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Speaker 1: She brought these dusty ass cookies over and I remember

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Speaker 1: I took a bite and I was like, this ship

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Speaker 1: is just trash ba something is it's? It had like

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Speaker 1: it had taken on the taste of being in like

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Speaker 1: like as if it was sat next to celery for

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Speaker 1: fucking five weeks or some shit. Wow, it was the

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Speaker 1: weirdest taste for like a triple chocolate cookie. Like You're like, brother,

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Speaker 1: this should not be That's not a good combo.

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Speaker 2: Hell, triple chocolate with celery is not what I'm looking for.

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Speaker 2: Do you think it was Do you think it was

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Speaker 2: stored next to celery? Is that what it taken on

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Speaker 2: the taste?

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Speaker 1: And also it was in a bag inside a bag

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Speaker 1: because the original bag had torn and they didn't rebag

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Speaker 1: it and then rebag it. You gotta rebag, I texted regift,

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Speaker 1: you gotta rebag. So what the fuck is up with

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Speaker 1: these cookies. She's like, oh, yeah, yeah, she they got

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Speaker 1: him in August or something, but she wasn't eating them,

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Speaker 1: so I thought you'd want it. And I'm like, cause

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Speaker 1: you didn't want it to fuck it, I'm like, how

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Speaker 1: long did you have She's like like maybe a week

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Speaker 1: or something. She didn't want to make it a way around.

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Speaker 1: She brings her She brings her old food and puts

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Speaker 1: it in my refrigerator that she doesn't want to throw away.

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Speaker 2: I feel like they probably had like three conversations about

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Speaker 2: those cookies, like yeah, like I don't know, maybe Miles,

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Speaker 2: do you think, Miles? Maybe Miles?

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Speaker 1: Yeah, yeah, he smokes weed. He won't even know. These

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Speaker 1: shits are two months old.

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Speaker 2: Hello the Internet, and welcome to season three point fifty nine,

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Speaker 2: Episode three.

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Speaker 1: Of Derney's I Guys Stay production of iHeartRadio. This is

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Speaker 1: a podcast where we take a deep dive.

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Speaker 2: Into America's shared consciousness.

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Speaker 1: And it is Wednesday, October ninth.

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Speaker 2: Twenty twenty four, ten nine eighty four, seven six spots.

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Speaker 1: So it starts elections, like what twenty something days away?

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Speaker 2: Boy, I don't want to talk about that, Miles on

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Speaker 2: this news podcast.

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Speaker 1: Well, let's focus on what today is done. At October ninth,

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Speaker 1: National Moldie Cheese Day. It's also National Curves Day. It's

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Speaker 1: also National bring your teddy bear to work or school Day,

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Speaker 1: National take your parents to Lunch Day, and National Emergency

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Speaker 1: Nurses Day. Shout out everybody who's keeping people alive.

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Speaker 2: We were talking about moldy something or other, you know,

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Speaker 2: but before Sam even joined us.

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Speaker 1: But I still like, don't feel like so.

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Speaker 2: We're talking two and a half months on some cookies.

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Speaker 1: We're bringing that up. Yeah, I don't know. It just

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Speaker 1: doesn't feel that bad to me. Don't.

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Speaker 2: And it's not the fact that they were stored with

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Speaker 2: the celery I think is what.

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Speaker 1: It's not the only thing that fucked it up. You

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Speaker 1: have to look at it this way. This was a

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Speaker 1: like artisanally baked cookie. It does not have like the

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Speaker 1: preservatives to give it an extended shelf life, maybe past

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Speaker 1: the five days after it's been baked, you know what

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Speaker 1: I mean. Like it was like one of those gift basket. Yes,

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Speaker 1: he was like in a cellophane with a ribbon on it.

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Speaker 1: This was some high end hit, you know what I mean.

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Speaker 1: This wasn't. I'll man, I'm sorry Jack you. I'll dig

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Speaker 1: them out of the trash and I'll drive them over

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Speaker 1: to your house. And I mean, I don't dare want

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Speaker 1: them out of the trash. I'm just saying, like, I'm

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Speaker 1: kind of with your mom on this one. I would

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Speaker 1: have bought the cookies over and thought I was doing

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Speaker 1: you a solid okay, all right, all right, anyways, all right,

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Speaker 1: my name is a shout out to moldy cheese, which

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Speaker 1: I will I have in the case of American cheese,

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Speaker 1: I think it. I think for me it has to

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Speaker 1: be American cheese.

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Speaker 2: But if there's like a piece of mold on a

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Speaker 2: slice of American cheese, I will pull the mold piece

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Speaker 2: off of the slice of American cheese and then consume

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Speaker 2: the rest of Americans.

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Speaker 1: How are you like you're talking about like cracked singles. Yeah, yeah, yeah,

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Speaker 1: you're you're holding on the craft singles to the point

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Speaker 1: that the mold is getting in the cell of phane.

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Speaker 1: I know. It's like science.

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Speaker 2: Yeah, that's too Yeah, just anyway, Yeah, I'm revealing too

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Speaker 2: much right now. My name's Jack O'Brien aka Potatoes O'Brien

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Speaker 2: aka Banjo Eric or aka rick E Banjo. You can

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Speaker 2: go the other way, you know, like a chuck e cheese. Yes, yes,

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Speaker 2: band entertainment band, Ricky Banjo, Rick Entertainment Banjo. We're we're

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Speaker 2: distant cousins, me and Charles Entertainment Cheese. I'm thrilled to

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Speaker 2: be joined as always by my co host, mister Miles Gras.

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Speaker 1: Yes, It's Miles Gray coming live to you from the

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Speaker 1: eight one eight, also known as the Lord of Lancasham,

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Speaker 1: the Showgun with no gun and occasionally no buns because

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Speaker 1: I do have podcasters, but that I am struggling with

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Speaker 1: every day. But I am on the bike. We're just

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Speaker 1: rejuvenating my backside. So it's just.

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Speaker 2: Achilles tendon right up to the back to your back, this.

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Speaker 1: Disarray. No no buns, it's not that bad. It's not

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Speaker 1: that bad.

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Speaker 2: But you know, sir, mix a lot would not want

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Speaker 2: none because there are no buns.

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Speaker 1: No, not here, none detected. But hey, look you when

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Speaker 1: you're forty, you gotta you gotta focus on that detective.

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Speaker 1: Focus on that part. You have to focus. Yeah.

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Speaker 2: Anyways, we are thrilled, Miles to be joined by a journalist,

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Speaker 2: a podcast host who you know is one of the

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Speaker 2: hosts of Vibe Check and the host the host of

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Speaker 2: the Sam Sanders Show.

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Speaker 1: Because it's Sam Sander.

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Speaker 3: I love this. Welcome there, Thank you'll, thank y'all for

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Speaker 3: having me. It's so nice to loving the.

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Speaker 1: Energy we have to bring our a game because you

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Speaker 1: are a first rate podcast one of the show, you

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Speaker 1: know what I mean.

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Speaker 3: We're too kind we're writing here, but I've been thinking

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Speaker 3: about cheese as all were talking. Can we count blue

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Speaker 3: cheese as moldy cheese, in which case moldy cheese, blue

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Speaker 3: cheese exquisite?

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Speaker 1: What about roque Fort? Who is that? That's the that's

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Speaker 1: the level up? How do I saw her name?

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Speaker 3: R r o q u e f o R t

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Speaker 3: roke high falutin? You are high faluten I like the

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Speaker 3: I like cheese. I like stinky ass cheese. I'm not

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Speaker 3: gonna lie saying the funkier the better.

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Speaker 1: I don't know.

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Speaker 3: I want like a little crumple of blue cheese on

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Speaker 3: like a Trader Joe's, the little crackers with like raisins

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Speaker 3: in them, and you drizzle a little honey.

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Speaker 1: Ye Sam, we gotta yeah, let's have a cheese party. Yeah,

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Speaker 1: I'm ready, I'm ready. I'm absolutely ready.

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Speaker 2: Yeah the Hollywood Bowl, you know, with that little.

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Speaker 1: Oh yeah, yeah yeah, bring out some crackers, some nice

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Speaker 1: cheese while you're watching the Justice concerts. I was there,

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Speaker 1: was it. It was pretty.

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Speaker 3: Let me tell you something, we all picked the wrong

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Speaker 3: career and this is no shade on the skills of

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Speaker 3: Justice as DJs. But I will say their live set

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Speaker 3: they stand in one place for two hours, the lights move,

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Speaker 3: everyone else is dancing. You feel alive and in it.

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Speaker 3: But those dudes get to just stand up. I want

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Speaker 3: that job.

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Speaker 1: I want that job. It's a gig and then you

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Speaker 1: just have to I mean it's it is kind of

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Speaker 1: like another job too, where it's like, oh look busy, now,

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Speaker 1: look busy, look busy. All about jobs. We've all had

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Speaker 1: that position at least once in our lives. Yeah.

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Speaker 2: A species of blue cheese of the family blue cheese

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Speaker 2: or is it, like, I don't know, rope Fort different

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Speaker 2: than blue because blue cheese just seems somewhat vague.

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Speaker 1: Yeah, yeah, yeah, I mean it is a blue cheese

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Speaker 1: made from sheep's milk in the Kamba Balu caves of

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Speaker 1: roque Forts or sol France.

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Speaker 3: No creamy texture and sharp tangy saltya something else from Wikipedia,

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Speaker 3: I'm gonna say that's just looking at the wikipedias for

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Speaker 3: both blue cheese and roque Fort, I'm gonna say blue

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Speaker 3: cheese goes to a private school, Roquefort goes to a

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Speaker 3: boarding school. Yeah yeah, rope for it's like it goes

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Speaker 3: to Sidwell friends.

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Speaker 1: Yeah, oh yeah, you know what I mean. You put

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Speaker 1: it in some decent context. Yeah, yeah, it's it's in

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Speaker 1: class with Malasho Obama basically.

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Speaker 3: Oh yeah, definitely cut forth period with Malia Obama.

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Speaker 1: Smoking cigarettes because I'm from France and you should try

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Speaker 1: these cigarettes. They're actually good for you when you get

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Speaker 1: them from friends. Yeah, it's like a steam cleaner for

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Speaker 1: your lungs. How you say how you say cigarette? Yeah,

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Speaker 1: four or five cigarette.

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Speaker 2: And the teacher's just like, yeah, no, that's actually cool

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Speaker 2: with us because we're on some like next level the

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Speaker 2: great friendship.

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Speaker 1: Authors smoked cigarettes.

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Speaker 2: Yeah, we are teaching Camu right now, so the students

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Speaker 2: are permitted to smoke cigarettes in class.

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Speaker 1: All right. I love that Camu reference. Yeah, he has

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Speaker 1: even stranger references coming up.

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Speaker 2: By the way, I do spell Camu the same as Shamoo,

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Speaker 2: so I'm not don't don't like.

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Speaker 1: A m u.

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Speaker 2: A m o o is Shamoo as distant cousin of Tima.

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Speaker 1: Yeah. His grandson is actually like a talent in Japan,

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Speaker 1: which is really wild. Camus Yeah, yeah, yeah, he's like

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Speaker 1: Shamu has a no Albert Camus. Albert right is that

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Speaker 1: his name is? Yeah, his grandson like fame is a

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Speaker 1: like he's a presenter on Japanese TV and he's like

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Speaker 1: fluent in Japanese, and I was always like, I remember

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Speaker 1: being like, what how do you what's that pass interesting?

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Speaker 2: But hey, yeah, I like that for him, I like

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Speaker 2: that for the Camu legacy, existential dread and truly the

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Speaker 2: only interesting question for humanity is why we don't kill ourselves?

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Speaker 2: And then his great grandson is like, welcome back back

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Speaker 2: to the mask singer. He would do as a mask

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Speaker 2: singer because he's like this blonde hair dude.

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Speaker 1: He would go there's a show that he would go

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Speaker 1: on where he would go around the streets of Tokyo

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Speaker 1: or Osaka or something, and he would ask a question,

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Speaker 1: He's like, what's your pet peeve? Like your biggest pet beef?

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Speaker 1: And they, because he's fluent in Japanese, the answer in Japanese,

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Speaker 1: and he would always go okay now in English. And

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Speaker 1: that was always like the bit And then like the

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Speaker 1: fund was watching people struggle with their English to say

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Speaker 1: some like really funny version of what their pet peeve was.

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Speaker 2: But anyway, the implication being everybody does know how to

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Speaker 2: speak English. You couldn't do that shit in America with

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Speaker 2: like any other language.

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Speaker 1: No, No, it would be wildly offensive.

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Speaker 2: I think like, yeah, oh for sure, the responses would

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Speaker 2: be wildly offensive for sure. All right, Sam, we're going

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Speaker 2: to get to know you a little bit better in

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Speaker 2: a moment. Right first, we're going to tell the listeners

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Speaker 2: a couple of things that we're all going to be

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Speaker 2: talking about a little bit later on. We're going to

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Speaker 2: talk about preparations for Hurricane Milton, specifically the GOP just

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Speaker 2: ramping up the racism and the what is causing this is?

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Speaker 3: Could it be would the Green just say that like

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Speaker 3: they control the weather maybe with lasers?

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Speaker 1: With lasers?

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Speaker 3: She said, yeah, yeah, Marjorie, come on.

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Speaker 1: Research, Sam, do some research Sam on Twitter. Clearly you're

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Speaker 1: not doing your own research.

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Speaker 2: We're going to talk about the mainstream media's favorite discourse

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Speaker 2: at the moment, which is is.

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Speaker 1: This an October surprise?

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Speaker 2: Is is Trump's wife writing a book we all knew

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Speaker 2: about an October surprise?

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Speaker 3: The real October surprise is call her Daddy doing a

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Speaker 3: better interview with Kamala than anyone else's cycle.

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Speaker 1: But yes, you started.

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Speaker 2: So we're going to talk about the October surprise, where

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Speaker 2: it comes from, where that phrase even comes from, and

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Speaker 2: why it might be time to you know, quiet down

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Speaker 2: about the October surprise. All of that plenty more. But

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Speaker 2: first Sam, we do like to ask our guest, what

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Speaker 2: is something from your search history?

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Speaker 3: I was so when I when they sent this question

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Speaker 3: over to me, I was like, oh Lord, let me

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Speaker 3: not go back and look at incognito mode. But I

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Speaker 3: am going to go right now to my phone and.

