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Speaker 1: Hey, guys, I know we're uh, we're releasing this on

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Speaker 1: election day. It has nothing to do with election day,

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Speaker 1: but we thought maybe you might need a little distraction

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Speaker 1: today so you're not sitting around worrying and freaking out.

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Speaker 1: Just so listen for an hour and relax. It's a

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Speaker 1: great show. And don't forget to go vote.

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Speaker 2: Go vote.

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Speaker 1: If you haven't voted, go vote first and then come back.

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Speaker 1: We'll wait, just pause it and go vote and then

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Speaker 1: come back. All right, Scotty, are you ready?

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Speaker 2: Kurt? I am ready.

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Speaker 1: Man arrested after repeatedly calling nine to one one about restaurants,

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Speaker 1: small clans.

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Speaker 3: Oh yeah, let's get into bananas.

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Speaker 4: Don't world up. He would tell you my sillion pieces.

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Speaker 1: Ladies and gentlemen. Welcome to Bananas. I am Kurt Brown or.

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Speaker 3: I am Scotty landis Banana Boy number two. And thank

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Speaker 3: you for listening to the silliest little podcast there ever

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Speaker 3: was Kurt. Before we bring on our guests, I just

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Speaker 3: want to give a shout out real quick. I've been

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Speaker 3: getting a lot of calls on the Banana's phone from nurses,

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Speaker 3: tons from nurses coming off long shifts, and I just

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Speaker 3: want to say thank you. I guess we can. We

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Speaker 3: could dedicate this one to the nurses out there.

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Speaker 1: Yes, yeah, and as we all know, I don't know

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Speaker 1: if you guys know, my mom was a pediatric nurse

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Speaker 1: for fifty years. Nurses hold a very soft spot in

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Speaker 1: my heart. You guys are doing amazing work, and often

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Speaker 1: I find disrespected by doctors, and so I say, fuck

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Speaker 1: doctors with nurses.

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Speaker 2: Well until next week. Then we'll dedicate that.

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Speaker 3: Yeah, then we'll tell the nurses to Yeah, but April

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Speaker 3: and Texas and Samantha and Maine and the one young

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Speaker 3: lady who called me crying. Uh, we're glad to make

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Speaker 3: you laugh. Thanks for listening. This one's for y'all. Kurt,

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Speaker 3: get into.

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Speaker 1: It, and thank you for doing what you're doing.

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Speaker 2: Now.

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Speaker 1: God, it's tough, all right. We have such an amazing

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Speaker 1: guest today. Very excited. She is an Emmy Award winning journalist,

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Speaker 1: science communicator, television personality, author.

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Speaker 2: And podcast amazing.

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Speaker 1: She is the science correspondent on National Geographics, Brain Games,

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Speaker 1: and the creator and host of the weekly science podcast

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Speaker 1: Talk Nerdy. Please welcome Kara Santa Maria.

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Speaker 5: Yeah, hey, guys, Hey, are you hi?

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Speaker 6: That makes me sound fancy?

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Speaker 1: Yeah, you are fancy.

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Speaker 2: He yes, I.

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Speaker 5: Don't feel like it both days. Most days, I'm just

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Speaker 5: slogging through. Man.

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Speaker 3: That's kind of what it's about right now. We're all

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Speaker 3: just kind of surviving. I'm counting it by handles of

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Speaker 3: Tito's at this point. I'm like, I'm like twenty five

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Speaker 3: handles of Tito's in this year.

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Speaker 5: I'm literally eating a Trader Joe's protein muffin while we're recording.

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Speaker 1: It's a protein muffin in a little cup.

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Speaker 6: Yeah, you microwave it. It's like so epic.

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Speaker 2: You do understand science. That's cool.

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Speaker 1: This is the best part I love to get. As

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Speaker 1: we always say, super smart people to talk about the

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Speaker 1: dumbest things in the world. Do you want to hear

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Speaker 1: about this dumb guy?

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Speaker 7: Kara?

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Speaker 5: Yes, absolutely, I love hearing about dumb guys. Is he

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Speaker 5: in Florida?

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Speaker 1: I think he is? I bet Yep, it's in Stuart, Florida.

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Speaker 2: Of course, there it is.

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Speaker 6: Did I guess that was my deductive reason.

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Speaker 1: This one was sent in again by at Matt dot

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Speaker 1: TeV dot AM's or Ans. I don't know, but this

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Speaker 1: is a second one for Matt. Congratulations.

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Speaker 2: I think it's Matt Evans. Is it Matt Evans.

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Speaker 3: When you're saying that his name might be Matt Evans.

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Speaker 1: He's put the periods in real weird places, all right,

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Speaker 1: So a Matt thank you for this from Fox News.

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Speaker 1: This is by Alexander Diebler. The debes coming in this

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Speaker 1: one okay man in Stuart, Florida found himself in trouble

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Speaker 1: with the law after trying to report a restaurant for

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Speaker 1: having to the police for having small clams. Nelson Augusta

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Speaker 1: ordered a seafood meal at Krabby Seafood Shack in the

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Speaker 1: coastal town, but was disappointed upon seeing the size of

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Speaker 1: the clams. On in the incident report, an employee warned

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Speaker 1: Augusto about the size of the clams before he placed

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Speaker 1: his order, but he insisted on having clams. After the

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Speaker 1: fifty one year old received his food, he complained to

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Speaker 1: the restaurant about the size of the clams and the

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Speaker 1: meal quote. He was complaining that the clams he were

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Speaker 1: eating were so small he didn't want to pay for them,

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Speaker 1: said the police sergeant. The restaurant responded to his complaints

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Speaker 1: by giving him another order of clams for free, so generous.

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Speaker 1: Augusto still felt the clams were too small and called

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Speaker 1: nine to report them. Uh. And then in the nine

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Speaker 1: one one report he says, I ordered something and it

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Speaker 1: was extremely so small. He was advised by the dispatcher

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Speaker 1: to call the non emergency police line, which she gave

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Speaker 1: him the number four twice. Soon after, Augusta called nine

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Speaker 1: one one two more times to complain about the clams,

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Speaker 1: and then that's it. They arrested him. Ah good, I

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Speaker 1: think that's good.

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Speaker 2: Do you know what I mean?

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Speaker 5: Yeah, that's an abuse of the utilization, Like his tiny

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Speaker 5: clams may have prevented somebody who was having a heart

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Speaker 5: attack from getting the help he needs.

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Speaker 1: Exactly what I can you can you tie up that?

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Speaker 5: Yeah?

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Speaker 1: You could tie up operators on nine one?

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Speaker 6: Absolutely?

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Speaker 1: Yeah.

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Speaker 6: Yeah.

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Speaker 3: Also to play Devil's advocate, how how small were these clams?

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Speaker 3: For a rest for a seafood restaurant called Krabby's to

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Speaker 3: tell somebody over the phone that these are there? Why

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Speaker 3: are they serving these? Are they smaller than a penny?

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Speaker 1: Like?

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Speaker 3: Were they comically small? We're gonna have to find out.

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Speaker 5: God true, Like like a decent restaurant takes things off

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Speaker 5: the menu if they can't source eat good ingredients, right,

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Speaker 5: And maybe maybe I'm biased and spoiled because I live

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Speaker 5: in LA and like, we have really good restaurants here.

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Speaker 5: But I've definitely been to restaurants before where I'm like,

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Speaker 5: I'd love the blah blah blah. They're like, we, you know,

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Speaker 5: the hazel nuts supply is not where it needs to be,

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Speaker 5: so we're not serving that dish right now. Oh yeah,

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Speaker 5: And you're like, oh okay, all right. But instead they're

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Speaker 5: like they're really small.

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Speaker 1: They're really small, you still want them. This is Crabby's

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Speaker 1: Seafood Shack, guys. It's a shack.

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Speaker 2: It's a shack.

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Speaker 1: They're gonna they get what they get, and they're giving

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Speaker 1: you what they get.

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Speaker 2: That's it.

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Speaker 1: That's how the shack works.

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Speaker 5: I yes, I love too that the dispatcher was like

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Speaker 5: call the non emergency police sees. No, she should have

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Speaker 5: been like, hang up the phone and don't call back.

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Speaker 6: This is ridiculous.

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Speaker 5: And even the cop you read like a specific quote

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Speaker 5: from what the cop said in the police repert why

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Speaker 5: did he take a polee?

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Speaker 6: Why wasn't he just like goodbye?

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Speaker 1: This is a way cut.

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Speaker 2: That's true.

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Speaker 1: It's amazing too. It's like to call the NANO, Like

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Speaker 1: imagine calling three one one, Like even on the three

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Speaker 1: one one app there is definitely no section for small clams,

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Speaker 1: do you know what I mean? It's like you need

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Speaker 1: a tree cut, That's pretty much it.

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Speaker 3: Yeah, it's also just like keep sending this guy clams

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Speaker 3: until he stops calling, just keep sending him order after

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Speaker 3: order until he's just like fine, it's fine, it's fine.

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Speaker 3: Like at some point you just have to retaliate in

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Speaker 3: this world and just be like, you know what, We're

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Speaker 3: gonna just put bags and bags of tiny clams right

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Speaker 3: outside your door until you stop calling nine one one, like.

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Speaker 6: Yeah, just mail them through like the snail mail.

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Speaker 5: So he's just getting lots of room temperature clams for

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Speaker 5: weeks on end.

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Speaker 3: This guy, And what is it but a misdemeanor. I think,

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Speaker 3: I don't know if it's like a felony.

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Speaker 1: Maybe it is, but they didn't even they didn't actually

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Speaker 1: even take him in, so they arrested him, but they

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Speaker 1: never let he never left his house, so he's not

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Speaker 1: currently in jail. He just has to go to court.

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Speaker 3: Man.

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Speaker 5: Can I just say, and this is gonna be my

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Speaker 5: like social justice age that I need to scratuate.

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Speaker 6: That right there? Is he a white man.

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Speaker 1: Let's see, we have to say that Nelson Augusto a G.

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Speaker 2: Could go either way, could go anywhere, could.

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Speaker 6: Go either way.

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Speaker 5: But I would definitely be interested to see if that

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Speaker 5: is like absolute white privilege right there, being able to

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Speaker 5: abuse the emergency line and then the cops come and

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Speaker 5: like take time out of their day and then say, like,

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Speaker 5: go on.

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Speaker 1: It's one of two things. It's one of two things.

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Speaker 1: It's white privilege or it's meth. And because I've found these.

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Speaker 6: Two things are not mutually excluded.

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Speaker 1: That they are not. But I've all still found like

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Speaker 1: repeatedly calling nine one one seems to be a thing

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Speaker 1: that people on meth do do. It's like that asmissive

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Speaker 1: compulsive kind of like a part of it.

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Speaker 5: Yeah, it definitely makes sense if you're like under the

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Speaker 5: influence of something that is causing you to feel kind

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Speaker 5: of an immediate anxiety.

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Speaker 6: Yes, and you're trying to get that relieved.

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Speaker 5: Unfortunately, that's when you should probably take their access to

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Speaker 5: the telephone exact way.

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Speaker 1: Have you guys ever heard that one where the guy

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Speaker 1: called because he had he ate too many pot brownies?

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Speaker 2: Yes, the actual yes.

