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Speaker 1: Hello the Internet, and welcome to Season one, thirty two,

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Speaker 1: Episode three of TAR Daily. See guys to production of

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Speaker 1: I Heart Radio. This is a podcast where we take

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Speaker 1: a deep dive into America's share consciousness and say, officially,

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Speaker 1: off the top, fuck the Cooke Brothers. I am, Fuck

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Speaker 1: Fox News. It's Wedness Day, May six. My name's Jack O'Brien,

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Speaker 1: a K in the town where I was born Linda

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Speaker 1: Mano quarantined, and he told us of his life in

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Speaker 1: the time of COVID nineteen at his courtesy of Rich Jefferson,

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Speaker 1: and I'm thrilled to be joined as always by my

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Speaker 1: co host, Mr Miles Grab fuck my life? Is this

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Speaker 1: genius trying to end this Core starts spending Danner much sooner,

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Speaker 1: don't give a funk on the Sheero, White, Boomer and Noice,

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Speaker 1: And we're back from a technical glitch. Miles just rocked

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Speaker 1: that a K so fucking hard that the H six

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Speaker 1: started not just buzzing in his headphones and started buzzing

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Speaker 1: like it was just like what the fun see And

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Speaker 1: it happened again because this technology is so unpredictable. So

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Speaker 1: uh yeah, I was gonna say Taylor Fleming inspired that

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Speaker 1: AK to do a Papa Roach one, and then I

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Speaker 1: just had to just something the lyrics for calling me

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Speaker 1: in a different direction. Yeah, I should have probably just

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Speaker 1: took his a K as written. See I learned my lesson. Yeah,

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Speaker 1: uh well Worth thrilled to be joined Dana third seat

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Speaker 1: by our choir co host Little Zam herself Jamie Lofter. Hey, Jamie,

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Speaker 1: I hear the zoom called go in with Miles and

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Speaker 1: Jacob Zeke guys, and he'll talk the devil too. Yeah

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Speaker 1: maybe on an a but you all know what to

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Speaker 1: do with those hot topics and Twitter treads. You're sing again?

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Speaker 1: Do do? Thank you? Okay, that's from Jeff Chriscope. I

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Speaker 1: got five versions of this, and I think everyone who

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Speaker 1: wrote me a version of the Fraser a k A

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Speaker 1: that I requested um and also to everyone who was

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Speaker 1: my I got a couple of different menchis being like, Jamie,

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Speaker 1: don't you know that Kelsey Grammar has bad politics? Like, yeah,

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Speaker 1: I've seen him. Of course he has bad, doesn't My

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Speaker 1: favorite bad thing about Kelsey Grammar is that he broke

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Speaker 1: up with his wife on the phone. No like earlier

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Speaker 1: and earlier I think so? Or was it? So he's

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Speaker 1: just like snile of broken women behind him. Basically, yeah,

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Speaker 1: he's a bad man, but Fraser is a good show.

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Speaker 1: Experiencing the Camille breakup through Beverly Hills Real Housewives of

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Speaker 1: Beverly Hills was it was very like he just went

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Speaker 1: to do a show in New York and like stopped

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Speaker 1: talking to her essentially. And then maybe it was Camille

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Speaker 1: that he broke up with over the phone. Maybe she

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Speaker 1: would have been lucky to get a phone break up

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Speaker 1: and he she just didn't get a phone a break

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Speaker 1: up at all. He just like stopped talking to her.

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Speaker 1: The Galaxy Brain, the Galaxy Brain take care is that

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Speaker 1: we uh stand David Hyde, Pierce and Kelsey Grammer is

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Speaker 1: an unfortunate accessory to the whole Fraser operation. Of course.

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Speaker 1: Of course, Well, we are thrilled to be joined in

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Speaker 1: our fourth seat by first time guest, the hilarious Ben

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Speaker 1: she Han. I am so thrilled that just started off

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Speaker 1: with Papa Rich parodies, and I can only imagine that

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Speaker 1: puddle of mud. He's really disappointed to have been left

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Speaker 1: out of them. They'll get there, they'll get there. I

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Speaker 1: don't know, Yeah, I don't know that. I know you're right.

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Speaker 1: We don't know, Ben, how are you Doing're doing okay?

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Speaker 1: You know, going on week I don't know seven eight

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Speaker 1: of quarantine and uh what are we sick of everything?

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Speaker 1: We're eating? Pretty much? Is I think where everyone is? Yeah,

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Speaker 1: I don't count eight, it's probably close. Let's see one

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Speaker 1: to three, four, five, six, seven, eight, yep, five six.

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Speaker 1: I'm going full out on this core now. That's uh, yeah,

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Speaker 1: I would have had no idea. I got I that.

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Speaker 1: That's good to know, though. Are you just eating kind

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Speaker 1: of the same thing? Is that why you're saying you're

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Speaker 1: kind of getting into the like boredom of the food?

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Speaker 1: What's going on? Said that? First? I know, well, look,

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Speaker 1: I'm saying that, you know, I may have a limited

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Speaker 1: range of things that that I can make, and you know,

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Speaker 1: you're going to the same store over and over. You're

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Speaker 1: kind of fall into your your routine, and I think

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Speaker 1: it's on me. It's really really this is me talking

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Speaker 1: to myself. It's my responsibility to either expand the grocery

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Speaker 1: stores or to expand my slate of things to to make.

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Speaker 1: What do you, I mean, give me an idea? What's

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Speaker 1: your thing? What are you making? Over and over that?

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Speaker 1: So I'm I'm saying I'm making this, but really this

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Speaker 1: my my girlfriend is a very very skilled chef and

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Speaker 1: she makes way better food than I do. So this

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Speaker 1: is this is me talking to myself and my shortcomings.

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Speaker 1: I'm reminded of every day. Um really big on you know,

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Speaker 1: the uh, the right mix of additions to a smoothie.

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Speaker 1: You've got your frozen fruit, but it's like adding a

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Speaker 1: little bit of gender, adding a little bit of honey,

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Speaker 1: adding a little bit of the right powder something to

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Speaker 1: kind of spice it up a little bit. And this

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Speaker 1: is like some high level stuff. I don't even more

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Speaker 1: power to you A powder. I can't even know powder.

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Speaker 1: A little um there is is that guy? Is that

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Speaker 1: the green one? I don't know. Just some people I

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Speaker 1: know who live in to Panga Panga Canyon talk about

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Speaker 1: we got some random like mushroom powder in the mail,

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Speaker 1: and that I don't really I mean not like like

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Speaker 1: just sort of like a regular dietary supplement powder. And

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Speaker 1: I'm not entirely sure it does anything, but you know,

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Speaker 1: we're experimenting with it where it goes, Yeah, experimenting with mushrooms.

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Speaker 1: And it's a great time to do that during core.

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Speaker 1: And are you publicly dating Jackie. I am publicly dating,

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Speaker 1: so we can mention that his past guest double j

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Speaker 1: first first actually got me handwashing much better the last

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Speaker 1: time she was on the show, because I think her

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Speaker 1: myth was about hand washing, about how long you have,

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Speaker 1: and that was months before, so in a way, oh

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Speaker 1: her my life. I mean, maybe she started this whole

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Speaker 1: thing just so that she could be right about be

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Speaker 1: right about that wouldn't put a pastor Jackie Michelle. All Right, well, Ben,

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Speaker 1: we're gonna get to know you a little bit better

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Speaker 1: in a moment. First, we're gonna tell our listeners what

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Speaker 1: we're talking about today. We're talking about the new spawn

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Speaker 1: of Grimes and her boyfriend. Uh yeah, I don't I

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Speaker 1: don't know how we're pronouncing the name. It's it's it's Joey. Yeah.

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Speaker 1: Is it Joey's Anthony? I think, Oh god, I hope

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Speaker 1: it's Anthony. We're gonna talk about that. We're gonna talk

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Speaker 1: about giant killer hornets. Uh. We're gonna talk about Trump

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Speaker 1: saying we're we're safe to work, ak saying working people

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Speaker 1: are expendable. We're gonna talk about skin hunger, hunger for

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Speaker 1: human skin. Uh, it's delicious and crispy when prepared correctly.

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Speaker 1: We're gonna talk about, uh, what recipes people are searching,

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Speaker 1: Wendy's being out of Meat and demolition Man J M McNabb,

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Speaker 1: a writer, rewatched it for us so we wouldn't have to,

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Speaker 1: and apparently it's kind of a eerie rewatch right now.

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Speaker 1: But first, Ben, we like to ask our guests, what

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Speaker 1: is something from your search history that is revealing about

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Speaker 1: who you are? Uh? My most recent Google search history

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Speaker 1: is John Radcliffe, who is the new nominee to head

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Speaker 1: all of Trump's intelligence, And they just found out that

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Speaker 1: he follows a whole bunch of conspiracy accounts on Twitter

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Speaker 1: like Q and on and ship even where he's like

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Speaker 1: one of two followers. Uh so he likes to follow

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Speaker 1: bots and he's gonna run our intelligence enthusiasts botanist. Yeah,

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Speaker 1: now that the world is teetering on the brink of

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Speaker 1: just all out societal breakdown, let's let's bring in the

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Speaker 1: guy believes in Q. Well, that's what you need, I think,

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Speaker 1: you know, for to work for the president is you

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Speaker 1: have to be able to reject reality just in the

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Speaker 1: blink of an eye. So, like I think that's now

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Speaker 1: the only prerequisite to work in the White House, Like

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Speaker 1: how willing are you to like shape shift in your

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Speaker 1: mind to adapt to whatever narrative, Like you need to

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Speaker 1: be true for your ego. Now, it's like I kind

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Speaker 1: of feel like Q would have been a better name

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Speaker 1: for the musk baby, Q mus m qumus if Q musk.

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Speaker 1: That's fun And isn't that The meanest thing a parent

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Speaker 1: can do to their child is like name them upon Yeah,

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Speaker 1: I knew I can name justin case when I was

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Speaker 1: in elementary school. That's so, did you really? Yeah? Justin

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Speaker 1: C A, I S S E. There was there was

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Speaker 1: a kid at my summer camp whose name His name

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Speaker 1: was Harley Davidson, but his dad's name was David Davidson,

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Speaker 1: and so he could say that he is also Harley

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Speaker 1: David's son. Whoa. And it was like this three level

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Speaker 1: thing where I was like, I don't know why you

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Speaker 1: introduce yourself like this, bro, I'm just trying to get

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Speaker 1: some fucking cream of wheat in. This guy he like

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Speaker 1: gave you the dissertation. When you're like, hey, Miles, it

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Speaker 1: was like, okay, well here's what you got. Understand. It

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Speaker 1: was a kid, It was a kid in his bunk.

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Speaker 1: It was like that thing where like I only knew

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Speaker 1: one other kid at this camp, and I was like, Hey,

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Speaker 1: what's going on? And You're like, are they weird too?

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Speaker 1: And he's like, there's this kid named Harley Davidson, but

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Speaker 1: he's David's and like he was saying it to me

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Speaker 1: as if that was the thing he shared when like

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Speaker 1: all everyone's meeting each other the first night, I was

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Speaker 1: gonna say, if that's your life, you never need to

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Speaker 1: develop a personality. Really, just say that, Just say that

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Speaker 1: everything your name. Yeah. Yeah, it's like being tall, you

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Speaker 1: never have to develop a personality. Yeah, uh fuck you

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Speaker 1: tall people? Uh Ben, what is what is? Uh? Something

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Speaker 1: you think is underrated? I think underrated is knowing how

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Speaker 1: the government works. Civics education is wildly underrated. And that's

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Speaker 1: kind of something important to you. It's something very important

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Speaker 1: to people. A couple last week this They do this

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Speaker 1: um evaluation, the study the Department of Education every four

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Speaker 1: years and they basically test all the eighth graders in

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Speaker 1: the country to see how good they are different subjects,

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Speaker 1: and for twenty years running, eighth graders only less than

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Speaker 1: a quarter of them are proficient in civics, So over

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Speaker 1: the course of the last twenty years have been consistently

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Speaker 1: proficient in civics. So think of all the people who

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Speaker 1: are now of the vote of voting age who don't

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Speaker 1: understand how the government works. And that's a lot of people.