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Speaker 2: Wow, we're getting the live results.

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Speaker 1: The results are.

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Speaker 3: Coming as we speak, and I feel like, you know,

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Speaker 3: there's always this divide with what you search.

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Speaker 1: It's like the.

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Speaker 3: Default browserund my iPhone is Safari, so I think my

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Speaker 3: first searches come there, but my favorite saves tabs are

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Speaker 3: in Chrome. So my third fourth wave searches live there

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Speaker 3: right right. But we're gonna start with my recent Safari

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Speaker 3: Google searches.

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Speaker 1: How do I? Okay? I googled roquefort cheese. There you go.

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Speaker 2: Oh.

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Speaker 3: I was talking in another podcast this morning about one

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Speaker 3: of these far right conspiracy theories about some people on

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Speaker 3: the right saying that Biden has been slow on hurricane

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Speaker 3: response because he's been at his beach house sunning his testicles.

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Speaker 3: So that led me to google the time that Tucker

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Speaker 3: Carlson was pushing testical tanning on his show. So my

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Speaker 3: last real Google were the three words Tucker Carlson testicles.

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Speaker 1: Yes, fantastic and are we how are the results?

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Speaker 2: What?

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Speaker 1: We don't want to go down that ball? You don't

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Speaker 1: want to go down that Now that is surprising to me.

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Speaker 3: It just kind of outlines how this dude was like

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Speaker 3: fully crazy and like two years ago he was telling

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Speaker 3: people to sun their testicles to up their testosterone, and

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Speaker 3: he had someone called a bromo therapist on or something

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Speaker 3: to talk about all this stuff just kook science.

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Speaker 1: Romeopathy or something like that. Yes, yes, yes, bromeopathy.

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Speaker 2: Yeah.

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Speaker 1: Yeah.

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Speaker 3: There's a Vanity Fair headline that reads, Tucker Carlson Colon

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Speaker 3: tan your balls if you want to.

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Speaker 1: Be a real man. Wow. Wow.

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Speaker 3: And while we're here, and I can say this because

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Speaker 3: I'm gay, so I can be offensive to straight men

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Speaker 3: who on the what straight man in the world has

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Speaker 3: taken how to be a man lessons from Tucker fucking Carlson.

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Speaker 1: The most Yeah, the most misguided? I think. Hold on, ye,

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Speaker 1: what did tuckles Tucker say? It's like, I guess, do

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Speaker 1: I keep my bow tie?

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Speaker 4: Yeah?

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Speaker 1: When I tanned my balls because I remember wasn't there

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Speaker 1: someone like around Like at the start of the Lockdown

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Speaker 1: someone was talking about like sunning your butthole too, and

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Speaker 1: like your taint was like that was the thing.

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Speaker 3: Also then for a while when it, Paltrow was like,

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Speaker 3: stick this jade egg up your nony.

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Speaker 2: Yeah, yeah, And then there was some nony sunning as

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Speaker 2: well on the side, if I'm not mistaken.

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Speaker 3: And for a second there was nony steaming, right And

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Speaker 3: I know this because years ago when that was a trend,

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Speaker 3: I was like, oh, they can't keep this from the man.

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Speaker 3: So I went to a spot in LA that did

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Speaker 3: the vaginal steaming in all earnestness. I went with my

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Speaker 3: former partner and I was like, well, can you do

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Speaker 3: it for us too? And they were mad that I

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Speaker 3: would even ask. I was like, well steamline too, like

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Speaker 3: a last They wouldn't steam me why. It's probably for

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Speaker 3: the best, it's just for vagins.

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Speaker 1: But I mean, like, is the technolo I mean what

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Speaker 1: I'm picturing just maybe someone having like a garment steamer

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Speaker 1: like under the sheet.

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Speaker 2: You know, and then like a barber shopped like cape

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Speaker 2: that you put like around your waist.

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Speaker 1: Right right right? Okay, Well yeah, hey, for the one

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Speaker 1: day I'll find out. Yeah, if you're being discriminated, just

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Speaker 1: get yourself a garment steamer or maybe a humidifier. We

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Speaker 1: legally cannot give this a buzz yep ye yeah yeah

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Speaker 1: yeah uh. Anyway, check out my live stream on Saturday morning.

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Speaker 1: But don't do what I do. Do as I say,

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Speaker 1: not as I do. That's right.

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Speaker 3: Also, Gwyneth, if you need a male volunteer as tribute, right, yeah,

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Speaker 3: I like your Gwyneth. I think you're cool. I volunteer

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Speaker 3: to be steamed.

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Speaker 2: It does suggest that the people who are doing the

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Speaker 2: steaming are like in it for the wrong reasons, Like

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Speaker 2: what why are they discriminating between you know, like right, hmm.

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Speaker 1: Because if because I'd imagine right, like if are they

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Speaker 1: saying like that you just won't get the benefits from it?

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Speaker 1: You're like, well what if I just want to feel

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Speaker 1: the steam up there?

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Speaker 3: Or they're just like I don't see that, you know

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Speaker 3: what was happening. I get it, and I understand this response.

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Speaker 3: They were just like, why is a man even trying

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Speaker 3: to get up in there?

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Speaker 1: It's for women?

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Speaker 3: And is as as well intentioned as I was going

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Speaker 3: to that storefront? They probably were like, is this guy

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Speaker 3: pranking us right right to get it.

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Speaker 1: Yeah, you did have an entire YouTube video crew with you.

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Speaker 1: I had James O'Keefe right behind me, yeah.

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Speaker 2: Wearing a ponzo. Yeah, Sam, what's something you think is underrated?

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Speaker 1: Walking? Mm hmm.

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Speaker 3: I live in LA and nobody wants to walk. Nobody

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Speaker 3: wants to freaking walk. And like, I have two dogs,

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Speaker 3: so I walk a lot with them. But I also

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Speaker 3: believe in if you have an errand to run that

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Speaker 3: you can get to in less than a mile and

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Speaker 3: a half, walk it if you have to die, yeah,

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Speaker 3: walking to it.

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Speaker 1: Like literally, I always feel better after a walk.

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Speaker 3: My mind is clearer after a walk. And you know,

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Speaker 3: y'all know this Angelino's will drive a block.

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Speaker 1: Yes you do, Yes, I just walk more, Yes I do.

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Speaker 1: I also, like I've I've been trying to use like

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Speaker 1: my bike more as like in between where it's like,

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Speaker 1: see that's a bridge too far because these drivers out

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Speaker 1: here are too fast, too furious. That's why I have

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Speaker 1: like created my own network of residential streets that I

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Speaker 1: used to not be on like those main thoroughfares, because yeah,

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Speaker 1: because they'll get you. There's nothing more frightening than being

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Speaker 1: on a bicycle, like on a main street in Los Angeles,

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Speaker 1: because people fucking just are so unaware.

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Speaker 3: Have you noticed how one since pandemic lockdown road rags

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Speaker 3: has gotten worse. And then two the basic rules and

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Speaker 3: laws of traffic people just disobey. Everyone runs red lights.

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Speaker 3: If you had a four way stop, a car behind

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Speaker 3: you might just come around you and zoom through. Like

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Speaker 3: the basic laws of how we commute in cars, people

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Speaker 3: ignore them.

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Speaker 1: Now in LA it's people are I'm seeing more and

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Speaker 1: more of people doing the Pittsburgh left turn. What is

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Speaker 1: that that? That's like when the the second the light

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Speaker 1: goes green, the person in the left turn lane just

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Speaker 1: cuts it across before New York. But I like that

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Speaker 1: you're slandering Pittsburgh with this. That's how I heard it

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Speaker 1: from a dude who I know, like, lived in Pittsburgh

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Speaker 1: any And if you look it up, if it's it's

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Speaker 1: Peopleburgh left, Yeahan's doing the Pittsburgh left. He's doing Pittsburgh left.

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Speaker 2: Hell Yeahan's doing the Pittsburgh left anymore.

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Speaker 1: You ever hear Pittsburgh people just adding anymore on to

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Speaker 1: the end of the sentence for some week.

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Speaker 2: I like that.

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Speaker 1: It's kind of fun anymore. It's like a nice open

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Speaker 1: ended thing. People also called the whole shot, which I think. Yeah,

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Speaker 1: that's also known as a Boston left or a New

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Speaker 1: York left either way illegal. Yeah, yes, we look down

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Speaker 1: on New York in this household, not the Yeah.

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Speaker 2: Yeah, I'm actually curious that gang us know, because this

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Speaker 2: is something that we've talked about a little bit here

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Speaker 2: and there. But it does feel like people have become

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Speaker 2: less and less aware that other human beings exist, or

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Speaker 2: like willing to drive as though other human beings exist.

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Speaker 3: Oh, it's just yeah, and everyone is like everyone sees

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Speaker 3: the slightest inconvenience while they're driving as like the biggest crime. Yes,

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Speaker 3: I'll be trying to change lanes. I will signal, which

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Speaker 3: is my way of saying please and thank you, and

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Speaker 3: the other car will speed up to block me. I

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Speaker 3: signaled courteous.

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Speaker 2: Right.

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Speaker 1: It's very competitive.

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Speaker 3: There's a competition going on, and there's like a rage

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Speaker 3: that is just in every single interaction in a car.

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Speaker 5: Yeah.

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Speaker 1: This is actually something I talked about in therapy because

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Speaker 1: I would get petty. Right, I'm like, oh, you're not

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Speaker 1: about like you know the thing, like, especially on freeway interchanges,

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Speaker 1: it'll be backed up and people just want to go

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Speaker 1: to the side and then in at their last time

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Speaker 1: on the shoulder, on the shoulder, and I'm like, hell, no,

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Speaker 1: you're not not to me. Not to me. H. My

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Speaker 1: therapist shout out. Doctor Shimitra was like, maybe we should

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Speaker 1: maybe we should investigate what is it about? Is it

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Speaker 1: because is it your ego? And I'm like, yeah, I

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Speaker 1: think it's like is it because you don't you think

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Speaker 1: to them, You're not that person who should be getting

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Speaker 1: cut in front of And I'm like this might be true.

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Speaker 1: So I now I have to like use it as

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Speaker 1: an exercise to like separate myself from my ego and

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Speaker 1: be like, yeah, people are trying to get places too,

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Speaker 1: I'm not in a rush. They might be fuck it.

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Speaker 1: Yeah fine.

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Speaker 3: I always tell myself when I'm dealing with traffic and

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Speaker 3: people being assholes in traffic. Most of the time they

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Speaker 3: don't know who you are and they don't care. Yeah,

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Speaker 3: you're a car they're trying to get by. No one

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Speaker 3: is like, that's Sam in that car, and I'm gonna

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Speaker 3: show them.

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Speaker 1: Oh that's Sam Sanders. Oh I'll be waiting for this

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Speaker 1: fucking day. I know they would be an asshole to

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Speaker 1: any car you were just in the way. Yeah, exactly,

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Speaker 1: a bogie yep. Sam Sanders on the road in front

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Speaker 1: of us. He's trying to zipper merge. He's trying to

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Speaker 1: ziper merge.

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Speaker 2: I backed out of my driveway this morning to take

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Speaker 2: my kids to school, and a car, like two cars

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Speaker 2: stopped to let me out.

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Speaker 1: It was like, thank you so much. Third car zoomed

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Speaker 1: around all of us, and just I just.

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Speaker 3: Can I tell you my worst fantasy about dealing with

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Speaker 3: road rage. I've thought a lot about whether or not

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Speaker 3: I could acquire those spikes that flattened tires and just

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Speaker 3: have them to toss out like Mario Kart when someone.

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Speaker 2: Kisses me off somehow, like drive fast enough to get

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Speaker 2: around them. Yes, but they're still giving you the finger

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Speaker 2: out the back of their car, like laughing, laughing, and

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Speaker 2: then you just say, I am.

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Speaker 1: Not the one. I am not the one, and today

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Speaker 1: is not the day. I always had a fantasy that

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Speaker 1: like I could have enough money, like fuck you money,

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Speaker 1: where I just had a car that I just talked

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Speaker 1: lessons in it. I'm not slowing down. I know you

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Speaker 1: think you can cut me off, but we'll get no

438
00:22:05,720 --> 00:22:08,040
Speaker 1: light out. That's bab and it will be your fault.

439
00:22:08,119 --> 00:22:10,280
Speaker 1: And I have time and guess what I am on

440
00:22:10,359 --> 00:22:12,680
Speaker 1: my fifth insurance provider boom, because they know this is

441
00:22:12,760 --> 00:22:15,040
Speaker 1: my fuck you car, This is my fuck you car

442
00:22:15,480 --> 00:22:17,480
Speaker 1: around to find out. Yeah, and that's what I'm like.

443
00:22:17,600 --> 00:22:19,280
Speaker 1: This is again, these are all things that the car

444
00:22:19,400 --> 00:22:20,000
Speaker 1: in more ways.

445
00:22:20,080 --> 00:22:23,359
Speaker 5: So all this to say, let's walk more as a

446
00:22:23,400 --> 00:22:28,320
Speaker 5: society exactly, let's walk, Yeah, walk more, and be very

447
00:22:28,720 --> 00:22:32,600
Speaker 5: careful when you're walking across the street because people no

448
00:22:32,800 --> 00:22:34,920
Speaker 5: longer can see pedestrians.

449
00:22:35,119 --> 00:22:38,320
Speaker 1: It's just not they they it's it's not happening anymore.

450
00:22:38,960 --> 00:22:41,200
Speaker 3: And if you ever are on the fence about thinking

451
00:22:41,240 --> 00:22:44,560
Speaker 3: you want to exhibit road rage, just remember you do

452
00:22:44,720 --> 00:22:47,639
Speaker 3: not know who has a gun and there, yes.

453
00:22:48,119 --> 00:22:50,280
Speaker 1: You actually who has or who has a strip of

454
00:22:50,359 --> 00:22:53,119
Speaker 1: spikes you knows.

455
00:22:52,320 --> 00:22:57,240
Speaker 2: Right, or who has the red shell from Mario car? Hey, Sam,

456
00:22:57,320 --> 00:22:59,560
Speaker 2: what's something you think is overrated? Oh?

457
00:23:00,280 --> 00:23:01,560
Speaker 1: Controversial opinion? Here?

458
00:23:02,400 --> 00:23:06,440
Speaker 3: The Spotify algorithm. Oh it was really great for a while,

459
00:23:06,520 --> 00:23:08,400
Speaker 3: but have you noticed over the last year it's gotten worse.