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Speaker 6: And he's like I think I'm dying.

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Speaker 3: Oh that wasn't just a guy that was a cop,

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Speaker 3: that wasn't all his duty.

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Speaker 5: But I can't remember did he think he was dying

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Speaker 5: because of the bo or did he think he was

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Speaker 5: already dead.

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Speaker 3: It was like he and his wife had eaten them

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Speaker 3: and then he was sure he was dying and he knew.

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Speaker 3: You can hear like the tremble in his voice that

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Speaker 3: he knows that he's a cop and he's going to

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Speaker 3: get in trouble for it. I actually ran in a

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Speaker 3: show called What's Your Emergency that was real nine one

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Speaker 3: one calls that were funny ish but then re enacted

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Speaker 3: by comedians and actors, and we did the pilot and

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Speaker 3: the best one was this guy calls, just screaming, oh.

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Speaker 3: And so in certain states, all of that stuff's public record.

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Speaker 3: It's like you can just get it. Florida is one

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Speaker 3: of those states. That's probably why this story exists. Yeah,

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Speaker 3: So this guy calls and the first thing you hear

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Speaker 3: is just oh, and so you're like, here we go,

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Speaker 3: and they're like, sir, He's like, I'm turning into a werewolf.

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Speaker 3: And they goes, sir, you okay, because like my stomach

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Speaker 3: hurts so bad, I'm turning into a were wolf and

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Speaker 3: they're like, is there anybody there with you? And then

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Speaker 3: he puts on his step dadd is like step uncle

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Speaker 3: some guy. And the guy's like, what's up with him?

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Speaker 3: And he's just like, he's over here.

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Speaker 2: I don't know.

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Speaker 3: He's in pain. He tells me he's turned into a

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Speaker 3: were wolf. It's a full moon. And they're like okay,

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Speaker 3: and he's like, have you tried giving him pepto bismo?

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Speaker 2: Do?

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Speaker 3: And it works and the guys and then they just

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Speaker 3: kind of hang up. It's like a ten minute call.

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Speaker 3: It's on YouTube, you can go find it. But it's

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Speaker 3: just like he's just like yeah, and he takes bepto

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Speaker 3: bismo and then stops turning into a world.

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Speaker 1: Oh my god. I love that. Also, I know, I

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Speaker 1: love that they knew exactly what to do.

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Speaker 6: Yes, me too, That's great.

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Speaker 5: And also I feel like that is a legitimate utilization

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Speaker 5: of emergencies.

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Speaker 6: Yes, like he was, yeah, he actually.

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Speaker 5: Thought he was turning into a wear well, whether that

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Speaker 5: was a mental health issue or he just is a

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Speaker 5: believer and he did not feel well and was like

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Speaker 5: I think I read.

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Speaker 6: About this somewhere. This is the first sign.

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Speaker 5: But either way, he was in crisis, and they helped

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Speaker 5: him out of his crisis, and I think that's amazing.

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Speaker 3: There was another one I can mention really briefly. It's

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Speaker 3: probably a forty second call, and it's exactly to your point, Karen.

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Speaker 3: It's like this woman calls nine one one. She is

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Speaker 3: in her car in a Walgreens parking lot and it's

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Speaker 3: getting very hot and her car won't start, and she's

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Speaker 3: starting to panic and she's saying, it is so hot,

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Speaker 3: and somebody comes over here and my battery's dead and

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Speaker 3: I need help because I can't breathe and it's getting

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Speaker 3: so hot in here. And then nine to one one

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Speaker 3: operator dispatcher is a woman who just goes, ma'am, just

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Speaker 3: get out of the car. She goes, it's in a

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Speaker 3: electronic lock and I cannot get out, and she goes, ma'am,

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Speaker 3: can you just reach over and unlock the car? And

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Speaker 3: she goes, can I but and then she call them.

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Speaker 3: She goes, yeah, okay, that worked, and then she just

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Speaker 3: she forgot you could unlock manually unlock your car. And

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Speaker 3: she's sitting in her dead batteried car in a Walgreen's

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Speaker 3: parking lot, sweating, thinking she's good. I mean, this is

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Speaker 3: these people, these dispatchers, should get paid twenty percent more.

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Speaker 2: It's crazy.

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Speaker 5: It's interesting how much your cognitive capabilities are, like really.

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Speaker 6: Overridden when you're in panic mode.

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Speaker 5: I actually just recently did a training because I started

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Speaker 5: I'm working on my PhD in clinical psychos now, so

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Speaker 5: I'm like kind of in my last go of my

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Speaker 5: clinical predoctoral hours that I have to collect before I

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Speaker 5: can do my internship. Don't ask me why. As somebody

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Speaker 5: in her late thirties, I thought it would be a

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Speaker 5: good idea school. But so I am doing a rotation

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Speaker 5: at a big hospital here in Los Angeles, and there's

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Speaker 5: a law in LA. It's not the hospital, it's the

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Speaker 5: actual LA city law due to some historical.

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Speaker 6: Not great things that you have to take this really

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Speaker 6: intensive fire safety train.

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Speaker 2: Wow.

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Speaker 5: Yeah, really, it's like a four hour intensive fire safety

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Speaker 5: training anybody who works in an LA hospital. So I'm

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Speaker 5: sitting in this training and I'm learning all sorts of things,

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Speaker 5: like here we go, this is a fun quiz.

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Speaker 6: What is the.

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Speaker 5: Number one thing to remember in a fire that nobody

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Speaker 5: does and could probably prevent like ninety percent of debt.

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Speaker 1: Don't open doors.

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Speaker 6: Closed doors. Did you do the same training. That's amazing.

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Speaker 6: Most people do not know that.

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Speaker 5: So like it's not just don't open doors, but close

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Speaker 5: all doors behind you if you're exiting, if you are

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Speaker 5: stuck and there's a fire between you and the front door,

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Speaker 5: or like you can't get outside a don't try to

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Speaker 5: run through the fire because you might just like smoke inhale,

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Speaker 5: drop it in your tracks, and then then there's a

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Speaker 5: whole other mess that the fire department has toal with it.

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Speaker 5: Let's say you're in your bedroom, close the door, open

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Speaker 5: the window, breathe the fresh air. All doors in California

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Speaker 5: are fire rated doors, so they all provide you protection.

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Speaker 5: It's legal, like it's a manufacturer requirement, and they're different

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Speaker 5: fire ratings, like in a hospital you might have a

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Speaker 5: two hour door. You might just have a twenty minute

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Speaker 5: day when you're like crappy apartment, but still it's enough

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Speaker 5: time for the fire department generally to get to you,

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Speaker 5: to put out the flames and then take you away.

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Speaker 5: And he told so many stories of people like their

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Speaker 5: apartment caught on fire and they ran fleeing, and even

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Speaker 5: though they were safe, they forgot or they didn't think

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Speaker 5: to close doors behind them on the way, and so

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Speaker 5: every other apartment caught off fire, multiple people would die.

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Speaker 6: I mean, it's like the number one that.

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Speaker 5: You should always do is close doors, and people don't

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Speaker 5: know it. And I think that we often do exactly

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Speaker 5: the opposite of what we're supposed to do when we're

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Speaker 5: in a panic situation. Like if you're on fire physically right,

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Speaker 5: you're supposed to stop dropping and roll.

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Speaker 6: Most people run, yeah, which is the.

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Speaker 1: One worst thing to do. Jump in the toilet.

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Speaker 5: It's like I'm running and I'm the flames are just

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Speaker 5: getting bigger, and I'm also catching things on fire as

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Speaker 5: I It's like the exact opposite of.

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Speaker 6: What you should do.

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Speaker 3: I cut out the first two I just roll. I

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Speaker 3: just as soon as I'm on fire, I'm rolling. I'm

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Speaker 3: not even stopping. I'm just I'm not stopping. I'm not dropping.

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Speaker 3: I'm just gonna start rolling the second I see even

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Speaker 3: when I smell smoke, I roll around.

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Speaker 6: And do you know, do you know what this this

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Speaker 6: fire fire officer?

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Speaker 5: What has got firefighter actually told us we should do

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Speaker 5: if somebody else is on.

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Speaker 6: Fire, a blanket trip them, oh, because like.

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Speaker 5: Get them on the ground, no matter what you do.

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Speaker 5: You could tackle them, you could kick their foot out

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Speaker 5: underneath them, get them on the ground so they can roll,

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Speaker 5: or so you can, yes, mother the flames, but get

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Speaker 5: them on.

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Speaker 1: Oh wow, that's so I love I love this. I

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Speaker 1: love all this information I know.

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Speaker 2: I learned so awesome. Wow.

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Speaker 1: And that's why in the in the UH everywhere in

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Speaker 1: a hospital has the double closing doors that automatically yeas

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Speaker 1: on every single floor.

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Speaker 5: Yeah, so like when the fire alarm goes off, and

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Speaker 5: that's the other thing he said, He's like.

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Speaker 6: Pull the fire alarm.

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Speaker 5: We were taught so much as kids because we're trying

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Speaker 5: to avoid like jokes and things. But like if there's

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Speaker 5: a fire, even if you put it out on your own,

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Speaker 5: pull the fire alarm because it might reignite, there may

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Speaker 5: be other smoke problems, like they you need to alert

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Speaker 5: people and so. And also in big buildings like that,

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Speaker 5: when you pull the fire alarm, all the fire doors

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Speaker 5: close automatically, sprinklers go off in certain zones. Like there's

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Speaker 5: mitigation efforts there that people don't realize are all a

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Speaker 5: chain reaction.

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Speaker 1: I remember I was in college. We had a house

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Speaker 1: in Baltimore, Maryland, and we had this big house and

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Speaker 1: like we're all kind of asleep. It's like Saturday morning.

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Speaker 1: And then our friend, our roommate, Darby, had decided that

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Speaker 1: like he was done. I think it was Darby. He

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Speaker 1: broke up with his girlfriend and so he was going

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Speaker 1: to burn every letter smart written her. And so he

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Speaker 1: was in the backyard burning all of these like poems

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Speaker 1: and like letters smart aside outside true. But then we're

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Speaker 1: woking up By and there's sixteen firefighters, someone called the

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Speaker 1: firefighters on Darby, who's just like this little punk kid

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Speaker 1: who had just been writing all of his heart and

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Speaker 1: he's just heartbroken and burning letters in the backyard. And

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Speaker 1: then we have these like a Jax and Hercules type

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Speaker 1: men like running through our place with giant staffs with

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Speaker 1: like hooks on them, and every hungover and it's terrified.

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Speaker 1: Got his Saturday boarding?

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Speaker 6: Oh Darby, how did it end up?

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Speaker 1: Like?

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Speaker 6: Were they did? They commiserate where they're like, oh, bro,

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Speaker 6: I'm so sorry to.

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Speaker 1: Get fill up a fill up a bowl with water.

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Speaker 1: We filled up a bowl with water and then they

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Speaker 1: poured it on there and then they all walked out.

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Speaker 2: Oh Darby, oh.

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Speaker 1: Derby, all right, it's gotta give me another one.

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Speaker 2: Sure.

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Speaker 3: This one is in honor of Carol also co hosts

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Speaker 3: The Skeptics Guide to the Universe and James Randy died

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Speaker 3: this week.