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Speaker 1: It's almost like it's by design or something. Then you

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Speaker 1: don't know how to properly ascertain or diagnose a problem

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Speaker 1: within the guy, I don't know, whatever should be on

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Speaker 1: some weird ship something we gotta make. You're kind of

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Speaker 1: right on the money. Actually, I mean, we used to

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Speaker 1: have these classes in the six and the fifties and sixties.

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Speaker 1: People took classes like foundations of the Democracy and civics

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Speaker 1: and American government. And then there are all these protests

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Speaker 1: and they led to the Civil Rights Act and the

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Speaker 1: Voting Rights Act and the twenty six Amendment allowing eighteen

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Speaker 1: year olds to vote after the Vietnam War, and then

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Speaker 1: I think people were like too much, so we cut

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Speaker 1: it back and now we don't have those classes anymore. Yeah.

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Speaker 1: Now it's just like a history class that's full of

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Speaker 1: bad info. Yeah, yeah, textbooks written by friends of the board.

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Speaker 1: Exactly do you think it is? Actually? Like, have people

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Speaker 1: looked into that is, was there an actual like by

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Speaker 1: design we shift money away from education. I'm sure, I'm

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Speaker 1: sure it's hard to like trace that back, but it's

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Speaker 1: hard to trace that back, but there is there is

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Speaker 1: this sort of I've been researching it a lot. I

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Speaker 1: can't find a direct cause in terms of like why

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Speaker 1: after the nineteen sixties stopped teaching this or how quickly,

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Speaker 1: but specifically in the last ten years there have been

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Speaker 1: a couple of really shitty policies that made it fall

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Speaker 1: even further down in terms of like priorities. So in

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Speaker 1: two thousand two, No Child Left Behind basically gave all

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Speaker 1: this money to states, if they know, increased scores in

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Speaker 1: math and reading and so all these other subjects became

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Speaker 1: less of a priority. And then common Core in basically

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Speaker 1: the same deal. So today only eight states require a

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Speaker 1: year of government or civic's education at some point between

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Speaker 1: kindergarten and twelfth grade. So you have been researching all

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Speaker 1: this stuff because you knew you were coming on daily.

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Speaker 1: Um No, I mean this is something that's there's a

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Speaker 1: passion of mine and it's kind of tied into the

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Speaker 1: work I've been doing. But I think this is something

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Speaker 1: you know when when you're in the middle of a

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Speaker 1: pandemic and you're like, who the funk has the power

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Speaker 1: to do what? You're helpful to know? You know where

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Speaker 1: I can put pressure onto get what I want. You know,

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Speaker 1: it's sort of feel it does feel like it's by

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Speaker 1: design that we that we don't know this stuff right absolutely.

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Speaker 1: I mean, I think the the one way you just

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Speaker 1: look at how the education has been defunded as you

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Speaker 1: just look at the budgets everywhere every year and you say, okay,

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Speaker 1: it got slashed this year and what got an increase

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Speaker 1: and you can start to see, like I mean, that's

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Speaker 1: like the only sort of raw way to look at

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Speaker 1: it every year to see, like, you know, one of

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Speaker 1: the last budgets Divas and Trump are proposings like slash

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Speaker 1: education like seven billion or some ship. And also having

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Speaker 1: somebody who wants to do who is the head of

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Speaker 1: a department that they don't want to exist, Like like

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Speaker 1: having somebody running the Department of Education who doesn't want

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Speaker 1: that department to exist is you know a pretty big signment.

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Speaker 1: It's like, yeah, so in charge of the d A

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Speaker 1: is now scarface and you're like what um? And you

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Speaker 1: have a book about this right then that you just published.

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Speaker 1: I do. Yeah, it's called oh my god, what the

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Speaker 1: fund does the Constitution actually say? And it's basically a

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Speaker 1: normal sort of language tone translation, paraphrase of the Constitution

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Speaker 1: so that we don't all have to pass through this

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Speaker 1: weird old English that's hard to understand and we can

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Speaker 1: just get the underlying information and sort of a normal,

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Speaker 1: you know, direct tone. Right. And are you do you

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Speaker 1: tackle like, are you going to finally tell me like

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Speaker 1: how I can tell a cop to funk off because

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Speaker 1: I'm a sovereign citizen. I mean yeah there, I mean yes, absolutely. Uh.

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Speaker 1: You know, basically that's the whole idea of the Fourth Amendment,

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Speaker 1: is that ship like stopping frisk and and you know,

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Speaker 1: you have to have a quote unquote reasonable idea. I

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Speaker 1: mean it's been really interesting to see, you know, Bloomberg

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Speaker 1: and the idea that you wouldn't get any pushback for

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Speaker 1: something that is clearly unconstitutional. Um. I mean there are

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Speaker 1: all these rights that we we need to know, um,

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Speaker 1: that we don't necessarily know, and that are constantly taking

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Speaker 1: advantage of in many ways. So yes, the answer rights

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Speaker 1: that we don't know are being violated, and we're brought

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Speaker 1: up in a system that tells us about our rights

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Speaker 1: only one year through the whole process. Typically it's the

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Speaker 1: very last year where you could give a funk about

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Speaker 1: anything anyone's telling you. Because I feel like most people

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Speaker 1: get like their hearts, like their government class or whatever.

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Speaker 1: A senior year of high school, or at least in

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Speaker 1: California it was like that. So yeah, yeah, I took

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Speaker 1: I didn't get I had AP government and but the

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Speaker 1: Civics class was like very relaxed. Oh let me tell something.

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Speaker 1: Did not pass that AP test. You want to know why,

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Speaker 1: because I'm senior year and I don't give a funk anymore.

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Speaker 1: So half the time I was I was literally getting

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Speaker 1: kicked out of my AP government class for farting too much,

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Speaker 1: like out loud and disrupting the class. That's where my

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Speaker 1: head was when they're telling me about, you know, inalienable rights.

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Speaker 1: And I took the only history well, I took like

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Speaker 1: a history class every year, but I did like the

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Speaker 1: IB classes where you just yeah, where they teach you

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Speaker 1: about your butt. Uh. I took like a two year

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Speaker 1: class on like the history of Russian communism, and then

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Speaker 1: I never learned what happened to quote unquote past the

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Speaker 1: Civil War in the US. I got some big old

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Speaker 1: blind spots. Yeah, they didn't even tell us what happened

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Speaker 1: in the Civil War, Clipper who won? I gotta be honest,

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Speaker 1: I don't know how the Civil War ended. It's not

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Speaker 1: over man, right, And you're like, and based on what

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Speaker 1: I'm seeing now, I think the South one. Yeah, there

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Speaker 1: are so many studies that are terrifying because there are they.

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Speaker 1: I mean, we joke about this, but there are thousands

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Speaker 1: upon thousands of students today who who think that, like

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Speaker 1: the outcome is way different than it actually was, or

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Speaker 1: couldn't even tell you who won the Civil War. I

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Speaker 1: mean these textbooks, I have no idea what the funk

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Speaker 1: is being distributed throughout those is about the economy. Yeah,

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Speaker 1: it was just an economic disagreement, um, and a war

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Speaker 1: of Northern aggression at Miles. I love that you had

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Speaker 1: a moment in school where your two different career paths

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Speaker 1: met in class, and like it was a government class

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Speaker 1: and you went into government immediately after school and then

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Speaker 1: you got kicked doubt for farting, which is hilarious, and

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Speaker 1: you did leave government to go into comedy. So interesting. Uh,

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Speaker 1: that's why I bring these truths to you, Jack, so

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Speaker 1: you can help me parse through them. Um, what is

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Speaker 1: something you think is overrated? National polls for president? They don't,

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Speaker 1: they don't, and yet I'm addicted to them. We are.

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Speaker 1: Why don't they matter? Because we don't vote nationally for president.

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Speaker 1: We vote with our states. So it's great that, you know,

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Speaker 1: somebody gets the highest percentage in a national poll, but

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Speaker 1: it's not of any bearing really on how we vote.

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Speaker 1: And I think it's just media companies wanting to addict

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Speaker 1: people to like a horse race and being, oh, this

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Speaker 1: person news ten points ahead up, now they're down four point.

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Speaker 1: I mean, it's just basically a way to get us

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Speaker 1: to pay attention to, you know, shipped to sell ads.

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Speaker 1: And I think that we should just scrap all national

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Speaker 1: polls for president and pay attention to state specific polls

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Speaker 1: because I think that would be more hopeful. Yeah, the

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Speaker 1: yeah post still love to uh send myself on a

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Speaker 1: downwards stress and depression spiral by watching Trump's approval rating

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Speaker 1: stayed stable dur as he completely just destroys our country.

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Speaker 1: But yeah, well that's just how I like to burn

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Speaker 1: my calories that. But those like public opinion political research

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Speaker 1: strategy firms that you know, get tons of money from everybody,

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Speaker 1: from you know, the parties themselves to lobbyists and industries.

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Speaker 1: Like it's such a fucking racket that Like when I

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Speaker 1: like there when I used to work in politics, like

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Speaker 1: I've I saw like one of the you know, pretty

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Speaker 1: significant posters for the for the Democratic Party like at work,

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Speaker 1: and I was like, how much are we paying for this?

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Speaker 1: Because like I mean like that our clients were like

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Speaker 1: wanted to use this person, and I was like trying

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Speaker 1: to doing the math. I'm like, this is the most

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Speaker 1: like lame focus group I've ever seen. That wouldn't even

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Speaker 1: if I saw this, I'm like, I wouldn't trust what's

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Speaker 1: happening in here. Half the people are checked out and

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Speaker 1: are just like there's there. Yeah, there's so many, I

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Speaker 1: think pieces to the polling that we don't see two

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Speaker 1: that at times you're just sort of like sometimes people

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Speaker 1: look like they're just agreeing with what other people are

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Speaker 1: saying in a room when you have like focus groups,

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Speaker 1: I get phone polling works, that's different, but like when

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Speaker 1: people begin to do those sorts of research, it's very uh,

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Speaker 1: it's fun to see, but also you can see a

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Speaker 1: lot of people make money. Focus groups can be so

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Speaker 1: bunk too, because it's just like usually it's like just

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Speaker 1: people who like need money quickly, and they'll answer, however,

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Speaker 1: is the easiest way to get out of the room.

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Speaker 1: Like I did focus groups in college, and I was

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Speaker 1: just like, I don't know, I just know I get

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Speaker 1: fifty dollars at the end of this. I'm not trying

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Speaker 1: to get into a conversation with anybody, like do you

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Speaker 1: do you like chips? I'm like, I love chips. Like

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Speaker 1: if you just say yes to everything, you can get

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Speaker 1: out of the room very quickly, you know, right. And

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Speaker 1: it's also like you can see like you know, like

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Speaker 1: like I've done folks like been uh done focus groups

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Speaker 1: of like renewable energy, and it'll be like in a

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Speaker 1: city like Pasadena, which you know has like a mix

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Speaker 1: of conservative and liberal people, but if the if the

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Speaker 1: blend is off in the room and there's a majority

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Speaker 1: of conservative or liberal, most people aren't gonna want to

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Speaker 1: be like an outlier in that group setting. So your

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Speaker 1: results just be like, yeah, these people basically agree with

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Speaker 1: what we're saying, and you're just like that's not nuanced enough.