460
00:23:09,240 --> 00:23:13,080
Speaker 1: I've as I'm a long time Spotify user. The algorithm

461
00:23:13,200 --> 00:23:17,320
Speaker 1: has half giveth many great suggestions and now my Discover

462
00:23:17,480 --> 00:23:20,520
Speaker 1: weekly is like a mess. It's a mess. It's not

463
00:23:20,800 --> 00:23:22,920
Speaker 1: it's not giving me the great And I've talked about

464
00:23:22,920 --> 00:23:25,200
Speaker 1: who the DJ the DJ part.

465
00:23:25,040 --> 00:23:27,520
Speaker 3: Of it, whoeveryone is like does that sounds that sounds

466
00:23:27,560 --> 00:23:30,320
Speaker 3: like sim People like, oh the Spotify DJ sounds like you, Sam,

467
00:23:30,400 --> 00:23:32,000
Speaker 3: and I'm like, one the racism not.

468
00:23:32,040 --> 00:23:34,040
Speaker 1: All, I don't know, it sounds like you.

469
00:23:34,200 --> 00:23:36,520
Speaker 3: And two if Spotify was paying me to be a

470
00:23:36,600 --> 00:23:38,880
Speaker 3: DJ voice, I wouldn't be doing shit else but taking

471
00:23:38,920 --> 00:23:40,920
Speaker 3: on Spotify money. You know, when I hear me on

472
00:23:41,000 --> 00:23:43,920
Speaker 3: podcasts like this, I'd be taking Spotify money. And no,

473
00:23:44,040 --> 00:23:44,920
Speaker 3: it's bad now, right.

474
00:23:44,960 --> 00:23:47,600
Speaker 1: Isn't it bad now? I definitely feel like because the

475
00:23:47,680 --> 00:23:49,639
Speaker 1: thing is it in? You know, like we use a

476
00:23:50,040 --> 00:23:53,399
Speaker 1: like my account on like whatever like smart speaker we

477
00:23:53,520 --> 00:23:56,560
Speaker 1: have so when we say so, sometimes we put other

478
00:23:56,680 --> 00:23:58,440
Speaker 1: music on that isn't my taste and then the next

479
00:23:58,480 --> 00:23:59,840
Speaker 1: thing is like, oh so you love this kind of

480
00:23:59,880 --> 00:24:02,119
Speaker 1: a like indie pop music and like not really, man

481
00:24:02,200 --> 00:24:04,200
Speaker 1: like please take it in totality like that was a

482
00:24:04,359 --> 00:24:07,320
Speaker 1: that was a moment, but that's not where my entire

483
00:24:07,480 --> 00:24:10,320
Speaker 1: interests lined. So yeah, it's gotten a little bit harder.

484
00:24:11,000 --> 00:24:12,080
Speaker 1: I had a theory about this.

485
00:24:12,640 --> 00:24:15,359
Speaker 3: So a few months ago Spotify made news because they

486
00:24:15,720 --> 00:24:20,880
Speaker 3: said and announced that new an upcoming artists could pay

487
00:24:20,920 --> 00:24:24,399
Speaker 3: Spotify money to have their songs show up higher in

488
00:24:24,480 --> 00:24:27,520
Speaker 3: people's algorithms and show up more frequently. And I think

489
00:24:27,560 --> 00:24:30,680
Speaker 3: as soon as that happened, it it really screwed with

490
00:24:31,480 --> 00:24:35,560
Speaker 3: the algorithm just tuning into me and my interest. I

491
00:24:35,720 --> 00:24:40,399
Speaker 3: also think that they have leaned more on giving you

492
00:24:40,520 --> 00:24:42,360
Speaker 3: more of the songs you already listened to a lot,

493
00:24:42,840 --> 00:24:44,280
Speaker 3: like I think we all had that three or four

494
00:24:44,320 --> 00:24:46,920
Speaker 3: months this year, where as soon as a playlist was

495
00:24:46,960 --> 00:24:49,320
Speaker 3: done or an album was done, the next song you

496
00:24:49,400 --> 00:24:52,080
Speaker 3: heard was Espresso by Sabrina Carpenter.

497
00:24:52,359 --> 00:24:53,320
Speaker 1: I couldn't avoid it.

498
00:24:53,920 --> 00:24:56,280
Speaker 3: And it felt like the algorithm of two or three

499
00:24:56,320 --> 00:24:58,760
Speaker 3: years ago was more expansive and just gave me more

500
00:24:58,840 --> 00:25:00,360
Speaker 3: new stuff that you'd never heard before.

501
00:25:00,520 --> 00:25:03,000
Speaker 1: But they felt aligned with their interest. It exchanged.

502
00:25:04,119 --> 00:25:06,440
Speaker 2: They're going through the shit the radio went through with

503
00:25:06,600 --> 00:25:09,320
Speaker 2: like Payola and exactly, yeah for sure.

504
00:25:09,520 --> 00:25:12,320
Speaker 1: But also we love spotifym my podcast thank you.

505
00:25:12,400 --> 00:25:15,720
Speaker 2: Yeah, yeah, we love Spotify to remember, we love it,

506
00:25:16,000 --> 00:25:19,879
Speaker 2: and also and Apple especially the podcast app doesn't have

507
00:25:19,960 --> 00:25:21,080
Speaker 2: any of these problems.

508
00:25:21,160 --> 00:25:26,800
Speaker 1: So no Apple Io Apple a friend of Woke a

509
00:25:26,960 --> 00:25:30,040
Speaker 1: woke god. We love the iOS updates, we love the

510
00:25:30,119 --> 00:25:33,320
Speaker 1: iOS find out. We love to have a podcast.

511
00:25:34,560 --> 00:25:37,200
Speaker 2: The I mean, I remember when this happened to Facebook.

512
00:25:37,240 --> 00:25:41,600
Speaker 2: It feels like every every piece of technology that is

513
00:25:41,720 --> 00:25:46,399
Speaker 2: designed around helping you find information or a thing that

514
00:25:46,520 --> 00:25:48,600
Speaker 2: is going to be entertaining to you goes through this

515
00:25:48,720 --> 00:25:53,159
Speaker 2: process where algorithm is designed to find a thing, like

516
00:25:53,560 --> 00:25:56,080
Speaker 2: and it gets it gets really good at helping you

517
00:25:56,200 --> 00:25:59,520
Speaker 2: find the thing that you want. And then they're like, okay,

518
00:25:59,560 --> 00:26:02,399
Speaker 2: and now we're making money, Like now we have these

519
00:26:02,520 --> 00:26:05,560
Speaker 2: massive numbers, and now we slowly make the product worse

520
00:26:05,640 --> 00:26:09,480
Speaker 2: and worse and worse. And I still remember like Facebook

521
00:26:09,800 --> 00:26:12,000
Speaker 2: was a good place for people to find things.

522
00:26:12,160 --> 00:26:15,160
Speaker 1: I had my phone numbers and my address on Facebook.

523
00:26:15,200 --> 00:26:18,080
Speaker 1: It was so great. Yeah, and then they were like okay,

524
00:26:18,119 --> 00:26:18,760
Speaker 1: and now we.

525
00:26:20,359 --> 00:26:22,080
Speaker 2: Like I remember, you know, on the other side, as

526
00:26:22,200 --> 00:26:24,639
Speaker 2: like somebody who was making content at that time, like

527
00:26:24,840 --> 00:26:27,679
Speaker 2: our you know, content was having a ton of success

528
00:26:27,720 --> 00:26:30,359
Speaker 2: on Facebook. And then slowly they were like, okay, you

529
00:26:30,480 --> 00:26:33,960
Speaker 2: can pay us to be like positioned better. And then

530
00:26:34,200 --> 00:26:37,560
Speaker 2: eventually it was you will not show up unless you

531
00:26:37,720 --> 00:26:41,560
Speaker 2: pay us, and that at that point, it's just only

532
00:26:41,720 --> 00:26:44,879
Speaker 2: the most gullible and not aware of like what is

533
00:26:45,000 --> 00:26:48,480
Speaker 2: actually happening to them. Aka, you know boomers are still

534
00:26:48,560 --> 00:26:50,120
Speaker 2: going to use that product at that point.

535
00:26:50,800 --> 00:26:51,359
Speaker 1: Can I tell you?

536
00:26:51,720 --> 00:26:56,840
Speaker 3: This brings up what is one of my favorite essays

537
00:26:56,920 --> 00:26:59,359
Speaker 3: that has explained the way the internet and apps have

538
00:26:59,400 --> 00:27:01,760
Speaker 3: treated us for fifteen years. You've probably read it before.

539
00:27:02,359 --> 00:27:07,119
Speaker 3: This writer and thinker called Cory Doctorow. He has a

540
00:27:07,240 --> 00:27:08,680
Speaker 3: theory called in shiitification.

541
00:27:09,080 --> 00:27:10,560
Speaker 1: Yeah, and he wrote this es.

542
00:27:10,520 --> 00:27:13,000
Speaker 3: Say about the incertification of everything. Y'all have heard it before.

543
00:27:13,080 --> 00:27:16,159
Speaker 3: But basically he argues that first these new apps, these

544
00:27:16,200 --> 00:27:19,080
Speaker 3: new vendors, these new players, they do whatever it takes

545
00:27:19,119 --> 00:27:22,879
Speaker 3: to attract users and be good to users. Then they

546
00:27:22,960 --> 00:27:25,960
Speaker 3: do whatever it takes to attract business customers, which means

547
00:27:26,359 --> 00:27:31,200
Speaker 3: that users matters less. And then they make their business

548
00:27:31,240 --> 00:27:35,560
Speaker 3: model just serve the shareholders in maximizing profit. And so,

549
00:27:35,960 --> 00:27:38,520
Speaker 3: without fail, an app that was really good to users,

550
00:27:39,200 --> 00:27:42,440
Speaker 3: within three to five years, it's only good for shareholders.

551
00:27:42,680 --> 00:27:45,399
Speaker 1: And this happens with whatever the app is.

552
00:27:46,119 --> 00:27:49,560
Speaker 2: Yeah, and it's currently the app that is gaining steam

553
00:27:49,680 --> 00:27:53,560
Speaker 2: because it's not doing the in stification aka rot economy.

554
00:27:53,600 --> 00:27:55,760
Speaker 2: We've called it before on the show shout out to

555
00:27:56,160 --> 00:28:03,000
Speaker 2: what's that his name, Ron, who calls it the rott economy.

556
00:28:03,240 --> 00:28:05,800
Speaker 2: But it feels like TikTok's the one place that isn't

557
00:28:06,119 --> 00:28:07,720
Speaker 2: actively making its product worse.

558
00:28:07,720 --> 00:28:11,000
Speaker 1: Or just wait monitor way once they find out how

559
00:28:11,040 --> 00:28:11,720
Speaker 1: to monetize it.

560
00:28:12,240 --> 00:28:14,879
Speaker 2: Yeah, the fact that like they're trying to figure out,

561
00:28:14,960 --> 00:28:17,320
Speaker 2: like how what's the next money making thing? Is it Ai,

562
00:28:17,600 --> 00:28:21,600
Speaker 2: like ai that writes shitty news articles for you or

563
00:28:21,760 --> 00:28:24,360
Speaker 2: you know, it's just like no, just have the thing

564
00:28:24,520 --> 00:28:27,520
Speaker 2: that is going to be good once TikTok starts being shitty,

565
00:28:27,640 --> 00:28:30,960
Speaker 2: because that's an inevitability.

566
00:28:30,880 --> 00:28:33,200
Speaker 1: Because they're trying, because like TikTok is really trying with

567
00:28:33,280 --> 00:28:34,160
Speaker 1: that TikTok shop.

568
00:28:34,280 --> 00:28:37,320
Speaker 3: But I think people really figured out quite quickly that

569
00:28:37,440 --> 00:28:38,960
Speaker 3: the stuff on the TikTok shop is.

570
00:28:39,000 --> 00:28:41,920
Speaker 1: Like worse than Timu. It's bad stuff you don't.

571
00:28:41,760 --> 00:28:44,760
Speaker 2: Want that, you don't want that turn green, even if

572
00:28:44,800 --> 00:28:47,120
Speaker 2: it's not a piece of jewelry that goes around your neck.

573
00:28:48,600 --> 00:28:50,120
Speaker 1: Somehow. Mm hmm.

574
00:28:50,880 --> 00:28:54,680
Speaker 3: Sorry, I like geek out on the incentification ship. It

575
00:28:54,760 --> 00:28:55,480
Speaker 3: explains everything.

576
00:28:55,560 --> 00:28:59,160
Speaker 1: It explains Oh yeah, cause most people just do the

577
00:28:59,200 --> 00:29:01,240
Speaker 1: thing where they're like this used to be good it

578
00:29:01,360 --> 00:29:03,200
Speaker 1: used to be good. Yeah, and then you're like, we're

579
00:29:03,280 --> 00:29:07,640
Speaker 1: just like so it's called shareholder value. Shareholder value, and

580
00:29:07,760 --> 00:29:08,800
Speaker 1: it's ruining everything.

581
00:29:09,280 --> 00:29:14,080
Speaker 2: Literally when Mark Zuckerberg walked into shareholder meetings and flip flops, yeah,

582
00:29:14,720 --> 00:29:18,959
Speaker 2: I'm aldoh bitch, and then he's eventually like, we need

583
00:29:19,040 --> 00:29:20,440
Speaker 2: to capture shareholder value.

584
00:29:20,560 --> 00:29:23,320
Speaker 3: So yeah, yeah, right now what shareholders are ruining and

585
00:29:23,440 --> 00:29:25,520
Speaker 3: what VC is ruining. There's tons of coverage around this

586
00:29:26,240 --> 00:29:30,480
Speaker 3: VC and venture capital. They're buying up veterinary care, so

587
00:29:30,560 --> 00:29:33,160
Speaker 3: a lot of vats that were private are now owned

588
00:29:33,200 --> 00:29:35,160
Speaker 3: by these vcs. And you'll notice all the rights of

589
00:29:35,240 --> 00:29:38,080
Speaker 3: going up. Yeah, all the rights for private equity is uh,

590
00:29:38,920 --> 00:29:40,320
Speaker 3: the devil private equity You're right, not.