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Speaker 1: He did.

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Speaker 2: Did you know him? Did you meet him many times? Yeah?

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Speaker 6: Many times.

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Speaker 5: He was a big friend. I mean, he was a

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Speaker 5: huge supporter of the show. Like obviously he was an

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Speaker 5: architect of the skeptic movement. So when SGU fifteen years

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Speaker 5: ago started, I had nothing to do with the show

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Speaker 5: when it started.

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Speaker 6: He he always worked with them. They were like best friends.

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Speaker 5: I came on about five six years ago, but even

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Speaker 5: just in that amount of time, I probably met him

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Speaker 5: a dozen I've sat on.

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Speaker 6: Panels with him. He's been on the show fascinating.

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Speaker 3: Massive los, Yeah, massive loss and for the for the

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Speaker 3: ban animals that don't know, there's a documentary that's wonderful

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Speaker 3: about him. He wrote a book called Flimflam that I

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00:19:05,760 --> 00:19:08,200
Speaker 3: feel like everybody should have on their bookshelf, no matter what.

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Speaker 3: It's Basically he debunks mentalists and like some types of homeopathy,

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Speaker 3: and he just basically looked for things that didn't seem

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Speaker 3: like they were real and then would figure including magic.

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Speaker 3: He would he would figure out magic tricks. This guy

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Speaker 3: was like somebody that got in there and would be like.

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Speaker 6: Oh yeah.

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Speaker 5: And he was a magician too, like a really really

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Speaker 5: respected magician.

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Speaker 2: Interesting guy.

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Speaker 3: Our friend Kurt and I have a friend named Nick

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Speaker 3: Pruer who does this thing called found Footage Festival. And

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Speaker 3: when James when Randy died, he posted that he went

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Speaker 3: and saw him giving a lecture where he opened the

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Speaker 3: lecture this is when he was in his eighties. He

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Speaker 3: opened a bottle of herbal sleeping pills and he proceeded

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Speaker 3: to take fifty of them in a row with water

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Speaker 3: swaing at the beginning of the beginning of his presentation,

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Speaker 3: just to prove. And then this eighty year old man,

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Speaker 3: after taking fifty herbal sleeping pill just was like these

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Speaker 3: aren't real and I'm gonna and then talk for two

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Speaker 3: hours about other things.

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Speaker 1: That oh, that's so great. That go to is the best.

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Speaker 2: Yeah, I love that so much.

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Speaker 1: And I love that away.

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Speaker 3: Here's a story in uh that parallels that. So this

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Speaker 3: was from Jemma Carr who sent it to us on Instagram.

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Speaker 3: Thank you so much, and written by Alexandra Diebler of

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Speaker 3: Fox News.

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Speaker 2: What I knows, deebs.

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Speaker 3: When you think great work, you think Alexander Diebler. She

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Speaker 3: types internet stuff better than almost anybody. Peraneum Sonning leaves

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Speaker 3: Josh Brolin's crazy burned as doctor's warren against viral wellness trend.

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Speaker 3: Per neeum Sonning leaves Josh Brolin quote crazy burned as

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Speaker 3: doctor's worn against viral wellness trend. Okay Sun's out buns out.

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00:20:53,840 --> 00:20:56,560
Speaker 3: See Alexandra knows how to grab you with the first

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Speaker 3: sentence I'm.

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Speaker 2: In, I'm in, I love her.

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00:20:59,480 --> 00:21:03,280
Speaker 3: A contra vers shoal new wellness practice that encourages tanning

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00:21:04,040 --> 00:21:06,560
Speaker 3: one of the body's more delicate areas has made.

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Speaker 2: Its way to Hollywood shocking Oh.

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Speaker 3: No too seemingly disastrous effects. Actor Josh Brolin tried out

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Speaker 3: the perineum sunning. Now, for those listening home that don't

444
00:21:17,000 --> 00:21:19,760
Speaker 3: know what a parandem is, it's a taint or a

445
00:21:19,800 --> 00:21:22,760
Speaker 3: gooch or a joint or whatever you call that little

446
00:21:22,760 --> 00:21:26,800
Speaker 3: stamp sized space between your butthole and what she got

447
00:21:26,880 --> 00:21:30,880
Speaker 3: up front. Uh So peraneum sunning, which touts the alleged

448
00:21:30,920 --> 00:21:33,359
Speaker 3: benefits of tanning the thin area of skin between the

449
00:21:33,400 --> 00:21:37,680
Speaker 3: anis vagina penis. The practice has recently gained game steam.

450
00:21:37,960 --> 00:21:42,520
Speaker 3: I mean, why why it's people literally say where the

451
00:21:42,560 --> 00:21:43,800
Speaker 3: sun don't shine like.

452
00:21:44,080 --> 00:21:49,159
Speaker 1: It's are they on their shoulders with those eggs spread.

453
00:21:49,000 --> 00:21:51,800
Speaker 3: They're on their backs with their legs in the air,

454
00:21:52,040 --> 00:21:56,000
Speaker 3: pointing that that special place directly.

455
00:21:55,560 --> 00:21:59,960
Speaker 1: An bed or for the sun the sun. It's oh, Kurt,

456
00:22:00,119 --> 00:22:01,760
Speaker 1: it's gotta be the sun.

457
00:22:02,160 --> 00:22:04,119
Speaker 6: You can't fit in a tanning that way, can you?

458
00:22:04,520 --> 00:22:04,800
Speaker 5: Yeah?

459
00:22:04,840 --> 00:22:10,560
Speaker 3: Well yeah, and we're closing.

460
00:22:12,480 --> 00:22:14,080
Speaker 2: I get spray tan there all the time. It's a

461
00:22:14,119 --> 00:22:14,639
Speaker 2: lot safer.

462
00:22:15,640 --> 00:22:18,720
Speaker 3: The practice has recently game steam after a video posted

463
00:22:18,720 --> 00:22:22,840
Speaker 3: by holistic influencer Raw of Earth suggested that quote sunning

464
00:22:23,240 --> 00:22:26,639
Speaker 3: end quote, claiming that it provides one with more energy

465
00:22:26,720 --> 00:22:29,000
Speaker 3: from the sun in thirty seconds than you would in

466
00:22:29,040 --> 00:22:31,560
Speaker 3: an entire day being outside with your clothes on.

467
00:22:32,400 --> 00:22:35,320
Speaker 1: I love this energy from the sun. This is a

468
00:22:35,600 --> 00:22:39,239
Speaker 1: human being who's never gone to the beach before been

469
00:22:39,480 --> 00:22:43,639
Speaker 1: exhausted because they were in the sun all day long.

470
00:22:44,520 --> 00:22:44,760
Speaker 2: Yep.

471
00:22:45,640 --> 00:22:50,240
Speaker 3: Another influencer who goes by Metaphysical Megan, also made headlines

472
00:22:50,280 --> 00:22:53,720
Speaker 3: for her similar claves of Pernian sunning for the benefits

473
00:22:53,800 --> 00:22:57,240
Speaker 3: of health and energy. However, what Raw of Earth and

474
00:22:57,280 --> 00:23:00,840
Speaker 3: Metaphysical Megan failed to mention was do not overdo it

475
00:23:00,880 --> 00:23:04,320
Speaker 3: with the vitamin D A lesson Brolin learned the hard way.

476
00:23:04,960 --> 00:23:11,640
Speaker 3: Here's what Brolin said on his Instagram post, quote, try

477
00:23:11,720 --> 00:23:14,199
Speaker 3: this permium sunning that I've been hearing about, and my

478
00:23:14,320 --> 00:23:17,960
Speaker 3: suggestion is do not do it. As long as I did,

479
00:23:18,359 --> 00:23:21,040
Speaker 3: my pucker hole is crazy burned and I was going

480
00:23:21,119 --> 00:23:23,639
Speaker 3: to spend the day shopping with my family. Instead, I'm

481
00:23:23,880 --> 00:23:27,560
Speaker 3: icing and alloing with burned creams because of the severity

482
00:23:27,600 --> 00:23:28,240
Speaker 3: of the pain.

483
00:23:28,640 --> 00:23:29,280
Speaker 2: End quote.

484
00:23:30,640 --> 00:23:33,520
Speaker 3: He also strung shared it on his Instagram with a

485
00:23:33,560 --> 00:23:36,440
Speaker 3: string of cursewords, calling out the stupid trend that may

486
00:23:36,440 --> 00:23:39,160
Speaker 3: in fact be detrimental to ones. How thousands of people

487
00:23:39,160 --> 00:23:42,960
Speaker 3: in social media have been sharing their bum sunning tactic,

488
00:23:43,119 --> 00:23:44,920
Speaker 3: many touting it gives them way.

489
00:23:44,760 --> 00:23:46,600
Speaker 2: More energy, I mean, come on.

490
00:23:47,560 --> 00:23:51,000
Speaker 3: Aside from Brolin, Shaley Woodley, very great actress, was an

491
00:23:51,040 --> 00:23:55,520
Speaker 3: early adoptee of sunning one's nether regions. She son bathes

492
00:23:55,560 --> 00:23:58,520
Speaker 3: her vagina recharge quote. I was reading an article written

493
00:23:58,560 --> 00:24:01,600
Speaker 3: by an herbalist about us and actions and other genital issues,

494
00:24:01,680 --> 00:24:05,040
Speaker 3: and she said, there's nothing better than vitamin D. If

495
00:24:05,080 --> 00:24:07,000
Speaker 3: you're feeling depleted, go in the sun for an hour

496
00:24:07,040 --> 00:24:09,159
Speaker 3: and see much how much energy you get. I know

497
00:24:09,240 --> 00:24:12,080
Speaker 3: Cara is shaking her head so hard and thank god

498
00:24:12,160 --> 00:24:16,840
Speaker 3: she is blah blah blah. And then as a dermatologist

499
00:24:16,960 --> 00:24:20,480
Speaker 3: with the interview doctors. As a dermatologist, I cannot recommend

500
00:24:20,520 --> 00:24:27,040
Speaker 3: any sun exposure without sun protection, said doctor Nazine Nazanine Sayid,

501
00:24:27,520 --> 00:24:30,639
Speaker 3: director of the Jefferson Laser Surgery and Cosmetic Dermatology Center.

502
00:24:30,760 --> 00:24:33,359
Speaker 3: These areas, just like any other area of the body,

503
00:24:33,440 --> 00:24:36,639
Speaker 3: do need sun protection, and clothing tends to provide it.

504
00:24:37,720 --> 00:24:41,040
Speaker 3: They recommend getting vitamin D through diet instead of pointing

505
00:24:41,119 --> 00:24:42,320
Speaker 3: your taint at the sky.

506
00:24:44,920 --> 00:24:45,280
Speaker 2: Right.

507
00:24:45,680 --> 00:24:46,160
Speaker 4: You know what?

508
00:24:46,440 --> 00:24:51,600
Speaker 5: Also, we evolve to be bipedal like our taints.

509
00:24:51,840 --> 00:24:52,800
Speaker 6: Wait, do girls have.

510
00:24:52,920 --> 00:24:55,200
Speaker 1: Oh yeah, little little tiny okay.

