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

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

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

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

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Speaker 1: the Weekly Zeitgeist. Really well, Uh, We're thrilled to be

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Speaker 1: joined in our third seat by a hilarious and talented

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Speaker 1: person who's probably the most likely guest we've ever had

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Speaker 1: to know what the funk you're talking about? Right there?

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Speaker 1: She is the hilarious, the talented, the brilliant Molly Lambert.

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Speaker 1: I'm trying to give a song parody. What's up, guys? Uh,

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Speaker 1: stop in game? Stop game stop in the name of

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Speaker 1: the stock market before you crash the stock market, before

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Speaker 1: you take my yacht? Hey, stop stopping? What's what's mapulation?

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Speaker 1: What's up? Molly? How are you? I am good? There's

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Speaker 1: how you think there'll be a new movement? Just like

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Speaker 1: walking down Wall Street and starting to pat people's pockets,

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Speaker 1: you know what I mean? Like if you see a

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Speaker 1: guy in a suit, like what's up from me? Like,

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Speaker 1: oh my gosh, yeah, I'm gonna show up in costume

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Speaker 1: as the Brave girl statue. Oh not the Brave girl

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Speaker 1: from Brave. The Brave Girl I do look like the

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Speaker 1: Brave girl from Brave. But there is a statue they

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Speaker 1: put up of like it's like a little girl Boss

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Speaker 1: and she's like standing looking at the bull and being like, mmm,

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Speaker 1: I'm gonna get you bull, girl Boss. So yeah, everybody,

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Speaker 1: uh give give the girl boss their money for girl bosses.

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Speaker 1: I also am into just bringing back like pick pottery,

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Speaker 1: yeah yeah, hell yeah yeah, yes, they forgotten Harple Dodger. Yeah,

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Speaker 1: I mean but pretty pretty uh like, whenever you go

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Speaker 1: anywhere that has like trains, it's gonna have yeah. I uh,

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Speaker 1: my first time in New York when I lived since

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Speaker 1: I was younger. I I lived in New York when

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Speaker 1: I was like six seven, but then as a as

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Speaker 1: a teenager, uh, when I lived in Kentucky. My friends

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Speaker 1: and I went to New York and I claimed that

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Speaker 1: I had been pickpocketed, and they're like, oh, ship, that's wild.

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Speaker 1: And then they eventually learned that I actually just had

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Speaker 1: like a twenty in the waist band of my basketball shorts.

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Speaker 1: And they're like, nobody pickpocket of that man that just

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Speaker 1: like fell out of your basketball shorts, You dumb, You

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Speaker 1: had you had a waste band money. When I had

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Speaker 1: that was no pockets just in my waist. Bam, you're

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Speaker 1: asking for the artful dodger. Yeah, I mean it fell

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Speaker 1: out a pocket or two. I remember those days. That's

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Speaker 1: like when I used to wear only Nike basketball shorts

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Speaker 1: before they wised up and put pockets in them. So

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Speaker 1: I would be wearing like Cincinnati bear Cats shorts, no

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Speaker 1: pockets and like eighty bucks in my waistband, like pinned

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Speaker 1: to my torso because I had. But I was really

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Speaker 1: careful about that ship because I could. I lost. I

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Speaker 1: remember I lost five once riding my bike, and I

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Speaker 1: after that, I always kept tracking my waistbandmin I just

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Speaker 1: blamed I blamed it on pickpockets every time, like damn

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Speaker 1: pickpockets times, Like I was wearing boxers to back then,

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Speaker 1: so like you were, like Mois came through like a

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Speaker 1: game and his clown makeup just heared on roller skates

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Speaker 1: and these guys who were dragging their hockey sticks all

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Speaker 1: menacingly on the ground as they walk. For uh, that

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Speaker 1: that needs to become a reality now that we're living

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Speaker 1: in this world. That bears a striking resemblance to lots

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Speaker 1: of different works of dystopian fiction. We need to start

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Speaker 1: dressing up as like themed gangs. I mean that's what

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Speaker 1: the Capital storming seemed like a little bit yeah, but

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Speaker 1: just like not very well designed. Like their theme was

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Speaker 1: all like dot matrix, printer camo and red hats. Like

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Speaker 1: it was a little bit clown gang. Though I had

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Speaker 1: just watched Batman Returns and saw a lot of similarities

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Speaker 1: with kind of just the roving clown gang. Right, so

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Speaker 1: you want to see like the Visco cam people like

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Speaker 1: march on the Capitol. So it's a little bit more

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Speaker 1: aesthetic to it. Uh, Matt, what is something you think

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Speaker 1: is underrated? Underwrited? Real talk? Uck? And I hate to

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Speaker 1: bring this you know, podcast down a little bit, but uh,

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Speaker 1: Dustin Diamond r a p to a real one. Uh.

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Speaker 1: I think Dustin Diamond, the guy who played Screech, you know,

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Speaker 1: he recently died, and uh I think that he uh

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Speaker 1: as a human being, was constantly underrated his whole life.

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Speaker 1: I think, uh he was treated like dogshit his entire life,

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Speaker 1: and people wondered why he was like such a dick

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Speaker 1: after you know, saved by the Bell, And I was like,

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Speaker 1: I get it, man, I understand as someone who grew

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Speaker 1: up looking like Screech and being called Screech a lot

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Speaker 1: until Harry Potter came out, and then I started being

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Speaker 1: called Harry Potter. Um, Like I understand what it's like

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Speaker 1: to uh, you know, to constantly be shipped on by

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Speaker 1: people who look like Zack Morris, and uh, you know,

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Speaker 1: I so, I I felt like after he died, I

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Speaker 1: felt like really sad about it, because like I feel

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Speaker 1: some sort of kinship with Screech, Like we're kind of like,

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Speaker 1: you know, we're kind of brothers in that way, except

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Speaker 1: for I was never a child actor, you know, and

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Speaker 1: never put out a porno or anything. But like, so,

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Speaker 1: what was the Like I thought there was something like

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Speaker 1: problematic about him, but then all the stories seemed to

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Speaker 1: be that he like edited himself into a port Like

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Speaker 1: it was like just actually a really sad story, like

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Speaker 1: edited himself. Listen, he edited himself into a porno to

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Speaker 1: make it seem like he was in a porno, which

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Speaker 1: is it's pretty bad. But there's there's a lot of

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Speaker 1: things about him that are like I mean, there's a

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Speaker 1: constant stories about him, you know, kind of like um

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Speaker 1: kind of just being dicks to people and whatnot. Like,

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Speaker 1: you know, there's a few Screech stories that have kind

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Speaker 1: of like made the rounds right, and and I understand,

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Speaker 1: like I understand why he would be the way he

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Speaker 1: is because, you know, like he was a child actor

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Speaker 1: in Hollywood, which is a predatory industry. He played a

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Speaker 1: character that was constantly getting shut on. He played the

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Speaker 1: worst kind of character too, because it's like, um in

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Speaker 1: any other TV show, it would have been like like

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Speaker 1: freaks and geeks, there's the nerds and there's the cool kids,

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Speaker 1: and they don't they don't meet, you know, in between.

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Speaker 1: The worst thing about saying by the Bell is that

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Speaker 1: technically Screech was Zack Morris's best friend is the most

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Speaker 1: gas lighty, emotionally manipulative relationship you've ever seen on television,

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Speaker 1: where you have this you know, freaking aryan god, you know,

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Speaker 1: who gets all the chicks and then this little like

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Speaker 1: crypto Semitic character who they never say that he's Jewish,

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Speaker 1: but let's be real, this is an Arian versus jew

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Speaker 1: type of thing. And and he's pretending like that's his

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Speaker 1: best friend, but he ships on him all the time

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Speaker 1: and everyone makes fun of him, and like Lisa Turtle

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Speaker 1: won't give him the time a day, Like why why not?

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Speaker 1: He's he's perfectly he's smart, and he's a smart guy.

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Speaker 1: I understand it's kind of weird, but you gotta get

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Speaker 1: to know him a little bit. The point is that

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Speaker 1: when is is that, you know, I feel like his

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Speaker 1: entire persona and whatnot is a result of playing this

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Speaker 1: character screech and people given him crap for that, and

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Speaker 1: you know, I feel like in the afterlife he shall

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Speaker 1: have his revenge. Revenge. You believe in a a vengeful god,

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Speaker 1: and the evengeful god is Dustin dion Um. Yeah, Zack

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Speaker 1: Morris is a very interesting character, like very much. I

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Speaker 1: haven't seen the reboot of Saved by the Bell, but

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Speaker 1: very much like introduced me to the concept of like

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Speaker 1: a winning, predatory capitalist kind of guy who like everybody

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Speaker 1: can't help but like while he is like, you know,

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Speaker 1: stealing money from you, but very likably. Yeah, yeah he does.

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Speaker 1: He does crimes likably and sheets all the time and

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Speaker 1: his original American psycho. Yeah, straight up, straight up original

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Speaker 1: American psycho and like, you know, but you're just charmed

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Speaker 1: by him because he's hot and you're just like, no,

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Speaker 1: there's more. There's more to this world than just being hot.

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Speaker 1: You know, you gotta have like strength of character I've

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Speaker 1: ever had that. I mean, I don't want to I

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Speaker 1: had to look it up and figure out what I

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Speaker 1: was going on with Justin's sex tape. Uh. So he

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Speaker 1: used a fake wang because you don't want to put

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Speaker 1: himself out there like that. He did hire a quote

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Speaker 1: body double, and he decided to do it after the

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Speaker 1: Paris Hilton tape where she apparently earned fourteen million dollars.

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Speaker 1: He was in his mid twenties and he thought it

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Speaker 1: was a good idea. But in two thousand and four

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Speaker 1: he went on Oprah's Where are They Now? Um, he

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Speaker 1: was in his mid thirties by then, and he was like, yeah,

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Speaker 1: I realized it was stupid of me to try to

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Speaker 1: get millions of dollars like Harris Hilton. Uh, but you know,

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Speaker 1: that is a very signs of the new That is

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Speaker 1: a very profound misunderstanding of the dynamics of the sex

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Speaker 1: tape industry. And people were looking for from from Paris

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Speaker 1: Hilton and from him. Yeah, he kind of misread He

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Speaker 1: misread that a bit like, Oh, clearly they just want

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Speaker 1: to see anyone who's ever been on television. Fuck Like,

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Speaker 1: that's that's not true, but it does. It begs the

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Speaker 1: question why he felt the need or how he could

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Speaker 1: have been in a financial situation in which he would

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Speaker 1: have been like desperate enough to put out a fake

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Speaker 1: uh sex tape, you know. And a lot of it

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Speaker 1: is because uh his you know, I'm sure he was

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Speaker 1: screwed out of all sorts of like syndication, money and

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Speaker 1: and all that stuff. You know, because like say, by

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Speaker 1: the Bell is in syndication. He was in both shows.

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Speaker 1: He was in the new class and the old class.

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Speaker 1: Why would he not have money? And he was constantly

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Speaker 1: in money trouble And you know, I look at that

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Speaker 1: and I said, a Hollywood's a predatory industry. Yeah, no,

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Speaker 1: that's that's very fair. Yeah, Ramsey is in the house.

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Speaker 1: By the way, my friend has joined us. Ramsey, you

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Speaker 1: want to say how to Matt and Joel? So I'm

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Speaker 1: at and go out, baby, alright, I'll have kids. Fine.

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Speaker 1: Drastic decisions like everybody getting an animal. I'm like a chill. Yeah,

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Speaker 1: that is a big thing right now, huh like just

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Speaker 1: a lot of dogs. I almost did it, get it.

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Speaker 1: I'm so close, Like I bought all the stuff for

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Speaker 1: the dog. Now he's needing the dog perfect one. You know,

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Speaker 1: you might just be okay with just all the stuff

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Speaker 1: for the dog that for a couple of weeks and

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Speaker 1: see how that goes. Joel keeps buying all of all

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Speaker 1: of these dog toys, but there's no My brother was like,

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Speaker 1: do we need three dog beats? It's like one for

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Speaker 1: each floor. I want to be comfortable wherever. Yeah, And

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Speaker 1: that also like gives him a place. It trains him

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Speaker 1: to always have a place, as opposed to just like

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Speaker 1: lying all over everything, brand new couch. I don't think so.

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Speaker 1: I don't think so dogs you're going to name him dog?

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Speaker 1: What is something you think is overrated? Overrated? I'm sorry

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Speaker 1: to gen Z, but that damn driver's license song? Good lord,

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Speaker 1: I can't I can't do. I'm so tired of the

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Speaker 1: avocado singing. I just gone my driver's license. But also

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Speaker 1: I'm like, maybe I get involved. You know, it seems

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Speaker 1: like an easy ship. Um yeah, oh yeah, I know.

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Speaker 1: She's got the Disney community behind her and stuff, so

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Speaker 1: I know that it's like, you know, the youth, like

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Speaker 1: they have plenty of time to stream the song and

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Speaker 1: blow it up. And I'm it's a. It's a fine song,

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Speaker 1: but I was like, really number one in the world, this,

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Speaker 1: this was this is what we live with, like it's

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Speaker 1: I was just like, what is this? And I have

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Speaker 1: the same thing to say about avocado singers. I have

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Speaker 1: to say about R and B singers who are doing that,

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Speaker 1: like sis, yeah, badger, what are you saying? I want

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Speaker 1: to sing along? I'm tired in it. I'm tired of

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Speaker 1: having to just be like I was, w ha, can

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Speaker 1: I know the word? Carry it? It's not a karaoke

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Speaker 1: friendly singing style because you're like, oh, I do need

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Speaker 1: the words, I really do need them, and then when

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Speaker 1: you read the words, you're like, wait, what that's what

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Speaker 1: she said? What right? We're all gonna be a kill

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Speaker 1: this up? Yeah? Yeah, yeah, number belt and I'm rading

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Speaker 1: co bad. The whole album is like what, like, yeah,

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Speaker 1: beautiful voices I've ever heard, and I don't ever know

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Speaker 1: what she'd be talking about. I don't know if we're

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Speaker 1: talking about sex. I don't know if we're talking about Honestly,

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Speaker 1: Ariana could be organizing for Anti Fish, but Wa're gonna meet,

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Speaker 1: We're gonna be That's how they stormed the Capitol. Arianna

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Speaker 1: single Yeah, she was sending messages through vocals. All that

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Speaker 1: of the Congress will be in the Ragley. We won't

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Speaker 1: know ever know that driver's License song. That was like

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Speaker 1: one of those things where I didn't think I had

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Speaker 1: heard it, but then I'm like, oh, I've heard that

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Speaker 1: at seven eleven every time I've been into seven eleven

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Speaker 1: for a month. I just didn't. It's a real seven

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Speaker 1: eleven kind of song. Oh, no, disrespect, I mean it's

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Speaker 1: like whatever, Like I because that was the Girl is from,

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Speaker 1: like the High School Musical TV series? Is that right? Right?