591
00:29:40,400 --> 00:29:43,480
Speaker 1: Via the devil, Corey doctor al. He's got a really

592
00:29:43,520 --> 00:29:46,120
Speaker 1: good substack post on just private equity too. That's just

593
00:29:46,200 --> 00:29:49,959
Speaker 1: how it's like everything died because of this red well

594
00:29:50,040 --> 00:29:51,000
Speaker 1: it's just smart.

595
00:29:51,200 --> 00:29:53,920
Speaker 3: Yeah, it's perverse sentives because their goal is not to

596
00:29:53,960 --> 00:29:55,520
Speaker 3: make a good company, is to make things that they

597
00:29:55,520 --> 00:29:58,880
Speaker 3: can sell for parts. Right, Yeah, you don't get me started, okay,

598
00:29:58,920 --> 00:30:00,920
Speaker 3: all right, sorry, yeah, we we won't.

599
00:30:01,280 --> 00:30:13,880
Speaker 1: Let's take a quick break. We'll be right back and

600
00:30:14,200 --> 00:30:17,120
Speaker 1: we're back and just a whore.

601
00:30:17,200 --> 00:30:20,720
Speaker 2: You know, we recently talked about Hurricane Helene and these

602
00:30:21,000 --> 00:30:24,120
Speaker 2: storms that are doing things that storms used to not do.

603
00:30:24,600 --> 00:30:27,120
Speaker 2: They used to be or they would happen, you know,

604
00:30:27,280 --> 00:30:30,400
Speaker 2: once a century, once every two century, and now they're

605
00:30:30,440 --> 00:30:34,200
Speaker 2: happening on a pretty regular basis. And before we were

606
00:30:34,280 --> 00:30:40,080
Speaker 2: finished saying that sentence, another even bigger hurricane started developing

607
00:30:40,280 --> 00:30:43,520
Speaker 2: in the Gulf of Mexico. Just like chilling in the

608
00:30:43,560 --> 00:30:48,640
Speaker 2: Gulf of Mexico, fucking terrifying storm. Hurricane Milton. It's intensifying

609
00:30:48,640 --> 00:30:52,760
Speaker 2: at a rate that like, I don't know, this clip

610
00:30:52,800 --> 00:30:54,520
Speaker 2: you found, Miles kind of blew my mind.

611
00:30:54,960 --> 00:30:57,200
Speaker 1: Yeah, I mean I think you saw things like it

612
00:30:57,280 --> 00:30:59,960
Speaker 1: started as a tropical storm and then became a Category

613
00:31:00,360 --> 00:31:02,960
Speaker 1: four just over the weekend. And people are like, that's

614
00:31:03,360 --> 00:31:07,040
Speaker 1: a progression that is pretty wild. And yeah, like you said,

615
00:31:07,040 --> 00:31:11,320
Speaker 1: I'm like, like hearing meteorologists and atmospheric scientists talk about it,

616
00:31:11,360 --> 00:31:15,920
Speaker 1: I'm like, I'm a podcaster. What does this all means? Simple?

617
00:31:16,040 --> 00:31:19,080
Speaker 1: Put right? So, like Helene brought like a four day

618
00:31:19,240 --> 00:31:22,280
Speaker 1: between four and eight feet of a storm search which

619
00:31:22,360 --> 00:31:25,200
Speaker 1: is to cause terrible damage. Milton is expected to bring

620
00:31:25,320 --> 00:31:28,920
Speaker 1: between ten and fifteen feet of like water, like we're

621
00:31:29,000 --> 00:31:32,440
Speaker 1: the wall, Yes, a wall of water storm surge that

622
00:31:32,560 --> 00:31:36,000
Speaker 1: has been described by the mayor of Tampa as unsurvivable.

623
00:31:36,080 --> 00:31:38,720
Speaker 1: They're saying, if you do not leave, write your name

624
00:31:38,920 --> 00:31:43,240
Speaker 1: on your body so people can identify. Listen, if you

625
00:31:43,400 --> 00:31:49,520
Speaker 1: got Tampa people saying it's unsurvivable, believe them. Yeah. And

626
00:31:49,680 --> 00:31:52,520
Speaker 1: so the thing that really freaked me out or not

627
00:31:52,560 --> 00:31:54,600
Speaker 1: freaked I mean, yes, freaked me out or I got

628
00:31:54,680 --> 00:31:56,920
Speaker 1: I understood, just the severity of it is this clip

629
00:31:57,120 --> 00:32:01,360
Speaker 1: of this meteorologist, nam John Morales, who's in Florida. He's

630
00:32:01,480 --> 00:32:05,200
Speaker 1: merely just watching the storm sort of you know, evolve,

631
00:32:05,720 --> 00:32:09,040
Speaker 1: and he is absolutely his breath is taken by this.

632
00:32:09,200 --> 00:32:10,760
Speaker 1: And I'll just play this for you because I think

633
00:32:10,840 --> 00:32:12,480
Speaker 1: it's like one of those scenes in a movie where

634
00:32:12,480 --> 00:32:15,120
Speaker 1: you hear like a scientist like sort of like just

635
00:32:15,520 --> 00:32:18,840
Speaker 1: like clutch their shirt or something in horror. That's kind

636
00:32:18,880 --> 00:32:20,680
Speaker 1: of what this feels like. So this is John Morales

637
00:32:20,760 --> 00:32:23,440
Speaker 1: sort of talking about just how powerful it's becoming and

638
00:32:23,480 --> 00:32:24,720
Speaker 1: how quickly it's become powerful.

639
00:32:25,000 --> 00:32:29,760
Speaker 6: It's just an incredible, incredible, incredible hurricane. It has dropped

640
00:32:34,800 --> 00:32:42,360
Speaker 6: he has dropped fifteen mili bars in ten hours. I apologize.

641
00:32:42,600 --> 00:32:43,160
Speaker 1: This is just.

642
00:32:44,760 --> 00:32:49,880
Speaker 6: Horrific when maximum sustained winds are one hundred and sixty

643
00:32:50,000 --> 00:32:56,200
Speaker 6: miles per hour and it it is just gaining strength

644
00:32:56,240 --> 00:32:59,280
Speaker 6: in the Gulf of Mexico where you can imagine the winds.

645
00:32:59,400 --> 00:33:04,440
Speaker 6: I mean, these are just so incredibly incredibly hot, a

646
00:33:04,600 --> 00:33:06,320
Speaker 6: record hot as you might imagine.

647
00:33:06,480 --> 00:33:08,480
Speaker 1: You know what's driving that. I don't need to tell you,

648
00:33:08,600 --> 00:33:12,360
Speaker 1: Globerg what what what is this guy talking about? I

649
00:33:12,440 --> 00:33:17,560
Speaker 1: didn't know that we were I was just channel Come on, man, well,

650
00:33:17,600 --> 00:33:21,120
Speaker 1: here's the thing. Is obviously the lower the pressure, the

651
00:33:21,320 --> 00:33:25,080
Speaker 1: higher the intensity, right, so when it's dropping that quickly,

652
00:33:25,400 --> 00:33:27,600
Speaker 1: it's intensifying at a rate. That's why he was just

653
00:33:27,760 --> 00:33:31,000
Speaker 1: like the he just couldn't believe what he was seeing.

654
00:33:31,480 --> 00:33:33,960
Speaker 1: And you and you understand that's why you're going to

655
00:33:34,040 --> 00:33:37,480
Speaker 1: get these like storm surges that are catastrophic. So while

656
00:33:37,560 --> 00:33:40,080
Speaker 1: this is happening now, that's that's someone who's trying to

657
00:33:40,120 --> 00:33:42,760
Speaker 1: communicate the severity of this storm that people need to

658
00:33:42,920 --> 00:33:45,800
Speaker 1: get like to evacuate if possible, and do whatever they

659
00:33:45,840 --> 00:33:48,880
Speaker 1: can to stay safe. You got Ron DeSantis over here,

660
00:33:49,040 --> 00:33:52,640
Speaker 1: the governor of Florida, just like now, evoking like the

661
00:33:52,800 --> 00:33:57,400
Speaker 1: specter of people of color looting, right, this is.

662
00:33:57,480 --> 00:34:01,040
Speaker 7: Not going to be an opportunity for folks to take

663
00:34:01,080 --> 00:34:04,120
Speaker 7: advantage of people. If you think you're going to go

664
00:34:04,240 --> 00:34:06,840
Speaker 7: in and loot, you got another thing coming. You go

665
00:34:06,920 --> 00:34:09,920
Speaker 7: into somebody's house after the storm passes, think that that

666
00:34:10,040 --> 00:34:14,040
Speaker 7: you're going to be able to commit crimes, You're going

667
00:34:14,120 --> 00:34:16,759
Speaker 7: to get in really serious trouble and quite frankly, you

668
00:34:16,800 --> 00:34:19,760
Speaker 7: don't know what's behind that door in a Second Amendment state,

669
00:34:19,920 --> 00:34:24,440
Speaker 7: So do not try to take advantage of people who

670
00:34:24,520 --> 00:34:27,080
Speaker 7: are suffering because of the results of this storm.

671
00:34:27,880 --> 00:34:30,880
Speaker 1: Yeah, so that's what he's most concerned about.

672
00:34:32,239 --> 00:34:32,279
Speaker 6: That.

673
00:34:33,040 --> 00:34:36,480
Speaker 1: What about people who like, what about critical medical infrastructure

674
00:34:36,520 --> 00:34:38,480
Speaker 1: if the power goes out? What of those people? And

675
00:34:38,560 --> 00:34:39,680
Speaker 1: you're doing this thing where it's like.

676
00:34:40,320 --> 00:34:45,480
Speaker 3: Yeah, dirty, hairy about what about Ron DeSantis fighting the

677
00:34:45,560 --> 00:34:48,120
Speaker 3: disinformation coming from Donald Trump ahead of his party?

678
00:34:48,280 --> 00:34:52,240
Speaker 1: What about that? Yeah? What about him actively avoiding phone

679
00:34:52,280 --> 00:34:55,279
Speaker 1: calls from Joe Biden or Kamala Harris because he doesn't

680
00:34:55,320 --> 00:34:57,800
Speaker 1: want their help, because he doesn't like he's trying to

681
00:34:57,840 --> 00:35:00,759
Speaker 1: politicize him, Like we're fine over here, I meet Paul

682
00:35:00,920 --> 00:35:05,360
Speaker 1: rob And also like, aren't all states Second Amendment states,

683
00:35:05,560 --> 00:35:10,320
Speaker 1: like if we're talking about the whatever, that's just that's associate.

684
00:35:09,680 --> 00:35:13,400
Speaker 2: With the ability to shoot anyone who like accidentally steps

685
00:35:13,480 --> 00:35:16,759
Speaker 2: on your property to with Florida. But yeah, I mean

686
00:35:16,880 --> 00:35:20,160
Speaker 2: technically the Second Amendment does exist in all states. He

687
00:35:20,600 --> 00:35:23,120
Speaker 2: it's just so wild because like to get to that

688
00:35:23,360 --> 00:35:26,000
Speaker 2: messaging that he's so desperately wanted to get to, he

689
00:35:26,200 --> 00:35:30,440
Speaker 2: has to set up a scenario where everybody's sticking around,

690
00:35:30,640 --> 00:35:34,200
Speaker 2: which is the whole fucking point he's trying to like

691
00:35:34,320 --> 00:35:37,239
Speaker 2: he's supposed to be getting is like get out, get out,

692
00:35:37,600 --> 00:35:39,840
Speaker 2: And he's like, and you know, if you're sticking around,

693
00:35:40,239 --> 00:35:44,080
Speaker 2: those homeowners might be super tough and cool and sticking around.

694
00:35:44,239 --> 00:35:47,719
Speaker 2: So like he's he's doing the opposite of sending the

695
00:35:47,760 --> 00:35:51,719
Speaker 2: message that he's supposed to be sending. Yeah, which, well

696
00:35:51,880 --> 00:35:54,840
Speaker 2: just one of like three thousand frustrating things about that.

697
00:35:55,080 --> 00:35:57,280
Speaker 1: But yeah, I don't know, horrible.

698
00:35:58,920 --> 00:36:03,000
Speaker 3: Yeah, I've been upset with all of the misinformation that's

699
00:36:03,080 --> 00:36:05,920
Speaker 3: been circling around recovery.

700
00:36:06,680 --> 00:36:06,839
Speaker 1: Right.

701
00:36:07,560 --> 00:36:09,600
Speaker 3: You know, there's some theories that were just coming from

702
00:36:09,640 --> 00:36:12,080
Speaker 3: the Internet. There's some theories that were coming from like

703
00:36:12,239 --> 00:36:15,680
Speaker 3: Marjorie Taylor Green, but like Donald Trump has had his

704
00:36:15,840 --> 00:36:18,880
Speaker 3: fingers and all of this just spreading lies. Yeah, like

705
00:36:20,000 --> 00:36:22,319
Speaker 3: there's a long list that I compiled. I don't even

706
00:36:22,320 --> 00:36:25,160
Speaker 3: want to go through it all, but it's just like ridiculous.

707
00:36:25,400 --> 00:36:28,680
Speaker 3: He has claimed that FEMA and the federal government were

708
00:36:28,840 --> 00:36:31,520
Speaker 3: quote going out of their way to not help people

709
00:36:31,680 --> 00:36:35,480
Speaker 3: in Red states. He claimed that Kamala spent all the

710
00:36:35,560 --> 00:36:39,319
Speaker 3: FEMA money on housing illegal immigrants. Yeah, he said there

711
00:36:39,360 --> 00:36:43,080
Speaker 3: were no helicopters or rescue in North Carolina. Like, it's

712
00:36:43,239 --> 00:36:47,239
Speaker 3: just nonsensical and so unhelpful at a moment when the

713
00:36:47,680 --> 00:36:50,439
Speaker 3: number one priority should be how do we get money,

714
00:36:50,520 --> 00:36:52,920
Speaker 3: aid and relief to whoever the fuck needs it? And

715
00:36:53,000 --> 00:36:55,840
Speaker 3: that's what FEMA's trying to do. Not a perfect organization,

716
00:36:56,080 --> 00:36:56,800
Speaker 3: but they're trying.

717
00:36:57,160 --> 00:36:59,880
Speaker 1: Yeah, and exactly. And also, like you know, the budgets

718
00:37:00,040 --> 00:37:03,200
Speaker 1: aren't dictated by Joe Biden or Kamala Harris. That's from

719
00:37:03,320 --> 00:37:07,080
Speaker 1: Congress exactly, and that's part of the that's part of DHS.