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Speaker 1: But anyway, yeah, you're subject to the Yeah, focus groups

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Speaker 1: are a nightmare. I mean you're subject to like the

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Speaker 1: whims of the person running them at Also, yeah, peer

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Speaker 1: pressure plays a factor. And to be honest, like I

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Speaker 1: kind of wish national polls did matter. I don't personally

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Speaker 1: support the electoral college. I think it's bullshit and it's

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Speaker 1: unfair and we should have a national popular vote for

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Speaker 1: president and make things more fair. But the system that

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Speaker 1: we have now, it's just sort of become a way.

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Speaker 1: These polls are just away for like, you know, news

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Speaker 1: organized nations to you know, addict boomers to tune Intery Hour, Hey,

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Speaker 1: and millennials and millennials not just Finally, what is a myth?

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Speaker 1: What's something people think is true, you know, to be

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Speaker 1: false or vice versa. Many people think that we have

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Speaker 1: the right to vote for president, and we don't. We

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Speaker 1: don't have the right to vote for president. It's up

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Speaker 1: to our states to let us vote for president. Basically,

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Speaker 1: they can decide how the electors were chosen. And for

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Speaker 1: the first hundred years of this country, Uh, we didn't

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Speaker 1: vote for president. Uh, state legislatures decided how they wanted

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Speaker 1: to pick the electors and they did that. It's only

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Speaker 1: been since eighteen eighty that we've actually been allowed by

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Speaker 1: our states to vote for president. And what makes me

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Speaker 1: very concerned right now is that in the middle of

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Speaker 1: a pandemic, as we are changing how we vote and

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Speaker 1: you know, talking about voting by mail, um, there isn't

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Speaker 1: anything to stop states from taking that right away and saying, well,

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Speaker 1: we're going to let the legislature do it. Um. I

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Speaker 1: mean it would lead to massive protests and basically an uprising.

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Speaker 1: But um, we don't actually have the right to vote

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Speaker 1: for president of citizens. You think that they'd be more

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Speaker 1: out there with that, and like just so you know,

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Speaker 1: like you actually don't have the right to vote, So like,

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Speaker 1: let's it sounds like a It sounds like a nice

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Speaker 1: thing to save until the very last second to tell everybody.

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Speaker 1: They're like, well, we slipped and we dropped all the

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Speaker 1: envelopes into a fire. But the good news is you

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Speaker 1: never had the right to vote to begin with. Yes,

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Speaker 1: I don't worry about it anyway. Alright, ays, let's take

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Speaker 1: a quick break and we'll be right back and we're back.

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Speaker 1: So elon Musk Grimes had their baby boy and uh

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Speaker 1: named it x uh any A twelve any like the

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Speaker 1: TV Channel and then A twelve like an airplane model.

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Speaker 1: Uh and I I don't give a ship, but it

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Speaker 1: is like they I don't know, like I I think

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Speaker 1: I have to give a ship because I think this

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Speaker 1: dude is just with us from here on out elon

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Speaker 1: musk and as well as uh x an e A twelve.

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Speaker 1: He's ineffable. He's like, he's like uh Idris Elba and cats.

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Speaker 1: I was just gonna make that same comparison, the clear

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Speaker 1: one to one. I don't know what you do? You

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Speaker 1: think this baby is going to grow up and do

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Speaker 1: something terrible? My guess is yes, I don't know. It

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Speaker 1: could be like I've met the sons of very famous

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Speaker 1: men and their teople. Yeah, and they're typically like never

425
00:24:56,440 --> 00:24:59,400
Speaker 1: trying to ever be like their dad's at all. Like

426
00:24:59,520 --> 00:25:03,400
Speaker 1: every like son of a comedian or actor or athlete

427
00:25:03,440 --> 00:25:05,760
Speaker 1: that I've ever like, they're all very much like trying

428
00:25:05,800 --> 00:25:08,359
Speaker 1: to just not be the thing their dad is known for.

429
00:25:08,880 --> 00:25:11,000
Speaker 1: I think the best case scenario for this is that

430
00:25:11,119 --> 00:25:16,520
Speaker 1: this child is very boring and had like is only

431
00:25:16,560 --> 00:25:18,760
Speaker 1: interested in the most boring ship ever, and it's just

432
00:25:18,800 --> 00:25:23,600
Speaker 1: a dull, dull, dull kid. I hope this scenario for

433
00:25:23,640 --> 00:25:28,120
Speaker 1: all of them. Yeah, that's true, yea, all of us. Yeah.

434
00:25:28,119 --> 00:25:30,040
Speaker 1: I just want to see this kid out a piano though,

435
00:25:31,040 --> 00:25:33,840
Speaker 1: just all that pain out there, you know what I mean.

436
00:25:33,920 --> 00:25:37,040
Speaker 1: And we're just like, I don't know, x Ash Archangel,

437
00:25:37,160 --> 00:25:40,400
Speaker 1: whatever the funk. This kid's name is Anthony. Between this

438
00:25:40,680 --> 00:25:45,240
Speaker 1: and the Amanda Palmer Neil Gaiman divorce news, you're just like, Oh,

439
00:25:45,280 --> 00:25:47,840
Speaker 1: the messiest couples are coming out to play this week,

440
00:25:47,880 --> 00:25:53,120
Speaker 1: and what is that? What? It's a whole the thing

441
00:25:53,160 --> 00:25:56,920
Speaker 1: that I like Neil Gaiman. I think he's a great writer.

442
00:25:57,160 --> 00:26:00,640
Speaker 1: Helped you get back on Twitter, I believe twice for

443
00:26:00,680 --> 00:26:03,760
Speaker 1: some reason. I love that. I appreciate that. Yeah. He

444
00:26:03,920 --> 00:26:07,040
Speaker 1: so he uh for a very for I think almost

445
00:26:07,080 --> 00:26:09,359
Speaker 1: ten years. He's been married to a musician who I

446
00:26:09,440 --> 00:26:11,760
Speaker 1: really liked in college and then I think I kind

447
00:26:11,760 --> 00:26:15,119
Speaker 1: of grew up. But her name is Amanda Palmer. I

448
00:26:15,160 --> 00:26:18,120
Speaker 1: like her. I liked her music in college a lot. Uh,

449
00:26:18,400 --> 00:26:20,840
Speaker 1: she's about She's had a lot of I mean, if

450
00:26:20,840 --> 00:26:24,399
Speaker 1: you google Amanda Palmer controversy, there's she's done some ship

451
00:26:24,440 --> 00:26:28,480
Speaker 1: where like just kind of like shady, like not paying

452
00:26:28,480 --> 00:26:31,399
Speaker 1: her opening acts. Like she's had a lot of missteps

453
00:26:31,440 --> 00:26:35,480
Speaker 1: over the years labor wise, but has this like radical

454
00:26:35,640 --> 00:26:39,640
Speaker 1: honesty vibe that she could kind of slither out of anything. Um.

455
00:26:40,200 --> 00:26:44,040
Speaker 1: And so anyways, they broke up and Amanda so she's

456
00:26:44,160 --> 00:26:46,520
Speaker 1: radical honesty, which basically means she shares a lot of

457
00:26:46,560 --> 00:26:49,920
Speaker 1: information with about her life without checking with people first.

458
00:26:50,359 --> 00:26:52,159
Speaker 1: And so I guess that she and Neil Gaiman. I

459
00:26:52,200 --> 00:26:54,440
Speaker 1: don't know what the situation is. I don't know whatever

460
00:26:54,760 --> 00:26:58,119
Speaker 1: they were, Polly, they broke up. She's quarantining with their

461
00:26:58,160 --> 00:27:00,440
Speaker 1: kid in New Zealand. He went back to the UK.

462
00:27:00,960 --> 00:27:04,119
Speaker 1: And then I think it seems like, just based on

463
00:27:04,320 --> 00:27:07,840
Speaker 1: the vibe of the tweets they've been exchanging, that they

464
00:27:08,200 --> 00:27:11,359
Speaker 1: Neil Gaiman was assuming we're not going to talk about this,

465
00:27:11,680 --> 00:27:15,320
Speaker 1: and then Amanda Palmer wrote about it on her Patreon blog.

466
00:27:17,119 --> 00:27:19,720
Speaker 1: That's not all makes sense. As I searched, you know,

467
00:27:19,840 --> 00:27:22,119
Speaker 1: she likes to use the hard war and word okay,

468
00:27:22,240 --> 00:27:27,320
Speaker 1: so she's done some funk that like it's it's it's

469
00:27:27,320 --> 00:27:30,360
Speaker 1: a tweet is what I was talking about earlier, because

470
00:27:30,359 --> 00:27:32,120
Speaker 1: I didn't know what it meant. But it just made

471
00:27:32,160 --> 00:27:33,720
Speaker 1: me laugh because I don't know what it means. You said,

472
00:27:33,720 --> 00:27:37,040
Speaker 1: Amanda Palmer, divorcing Neil Gaiman on Patreon is Tiger King

473
00:27:37,080 --> 00:27:40,600
Speaker 1: for ukulele Goths. Yes, yes, yes, I saw that there.

474
00:27:41,640 --> 00:27:45,080
Speaker 1: It's like it's annoying from so many angles. My my tweet,

475
00:27:45,160 --> 00:27:47,440
Speaker 1: my favorite tweet that I saw about it. I'll cite

476
00:27:47,480 --> 00:27:50,400
Speaker 1: it later, but it was like, uh, I can't wait

477
00:27:50,440 --> 00:27:53,159
Speaker 1: to see Helen and Bonham Carter play the Vampire that

478
00:27:53,280 --> 00:27:56,720
Speaker 1: Neil Gaiman inevitably writes a book about about his divorce

479
00:27:56,760 --> 00:28:00,600
Speaker 1: with Amanda Palmer. There's gonna be some exhausting any series

480
00:28:00,600 --> 00:28:03,199
Speaker 1: about this whole thing. I don't know. It's just just

481
00:28:03,359 --> 00:28:06,320
Speaker 1: the most exhausting couples are coming out to play this week.

482
00:28:06,960 --> 00:28:10,880
Speaker 1: Shout out to Anthony. Yeah, what is her music sound like?

483
00:28:12,119 --> 00:28:15,320
Speaker 1: If you had to compare to somebody, it's like performance

484
00:28:15,400 --> 00:28:21,760
Speaker 1: art music. It's like singing about important issues, not very well.

485
00:28:22,600 --> 00:28:24,840
Speaker 1: I'm sure someone. I'm sure someone will come for me

486
00:28:24,880 --> 00:28:27,520
Speaker 1: for that. But that was I was into that ship

487
00:28:27,640 --> 00:28:29,879
Speaker 1: in college, and then I was like, wait, this woman

488
00:28:30,000 --> 00:28:32,960
Speaker 1: is like maybe not maybe not so great because I

489
00:28:33,080 --> 00:28:35,240
Speaker 1: was she. I was in college and during that whole

490
00:28:35,240 --> 00:28:39,080
Speaker 1: scandal where she didn't pay anyone she paid, she was like, Oh,

491
00:28:39,200 --> 00:28:43,160
Speaker 1: I'm looking for opening acts for my national tour and

492
00:28:43,360 --> 00:28:46,120
Speaker 1: she had raised a million dollars on Kickstarter for it,

493
00:28:46,520 --> 00:28:48,960
Speaker 1: and she was just like, yeah, I pay him beer

494
00:28:49,000 --> 00:28:50,520
Speaker 1: and hugs. And I was like, well, I don't know

495
00:28:50,600 --> 00:28:56,400
Speaker 1: if I funk with this person. So, you know, I

496
00:28:56,440 --> 00:29:00,480
Speaker 1: had not heard of her before this divorce worry. But

497
00:29:00,560 --> 00:29:07,320
Speaker 1: she sounds everything you've said about her makes her sound

498
00:29:07,400 --> 00:29:12,040
Speaker 1: like Trump. She like radical honesty and can get out

499
00:29:12,040 --> 00:29:17,320
Speaker 1: of anything uh hard r N word um doesn't pay

500
00:29:17,360 --> 00:29:21,880
Speaker 1: anybody like that's all like the things Trump is most

501
00:29:21,920 --> 00:29:26,600
Speaker 1: famous for. Its very presidential. And I remember her as

502
00:29:26,600 --> 00:29:29,080
Speaker 1: being one of the first artists that really like went

503
00:29:29,480 --> 00:29:32,880
Speaker 1: full on the independent route. Where she was basically was

504
00:29:32,920 --> 00:29:35,520
Speaker 1: like a few years after everyone was like the R

505
00:29:35,600 --> 00:29:38,120
Speaker 1: I A. A was like suing everyone's grandma for you know,

506
00:29:38,320 --> 00:29:42,880
Speaker 1: downloading Frank Sinatra on Napster and people were um saying that,

507
00:29:42,920 --> 00:29:44,680
Speaker 1: you know, record labels are gonna be here forever, and

508
00:29:44,720 --> 00:29:46,560
Speaker 1: it's gonna be you know, it's it's still the future.