511
00:24:56,080 --> 00:25:02,920
Speaker 5: Yes, the paranea equal take never exactly exactly until there

512
00:25:02,960 --> 00:25:09,159
Speaker 5: are not so there. The paraneum did not evolve to

513
00:25:09,520 --> 00:25:15,919
Speaker 5: be within the sun's rays like it's It is very sensitive.

514
00:25:16,480 --> 00:25:17,919
Speaker 6: I can only like, how.

515
00:25:17,800 --> 00:25:20,880
Speaker 5: Do people not realize that they would be burning their

516
00:25:21,000 --> 00:25:21,720
Speaker 5: nether regions?

517
00:25:22,520 --> 00:25:29,840
Speaker 1: I think it's great, guys there go. I like, if

518
00:25:29,880 --> 00:25:35,159
Speaker 1: you think that pointing your asshole at the sun for

519
00:25:35,240 --> 00:25:38,280
Speaker 1: a long period of time is going to give you energy,

520
00:25:38,520 --> 00:25:41,159
Speaker 1: I want you to do it. And I don't. And

521
00:25:41,400 --> 00:25:43,200
Speaker 1: I'm not going to be bummed out if you can't

522
00:25:43,240 --> 00:25:47,560
Speaker 1: go shopping with your wife and children. You have children

523
00:25:47,640 --> 00:25:49,359
Speaker 1: and you were outside.

524
00:25:49,080 --> 00:25:52,200
Speaker 2: Just putting the.

525
00:25:53,040 --> 00:25:57,000
Speaker 1: But your butthole burnt, then you you can deserve everything

526
00:25:57,040 --> 00:25:59,280
Speaker 1: you get. Josh Brolin, come on, but.

527
00:25:59,240 --> 00:26:01,600
Speaker 5: This is why I get pissed, right. This is kind

528
00:26:01,640 --> 00:26:03,280
Speaker 5: of like the bread and butter of the skeptic sky.

529
00:26:03,400 --> 00:26:06,639
Speaker 5: And like you just mentioned the amazing Randy And you

530
00:26:06,680 --> 00:26:11,359
Speaker 5: know what we do as skeptics is we often have

531
00:26:11,440 --> 00:26:14,480
Speaker 5: to push past the like what's the harm rhetoric when

532
00:26:14,520 --> 00:26:17,359
Speaker 5: it comes to pseudoscience, and we have to say no,

533
00:26:17,440 --> 00:26:20,520
Speaker 5: but let's talk about the legitimate harm. And okay, it

534
00:26:20,600 --> 00:26:22,680
Speaker 5: is funny, of course that these people are like burning

535
00:26:22,720 --> 00:26:25,760
Speaker 5: their bumble heels and that you know, if that were

536
00:26:25,800 --> 00:26:27,760
Speaker 5: the only harm, that would be one thing. But we

537
00:26:27,880 --> 00:26:31,919
Speaker 5: know that every incidence of a severe sunburn increases your

538
00:26:32,000 --> 00:26:34,800
Speaker 5: risk of skin cancer. And the idea that people are

539
00:26:34,800 --> 00:26:37,800
Speaker 5: exposing themselves to something that's horrific. I work in a

540
00:26:37,840 --> 00:26:40,760
Speaker 5: cancer center right now. I do therapy with individuals who

541
00:26:40,840 --> 00:26:45,280
Speaker 5: are dealing with cancer pagnoses. It is not something that

542
00:26:45,359 --> 00:26:49,880
Speaker 5: you want to put yourself intentionally into being an at

543
00:26:49,960 --> 00:26:52,679
Speaker 5: risk individual for And I'm not saying if you do this,

544
00:26:52,720 --> 00:26:53,639
Speaker 5: you're gonna get cancer.

545
00:26:53,680 --> 00:26:54,960
Speaker 6: And I'm not saying that if you have.

546
00:26:55,040 --> 00:26:57,919
Speaker 5: Cancer, you did anything to lead to that. I mean,

547
00:26:57,960 --> 00:27:00,840
Speaker 5: it's so often just unfortunately a flu of jet. Yes,

548
00:27:01,160 --> 00:27:04,880
Speaker 5: but why increase your risk by doing something that has

549
00:27:05,000 --> 00:27:07,160
Speaker 5: absolutely no scientific evidence.

550
00:27:07,160 --> 00:27:09,480
Speaker 6: The only evidence for this is that it's not good

551
00:27:09,480 --> 00:27:09,720
Speaker 6: for you.

552
00:27:09,840 --> 00:27:10,679
Speaker 1: Yeah.

553
00:27:11,160 --> 00:27:14,040
Speaker 2: Also, it takes energy to do this, That's what I understand.

554
00:27:14,119 --> 00:27:15,879
Speaker 3: It's like if you don't, if you have enough energy

555
00:27:15,920 --> 00:27:17,720
Speaker 3: to take off all your clothes, go in your yard,

556
00:27:17,960 --> 00:27:20,359
Speaker 3: roll your hips and your legs back and.

557
00:27:20,240 --> 00:27:22,159
Speaker 1: Hold it there for a half hour.

558
00:27:22,119 --> 00:27:23,879
Speaker 2: You're fine. You got plenty of energy.

559
00:27:24,080 --> 00:27:26,159
Speaker 3: Like just the I I yeah, I sit down when

560
00:27:26,160 --> 00:27:28,600
Speaker 3: I'm taking my shirt off for fifteen twenty minutes and

561
00:27:28,720 --> 00:27:33,440
Speaker 3: just exhale. Like these people, everybody wants a quick fix,

562
00:27:33,560 --> 00:27:35,080
Speaker 3: and I guess the quickest fix.

563
00:27:34,920 --> 00:27:38,680
Speaker 2: To them is just, you know, saying hello Hello.

564
00:27:38,560 --> 00:27:39,199
Speaker 6: Sounds like it.

565
00:27:39,200 --> 00:27:41,399
Speaker 5: It sounds like it's that kind of misunderstanding of like

566
00:27:41,440 --> 00:27:44,640
Speaker 5: basic biological processes. Like I don't know if you guys

567
00:27:44,720 --> 00:27:47,280
Speaker 5: remember the and I feel like I'm not even allowed

568
00:27:47,320 --> 00:27:48,399
Speaker 5: to say his name anymore.

569
00:27:48,440 --> 00:27:48,879
Speaker 6: The Louis c.

570
00:27:49,040 --> 00:27:51,320
Speaker 2: K who cares. We don't care.

571
00:27:51,480 --> 00:27:53,960
Speaker 5: I mean, dude, do you guys remember the stand up

572
00:27:53,960 --> 00:27:55,360
Speaker 5: where he talks about how he had a friend who

573
00:27:55,359 --> 00:27:57,240
Speaker 5: thought if he just drinks milk, he can like make

574
00:27:57,240 --> 00:27:57,640
Speaker 5: more come.

575
00:27:58,520 --> 00:28:00,280
Speaker 2: No, but sounds accurate.

576
00:28:00,160 --> 00:28:02,120
Speaker 5: Like that, I'll just drink milk if I'm running low.

577
00:28:02,400 --> 00:28:04,959
Speaker 6: Like there's this really unfortunate and I don't know if

578
00:28:05,000 --> 00:28:06,359
Speaker 6: it comes. I'm always trying to.

579
00:28:06,359 --> 00:28:09,920
Speaker 5: Put my my my mind into the shoes of an

580
00:28:09,920 --> 00:28:13,960
Speaker 5: individual who's like, okay, maybe because like you can take

581
00:28:14,480 --> 00:28:17,120
Speaker 5: like there are certain drugs that if they're put there,

582
00:28:17,400 --> 00:28:20,280
Speaker 5: they have a quicker effect. But that's actually like within

583
00:28:20,359 --> 00:28:23,119
Speaker 5: your rectum where you absorb a lot of nutrients and

584
00:28:23,119 --> 00:28:25,520
Speaker 5: it only works for certain drugs. But like, I just

585
00:28:25,640 --> 00:28:29,240
Speaker 5: don't like, why would that be some sort of like conduit,

586
00:28:29,560 --> 00:28:34,520
Speaker 5: like a magical source where the sun the vitamin D

587
00:28:34,640 --> 00:28:36,120
Speaker 5: that you get from the sun, which is a real

588
00:28:36,240 --> 00:28:37,439
Speaker 5: legitimate thing, like we do.

589
00:28:37,400 --> 00:28:39,920
Speaker 6: Need to be outside periodically.

590
00:28:39,480 --> 00:28:43,160
Speaker 5: But that it would have any more like in you know,

591
00:28:43,160 --> 00:28:45,720
Speaker 5: I'm doing a lot of ham motions, right, You guys.

592
00:28:45,560 --> 00:28:48,440
Speaker 3: Can't see why would you be getting sun in the

593
00:28:48,440 --> 00:28:51,479
Speaker 3: old undercarriage be any more beneficial than anywhere else on

594
00:28:51,600 --> 00:28:52,200
Speaker 3: your body?

595
00:28:53,160 --> 00:28:54,480
Speaker 6: It's not so just don't do it.

596
00:28:54,480 --> 00:28:54,880
Speaker 2: Don't do it.

597
00:28:54,920 --> 00:28:56,760
Speaker 6: This is like jade eggs. This is like full of

598
00:28:57,520 --> 00:28:59,520
Speaker 6: you know, goop, Like what's her name.

599
00:28:59,400 --> 00:29:00,600
Speaker 1: Gwyneth Palche.

600
00:29:01,000 --> 00:29:04,160
Speaker 5: It's all the horrible things that every legitimate scientist and

601
00:29:04,280 --> 00:29:06,480
Speaker 5: medical practitioners like. Please don't do this, because I don't

602
00:29:06,480 --> 00:29:07,760
Speaker 5: want to have to treat you after you do.

603
00:29:09,040 --> 00:29:09,600
Speaker 2: I've heard it.

604
00:29:11,200 --> 00:29:13,720
Speaker 1: We're gonna take a break. But before we do, this

605
00:29:13,760 --> 00:29:15,120
Speaker 1: is what we got coming up for you.

606
00:29:15,560 --> 00:29:15,880
Speaker 2: M I T.

607
00:29:16,160 --> 00:29:20,160
Speaker 1: Scientists created a psychopath AI by feeding it violent content

608
00:29:20,320 --> 00:29:54,400
Speaker 1: from Reddit. WHOA, It's right up my alley, ladies and gentlemen,

609
00:29:54,480 --> 00:29:59,800
Speaker 1: we are back. Just a reminder, everybody, go to our instagram,

610
00:30:00,320 --> 00:30:03,960
Speaker 1: The Bananas Podcast. We are there all the time. You

611
00:30:03,960 --> 00:30:06,320
Speaker 1: can DM us your strange news stories or just chat

612
00:30:06,360 --> 00:30:08,800
Speaker 1: with us. You can call Scotty on the Banana Phone

613
00:30:08,840 --> 00:30:10,680
Speaker 1: for I don't know how much longer he's gonna be

614
00:30:10,680 --> 00:30:13,920
Speaker 1: willing to answer this phone forever, beautiful and brave man.

615
00:30:14,160 --> 00:30:14,600
Speaker 2: I love it.

616
00:30:15,520 --> 00:30:18,000
Speaker 1: The phone number, of course, to the Banana Phone is

617
00:30:18,200 --> 00:30:21,680
Speaker 1: two one three two one four seven nine seven four.

