
00:57:03,840 --> 00:57:05,359
Speaker 2: It's like, yeah, it's a fun movie.

1124
00:57:05,440 --> 00:57:06,640
Speaker 1: Perfect, that's what I mean. Yeah.

1125
00:57:06,719 --> 00:57:09,440
Speaker 4: Yeah, it's not because you're like, this is cinema. No,

1126
00:57:09,560 --> 00:57:11,600
Speaker 4: it's like, no, it's like a popcorn movie. And it's

1127
00:57:11,640 --> 00:57:13,200
Speaker 4: great at being a popcorn Yeah.

1128
00:57:13,280 --> 00:57:15,360
Speaker 1: Okay, I like that up in the nineties.

1129
00:57:15,920 --> 00:57:18,240
Speaker 2: It's bad that I I have only I think the

1130
00:57:18,320 --> 00:57:23,880
Speaker 2: only Safti Brothers movie that I've seen is Uncut Gems

1131
00:57:23,920 --> 00:57:26,400
Speaker 2: because I really want to understand memes, you know, so

1132
00:57:26,480 --> 00:57:29,520
Speaker 2: I like diving into where they're where they come from,

1133
00:57:30,080 --> 00:57:32,400
Speaker 2: and I was stressful. But I haven't I haven't really

1134
00:57:32,920 --> 00:57:37,640
Speaker 2: like gotten into the Safti Brothers that I also saw.

1135
00:57:39,000 --> 00:57:41,880
Speaker 1: Ye, I mean because like the other one, the other

1136
00:57:41,960 --> 00:57:46,480
Speaker 1: brother did Smashing Machine right. Yeah, yeah, so wow, wow

1137
00:57:46,560 --> 00:57:49,960
Speaker 1: house divided. Who who will win between the two of them?

1138
00:57:50,080 --> 00:57:53,000
Speaker 1: We don't know. What we do know is Kevin O'Leary

1139
00:57:53,160 --> 00:57:57,720
Speaker 1: ech Molly Lambert, thank you so much for joining us

1140
00:57:57,760 --> 00:57:59,760
Speaker 1: today on the daily' sye case. Where do the people

1141
00:57:59,800 --> 00:58:03,160
Speaker 1: find you? Follow you can port your wonderful work. Let

1142
00:58:03,240 --> 00:58:05,880
Speaker 1: me finish and what's the work of social media?

1143
00:58:06,320 --> 00:58:11,320
Speaker 4: Regular find me on Instagram, Molly Underscore Lambert. I'm on

1144
00:58:11,440 --> 00:58:15,600
Speaker 4: TikTok at Molly World and might start posting there. Okay,

1145
00:58:15,680 --> 00:58:19,000
Speaker 4: and check out general World. Jenna Jamison vivid video in

1146
00:58:19,080 --> 00:58:24,440
Speaker 4: the Valley starting October twenty seventh, every Monday for thirteen weeks.

1147
00:58:24,720 --> 00:58:27,080
Speaker 1: Now are there it? Does any crime intersect with this

1148
00:58:27,240 --> 00:58:27,880
Speaker 1: narrative at all?

1149
00:58:28,240 --> 00:58:28,400
Speaker 4: Oh?

1150
00:58:28,640 --> 00:58:29,760
Speaker 2: The dance? Yeah?

1151
00:58:30,640 --> 00:58:33,360
Speaker 1: Oh god, I thought everything was above board there.

1152
00:58:33,840 --> 00:58:36,720
Speaker 4: Well, not in the not in the porn business proper.

1153
00:58:36,720 --> 00:58:38,960
Speaker 1: Yeah I know, I mean, but just the characters around it.

1154
00:58:39,400 --> 00:58:41,360
Speaker 4: Yeah, you'll see there's some fun.

1155
00:58:42,840 --> 00:58:47,080
Speaker 1: Stuff. As someone who only knows of Jenna Jamison in

1156
00:58:47,200 --> 00:58:51,479
Speaker 1: one dimension through like pornography, I'm I'm really looking forward

1157
00:58:51,520 --> 00:58:53,640
Speaker 1: to this because you do such good work.

1158
00:58:53,440 --> 00:58:57,760
Speaker 4: Of like oh thank you, Lawrence Sera. Jenna is also incredible.

1159
00:58:57,960 --> 00:59:01,680
Speaker 1: So get ready, okay, I am, I'm buckling up. What's

1160
00:59:01,720 --> 00:59:02,920
Speaker 1: the working media that you've been enjoying?

1161
00:59:05,280 --> 00:59:10,160
Speaker 2: Simpsons, Treehouse of Horror class, What would your Treehouse of Horror?