509
00:29:46,600 --> 00:29:48,360
Speaker 1: And she was like, no, I'm good. I can do

510
00:29:48,400 --> 00:29:50,720
Speaker 1: it with like, you know, a few hundred fans. I'll

511
00:29:50,760 --> 00:29:52,880
Speaker 1: just sell my music directly and make money on streaming

512
00:29:52,880 --> 00:29:55,400
Speaker 1: and touring. And I feel like she was I mean,

513
00:29:55,520 --> 00:29:57,400
Speaker 1: I didn't know any of this other ship. I mean

514
00:29:57,400 --> 00:30:00,240
Speaker 1: she sounds like a nightmare. But um, this this off

515
00:30:00,280 --> 00:30:03,120
Speaker 1: like I guess economically she was, you know, kind of

516
00:30:03,160 --> 00:30:06,800
Speaker 1: ahead of the curve visionary economically. She she definitely like

517
00:30:06,920 --> 00:30:08,760
Speaker 1: she was like, I think, the first person to raise

518
00:30:08,800 --> 00:30:11,080
Speaker 1: a million dollars on Kickstarter. She was like early to

519
00:30:11,120 --> 00:30:15,400
Speaker 1: the Patreon wave. But she she does, you know, give

520
00:30:15,520 --> 00:30:19,320
Speaker 1: up those narcissists of vibes and uh, those like I

521
00:30:19,400 --> 00:30:21,760
Speaker 1: can't how can I possibly do something wrong if I'm

522
00:30:21,840 --> 00:30:27,720
Speaker 1: radically honest vibes. Um, so you know, don't google or

523
00:30:27,920 --> 00:30:31,360
Speaker 1: save your time. Your time is valuable. You don't need

524
00:30:31,400 --> 00:30:34,080
Speaker 1: to google Amanda Palmer at this time. Yeah, Jack, tell

525
00:30:34,120 --> 00:30:38,240
Speaker 1: people what they should be googling. Let's google giant killer

526
00:30:38,280 --> 00:30:44,640
Speaker 1: hornets instead. Um, this is this is something that so

527
00:30:45,720 --> 00:30:47,680
Speaker 1: we wrote about this back in two thousand and eight,

528
00:30:47,680 --> 00:30:51,440
Speaker 1: it cracked that there are things in Japan called, uh

529
00:30:51,920 --> 00:30:58,680
Speaker 1: giant hornets that uh kill forty people a year sometimes

530
00:30:59,240 --> 00:31:05,000
Speaker 1: uh with just horrible painful stings. Uh. There there as

531
00:31:05,040 --> 00:31:07,920
Speaker 1: their name suggests, like giant, they're the size of like

532
00:31:08,000 --> 00:31:11,760
Speaker 1: a thumb. They they are like three to four times

533
00:31:11,800 --> 00:31:15,440
Speaker 1: the size of like a bumblebee and bumblebees already looked

534
00:31:15,440 --> 00:31:17,960
Speaker 1: like they shouldn't be able to fly because they're so big.

535
00:31:18,320 --> 00:31:22,320
Speaker 1: These are just like they're but somewhere between a bee

536
00:31:22,360 --> 00:31:28,320
Speaker 1: and a bird. Um, and they are like fucking so

537
00:31:28,560 --> 00:31:32,720
Speaker 1: metal like they so yeah, they can sting through a

538
00:31:32,760 --> 00:31:37,520
Speaker 1: beekeeper uniform. They have like armor piercing stings. So the

539
00:31:37,600 --> 00:31:40,320
Speaker 1: weird thing is it really has the vibe of like

540
00:31:40,520 --> 00:31:44,960
Speaker 1: the famous media panic of the African killer bees that

541
00:31:45,000 --> 00:31:49,000
Speaker 1: we're supposed to like invade America from the South and

542
00:31:49,320 --> 00:31:56,280
Speaker 1: just take take over our country, and um, that it's

543
00:31:56,560 --> 00:32:00,200
Speaker 1: probably going to be over end up being overblown at

544
00:32:00,240 --> 00:32:05,360
Speaker 1: the same time, like these are real and all the

545
00:32:05,440 --> 00:32:09,880
Speaker 1: details about them are details from a horror movie. What's

546
00:32:09,920 --> 00:32:12,240
Speaker 1: the reason it came back was because of that clip

547
00:32:12,280 --> 00:32:15,600
Speaker 1: of like the mouse getting like stung to death by

548
00:32:15,600 --> 00:32:18,520
Speaker 1: the hornets. Because you know, like this has been a

549
00:32:18,600 --> 00:32:21,400
Speaker 1: thing on the internet for a while, like whether it's

550
00:32:21,520 --> 00:32:24,080
Speaker 1: articles about it or like that one clip everywhere most

551
00:32:24,120 --> 00:32:27,120
Speaker 1: people who probably their first interaction is that video where

552
00:32:27,120 --> 00:32:29,880
Speaker 1: they going to a bee hive and just just there's

553
00:32:29,960 --> 00:32:35,600
Speaker 1: body parts flying everywhere. He completely annihilated. Well, so the

554
00:32:35,680 --> 00:32:44,960
Speaker 1: reason this is back, unfortunately is because in Canada and Washington,

555
00:32:45,960 --> 00:32:50,760
Speaker 1: beekeepers were finding uh, their hives of bees with all

556
00:32:50,800 --> 00:32:55,200
Speaker 1: their bees having their heads ripped off, and they were like, oh,

557
00:32:55,280 --> 00:32:59,320
Speaker 1: that's that's not good. That that means that we might

558
00:32:59,440 --> 00:33:03,760
Speaker 1: have giant Japanese hornets in American. Sure enough, a couple

559
00:33:03,840 --> 00:33:08,400
Speaker 1: were spotted. And the way that they're talking, like the

560
00:33:08,800 --> 00:33:12,920
Speaker 1: uh insectologists that's not the name, but you know, the

561
00:33:12,960 --> 00:33:16,600
Speaker 1: people who pay attention to insects, were like, yeah, so

562
00:33:17,040 --> 00:33:19,400
Speaker 1: we're probably gonna be okay. All we need to do

563
00:33:19,800 --> 00:33:25,160
Speaker 1: is find these giant hornets, knock them out, put electronic

564
00:33:25,280 --> 00:33:29,840
Speaker 1: collars around them, follow them back to their underground hive. Yeah,

565
00:33:29,960 --> 00:33:33,360
Speaker 1: follow them back to their underground hive, and destroy their colony.

566
00:33:33,760 --> 00:33:38,040
Speaker 1: It's like this, this sounds like a good movie sign.

567
00:33:38,800 --> 00:33:42,719
Speaker 1: They're so just like I still over their size, like

568
00:33:42,800 --> 00:33:47,040
Speaker 1: just the uh that you could just the they're like

569
00:33:47,120 --> 00:33:51,840
Speaker 1: half the size of a palm. Yeah. Yeah, I didn't

570
00:33:51,840 --> 00:34:00,440
Speaker 1: realize these heads are falling off. Literally this literally from

571
00:34:00,480 --> 00:34:04,240
Speaker 1: the CNN report. Beekeepers have reported piles of dead bees

572
00:34:04,280 --> 00:34:10,239
Speaker 1: with their heads ripped off. That's even like reading that

573
00:34:10,280 --> 00:34:12,359
Speaker 1: first report where I'm like, oh, this is a little

574
00:34:12,480 --> 00:34:16,160
Speaker 1: dramatic where it's like getting stung by this hornet feels

575
00:34:16,160 --> 00:34:20,840
Speaker 1: like hot metal being injected into your veins. I'm like, what,

576
00:34:21,000 --> 00:34:23,319
Speaker 1: but we've all been there. Yeah, I know. It's like

577
00:34:23,400 --> 00:34:27,280
Speaker 1: I can't even man, I've never been in a Saw movie.

578
00:34:27,320 --> 00:34:32,000
Speaker 1: I don't know what that feels like. Ben, Are you

579
00:34:32,000 --> 00:34:36,279
Speaker 1: a very outdoor Are you a very outdoorsy? Oh? I was?

580
00:34:38,160 --> 00:34:41,640
Speaker 1: I can't, I can't. I can't stop thinking. I'm not

581
00:34:41,680 --> 00:34:45,680
Speaker 1: a particularly religious person. I'm like bare minimum Jew, but

582
00:34:45,840 --> 00:34:48,759
Speaker 1: I feel like, from what I remember, of the ten

583
00:34:48,840 --> 00:34:55,080
Speaker 1: plagues were in with deadly disease and some version of locusts.

584
00:34:55,160 --> 00:34:56,600
Speaker 1: So I'm sort of looking at the rest of the

585
00:34:56,600 --> 00:35:00,879
Speaker 1: bingo card wondering what's next. Oh yeah, my like bare

586
00:35:00,960 --> 00:35:06,799
Speaker 1: minimum Jew as the equip as the alternate variant on

587
00:35:07,120 --> 00:35:12,960
Speaker 1: the bare Jew from Inglorious Bastard. Bare Minimum. Well, yeah,

588
00:35:13,000 --> 00:35:15,640
Speaker 1: if these are the plagues in the words of like

589
00:35:15,680 --> 00:35:19,120
Speaker 1: the Passover song, Diane, it would have been enough. This,

590
00:35:19,120 --> 00:35:24,040
Speaker 1: this is enough if if they were good, I'm good here,

591
00:35:24,120 --> 00:35:29,920
Speaker 1: we're good. Message received. Uh, don't try to take them

592
00:35:29,920 --> 00:35:34,239
Speaker 1: out yourself if you see them in, said entomologist Chriss Looney.

593
00:35:34,320 --> 00:35:37,360
Speaker 1: That is a fucking line from Jaws. That is a

594
00:35:37,440 --> 00:35:40,480
Speaker 1: line from like a horror movie, don't try to take

595
00:35:40,520 --> 00:35:44,080
Speaker 1: them out yourself. And in this film, inevitably there's a

596
00:35:44,120 --> 00:35:48,160
Speaker 1: small b plot or fun or just a scene or

597
00:35:48,200 --> 00:35:51,040
Speaker 1: you see these like renegade assholes who are drunk who

598
00:35:51,040 --> 00:35:54,120
Speaker 1: were like, man, we're gonna go fucking kill those hornets ourselves,

599
00:35:54,400 --> 00:35:58,680
Speaker 1: and they're absolutely destroyed by them. Yes, um, don't be

600
00:35:58,719 --> 00:36:02,000
Speaker 1: surprised if you see small children just being carried away

601
00:36:02,640 --> 00:36:06,080
Speaker 1: and I guess you will be able to see the

602
00:36:06,080 --> 00:36:11,480
Speaker 1: the giant hornet carrying them. Um what anyways, go ahead? No,

603
00:36:11,560 --> 00:36:14,520
Speaker 1: I'm like, is there any like, is there any rhyme

604
00:36:14,600 --> 00:36:17,320
Speaker 1: or reason like that someone could like their tips or

605
00:36:17,360 --> 00:36:19,560
Speaker 1: it's like you probably don't want to be in this

606
00:36:19,640 --> 00:36:22,160
Speaker 1: area or around this ship. They're just sort of like, hey, bro,

607
00:36:22,239 --> 00:36:24,000
Speaker 1: I don't know. But if you see him, fucking run

608
00:36:24,080 --> 00:36:28,520
Speaker 1: for your life. Is so fortunately, uh and just kidding.