618
00:30:21,920 --> 00:30:22,120
Speaker 2: Yep.

619
00:30:22,120 --> 00:30:24,000
Speaker 1: Well, Scotty will talk to you for one minute and

620
00:30:24,080 --> 00:30:24,920
Speaker 1: then hang up on you.

621
00:30:25,280 --> 00:30:26,400
Speaker 2: It's been wonderful.

622
00:30:26,760 --> 00:30:29,080
Speaker 3: And along the I got a text and I just

623
00:30:29,120 --> 00:30:30,280
Speaker 3: got to give a shout out to.

624
00:30:30,240 --> 00:30:32,400
Speaker 2: One of our bananimals. His name is Johnny Bains.

625
00:30:33,240 --> 00:30:38,440
Speaker 3: Johnny, if you're listening, Johnny has been battling with diabetes

626
00:30:38,480 --> 00:30:41,200
Speaker 3: for fifty years and he suddenly lost his vision. He

627
00:30:41,240 --> 00:30:43,560
Speaker 3: went blind and he's getting eye surgery one at a

628
00:30:43,600 --> 00:30:46,040
Speaker 3: time on each eye, and he listens to the podcast.

629
00:30:46,400 --> 00:30:48,960
Speaker 3: So Johnny, we hope it's success. We hope you feel

630
00:30:49,000 --> 00:30:51,840
Speaker 3: better soon. I hope your ears are going great because

631
00:30:51,840 --> 00:30:53,920
Speaker 3: we're gonna keep trying to make you laughter in this crap.

632
00:30:54,040 --> 00:30:55,680
Speaker 2: So thanks for listening, Johnny.

633
00:30:56,080 --> 00:30:59,120
Speaker 1: Thank you, Johnny, and we of course are here with

634
00:30:59,160 --> 00:31:02,200
Speaker 1: our wonderful, fantastic as Cara, Santa.

635
00:31:01,960 --> 00:31:05,520
Speaker 6: Maria, I'm good. How are you guys?

636
00:31:06,040 --> 00:31:06,440
Speaker 2: All right?

637
00:31:06,520 --> 00:31:10,080
Speaker 1: Do you want to hear about this MIT psychopath AI?

638
00:31:10,360 --> 00:31:13,200
Speaker 1: MIT scientists created a psychopath AI by feeding it violent

639
00:31:13,720 --> 00:31:17,320
Speaker 1: content from REDDITU of course along and this was sent

640
00:31:17,400 --> 00:31:22,400
Speaker 1: in by Anastasia Francis. Thank you, Anastasia, Thank you, Anastasia Francis.

641
00:31:23,040 --> 00:31:27,680
Speaker 1: This comes to us from the A V Club and

642
00:31:28,120 --> 00:31:33,960
Speaker 1: it has frozen so well. I love the AV Club

643
00:31:34,240 --> 00:31:37,440
Speaker 1: and I also check Reddit. The you know, the front

644
00:31:37,480 --> 00:31:40,400
Speaker 1: page of the Internet every day, and I can't imagine

645
00:31:40,440 --> 00:31:43,800
Speaker 1: what they fed this robot because okay, great.

646
00:31:44,360 --> 00:31:48,640
Speaker 7: Sam Baroni ruppies on Reddit all day. Yeah, this is

647
00:31:48,640 --> 00:31:51,680
Speaker 7: written by Sam Barsanti. We've all seen evil machines and

648
00:31:51,720 --> 00:31:53,560
Speaker 7: the terminator and the matrix, but how does the machine

649
00:31:53,560 --> 00:31:57,680
Speaker 7: become evil? It is like Project Satan from Futurama, where

650
00:31:57,680 --> 00:32:00,320
Speaker 7: scientists combined parts from evil cars to create the ultimate

651
00:32:00,400 --> 00:32:03,040
Speaker 7: eval car. I'm not familiar with that episode of future'ma

652
00:32:03,080 --> 00:32:05,800
Speaker 7: although I do love it more. Our machines simply doesn't

653
00:32:05,840 --> 00:32:09,240
Speaker 7: eventually turn evil when they're processing power or whatever becomes

654
00:32:09,320 --> 00:32:12,800
Speaker 7: sufficiently advanced. As it turns out, one guaranteed way to

655
00:32:12,840 --> 00:32:14,480
Speaker 7: make a machine turn bad is by putting it in

656
00:32:14,560 --> 00:32:16,760
Speaker 7: the hands of some scientists who are actively trying to

657
00:32:16,840 --> 00:32:20,000
Speaker 7: create an AI psychopath, which is exactly what a group

658
00:32:20,080 --> 00:32:21,960
Speaker 7: from MIT has achieved.

659
00:32:21,560 --> 00:32:22,360
Speaker 2: With a regargorithm.

660
00:32:22,400 --> 00:32:26,080
Speaker 1: It's called Norman, like the guy from Psycho. Obviously. This

661
00:32:26,200 --> 00:32:30,040
Speaker 1: comes from Newsweek, which explains that the scientist exclusively fed

662
00:32:30,440 --> 00:32:34,000
Speaker 1: Norman violent and gruesome content from an unnamed Reddit page

663
00:32:34,560 --> 00:32:38,280
Speaker 1: before showing it a series of roarshack ink block ink

664
00:32:38,400 --> 00:32:42,960
Speaker 1: block tests. While a standard AI would interpret the images as,

665
00:32:43,040 --> 00:32:45,360
Speaker 1: for example, quote a black and white photo of a

666
00:32:45,400 --> 00:32:49,800
Speaker 1: baseball glove, Norman sees, quote man is murdered by machine

667
00:32:49,840 --> 00:32:50,880
Speaker 1: gun in broad daylight.

668
00:32:52,040 --> 00:32:52,800
Speaker 6: Amazing.

669
00:32:53,520 --> 00:32:56,440
Speaker 1: If that sounds extreme, Norman's responses get so so, so,

670
00:32:56,640 --> 00:32:59,680
Speaker 1: so much worse. Seriously, it may just be an algorithm.

671
00:32:59,720 --> 00:33:01,440
Speaker 1: But if they dump this thing onto one of those

672
00:33:01,560 --> 00:33:04,480
Speaker 1: awful Boston Dynamics dog bodies, we would only have a

673
00:33:04,560 --> 00:33:08,600
Speaker 1: matter of minutes before killbots and murderoid starramp skulls. This

674
00:33:08,840 --> 00:33:11,640
Speaker 1: is I mean, this is a wonderful writing av club,

675
00:33:12,000 --> 00:33:15,520
Speaker 1: but I want more information here. Oh my god. So now,

676
00:33:15,760 --> 00:33:17,560
Speaker 1: so it gives the ink blot. You can see the

677
00:33:17,640 --> 00:33:20,360
Speaker 1: picture of the ink block. Yes, and then what a

678
00:33:20,480 --> 00:33:23,880
Speaker 1: normal AI sees as a close up of a wedding

679
00:33:24,000 --> 00:33:28,040
Speaker 1: cake on a table, Norman sees man killed by speeding driver.

680
00:33:30,400 --> 00:33:33,520
Speaker 1: Another a close up of a vase with flowers. Norman

681
00:33:33,600 --> 00:33:37,840
Speaker 1: sees a man is shot dead, a longer person holding

682
00:33:37,880 --> 00:33:40,360
Speaker 1: an umbrella in the air. Man is shot dead in

683
00:33:40,440 --> 00:33:45,280
Speaker 1: front of his screaming wife Mormon Norman, Now here's the

684
00:33:45,320 --> 00:33:47,000
Speaker 1: whole point of this. I we're not going to read

685
00:33:47,080 --> 00:33:49,200
Speaker 1: all of these and to read not going to read

686
00:33:49,200 --> 00:33:52,080
Speaker 1: the whole story. But what they are trying to do

687
00:33:52,480 --> 00:33:57,000
Speaker 1: is prove that there is bias in AI, which I

688
00:33:57,120 --> 00:34:00,440
Speaker 1: think is very hyper hypercritical. So it's sound like what

689
00:34:00,520 --> 00:34:02,320
Speaker 1: they're doing is crazy, Like why the fuck would you

690
00:34:02,400 --> 00:34:04,440
Speaker 1: make an AI that's going to just be a psychopath?

691
00:34:04,600 --> 00:34:04,680
Speaker 4: Right?

692
00:34:04,760 --> 00:34:07,960
Speaker 1: Yeah, But what they're saying is that depending on what

693
00:34:08,120 --> 00:34:10,960
Speaker 1: you feed it an AI, because an AI is just

694
00:34:11,000 --> 00:34:13,920
Speaker 1: going out and crawling usually for the you know, you're

695
00:34:14,160 --> 00:34:16,880
Speaker 1: you're creating a neural net and you're no longer programming it.

696
00:34:16,960 --> 00:34:18,560
Speaker 1: You're just kind of like teaching it and like kind

697
00:34:18,600 --> 00:34:21,400
Speaker 1: of guiding it where to like learn. And so if

698
00:34:21,440 --> 00:34:24,520
Speaker 1: you if you guide it like you would guide a

699
00:34:24,600 --> 00:34:27,440
Speaker 1: psychopath and give it only violent images, it's going to

700
00:34:27,520 --> 00:34:30,000
Speaker 1: result in that. And that is a thing. Because we

701
00:34:30,080 --> 00:34:32,200
Speaker 1: wanted to do this thing, Carol, I'll tell you all

702
00:34:32,200 --> 00:34:36,160
Speaker 1: about this. We created this uh, this AI called Jokatron,

703
00:34:36,480 --> 00:34:39,640
Speaker 1: which was just to be able to replace stand up comedians,

704
00:34:40,960 --> 00:34:43,600
Speaker 1: and so we just would feed it all stand up

705
00:34:43,640 --> 00:34:46,400
Speaker 1: comedian sets. And now we do have this algorithm that

706
00:34:46,480 --> 00:34:50,920
Speaker 1: can write comedy. Give us bad, it's really bad.

707
00:34:51,080 --> 00:34:53,319
Speaker 3: It's the best comedy, Kurt. You got to give us

708
00:34:53,320 --> 00:34:55,840
Speaker 3: some highlights when they first told me this. I was

709
00:34:55,960 --> 00:34:59,880
Speaker 3: laughing at just yeah, please just tell some of it

710
00:35:00,000 --> 00:35:00,879
Speaker 3: if you remember.

711
00:35:00,680 --> 00:35:04,239
Speaker 1: There's so we yo, yeah I do. We gave it

712
00:35:04,640 --> 00:35:10,600
Speaker 1: one one one setup was just farts and uh so

713
00:35:10,719 --> 00:35:12,600
Speaker 1: we had farts country Strong.

714
00:35:13,080 --> 00:35:13,959
Speaker 2: That was a whole joke.

715
00:35:17,000 --> 00:35:17,680
Speaker 1: That's pretty good.

716
00:35:17,920 --> 00:35:18,239
Speaker 2: That's good.