1162
00:59:10,240 --> 00:59:17,920
Speaker 1: Name be Scully No, Golly Molly lamboo. Oh yeah, Molly

1163
00:59:18,080 --> 00:59:25,360
Speaker 1: Lamb's Blood Yeah, uh, mine would be I think what

1164
00:59:25,840 --> 00:59:31,760
Speaker 1: Bles Gray? Yeah, Biles Biles Ghoul, Biles Gray. We were

1165
00:59:31,760 --> 00:59:33,280
Speaker 1: trying to think of another one. I was doing this,

1166
00:59:33,440 --> 00:59:35,720
Speaker 1: I got a like a get together recently, I'm like,

1167
00:59:35,720 --> 00:59:37,880
Speaker 1: what's it does? Everybody has? Everybody thought about what their

1168
00:59:38,000 --> 00:59:39,200
Speaker 1: Treehouse of Horror name would be?

1169
00:59:39,560 --> 00:59:40,360
Speaker 4: Just when I'm watching it?

1170
00:59:40,680 --> 00:59:41,360
Speaker 2: What would mind be?

1171
00:59:41,880 --> 00:59:42,440
Speaker 4: What would yours be?

1172
00:59:44,280 --> 00:59:47,440
Speaker 2: I do have a potential for goo in my last name?

1173
00:59:50,920 --> 00:59:51,680
Speaker 1: Yes? Yes? Yes?

1174
00:59:52,720 --> 00:59:53,160
Speaker 3: Is that gang?

1175
00:59:53,280 --> 00:59:54,560
Speaker 2: We need your help? Yes?

1176
00:59:55,440 --> 00:59:56,320
Speaker 4: That chime in?

1177
00:59:56,880 --> 00:59:57,080
Speaker 6: Yeah?

1178
00:59:58,080 --> 00:59:59,800
Speaker 4: Tree House of Horror names and your own treehouse?

1179
00:59:59,840 --> 01:00:02,400
Speaker 1: Yeah? Who's got the best one? Who's got the best one?

1180
01:00:02,760 --> 01:00:05,800
Speaker 1: Paula v thank you so much for joining me us today.

1181
01:00:05,840 --> 01:00:07,520
Speaker 1: Where did the people find you? Follow you, support you?

1182
01:00:07,760 --> 01:00:08,800
Speaker 1: What's the working media you like?

1183
01:00:09,400 --> 01:00:11,840
Speaker 2: I'm at Paula Viganalan p A L L A B

1184
01:00:11,960 --> 01:00:14,920
Speaker 2: I g U n A l A N everywhere. The

1185
01:00:15,000 --> 01:00:18,120
Speaker 2: next Facial Recognition Comedy Show is at the Comedy Store

1186
01:00:18,200 --> 01:00:21,920
Speaker 2: on the twenty first of November. Please come through. We

1187
01:00:22,040 --> 01:00:25,160
Speaker 2: have such a great time. Actually, this last one super fun.

1188
01:00:26,080 --> 01:00:30,440
Speaker 2: It's a good hang and the work of media. You

1189
01:00:30,560 --> 01:00:35,200
Speaker 2: could oh, I you guys thought it's a tweet. It's

1190
01:00:35,240 --> 01:00:39,280
Speaker 2: a picture, an old picture of Aretha Franklin and Brandy,

1191
01:00:39,400 --> 01:00:43,440
Speaker 2: and Brandy is looking like like smiling at the camera

1192
01:00:43,880 --> 01:00:46,000
Speaker 2: but trying to like hold back what looks like pain.

1193
01:00:46,400 --> 01:00:49,720
Speaker 2: And someone quote tweeted it at easy like feazy quote

1194
01:00:49,720 --> 01:00:52,240
Speaker 2: tweeted Aretha was stepping on that toe bad and it

1195
01:00:52,400 --> 01:00:57,280
Speaker 2: was I've been watching the discourse around it and everybody

1196
01:00:57,400 --> 01:00:57,680
Speaker 2: was like this.

1197
01:01:00,280 --> 01:01:04,560
Speaker 5: Brandy is also looking down too, Yeah, steps so funny,

1198
01:01:05,560 --> 01:01:08,440
Speaker 5: fun Oh my god, Uh find me everywhere at Miles

1199
01:01:08,640 --> 01:01:11,040
Speaker 5: of Gray, a work in media, like I've just been

1200
01:01:11,080 --> 01:01:12,800
Speaker 5: watching the trash that his love is blind.

1201
01:01:13,400 --> 01:01:16,320
Speaker 1: If I just there's just something so intereresting to add

1202
01:01:16,360 --> 01:01:19,000
Speaker 1: you to our group chat, please do, please do it

1203
01:01:19,120 --> 01:01:21,760
Speaker 1: because I have so many things to say all the time,

1204
01:01:21,880 --> 01:01:25,960
Speaker 1: and my own partner doesn't give a fuck about these

1205
01:01:26,080 --> 01:01:30,520
Speaker 1: couples at all. It's infuriating. But anyway, find me there.

1206
01:01:30,680 --> 01:01:32,600
Speaker 1: Those are the that's a work of media. I'm like,

1207
01:01:32,680 --> 01:01:35,440
Speaker 1: you know, you could also find me on for Twenty

1208
01:01:35,520 --> 01:01:38,880
Speaker 1: Day Fiance and you know you've got some other things

1209
01:01:38,960 --> 01:01:41,439
Speaker 1: coming up too, Just so you know, I'm in the lab.