609
00:36:28,560 --> 00:36:30,840
Speaker 1: None of the there's not a single detail unless that

610
00:36:30,960 --> 00:36:34,319
Speaker 1: is fortunate. So like with with a bee, like there's

611
00:36:34,360 --> 00:36:38,880
Speaker 1: a big old honeycomb hive that like you see hanging

612
00:36:38,920 --> 00:36:42,040
Speaker 1: from a tree and you can like hear them. These

613
00:36:42,080 --> 00:36:45,360
Speaker 1: things burrow underground, so you can just like be walking

614
00:36:45,400 --> 00:36:49,160
Speaker 1: around the ground and step into a nest of these

615
00:36:49,360 --> 00:36:54,400
Speaker 1: and then you're fucked. Uh. So yeah, there's just like

616
00:36:54,560 --> 00:36:59,640
Speaker 1: no good no good news on the giant killer Japanese

617
00:36:59,680 --> 00:37:03,080
Speaker 1: horn front. So you know, one wrong step and you

618
00:37:03,080 --> 00:37:07,440
Speaker 1: could descend into waspy hell yeah. Maybe the Bible was

619
00:37:07,520 --> 00:37:12,799
Speaker 1: like onto something. Yeah, this is the phase right now

620
00:37:13,960 --> 00:37:16,719
Speaker 1: take today. Maybe they were onto something with that Bible. Yeah,

621
00:37:16,760 --> 00:37:19,759
Speaker 1: I don't know. Maybe I'm just gonna throw it out there.

622
00:37:20,360 --> 00:37:23,319
Speaker 1: All right, guys, let's take a quick break. Jamie, you

623
00:37:23,400 --> 00:37:25,640
Speaker 1: have to leave us. It has been a pleasure of

624
00:37:25,680 --> 00:37:31,080
Speaker 1: having you for these two. I gotta go breastfeeding Musk's baby. Okay,

625
00:37:31,440 --> 00:37:35,759
Speaker 1: good luck because breasts are dry. Well, no grimes, she

626
00:37:35,760 --> 00:37:42,719
Speaker 1: she la tats like like electricity. It's bad. So I'm

627
00:37:42,800 --> 00:37:58,160
Speaker 1: I'm a wit nurse. Got a hustle. Okay, bye, and

628
00:37:58,280 --> 00:38:03,600
Speaker 1: we're back. And we're starting to hear about something called

629
00:38:03,680 --> 00:38:07,520
Speaker 1: skin hunger. Uh. And that's not just me. When I

630
00:38:07,680 --> 00:38:16,040
Speaker 1: order KFC, I right, got delicious. Uh. No, I actually

631
00:38:16,120 --> 00:38:19,040
Speaker 1: noticed this in So I was talking about that New

632
00:38:19,120 --> 00:38:22,279
Speaker 1: York Times article, the Frank Brine column, where he was

633
00:38:22,320 --> 00:38:27,799
Speaker 1: interviewing like this uh COVID nineteen Uh, this woman who

634
00:38:27,800 --> 00:38:31,560
Speaker 1: had predicted COVID nineteen and it ends with her just

635
00:38:31,640 --> 00:38:35,520
Speaker 1: being like like, it's all just a very like matter

636
00:38:35,560 --> 00:38:39,719
Speaker 1: of fact. She's an expert. She's giving these really like intelligent, interesting,

637
00:38:40,520 --> 00:38:43,920
Speaker 1: decisive takes. And then that interview ends with her just

638
00:38:44,000 --> 00:38:47,200
Speaker 1: being like, I really want to hug someone. I I

639
00:38:47,280 --> 00:38:50,200
Speaker 1: just need to hug, like for like three sentences, just

640
00:38:50,239 --> 00:38:53,000
Speaker 1: talking about how badly she wants to hug someone's like,

641
00:38:53,040 --> 00:38:55,040
Speaker 1: even if it was just for five seconds, I just

642
00:38:55,120 --> 00:38:57,759
Speaker 1: want to want to hug someone. Yeah, I don't know,

643
00:38:57,840 --> 00:39:00,399
Speaker 1: it's a it's a real thing that people are are

644
00:39:00,480 --> 00:39:03,480
Speaker 1: going through, for sure. Oh yeah, I think also just

645
00:39:03,960 --> 00:39:08,080
Speaker 1: you know, we're lucky enough to be like sheltering with

646
00:39:08,120 --> 00:39:12,200
Speaker 1: a partner, so it's not it's a very different experience.

647
00:39:12,200 --> 00:39:14,480
Speaker 1: And like with my single friends and like other like

648
00:39:14,960 --> 00:39:16,799
Speaker 1: coworkers I've had in the past, I've caught up with

649
00:39:16,840 --> 00:39:19,960
Speaker 1: the ones who are isolating alone, Like it's really it's

650
00:39:19,960 --> 00:39:22,640
Speaker 1: like I said, it's really hard, and it's boils down

651
00:39:22,640 --> 00:39:26,520
Speaker 1: to like just just some kind of touch and a

652
00:39:26,520 --> 00:39:28,840
Speaker 1: lot of this whole idea of skin hunger now is

653
00:39:29,160 --> 00:39:30,960
Speaker 1: you know, a lot of experts like this is another

654
00:39:31,000 --> 00:39:33,400
Speaker 1: part of this whole social distancing thing. We also have

655
00:39:33,440 --> 00:39:37,200
Speaker 1: to talk about because it has effects overall because you know,

656
00:39:37,239 --> 00:39:40,440
Speaker 1: we're all social animals, so we need that touch, We

657
00:39:40,480 --> 00:39:43,239
Speaker 1: need that feeling of like feedback of community from other

658
00:39:43,239 --> 00:39:46,440
Speaker 1: people around us, like the same reason why babies who

659
00:39:46,440 --> 00:39:50,120
Speaker 1: are neonatal intensive care like needs like skin contact and

660
00:39:50,160 --> 00:39:54,839
Speaker 1: skin context of vital for children, um, and what they're there.

661
00:39:54,920 --> 00:39:58,040
Speaker 1: You know, they're just wanting to let people know like, yes,

662
00:39:58,080 --> 00:40:01,080
Speaker 1: this is very normal. Uh, but it's also something that

663
00:40:01,120 --> 00:40:04,080
Speaker 1: we need to take care of ourselves because it's hard

664
00:40:04,120 --> 00:40:06,200
Speaker 1: to do, you know if you don't have someone around.

665
00:40:06,239 --> 00:40:10,359
Speaker 1: So you know that the problem is we're in an

666
00:40:10,360 --> 00:40:14,040
Speaker 1: era where like video and audio, we can beam fucking

667
00:40:14,080 --> 00:40:17,960
Speaker 1: anywhere in an instant, but the haptic you know, the

668
00:40:18,040 --> 00:40:21,279
Speaker 1: touch senses and things like that, we're just absolutely there's

669
00:40:21,320 --> 00:40:24,480
Speaker 1: just nothing for that. Um. So you know, we're all

670
00:40:24,600 --> 00:40:26,040
Speaker 1: I think a lot of people are trying to st

671
00:40:26,080 --> 00:40:27,759
Speaker 1: are struggling a bit to try and feel like in

672
00:40:27,800 --> 00:40:30,080
Speaker 1: their own bodies a bit and get that sort of stimulation.

673
00:40:30,560 --> 00:40:33,360
Speaker 1: And this is something that there was even like uh, um,

674
00:40:33,400 --> 00:40:36,080
Speaker 1: there's like a business and I've I've read articles about this,

675
00:40:36,680 --> 00:40:39,800
Speaker 1: I think even last year that there's like I don't know,

676
00:40:39,840 --> 00:40:41,840
Speaker 1: if it's an app, it's just people on Craigslist, but

677
00:40:41,880 --> 00:40:45,960
Speaker 1: like people just like requesting someone to cuddle. Yeah, like

678
00:40:46,040 --> 00:40:50,520
Speaker 1: these like cuddle opportunities, cuddle parties, BA Get Cracked. Robert

679
00:40:50,520 --> 00:40:54,160
Speaker 1: Evans interviewed people who had like started a whole business

680
00:40:54,200 --> 00:40:56,960
Speaker 1: based on cuddle parties, and it was like they've had

681
00:40:57,000 --> 00:40:59,640
Speaker 1: the cuddle party circuit and it was all like they

682
00:40:59,640 --> 00:41:02,600
Speaker 1: were all these rules to like keep it just you know,

683
00:41:03,040 --> 00:41:06,200
Speaker 1: so that strangers were all just like taking care of

684
00:41:06,200 --> 00:41:09,760
Speaker 1: their skin hunger. In this new reality where we don't

685
00:41:10,320 --> 00:41:13,719
Speaker 1: have a lot of people to interact with like physically

686
00:41:14,239 --> 00:41:18,279
Speaker 1: because we're all you know, we were already interacting over

687
00:41:18,719 --> 00:41:23,799
Speaker 1: phones and you know now like even more so. Yeah,

688
00:41:23,840 --> 00:41:27,840
Speaker 1: I was just thinking about like I think, like I

689
00:41:27,880 --> 00:41:31,200
Speaker 1: feel like there's people at the grocery store who have

690
00:41:31,400 --> 00:41:38,000
Speaker 1: I would say, hungry eyes, great song k Patrick Swazy.

691
00:41:38,080 --> 00:41:40,960
Speaker 1: I feel like there's just like that need and it's

692
00:41:41,000 --> 00:41:43,840
Speaker 1: not necessarily a sexual thing, but it's like a human

693
00:41:44,040 --> 00:41:47,759
Speaker 1: contact thing where people are just like more likely to

694
00:41:47,800 --> 00:41:50,440
Speaker 1: like make eye contact with you and like acknowledge you

695
00:41:50,600 --> 00:41:54,759
Speaker 1: just because they're there's just like a profound loneliness and

696
00:41:54,880 --> 00:41:58,799
Speaker 1: like absence of human contact I've never said hello to

697
00:41:59,080 --> 00:42:01,480
Speaker 1: so many people wife house on the street. Never in

698
00:42:01,520 --> 00:42:05,080
Speaker 1: my fucking life. I've never had so many older white

699
00:42:05,120 --> 00:42:08,279
Speaker 1: people go out of their way to say hello to

700
00:42:08,360 --> 00:42:12,200
Speaker 1: me in my fucking life. It's just I think we

701
00:42:12,280 --> 00:42:15,160
Speaker 1: all feel it, man, Like we all we all know

702
00:42:15,280 --> 00:42:17,600
Speaker 1: we're doing what's best by staying inside. But then when

703
00:42:17,600 --> 00:42:20,160
Speaker 1: you go out, it's almost kind of like hey, man, cool,

704
00:42:20,320 --> 00:42:26,720
Speaker 1: like yeah, and it's gonna be weird because there's going

705
00:42:26,880 --> 00:42:30,760
Speaker 1: like I think people are ready for this release to happen,

706
00:42:31,320 --> 00:42:35,759
Speaker 1: where it's like and now the quarantine's over and we

707
00:42:35,800 --> 00:42:37,960
Speaker 1: can all go out and hug each other and go

708
00:42:38,000 --> 00:42:42,080
Speaker 1: to cuddle parties, and it's like that that isn't gonna

709
00:42:42,120 --> 00:42:46,839
Speaker 1: happen until there's a vaccine, and like, for the next

710
00:42:46,880 --> 00:42:49,919
Speaker 1: couple of years, it's just gonna be a process of like,

711
00:42:50,520 --> 00:42:52,880
Speaker 1: you know, there's gonna be an uptick in your community,

712
00:42:53,200 --> 00:42:57,040
Speaker 1: and then like the hospitals will get overwhelmed and we'll

713
00:42:57,040 --> 00:42:59,400
Speaker 1: have to go back to social distancing for a little while,

714
00:42:59,800 --> 00:43:04,040
Speaker 1: and then the you know, virus rate will go down,

715
00:43:04,160 --> 00:43:07,080
Speaker 1: and then we'll go back out there and it's just

716
00:43:07,120 --> 00:43:12,400
Speaker 1: gonna be there's not going to be that satisfying release. Unfortunately, Yeah,

717
00:43:12,480 --> 00:43:14,480
Speaker 1: in China that they're saying, there's this thing, it's like

718
00:43:14,480 --> 00:43:18,920
Speaker 1: a phenomenon that consumer analysts are saying it's called revenge spending.