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Speaker 1: High School Musical, the movie, the TV show or something

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Speaker 1: doesn't have like some meta title like that. Yeah, I'm

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Speaker 1: feeling like an absolute boom or not really knowing what

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Speaker 1: it is. It's good, but I just like the this

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Speaker 1: one seems acutely designed to be only meaningful to people

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Speaker 1: between like who who aren't of legal drinking age yet,

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Speaker 1: and like that seems like it's kind of creating some

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Speaker 1: of the some of the popularity because then everybody else

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Speaker 1: is talking about it, and like that's actually what makes it,

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Speaker 1: what makes pop music cool, Like old people hating it.

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Speaker 1: So it's she was in that and then High School

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Speaker 1: Musical the musical the series. Yes, that's exactly what it's called.

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Speaker 1: I think there was one other show though, Yeah, but

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Speaker 1: I don't know. Jack. It's like it gives me like,

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Speaker 1: remember that song. I was like, it's not I would

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Speaker 1: a whisper. We all got tortured, so a huge seven

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Speaker 1: eleven songs. They all got tortured by this song. What

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Speaker 1: was anybody ever like? This is a bad up? Like, yeah,

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Speaker 1: listen to the song punching cram it down? And I

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Speaker 1: whose song is that? Even? Who knows? Who know? Yeah? No,

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Speaker 1: nobody knows, Jamie. We've been trying to figure that out

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Speaker 1: for years and the scientific community is still baffled, unable

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Speaker 1: to figure it out. When I get the little emo

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Speaker 1: side of the kids wanting this avocado song and liking

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Speaker 1: to listen to it, it's fine, and she plays instruments.

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Speaker 1: I'm not trying to take anything away from her as

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Speaker 1: a musician. I was just like, I don't know, can

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Speaker 1: we sing with our voices again? No, man, we're not

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Speaker 1: gonna say. We're not gonna put the teas at the

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Speaker 1: ends of what No is? What? No? Okay? Fair? Fair?

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Speaker 1: What did you just say? Maybe that is like a

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Speaker 1: thing like every general I feel like every generation has

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Speaker 1: like a musical style where they don't respect certain letters

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Speaker 1: because it's like whatever, Like early two thousands pop music,

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Speaker 1: they didn't finish their words either, where it's like yeah,

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Speaker 1: it was like more of a vowel issue for that generation.

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Speaker 1: Their vowels are all over the place. All right, let's

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Speaker 1: take a quick break and we'll come right back and

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Speaker 1: we're back. What is something you think is underrated? Underrated?

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Speaker 1: Great question, Jack, Thank you so much. I will say

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Speaker 1: underrated is any type of YouTube cooking video. Like we've

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Speaker 1: all been in pandemic now for almost a year, so

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Speaker 1: we've all been cooking at home. Like I have really

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Speaker 1: been tearing through um YouTube cooking videos. But not just

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Speaker 1: like you know the dude or the lady or whoever

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Speaker 1: sitting in their kitchen. Have you seen these videos of

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Speaker 1: like it will just be like some random like Hungarian

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Speaker 1: man with like a big knife in the woods just

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Speaker 1: cooking in a pot. Have you seen those videos? Yeah,

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Speaker 1: it'll he'll he'll like build a fire. It just has

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Speaker 1: this giant or Dane knife and like he'll he'll be

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Speaker 1: like him cutting up the meat and cutting up the onions,

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Speaker 1: and like he always puts like the spices on the

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Speaker 1: giant knife and then dumps it into like his like

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Speaker 1: cast iron as he's cooking over wood. The one that

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Speaker 1: I watched the most is called Men with the Pot.

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Speaker 1: I think he's like a Polish or Hungarian guy because

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Speaker 1: it will have like salt in English and then we'll

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Speaker 1: have like whatever like language he speaks translated and it's

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Speaker 1: just him cooking random, delicious looking food in the woods

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Speaker 1: with a pot and one giant knife. No spatulors, no

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Speaker 1: no tongs. It's just a dude with a big gass

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Speaker 1: knife in the woods. I love that when whenever you

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Speaker 1: see videos like that, I'm like, does this know does

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Speaker 1: this guy know about the coronavirus? Or he just like

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Speaker 1: been in thes with his knife for years. It's amazing

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Speaker 1: just doing this thing. It's great. I do wonder are

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Speaker 1: there like remember that article right after Trump one where

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Speaker 1: the New York Times guy is like, he's not a

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Speaker 1: New York Time, he doesn't work for the New York Times,

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Speaker 1: but he's just like the most New York Times reader

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Speaker 1: that The New York Times has ever profiled. He's got

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Speaker 1: a beard and like a tote bag, and he had

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Speaker 1: quarantined himself off from the real world so he wouldn't

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Speaker 1: find out who won the election and was like living

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Speaker 1: in a separate reality. I wish I could have that

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Speaker 1: type of privilege. I could escape reality for four years.

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Speaker 1: I wonder if he's still out there and doesn't know

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Speaker 1: about the Maybe this is the guy. Maybe he's got

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Speaker 1: his own bad developed Yeah. I love isolated people with

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Speaker 1: YouTube channels. It's so you have you have you? Have

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Speaker 1: you seen the dude that builds like spas in the

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Speaker 1: middle of the jungle in South America, right, like carves

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Speaker 1: them into the ground. Yeah. He it's just this one dude.

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Speaker 1: He has two tools and it's just him like moving

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Speaker 1: tons of dirt and building like elaborate spas in the

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Speaker 1: middle of note in the jungle. It's great. How do

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Speaker 1: you get there? Like how do you arrive at that

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Speaker 1: point where you're like this is it for me? Like

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Speaker 1: I've done. It's like the Rock the Raccoon Guy channel

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Speaker 1: that he's like it's this old man in Canada and

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Speaker 1: he leaves out food and then there's like fifty raccoons

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Speaker 1: that comes to his porch every day and he has

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Speaker 1: five trillion subscribers. That's my life given it's nice and

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Speaker 1: octopus teacher. It's like my occopus teacher, but with fifty raccoons,

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Speaker 1: My fifty raccoon teachers. I do think that there's like

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Speaker 1: a fascination with like the blending of Yeah, like a

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Speaker 1: spa that's like dug into just like Earth, or you know,

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Speaker 1: a cooking video that's like that. The sort of complete

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Speaker 1: other end of that continuum is that the new Amazon building.

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Speaker 1: I don't know if you guys saw that, but it's

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Speaker 1: like they've created did this giant like prism shaped spiral

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Speaker 1: skyscraper but like like kiked a park onto the outside

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Speaker 1: of it, Like there's like a big full super villain stuff.

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Speaker 1: I love it. Yeah, really at this point, why not? Yeah? Um, yeah,

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Speaker 1: it's very lysium. But of what's something you think is overrated? Overrated?

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Speaker 1: I would say is coppaganda like TV shows that portray

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Speaker 1: police officers, because these shows are basically marketing for police departments,

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Speaker 1: and they glorify and normalize the systemic violence and injustices

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Speaker 1: that are handed out by the police and instead make

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Speaker 1: them heroes and so overrated. What is there a piece

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Speaker 1: of coppaganda you've had, You've had to have a reckoning

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Speaker 1: with over time as you're like I realized this is

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Speaker 1: this is just straight nonsense. But but I loved it

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Speaker 1: as a TV show or film. Um, I most of

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Speaker 1: the time watch that stuff in it, Like I I'm

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Speaker 1: no fun to watch legal shows with. I scream at

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Speaker 1: the TV. I'm like that that's not true, that would

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Speaker 1: ever happen, you know, I'm like really unfund So this

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Speaker 1: is why I just like, you know, I just instead

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Speaker 1: watched like reality television. There you go, yeah, because like

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Speaker 1: what do we know about the K one visa process

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Speaker 1: on fiance? But watch a procedural with you you're like,

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Speaker 1: oh that is not Oh my god. The chain of

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Speaker 1: custody on that is absolutely bizarre. Right, that makes sense.

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Speaker 1: I watched Den of Thieves over the weekend. I had

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Speaker 1: not seen that that's the Gerard Butler two thousand eighteen

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Speaker 1: movie that it's like the protagonists are the l A

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Speaker 1: Sheriff's Department, um who and like it's there are like

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Speaker 1: vague implications that they're the ones who like have those

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Speaker 1: tattoos and like basically kill people and like have white

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Speaker 1: supremacist ties. Uh, but they like they cut all that out,

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Speaker 1: you know, they make it a little the team a

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Speaker 1: little bit more first, but it's like you're supposed to

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Speaker 1: be rooting for the l A. Sheriff's Department in two

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Speaker 1: thousand eighteen, um still having trouble, just like that Denzel

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Speaker 1: movie that came out where people are like, this is

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Speaker 1: also capaganda. I don't care if it's Denzel, and like

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Speaker 1: we're taking a like Rosie lens to look at policing.

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Speaker 1: But yeah, it's everywhere. Yeah, Chopot trap House was like

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Speaker 1: had recommended that. They were like that movie is great.

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Speaker 1: It's like about a dirt bag and it's like, huh,

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Speaker 1: that's the one with Ocean Jackson Jr. Right, Yeah, and

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Speaker 1: it's yeah, that one takes a weird turn and I'm

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Speaker 1: like whatever, it's just like it's just like testosterone fast.

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Speaker 1: It's really there's not much else in it. I haven't

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Speaker 1: seen it, but I'm not going to. Yeah, good watch

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Speaker 1: a watch Bling Empire instead about the real crazy rich

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Speaker 1: Asians of l A. Which I was watching the weekend.

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Speaker 1: How is that? It's wild? You know, it's funny when

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Speaker 1: you see like the you know, just obscene wealth where

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Speaker 1: like people are giving each other gifts and like, yeah,

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Speaker 1: the towel has real gold in it you're like, you

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Speaker 1: gave someone a towel that had gold in it, and

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Speaker 1: you're like, that's it's so obscene, And it's just like

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Speaker 1: a whole other dimension of reality that we're not used to.

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Speaker 1: Lies I am curious as running for d A and

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Speaker 1: saying things like coppaganda, right. You know, a lot of people,

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Speaker 1: as we've seen over the years, like to walk this

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Speaker 1: weird line of being like, oh, I don't want to

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Speaker 1: make the police mad, but also wanting to also seek justice.

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Speaker 1: Um in terms of and I don't, I don't you

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Speaker 1: don't need the cash dispersions on the other people running,

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Speaker 1: But it seems like I think there are what eight

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Speaker 1: how many people are running at the moment? Eight people?

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Speaker 1: Is that? Has that been a tone right now for

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Speaker 1: for the other candidates, because I feel like only one

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Speaker 1: is not really about any kind of real reform or

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Speaker 1: seemingly doesn't seem like very forward thinking. But in terms

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Speaker 1: of the race, um as it is right now, how

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Speaker 1: how many people are sort of have this sort of

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Speaker 1: progressive viewpoint on how things need to change within New York? Well,

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Speaker 1: so you know what's so interesting? And I was kind

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Speaker 1: of touching on this a little bit when I say

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Speaker 1: that that now, all of a sudden, it's become popular

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Speaker 1: to say things like sex work is work, um, And

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Speaker 1: I'm so thrilled that people are coming around to the

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Speaker 1: to the progressive views that we should decriminalize sex work,

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Speaker 1: we should decriminalize drug possession, we should end mass incarceration

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Speaker 1: and stop using you know, jail as the default and

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Speaker 1: punitive prison sentences for for low level offenses. But the

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Speaker 1: problem is even people who are now espousing progressive talking

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Speaker 1: points because they're popular, are not necessarily people who truly

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Speaker 1: believe these things. And I think some of the evaluations

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Speaker 1: that have come out recently about the candidates really do

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Speaker 1: kind of delve into these nuanced views of what kinds

422
00:26:11,760 --> 00:26:14,800
Speaker 1: of changes you would make, and in those like I

423
00:26:14,920 --> 00:26:17,200
Speaker 1: come out, you know, heade shoulders above everyone else, like

424
00:26:17,240 --> 00:26:18,919
Speaker 1: I'm the only real progressive in the race who has

425
00:26:18,920 --> 00:26:22,800
Speaker 1: the authentic commitment from my career, from my experience as

426
00:26:23,080 --> 00:26:27,159
Speaker 1: being a public defender and fighting against this system of injustice.