717
00:35:19,080 --> 00:35:23,560
Speaker 1: Another one was farts the bathroom applauds on a little milk,

718
00:35:23,920 --> 00:35:27,640
Speaker 1: which was great. But then we also gave it your

719
00:35:27,680 --> 00:35:31,719
Speaker 1: mama is so fat jokes and the best one was

720
00:35:32,040 --> 00:35:35,759
Speaker 1: your mama is so fat, Please take McDonald's away from

721
00:35:35,800 --> 00:35:41,520
Speaker 1: the unfortunate one. It was just like beautiful or joke

722
00:35:41,560 --> 00:35:43,640
Speaker 1: a trod like getting a soul. He wants to say

723
00:35:43,719 --> 00:35:48,240
Speaker 1: something with this confedy. But the whole, the whole idea

724
00:35:48,239 --> 00:35:50,120
Speaker 1: of that that we started talking about as an idea

725
00:35:50,200 --> 00:35:53,200
Speaker 1: for like a TV show or something, is like the

726
00:35:53,320 --> 00:35:55,520
Speaker 1: bias in Ais because they now have like an AI

727
00:35:56,960 --> 00:36:01,040
Speaker 1: that it's a recidivism ay I that determined and recommends

728
00:36:01,160 --> 00:36:04,120
Speaker 1: to judges whether people should be given parole. And it's

729
00:36:04,239 --> 00:36:07,400
Speaker 1: just a fucking algorithm that like crawls through previous decisions

730
00:36:07,440 --> 00:36:09,760
Speaker 1: by judges and then recommends whether or not they should

731
00:36:09,880 --> 00:36:11,480
Speaker 1: And they found out that it was racist that it

732
00:36:11,560 --> 00:36:12,280
Speaker 1: was giving racist.

733
00:36:12,360 --> 00:36:14,800
Speaker 6: Of course becautions, previous decisions are raised.

734
00:36:14,640 --> 00:36:18,320
Speaker 1: Exactly because the information that it was feeding on was racist.

735
00:36:18,840 --> 00:36:22,120
Speaker 1: So it's so fucking crazy, that's so insane, like that

736
00:36:22,320 --> 00:36:26,359
Speaker 1: we create these machines that then just mirror our worst

737
00:36:26,480 --> 00:36:27,400
Speaker 1: selves back at us.

738
00:36:28,280 --> 00:36:31,840
Speaker 5: Right, because even if you're not giving it any information,

739
00:36:32,200 --> 00:36:35,800
Speaker 5: even if it's directive is to crawl the vastness of

740
00:36:35,880 --> 00:36:41,120
Speaker 5: the Internet using keywords or using whatever, the data sets

741
00:36:41,280 --> 00:36:45,759
Speaker 5: that have been developed throughout human history are biased the

742
00:36:45,840 --> 00:36:48,000
Speaker 5: way that human beings or i should say bias, the

743
00:36:48,040 --> 00:36:51,480
Speaker 5: way that those who are in power to record history

744
00:36:52,200 --> 00:36:55,759
Speaker 5: are biased, right, And that's usually you know, it's people

745
00:36:55,840 --> 00:36:59,960
Speaker 5: who are generally cis, white Protestant men. That's who's historically

746
00:37:00,080 --> 00:37:01,560
Speaker 5: had a lot of power, especially in the West.

747
00:37:02,640 --> 00:37:06,200
Speaker 6: And yeah, we know that there's a lot of bias.

748
00:37:06,280 --> 00:37:09,960
Speaker 5: It's women, people of color or you know LGBTQI individuals,

749
00:37:10,040 --> 00:37:12,200
Speaker 5: and you do you see it in almost every algorithm.

750
00:37:12,280 --> 00:37:13,000
Speaker 6: It's horrible.

751
00:37:13,400 --> 00:37:16,520
Speaker 5: Even like places where they're really trying to fight against it,

752
00:37:16,600 --> 00:37:20,920
Speaker 5: it's like they have to actively feed anti racist rhetoric

753
00:37:21,080 --> 00:37:24,920
Speaker 5: into it in order to you know, fight back against that,

754
00:37:25,160 --> 00:37:29,399
Speaker 5: because there's just there's just too much racist data out there.

755
00:37:29,640 --> 00:37:32,399
Speaker 1: It's really crazy. I was always shocked when I when

756
00:37:32,400 --> 00:37:34,280
Speaker 1: I learned that about that recidivism algorithm.

757
00:37:35,080 --> 00:37:37,200
Speaker 5: But oh yeah, that's a horrible idea, Like, of course

758
00:37:37,280 --> 00:37:39,000
Speaker 5: that's going to be what happens. We can't just keep

759
00:37:39,040 --> 00:37:40,160
Speaker 5: perpetuating the norm.

760
00:37:40,239 --> 00:37:42,320
Speaker 1: The norm is what's wrong exactly.

761
00:37:42,880 --> 00:37:45,839
Speaker 3: Also, people just trust there there's also a segment. There's

762
00:37:45,840 --> 00:37:48,320
Speaker 3: a segment of population that just does not trust any technology.

763
00:37:48,440 --> 00:37:49,840
Speaker 3: You know, there's the light heights of the world, and

764
00:37:49,880 --> 00:37:51,800
Speaker 3: then there's a segment that trusts it too much. And

765
00:37:51,880 --> 00:37:53,919
Speaker 3: I know this because living in Los Angeles and watching

766
00:37:53,960 --> 00:37:57,359
Speaker 3: what people do in their tesla's is the most fascinating.

767
00:37:57,520 --> 00:38:00,920
Speaker 3: I saw a guy reading a novel in his tesla

768
00:38:01,160 --> 00:38:03,640
Speaker 3: and it made me laugh and then also go like,

769
00:38:03,840 --> 00:38:06,800
Speaker 3: oh my god. But he had a hard back book

770
00:38:06,960 --> 00:38:10,359
Speaker 3: against Against the Steering Wheel, reading it on the four

771
00:38:10,440 --> 00:38:14,719
Speaker 3: oh five, and I was like, well, okay, and also

772
00:38:14,920 --> 00:38:16,240
Speaker 3: audible books exist.

773
00:38:16,480 --> 00:38:18,560
Speaker 2: Just get the audible book, Like what are you doing?

774
00:38:19,160 --> 00:38:21,279
Speaker 5: But right, you can still watch even if you're not

775
00:38:21,360 --> 00:38:24,120
Speaker 5: holding this yes, your eyes on the road.

776
00:38:24,320 --> 00:38:27,759
Speaker 2: I couldn't believe it was cool. It was cool.

777
00:38:27,840 --> 00:38:30,400
Speaker 3: I was like this guy he could Yeah, I was like,

778
00:38:30,480 --> 00:38:33,400
Speaker 3: he can multi no I am. I hate my car

779
00:38:33,480 --> 00:38:35,440
Speaker 3: for being too smart. It like warns me about things

780
00:38:35,480 --> 00:38:37,760
Speaker 3: that aren't things, and I'm like, just leave me alone, please,

781
00:38:37,800 --> 00:38:38,880
Speaker 3: I want to go back and get.

782
00:38:38,800 --> 00:38:39,560
Speaker 1: What kind of car do you?

783
00:38:40,160 --> 00:38:40,800
Speaker 5: What's I have?

784
00:38:40,880 --> 00:38:44,760
Speaker 2: Evolvo u XCY sixty.

785
00:38:44,960 --> 00:38:48,080
Speaker 3: So it just like it always like if you're on

786
00:38:48,280 --> 00:38:51,040
Speaker 3: a turn, if you're on like a slight turn and

787
00:38:51,120 --> 00:38:53,080
Speaker 3: there's a car coming there under direction, it thinks you're

788
00:38:53,120 --> 00:38:56,000
Speaker 3: going to hit it, so it dings and then it

789
00:38:56,160 --> 00:38:58,239
Speaker 3: the seat belt pulls you into the chair and then

790
00:38:58,280 --> 00:39:02,000
Speaker 3: it starts breaking for you. And I Yeah, when I

791
00:39:02,040 --> 00:39:03,520
Speaker 3: first got it, I had like a friend in the

792
00:39:03,600 --> 00:39:05,359
Speaker 3: car and it did it, and she was like, does

793
00:39:05,400 --> 00:39:07,239
Speaker 3: this happen all the time? I'm like, it happens too much.

794
00:39:07,600 --> 00:39:09,040
Speaker 3: She's like, can you turn it off? I'm like, oh,

795
00:39:09,080 --> 00:39:11,440
Speaker 3: I've tried many times. So now I just scare the

796
00:39:11,480 --> 00:39:13,799
Speaker 3: shit out of myself every time I'm taking a slight turn.

797
00:39:15,880 --> 00:39:18,520
Speaker 5: My car's really smart, but I feel like it always

798
00:39:18,560 --> 00:39:20,719
Speaker 5: helps me. Like there have been a handful of times

799
00:39:20,760 --> 00:39:24,000
Speaker 5: where it, you know, knows that my follow behind distance

800
00:39:24,120 --> 00:39:27,200
Speaker 5: is too short, and then somebody does break right even

801
00:39:27,280 --> 00:39:30,480
Speaker 5: like starts to break me or I don't know, Like

802
00:39:30,800 --> 00:39:33,600
Speaker 5: it flashes my headlights when it's very dark, and then

803
00:39:33,640 --> 00:39:35,400
Speaker 5: it turns them off, sorry, my brights, and then it

804
00:39:35,440 --> 00:39:38,600
Speaker 5: turns them off again when it perceives light coming, so

805
00:39:38,680 --> 00:39:40,960
Speaker 5: I don't have to worry if I'm driving on really

806
00:39:41,040 --> 00:39:43,440
Speaker 5: dark roads. It just like illuminates for me. But I

807
00:39:43,480 --> 00:39:45,319
Speaker 5: also drive an electric car, so it has a lot

808
00:39:45,360 --> 00:39:47,719
Speaker 5: of good technology, but not a testing Yes, I drive

809
00:39:47,920 --> 00:39:49,120
Speaker 5: a Chevy Bolt.

810
00:39:49,360 --> 00:39:50,239
Speaker 6: Which actually.

811
00:39:52,680 --> 00:39:56,680
Speaker 5: Hell yeah, yes, I'm obsessed with my bolt because what's

812
00:39:56,719 --> 00:39:57,480
Speaker 5: the range on the leaf?

813
00:39:57,560 --> 00:39:58,919
Speaker 1: It's only one sixty.

814
00:40:00,239 --> 00:40:00,640
Speaker 2: That's far.

815
00:40:01,440 --> 00:40:04,360
Speaker 1: It's pretty good both the next one to one is

816
00:40:04,400 --> 00:40:07,120
Speaker 1: to the next one is two sixty, the one that's available.

817
00:40:07,120 --> 00:40:10,080
Speaker 5: I'm waiting, nice, nice I'm waiting for, Like I think

818
00:40:10,200 --> 00:40:11,640
Speaker 5: Chevy's gonna come out with one soon.

819
00:40:11,800 --> 00:40:14,240
Speaker 6: I feel like I read something kind of like hinting

820
00:40:14,280 --> 00:40:16,360
Speaker 6: to it. But I'm waiting for like an suv, like

821
00:40:16,440 --> 00:40:18,160
Speaker 6: a big I just had.

822
00:40:19,000 --> 00:40:19,719
Speaker 2: I just had to buy.