719
00:43:19,480 --> 00:43:22,800
Speaker 1: That was happening because things are as things are being eased,

720
00:43:22,800 --> 00:43:25,200
Speaker 1: like a lot of people are trying to spend a

721
00:43:25,200 --> 00:43:27,839
Speaker 1: lot more money like right away. They've just been sort

722
00:43:27,840 --> 00:43:29,960
Speaker 1: of cooped up. And that's been one way people have

723
00:43:30,000 --> 00:43:33,320
Speaker 1: been releasing their anxiety rather than like traveling so much.

724
00:43:33,640 --> 00:43:38,319
Speaker 1: It's just been happening through like assumption. Um, so I think, yeah,

725
00:43:38,400 --> 00:43:40,279
Speaker 1: whatever it is, we're all going to find our way

726
00:43:40,320 --> 00:43:43,000
Speaker 1: to try and feel normal. But like that thing even

727
00:43:43,040 --> 00:43:45,040
Speaker 1: you say about touch, Like there's even studies about how

728
00:43:45,040 --> 00:43:47,520
Speaker 1: like getting a pat on your back before a task

729
00:43:48,080 --> 00:43:51,239
Speaker 1: like had an effect on people's performance to that's just

730
00:43:51,360 --> 00:43:54,160
Speaker 1: something like that. And so you know they say, obviously

731
00:43:54,160 --> 00:43:56,440
Speaker 1: a pet helps. If you have a pet, great because

732
00:43:56,920 --> 00:43:59,719
Speaker 1: you know, being able to hold something, there's warmth from it,

733
00:43:59,760 --> 00:44:02,240
Speaker 1: you can massage it, and they you know, their studies

734
00:44:02,280 --> 00:44:04,720
Speaker 1: that say massage is just as pleasurable for the person

735
00:44:04,920 --> 00:44:08,120
Speaker 1: applying the massage is the same person receiving it. And

736
00:44:08,160 --> 00:44:11,920
Speaker 1: then exercise just so you can get your feet circulating

737
00:44:11,960 --> 00:44:15,200
Speaker 1: a bit, you know, fucking massage your scalp, maybe put

738
00:44:15,239 --> 00:44:18,200
Speaker 1: some lotiontion on, like just do you know, just love

739
00:44:18,200 --> 00:44:22,960
Speaker 1: on yourself, touching yourself. I feel like there's something like

740
00:44:23,000 --> 00:44:26,520
Speaker 1: that doesn't count. I feel like as much as like

741
00:44:26,640 --> 00:44:29,880
Speaker 1: I I just yes, I want people who are you know,

742
00:44:29,960 --> 00:44:33,800
Speaker 1: quarantining by themselves to have like some sort of outlet.

743
00:44:33,960 --> 00:44:37,320
Speaker 1: But at the same time that like we should find

744
00:44:37,320 --> 00:44:40,680
Speaker 1: a better solution for them. I mean, just have like

745
00:44:40,719 --> 00:44:44,200
Speaker 1: a suck man if we can sooner find people who

746
00:44:44,200 --> 00:44:47,200
Speaker 1: have like antibodies, just have like the pro hug squad

747
00:44:47,280 --> 00:44:49,279
Speaker 1: to be like real bro, you can like I'm not

748
00:44:49,320 --> 00:44:54,080
Speaker 1: gonna don't worry about me man, the hug a muans. Yeah. Yeah,

749
00:44:54,280 --> 00:44:56,840
Speaker 1: inevitably there will be a documentary about those heroes, that

750
00:44:56,880 --> 00:44:58,880
Speaker 1: group of heroes. But yeah, I mean the thing you

751
00:44:58,920 --> 00:45:00,959
Speaker 1: were just talking about about the pat on the back

752
00:45:01,120 --> 00:45:04,200
Speaker 1: like that is we've talked about it before, but there's

753
00:45:04,239 --> 00:45:07,920
Speaker 1: a study that shows that NBA teams that touch do better.

754
00:45:08,320 --> 00:45:11,719
Speaker 1: And that's why you see all the NBA players like

755
00:45:11,800 --> 00:45:14,560
Speaker 1: touch each other's hands. It's not even like giving a five.

756
00:45:14,640 --> 00:45:17,800
Speaker 1: They're like literally touching hands like they're passing a charge

757
00:45:17,800 --> 00:45:21,359
Speaker 1: from one person to the other just before like a

758
00:45:21,400 --> 00:45:23,880
Speaker 1: free thrower at a time out or something like that.

759
00:45:23,960 --> 00:45:30,719
Speaker 1: It's like that improves performance, That improves like camaraderie. Uh.

760
00:45:30,840 --> 00:45:34,759
Speaker 1: And just think of the poor NBA teams not touch

761
00:45:34,880 --> 00:45:37,200
Speaker 1: out there, not having anybody to touch hands with. Just

762
00:45:37,280 --> 00:45:42,760
Speaker 1: that one creepy coach was right, huh yeah exactly. Yeah,

763
00:45:42,880 --> 00:45:44,640
Speaker 1: the guy who kept hitting you on the button and

764
00:45:44,800 --> 00:45:47,120
Speaker 1: being like, good hustle out there, and you're like, Bro,

765
00:45:47,320 --> 00:45:49,759
Speaker 1: I don't even play for this team. What are you

766
00:45:49,840 --> 00:45:52,520
Speaker 1: talking about? Bro? I'm bro. I'm the uncle of the

767
00:45:52,600 --> 00:45:57,520
Speaker 1: kid on the field. Just love love, love the commitment,

768
00:45:57,800 --> 00:46:06,319
Speaker 1: love the hustle, and guard the guy. Uh. Did we

769
00:46:06,920 --> 00:46:10,120
Speaker 1: cover the guy who would jump on people's backs and

770
00:46:10,200 --> 00:46:13,760
Speaker 1: give them like he wanted to get piggyback rides from people,

771
00:46:13,920 --> 00:46:17,120
Speaker 1: so he would, uh like that was his kink. And

772
00:46:17,200 --> 00:46:22,720
Speaker 1: so he would go to high school sporting events and

773
00:46:23,640 --> 00:46:27,040
Speaker 1: like when the people were celebrating, he would run up

774
00:46:27,080 --> 00:46:32,840
Speaker 1: and jump on their back. And it was because because

775
00:46:32,920 --> 00:46:36,160
Speaker 1: that was his kink. And like, so it's a very

776
00:46:36,239 --> 00:46:39,560
Speaker 1: dark story. Was he eventually like got arrested, Oh, but

777
00:46:39,600 --> 00:46:43,200
Speaker 1: he was like sexually aroused popping on those backs. I

778
00:46:43,200 --> 00:46:46,480
Speaker 1: don't know if he was sexually aroused, but I think

779
00:46:46,520 --> 00:46:49,880
Speaker 1: people were creeped out or not. I mean that sounds

780
00:46:49,920 --> 00:46:53,279
Speaker 1: like a like a really terrible sketch idea like someone

781
00:46:53,360 --> 00:46:56,400
Speaker 1: to be right. Yeah, dude, a guy like he loves it,

782
00:46:56,480 --> 00:47:02,520
Speaker 1: so he like cruises sporting events to find people. People.

783
00:47:02,719 --> 00:47:06,359
Speaker 1: Imagine you like hit a game winning shot and your

784
00:47:06,800 --> 00:47:10,279
Speaker 1: teammates are celebrating with you, and then like someone's on

785
00:47:10,320 --> 00:47:12,839
Speaker 1: your back and you turn around and that's a stranger.

786
00:47:13,000 --> 00:47:18,560
Speaker 1: You're like, yeah, yeah, yeah, You're gonna see a lot

787
00:47:18,560 --> 00:47:21,040
Speaker 1: of high schools like start to like throw the final

788
00:47:21,120 --> 00:47:24,000
Speaker 1: pass and like missed the final shot on purpose for

789
00:47:24,040 --> 00:47:27,319
Speaker 1: the safety of their fellow They just like look off

790
00:47:27,360 --> 00:47:29,600
Speaker 1: to the side and the guy's licking his lips and

791
00:47:29,640 --> 00:47:33,560
Speaker 1: he's like he only likes victory. They're like, but he

792
00:47:33,880 --> 00:47:37,160
Speaker 1: he actually becomes like a really good like saber metrics

793
00:47:37,200 --> 00:47:40,480
Speaker 1: analyst because he's like he's identifying teams that have a

794
00:47:40,560 --> 00:47:45,960
Speaker 1: high propensity for like clutched winds. Yeah, loves the game seven.

795
00:47:46,239 --> 00:47:49,520
Speaker 1: Loves a game seven. Where did all that wasted oxygen go?

796
00:47:50,440 --> 00:47:55,799
Speaker 1: I know, let's talk about the recipes that people are

797
00:47:56,000 --> 00:47:59,080
Speaker 1: searching for. Ben, are you cooking at all. I know

798
00:47:59,200 --> 00:48:03,160
Speaker 1: you said it, Jackie was cooking, You were doing a

799
00:48:03,160 --> 00:48:06,359
Speaker 1: little bit of stuff. Have you been googling any recipes,

800
00:48:06,680 --> 00:48:10,600
Speaker 1: looking up any any new uh foods that you're preparing?

801
00:48:10,840 --> 00:48:13,520
Speaker 1: I I mean, I'm I'm going to start. And I'm

802
00:48:13,600 --> 00:48:15,600
Speaker 1: not just saying this because the question has been posed me,

803
00:48:15,640 --> 00:48:17,439
Speaker 1: but this is this was something I've been thinking about

804
00:48:17,480 --> 00:48:20,600
Speaker 1: these last few days. Uh, to really expand my my

805
00:48:20,680 --> 00:48:23,640
Speaker 1: palate and my contributions to this, uh, this household. It

806
00:48:23,760 --> 00:48:25,920
Speaker 1: is intimidating, though, to be living with somebody who is

807
00:48:25,960 --> 00:48:28,359
Speaker 1: such a skilled cook because I can't. I feel like

808
00:48:28,400 --> 00:48:31,200
Speaker 1: it's always going to be put up against that and

809
00:48:31,280 --> 00:48:34,239
Speaker 1: I just have to really speed up my expertise in

810
00:48:34,280 --> 00:48:36,680
Speaker 1: a in a short amount of time to compete. Yeah.

811
00:48:36,800 --> 00:48:39,960
Speaker 1: Does she does she like grade you on a curve?

812
00:48:40,080 --> 00:48:42,600
Speaker 1: Or is she like, really, this is this is? This

813
00:48:42,640 --> 00:48:45,560
Speaker 1: is how you're going to prepare chicken. We're start, We're starting.