427
00:26:27,200 --> 00:26:29,000
Speaker 1: And it's not like all of a sudden, one day

428
00:26:29,040 --> 00:26:30,680
Speaker 1: I woke up and was like, oh, you know what,

429
00:26:31,080 --> 00:26:33,680
Speaker 1: I think it'd be popular to say we should end

430
00:26:33,720 --> 00:26:36,440
Speaker 1: mass incarceration. So that's the pivot I'm going to take

431
00:26:36,800 --> 00:26:39,280
Speaker 1: and yeah, I'm gonna hold police accountable. And it's like

432
00:26:39,560 --> 00:26:42,040
Speaker 1: people who have been working in conjunction with the police

433
00:26:42,080 --> 00:26:44,520
Speaker 1: to lock people up for their entire careers all of

434
00:26:44,560 --> 00:26:46,919
Speaker 1: a sudden are saying they're gonna hold police accountable. Well,

435
00:26:46,960 --> 00:26:49,200
Speaker 1: I've spent every day of my career cross examining police

436
00:26:49,200 --> 00:26:52,720
Speaker 1: officers and questioning the veracity of the things that they say. Um,

437
00:26:52,760 --> 00:26:56,480
Speaker 1: and so I think that, you know, prioritizing this kind

438
00:26:56,480 --> 00:26:59,119
Speaker 1: of accountability for the police and these real reforms is

439
00:26:59,160 --> 00:27:02,560
Speaker 1: incredibly important. But making sure that we're not just listening

440
00:27:02,600 --> 00:27:05,840
Speaker 1: to someone's memorized talking points, but looking into their record,

441
00:27:05,920 --> 00:27:08,280
Speaker 1: looking into their history, making sure that this is an

442
00:27:08,320 --> 00:27:12,520
Speaker 1: authentic commitment to bringing about real change, right. And I

443
00:27:12,560 --> 00:27:15,040
Speaker 1: can I can tell by the New York Post treatment

444
00:27:15,080 --> 00:27:18,840
Speaker 1: of you there. You probably are walking the walk because

445
00:27:18,840 --> 00:27:22,240
Speaker 1: they're painting you as someone who's like this headline most men,

446
00:27:22,560 --> 00:27:28,160
Speaker 1: most Manhattan DA candidates care most for protecting criminals. Wow.

447
00:27:28,280 --> 00:27:32,320
Speaker 1: And just like such a disingenuous look on reform, which

448
00:27:32,359 --> 00:27:35,440
Speaker 1: is like these people just want It's like it's gonna

449
00:27:35,480 --> 00:27:38,200
Speaker 1: look like a Batman movie where they just open up

450
00:27:38,240 --> 00:27:41,359
Speaker 1: the asylums and the jails and it's it's it's you know,

451
00:27:41,720 --> 00:27:43,720
Speaker 1: the people are gonna be running wild when it's really

452
00:27:43,760 --> 00:27:47,399
Speaker 1: about we have such an inhumane of treating people and

453
00:27:47,400 --> 00:27:51,200
Speaker 1: we're not actually we're not addressing the root causes of anything,

454
00:27:51,760 --> 00:27:54,760
Speaker 1: um so rather than it. So, you know, credit to you,

455
00:27:54,800 --> 00:27:57,760
Speaker 1: because the New York Post is absolute trash. Listen, if

456
00:27:57,760 --> 00:27:59,919
Speaker 1: the New York Post is criticizing me, I'm obviously doing

457
00:28:00,160 --> 00:28:04,000
Speaker 1: something right. So I don't I feel like great about it?

458
00:28:04,320 --> 00:28:08,800
Speaker 1: Our pick for Manhattan d A, then he'd be likely.

459
00:28:10,000 --> 00:28:12,199
Speaker 1: Uh do you do you aspire to one day have

460
00:28:12,320 --> 00:28:16,119
Speaker 1: like a real shitty New York Posts like pun headline

461
00:28:16,240 --> 00:28:18,320
Speaker 1: about you. I feel I feel like that would be

462
00:28:18,440 --> 00:28:22,200
Speaker 1: the ultimate honor is like some yeah, some pot they're

463
00:28:22,200 --> 00:28:25,719
Speaker 1: gonna they're gonna come after me, undoubtedly, Like it'll be

464
00:28:25,760 --> 00:28:30,080
Speaker 1: it'll be a daily occurrence of them just waiting on me. Right,

465
00:28:30,600 --> 00:28:34,480
Speaker 1: I'm looking forward to it. Yeah, hell yeah. Let's talk

466
00:28:34,520 --> 00:28:39,480
Speaker 1: about coronavirus COVID nineteen, the big I don't know, there's

467
00:28:39,520 --> 00:28:43,000
Speaker 1: the only two names I know for it. Are you okay?

468
00:28:43,160 --> 00:28:44,840
Speaker 1: You are you? Like as soon as you said it?

469
00:28:44,960 --> 00:28:48,760
Speaker 1: Like for effects? Yeah, that could be like that could

470
00:28:48,760 --> 00:28:51,640
Speaker 1: be a sound cue that we have every time we

471
00:28:51,720 --> 00:29:04,239
Speaker 1: bring up coronavirus sensitive America. Amazing. It would be an

472
00:29:04,240 --> 00:29:09,520
Speaker 1: amazing like Morning Zoo like talk radio thing where they're

473
00:29:09,560 --> 00:29:12,000
Speaker 1: like and now in coronavirus news, and then you just

474
00:29:12,040 --> 00:29:21,680
Speaker 1: have like, um, all right, well the numbers are dropping,

475
00:29:21,720 --> 00:29:24,480
Speaker 1: so we can't we can have fun here, folks. Uh

476
00:29:25,360 --> 00:29:29,480
Speaker 1: it Uh. People aren't really sure why. Like it seems

477
00:29:29,520 --> 00:29:34,920
Speaker 1: like it's partially vaccine. Uh, partially we're seeing the you know,

478
00:29:35,000 --> 00:29:39,960
Speaker 1: remnants of the you know, holiday travel. It's kind of

479
00:29:39,960 --> 00:29:43,640
Speaker 1: clearing through our system after everybody went and saw their

480
00:29:43,680 --> 00:29:47,920
Speaker 1: family during the holiday. Um. And then there's also well

481
00:29:48,320 --> 00:29:51,080
Speaker 1: so yesterday when I saw this chart, I was like, yeah,

482
00:29:51,080 --> 00:29:54,480
Speaker 1: of course, of course it's because Trump is gone, like

483
00:29:54,560 --> 00:29:57,160
Speaker 1: he was telling he was lying, and like people, it's

484
00:29:57,200 --> 00:29:59,560
Speaker 1: happening everywhere in the world. So we actually had to

485
00:29:59,600 --> 00:30:02,200
Speaker 1: like at a chunk of yesterday's episode out where I

486
00:30:02,240 --> 00:30:05,360
Speaker 1: was just like ranting about how it was all Joe Biden.

487
00:30:06,320 --> 00:30:09,280
Speaker 1: But it's I think that at least has to be

488
00:30:09,360 --> 00:30:13,960
Speaker 1: like I think there's a bunch of different factors combined, right,

489
00:30:14,160 --> 00:30:17,640
Speaker 1: Like that's in medicine, Like that's they do they do

490
00:30:17,680 --> 00:30:19,960
Speaker 1: that all the time where they're like, there are four

491
00:30:20,000 --> 00:30:22,240
Speaker 1: medications that we know how to treat this cancer with,

492
00:30:22,640 --> 00:30:26,160
Speaker 1: we're gonna give you all of them. Yeah, and I

493
00:30:26,200 --> 00:30:28,640
Speaker 1: mean I I do think weather has something to do

494
00:30:28,760 --> 00:30:31,640
Speaker 1: with it too. Yeah. Yeah, So that was something I

495
00:30:31,680 --> 00:30:34,560
Speaker 1: didn't realize until I started like kind of trying to

496
00:30:34,600 --> 00:30:38,400
Speaker 1: research why it's dropping. Whether is a big contributing factor,

497
00:30:39,040 --> 00:30:41,920
Speaker 1: like to the point that it's more important than like

498
00:30:41,960 --> 00:30:45,720
Speaker 1: whether somebody is social distancing or not. Yeah, well, I

499
00:30:45,720 --> 00:30:49,600
Speaker 1: think because it, um, And I'm not a scientist. I

500
00:30:49,640 --> 00:30:52,960
Speaker 1: just want to point that out in case people got confused. Um,

501
00:30:53,000 --> 00:30:57,080
Speaker 1: but I think social distancing and whether they're correlated in

502
00:30:57,120 --> 00:31:00,360
Speaker 1: that like you know, if you're if it's freezing out side,

503
00:31:00,880 --> 00:31:05,280
Speaker 1: you're most likely to be inside, uh and stay inside

504
00:31:05,320 --> 00:31:08,000
Speaker 1: with other groups of people rather than like these outdoor

505
00:31:08,040 --> 00:31:10,720
Speaker 1: restaurants and whatnot. So people are still meeting up, but

506
00:31:10,840 --> 00:31:13,280
Speaker 1: before you know, they would go to a park or something,

507
00:31:13,320 --> 00:31:15,080
Speaker 1: and now people are like, oh, let's go hang out,

508
00:31:15,440 --> 00:31:20,280
Speaker 1: you know whatever. This is also I think, um, the

509
00:31:20,360 --> 00:31:24,440
Speaker 1: Christmas you know holiday bump, um, you know, kind of

510
00:31:24,480 --> 00:31:26,800
Speaker 1: like had a huge surge and now it's kind of

511
00:31:26,800 --> 00:31:29,000
Speaker 1: like dropping again. So so I think we're going to

512
00:31:29,160 --> 00:31:32,120
Speaker 1: kind of level out for a bit and then um,

513
00:31:32,240 --> 00:31:37,640
Speaker 1: and then we'll continue dropping. Yeah. So there there there

514
00:31:37,680 --> 00:31:40,000
Speaker 1: are a bunch of different articles about this, talking about

515
00:31:40,240 --> 00:31:43,040
Speaker 1: like what one thing that we know for certain is

516
00:31:43,640 --> 00:31:48,600
Speaker 1: uh good for not spreading coronavirus or like bad for

517
00:31:48,760 --> 00:31:51,560
Speaker 1: the actual spread of the virus is wind Like if

518
00:31:51,600 --> 00:31:55,280
Speaker 1: it's windy, it spreads much worse. And then we also

519
00:31:55,360 --> 00:31:59,640
Speaker 1: know it really seems to be like a completely correlated

520
00:31:59,760 --> 00:32:06,000
Speaker 1: wind temperature. There's this study that found I think it

521
00:32:06,160 --> 00:32:11,600
Speaker 1: was so starting at eighty eight degrees and going down

522
00:32:11,760 --> 00:32:16,000
Speaker 1: by one temperature, every time you drop a single degree, uh,

523
00:32:16,160 --> 00:32:20,640
Speaker 1: the rate of transmission rose by three point seven percent.

524
00:32:21,360 --> 00:32:24,640
Speaker 1: So it's like that much of a just straightforward like

525
00:32:25,160 --> 00:32:27,360
Speaker 1: if it's this temperature, you were going to have a

526
00:32:27,400 --> 00:32:33,120
Speaker 1: COVID spike. Um, which seems relevant, And like I was thinking, like,

527
00:32:33,160 --> 00:32:36,040
Speaker 1: why why aren't we telling everybody this because that seems

528
00:32:36,080 --> 00:32:39,240
Speaker 1: like a very important thing, But they like nobody knows

529
00:32:39,440 --> 00:32:44,120
Speaker 1: why other than that the actual like physical virus likes

530
00:32:44,160 --> 00:32:48,560
Speaker 1: that temperature better. Because they were saying that, apparently, I

531
00:32:48,560 --> 00:32:54,280
Speaker 1: I always assumed the influenza, what influenza was seasonal because

532
00:32:54,320 --> 00:32:56,960
Speaker 1: of you know, what you were mentioning, Matt, like staying

533
00:32:56,960 --> 00:33:01,120
Speaker 1: inside versus going outside during the summer months. And this

534
00:33:01,200 --> 00:33:04,520
Speaker 1: scientist in this article was saying that, like that, actually

535
00:33:05,000 --> 00:33:10,200
Speaker 1: the literature doesn't support that. Um, we actually only spend

536
00:33:10,280 --> 00:33:14,720
Speaker 1: like ten more time indoors during the winter than outdoors

537
00:33:14,760 --> 00:33:19,920
Speaker 1: on average than we do during the summer on average. Right,

538
00:33:21,160 --> 00:33:23,680
Speaker 1: I mean you know which people are this who is

539
00:33:23,680 --> 00:33:27,040
Speaker 1: outside less in the way. I feel like I never

540
00:33:27,080 --> 00:33:29,280
Speaker 1: go outside in the winter. I'm like home inside. Great,

541
00:33:29,880 --> 00:33:31,600
Speaker 1: it might be because we never go outside in the

542
00:33:31,600 --> 00:33:48,400
Speaker 1: summer either, to right, right, I'm a hermit in Um. Yeah.

543
00:33:48,480 --> 00:33:53,880
Speaker 1: Another kind of new emerging study or like kind of

544
00:33:54,000 --> 00:33:57,600
Speaker 1: scientific area that they're looking at is uh COVID what

545
00:33:57,640 --> 00:34:01,160
Speaker 1: they're calling COVID longhaulers, which gives it a very like

546
00:34:01,800 --> 00:34:06,040
Speaker 1: seventies smokey in the bear uh like type vibe. But

547
00:34:06,120 --> 00:34:09,720
Speaker 1: it's actually like people who a recent study of patients

548
00:34:09,719 --> 00:34:13,840
Speaker 1: in Wuhan, China, found three quarters of them still have

549
00:34:13,960 --> 00:34:19,480
Speaker 1: symptoms six months after they left the hospital. So like,

550
00:34:19,640 --> 00:34:23,640
Speaker 1: that's how many do you say, three quarters? Three three quarters?

551
00:34:23,680 --> 00:34:28,080
Speaker 1: So that's obviously, like they this isn't a sample of

552
00:34:28,160 --> 00:34:30,759
Speaker 1: everybody who tested positive, right, this is a sample of

553
00:34:30,760 --> 00:34:35,719
Speaker 1: people who were bad enough to have to be hospitalized. Um,

554
00:34:35,760 --> 00:34:39,719
Speaker 1: but still it's I guess, I guess I have generally

555
00:34:39,760 --> 00:34:43,680
Speaker 1: heard the stories of people who uh don't make it

556
00:34:44,080 --> 00:34:47,600
Speaker 1: or people who recover and just get back to their lives.