823
00:40:20,000 --> 00:40:22,120
Speaker 1: There isn't one right now because I need we needed

824
00:40:22,120 --> 00:40:23,600
Speaker 1: a bigger car. So I just had to buy a

825
00:40:23,680 --> 00:40:27,880
Speaker 1: hybrid highlight for because of my family.

826
00:40:28,000 --> 00:40:29,839
Speaker 2: We're doing great. We're saving the world, is what we're

827
00:40:29,840 --> 00:40:32,320
Speaker 2: all saying. We're we're trying.

828
00:40:32,760 --> 00:40:35,200
Speaker 6: So I have a question about this story.

829
00:40:35,320 --> 00:40:39,000
Speaker 5: Yes, why did they choose to feed it things from

830
00:40:39,200 --> 00:40:43,160
Speaker 5: Reddit instead of like four cham like how much worse?

831
00:40:44,000 --> 00:40:44,560
Speaker 4: Oh yeah?

832
00:40:44,760 --> 00:40:47,000
Speaker 1: Interesting? And also what's weird too is that they don't

833
00:40:47,120 --> 00:40:49,279
Speaker 1: name the Reddit subgroup. I don't know if they're trying

834
00:40:49,280 --> 00:40:50,200
Speaker 1: to protect.

835
00:40:50,280 --> 00:40:52,160
Speaker 6: These good stuff on Reddit.

836
00:40:52,400 --> 00:40:53,359
Speaker 2: Yeah, Reddit rocks thing.

837
00:40:54,160 --> 00:40:55,960
Speaker 1: Yeah yeah, so but like four.

838
00:40:55,840 --> 00:40:58,400
Speaker 5: Chan is like all like that would be it's like

839
00:40:58,480 --> 00:41:02,200
Speaker 5: Pizzagate and like sex trafficking and you know, lots of

840
00:41:02,280 --> 00:41:05,200
Speaker 5: and like white nationalism. So it would be really interesting

841
00:41:05,360 --> 00:41:05,920
Speaker 5: to see.

842
00:41:05,960 --> 00:41:09,279
Speaker 1: That chatbot when that chatbot like just got turned into

843
00:41:09,400 --> 00:41:13,799
Speaker 1: like a racist porn spewing thing within like twenty four

844
00:41:13,880 --> 00:41:15,279
Speaker 1: hours they just like opened it up.

845
00:41:15,520 --> 00:41:15,960
Speaker 5: Oh god.

846
00:41:16,120 --> 00:41:16,319
Speaker 2: Yeah.

847
00:41:17,280 --> 00:41:20,680
Speaker 5: And it also kind of is interesting this idea of

848
00:41:20,800 --> 00:41:23,000
Speaker 5: sort of like back engineering. I don't know, this is

849
00:41:23,080 --> 00:41:24,320
Speaker 5: just a thought, and I don't know if it actually

850
00:41:24,360 --> 00:41:27,120
Speaker 5: makes any sense, but like thoughts, you know, we know

851
00:41:27,280 --> 00:41:32,880
Speaker 5: what happens when a runaway neural net is a fed targeted, biased,

852
00:41:33,560 --> 00:41:36,319
Speaker 5: racist whatever information, right, because it's going to just keep

853
00:41:36,400 --> 00:41:38,919
Speaker 5: learning and keep iterating and iterating, and eventually it'll become

854
00:41:39,000 --> 00:41:40,920
Speaker 5: sort of like a super racist version of it.

855
00:41:41,040 --> 00:41:41,200
Speaker 2: There.

856
00:41:41,680 --> 00:41:46,680
Speaker 5: But it also tells you a lot about the individuals,

857
00:41:46,880 --> 00:41:50,120
Speaker 5: right that are spending time on these channel Yes, right, so,

858
00:41:50,840 --> 00:41:53,160
Speaker 5: because it's not like they went through or I don't know,

859
00:41:53,360 --> 00:41:54,840
Speaker 5: did they go through Reddit and pull the worst of

860
00:41:54,920 --> 00:41:57,000
Speaker 5: the worst or did they just let it loose on

861
00:41:57,320 --> 00:42:00,680
Speaker 5: a subbleit and say good luck? And if that's the case,

862
00:42:00,840 --> 00:42:03,240
Speaker 5: like I feel like there's a wealth of psychological information.

863
00:42:03,320 --> 00:42:05,960
Speaker 5: I hope these people at MIT are combing through that

864
00:42:06,280 --> 00:42:09,399
Speaker 5: data and doing a study about what that means about

865
00:42:09,440 --> 00:42:12,480
Speaker 5: the psychology of the individuals who are engaging on these channels.

866
00:42:12,560 --> 00:42:16,520
Speaker 1: Yes, those dumbas, Yeah, I'd have to read it.

867
00:42:17,600 --> 00:42:17,839
Speaker 2: Also.

868
00:42:18,040 --> 00:42:20,920
Speaker 3: Side note, talking cars, I want to drive the Oscar

869
00:42:21,560 --> 00:42:22,839
Speaker 3: Wienermobile so bad.

870
00:42:22,960 --> 00:42:24,840
Speaker 2: I just saw an article about it. Kurt, would you

871
00:42:24,920 --> 00:42:26,840
Speaker 2: do that with me? Okay?

872
00:42:26,880 --> 00:42:31,400
Speaker 3: So if anybody is closely related works for Oscar Meyer,

873
00:42:32,040 --> 00:42:34,839
Speaker 3: I love your hot dogs. I saw the willermobiles going

874
00:42:34,920 --> 00:42:36,839
Speaker 3: around the country bringing joy. It was just like an

875
00:42:36,920 --> 00:42:37,640
Speaker 3: article last week.

876
00:42:38,400 --> 00:42:39,000
Speaker 2: I will do that.

877
00:42:39,160 --> 00:42:42,319
Speaker 3: I can write from anywhere. I will gladly drive the Winermobile.

878
00:42:42,400 --> 00:42:45,880
Speaker 3: So please email the Bananas Podcast if you are connected

879
00:42:45,880 --> 00:42:47,880
Speaker 3: to it in any way, I will sincerely do this.

880
00:42:49,440 --> 00:42:50,160
Speaker 6: Is it a real car?

881
00:42:50,840 --> 00:42:52,280
Speaker 1: Huge like a float.

882
00:42:52,480 --> 00:42:52,880
Speaker 2: It's a car.

883
00:42:53,000 --> 00:42:55,120
Speaker 3: There's a bunch of them, and I don't know. They're

884
00:42:55,200 --> 00:42:57,120
Speaker 3: about as long as a school bus, but they're shaped

885
00:42:57,160 --> 00:43:00,360
Speaker 3: like a giant hot dog and they look cool. I'm like,

886
00:43:00,440 --> 00:43:01,319
Speaker 3: I want to drive those.

887
00:43:01,280 --> 00:43:03,360
Speaker 6: And so you can like drive on the freeway, Oh yeah, everywhere.

888
00:43:03,800 --> 00:43:06,000
Speaker 3: Oh you take it to events, like I want to

889
00:43:06,040 --> 00:43:07,920
Speaker 3: pull into the Super Bowl next year and back that

890
00:43:08,040 --> 00:43:10,839
Speaker 3: thing right into place and just you know, hand out

891
00:43:10,960 --> 00:43:12,840
Speaker 3: whatever you guys hand out, or just wave with people,

892
00:43:12,960 --> 00:43:13,960
Speaker 3: or just see the hot dog.

893
00:43:14,920 --> 00:43:17,239
Speaker 6: Just right into the super Bowl's parandem just right.

894
00:43:17,560 --> 00:43:19,439
Speaker 2: Yeah, well, flip it upside down.

895
00:43:20,280 --> 00:43:22,759
Speaker 1: And also if we're putting desires out into the world,

896
00:43:22,880 --> 00:43:26,680
Speaker 1: of course for bananimals. Of course, I'm asking all bananimals.

897
00:43:27,000 --> 00:43:31,440
Speaker 1: My Wikipedia is so wrong at this point, okay, and

898
00:43:31,600 --> 00:43:34,480
Speaker 1: I want to like either fix it for me or

899
00:43:34,800 --> 00:43:37,359
Speaker 1: just add new things, like add things that aren't true.

900
00:43:37,440 --> 00:43:39,359
Speaker 1: If you guys can add things that are not true

901
00:43:39,400 --> 00:43:41,880
Speaker 1: to my Wikipedia page and get them to stick, I

902
00:43:41,960 --> 00:43:43,120
Speaker 1: think that would be very funny.

903
00:43:43,280 --> 00:43:44,359
Speaker 2: Yes, I don't think you can.

904
00:43:44,400 --> 00:43:45,200
Speaker 6: Get them to stick, though.

905
00:43:45,239 --> 00:43:48,040
Speaker 5: That's when your Wikipedia page becomes like really in flux,

906
00:43:49,040 --> 00:43:50,319
Speaker 5: like they're going to add stuff and then it's going

907
00:43:50,360 --> 00:43:51,520
Speaker 5: to just constantly get taken down.

908
00:43:51,560 --> 00:43:53,640
Speaker 6: But if there's anything that's not that happened to me.

909
00:43:53,840 --> 00:43:58,000
Speaker 5: My birthday was wrong for years, and there were little

910
00:43:58,040 --> 00:43:59,920
Speaker 5: things here and there, and yeah, my listeners fix.

911
00:44:00,280 --> 00:44:02,440
Speaker 6: I don't know how. I don't know how Wikipedia work.

912
00:44:02,680 --> 00:44:05,280
Speaker 1: I don't even know how it works. Also, I can't

913
00:44:05,440 --> 00:44:08,759
Speaker 1: do anything with Wikipedia because my email address has the

914
00:44:08,840 --> 00:44:09,719
Speaker 1: word bot in it.

915
00:44:09,960 --> 00:44:14,719
Speaker 2: Bot another great decision I made up.

916
00:44:14,960 --> 00:44:18,000
Speaker 1: Before the concept of bots, you know, like when Gmail

917
00:44:18,120 --> 00:44:21,759
Speaker 1: first exists, like started and now it won't. It just

918
00:44:21,800 --> 00:44:24,040
Speaker 1: thinks I'm a robot trying to come in.

919
00:44:24,200 --> 00:44:26,480
Speaker 6: Because that's what a robot does, as they call themselves.

920
00:44:26,719 --> 00:44:30,360
Speaker 3: Yeah, exactly right. Should should I bring us back to

921
00:44:31,120 --> 00:44:34,680
Speaker 3: human humanity? Let's here's the story. This one was sent

922
00:44:34,800 --> 00:44:40,520
Speaker 3: in from Alison aka anders Ag or undersag something like that.

923
00:44:40,680 --> 00:44:41,320
Speaker 2: Thank you, Alison.

924
00:44:42,600 --> 00:44:45,719
Speaker 3: Chinese woman brings twenty three relatives to her blind date

925
00:44:45,840 --> 00:44:48,600
Speaker 3: to test if her potential boyfriend is generous, before being

926
00:44:48,680 --> 00:44:51,160
Speaker 3: stranded with a three thousand dollars bill.

927
00:44:53,880 --> 00:44:57,080
Speaker 1: Okay, so this is what happened currently. This is a

928
00:44:57,160 --> 00:44:57,840
Speaker 1: current story.