814
00:48:45,560 --> 00:48:48,239
Speaker 1: I'm getting accolades for for effort and initiative at all,

815
00:48:48,320 --> 00:48:50,920
Speaker 1: which sort of feels like a little pedantic. But it's fine.

816
00:48:50,960 --> 00:48:54,239
Speaker 1: I'll take word. I can go and it's a fine

817
00:48:54,280 --> 00:48:56,680
Speaker 1: texting woman. I can't see her giving you this smoke

818
00:48:56,880 --> 00:48:59,319
Speaker 1: like right, anyway, it's like the stuff that she makes

819
00:48:59,320 --> 00:49:02,840
Speaker 1: and I'm I'm four months in, five months into being vegan,

820
00:49:03,040 --> 00:49:06,319
Speaker 1: and this has been an interesting adjustment period. And but

821
00:49:06,520 --> 00:49:09,160
Speaker 1: the food that she makes is like I mean, like

822
00:49:09,200 --> 00:49:12,279
Speaker 1: everything from tacos to pizza. I I if I had

823
00:49:12,360 --> 00:49:15,120
Speaker 1: known years ago that vegan food or I guess the

824
00:49:15,160 --> 00:49:18,080
Speaker 1: word is plant based now to taste like this, I

825
00:49:18,120 --> 00:49:20,279
Speaker 1: would have not made jokes about it. I wouldn't have

826
00:49:20,320 --> 00:49:21,680
Speaker 1: had a problem with it. I would have been like

827
00:49:21,719 --> 00:49:25,239
Speaker 1: a dumb idiot about it, because it's truly, it is

828
00:49:25,280 --> 00:49:27,400
Speaker 1: the amount. And maybe it's because we live in Los Angeles,

829
00:49:27,400 --> 00:49:30,000
Speaker 1: and maybe it's we have access to great ingredients and

830
00:49:30,120 --> 00:49:33,440
Speaker 1: great restaurants, but it is, it is. I just realized,

831
00:49:33,440 --> 00:49:35,840
Speaker 1: I guess this quarantine is teaching me the more I

832
00:49:35,880 --> 00:49:39,680
Speaker 1: eat of this food, like how much anti vegan propaganda

833
00:49:39,840 --> 00:49:42,360
Speaker 1: and like jokes and ship that I just accepted my

834
00:49:42,560 --> 00:49:45,080
Speaker 1: entire life, Whereas in reality it's like not, you can

835
00:49:45,120 --> 00:49:47,680
Speaker 1: make some pretty amazing delicious ship and all the stuff

836
00:49:47,719 --> 00:49:50,880
Speaker 1: that like approximates what you were eating before. Yeah, everyone

837
00:49:50,920 --> 00:49:53,480
Speaker 1: needs that moment where they can humble themselves eating a

838
00:49:53,560 --> 00:49:57,480
Speaker 1: plant based meal and you're like that was so fucking

839
00:49:57,520 --> 00:50:00,600
Speaker 1: good and let go of my like k of man

840
00:50:00,719 --> 00:50:05,319
Speaker 1: idea of like what food is because Western media told

841
00:50:05,360 --> 00:50:08,520
Speaker 1: me I eat the fucking meat to feel like a

842
00:50:08,600 --> 00:50:14,359
Speaker 1: fucking man. Uh, let meet them. Best love plant based

843
00:50:14,360 --> 00:50:17,480
Speaker 1: with the best stuffing I ever had was like a

844
00:50:17,960 --> 00:50:23,000
Speaker 1: walnut mushroom stuffing, like a Thanksgiving that we had with

845
00:50:23,080 --> 00:50:28,000
Speaker 1: like my sisters, sophisticated vegan friends. I was like, Christ,

846
00:50:28,120 --> 00:50:31,600
Speaker 1: here we go. They're gonna push this vegan food on me.

847
00:50:31,680 --> 00:50:33,759
Speaker 1: But that that was my moment when I was like, oh,

848
00:50:33,840 --> 00:50:38,279
Speaker 1: this is better than any Thanksgiving food that I've ever had,

849
00:50:38,600 --> 00:50:42,120
Speaker 1: the like they fucking crushed it. So And for people

850
00:50:42,120 --> 00:50:45,080
Speaker 1: who might be a little weary, try and find good

851
00:50:45,160 --> 00:50:48,520
Speaker 1: junk food, vegan junk food, because that is a great

852
00:50:48,880 --> 00:50:51,560
Speaker 1: gateway food to open your eyes. You'll be like, damn that,

853
00:50:51,840 --> 00:50:54,160
Speaker 1: like because you know it doesn't it's not always like healthy,

854
00:50:54,239 --> 00:50:57,120
Speaker 1: Like you're drinking a rain drop with one grain of

855
00:50:57,160 --> 00:51:00,759
Speaker 1: glad snow. It's sucking. The junk food is probably some

856
00:51:00,760 --> 00:51:02,840
Speaker 1: of my favorite that one Mexican spob we go to,

857
00:51:03,239 --> 00:51:05,840
Speaker 1: what's a good junk food that they make? Remember that

858
00:51:05,880 --> 00:51:10,560
Speaker 1: wet burrito we'd have, Uh, that's nearest near the office.

859
00:51:10,560 --> 00:51:12,480
Speaker 1: I don't want to say exactly, but it's out here

860
00:51:12,480 --> 00:51:15,000
Speaker 1: in Los Angeles, and they have a wet burrito that

861
00:51:15,200 --> 00:51:17,919
Speaker 1: I could I would have told you has all kinds

862
00:51:17,960 --> 00:51:20,840
Speaker 1: of dairy in it. But we digress. The top recipes,

863
00:51:20,920 --> 00:51:23,680
Speaker 1: we do digress. Yeah, so let's talk about the top

864
00:51:23,760 --> 00:51:26,880
Speaker 1: things people are searching for. Oh, by the way, speaking

865
00:51:26,920 --> 00:51:31,680
Speaker 1: of Texas, I started making waves Ronchero's with American cheese

866
00:51:32,000 --> 00:51:36,200
Speaker 1: and that's like that that that took it from Mexican

867
00:51:36,280 --> 00:51:39,480
Speaker 1: to text mex In my mind, I was like, yeah,

868
00:51:39,520 --> 00:51:41,920
Speaker 1: that's a good too. Yeah, or you might catch somebody's

869
00:51:41,960 --> 00:51:45,640
Speaker 1: hands in the wrong kitchen if you came out. I

870
00:51:45,719 --> 00:51:48,560
Speaker 1: was just out. I was out of the shredded cheese

871
00:51:48,560 --> 00:51:50,759
Speaker 1: that we usually use. Got it. But Yeah. The thing

872
00:51:50,920 --> 00:51:54,760
Speaker 1: that's interesting is the over the most popular recipe overall

873
00:51:54,800 --> 00:51:59,880
Speaker 1: in the United States overall is drumroll banana bread. Mm.

874
00:52:00,239 --> 00:52:04,480
Speaker 1: I feel I have myself had banana bread already during

875
00:52:04,520 --> 00:52:06,800
Speaker 1: this quarantine, I've been the recipient of banana bread. I

876
00:52:06,800 --> 00:52:09,200
Speaker 1: don't know how many else have made I haven't. I

877
00:52:09,200 --> 00:52:13,200
Speaker 1: haven't had any banana bread. Oh well, parton part of us?

878
00:52:13,320 --> 00:52:14,920
Speaker 1: Then where are you from origin? What stayed a you

879
00:52:14,960 --> 00:52:20,200
Speaker 1: from your state's most searched item. I was born in Washington,

880
00:52:20,360 --> 00:52:22,719
Speaker 1: d C. And I lived there for seven or eight years,

881
00:52:22,719 --> 00:52:24,960
Speaker 1: and then I grew up in Maryland. Okay, well part

882
00:52:25,000 --> 00:52:29,239
Speaker 1: of Maryland. Okay, yeah, yeah, Her majesty is from Tacoma Park,

883
00:52:29,680 --> 00:52:33,719
Speaker 1: nice Maryland. Top recipe there Salmon. This is another thing.

884
00:52:33,840 --> 00:52:36,279
Speaker 1: It's been very common. There's like a few things that

885
00:52:36,280 --> 00:52:39,400
Speaker 1: are through lines I've seen, like bread is like a

886
00:52:39,520 --> 00:52:44,320
Speaker 1: very popular place, like in New England, like Maine, Massachusetts,

887
00:52:44,320 --> 00:52:47,160
Speaker 1: I think New Hampshire everyone was like searching bread, but

888
00:52:47,239 --> 00:52:50,480
Speaker 1: then other places where a lot of places were searching salmon.

889
00:52:51,120 --> 00:52:53,879
Speaker 1: New York the most search recipe does it makes sense

890
00:52:53,880 --> 00:52:56,120
Speaker 1: because it's the last thirty days and passover just happened.

891
00:52:56,200 --> 00:52:59,280
Speaker 1: Harrosa for your pass over your state or plate both

892
00:52:59,320 --> 00:53:03,719
Speaker 1: Carolina is search for pound kick. I must know because

893
00:53:03,760 --> 00:53:07,040
Speaker 1: I know we have North and South kac site gang.

894
00:53:07,640 --> 00:53:09,759
Speaker 1: What's going on? What am I missing? Do I need

895
00:53:09,760 --> 00:53:11,600
Speaker 1: to know how to make this? It's a lot of bread.

896
00:53:11,640 --> 00:53:15,719
Speaker 1: Feels like a very weird, like depression chic move. I

897
00:53:15,760 --> 00:53:18,440
Speaker 1: don't know with all this talk about this being a

898
00:53:18,520 --> 00:53:21,200
Speaker 1: new depression and I like breadlines, like why would people

899
00:53:21,400 --> 00:53:23,400
Speaker 1: we have so many food options, why would people go?

900
00:53:23,480 --> 00:53:24,920
Speaker 1: And it's like, no, I guess I don't know. This

901
00:53:25,000 --> 00:53:27,560
Speaker 1: is like this is like comforting for people. Yeah, New

902
00:53:27,600 --> 00:53:35,919
Speaker 1: Mexico they searched towards the highest search recipe tortillas Florida margarita. Yeah,

903
00:53:36,040 --> 00:53:41,640
Speaker 1: that checks out, And California is a snickerdoodle, which seems

904
00:53:42,000 --> 00:53:44,880
Speaker 1: very specific that that's the one result that has me

905
00:53:44,960 --> 00:53:46,719
Speaker 1: kind of scratching my head about this whole thing, And

906
00:53:46,760 --> 00:53:50,680
Speaker 1: I'm like, really, yeah, I I do wonder, like on

907
00:53:50,920 --> 00:53:55,760
Speaker 1: on things where they isolate different states, like top search,

908
00:53:55,960 --> 00:53:58,720
Speaker 1: I feel like a lot of the times they're doing

909
00:53:58,760 --> 00:54:03,200
Speaker 1: something statistically to like add variety. I feel like a

910
00:54:03,200 --> 00:54:06,319
Speaker 1: lot of states would have the same recipe if you

911
00:54:06,760 --> 00:54:11,880
Speaker 1: didn't like tweak it in somewhere we're just lurking up

912
00:54:12,040 --> 00:54:17,160
Speaker 1: hamburger or hamburger meat, which I'm was curious like what

913
00:54:17,239 --> 00:54:19,279
Speaker 1: someone was trying to achieve by searching that, Like are

914
00:54:19,280 --> 00:54:22,400
Speaker 1: they right, well that's what I mean, Like are they

915
00:54:22,440 --> 00:54:26,200
Speaker 1: making their own blends of like chuck and brisket and

916
00:54:26,239 --> 00:54:28,800
Speaker 1: like what are they doing? Are they going that wild

917
00:54:28,840 --> 00:54:30,879
Speaker 1: on it? Or they are they trying to figure out

918
00:54:30,920 --> 00:54:35,840
Speaker 1: like how do you make a Hamburger. What is the

919
00:54:35,880 --> 00:54:39,000
Speaker 1: criteria through Google? I just imagine like people trying to

920
00:54:39,040 --> 00:54:41,640
Speaker 1: get like, you know, it just feels like it's it's

921
00:54:41,640 --> 00:54:43,640
Speaker 1: a big deal to get on any list these days,

922
00:54:43,680 --> 00:54:45,600
Speaker 1: just trying to get your pr out there. I imagine

923
00:54:45,680 --> 00:54:47,680
Speaker 1: like snicker Doodles somehow found their way to get on

924
00:54:47,719 --> 00:54:54,880
Speaker 1: this list and big all right, And finally, uh, speaking

925
00:54:54,880 --> 00:55:00,200
Speaker 1: to Hamburger Meat, it turns out Wendy's is struggling. They're

926
00:55:00,200 --> 00:55:05,800
Speaker 1: out of beef some locations. Are you made the mistake

927
00:55:05,880 --> 00:55:13,120
Speaker 1: of of selling only fresh beef in their restaurants? Bad move, assholes.