557
00:34:47,680 --> 00:34:51,920
Speaker 1: I didn't really know about this, And apparently the illness

558
00:34:51,960 --> 00:34:54,719
Speaker 1: that they're seeing a lot of these people have is

559
00:34:54,840 --> 00:35:00,360
Speaker 1: very similar to chronic fatigue syndrome, which is uh, really

560
00:35:00,760 --> 00:35:06,239
Speaker 1: strange and interesting disease that has like no biomarker, like

561
00:35:06,280 --> 00:35:09,439
Speaker 1: they can't find any physical thing in the blood, but

562
00:35:09,640 --> 00:35:14,399
Speaker 1: it is so like it's a nightmare scenario where you

563
00:35:14,880 --> 00:35:19,080
Speaker 1: like are you know people doctors are like, you're it's

564
00:35:19,120 --> 00:35:22,120
Speaker 1: just in your head, and like, more and more they've

565
00:35:22,239 --> 00:35:24,560
Speaker 1: been able to get rid of that stigma and been like, no,

566
00:35:24,680 --> 00:35:27,960
Speaker 1: it's actually like they were talking to this one sixteen

567
00:35:28,040 --> 00:35:30,960
Speaker 1: year old who can only sit up in bed for

568
00:35:31,000 --> 00:35:34,399
Speaker 1: like two hours a day, and when he sits up,

569
00:35:34,760 --> 00:35:37,800
Speaker 1: like when he's lying down, his heart rate of sixty

570
00:35:37,840 --> 00:35:40,960
Speaker 1: five or in the sixties, and when he sat up

571
00:35:41,040 --> 00:35:45,759
Speaker 1: it goes to one thirty five, Like it's insane. Bryan

572
00:35:45,840 --> 00:35:48,400
Speaker 1: Gumble just did a really good piece on this for

573
00:35:48,520 --> 00:35:52,360
Speaker 1: Real Sports of Bran Gumble on HBO where he interviewed

574
00:35:52,480 --> 00:35:55,200
Speaker 1: athletes who had gotten COVID. Most of them were like

575
00:35:55,280 --> 00:35:59,320
Speaker 1: college age athletes, like on their track team from we

576
00:35:59,520 --> 00:36:02,520
Speaker 1: got COVID it. So she had all the like base symptoms,

577
00:36:02,560 --> 00:36:06,440
Speaker 1: like couldn't smell anything, like a feverish sort of symptoms.

578
00:36:06,920 --> 00:36:09,160
Speaker 1: It was out for two weeks. She got up, She's like, oh,

579
00:36:09,320 --> 00:36:12,160
Speaker 1: I feel better. I'm gonna go for a run this morning,

580
00:36:12,440 --> 00:36:15,680
Speaker 1: she said out of her door, and was like ready

581
00:36:15,719 --> 00:36:18,680
Speaker 1: to collapse and just couldn't do it. And it's been

582
00:36:18,719 --> 00:36:21,040
Speaker 1: something like three or four months and she still can't

583
00:36:21,040 --> 00:36:24,040
Speaker 1: go for like a regular run. It's just whild the

584
00:36:24,440 --> 00:36:28,200
Speaker 1: havoc this can wrete on bodies, especially perfectly healthy bodies.

585
00:36:28,239 --> 00:36:32,640
Speaker 1: I think, you know, for preconditioning pre existing conditions, there's

586
00:36:32,640 --> 00:36:34,560
Speaker 1: a lot of thought of like, okay, well obviously that's

587
00:36:34,560 --> 00:36:37,240
Speaker 1: going to take some extra effort. But it's perfectly healthy

588
00:36:37,400 --> 00:36:40,239
Speaker 1: human beings that are just being like knocked over by

589
00:36:40,280 --> 00:36:42,759
Speaker 1: this disease. It's wild to think some people are still

590
00:36:42,760 --> 00:36:48,840
Speaker 1: like it's the flu. It's not right like after U

591
00:36:49,719 --> 00:36:52,600
Speaker 1: bender of like ice cream and pizza for a week,

592
00:36:53,160 --> 00:36:58,200
Speaker 1: that a college track athlete is healthier than I have

593
00:36:58,320 --> 00:37:01,600
Speaker 1: been on my healthiest day in the history of my life. Like,

594
00:37:01,760 --> 00:37:04,800
Speaker 1: so that is my biggest fear about starting to work out,

595
00:37:06,440 --> 00:37:09,680
Speaker 1: like totally. My biggest fear about like deciding to like

596
00:37:09,800 --> 00:37:12,719
Speaker 1: overhaul my life and go completely you know, have a

597
00:37:12,800 --> 00:37:15,640
Speaker 1: healthy lifestyle, is that like I'll be stricken with something

598
00:37:16,080 --> 00:37:18,040
Speaker 1: and I'll be like, you know what, I should have

599
00:37:18,080 --> 00:37:19,799
Speaker 1: never started. I should have just lived up the last

600
00:37:19,800 --> 00:37:27,359
Speaker 1: few years to get all buff look good. Yeah, now

601
00:37:27,360 --> 00:37:29,320
Speaker 1: I'm saying I can't do nothing and I should have

602
00:37:29,400 --> 00:37:33,239
Speaker 1: just been eating hamburgers the whole time. Same ship. Yeah,

603
00:37:33,480 --> 00:37:36,200
Speaker 1: that's my big fear. It really does seem so much random.

604
00:37:36,360 --> 00:37:39,239
Speaker 1: There's also and I have no reason to believe this

605
00:37:39,320 --> 00:37:43,399
Speaker 1: is connected other than that they reminded me of each other.

606
00:37:43,440 --> 00:37:49,200
Speaker 1: But just anecdotally, I feel tired constantly. I know so

607
00:37:49,239 --> 00:37:51,960
Speaker 1: many people who feel tired constantly. I don't know if

608
00:37:52,000 --> 00:37:56,080
Speaker 1: that is um, you know, just the fact that we don't.

609
00:37:56,560 --> 00:37:59,120
Speaker 1: Like I I definitely feel less tired if I go

610
00:37:59,640 --> 00:38:02,359
Speaker 1: some where during the day. So maybe it's just like

611
00:38:02,440 --> 00:38:05,799
Speaker 1: that we're in the Like I do exercise, I run,

612
00:38:05,960 --> 00:38:09,560
Speaker 1: but I am running, you know, thirty feet from where

613
00:38:09,560 --> 00:38:13,080
Speaker 1: I'm sitting right now on a treadmill, and like, yeah,

614
00:38:13,080 --> 00:38:16,560
Speaker 1: it's just different because like the fatigue you're talking about

615
00:38:16,719 --> 00:38:21,200
Speaker 1: is like that. It's it's like almost a psychosomatic fatigue

616
00:38:21,200 --> 00:38:24,680
Speaker 1: where it's not really about the overall health of your body.

617
00:38:24,719 --> 00:38:27,800
Speaker 1: It's more about, you know, the fact that you're stuck

618
00:38:27,800 --> 00:38:32,440
Speaker 1: inside during a you know, a massive pandemic, and and

619
00:38:32,480 --> 00:38:35,000
Speaker 1: it's very depressing and you're just like, you know, in

620
00:38:35,040 --> 00:38:37,920
Speaker 1: this little you know, hamster cage, and we're like, I

621
00:38:37,920 --> 00:38:40,480
Speaker 1: guess I'll spin on the wheel, like, you know, the

622
00:38:40,520 --> 00:38:44,759
Speaker 1: hamster might be physically healthy, but he's so sad. Yeah,

623
00:38:45,200 --> 00:38:49,320
Speaker 1: and people at home can't see that I am drinking

624
00:38:49,360 --> 00:38:52,120
Speaker 1: from one of those upside down drip bottle things that

625
00:38:52,120 --> 00:38:57,080
Speaker 1: they and hamster cages. Uh so that's probably sitting on

626
00:38:57,120 --> 00:39:00,920
Speaker 1: a bunch of wood chips. Um. If anybody's doubt with

627
00:39:01,000 --> 00:39:05,920
Speaker 1: the exhaustion and has like ideas, uh all years, you

628
00:39:05,920 --> 00:39:08,640
Speaker 1: know where to find me. I have an idea for you. Though.

629
00:39:10,480 --> 00:39:15,439
Speaker 1: How often do you go outside and like do activities? Oh?

630
00:39:16,360 --> 00:39:22,600
Speaker 1: Not that often? What is it February? Uh? Probably? Now

631
00:39:22,640 --> 00:39:24,960
Speaker 1: I do go outside with my kids and like take

632
00:39:25,000 --> 00:39:28,920
Speaker 1: walks and stuff. Okay, well, so you're you're probably fine then,

633
00:39:28,960 --> 00:39:32,000
Speaker 1: but I as someone who was spending months and months

634
00:39:32,040 --> 00:39:35,399
Speaker 1: and months inside and like every time thinking about like

635
00:39:35,960 --> 00:39:38,279
Speaker 1: going out, I was just like, it's always got to

636
00:39:38,320 --> 00:39:40,839
Speaker 1: be at the like park, and and and it's always like,

637
00:39:41,480 --> 00:39:43,880
Speaker 1: you know, I'm just walking around and I'm just like,

638
00:39:43,920 --> 00:39:47,680
Speaker 1: it's just it wasn't fulfilling. And then I discovered the

639
00:39:47,800 --> 00:39:52,680
Speaker 1: game of golf. And I tell you, guys, golf, I

640
00:39:52,800 --> 00:39:56,600
Speaker 1: get it now. I get it. Yeah, golf. You go

641
00:39:57,600 --> 00:40:01,760
Speaker 1: and there's like and all the people are far away

642
00:40:01,800 --> 00:40:04,040
Speaker 1: from you. Everyone who's playing at the hole in front

643
00:40:04,040 --> 00:40:06,680
Speaker 1: of you there, you know, a hundred two hundred three

644
00:40:06,760 --> 00:40:10,000
Speaker 1: hundred yards away, the people behind you another two three

645
00:40:10,040 --> 00:40:12,560
Speaker 1: hundred yards and you're just alone and you're just playing

646
00:40:12,600 --> 00:40:14,920
Speaker 1: golf and you're bad at it, and people behind you

647
00:40:14,920 --> 00:40:16,880
Speaker 1: are mad because you're like taking a lot of time.

648
00:40:17,120 --> 00:40:20,879
Speaker 1: But you're free, dog, you're friend, You're out there, You're

649
00:40:20,920 --> 00:40:24,160
Speaker 1: breathing the good air. It's like it's a good COVID

650
00:40:24,400 --> 00:40:29,400
Speaker 1: relaxation sport. You get outside, you know, physical exercise, and

651
00:40:29,600 --> 00:40:31,520
Speaker 1: you don't feel like you're a hamster on the wheel.

652
00:40:31,560 --> 00:40:36,120
Speaker 1: So play golf, Okay, Yeah, it's they do have the

653
00:40:36,120 --> 00:40:38,960
Speaker 1: they do have all the best spots in l A.

654
00:40:39,360 --> 00:40:41,600
Speaker 1: They've just been like, Okay, these are golf courses. Now

655
00:40:41,800 --> 00:40:45,520
Speaker 1: everybody can go funk themselves except people who golf. Yeah,

656
00:40:45,560 --> 00:40:47,319
Speaker 1: but now you can be someone who golfs. And I

657
00:40:47,400 --> 00:40:49,560
Speaker 1: tell you, you feel bad for the first few times

658
00:40:49,600 --> 00:40:51,319
Speaker 1: doing it because you're like, oh, this is what my

659
00:40:51,360 --> 00:40:53,600
Speaker 1: life has become. I'm a douche bag. But then after

660
00:40:53,640 --> 00:40:55,640
Speaker 1: a while you start to own the douchey nous of it,

661
00:40:56,440 --> 00:40:59,759
Speaker 1: um right, and then it's not so bad. Yeah, I

662
00:41:00,000 --> 00:41:04,280
Speaker 1: would be going around on one of those scooter things

663
00:41:04,280 --> 00:41:07,640
Speaker 1: from hole to hole. Well, like I say, like a

664
00:41:07,680 --> 00:41:20,000
Speaker 1: standing job, Segu's gonna be so mad at you take

665
00:41:20,040 --> 00:41:22,560
Speaker 1: a segway back and forth to the golf to the

666
00:41:22,760 --> 00:41:29,319
Speaker 1: uh golf cart. Yes, I don't want to do any

667
00:41:29,320 --> 00:41:37,600
Speaker 1: physical exercise. The world is like reacting to the fact

668
00:41:37,600 --> 00:41:42,240
Speaker 1: that Jeff Bezos stepping down as Amazon CEO to become

669
00:41:42,719 --> 00:41:49,640
Speaker 1: vice chair, which is another position that allows him to

670
00:41:49,680 --> 00:41:52,400
Speaker 1: do the same thing he's been doing. Like I I

671
00:41:52,640 --> 00:41:56,279
Speaker 1: really need someone to explain to me. I've read the

672
00:41:56,400 --> 00:41:59,960
Speaker 1: articles about this and I cannot figure out why anyone

673
00:42:00,000 --> 00:42:03,280
Speaker 1: and should give a ship about this at all. But people,

674
00:42:03,760 --> 00:42:06,239
Speaker 1: it's just it just seems like an opportunity for the

675
00:42:06,280 --> 00:42:11,560
Speaker 1: mainstream media to write articles that reinforce the sort of

676
00:42:11,600 --> 00:42:16,239
Speaker 1: pro billionaire propaganda. Like it's all like he started Amazon

677
00:42:16,480 --> 00:42:21,160
Speaker 1: in a garage in Washington State, Uh, you know, a

678
00:42:21,280 --> 00:42:23,840
Speaker 1: mere twenty years ago, and it's like, well, he was

679
00:42:23,960 --> 00:42:27,440
Speaker 1: also a Wall Street guy who then did that, Like

680
00:42:27,680 --> 00:42:30,480
Speaker 1: he rented out a garage, probably for a lot of money,

681
00:42:30,520 --> 00:42:33,640
Speaker 1: and like outfit did it with an orange couch because

682
00:42:33,640 --> 00:42:35,839
Speaker 1: he heard that's what you're supposed to do it startups,

683
00:42:35,880 --> 00:42:39,080
Speaker 1: and like, uh, but he's what people don't think of

684
00:42:39,200 --> 00:42:43,040
Speaker 1: garage like that, Like when they when he whenever I

685
00:42:43,120 --> 00:42:46,160
Speaker 1: hear that narrative spun, it's always he started it in

686
00:42:46,239 --> 00:42:49,600
Speaker 1: his garage, so people were thinking like a two car