720
00:37:07,200 --> 00:37:09,800
Speaker 1: There's a lot of stuff that like again because like

721
00:37:09,960 --> 00:37:12,040
Speaker 1: the structure of the government is not really something most

722
00:37:12,080 --> 00:37:15,840
Speaker 1: people are paying attention to. That it's easiest one, Oh, immigrants,

723
00:37:15,920 --> 00:37:17,840
Speaker 1: they get all the money. So there's no, there's no

724
00:37:18,000 --> 00:37:22,400
Speaker 1: disaster relief money, Like, no, that's not what is happening. Yeah. Good.

725
00:37:23,440 --> 00:37:28,240
Speaker 3: And the politicization of what is usually and customarily something

726
00:37:28,320 --> 00:37:29,920
Speaker 3: both sides they I'll get along on.

727
00:37:30,200 --> 00:37:31,240
Speaker 1: That's been so strange.

728
00:37:31,560 --> 00:37:34,000
Speaker 3: I remember when I was a kid, it didn't matter

729
00:37:34,239 --> 00:37:36,600
Speaker 3: if the governor of your state was a Republican or

730
00:37:36,640 --> 00:37:39,680
Speaker 3: a Democrat. If there was a natural disaster, you made

731
00:37:39,680 --> 00:37:42,600
Speaker 3: an emergent declaration, you asked for that femal money and

732
00:37:42,719 --> 00:37:45,120
Speaker 3: you got it, and the President called the governor and

733
00:37:45,200 --> 00:37:47,480
Speaker 3: they talked, and party didn't matter because you wanted to

734
00:37:47,560 --> 00:37:49,840
Speaker 3: get money and aid to people.

735
00:37:50,600 --> 00:37:50,719
Speaker 1: Right.

736
00:37:50,800 --> 00:37:53,640
Speaker 3: And the fact that you got Ron DeSantis and Trump

737
00:37:54,080 --> 00:37:58,080
Speaker 3: and others politicizing what should actually be the moment of

738
00:37:58,160 --> 00:38:00,000
Speaker 3: the most bipartisan collaboration.

739
00:38:00,880 --> 00:38:05,680
Speaker 1: Yeah, it is disgusting. Yeah, it's all. It's costing lives.

740
00:38:06,200 --> 00:38:09,759
Speaker 1: More people will die because of this bullshit. And like

741
00:38:09,880 --> 00:38:12,440
Speaker 1: Marjorie Taylor Greenow, she posts like, oh, you don't believe me.

742
00:38:12,480 --> 00:38:14,920
Speaker 1: Look at all these patents the US government has filed.

743
00:38:14,960 --> 00:38:17,880
Speaker 1: And if you like bother to click one, you're like

744
00:38:18,320 --> 00:38:22,080
Speaker 1: this one says about like dropping water from balloons to

745
00:38:22,239 --> 00:38:25,040
Speaker 1: make it to simulate rain, or just things have nothing

746
00:38:25,160 --> 00:38:27,279
Speaker 1: to do with actually controlling the weather, because as you

747
00:38:27,320 --> 00:38:30,759
Speaker 1: were saying earlier, she said they whoever they are. And

748
00:38:30,880 --> 00:38:32,399
Speaker 1: I know, you know, if you look at her history

749
00:38:32,400 --> 00:38:35,200
Speaker 1: of talking about people controlling the weather and shit, yes

750
00:38:35,400 --> 00:38:39,160
Speaker 1: she means usually antisy nonsense. And so the other thing

751
00:38:39,239 --> 00:38:41,000
Speaker 1: too is then you have like people like you know,

752
00:38:41,200 --> 00:38:44,640
Speaker 1: sexual predator and Sea Pac chairman Matt Schlapp, who's like

753
00:38:44,760 --> 00:38:47,880
Speaker 1: wondering out loud, tweeting stuff like quote, we will see

754
00:38:48,000 --> 00:38:50,919
Speaker 1: what happens with this most terrifying of hurricanes in the Gulf.

755
00:38:51,000 --> 00:38:53,520
Speaker 1: At some point we have to ask ourselves if there's

756
00:38:53,560 --> 00:38:56,759
Speaker 1: a divine attempt to get our attention and stop all

757
00:38:56,880 --> 00:39:00,360
Speaker 1: the insanity in our modern existence. And I'm like, I

758
00:39:00,440 --> 00:39:03,800
Speaker 1: guess if the insanity of our modern existence is the

759
00:39:03,920 --> 00:39:06,920
Speaker 1: continued burning of fossil fuels that hastens the death of

760
00:39:07,000 --> 00:39:09,560
Speaker 1: this planet, yeah, then this is definitely one of those

761
00:39:09,640 --> 00:39:14,120
Speaker 1: Jesus warnings. But if this is just a sad, you know,

762
00:39:14,320 --> 00:39:17,760
Speaker 1: regressive attempt to connect this shit to like trans rites

763
00:39:17,840 --> 00:39:20,360
Speaker 1: or something, then please fuck right off. Like we've retired

764
00:39:20,400 --> 00:39:21,840
Speaker 1: of this nonsense like trying to be like, you know,

765
00:39:22,120 --> 00:39:24,080
Speaker 1: you know why, because God hates you know, who that's

766
00:39:24,160 --> 00:39:25,359
Speaker 1: like us.

767
00:39:25,680 --> 00:39:27,640
Speaker 3: And then here's the most annoying part of all of it.

768
00:39:28,480 --> 00:39:31,360
Speaker 3: After the dust settles with this and the rain dries up,

769
00:39:32,000 --> 00:39:36,040
Speaker 3: the same Republican political leaders who were spreading lies about

770
00:39:36,080 --> 00:39:40,359
Speaker 3: FEMA and recovery will make campaign ads talking about how

771
00:39:40,400 --> 00:39:42,600
Speaker 3: they got federally funded to their districts.

772
00:39:42,800 --> 00:39:46,759
Speaker 1: Yeah, it has some bullshit. Yeah, and it's always funny too,

773
00:39:46,760 --> 00:39:48,920
Speaker 1: because I remember Lauren Bobert was like saying, like, you know,

774
00:39:49,600 --> 00:39:52,080
Speaker 1: the state didn't give Colorado anything. It's like, you voted

775
00:39:52,080 --> 00:39:54,280
Speaker 1: against these bills and then you said, then you touted

776
00:39:54,320 --> 00:39:56,560
Speaker 1: the benefits of it. She's like, well, you know, you

777
00:39:56,719 --> 00:40:00,759
Speaker 1: have to understand. But again, for that base, it doesn't matter.

778
00:40:01,000 --> 00:40:04,520
Speaker 1: It's just it's all it's it's all just part of

779
00:40:04,600 --> 00:40:06,799
Speaker 1: the narrative that they need to invest in. And yeah,

780
00:40:06,840 --> 00:40:10,759
Speaker 1: and here we are, here, we are here, we are Yeah.

781
00:40:11,400 --> 00:40:14,399
Speaker 1: I do feel like you still hear stories about people

782
00:40:14,640 --> 00:40:18,040
Speaker 1: just working together at a local, like human to human level,

783
00:40:18,800 --> 00:40:21,440
Speaker 1: like regardless of what their political affiliation is.

784
00:40:21,680 --> 00:40:24,399
Speaker 2: You know, people are still helping each other out when

785
00:40:24,719 --> 00:40:27,680
Speaker 2: a major disaster like this happens. It's just that the

786
00:40:28,280 --> 00:40:31,520
Speaker 2: leadership has gotten so polarized that they well, this isn't

787
00:40:31,680 --> 00:40:32,240
Speaker 2: work together.

788
00:40:32,520 --> 00:40:35,800
Speaker 3: Yeah, well, it's like you'll see these stories, especially in

789
00:40:36,239 --> 00:40:38,480
Speaker 3: like Louisiana and that part of the country.

790
00:40:38,600 --> 00:40:40,600
Speaker 1: It'll be like it'll be these.

791
00:40:40,680 --> 00:40:45,320
Speaker 3: Grizzly ass, middle aged white dudes who look like full Trumpers.

792
00:40:45,400 --> 00:40:47,839
Speaker 3: They would scare me if I saw them at night

793
00:40:47,960 --> 00:40:50,719
Speaker 3: on the street. But then the storm comes and they

794
00:40:50,840 --> 00:40:53,640
Speaker 3: just get in their boats and start saving people, and

795
00:40:53,719 --> 00:40:56,759
Speaker 3: it's just this beautiful harmony, like you will see the

796
00:40:56,880 --> 00:41:00,600
Speaker 3: most coming together of American people at the after a

797
00:41:00,680 --> 00:41:03,919
Speaker 3: disaster like this, black folks, white folks, rich folks, poor people.

798
00:41:04,400 --> 00:41:08,080
Speaker 3: And the fact that DeSantis and Trump and Marjorie are

799
00:41:08,160 --> 00:41:09,719
Speaker 3: trying to shit on that right now.

800
00:41:10,880 --> 00:41:14,279
Speaker 1: Oof yeah, yeah, pisses me off. It's just the I guess,

801
00:41:14,320 --> 00:41:17,040
Speaker 1: you know, especially looking at this election, that's just the

802
00:41:17,080 --> 00:41:20,080
Speaker 1: playbook is just to turn up the rhetoric to the

803
00:41:20,280 --> 00:41:23,239
Speaker 1: most disgusting levels and then just hoping it's like, well,

804
00:41:23,520 --> 00:41:26,400
Speaker 1: maybe we can turn out the people who really respond

805
00:41:26,480 --> 00:41:28,600
Speaker 1: to this really vile stuff, because like, we're not winning

806
00:41:28,600 --> 00:41:30,080
Speaker 1: people in the middle, so we might as well just

807
00:41:30,160 --> 00:41:31,440
Speaker 1: go further to the right and see who we can

808
00:41:31,480 --> 00:41:33,000
Speaker 1: turn it out mathematically there.

809
00:41:33,120 --> 00:41:36,440
Speaker 3: And it seems like a true extension of what Vance

810
00:41:36,520 --> 00:41:39,000
Speaker 3: and Trump were doing in Springfield, Ohio just a few

811
00:41:39,040 --> 00:41:42,240
Speaker 3: weeks ago, spreading lies about migrants eating cats and dogs.

812
00:41:42,520 --> 00:41:45,080
Speaker 3: They knew it wasn't true, but they lied and then

813
00:41:45,120 --> 00:41:47,759
Speaker 3: basically said they were lying and kept doing it. Right, Like,

814
00:41:48,440 --> 00:41:51,239
Speaker 3: even if these officials are called out about the lies

815
00:41:51,280 --> 00:41:55,440
Speaker 3: about hurricane stuff, they won't retract the statement, they won't apologize,

816
00:41:55,440 --> 00:41:56,680
Speaker 3: They'll just say, all right, whatever.

817
00:41:57,000 --> 00:41:59,279
Speaker 1: Yeah exactly. It's like, well, I guess maybe it wasn't

818
00:41:59,280 --> 00:42:00,520
Speaker 1: one of those warnings from God.

819
00:42:01,160 --> 00:42:04,640
Speaker 2: Yeah, yeah, yeah, all right, let's let's take a quick

820
00:42:04,680 --> 00:42:18,920
Speaker 2: break and we'll be right back, and we're back. You

821
00:42:19,040 --> 00:42:24,000
Speaker 2: might have seen a headlined maybe two that mentioned the

822
00:42:24,080 --> 00:42:28,480
Speaker 2: idea of October surprise. Hell, we've covered it on this podcast.

823
00:42:29,520 --> 00:42:32,759
Speaker 2: We're not we're not innocent. Our hands aren't clean. It's

824
00:42:33,320 --> 00:42:36,840
Speaker 2: it's kind of a perfect story because it's, you know,

825
00:42:36,920 --> 00:42:39,120
Speaker 2: it's like being scared of the dark. It's like, you know,

826
00:42:39,200 --> 00:42:43,200
Speaker 2: we don't know what it is, and so our imagination

827
00:42:43,520 --> 00:42:46,680
Speaker 2: can concoct all these things that could totally flip the

828
00:42:46,760 --> 00:42:49,320
Speaker 2: election on its head. Right, But it does seem to

829
00:42:49,360 --> 00:42:52,240
Speaker 2: have turned a corner to the point where the media

830
00:42:52,680 --> 00:42:57,480
Speaker 2: is just using this story to get clicks, get attention,

831
00:42:57,960 --> 00:43:02,560
Speaker 2: create a heightened sense of anxiety without there being really

832
00:43:02,600 --> 00:43:06,000
Speaker 2: anything there. So I'm just gonna read a couple headlines

833
00:43:06,400 --> 00:43:11,200
Speaker 2: for you. The first is from the BBC Notable tabloid.

834
00:43:11,560 --> 00:43:15,480
Speaker 2: The BBC wrote the headline Trump and Harris are deadlocked?

835
00:43:15,600 --> 00:43:17,879
Speaker 2: Could October surprise change the game?

836
00:43:19,440 --> 00:43:19,719
Speaker 1: Could it?

837
00:43:20,360 --> 00:43:23,640
Speaker 2: The potential October surprise looms a month before election?

838
00:43:23,880 --> 00:43:24,080
Speaker 1: Deck?

839
00:43:24,600 --> 00:43:28,759
Speaker 2: The potential October surprise looms a month before Like, that's

840
00:43:28,800 --> 00:43:31,719
Speaker 2: not even a sentence. That's from the State Press Statepress

841
00:43:31,719 --> 00:43:35,360
Speaker 2: dot com. Could us port strength be the October surprise

842
00:43:35,520 --> 00:43:39,200
Speaker 2: that trips up Kamala Harris? Is Malania Trump her husband's

843
00:43:39,200 --> 00:43:40,280
Speaker 2: October surprise?

844
00:43:40,760 --> 00:43:42,279
Speaker 1: That's courtesy of Northeastern.

845
00:43:42,680 --> 00:43:45,320
Speaker 2: And then this is my favorite because I actually clicked

846
00:43:45,360 --> 00:43:49,600
Speaker 2: through read this article how an October surprise could impact

847
00:43:49,760 --> 00:43:54,520
Speaker 2: the twenty twenty four election comma. According to Pulling Nostradamus,

848
00:43:54,920 --> 00:43:57,920
Speaker 2: uh So, I was like, Okay, I think I know

849
00:43:58,000 --> 00:44:00,279
Speaker 2: who they're talking about. It's the guy who has like

850
00:44:00,400 --> 00:44:02,920
Speaker 2: thirteen keys of the election.