928
00:55:14,040 --> 00:55:19,400
Speaker 1: Because now that the domestic beef supply chain has been disrupted,

929
00:55:20,360 --> 00:55:24,080
Speaker 1: and because CEOs are unwilling to spend the money to

930
00:55:24,400 --> 00:55:29,680
Speaker 1: properly protect their employees, Wendy's is having to cut beef

931
00:55:29,719 --> 00:55:32,399
Speaker 1: from the menus at some of their restaurants, which must

932
00:55:32,400 --> 00:55:36,719
Speaker 1: be an awful feeling for people who like when you

933
00:55:36,800 --> 00:55:39,600
Speaker 1: have a fast food place you go to and it's

934
00:55:39,640 --> 00:55:42,320
Speaker 1: been dependable and you pull up and that thing is

935
00:55:42,360 --> 00:55:49,719
Speaker 1: not there. I don't wish that on anyone except Donald Trump. Yeah, yeah,

936
00:55:49,760 --> 00:55:53,920
Speaker 1: what's his what's his order? McDonald's. It's like big big Max.

937
00:55:53,920 --> 00:55:56,200
Speaker 1: And then other one's just like the good part of

938
00:55:56,200 --> 00:55:59,000
Speaker 1: the pizza, which is just the cheese and topping's not

939
00:55:59,040 --> 00:56:02,799
Speaker 1: the bread part which is so childish. But again, look,

940
00:56:02,880 --> 00:56:05,120
Speaker 1: bottom line is you don't protect workers, you don't get beef.

941
00:56:05,320 --> 00:56:09,600
Speaker 1: So yes, super producer Anajosnier is saying his order is

942
00:56:09,680 --> 00:56:14,279
Speaker 1: filet oh fish. Huh damn weird choice. I wonder if

943
00:56:14,320 --> 00:56:17,040
Speaker 1: he ever rocks the mix surf and turf. Yeah, the

944
00:56:17,080 --> 00:56:21,239
Speaker 1: double quarter pounder with the filet inside. He's a man

945
00:56:21,280 --> 00:56:24,319
Speaker 1: of taste. He has a man of taste, and that

946
00:56:24,440 --> 00:56:29,600
Speaker 1: taste is sodium. Well, Ben, it has been a pleasure

947
00:56:29,719 --> 00:56:32,920
Speaker 1: having you on the daily zy Guist. Where can people

948
00:56:33,160 --> 00:56:36,000
Speaker 1: find you and follow? You can find me on Twitter

949
00:56:36,160 --> 00:56:41,160
Speaker 1: and Instagram at that benchion right, And is there a

950
00:56:41,200 --> 00:56:45,839
Speaker 1: tweet or some other work of social media you've been enjoying. Yes,

951
00:56:45,920 --> 00:56:49,080
Speaker 1: I want to shout out this tweet by Alison Rosen. Uh,

952
00:56:49,120 --> 00:56:51,600
Speaker 1: this is not coming true because it turns out that

953
00:56:51,840 --> 00:56:54,040
Speaker 1: Kim Jong hun, as far as we know, did not

954
00:56:54,200 --> 00:56:57,680
Speaker 1: die and was replaced by a body stunt double. But uh,

955
00:56:57,880 --> 00:57:00,319
Speaker 1: it says that if Kim Jong Gun's sister take so over,

956
00:57:00,400 --> 00:57:02,839
Speaker 1: North Korea will have a female leader. Before we do.

957
00:57:03,000 --> 00:57:09,920
Speaker 1: I hope she's likable. Miles where can people find you on?

958
00:57:09,920 --> 00:57:13,960
Speaker 1: What tweet you've been enjoying? Oh, you can find me Twitter, Instagram,

959
00:57:14,080 --> 00:57:18,160
Speaker 1: PlayStation Network, Miles of Gray. Also on my other podcast

960
00:57:18,240 --> 00:57:21,760
Speaker 1: for twenty Day Fiance talking about ninety Day Fiance, the

961
00:57:22,280 --> 00:57:27,400
Speaker 1: great show that's absolutely nourishing our trash souls. Uh. Some

962
00:57:27,440 --> 00:57:30,960
Speaker 1: tweets that I like, Yes, let's me allow me to

963
00:57:31,360 --> 00:57:37,880
Speaker 1: scroll down. Uh. First one is from Sean Paul Shana Paul. Uh.

964
00:57:37,920 --> 00:57:41,000
Speaker 1: He was re quote tweeting somebody who didn't even tag

965
00:57:41,080 --> 00:57:43,400
Speaker 1: him and just said, Sean Paul did not have to

966
00:57:43,480 --> 00:57:46,080
Speaker 1: go so hard in the early two thousand's like that

967
00:57:46,120 --> 00:57:49,000
Speaker 1: with like stank face emoji and the flame emoji. And

968
00:57:49,080 --> 00:57:53,480
Speaker 1: he just comes back quote tweet all caps. I did, Okay,

969
00:57:53,480 --> 00:57:57,320
Speaker 1: thank you, Seana Paul. Um. And then another one Jack

970
00:57:57,360 --> 00:57:59,120
Speaker 1: and I don't know if Ben, if you also loved

971
00:57:59,160 --> 00:58:01,720
Speaker 1: I think you should leave of now. Um, but this

972
00:58:01,800 --> 00:58:04,400
Speaker 1: is a great reference to that show. Uh. Was just

973
00:58:04,520 --> 00:58:09,480
Speaker 1: from at Claire Lizzie Claire Claire Lower where it's two images.

974
00:58:09,520 --> 00:58:12,560
Speaker 1: The first one just says Grimes gives birth welcome's first

975
00:58:12,640 --> 00:58:15,360
Speaker 1: child with Elon Musk, and then the next image is

976
00:58:15,440 --> 00:58:18,840
Speaker 1: from that like baby beauty pageant sketch that they did

977
00:58:18,880 --> 00:58:21,240
Speaker 1: on this show, and so it's the one that had

978
00:58:21,280 --> 00:58:24,040
Speaker 1: like all the biker ship the baby called Bart Harley

979
00:58:24,160 --> 00:58:27,800
Speaker 1: Jarvis and then the captions just say hard rock music

980
00:58:27,840 --> 00:58:36,080
Speaker 1: playing audience booing perfect. Uh. You can find me on

981
00:58:36,080 --> 00:58:40,520
Speaker 1: Twitter at Jack Underscore O'Brien. Some tweets I've been enjoying.

982
00:58:41,120 --> 00:58:44,960
Speaker 1: Uh Noah, Garfinkel tweeted, the Wallennium has been fucking awful.

983
00:58:46,760 --> 00:58:49,640
Speaker 1: Butcher tweeted, hell hath no fury like a white person

984
00:58:49,720 --> 00:58:54,400
Speaker 1: mildly inconvenienced. Uh. Megan Gaily tweeted I've done everything I

985
00:58:54,440 --> 00:59:05,120
Speaker 1: can for Jay Crew Uh and perfect, and then LB

986
00:59:05,400 --> 00:59:09,760
Speaker 1: hunked Tears tweeted, which is a great name. Being a

987
00:59:09,800 --> 00:59:12,120
Speaker 1: funk rather than a merry or a kill is nothing

988
00:59:12,160 --> 00:59:15,040
Speaker 1: to brag about. It's the lowest commitment. Kill is the

989
00:59:15,120 --> 00:59:19,919
Speaker 1: highest commitment, which is why it's the biggest compliments, don't Yeah?

990
00:59:20,040 --> 00:59:26,320
Speaker 1: And then uh, finally, Mario Girl seventeen tweeted, what's the matter? Baby,

991
00:59:26,480 --> 00:59:32,480
Speaker 1: barely touched your Baja blast. I got that sent to

992
00:59:32,520 --> 00:59:35,840
Speaker 1: me quite a bit by Zeke Gang and I appreciate it.

993
00:59:36,600 --> 00:59:39,360
Speaker 1: You can find us on Twitter at Daily Zeygeist. We're

994
00:59:39,400 --> 00:59:42,640
Speaker 1: at the Daily zeitgeis on Instagram, we have Facebook champage

995
00:59:42,640 --> 00:59:45,680
Speaker 1: and a website Daily zycheis dot com where we post

996
00:59:45,720 --> 00:59:49,760
Speaker 1: our episodes and our footnotes. We link off to the

997
00:59:49,800 --> 00:59:52,959
Speaker 1: information that we talked about in today's episode, as well

998
00:59:53,000 --> 00:59:56,640
Speaker 1: as the song we ride down on miles. What's it

999
00:59:56,680 --> 01:00:00,440
Speaker 1: gonna be today? Uh? This is a track from French

1000
01:00:00,560 --> 01:00:05,280
Speaker 1: artist band but a Melody Melodies Echo Chamber. Uh. And

1001
01:00:05,360 --> 01:00:07,720
Speaker 1: this track is called sheer M s H I R

1002
01:00:07,760 --> 01:00:10,960
Speaker 1: I Am and her music is really dope, very like

1003
01:00:11,080 --> 01:00:15,840
Speaker 1: psych pop, rocky but really interesting production. Um so it's

1004
01:00:15,840 --> 01:00:18,720
Speaker 1: got a little got a hip tang to it. So

1005
01:00:18,840 --> 01:00:23,120
Speaker 1: check this one out from a Melodies Echo Chamber. Alright, well,

1006
01:00:23,480 --> 01:00:26,080
Speaker 1: the Daily zey guys the production of I Heart Radio.

1007
01:00:26,160 --> 01:00:28,400
Speaker 1: For more podcasts from my Heart Radio is the I

1008
01:00:28,520 --> 01:00:32,200
Speaker 1: Heart Radio app, Apple podcast or wherever you listen to

1009
01:00:32,280 --> 01:00:35,840
Speaker 1: your favorite shows. That's gonna do it for this morning,

1010
01:00:35,880 --> 01:00:39,520
Speaker 1: We're going to ride out on that hip tang, my

1011
01:00:39,640 --> 01:00:45,080
Speaker 1: second favorite flavor of tang behind orange. Uh. And we'll

1012
01:00:45,120 --> 01:00:47,240
Speaker 1: be back this afternoon to tell you what's trending. We

1013
01:00:47,280 --> 01:01:02,400
Speaker 1: will talk to you then bye. Enchoanted which my son

1014
01:01:03,560 --> 01:01:07,320
Speaker 1: you try to hit my thought, and you talk, get

1015
01:01:07,440 --> 01:01:23,800
Speaker 1: cold on the say, Call long, The feelings of the

1016
01:01:24,000 --> 01:01:24,280
Speaker 1: foll