687
00:42:49,760 --> 00:42:55,560
Speaker 1: garage and like he was like Amazon dot Com like

688
00:42:55,160 --> 00:43:01,239
Speaker 1: it was fucking Nirvana or something like yeah yeah, um uh,

689
00:43:03,360 --> 00:43:05,680
Speaker 1: I don't know. It just ties into the overall myth

690
00:43:05,719 --> 00:43:11,200
Speaker 1: of American capitalism that there's like these individual great man

691
00:43:11,280 --> 00:43:16,479
Speaker 1: accomplishments and not that this is the inevitable consequence of

692
00:43:16,719 --> 00:43:21,439
Speaker 1: a system that doesn't defend against monopoly and like one

693
00:43:21,520 --> 00:43:25,960
Speaker 1: person is going to get that successful and like it's

694
00:43:26,000 --> 00:43:30,839
Speaker 1: funny even this Wall Street Journal article. Uh, Like it's

695
00:43:30,880 --> 00:43:34,480
Speaker 1: like with a day one philosophy of always maintaining an

696
00:43:34,560 --> 00:43:39,040
Speaker 1: underdog startup ethos. However, in recent years, missed Mr Bezos

697
00:43:39,080 --> 00:43:42,320
Speaker 1: has stepped back from day to day management. He doesn't

698
00:43:42,360 --> 00:43:45,279
Speaker 1: set schedule meetings before ten am and makes all his

699
00:43:45,360 --> 00:43:49,240
Speaker 1: tough decisions before five pm. H employees say the billionaire

700
00:43:49,280 --> 00:43:52,240
Speaker 1: is elusive. That's how they describe it, with many saying

701
00:43:52,600 --> 00:43:55,160
Speaker 1: they have never spotted him on the company sprawling downtown

702
00:43:55,200 --> 00:43:58,200
Speaker 1: Seattle campus, so he doesn't show up to work or

703
00:43:58,280 --> 00:44:02,080
Speaker 1: works like you know, between ten and five, which are

704
00:44:02,200 --> 00:44:07,399
Speaker 1: things that would cause somebody to get immediately fired from

705
00:44:07,440 --> 00:44:11,160
Speaker 1: an Amazon warehouse job. Well, also, he could fucking solve

706
00:44:11,200 --> 00:44:15,799
Speaker 1: world hunger today, like just the like discussing the like

707
00:44:16,200 --> 00:44:18,040
Speaker 1: ins and outs of his day to day I feel

708
00:44:18,040 --> 00:44:21,839
Speaker 1: like it's just like glorifying some like you know, innocuous,

709
00:44:22,960 --> 00:44:25,840
Speaker 1: like who gives a ship what he does at what time?

710
00:44:25,920 --> 00:44:28,840
Speaker 1: He could solve world to hunger? He could help people,

711
00:44:29,160 --> 00:44:32,880
Speaker 1: but he is not. He fucking destroyed Seattle and he's

712
00:44:32,960 --> 00:44:36,080
Speaker 1: like just I don't know, I just and and the

713
00:44:36,080 --> 00:44:40,280
Speaker 1: way that these stories are framed of like the whatever

714
00:44:40,360 --> 00:44:43,480
Speaker 1: the like he's just a startup guy who like worked

715
00:44:43,560 --> 00:44:46,080
Speaker 1: really hard and hustled his way to the top. And

716
00:44:46,120 --> 00:44:49,480
Speaker 1: it's it just like implies that he has somehow earned

717
00:44:49,920 --> 00:44:52,480
Speaker 1: all of this, when it's like, we know that that's

718
00:44:52,520 --> 00:44:57,600
Speaker 1: not true, Like it's just finding people and that he's killing. Yeah,

719
00:44:57,680 --> 00:45:00,319
Speaker 1: and he's responsible for many deaths that they cover up

720
00:45:00,360 --> 00:45:04,279
Speaker 1: all the time. The Amazon warehouses are an ocean nightmare, like,

721
00:45:04,440 --> 00:45:06,879
Speaker 1: and they just hide it. They don't make reports. There's

722
00:45:06,920 --> 00:45:09,240
Speaker 1: been so much as you just one quick google away

723
00:45:09,280 --> 00:45:11,960
Speaker 1: you can find out. And and that's why I hated

724
00:45:12,040 --> 00:45:14,520
Speaker 1: when all that negative press came out about Amazon during

725
00:45:14,520 --> 00:45:19,200
Speaker 1: the pandemic. Um they made all these weird commercials where

726
00:45:19,239 --> 00:45:23,239
Speaker 1: they basically like holding people at gunpoint, Like I love Amazon.

727
00:45:23,680 --> 00:45:27,080
Speaker 1: They treat me so good here. Jeff Bezos is like

728
00:45:27,120 --> 00:45:30,399
Speaker 1: a father to me, Like what is happening? Those were

729
00:45:30,520 --> 00:45:35,319
Speaker 1: so weird. And also and everywhere, yeah, everywhere. And if

730
00:45:35,360 --> 00:45:37,719
Speaker 1: we haven't learned anything from the game, stop thing is

731
00:45:37,719 --> 00:45:40,480
Speaker 1: that the game is fucking rigged. Look at what happened

732
00:45:40,480 --> 00:45:43,160
Speaker 1: when all the little everyday average joe people got their

733
00:45:43,200 --> 00:45:45,640
Speaker 1: hands on some stocks that was being shorted. All of

734
00:45:45,680 --> 00:45:47,920
Speaker 1: a sudden, your app doesn't work and you can't trade

735
00:45:47,920 --> 00:45:50,560
Speaker 1: at all because it was never built for you to

736
00:45:50,719 --> 00:45:53,319
Speaker 1: be a millionaire. You're not gonna be able to work

737
00:45:53,320 --> 00:45:55,919
Speaker 1: hard or make trades and be a millionaire because there's

738
00:45:55,920 --> 00:45:58,960
Speaker 1: already millionaires and billionaires who are going to make sure

739
00:45:59,040 --> 00:46:01,400
Speaker 1: you cannot get to the level because that's how they

740
00:46:01,400 --> 00:46:04,399
Speaker 1: stay rich. So I'm like, I'm still praying for game stock.

741
00:46:04,480 --> 00:46:06,040
Speaker 1: They and my prayers like they on the stick of

742
00:46:06,080 --> 00:46:08,560
Speaker 1: shet and I'm like, please, please y'all hold the line

743
00:46:08,560 --> 00:46:11,239
Speaker 1: they'll sell them stocks so that we can just I

744
00:46:11,280 --> 00:46:14,200
Speaker 1: want to ruin all the hedge funds. I know we're

745
00:46:14,200 --> 00:46:15,880
Speaker 1: gonna end up paying for it in our tax dollars,

746
00:46:15,920 --> 00:46:19,640
Speaker 1: but I just want to see it happen. I feel

747
00:46:19,640 --> 00:46:23,319
Speaker 1: like that one's already been is already being sunset to

748
00:46:23,719 --> 00:46:26,520
Speaker 1: like this is what happens when you go against the

749
00:46:26,520 --> 00:46:30,080
Speaker 1: big guy and like being covered as like the GameStop

750
00:46:30,160 --> 00:46:34,279
Speaker 1: thing was folly, But it's like, but also keep hustling, everybody,

751
00:46:34,320 --> 00:46:36,640
Speaker 1: this could be you, and it's like, no, no, it couldn't.

752
00:46:36,800 --> 00:46:39,680
Speaker 1: Like it's been made exceedingly clear that it fucking couldn't be.

753
00:46:39,920 --> 00:46:41,520
Speaker 1: I think we all need to just like look at

754
00:46:41,560 --> 00:46:44,480
Speaker 1: that and realize, like that is the perfect example of

755
00:46:44,520 --> 00:46:47,160
Speaker 1: like you cannot be a billionaire because billionaires will not

756
00:46:47,239 --> 00:46:52,880
Speaker 1: let you right right. The thing of specifically trying to

757
00:46:53,000 --> 00:46:57,200
Speaker 1: reinforce the underdog myth um, which is is the main

758
00:46:57,280 --> 00:47:01,200
Speaker 1: motif that gets reasserted over and over again in these

759
00:47:01,280 --> 00:47:05,680
Speaker 1: articles about him retiring. Um really like it really seems

760
00:47:05,719 --> 00:47:10,600
Speaker 1: like it's uh the war department thing again, Like I

761
00:47:10,600 --> 00:47:14,400
Speaker 1: taught for shorthand, I I talked about how the US

762
00:47:14,560 --> 00:47:19,560
Speaker 1: military changed it's uh name from War Department to Department

763
00:47:19,600 --> 00:47:24,160
Speaker 1: of Defense once they started waging offensive wars because you

764
00:47:24,280 --> 00:47:27,520
Speaker 1: like do that you change the name to be the

765
00:47:27,560 --> 00:47:29,719
Speaker 1: opposite of the truth so that you can like kind

766
00:47:29,719 --> 00:47:33,960
Speaker 1: of cover up for it. And like with trying to

767
00:47:34,000 --> 00:47:37,919
Speaker 1: portray billionaires is underdog stories like the when people look

768
00:47:37,960 --> 00:47:42,440
Speaker 1: at how billionaires make their fortune, it's always the opposite

769
00:47:42,480 --> 00:47:45,480
Speaker 1: of that. It's always they find an advantage over someone

770
00:47:45,520 --> 00:47:49,239
Speaker 1: who's smaller or has less you know, resources than them,

771
00:47:49,640 --> 00:47:53,160
Speaker 1: and just exploit the ship out of that until they

772
00:47:53,160 --> 00:47:55,600
Speaker 1: are they have billions of dollars. That's the only way

773
00:47:55,600 --> 00:47:59,160
Speaker 1: to become a billionaire is by being a predatory uh

774
00:47:59,280 --> 00:48:05,439
Speaker 1: capitalist praise on less powerful you know dynamics basically, Um.

775
00:48:05,480 --> 00:48:09,520
Speaker 1: But because we don't like the idea that that is

776
00:48:09,560 --> 00:48:13,279
Speaker 1: the secret to capitalism. We tell ourselves over and over

777
00:48:13,320 --> 00:48:16,600
Speaker 1: again and pay the Wall Street Journal to tell us

778
00:48:16,600 --> 00:48:19,200
Speaker 1: over and over again that it's all Disney movies where

779
00:48:19,320 --> 00:48:24,799
Speaker 1: the underdog came up. It's yeah, it's it's just like,

780
00:48:26,320 --> 00:48:28,200
Speaker 1: I don't know, and it's it's weird because I feel

781
00:48:28,200 --> 00:48:30,600
Speaker 1: like it's kind of unspoken that most people recognize that

782
00:48:30,640 --> 00:48:34,400
Speaker 1: it is like a false narrative, but it hasn't stopped

783
00:48:34,400 --> 00:48:38,959
Speaker 1: it from being pushed over and over and over. Yeah,

784
00:48:39,000 --> 00:48:42,520
Speaker 1: I think it's I do wonder if we're like moving

785
00:48:42,560 --> 00:48:47,480
Speaker 1: in that direction, But it does seem like it's you know,

786
00:48:47,560 --> 00:48:50,040
Speaker 1: you you wouldn't know it from reading like the mainstream

787
00:48:50,040 --> 00:48:54,520
Speaker 1: accounts of Jeff Bezos and way that It's also it's

788
00:48:54,520 --> 00:48:56,080
Speaker 1: like a question of like, well, how many of these

789
00:48:56,080 --> 00:48:59,880
Speaker 1: papers does Jeff Bezos own? You know, it goes off

790
00:48:59,920 --> 00:49:03,560
Speaker 1: the way to the top there. Yeah, so this diet

791
00:49:03,680 --> 00:49:09,880
Speaker 1: left past story is one that it's it's a staple

792
00:49:10,160 --> 00:49:15,320
Speaker 1: of the um, you know, conspiracy theory community. I first

793
00:49:15,320 --> 00:49:20,279
Speaker 1: came across it in an article like I think over

794
00:49:20,320 --> 00:49:25,040
Speaker 1: a decade ago and cracked that was basically miss like

795
00:49:25,160 --> 00:49:30,279
Speaker 1: big famous unsolved mysteries that totally have solutions. Um And

796
00:49:30,360 --> 00:49:33,600
Speaker 1: so here I'll tell you what the mystery is all

797
00:49:33,719 --> 00:49:37,880
Speaker 1: since you're not familiar with it. Um So, ten members

798
00:49:38,040 --> 00:49:40,560
Speaker 1: of this Uh, this is a real thing. This is

799
00:49:40,560 --> 00:49:43,200
Speaker 1: a real thing. The way you started off, it sounded

800
00:49:43,239 --> 00:49:47,080
Speaker 1: like a weird so it was a stormy night and

801
00:49:47,440 --> 00:49:53,000
Speaker 1: ten so ten members of like a polytechnic institute, like

802
00:49:53,040 --> 00:49:58,279
Speaker 1: a scientific college, nine students and one sports instructor who

803
00:49:58,360 --> 00:50:00,880
Speaker 1: had fought in World War Two headed up into the

804
00:50:00,960 --> 00:50:05,000
Speaker 1: frigid wilderness. Is like nineteen fifty nine, One student with

805
00:50:05,080 --> 00:50:09,080
Speaker 1: joint pain, uh turned back, and the rest, led by

806
00:50:09,280 --> 00:50:14,400
Speaker 1: a twenty three year old engineering student, continued on. There's

807
00:50:14,800 --> 00:50:19,040
Speaker 1: camera film personal diaries later found on the scene that

808
00:50:19,239 --> 00:50:22,400
Speaker 1: makes it clear they made camp on February one, pitching

809
00:50:22,440 --> 00:50:26,200
Speaker 1: a large tent on the snowy slopes of a mountain

810
00:50:26,239 --> 00:50:29,279
Speaker 1: I'm not gonna try to pronounce, probably not when you're

811
00:50:29,840 --> 00:50:33,640
Speaker 1: intimately familiar with but the name can be interpreted as

812
00:50:33,760 --> 00:50:38,600
Speaker 1: dead mountain in the language of the region's indigenous Mancie people.