1210
01:01:41,560 --> 01:01:43,240
Speaker 1: I'm actually in the lab. There will be some some

1211
01:01:43,440 --> 01:01:47,120
Speaker 1: announcements coming up, doing some new things, one with Jack,

1212
01:01:47,360 --> 01:01:51,280
Speaker 1: one without, and you will like it. I hope we'll

1213
01:01:51,320 --> 01:01:55,680
Speaker 1: see Anyway, you can find us everywhere at Daily Zeitgeist,

1214
01:01:55,760 --> 01:01:58,000
Speaker 1: at the Daily Zeitgeist on Instagram. You can go to

1215
01:01:58,000 --> 01:02:00,439
Speaker 1: the description of this episode right now wherever you're listening,

1216
01:02:00,480 --> 01:02:03,400
Speaker 1: and at the bottom that's where you find the footnotes, foodnotes,

1217
01:02:03,560 --> 01:02:05,520
Speaker 1: thank you, and that's where we link off to the

1218
01:02:05,600 --> 01:02:08,840
Speaker 1: information articles we talked about. Today's episode. Also a song

1219
01:02:08,920 --> 01:02:11,000
Speaker 1: you might enjoy. What's the song I think you'll enjoy?

1220
01:02:11,720 --> 01:02:14,520
Speaker 1: In yesterday's episode, we were talking to Francesca Fiorentini and

1221
01:02:14,560 --> 01:02:17,080
Speaker 1: she was talking about how she like Cardis Watch and

1222
01:02:17,160 --> 01:02:18,360
Speaker 1: she didn't know I didn't know what it's called. And

1223
01:02:18,400 --> 01:02:21,440
Speaker 1: I said, Oh, that's a reshad Me watch that she's

1224
01:02:21,480 --> 01:02:23,720
Speaker 1: got on because it's millions of dollars. And then I

1225
01:02:23,920 --> 01:02:26,560
Speaker 1: was like, oh, there's a West Side Gun song that

1226
01:02:26,760 --> 01:02:28,919
Speaker 1: reminded me of this because there's a whole part where

1227
01:02:28,920 --> 01:02:32,440
Speaker 1: they're talking about pronouncing reshad Me and that track is

1228
01:02:32,560 --> 01:02:37,240
Speaker 1: called Margella Split Toes. It's by Buffalo's West Side Gun.

1229
01:02:37,840 --> 01:02:40,800
Speaker 1: Please check it out. It's great, probably some of the

1230
01:02:40,840 --> 01:02:43,480
Speaker 1: best ad libs in the game from West Side, so

1231
01:02:43,960 --> 01:02:46,200
Speaker 1: check that out. The production or the day is Geist

1232
01:02:46,240 --> 01:02:48,480
Speaker 1: is a production of iHeartRadio. So for more podcasts you

1233
01:02:48,520 --> 01:02:51,160
Speaker 1: already know iHeartRadio app Apple Podcasts wherever you get them

1234
01:02:51,200 --> 01:02:53,680
Speaker 1: for free, check it out. All right, until then, we'll

1235
01:02:53,720 --> 01:02:55,840
Speaker 1: see you then, I mean until then. By then, I

1236
01:02:55,920 --> 01:02:58,760
Speaker 1: mean Monday, I'll see you Monday, and then also tune

1237
01:02:58,760 --> 01:03:01,400
Speaker 1: in this weekend for the best of recap in case

1238
01:03:01,560 --> 01:03:03,360
Speaker 1: you're not able to listen to every episode, so you

1239
01:03:03,440 --> 01:03:04,840
Speaker 1: just get the best bits in one place.

1240
01:03:05,040 --> 01:03:06,680
Speaker 2: Jenna's World drops Monday too.

1241
01:03:07,080 --> 01:03:14,320
Speaker 1: Jenneral World drops on Monday. Kid Kid, the first thing

1242
01:03:14,400 --> 01:03:17,160
Speaker 1: in your ears buds is my voice as kid Rock.

1243
01:03:17,400 --> 01:03:20,680
Speaker 1: I mean, what are you waiting on? Pre pre download?

1244
01:03:24,480 --> 01:03:30,280
Speaker 1: I would be Bald with the Bald, Yeah anyway. Bald

1245
01:03:30,320 --> 01:03:31,640
Speaker 1: with the Bald later.

1246
01:03:31,600 --> 01:03:36,240
Speaker 2: By The Daily Guys is executive produced by Catherine Long,

1247
01:03:36,640 --> 01:03:38,640
Speaker 2: co produced by Bae Wang.

1248
01:03:38,880 --> 01:03:42,720
Speaker 1: Co produced by Victor Wright, co written by j M mcnapp,

1249
01:03:43,280 --> 01:03:45,760
Speaker 1: edited and engineered by Justin Connor.