851
00:44:03,200 --> 00:44:07,879
Speaker 1: He's been everywhere, he's been everywhere, hungry they're even doing

852
00:44:07,960 --> 00:44:10,279
Speaker 1: that is a horse race. They're like, ooh, she's got

853
00:44:10,360 --> 00:44:13,200
Speaker 1: ten of the thirteen keys. Ooh, maybe she has nine

854
00:44:13,239 --> 00:44:15,800
Speaker 1: of thirteen and Trump that's spot like okay, so it

855
00:44:15,920 --> 00:44:18,239
Speaker 1: is just want to pick me energy, look over here,

856
00:44:18,400 --> 00:44:20,879
Speaker 1: click over here, pick me yeah. Yeah.

857
00:44:21,360 --> 00:44:23,080
Speaker 2: So, first of all, it's interesting they call him the

858
00:44:23,120 --> 00:44:26,640
Speaker 2: polling noster Domas because his model does not take poles

859
00:44:26,640 --> 00:44:27,680
Speaker 2: into account at all.

860
00:44:28,080 --> 00:44:29,640
Speaker 1: In fact, it like explicitly does.

861
00:44:29,960 --> 00:44:33,480
Speaker 2: The point is that he's only looking at big picture stuff,

862
00:44:33,600 --> 00:44:36,680
Speaker 2: not polling, and is still able to do this. Also,

863
00:44:37,280 --> 00:44:40,200
Speaker 2: he's been able to pick the right election every time

864
00:44:40,360 --> 00:44:42,000
Speaker 2: since nineteen eighty.

865
00:44:42,440 --> 00:44:44,239
Speaker 1: Except for al Gore.

866
00:44:44,800 --> 00:44:47,880
Speaker 2: And he's like, yeah, but al Gore won the popular vote,

867
00:44:48,160 --> 00:44:50,919
Speaker 2: and then people are like, okay, so then what about

868
00:44:50,960 --> 00:44:54,520
Speaker 2: Trump because he picked Trump in twenty sixteen and he

869
00:44:54,800 --> 00:44:58,360
Speaker 2: did on the popular vote. Yeah, And he's like, and

870
00:44:58,400 --> 00:45:00,360
Speaker 2: then he throws a smoke bomb on the around and

871
00:45:00,520 --> 00:45:04,000
Speaker 2: dives through a window. But the so the way the

872
00:45:04,080 --> 00:45:07,360
Speaker 2: headline is constructed, how an October surprise could impact the

873
00:45:07,440 --> 00:45:10,759
Speaker 2: twenty twenty four election, You would seem to think that

874
00:45:10,880 --> 00:45:14,000
Speaker 2: there's an answer in the article that is like, here's

875
00:45:14,080 --> 00:45:14,560
Speaker 2: how could it.

876
00:45:14,920 --> 00:45:19,680
Speaker 1: Yeah, The answer, in fact is it won't. It won't impact.

877
00:45:20,040 --> 00:45:21,200
Speaker 1: That's how they.

878
00:45:21,200 --> 00:45:25,120
Speaker 2: Literally ask him and in the first paragraph, he's like, yeah,

879
00:45:25,120 --> 00:45:28,720
Speaker 2: I've never once changed my prediction based on an October surprise.

880
00:45:29,239 --> 00:45:33,920
Speaker 2: I think October surprises are bullshit. And yeah, he's just like,

881
00:45:34,239 --> 00:45:36,600
Speaker 2: you know, the all the stories that have happened in

882
00:45:36,719 --> 00:45:41,560
Speaker 2: October not necessarily that as impactful. It's just a thing

883
00:45:41,680 --> 00:45:44,600
Speaker 2: that you know, the media is on heightened alert, and

884
00:45:45,480 --> 00:45:49,680
Speaker 2: you know, when you are super amped up, like the

885
00:45:49,800 --> 00:45:52,719
Speaker 2: memories that forma at that moment seem more significant.

886
00:45:52,840 --> 00:45:56,200
Speaker 3: Yeah, it feels like can kind of Yeah, can I

887
00:45:56,320 --> 00:46:00,120
Speaker 3: tell you, as a legacy or as an alumni of

888
00:46:00,480 --> 00:46:02,880
Speaker 3: a legacy newsroom, can I tell you what I think

889
00:46:02,920 --> 00:46:06,520
Speaker 3: an October surprise is. Yes, it is a message to

890
00:46:06,680 --> 00:46:09,879
Speaker 3: everyone in your newsroom that you got a month left

891
00:46:10,280 --> 00:46:14,080
Speaker 3: to get as many clicks as possible for during election coverage,

892
00:46:14,200 --> 00:46:15,680
Speaker 3: because after election.

893
00:46:15,560 --> 00:46:19,600
Speaker 1: Date it falls off a cliff, right. Yeah, this is

894
00:46:19,680 --> 00:46:23,760
Speaker 1: a message to the industry, not a message to voters. Yeah. Interest,

895
00:46:23,880 --> 00:46:25,680
Speaker 1: And it's very.

896
00:46:27,400 --> 00:46:30,120
Speaker 3: All these October surprise headlines you listed, it very much

897
00:46:30,200 --> 00:46:32,680
Speaker 3: feels like crying wolf and there's no wolf.

898
00:46:33,040 --> 00:46:34,560
Speaker 1: Look over here. I think I hear something. Oh, I

899
00:46:34,560 --> 00:46:38,319
Speaker 1: don't hear anything. It's just such bs And I think

900
00:46:38,360 --> 00:46:39,000
Speaker 1: the last.

901
00:46:38,800 --> 00:46:41,319
Speaker 3: Time that we thought we had a real, real, real

902
00:46:41,400 --> 00:46:44,719
Speaker 3: live October surprise was probably that Trump.

903
00:46:46,000 --> 00:46:48,759
Speaker 1: Access Hollywood tape. And you know what, it didn't do.

904
00:46:49,560 --> 00:46:52,120
Speaker 3: It didn't cost that man the election. It didn't cost

905
00:46:52,160 --> 00:46:54,680
Speaker 3: some of the election at all. So no, I'm so

906
00:46:54,840 --> 00:46:57,640
Speaker 3: over the October surprise discourse. And it's just like the

907
00:46:57,800 --> 00:47:00,640
Speaker 3: last grasp. And I still love legacy media. I listened

908
00:47:00,640 --> 00:47:03,320
Speaker 3: to it. I like it, but it's the last grasp

909
00:47:04,719 --> 00:47:07,880
Speaker 3: of legacy media pretending as if they can control a

910
00:47:08,000 --> 00:47:09,560
Speaker 3: media narrative around politics.

911
00:47:10,000 --> 00:47:13,400
Speaker 2: Right, it is just grasps for control. Even if it

912
00:47:13,480 --> 00:47:17,279
Speaker 2: were surprise, yeah yeah, even if it was real, at

913
00:47:17,320 --> 00:47:20,440
Speaker 2: one point, it would no longer be real, right, because

914
00:47:20,560 --> 00:47:22,680
Speaker 2: the legacy media doesn't have the ability to.

915
00:47:23,400 --> 00:47:25,840
Speaker 1: And it's not for lack of trying. I do want to,

916
00:47:26,000 --> 00:47:26,960
Speaker 1: we try, Yeah yeah.

917
00:47:27,040 --> 00:47:30,280
Speaker 2: The New York Times did have this opinion piece yesterday,

918
00:47:30,560 --> 00:47:34,920
Speaker 2: this year's October surprise maybe that there isn't one. So

919
00:47:35,480 --> 00:47:38,120
Speaker 2: the October surprise in this case is the fact that

920
00:47:38,719 --> 00:47:41,319
Speaker 2: the real October surprise was the friends we made.

921
00:47:41,360 --> 00:47:42,520
Speaker 1: Friends we made a lot of way.

922
00:47:44,400 --> 00:47:46,640
Speaker 3: My thing with these October surprise is that a story

923
00:47:46,719 --> 00:47:50,439
Speaker 3: isn't it's a story if you can write a whole

924
00:47:50,560 --> 00:47:55,799
Speaker 3: story that changes not one iota of any reader's worldview

925
00:47:56,000 --> 00:47:59,839
Speaker 3: or perspective or knowledge. The article shouldn't be written, right,

926
00:48:00,040 --> 00:48:02,680
Speaker 3: If you have a whole article of a thousand words

927
00:48:02,719 --> 00:48:03,839
Speaker 3: of maybe.

928
00:48:03,600 --> 00:48:07,239
Speaker 1: We'll see you didn't need to write it. Yeah, I

929
00:48:07,320 --> 00:48:08,600
Speaker 1: don't know. It pisses me off.

930
00:48:09,280 --> 00:48:12,839
Speaker 2: That would be so dope if like just the New

931
00:48:12,920 --> 00:48:16,640
Speaker 2: York Times, like any media outlet, only published when they

932
00:48:16,719 --> 00:48:19,759
Speaker 2: had something that was actually new, and you were like,

933
00:48:19,920 --> 00:48:22,320
Speaker 2: holy shit, you guys, The New York Times just dropped

934
00:48:22,360 --> 00:48:25,760
Speaker 2: a story like they hadn't dropped one in eight days

935
00:48:26,120 --> 00:48:28,160
Speaker 2: and we're only a week out in the election.

936
00:48:28,800 --> 00:48:30,640
Speaker 1: This must be important.

937
00:48:31,400 --> 00:48:35,880
Speaker 3: I want I want legacy newsrooms to drop headlines and

938
00:48:36,080 --> 00:48:39,080
Speaker 3: articles the way Beyonce drops albums.

939
00:48:39,760 --> 00:48:41,719
Speaker 1: Yeah yeah, yeah yeah, Only.

940
00:48:41,560 --> 00:48:45,520
Speaker 3: When it's ready, only when it's good, usually by surprise,

941
00:48:46,400 --> 00:48:49,600
Speaker 3: at a time that is connected to when the story

942
00:48:49,880 --> 00:48:50,400
Speaker 3: is ready.

943
00:48:50,600 --> 00:48:55,560
Speaker 1: Yeah, and not when they think it's optimal for viewing, right,

944
00:48:55,760 --> 00:48:58,040
Speaker 1: not like how like Taylor Swift has new albums that

945
00:48:58,160 --> 00:49:00,360
Speaker 1: are like special editions and all the time like was

946
00:49:00,400 --> 00:49:02,040
Speaker 1: this new? It's like, oh, well, it's on a different

947
00:49:02,120 --> 00:49:04,480
Speaker 1: kind of vinyl, Like I guess that's.

948
00:49:04,400 --> 00:49:05,880
Speaker 3: Let me tell you one thing I'll never do on

949
00:49:05,920 --> 00:49:08,399
Speaker 3: a microphone ever again, is say anything not even nice

950
00:49:08,400 --> 00:49:09,480
Speaker 3: about Taylor's.

951
00:49:09,120 --> 00:49:12,200
Speaker 1: Well, oh yeah, we've already we've already burned those bridges.

952
00:49:12,280 --> 00:49:15,399
Speaker 1: We don't have to analyze something. But look, it's all love.

953
00:49:15,440 --> 00:49:17,920
Speaker 1: I'm just saying, get your money, you know, get your money.

954
00:49:18,040 --> 00:49:20,520
Speaker 2: Yeah, but I see famous to your point. Some of

955
00:49:20,560 --> 00:49:23,640
Speaker 2: the most famous recent examples of October surprises were Bush's

956
00:49:23,680 --> 00:49:28,000
Speaker 2: dui and Trump's Access Hollywood tape. I'd forgotten Dui. Yeah,

957
00:49:28,040 --> 00:49:31,120
Speaker 2: but they both won, and people considered the Comy letter

958
00:49:31,200 --> 00:49:33,920
Speaker 2: also like some kind of Yeah, I guess the Comy

959
00:49:34,040 --> 00:49:36,959
Speaker 2: letter is the one that still seems to like hold

960
00:49:37,080 --> 00:49:41,320
Speaker 2: weight as well. This might have hurt, and I do

961
00:49:41,480 --> 00:49:46,760
Speaker 2: think it probably cuts in the direction of like people

962
00:49:47,520 --> 00:49:52,440
Speaker 2: didn't trust Hillary Clinton, and so it undermined in the

963
00:49:52,520 --> 00:49:54,960
Speaker 2: same way. And I also think like the Access Hollywood

964
00:49:54,960 --> 00:49:56,560
Speaker 2: tape probably didn't help him.

965
00:49:56,880 --> 00:50:00,520
Speaker 1: I think he probably won. No, I think I think, yeah,

966
00:50:00,600 --> 00:50:02,560
Speaker 1: even if both of those things didn't exist, I think

967
00:50:02,600 --> 00:50:04,400
Speaker 1: that election probably was going to end the same way.

968
00:50:04,520 --> 00:50:06,719
Speaker 1: But yeah, yeah, again, I think that's all because in

969
00:50:06,840 --> 00:50:09,759
Speaker 1: that when we do post mortems on election, it's always like, well,

970
00:50:09,800 --> 00:50:12,000
Speaker 1: we have to describe all this importance to these things

971
00:50:12,080 --> 00:50:14,680
Speaker 1: to make it seem like logical, like how we got here.