813
00:50:39,239 --> 00:50:43,399
Speaker 1: Uh So, when a search team arrived a few weeks later,

814
00:50:43,480 --> 00:50:46,200
Speaker 1: because they just nobody ever heard from them again. The

815
00:50:47,840 --> 00:50:49,839
Speaker 1: other guy made it back and he never heard from

816
00:50:49,920 --> 00:50:56,160
Speaker 1: them again. Like none of the planned you know, rendezvous happened. Uh.

817
00:50:56,640 --> 00:50:59,000
Speaker 1: Their tent was found barely sticking out of the snow.

818
00:50:59,800 --> 00:51:02,799
Speaker 1: It here to be cut open from the inside. Uh.

819
00:51:02,840 --> 00:51:04,719
Speaker 1: The next day, the first of the bodies were found

820
00:51:04,800 --> 00:51:07,759
Speaker 1: near Cedar Tree. Over the next few months, as the

821
00:51:07,800 --> 00:51:14,400
Speaker 1: snow thawed, they gradually uncovered just all sorts of creepy bodies.

822
00:51:14,480 --> 00:51:16,959
Speaker 1: All nine of the team members. Bodies were scattered around

823
00:51:16,960 --> 00:51:20,239
Speaker 1: the mountain slope, some in a baffling state of undressed.

824
00:51:20,239 --> 00:51:22,399
Speaker 1: They were half naked, some of their skulls and chests

825
00:51:22,440 --> 00:51:26,040
Speaker 1: have been smashed open. Others had eyes and one lacked

826
00:51:26,080 --> 00:51:29,200
Speaker 1: a tongue. Others had eyes missing and one lacked a tongue.

827
00:51:29,719 --> 00:51:32,880
Speaker 1: And yeah, people were like, this doesn't make any sense.

828
00:51:32,920 --> 00:51:36,880
Speaker 1: There was also uh, like radiation on one of the bodies,

829
00:51:37,600 --> 00:51:42,920
Speaker 1: and so people like the official explanation from the Soviet

830
00:51:42,960 --> 00:51:47,640
Speaker 1: bureaucracy was quote unknown natural force and so that like,

831
00:51:47,760 --> 00:51:51,960
Speaker 1: it's it's impossible not to be into this as like

832
00:51:52,000 --> 00:51:57,200
Speaker 1: a somebody who's open to conspiracy theories. Yeah, it could

833
00:51:57,200 --> 00:52:01,440
Speaker 1: be anything. Monsters yeties what her. So back when we

834
00:52:01,480 --> 00:52:04,800
Speaker 1: wrote about it, we pointed out that it made sense

835
00:52:04,880 --> 00:52:07,719
Speaker 1: as an avalanche, uh, and just kind of some of

836
00:52:07,760 --> 00:52:13,000
Speaker 1: the more inexplicable details, like the radiation isn't actually that

837
00:52:13,239 --> 00:52:17,520
Speaker 1: uncommon for anything that's been laying in a snowy area

838
00:52:18,000 --> 00:52:21,200
Speaker 1: that gets a lot of sun because sun is a

839
00:52:21,320 --> 00:52:24,600
Speaker 1: snow is a tremendous reflector of the sun's energy. The

840
00:52:24,680 --> 00:52:29,839
Speaker 1: missing eyes and tongue are pretty common with bodies left

841
00:52:29,920 --> 00:52:32,200
Speaker 1: in the wilderness for a long time, since animals go

842
00:52:32,280 --> 00:52:35,560
Speaker 1: for the soft parts first. Um. And the various states

843
00:52:35,560 --> 00:52:41,560
Speaker 1: of undressed are pretty common for anybody suffering from hypothermia.

844
00:52:42,000 --> 00:52:44,640
Speaker 1: And you know, the theory being that they ran out

845
00:52:44,640 --> 00:52:47,920
Speaker 1: of their tent when an avalanche they heard an avalanche

846
00:52:47,920 --> 00:52:50,920
Speaker 1: coming at night, uh, and the tent and all their

847
00:52:51,000 --> 00:52:55,120
Speaker 1: stuff was buried, and so they died of hypothermia. People

848
00:52:55,520 --> 00:52:58,640
Speaker 1: will as they're dying of hypothermia feel hot and like

849
00:52:58,719 --> 00:53:02,960
Speaker 1: take off some of their clothes. Is, um, oh yeah,

850
00:53:03,000 --> 00:53:10,840
Speaker 1: that's yeah. So the but people there there was a

851
00:53:10,840 --> 00:53:14,600
Speaker 1: lot of like pushback on that theory, not just that

852
00:53:14,600 --> 00:53:17,600
Speaker 1: that was like one of the more common explanations, and

853
00:53:17,640 --> 00:53:19,600
Speaker 1: we just pointed out that it made a lot of sense,

854
00:53:20,200 --> 00:53:24,279
Speaker 1: uh in ways that conspiracy theory that pushing back, Like

855
00:53:24,480 --> 00:53:27,000
Speaker 1: my first thing was like, yeah, probably, like if they're

856
00:53:27,040 --> 00:53:29,920
Speaker 1: scattered everywhere to like who knows if even the avalanche

857
00:53:29,920 --> 00:53:33,640
Speaker 1: took some people. Yeah, So there was no snowfall on

858
00:53:33,680 --> 00:53:37,320
Speaker 1: the night that the avalanche would have happened, and usually

859
00:53:37,320 --> 00:53:40,840
Speaker 1: you need snowfall to add weight to the snow burden

860
00:53:41,120 --> 00:53:44,400
Speaker 1: that triggers the collapse. Most of the blunt forced trauma

861
00:53:44,440 --> 00:53:47,799
Speaker 1: like injuries and some of the soft tissue damage were

862
00:53:47,840 --> 00:53:53,680
Speaker 1: atypical of things caused by avalanches, um, where usually people

863
00:53:53,880 --> 00:54:00,120
Speaker 1: mostly asphyxiate. And then if an avalanche had occurred, uh oh.

864
00:54:00,160 --> 00:54:02,600
Speaker 1: There there's this thing about like a gap of nine

865
00:54:02,640 --> 00:54:07,000
Speaker 1: hours between when they made camp and when the avalanche happened.

866
00:54:07,040 --> 00:54:09,120
Speaker 1: I think it assumes that they would have caused the

867
00:54:09,120 --> 00:54:12,360
Speaker 1: avalanche because they're like cutting into the side of the

868
00:54:12,400 --> 00:54:15,640
Speaker 1: mountain to make camp and that's usually how those things happen,

869
00:54:15,840 --> 00:54:19,799
Speaker 1: and yet it happened nine hours later. Um. So this

870
00:54:19,880 --> 00:54:24,399
Speaker 1: new study basically just takes those down point by point. Um.

871
00:54:24,680 --> 00:54:28,000
Speaker 1: I think the most interesting the way it's taken down

872
00:54:28,080 --> 00:54:31,480
Speaker 1: is that the idea that there's dimension, the fact that

873
00:54:31,520 --> 00:54:34,719
Speaker 1: people say it wasn't a steep enough hill that they

874
00:54:34,760 --> 00:54:37,359
Speaker 1: were camping. Oh, so they're saying it was even too

875
00:54:37,360 --> 00:54:39,640
Speaker 1: flat for an aval It was too flat for an avalanche,

876
00:54:39,680 --> 00:54:42,759
Speaker 1: is one of the things they're saying. But that's actually

877
00:54:43,680 --> 00:54:47,359
Speaker 1: a optical illusion that you see. Have you ever heard

878
00:54:47,360 --> 00:54:50,480
Speaker 1: of places where they say, like water flows uphill and

879
00:54:50,520 --> 00:54:54,920
Speaker 1: it's like this mystery of like a place where gravity

880
00:54:55,000 --> 00:54:57,400
Speaker 1: doesn't operate or gravity is weird, like you drop a

881
00:54:57,400 --> 00:55:00,120
Speaker 1: stone and it kind of falls to the side, or

882
00:55:00,120 --> 00:55:05,880
Speaker 1: a burning man. So all of uh that that actually

883
00:55:06,600 --> 00:55:09,799
Speaker 1: is a thing that happens. Like basically, you're at a

884
00:55:09,880 --> 00:55:13,400
Speaker 1: place that a chunk of flat ground that is actually

885
00:55:14,239 --> 00:55:17,880
Speaker 1: on a portion of ground that's embedded with within a

886
00:55:17,960 --> 00:55:23,239
Speaker 1: larger slope. So even though all your sort of context

887
00:55:23,400 --> 00:55:26,040
Speaker 1: clues point to the fact that you're on flat ground,

888
00:55:26,640 --> 00:55:30,080
Speaker 1: you're actually on a slope. And that's what was happening here.

889
00:55:30,120 --> 00:55:33,000
Speaker 1: They say that this piece of land, when you go

890
00:55:33,040 --> 00:55:38,239
Speaker 1: and study it, has at least thet grade needed to

891
00:55:38,320 --> 00:55:42,320
Speaker 1: trigger avalanches. There wasn't snowfall, but there was massive wind.

892
00:55:42,960 --> 00:55:44,799
Speaker 1: But one of the reasons this is like kind of

893
00:55:44,800 --> 00:55:48,840
Speaker 1: a fun story that I think might actually like become

894
00:55:48,840 --> 00:55:51,200
Speaker 1: popular enough to put an end to this is that

895
00:55:51,239 --> 00:55:56,000
Speaker 1: they used frozen the Disney movie to figure this out

896
00:55:57,200 --> 00:56:04,759
Speaker 1: like like clues from the film or so. One of

897
00:56:04,800 --> 00:56:10,080
Speaker 1: the scientists who is basically created this paper with the

898
00:56:10,160 --> 00:56:14,719
Speaker 1: official explanation back when Frozen came out was like, holy shit,

899
00:56:14,920 --> 00:56:20,400
Speaker 1: they have absolutely nailed h the way snowfalls and is

900
00:56:20,440 --> 00:56:24,440
Speaker 1: blown away and is like actually behaves. And so he

901
00:56:24,520 --> 00:56:27,160
Speaker 1: actually traveled to Hollywood and met with the three D

902
00:56:27,280 --> 00:56:31,080
Speaker 1: modeling company that created the snow for Frozen and like

903
00:56:31,200 --> 00:56:34,799
Speaker 1: got a better idea of how snow behaves and like

904
00:56:35,040 --> 00:56:39,240
Speaker 1: used their algorithms that they used on Frozen to better

905
00:56:39,320 --> 00:56:44,080
Speaker 1: inform his algorithms of just like how snow operates. And

906
00:56:44,080 --> 00:56:49,120
Speaker 1: then they also consulted these old GM studies that they

907
00:56:49,160 --> 00:56:52,640
Speaker 1: had done with a bunch of cadavers, like back when

908
00:56:53,160 --> 00:56:56,040
Speaker 1: people weren't paying as much attention. GM took a hundred

909
00:56:56,080 --> 00:57:00,000
Speaker 1: dead bodies and just like through heavy shit at them, uh,

910
00:57:00,040 --> 00:57:03,080
Speaker 1: and just like studied the way that the bodies were destroyed.

911
00:57:03,680 --> 00:57:08,360
Speaker 1: Um were fourteen year olds in charge of Yeah, I

912
00:57:08,600 --> 00:57:14,760
Speaker 1: just smash them up, and we're like, oh and so yeah,

913
00:57:15,120 --> 00:57:18,280
Speaker 1: that's bad. It's bad. So looking at that study data,

914
00:57:18,320 --> 00:57:23,000
Speaker 1: they basically found that the injuries were pretty consistent with

915
00:57:23,520 --> 00:57:26,320
Speaker 1: what you would have seen if there was a like

916
00:57:26,600 --> 00:57:30,840
Speaker 1: suv style chunk of hard snow or ice inside of

917
00:57:30,880 --> 00:57:33,880
Speaker 1: the avalanche which is hitting you right, And yeah, so

918
00:57:34,560 --> 00:57:37,800
Speaker 1: they think the avalanche hit them. They were camped at

919
00:57:37,800 --> 00:57:40,520
Speaker 1: a pretty like when you look at where their beds were,

920
00:57:40,560 --> 00:57:42,440
Speaker 1: they were actually like dug into the snow in a

921
00:57:42,480 --> 00:57:45,960
Speaker 1: way that they were pretty well supported. So when the

922
00:57:46,000 --> 00:57:51,240
Speaker 1: thing hit them, they were pre demolished but probably didn't die.

923
00:57:51,400 --> 00:57:55,200
Speaker 1: And then their camp mates like dragged them out to

924
00:57:55,360 --> 00:58:00,160
Speaker 1: safety and then went downhill. Yeah, all went downhill from there. Um,

925
00:58:00,880 --> 00:58:04,440
Speaker 1: but it's a wild story. Uh. And I don't know.

926
00:58:05,440 --> 00:58:08,280
Speaker 1: I do think that this is the explanation. I don't

927
00:58:08,280 --> 00:58:13,240
Speaker 1: think there's been Yeah, Yettie explanation, Eddie Gang, where are

928
00:58:13,240 --> 00:58:17,240
Speaker 1: you at? Come on rebut this terrible study Yetie, they're

929
00:58:17,320 --> 00:58:21,439
Speaker 1: going to uh they Yeah, I am making a lot

930
00:58:21,480 --> 00:58:24,479
Speaker 1: of enemies. As reasonable as this might sound, I'm gonna

931
00:58:24,520 --> 00:58:30,440
Speaker 1: be what in big community, people like a sexier Yetie explanation.

932
00:58:31,720 --> 00:58:34,880
Speaker 1: Come on watch, they're gonna be like, well, if they

933
00:58:34,960 --> 00:58:38,160
Speaker 1: use Frozen, we will use the modeling of the child

934
00:58:38,280 --> 00:58:42,960
Speaker 1: Child's film Abominable to then prove our YETI theory. It's like, well, no,

935
00:58:43,040 --> 00:58:45,440
Speaker 1: that's not what they did. It wasn't just because there

936
00:58:45,520 --> 00:58:49,520
Speaker 1: was a movie that that reinforced their their argument. But

937
00:58:50,240 --> 00:58:52,400
Speaker 1: go at it yetie Gang, I'd love to see it. Yeah,

938
00:58:52,560 --> 00:58:57,120
Speaker 1: they probably will use the fact that, oh because frozen Okay, yeah, yeah,

939
00:58:57,480 --> 00:59:00,080
Speaker 1: what did a nice monster do it? That elsa of

940
00:59:00,160 --> 00:59:03,560
Speaker 1: created Right, That's where it's that's where you realize to like,

941
00:59:03,960 --> 00:59:06,800
Speaker 1: you don't get don't get an arguments with conspiracy theorists,

942
00:59:07,360 --> 00:59:10,640
Speaker 1: because if you're not on the same page, then nothing

943
00:59:10,680 --> 00:59:13,560
Speaker 1: you're saying is real and there will be It's like,

944
00:59:13,600 --> 00:59:15,880
Speaker 1: I don't even know how you reverse engineer common ground.

945
00:59:15,920 --> 00:59:17,400
Speaker 1: At that point, we're like, all right, well, where can

946
00:59:17,440 --> 00:59:21,000
Speaker 1: we agree what snow? Can we agree that that's frozen

947
00:59:21,080 --> 00:59:23,960
Speaker 1: like a water that's very in a solid state? Okay? Okay,

948
00:59:24,000 --> 00:59:27,600
Speaker 1: moving on, what's Russia? And then it all falls apart

949
00:59:27,920 --> 00:59:30,400
Speaker 1: like an experimental ground Russian governments of the world to

950
00:59:30,520 --> 00:59:33,640
Speaker 1: like create like new bio bio organisms that are like

951
00:59:33,640 --> 00:59:37,840
Speaker 1: like just terrorize the earth. Russia exists, right, and you're like,

952
00:59:38,080 --> 00:59:44,240
Speaker 1: who's now, who's naive? Uh? Did you say Russia? What?

953
00:59:45,160 --> 00:59:47,360
Speaker 1: Let's take a quick break and we'll be right back,

954
00:59:57,640 --> 01:00:02,880
Speaker 1: and we're back. Nancy Flosie told me about this new

955
01:00:02,960 --> 01:00:06,840
Speaker 1: treat that she's stocking in her fridge. Uh in your

956
01:00:06,880 --> 01:00:12,760
Speaker 1: telegram channel called lit Freezers. Yeah, Jenny's, which is what

957
01:00:13,080 --> 01:00:17,000
Speaker 1: Nancy Pelosi had her fridge stocked with. It's like, uh,

958
01:00:17,480 --> 01:00:22,480
Speaker 1: fourteen dollar a pint ice cream? Um, it's nine Jack

959
01:00:22,560 --> 01:00:29,080
Speaker 1: don alright, I don't know. I think it's like twelve.

960
01:00:29,160 --> 01:00:31,400
Speaker 1: Maybe you guys are just like Nancy Pelosi. You have

961
01:00:31,440 --> 01:00:33,520
Speaker 1: no idea how much a pint of ice cream? Actually,

962
01:00:33,720 --> 01:00:40,400
Speaker 1: I don't know, out of touch, how much is a banana?

963
01:00:41,600 --> 01:00:43,320
Speaker 1: Did you guys read? There is that interview with Billie

964
01:00:43,320 --> 01:00:44,880
Speaker 1: Eilish the other day where she was like, I don't

965
01:00:44,920 --> 01:00:47,240
Speaker 1: know how much cereal costs. So I ordered like what

966
01:00:47,280 --> 01:00:49,120
Speaker 1: I thought was a box of cereal and it was

967
01:00:49,200 --> 01:00:53,080
Speaker 1: like fifty boxes of cereal. She thought a cereal boxing

968
01:00:53,160 --> 01:00:59,560
Speaker 1: zero was like, yeah, she doesn't know. Like you're too young,

969
01:00:59,680 --> 01:01:04,040
Speaker 1: probably doesn't even know what that because she's rich for

970
01:01:04,080 --> 01:01:07,080
Speaker 1: so long. And the combination of like you're a teenager

971
01:01:07,320 --> 01:01:10,600
Speaker 1: maybe doesn't buy your own groceries and now you're incredibly

972
01:01:10,720 --> 01:01:13,200
Speaker 1: rich and have no idea how much things cost because

973
01:01:13,240 --> 01:01:16,360
Speaker 1: she completely skipped that phase of life where you have

974
01:01:16,560 --> 01:01:18,720
Speaker 1: like a little bit of money that you've earned and

975
01:01:18,760 --> 01:01:20,520
Speaker 1: you try and go out to eat with your friends.

976
01:01:21,560 --> 01:01:24,120
Speaker 1: That's a very formative period. So if you go straight

977
01:01:24,160 --> 01:01:26,160
Speaker 1: from I don't know every time I go, my parents

978
01:01:26,200 --> 01:01:28,400
Speaker 1: pay for everything to I don't know my accountant, I

979
01:01:28,440 --> 01:01:29,960
Speaker 1: have a card to my account and gave me and

980
01:01:29,960 --> 01:01:32,560
Speaker 1: I just I waived that at whatever. You don't have

981
01:01:32,640 --> 01:01:36,360
Speaker 1: to choose between like seeing the movie and having dinner exactly,

982
01:01:37,560 --> 01:01:39,520
Speaker 1: or be like, all right, fuck it, let's let's let's

983
01:01:39,560 --> 01:01:41,360
Speaker 1: figure out what you got a calculator or just do

984
01:01:41,400 --> 01:01:43,720
Speaker 1: it on paper with the tax Okay, so we'll get

985
01:01:43,840 --> 01:01:46,640
Speaker 1: nachos and then a case idea, and then we'll all

986
01:01:46,640 --> 01:01:49,520
Speaker 1: have enough to go in the movie and then maybe

987
01:01:49,520 --> 01:01:52,440
Speaker 1: split a smoothie at the end. Okay. There's also that

988
01:01:52,560 --> 01:01:56,840
Speaker 1: point where you're growing out of like being young enough

989
01:01:56,880 --> 01:01:59,920
Speaker 1: where it's still kind of cute that you don't know stuff,

990
01:02:00,560 --> 01:02:03,400
Speaker 1: uh right, right, which is why it's not cute that

991
01:02:03,520 --> 01:02:08,080
Speaker 1: Nancy Pelosi doesn't know it's a bad look to have

992
01:02:08,520 --> 01:02:11,960
Speaker 1: five hundred pints of really expensive ice cream in your

993
01:02:11,960 --> 01:02:14,920
Speaker 1: fridge when people are starving. You know, like, how much

994
01:02:14,960 --> 01:02:18,040
Speaker 1: is a violet insulin? Nancy, I don't know. She's like

995
01:02:18,080 --> 01:02:24,680
Speaker 1: I don't know like three, but yeah, So this boutique creamery, Jenny's,

996
01:02:24,920 --> 01:02:27,040
Speaker 1: it's not really boutique, it's a chain now right, huge

997
01:02:27,080 --> 01:02:31,920
Speaker 1: Now they're huge. But they dropped a flavor everything Bagel

998
01:02:32,400 --> 01:02:36,560
Speaker 1: and I don't know if it was viral marketing or whatever,

999
01:02:36,680 --> 01:02:41,720
Speaker 1: but they call it violent marketing. They had somebody who

1000
01:02:41,760 --> 01:02:44,560
Speaker 1: I follow and trust on socials like I don't know

1001
01:02:44,640 --> 01:02:46,960
Speaker 1: how it's this good, but it is. And I was like,

1002
01:02:46,960 --> 01:02:50,560
Speaker 1: well that's enough for me. Yeah, I'm I'm worried because

1003
01:02:51,360 --> 01:02:53,800
Speaker 1: when I saw the thing, I'm like, get the funk

1004
01:02:53,840 --> 01:02:56,240
Speaker 1: out of my face with this everything Bagel ice cream.

1005
01:02:56,320 --> 01:02:59,160
Speaker 1: My friend Goldie was like, come on, you cowards, like

1006
01:02:59,240 --> 01:03:05,240
Speaker 1: put locks in there. Yeah, let's actually yes, I will try,

1007
01:03:05,640 --> 01:03:09,800
Speaker 1: but you're gonna do it. They mentioned how, you know,

1008
01:03:10,080 --> 01:03:14,200
Speaker 1: the like cream cheese like a great already stabilizer for

1009
01:03:14,320 --> 01:03:16,200
Speaker 1: ice creams as it is, so you don't have to

1010
01:03:16,200 --> 01:03:18,440
Speaker 1: put in a lot of like artificial things in it.

1011
01:03:18,640 --> 01:03:20,840
Speaker 1: So cream cheese is always like for for people who

1012
01:03:20,840 --> 01:03:24,840
Speaker 1: make ice cream, isn't anything new? Um, So I was like, okay, fine,

1013
01:03:25,280 --> 01:03:27,800
Speaker 1: I see the logic there, but like, really, like what's

1014
01:03:27,840 --> 01:03:29,800
Speaker 1: the description? They say? It's cream cheese ice cream with

1015
01:03:29,880 --> 01:03:36,280
Speaker 1: everything Bagel gravel like poppy set me onions and garlic.

1016
01:03:36,640 --> 01:03:40,000
Speaker 1: Here's what I think you really onions and garlics. Yes, yeah,

1017
01:03:40,040 --> 01:03:44,960
Speaker 1: that's everything Bagel, everything baby. I was just thinking like salty.

1018
01:03:45,000 --> 01:03:47,040
Speaker 1: I mean, I love everything bagels and I like a

1019
01:03:47,080 --> 01:03:52,080
Speaker 1: salty sweet thing. But I'm blaming this entirely on the

1020
01:03:52,080 --> 01:03:55,560
Speaker 1: Trader Joe's Everything Bagel seasoning that came out like last

1021
01:03:55,680 --> 01:03:57,640
Speaker 1: year where they put all that stuff in a shaker

1022
01:03:57,720 --> 01:03:59,600
Speaker 1: so you could just put it on stuff, and then

1023
01:03:59,640 --> 01:04:01,880
Speaker 1: in your Trader Juice fashion. They started just making a

1024
01:04:01,880 --> 01:04:05,440
Speaker 1: lot of other products that have that Everything Babel Bagel

1025
01:04:05,440 --> 01:04:08,440
Speaker 1: seasoning on it. So I think kind of the idea

1026
01:04:08,520 --> 01:04:10,760
Speaker 1: of everything Bagel. There's also just kind of like a

1027
01:04:10,760 --> 01:04:14,360
Speaker 1: bagel boom going on for Hope, They're You're late to

1028
01:04:14,440 --> 01:04:18,960
Speaker 1: the party. All there's been no bagel boom. There's I've

1029
01:04:19,000 --> 01:04:21,880
Speaker 1: been I've been down with the bagel boom since the eighties.

1030
01:04:22,880 --> 01:04:25,600
Speaker 1: There's that. I just feel like anytime you make a

1031
01:04:25,640 --> 01:04:29,320
Speaker 1: savory ice cream flavor, you're dancing with the devil. Did

1032
01:04:29,320 --> 01:04:32,720
Speaker 1: you ever go to a Stinking Rose the garlic restaurant? Yeah?

1033
01:04:32,760 --> 01:04:35,400
Speaker 1: But I did not get the garlic. Okay, so I've

1034
01:04:35,440 --> 01:04:38,600
Speaker 1: had garlic ice cream before, and garlic ice cream isn't bad.

1035
01:04:38,800 --> 01:04:41,320
Speaker 1: You know, It's not like something I go, oh, fuck,

1036
01:04:42,240 --> 01:04:44,640
Speaker 1: get the garlic ice cream because it's going up tonight.

1037
01:04:44,880 --> 01:04:47,120
Speaker 1: But it's one of those things you eat and you're like, damn,

1038
01:04:47,200 --> 01:04:50,560
Speaker 1: I'm actually more interested because it's not bad, Like I

1039
01:04:50,640 --> 01:04:53,280
Speaker 1: honestly think there are Yeah, I mean, like if they

1040
01:04:53,360 --> 01:04:56,560
Speaker 1: didn't call it ice cream, I think that's the key.

1041
01:04:56,600 --> 01:04:58,640
Speaker 1: I think if you made like a like I thought,

1042
01:04:58,680 --> 01:05:00,360
Speaker 1: I think about this always in the sun, or like

1043
01:05:00,840 --> 01:05:07,160
Speaker 1: soup popsicles, like a gaspacho popsicle and like a tomato

1044
01:05:07,280 --> 01:05:10,600
Speaker 1: soup popsicle. Maybe not a clam chowder popsicle, but just

1045
01:05:10,720 --> 01:05:13,560
Speaker 1: things like that, just thinking about it. But I think

1046
01:05:13,560 --> 01:05:17,800
Speaker 1: you have you gotta call it like a granita or something.