972
00:50:15,560 --> 00:50:20,480
Speaker 2: Two October surprises that are pretty wild. And so the

973
00:50:20,560 --> 00:50:24,719
Speaker 2: first was Nixon kind of going behind the scenes with

974
00:50:25,160 --> 00:50:30,480
Speaker 2: it and trying to hold off the negotiation of peace

975
00:50:30,840 --> 00:50:34,719
Speaker 2: in the Vietnam War until he was elected and being like,

976
00:50:34,840 --> 00:50:37,120
Speaker 2: I actually have a better plan, it will be more

977
00:50:37,200 --> 00:50:40,840
Speaker 2: favorable to you. Then he gets elected psych two and

978
00:50:40,880 --> 00:50:44,080
Speaker 2: a half more years of war, more than that, more

979
00:50:44,160 --> 00:50:48,320
Speaker 2: years of war. And then there's also where we actually

980
00:50:48,440 --> 00:50:51,759
Speaker 2: got the idea of an October surprise. So it was

981
00:50:51,840 --> 00:50:54,880
Speaker 2: invented by the Republicans. And I know that's going to

982
00:50:54,920 --> 00:50:58,160
Speaker 2: be hard for people to believe because it is an annoying,

983
00:50:58,400 --> 00:51:02,719
Speaker 2: a moral scheme and that doesn't cohere with what we

984
00:51:02,760 --> 00:51:05,880
Speaker 2: think of the Republicans. But basically it was coined by

985
00:51:06,320 --> 00:51:10,160
Speaker 2: Ronald Reagan, ally William Casey, who later became the director

986
00:51:10,200 --> 00:51:12,480
Speaker 2: of the CIA, but at this time he was working

987
00:51:12,560 --> 00:51:14,839
Speaker 2: to try and get Ronald Reagan elected in nineteen eighty

988
00:51:15,320 --> 00:51:19,680
Speaker 2: and he was warning Republicans that President Jimmy Carter was

989
00:51:19,800 --> 00:51:23,480
Speaker 2: preparing an October surprise, which was the release of the

990
00:51:23,560 --> 00:51:26,800
Speaker 2: American hostages in Iran. Because they had yet to be

991
00:51:26,880 --> 00:51:28,040
Speaker 2: rescued by Ben Affleck.

992
00:51:29,040 --> 00:51:29,319
Speaker 1: And so.

993
00:51:30,840 --> 00:51:33,640
Speaker 2: In the very first place, October Surprise was just a

994
00:51:33,840 --> 00:51:38,680
Speaker 2: threat being used by the Republicans to scare themselves. So

995
00:51:39,000 --> 00:51:42,360
Speaker 2: that is its proud tradition, is it is a threat

996
00:51:42,600 --> 00:51:46,719
Speaker 2: of something that doesn't ultimately come to pass. And that

997
00:51:46,960 --> 00:51:51,400
Speaker 2: threat led them to secretly negotiate the delay of the

998
00:51:51,480 --> 00:51:56,200
Speaker 2: release of the hostages until after Reagan had been elected damn.

999
00:51:56,360 --> 00:51:59,440
Speaker 2: And there were some congressional investigations into that, and they

1000
00:51:59,440 --> 00:52:03,040
Speaker 2: were like, the congressional investigations were like, actually, we found

1001
00:52:03,080 --> 00:52:06,720
Speaker 2: out this didn't happen. And then last year, former protege

1002
00:52:07,160 --> 00:52:12,239
Speaker 2: of former Texas Governor John Connolly admitted his name is

1003
00:52:12,280 --> 00:52:14,680
Speaker 2: Ben Barnes. He admitted to The New York Times that

1004
00:52:14,880 --> 00:52:18,680
Speaker 2: he was involved in those secret negotiations and that they

1005
00:52:18,800 --> 00:52:23,280
Speaker 2: reported them back to Casey. So it did happen according

1006
00:52:23,400 --> 00:52:26,960
Speaker 2: to this source who was involved in it. And that

1007
00:52:27,239 --> 00:52:31,160
Speaker 2: is that is like the October Surprise that like does

1008
00:52:31,280 --> 00:52:36,080
Speaker 2: actually seem like it would cause changes. But to me

1009
00:52:36,400 --> 00:52:39,640
Speaker 2: right now, it feels like every day there are three

1010
00:52:39,800 --> 00:52:43,400
Speaker 2: Trump stories. Like we talked yesterday about Trump talking about

1011
00:52:43,560 --> 00:52:48,000
Speaker 2: the genes of people coming into this country, like them

1012
00:52:48,080 --> 00:52:50,720
Speaker 2: having like murder Jens like race science.

1013
00:52:50,760 --> 00:52:52,640
Speaker 1: All right, I didn't see that. Wait where do you

1014
00:52:52,680 --> 00:52:55,799
Speaker 1: say that? Which broke said that? Which like not even

1015
00:52:56,280 --> 00:52:59,359
Speaker 1: his ultimate conservative bro, Hugh Hewitt. He was on Hugh

1016
00:52:59,440 --> 00:53:01,359
Speaker 1: Hewitt's that ship.

1017
00:53:01,880 --> 00:53:04,719
Speaker 3: Yeah, Donald Trump go on a podcast hosted by a

1018
00:53:04,800 --> 00:53:05,680
Speaker 3: woman challenge.

1019
00:53:08,840 --> 00:53:12,080
Speaker 1: That would be how Laura Ingram fact checked him though

1020
00:53:12,239 --> 00:53:16,359
Speaker 1: the other day. Oh, she was checking him in real

1021
00:53:16,560 --> 00:53:19,320
Speaker 1: time and he was like trying, like when he was

1022
00:53:19,440 --> 00:53:24,080
Speaker 1: talking about you know, different again like Helene misinformation. She

1023
00:53:24,239 --> 00:53:25,920
Speaker 1: was like, you know, I think he should be here.

1024
00:53:25,960 --> 00:53:27,760
Speaker 1: I'll just play this clip because it is really interesting

1025
00:53:28,200 --> 00:53:31,719
Speaker 1: just to see how he is getting fact checked by

1026
00:53:31,880 --> 00:53:33,719
Speaker 1: Laura Ingram of all people. But here it is.

1027
00:53:34,200 --> 00:53:37,160
Speaker 4: Yeah, they're offering people seven hundred and fifty dollars for

1028
00:53:37,239 --> 00:53:40,800
Speaker 4: immediately for the worst. Yeah, but for the worst hurricane

1029
00:53:40,840 --> 00:53:44,000
Speaker 4: that anybody's seen. But she shouldn't be there anyway, she

1030
00:53:44,080 --> 00:53:48,279
Speaker 4: should be I would say that North Carolina is so bad.

1031
00:53:48,760 --> 00:53:51,280
Speaker 1: And she was there today for three hours. I believe

1032
00:53:52,000 --> 00:53:56,799
Speaker 1: Kamala Harris. Oh, Laura said not on my watch. Yeah,

1033
00:53:56,920 --> 00:53:58,960
Speaker 1: just somehow was like I'm done with you, bro, I'm

1034
00:53:59,000 --> 00:54:01,760
Speaker 1: done with you. She was there three hours, asshole, anyways.

1035
00:54:01,880 --> 00:54:06,480
Speaker 2: Yeah, but yeah, I mean that would be like in

1036
00:54:06,600 --> 00:54:09,480
Speaker 2: it in and out with another presidential candidate.

1037
00:54:09,680 --> 00:54:10,800
Speaker 1: That would be news.

1038
00:54:11,280 --> 00:54:15,560
Speaker 2: Him just going full eugenics would be news. Him saying

1039
00:54:16,040 --> 00:54:19,120
Speaker 2: that when he gets into office he would like to

1040
00:54:19,440 --> 00:54:25,480
Speaker 2: develop Gaza into like an island resort resort would be news.

1041
00:54:25,800 --> 00:54:28,600
Speaker 2: There's also you know, Bob Woodward has a book coming

1042
00:54:28,640 --> 00:54:32,919
Speaker 2: out that talks about how Trump during his administration sent

1043
00:54:33,040 --> 00:54:37,160
Speaker 2: Vladimir Putin like his private stash of COVID tests at

1044
00:54:37,200 --> 00:54:39,880
Speaker 2: a time when like the nation was sure. It was

1045
00:54:40,800 --> 00:54:43,520
Speaker 2: like straight up private stash, like here you go, buddy,

1046
00:54:43,800 --> 00:54:46,160
Speaker 2: and Putin had to be like Okay, thank you, but

1047
00:54:46,440 --> 00:54:49,120
Speaker 2: do not tell anybody about this. They're gonna they're gonna

1048
00:54:49,200 --> 00:54:50,120
Speaker 2: know something's going on.

1049
00:54:50,320 --> 00:54:53,560
Speaker 1: Oh yeah, So all these things. We talked about these

1050
00:54:53,600 --> 00:54:54,400
Speaker 1: on trending yesterday.

1051
00:54:54,440 --> 00:54:57,160
Speaker 2: But I just got like, yeah, I want to give

1052
00:54:57,280 --> 00:55:00,920
Speaker 2: these examples as like things that every day, there's like

1053
00:55:01,160 --> 00:55:03,480
Speaker 2: four things that could be an October surprise. So I

1054
00:55:03,600 --> 00:55:06,279
Speaker 2: just I think it's interesting to keep in mind the

1055
00:55:06,440 --> 00:55:10,399
Speaker 2: context whenever somebody says October surprise, the context they're using

1056
00:55:10,640 --> 00:55:13,840
Speaker 2: is a story about Kamala Harris that is going to

1057
00:55:13,920 --> 00:55:18,000
Speaker 2: torpedo Hart because we there is no conceivable story that

1058
00:55:18,239 --> 00:55:21,480
Speaker 2: would damage Donald Trump at this point, like we because

1059
00:55:21,520 --> 00:55:23,560
Speaker 2: we get three four of them every day, Like he

1060
00:55:23,640 --> 00:55:27,440
Speaker 2: doesn't give a fuck, He's throwing just shedding these stories.

1061
00:55:27,840 --> 00:55:31,520
Speaker 3: Well, and this is what's so crazy and frustrating to see.

1062
00:55:31,960 --> 00:55:36,000
Speaker 3: I mentioned earlier, Kamala is really good and impressive interview

1063
00:55:36,200 --> 00:55:38,759
Speaker 3: on Alex Cooper's Call Her Daddy, where they went deep

1064
00:55:38,840 --> 00:55:41,520
Speaker 3: on women's rights and sexual assault, and it was a

1065
00:55:42,160 --> 00:55:45,959
Speaker 3: deep and introspective conversation that you would not have seen

1066
00:55:46,040 --> 00:55:48,719
Speaker 3: Kamala have in a legacy newsroom. It was beautiful to

1067
00:55:48,840 --> 00:55:52,520
Speaker 3: behold and a surprise to me as someone who's covered

1068
00:55:52,560 --> 00:55:57,680
Speaker 3: politics before. And like, she is continually getting better as

1069
00:55:57,680 --> 00:56:01,839
Speaker 3: a candidate, better at doing this thing. Trump consistently gets

1070
00:56:01,920 --> 00:56:04,840
Speaker 3: worse every day. He's saying more foolishness. And if the

1071
00:56:04,920 --> 00:56:08,840
Speaker 3: polls remained locked and tied and close, close, close, it

1072
00:56:09,000 --> 00:56:09,560
Speaker 3: baffles me.

1073
00:56:10,120 --> 00:56:12,840
Speaker 1: It baffles me. Yeah, I think it's just like I

1074
00:56:12,880 --> 00:56:15,359
Speaker 1: think at this point, it's clear to most people. It's like, yeah,

1075
00:56:15,440 --> 00:56:18,880
Speaker 1: you're when you're looking at this binary between the two candidates,

1076
00:56:19,160 --> 00:56:21,200
Speaker 1: most people are like, yeah, I'm not moving from where

1077
00:56:21,200 --> 00:56:24,719
Speaker 1: I'm at. Yeah, there's no amount and that's the thing

1078
00:56:24,800 --> 00:56:28,480
Speaker 1: with this October surprise. It's like just for people's confirmation bias,

1079
00:56:28,560 --> 00:56:29,719
Speaker 1: you know, and just to be like, well is this

1080
00:56:30,000 --> 00:56:31,759
Speaker 1: this could be this if look, if everything is in

1081
00:56:31,840 --> 00:56:35,640
Speaker 1: October surprise, then nothing is in October surprise, So yeah,

1082
00:56:35,840 --> 00:56:36,640
Speaker 1: leave it alone.

1083
00:56:37,040 --> 00:56:40,000
Speaker 3: The October surprise is that we as a nation still

1084
00:56:40,040 --> 00:56:42,120
Speaker 3: make it really hard for most people to vote. And

1085
00:56:42,200 --> 00:56:44,480
Speaker 3: I'm surprised by that, and so I want to use

1086
00:56:44,520 --> 00:56:47,000
Speaker 3: this moment. Does anyone listen to this podcast right now

1087
00:56:47,280 --> 00:56:49,920
Speaker 3: who doesn't have a voting plan and isn't registered. It's

1088
00:56:49,960 --> 00:56:51,719
Speaker 3: actually hard to do in America to work on it.

1089
00:56:51,840 --> 00:56:54,160
Speaker 3: Now you have a month, yeah, yeah, we have a month.

1090
00:56:54,440 --> 00:56:54,640
Speaker 1: Yes.

1091
00:56:55,040 --> 00:56:58,799
Speaker 2: I just I think it's worth like keeping an eye

1092
00:56:58,880 --> 00:57:02,360
Speaker 2: on the effect, not like keeping an eye on like

1093
00:57:02,480 --> 00:57:05,560
Speaker 2: wait for the October surprise, but just keep like the

1094
00:57:05,680 --> 00:57:11,680
Speaker 2: media is thirsty for an October surprise, and they can't

1095
00:57:11,800 --> 00:57:14,959
Speaker 2: conceivably come up one with one for Trump. We've seen

1096
00:57:15,280 --> 00:57:17,680
Speaker 2: them come up with not an October surprise, but like

1097
00:57:17,760 --> 00:57:20,400
Speaker 2: the Dean Scream was a situation where I was like

1098
00:57:20,760 --> 00:57:24,440
Speaker 2: that the mainstream media was like this guy not not

1099
00:57:24,640 --> 00:57:28,000
Speaker 2: really right, Like yeah, you guys like them, but not

1100
00:57:28,280 --> 00:57:33,160
Speaker 2: really and so I'm not saying they're definitely gonna concoct something,

1101
00:57:33,560 --> 00:57:35,760
Speaker 2: but I think they are going to give a good

1102
00:57:35,880 --> 00:57:39,760
Speaker 2: hard look at anything that they can take the take

1103
00:57:39,880 --> 00:57:43,840
Speaker 2: heed of, you know, the not so subtle message coming

1104
00:57:43,920 --> 00:57:46,479
Speaker 2: from the head of their newsroom, like you said, Sam,

1105
00:57:46,600 --> 00:57:48,520
Speaker 2: that like this is your warning.

1106
00:57:48,440 --> 00:57:52,480
Speaker 1: Get big ass news stories cooked up now.