1047
01:05:17,840 --> 01:05:20,280
Speaker 1: If you call it an ice cream, like, people's minds

1048
01:05:20,360 --> 01:05:23,160
Speaker 1: go to sweet, and I feel like most of the

1049
01:05:23,160 --> 01:05:26,080
Speaker 1: time when people try to do savory, I don't really

1050
01:05:26,120 --> 01:05:28,360
Speaker 1: funk with all those artisanal ice creams that have like

1051
01:05:28,520 --> 01:05:31,320
Speaker 1: fucking like duck skin in them or whatever. You know,

1052
01:05:31,560 --> 01:05:34,600
Speaker 1: there's been a lot of that lately. Wait, there was

1053
01:05:36,600 --> 01:05:39,960
Speaker 1: like salt and straw all they're weird as you know,

1054
01:05:40,280 --> 01:05:42,320
Speaker 1: things where it's like a thing you wouldn't expect an

1055
01:05:42,360 --> 01:05:46,000
Speaker 1: ice cream that's an ice cream. And there's a place,

1056
01:05:46,640 --> 01:05:49,880
Speaker 1: there's a place in Philadelphia called Little Babies that did

1057
01:05:49,920 --> 01:05:54,840
Speaker 1: a pizza ice cream. No, thank you? Right, Like I

1058
01:05:54,840 --> 01:05:58,440
Speaker 1: don't want that. I respect it's right to exist, but like, okay,

1059
01:05:58,680 --> 01:06:00,880
Speaker 1: so it's one of those things the idea you say

1060
01:06:00,920 --> 01:06:02,960
Speaker 1: no to, just like I would say no to everything

1061
01:06:03,000 --> 01:06:06,240
Speaker 1: bagel ice cream. No, don't need it. But we all

1062
01:06:06,280 --> 01:06:08,640
Speaker 1: have this morbid fascination to try. You would you not

1063
01:06:08,800 --> 01:06:11,680
Speaker 1: try this pizza ice cream? Jack, I'll try anything. Okay,

1064
01:06:11,720 --> 01:06:14,680
Speaker 1: we'll try anything for free, right right? All right? Then

1065
01:06:14,680 --> 01:06:16,320
Speaker 1: maybe what we'll do is we can all go in

1066
01:06:17,000 --> 01:06:19,360
Speaker 1: a couple of bucks. Maybe we'll have zeit gang because

1067
01:06:19,360 --> 01:06:22,120
Speaker 1: it's expensive. If every if the listeners and all of

1068
01:06:22,200 --> 01:06:23,720
Speaker 1: us put in a dollar, we might be able to

1069
01:06:23,720 --> 01:06:27,960
Speaker 1: afford one of these points, one of the everything bagel points. Yeah, alright,

1070
01:06:28,000 --> 01:06:30,120
Speaker 1: did you wait? This is like related, But did you

1071
01:06:30,120 --> 01:06:33,280
Speaker 1: guys see the mac and cheese, the pink mac? And yeah,

1072
01:06:34,080 --> 01:06:37,200
Speaker 1: it made me hate mac and cheese more. By the

1073
01:06:37,280 --> 01:06:39,520
Speaker 1: end of talking about it, I was like craft has

1074
01:06:39,600 --> 01:06:42,320
Speaker 1: lost its way and it's like the Q and on on.

1075
01:06:42,520 --> 01:06:44,520
Speaker 1: You're like, I gotta put you to bed now. I

1076
01:06:44,600 --> 01:06:46,920
Speaker 1: just set like you could make it pink without making

1077
01:06:46,920 --> 01:06:51,840
Speaker 1: it sweet and cheese. But then I'm like, isn't it

1078
01:06:51,920 --> 01:06:55,920
Speaker 1: maybe sweet mac and cheese is just coogle? Oh yeah,

1079
01:06:56,160 --> 01:06:57,960
Speaker 1: a little bit. I think again, it's like you just

1080
01:06:58,000 --> 01:07:00,200
Speaker 1: have to have different words for these things. You could

1081
01:07:00,280 --> 01:07:03,160
Speaker 1: talk somebody into a sweet pasta. You just have to

1082
01:07:03,200 --> 01:07:05,840
Speaker 1: not call it Kraft mac and cheese but it's sweet

1083
01:07:05,880 --> 01:07:10,040
Speaker 1: because then your mind just reels. Yeah, I guess coogle

1084
01:07:10,080 --> 01:07:11,920
Speaker 1: would have been better, because now that you say that,

1085
01:07:11,960 --> 01:07:14,600
Speaker 1: I'll be like, well, yeah, okay, because I'm pro like

1086
01:07:14,680 --> 01:07:18,360
Speaker 1: dessert pizza. I'm pro a pizza ki. Well, yeah, I

1087
01:07:18,360 --> 01:07:22,120
Speaker 1: mean pizzuki is like not mixing flavors. It's just like

1088
01:07:22,200 --> 01:07:26,520
Speaker 1: taking the concept of pizza shapes and putting desserts in

1089
01:07:26,560 --> 01:07:29,560
Speaker 1: the shape of pizza. Like, I'm all about that, but

1090
01:07:29,680 --> 01:07:34,680
Speaker 1: like trying to make the base of the dessert actual pasta.

1091
01:07:35,480 --> 01:07:40,200
Speaker 1: I cannot abide it be J that you say that

1092
01:07:40,200 --> 01:07:43,160
Speaker 1: that's one of those restaurants like in my late teens

1093
01:07:43,480 --> 01:07:45,920
Speaker 1: that you're like, yeah, we're going to be J's Brewery

1094
01:07:45,960 --> 01:07:47,960
Speaker 1: with our fake I d s funk out of here.

1095
01:07:48,240 --> 01:07:50,280
Speaker 1: And then you're like, we don't have We shouldn't really,

1096
01:07:50,320 --> 01:07:56,440
Speaker 1: we can't really afford to drink in public. No, you

1097
01:07:56,480 --> 01:08:00,800
Speaker 1: can't afford the prices that any of those arcades. Those

1098
01:08:00,800 --> 01:08:05,959
Speaker 1: are for barcades. The barcade scene in l a Is despicable.

1099
01:08:07,240 --> 01:08:10,680
Speaker 1: I'm like, what y'all are charging so much money for

1100
01:08:10,720 --> 01:08:13,720
Speaker 1: these games? Like, no, have you been to that one

1101
01:08:13,720 --> 01:08:17,080
Speaker 1: spot in Hollywood that's like the pizza nineties pizza arcade

1102
01:08:17,240 --> 01:08:19,719
Speaker 1: in the before Now, I haven't been in there. Yeah,

1103
01:08:19,800 --> 01:08:23,240
Speaker 1: the pizza was okay, and the you know, they were

1104
01:08:23,240 --> 01:08:25,640
Speaker 1: they were going for an aggressive nineties aesthetic that just

1105
01:08:25,680 --> 01:08:28,200
Speaker 1: felt a little ham fisted for me. It feels ham fisted.

1106
01:08:28,240 --> 01:08:30,679
Speaker 1: But then there was also that one in like down

1107
01:08:30,680 --> 01:08:34,639
Speaker 1: by Dodger Stadium. Yeah, yeah, yeah that I was like, oh,

1108
01:08:34,720 --> 01:08:36,960
Speaker 1: this is so stupid. And then I was like, oh no,

1109
01:08:37,040 --> 01:08:40,599
Speaker 1: they like exactly got all the games, but they got

1110
01:08:40,800 --> 01:08:43,479
Speaker 1: It's like it wasn't eighties games. It was like late

1111
01:08:43,520 --> 01:08:46,599
Speaker 1: eighties early nineties games, so it was like arcade games

1112
01:08:46,640 --> 01:08:49,760
Speaker 1: like you we all played at the Hut, and I

1113
01:08:49,880 --> 01:08:54,160
Speaker 1: was like, it got me. I think Button Mash is

1114
01:08:54,160 --> 01:08:56,880
Speaker 1: still in business too, Maybe I mean, I can't imagine.

1115
01:08:56,880 --> 01:09:01,040
Speaker 1: The barcade business is like very uh popping right now.

1116
01:09:01,080 --> 01:09:05,479
Speaker 1: There's one in Echo Park that closed. I'm sure stuff

1117
01:09:06,000 --> 01:09:08,800
Speaker 1: for me. I did all the experimenting I needed this

1118
01:09:08,880 --> 01:09:12,439
Speaker 1: week when I got a peanut Reese's Peanut butter big

1119
01:09:12,479 --> 01:09:17,479
Speaker 1: cup with chunks of pretzel inside. The chips one, oh chips,

1120
01:09:17,640 --> 01:09:20,680
Speaker 1: I don't know which chips the pretzel one as good

1121
01:09:20,680 --> 01:09:25,120
Speaker 1: as Oh my god. Her majesty steals them from set

1122
01:09:25,520 --> 01:09:28,720
Speaker 1: and brings them here Like any good person, if you

1123
01:09:28,720 --> 01:09:30,880
Speaker 1: have a partner who works in production, they better be

1124
01:09:30,920 --> 01:09:33,680
Speaker 1: stealing from rafty for you and bringing it home. But

1125
01:09:34,200 --> 01:09:35,840
Speaker 1: she came home with him, and she's like, you'll never

1126
01:09:35,960 --> 01:09:39,400
Speaker 1: guess what's happened. I don't know what the you got

1127
01:09:39,479 --> 01:09:42,439
Speaker 1: a promotion? And she like I hadn't seen them. But

1128
01:09:42,479 --> 01:09:47,519
Speaker 1: the chip one is fucking potato. Yeah I will. I

1129
01:09:47,560 --> 01:09:50,640
Speaker 1: will funk with some potato chips in there as like

1130
01:09:50,720 --> 01:09:57,160
Speaker 1: a you know, a salty accent. I might. I might

1131
01:09:57,240 --> 01:10:00,040
Speaker 1: do this Everything Bagel ice cream, you gotta do it.

1132
01:10:00,080 --> 01:10:04,439
Speaker 1: I want it doesn't especially because it doesn't have locks

1133
01:10:04,479 --> 01:10:06,200
Speaker 1: in it like it it sounds like it might not

1134
01:10:06,320 --> 01:10:08,840
Speaker 1: even be that crazy, like it'll taste like a like

1135
01:10:08,880 --> 01:10:12,200
Speaker 1: a cheesecake ice cream probably right. The closest thing they

1136
01:10:12,240 --> 01:10:14,880
Speaker 1: say is like if you've had a garlic ice cream

1137
01:10:14,960 --> 01:10:18,000
Speaker 1: that was good or it's just like it's subtle. It's there,

1138
01:10:18,360 --> 01:10:22,760
Speaker 1: but you're not like, what's like a frozen you know

1139
01:10:22,760 --> 01:10:26,040
Speaker 1: what I mean? Like apparently has but I would do

1140
01:10:26,200 --> 01:10:29,280
Speaker 1: like you know, I would do a sour cream ice cream.

1141
01:10:29,479 --> 01:10:33,000
Speaker 1: There there are other you know, there's like a really

1142
01:10:33,040 --> 01:10:38,200
Speaker 1: good avocado ice cream, the Filipino ice cream, things that

1143
01:10:38,240 --> 01:10:40,840
Speaker 1: you might not necessarily consider for ice cream. Then you

1144
01:10:40,920 --> 01:10:43,760
Speaker 1: have it in ice cream and you're like, actually this

1145
01:10:43,920 --> 01:10:48,400
Speaker 1: kind of makes sense. There's only find out all right,

1146
01:10:48,560 --> 01:10:53,320
Speaker 1: let's finally dig into some wholesomeness. Uh that still has

1147
01:10:53,400 --> 01:10:58,360
Speaker 1: like a depressing news peg. So there's this guy, I

1148
01:10:58,400 --> 01:11:00,479
Speaker 1: don't know, did you guys know about cat Done, Sir

1149
01:11:00,640 --> 01:11:06,280
Speaker 1: Tom Moore? No? Okay, So he is a He was

1150
01:11:06,320 --> 01:11:09,320
Speaker 1: a nine year old man who was about to turn

1151
01:11:09,400 --> 01:11:14,479
Speaker 1: one hundred and decided to raise funds for the NHS

1152
01:11:14,600 --> 01:11:20,000
Speaker 1: uh by trying to walk a hundred laps in his

1153
01:11:20,120 --> 01:11:25,880
Speaker 1: garden before his hundredth birthday. Uh and just be like

1154
01:11:26,560 --> 01:11:28,839
Speaker 1: people just really liked him. He's just like a charming

1155
01:11:28,840 --> 01:11:32,360
Speaker 1: ass old man to the point that he ended up

1156
01:11:32,720 --> 01:11:36,360
Speaker 1: like collabing with a famous pop star on a song

1157
01:11:36,439 --> 01:11:41,000
Speaker 1: that went to number one in the UK. Really yeah,

1158
01:11:42,000 --> 01:11:45,479
Speaker 1: and he raised thirty five million pounds for the NHS,

1159
01:11:45,600 --> 01:11:49,439
Speaker 1: which is like incredible. Um, everybody loved him. He then

1160
01:11:49,479 --> 01:11:57,160
Speaker 1: got knighted. Uh and um he just passed away from COVID,

1161
01:11:57,600 --> 01:12:01,400
Speaker 1: which is not you like a little old man mustache

1162
01:12:01,640 --> 01:12:05,080
Speaker 1: this guy. Yeah, this is gonna be Anthony hopkins greatest

1163
01:12:05,200 --> 01:12:10,880
Speaker 1: role it really yeah, because like that ending the third act,

1164
01:12:11,160 --> 01:12:17,719
Speaker 1: you know you've got coronavirus love. I think it's bollocks

1165
01:12:18,520 --> 01:12:24,280
Speaker 1: what I bet he had. He's this whole star. I'm like,

1166
01:12:25,040 --> 01:12:26,840
Speaker 1: even if they make it up, this guy has some

1167
01:12:27,000 --> 01:12:32,800
Speaker 1: profound last words. Everyone's going to be sobbing. Yeah. He's

1168
01:12:32,800 --> 01:12:36,519
Speaker 1: spent his final hours with his kids, like reminiscing about

1169
01:12:36,560 --> 01:12:41,560
Speaker 1: their mom who passed away, and uh yeah, just seems

1170
01:12:42,080 --> 01:12:47,640
Speaker 1: generally like an awesome dude. Uns are from from all

1171
01:12:47,720 --> 01:12:50,599
Speaker 1: the other stories. Yeah, shout out to him, shout out

1172
01:12:50,640 --> 01:12:59,439
Speaker 1: to something. Uh to believe in? That's a that's that

1173
01:12:59,520 --> 01:13:01,800
Speaker 1: really speak to where we're at. Where are like new

1174
01:13:01,880 --> 01:13:06,240
Speaker 1: thing to believe in is a recently deceased, very old man. Yeah,

1175
01:13:06,640 --> 01:13:09,800
Speaker 1: ocially this is a winner your British army man. Yeah,

1176
01:13:10,400 --> 01:13:15,040
Speaker 1: all right, that's gonna do it for this week's weekly Zeite. Guys,

1177
01:13:15,160 --> 01:13:18,960
Speaker 1: please like and review the show. If you like the show,

1178
01:13:19,600 --> 01:13:24,000
Speaker 1: uh means the world to Miles. He needs your validation. Folks.

1179
01:13:24,600 --> 01:13:27,639
Speaker 1: I hope you're having a great weekend and I will

1180
01:13:27,680 --> 01:14:16,519
Speaker 1: talk to you Monday. By Dat