1107
00:57:53,120 --> 00:57:56,000
Speaker 3: Well, and I mean, especially for the cable news players,

1108
00:57:57,200 --> 00:57:59,880
Speaker 3: we know now we've seen the numbers, Trump is actually

1109
00:58:00,000 --> 00:58:02,400
Speaker 3: good for their bottom lines. Trump isn't good for their

1110
00:58:02,400 --> 00:58:04,520
Speaker 3: bottom lines, good for their ratings. And so if you're

1111
00:58:04,560 --> 00:58:06,800
Speaker 3: seeing INN, if you're MSNBC, if you're any of those players,

1112
00:58:06,880 --> 00:58:09,920
Speaker 3: you actually know in your heart of hearts that him

1113
00:58:09,960 --> 00:58:10,960
Speaker 3: being foolish.

1114
00:58:10,640 --> 00:58:11,160
Speaker 1: Is good for you.

1115
00:58:11,520 --> 00:58:14,720
Speaker 3: And so my question and my challenge to my colleagues

1116
00:58:14,800 --> 00:58:18,440
Speaker 3: and these legacy newsrooms is just like, how can you

1117
00:58:19,720 --> 00:58:22,640
Speaker 3: see that reality, know that reality, but still like call

1118
00:58:22,720 --> 00:58:25,480
Speaker 3: out the bullshit and speak truth and understand.

1119
00:58:25,120 --> 00:58:25,520
Speaker 2: That, like.

1120
00:58:27,040 --> 00:58:29,360
Speaker 3: You need to be looking for the surprises or non surprises,

1121
00:58:29,480 --> 00:58:32,600
Speaker 3: like even after this election cycle, even if Trump goes away,

1122
00:58:32,720 --> 00:58:37,080
Speaker 3: It's just like I hate to see what the October

1123
00:58:37,280 --> 00:58:43,840
Speaker 3: surprise symbolizes, which is this real business cycle and money

1124
00:58:43,960 --> 00:58:47,480
Speaker 3: cycle of the way news is covered, and there's more

1125
00:58:47,520 --> 00:58:51,040
Speaker 3: attention paid to journalism in election years. There's more attention

1126
00:58:51,200 --> 00:58:54,440
Speaker 3: paid to journalism and journalists when the candidates are crazier.

1127
00:58:54,560 --> 00:58:56,880
Speaker 3: And it's just like these perverse incentives that I'm really

1128
00:58:56,960 --> 00:58:57,280
Speaker 3: tired of.

1129
00:58:57,800 --> 00:58:59,320
Speaker 1: AnyWho? Any Who?

1130
00:58:59,680 --> 00:59:03,360
Speaker 2: Sam, Yes, truly a pleasure having you on the show today.

1131
00:59:03,560 --> 00:59:06,360
Speaker 2: Where can people find you? Follow you, hear you all

1132
00:59:06,440 --> 00:59:07,760
Speaker 2: that good stuff? Yeah?

1133
00:59:07,920 --> 00:59:10,600
Speaker 3: Well, One, thank y'all for indulging me and letting me

1134
00:59:11,560 --> 00:59:14,800
Speaker 3: ramble and soapbox and shake my fist like an old man.

1135
00:59:15,080 --> 00:59:19,560
Speaker 1: Thank you for class to join us. And two, in

1136
00:59:19,680 --> 00:59:20,000
Speaker 1: terms of.

1137
00:59:20,040 --> 00:59:23,480
Speaker 3: Socials, I'm on most platforms at Sam Sanders all one

1138
00:59:23,520 --> 00:59:27,160
Speaker 3: word S A M S A N D E R S.

1139
00:59:27,840 --> 00:59:30,400
Speaker 3: But I really want to talk about my two podcasts.

1140
00:59:30,520 --> 00:59:32,919
Speaker 3: One's been around for a few years, the other is new.

1141
00:59:33,480 --> 00:59:35,520
Speaker 3: I'll mention the new one first. It's called The Sam

1142
00:59:35,640 --> 00:59:39,000
Speaker 3: Sanders Show. It's an entertainment and pop culture show about

1143
00:59:39,120 --> 00:59:43,240
Speaker 3: the fun stuff we obsess over in our free time, movies, books, TVs, internet, memes,

1144
00:59:43,280 --> 00:59:45,320
Speaker 3: et cetera, and the people who make it. We've got

1145
00:59:45,360 --> 00:59:47,320
Speaker 3: two episodes out right now. You can hear it on

1146
00:59:47,440 --> 00:59:49,720
Speaker 3: KSRW here in Los Angeles. You can find it in

1147
00:59:49,800 --> 00:59:53,920
Speaker 3: podcast feeds and it's also on YouTube. Full video in studio.

1148
00:59:54,400 --> 00:59:57,840
Speaker 3: Two EPs up now, one conversation with Joel Kim Booster

1149
00:59:58,080 --> 01:00:03,240
Speaker 3: Activity Writer, anothernversation with Sesher Zameta, one of the witches

1150
01:00:03,320 --> 01:00:07,120
Speaker 3: and stars of Agatha. All along, they're fun, The show

1151
01:00:07,240 --> 01:00:10,120
Speaker 3: is fun. It's good, big energy. And then my other

1152
01:00:10,160 --> 01:00:12,720
Speaker 3: show that's been around for a while is called Vibe Check.

1153
01:00:12,920 --> 01:00:16,560
Speaker 3: It's a weekly chat around news and culture in the

1154
01:00:16,600 --> 01:00:18,880
Speaker 3: spirit of this show, and I talk with my dear

1155
01:00:18,960 --> 01:00:22,400
Speaker 3: friends Zach Stafford and Sai Jones every week and publish

1156
01:00:22,480 --> 01:00:27,640
Speaker 3: those episodes every Wednesday. And we soapbox a lot about politics.

1157
01:00:27,680 --> 01:00:30,400
Speaker 3: And let me tell you, what's fun hearing a poet

1158
01:00:30,520 --> 01:00:34,480
Speaker 3: like Saii Jones soapbox on politics. It's music of the years.

1159
01:00:34,840 --> 01:00:37,960
Speaker 1: AnyWho? Those are my shows. Great. Is there a work

1160
01:00:38,040 --> 01:00:39,400
Speaker 1: of media that you've been enjoying?

1161
01:00:39,720 --> 01:00:45,160
Speaker 3: Ooh, this novel is bonkers. It's called Rejection. It's a

1162
01:00:45,240 --> 01:00:48,000
Speaker 3: fiction work that was long listed for the National Book

1163
01:00:48,000 --> 01:00:52,200
Speaker 3: Award this year. It's by Tony Tula Tamute and it's

1164
01:00:52,280 --> 01:00:58,120
Speaker 3: these seven connected short stories all about asshole people facing rejection.

1165
01:00:59,120 --> 01:01:03,800
Speaker 3: The first essay fiction is about this guy who purports

1166
01:01:03,880 --> 01:01:06,760
Speaker 3: to be an ally and supports women and is woke

1167
01:01:06,920 --> 01:01:10,840
Speaker 3: as fuck. But after too many women FriendZone him, he

1168
01:01:10,960 --> 01:01:16,040
Speaker 3: becomes an inceell, and the essay chronicles the shift. Then

1169
01:01:16,080 --> 01:01:18,440
Speaker 3: the next essay is about a woman who becomes an inceell,

1170
01:01:18,920 --> 01:01:20,680
Speaker 3: And then you realize, over the course of the book,

1171
01:01:20,880 --> 01:01:24,360
Speaker 3: all these horrible people facing rejection end up with plotlines

1172
01:01:24,400 --> 01:01:27,840
Speaker 3: that converge and connect. It's wild. I've been covering my

1173
01:01:27,920 --> 01:01:29,040
Speaker 3: mouth reading the whole thing.

1174
01:01:29,840 --> 01:01:32,760
Speaker 1: Read it. It's insane rejection. I like it.

1175
01:01:33,320 --> 01:01:40,560
Speaker 2: Damn classy media recommendation for a classy guests. Oh my god,

1176
01:01:40,840 --> 01:01:43,400
Speaker 2: Mile Miles, Where can people find you? Is there a

1177
01:01:43,440 --> 01:01:45,160
Speaker 2: work media you've been enjoyed? Yeah?

1178
01:01:45,280 --> 01:01:47,680
Speaker 1: Find me on Twitter and Instagram at Miles of Gray.

1179
01:01:47,720 --> 01:01:50,200
Speaker 1: If you like the NBA basketball talk, you can find

1180
01:01:50,240 --> 01:01:52,400
Speaker 1: Jack and I on that podcast Miles and Jack Got

1181
01:01:52,440 --> 01:01:55,040
Speaker 1: Mad Boosties. You can also find me talking about ninety

1182
01:01:55,120 --> 01:01:59,800
Speaker 1: day Fiance on four to twenty Day Fiance a tweet

1183
01:02:00,240 --> 01:02:02,880
Speaker 1: I like, is I think I have a tweet? Yes?

1184
01:02:03,440 --> 01:02:06,640
Speaker 1: Where is it again? I'm going off of the conspiracy

1185
01:02:06,680 --> 01:02:10,320
Speaker 1: theories from Marjorie Taylor Green at Candorade. The Great el

1186
01:02:10,400 --> 01:02:14,120
Speaker 1: Wilkisimo on Twitter tweeted as a lib. The worst part

1187
01:02:14,160 --> 01:02:16,200
Speaker 1: of controlling the hurricanes is you still have to send

1188
01:02:16,280 --> 01:02:18,760
Speaker 1: ninety five percent of them at random Caribbean islands or

1189
01:02:18,760 --> 01:02:21,360
Speaker 1: the Yucatan or wherever to keep up the ruse that

1190
01:02:21,440 --> 01:02:24,960
Speaker 1: they're natural. Now, the tornado machine, you can really go

1191
01:02:25,120 --> 01:02:28,880
Speaker 1: wild on conservatives with that thing. That tornado machine.

1192
01:02:29,760 --> 01:02:35,200
Speaker 2: Oh wow, that's where you really get to cook, all right,

1193
01:02:35,760 --> 01:02:40,840
Speaker 2: tweet I've been enjoying PJ at PJ Evans tweeted, Hey guys,

1194
01:02:40,880 --> 01:02:42,920
Speaker 2: I'll be doing some stuff with mister Beast on this

1195
01:02:43,160 --> 01:02:45,520
Speaker 2: channel soon. Don't want to give too much away, but

1196
01:02:45,920 --> 01:02:47,640
Speaker 2: I'll be killing a dentist.

1197
01:02:48,720 --> 01:02:54,360
Speaker 1: Whoa Also everything mister Beast makes me feel one hundred

1198
01:02:54,440 --> 01:02:57,120
Speaker 1: years old. I don't want it. Yeah, I don't get it.

1199
01:02:57,520 --> 01:02:59,400
Speaker 1: What sounds like that that things starting to crumble a

1200
01:02:59,440 --> 01:02:59,720
Speaker 1: little bit?

1201
01:02:59,840 --> 01:03:00,000
Speaker 6: Him?

1202
01:03:00,720 --> 01:03:02,320
Speaker 1: Yeah, I mean it killed that dentist.

1203
01:03:02,880 --> 01:03:03,000
Speaker 4: Uh.

1204
01:03:03,400 --> 01:03:07,080
Speaker 2: You can find me on Twitter at Jack Underscore O'Brien.

1205
01:03:07,160 --> 01:03:10,040
Speaker 2: You can find us on Twitter at Daily Zeitgeist. We're

1206
01:03:10,080 --> 01:03:12,920
Speaker 2: at the Daily Zeitgeist on Instagram. We have a Facebook

1207
01:03:12,960 --> 01:03:15,560
Speaker 2: fan page and a website, Daily zeitgeist dot com, where

1208
01:03:15,600 --> 01:03:19,400
Speaker 2: we post our episodes and our footnote. We link off

1209
01:03:19,440 --> 01:03:21,360
Speaker 2: to the information that we talked about in today's episode,

1210
01:03:21,360 --> 01:03:23,320
Speaker 2: as well as a song that we think you might enjoy.

1211
01:03:23,760 --> 01:03:25,960
Speaker 1: Hey, Miles, is there a song that you think you

1212
01:03:26,040 --> 01:03:29,560
Speaker 1: might are doing? I think so. Uh, we've I think

1213
01:03:29,600 --> 01:03:32,080
Speaker 1: we went out on a track before by Remy Wolf.

1214
01:03:32,200 --> 01:03:36,120
Speaker 1: It was Cinderella. Last time I suggest one to say

1215
01:03:36,720 --> 01:03:40,960
Speaker 1: a little birdie named Novena Carmel. I overheard this today.

1216
01:03:41,040 --> 01:03:43,959
Speaker 1: I heard our very Sam Sanders is also a fan

1217
01:03:44,080 --> 01:03:47,280
Speaker 1: of Remy Wolf. Uh, and that's why there's another track

1218
01:03:47,320 --> 01:03:50,200
Speaker 1: called Poro that I really like to. Remy Wolf has

1219
01:03:50,240 --> 01:03:52,800
Speaker 1: a great voice, her style is really dope for like

1220
01:03:52,880 --> 01:03:55,720
Speaker 1: these newer artists. She also if you like Lola Young,

1221
01:03:56,000 --> 01:03:59,640
Speaker 1: I've suggested a few Lola Young's tracks. Similar same production team,

1222
01:03:59,720 --> 01:04:02,240
Speaker 1: so like they have overlapping collaborators. So that's why I

1223
01:04:02,280 --> 01:04:04,600
Speaker 1: think they kind of they have like that little bit

1224
01:04:04,640 --> 01:04:08,080
Speaker 1: of swag to them. So this is choral by Remy Wolf.

1225
01:04:08,840 --> 01:04:10,840
Speaker 2: All right, we will link off to that in the

1226
01:04:11,000 --> 01:04:13,320
Speaker 2: footnote from the daily is guys is the production of

1227
01:04:13,360 --> 01:04:15,320
Speaker 2: by Heart Radio. For more podcasts from my Heart Radio,

1228
01:04:15,400 --> 01:04:17,480
Speaker 2: visit Yeah Heart Radio, Wrap, Apple Podcast, or wherever you

1229
01:04:17,560 --> 01:04:19,320
Speaker 2: listen to your pavorite shows. That is gonna do it

1230
01:04:19,440 --> 01:04:21,840
Speaker 2: for us this morning, but we are back this afternoon

1231
01:04:21,920 --> 01:04:24,920
Speaker 2: to tell you what is trending, and we will talk

1232
01:04:24,960 --> 01:04:25,400
Speaker 2: to you all then.

1233
01:04:25,560 --> 01:04:26,360
Speaker 1: Bye bye,