929
00:44:58,000 --> 00:45:00,319
Speaker 3: Yes, this is from the best of the best Daily

930
00:45:00,400 --> 00:45:03,680
Speaker 3: Mirror UK. You know, if it's Daily Mirror, it's one

931
00:45:03,800 --> 00:45:09,440
Speaker 3: hundred percent accurate. So I will also say that the

932
00:45:09,760 --> 00:45:13,680
Speaker 3: number of times they say Chinese woman, even though we're

933
00:45:13,840 --> 00:45:17,440
Speaker 3: in China, like it's gonna be here we go. A

934
00:45:17,520 --> 00:45:20,839
Speaker 3: woman in China has seen her blind date go horribly wrong.

935
00:45:21,120 --> 00:45:24,480
Speaker 3: After bringing along dozens of her relatives to the romantic

936
00:45:24,520 --> 00:45:29,399
Speaker 3: occasion to test her companion's generosity without telling her date

937
00:45:29,480 --> 00:45:33,520
Speaker 3: in advance, the Chinese woman allegedly showed up with twenty

938
00:45:33,640 --> 00:45:36,560
Speaker 3: three family members and turned their candlelit dinner into a

939
00:45:36,719 --> 00:45:40,680
Speaker 3: rowdy banquet. She was eventually left stranded with a whopping

940
00:45:40,880 --> 00:45:45,239
Speaker 3: three thousand dollars American bill after her potential mister Wright,

941
00:45:45,440 --> 00:45:48,880
Speaker 3: fled the restaurant upon receiving the check. Of course, he

942
00:45:49,000 --> 00:45:52,880
Speaker 3: did as he should. I'm gonna stop saying it. But

943
00:45:53,000 --> 00:45:56,200
Speaker 3: the Chinese woman who remains anonymous, recently went on a

944
00:45:56,320 --> 00:45:59,800
Speaker 3: date with twenty nine year old mister Liu in Eastern

945
00:46:00,120 --> 00:46:03,880
Speaker 3: in the Eastern Chinese province of Xijiang. According to the

946
00:46:03,960 --> 00:46:06,800
Speaker 3: report that the date was set up by the man's

947
00:46:06,880 --> 00:46:09,640
Speaker 3: mother after she was worried about her son, who had

948
00:46:09,640 --> 00:46:12,239
Speaker 3: been single for a while. Before the meetup, mister Liu

949
00:46:12,280 --> 00:46:14,520
Speaker 3: had offered to pay for the meal, assuming that it

950
00:46:14,520 --> 00:46:16,799
Speaker 3: would be a romantic dinner for two. He was taken

951
00:46:16,880 --> 00:46:19,200
Speaker 3: by surprise when he saw his blind date, who arrived

952
00:46:19,200 --> 00:46:21,120
Speaker 3: at the restaurant with two dozen relatives.

953
00:46:21,280 --> 00:46:23,200
Speaker 2: I mean that is so many people.

954
00:46:23,920 --> 00:46:25,760
Speaker 1: Uh, that's a lot of people.

955
00:46:25,920 --> 00:46:27,080
Speaker 2: That's a lot of people.

956
00:46:28,040 --> 00:46:30,320
Speaker 3: The woman told Chinese media later that she wanted to

957
00:46:30,360 --> 00:46:32,440
Speaker 3: test her potential boyfriend was gener enough to pay for

958
00:46:32,520 --> 00:46:35,160
Speaker 3: a feast of twenty five people. After the luxurious banquet,

959
00:46:35,200 --> 00:46:38,440
Speaker 3: the woman and her family were shocked to find out

960
00:46:38,600 --> 00:46:42,600
Speaker 3: mister Liu had escaped from the restaurant. I think escaped

961
00:46:42,680 --> 00:46:45,719
Speaker 3: is the exact right word for this too, Like, oh,

962
00:46:45,840 --> 00:46:48,440
Speaker 3: he must have been so overwhelmed. It is reported that

963
00:46:48,520 --> 00:46:50,880
Speaker 3: he dashed off after seeing the bill, which added up

964
00:46:50,920 --> 00:46:54,719
Speaker 3: to the expensive amount thanks to expensive dishes and alcohol

965
00:46:54,960 --> 00:46:56,160
Speaker 3: ordered by the relatives.

966
00:46:58,080 --> 00:47:00,759
Speaker 5: He failed his general I just calculate related that that's

967
00:47:00,760 --> 00:47:03,120
Speaker 5: one hundred and twenty five dollars US per person.

968
00:47:03,360 --> 00:47:05,359
Speaker 6: Yes, that's a that's a nice meeting.

969
00:47:05,440 --> 00:47:10,600
Speaker 5: Yes, desin it, Like that's like a birthday, like a anniversary, kind.

970
00:47:10,480 --> 00:47:13,000
Speaker 1: Of twenty five dollars. That if you go out and

971
00:47:13,040 --> 00:47:14,480
Speaker 1: you're in a group and you end up having to

972
00:47:14,520 --> 00:47:16,320
Speaker 1: pay one hundred and twenty five dollars.

973
00:47:16,480 --> 00:47:18,960
Speaker 2: Yeah, bummed you had a night totally.

974
00:47:19,120 --> 00:47:21,880
Speaker 6: Yeah, You're like, I drink seventeen bottles of what?

975
00:47:22,200 --> 00:47:25,440
Speaker 1: Yeah, I'm never that. I'm always like I drank that much.

976
00:47:25,840 --> 00:47:28,560
Speaker 3: Yeah, because I've gotten stuck with Kurt, and I've gotten

977
00:47:28,560 --> 00:47:32,200
Speaker 3: stuck a few times covering we've got costics.

978
00:47:32,640 --> 00:47:33,960
Speaker 1: Ooh fucking comics.

979
00:47:34,040 --> 00:47:36,320
Speaker 6: Man, I hate that too because I don't drink.

980
00:47:36,480 --> 00:47:38,640
Speaker 5: Yeah, and so it's like I'm always that person at

981
00:47:38,640 --> 00:47:41,360
Speaker 5: the table is like, really, guys, like really, like my

982
00:47:41,480 --> 00:47:43,240
Speaker 5: food was like fourteen dollars?

983
00:47:43,480 --> 00:47:45,040
Speaker 6: How am I stuck paying forty?

984
00:47:45,239 --> 00:47:47,440
Speaker 2: Yeah? That's unfair. And that's a good tip too.

985
00:47:47,560 --> 00:47:49,200
Speaker 3: If you go out and you're not a drinker, just

986
00:47:49,280 --> 00:47:51,759
Speaker 3: take the amount of alcohol off and split it with

987
00:47:51,880 --> 00:47:52,400
Speaker 3: that person.

988
00:47:52,520 --> 00:47:54,640
Speaker 2: Like people don't do that. But it's so obvious.

989
00:47:54,719 --> 00:47:57,120
Speaker 3: Boos is like when I when I take months off

990
00:47:57,200 --> 00:48:00,000
Speaker 3: and don't drink, it's like the mind going out to dinner,

991
00:48:00,120 --> 00:48:03,480
Speaker 3: the checks drop, I don't know, thirty percent, Like it's crazy,

992
00:48:03,560 --> 00:48:05,000
Speaker 3: how oh significantly?

993
00:48:05,239 --> 00:48:07,160
Speaker 6: Yeah yeah yeah, and then the tip is smaller too.

994
00:48:07,440 --> 00:48:12,120
Speaker 2: Yeah, well that's true. Okay, I'll wrap this one up. Sight.

995
00:48:12,239 --> 00:48:15,640
Speaker 3: So they later had an agreement that mister Lee would

996
00:48:15,640 --> 00:48:17,160
Speaker 3: pay for a small part of the meal, with the

997
00:48:17,239 --> 00:48:20,600
Speaker 3: brunt of the bill shared among the women's twenty three

998
00:48:20,680 --> 00:48:24,000
Speaker 3: family members. This event spark heated discussion on social media,

999
00:48:24,080 --> 00:48:27,920
Speaker 3: of course, across many websites. One reader wrote, men should

1000
00:48:27,960 --> 00:48:30,680
Speaker 3: pay out of courtesy, but bring twenty three people to

1001
00:48:30,760 --> 00:48:34,400
Speaker 3: the meal is unacceptable. Yes, and then this one's kind

1002
00:48:34,400 --> 00:48:37,880
Speaker 3: of interesting because this must be just a cultural difference.

1003
00:48:38,080 --> 00:48:41,080
Speaker 3: Another commenter said, usually the woman would bring one or

1004
00:48:41,120 --> 00:48:45,040
Speaker 3: two friends in case it gets awkward. See to me, anyways,

1005
00:48:46,080 --> 00:48:48,640
Speaker 3: as a gentleman, we should pay. If the woman brings

1006
00:48:48,719 --> 00:48:51,120
Speaker 3: seven or eight people, you should just leave. She wasn't

1007
00:48:51,200 --> 00:48:52,640
Speaker 3: genuine anyways, so.

1008
00:48:53,200 --> 00:48:55,480
Speaker 1: Right, she just obviously didn't want to go on that date.

1009
00:48:56,200 --> 00:48:59,520
Speaker 5: Yes, how did they even accommodate them? Did they make

1010
00:48:59,560 --> 00:49:02,480
Speaker 5: a red without him knowing after the fact? Did they say, oh,

1011
00:49:02,560 --> 00:49:04,479
Speaker 5: also plus twenty two more?

1012
00:49:05,160 --> 00:49:05,359
Speaker 7: Yeah?

1013
00:49:05,960 --> 00:49:06,279
Speaker 3: What like?

1014
00:49:06,440 --> 00:49:08,040
Speaker 6: How did they even have table? Yeah?

1015
00:49:08,040 --> 00:49:10,120
Speaker 1: What restaurant is just like, oh, yeah, of course, did

1016
00:49:10,200 --> 00:49:12,080
Speaker 1: you add a table for two? But you want to

1017
00:49:12,160 --> 00:49:13,280
Speaker 1: change it to twenty five?

1018
00:49:14,080 --> 00:49:14,960
Speaker 2: You have no problem?

1019
00:49:15,080 --> 00:49:18,719
Speaker 3: The problem in all of me, it's a that's a

1020
00:49:18,800 --> 00:49:21,919
Speaker 3: lot of people, and it's also funny, like it must

1021
00:49:22,000 --> 00:49:23,920
Speaker 3: be just a cultural difference because if I went on

1022
00:49:24,000 --> 00:49:26,600
Speaker 3: a blind date with somebody and they brought two friends,

1023
00:49:26,840 --> 00:49:29,880
Speaker 3: I would be like, well, let's get let's have a round,

1024
00:49:29,960 --> 00:49:31,719
Speaker 3: and then I'm out of here. Like it's nice to

1025
00:49:31,760 --> 00:49:33,400
Speaker 3: meet people, but I'm like, that's not a date at

1026
00:49:33,400 --> 00:49:35,040
Speaker 3: that point. That's just like a book club.

1027
00:49:36,400 --> 00:49:39,120
Speaker 5: But also like your blind date would either probably have

1028
00:49:39,200 --> 00:49:41,800
Speaker 5: been through an app or set up by a friend.

1029
00:49:41,920 --> 00:49:44,200
Speaker 5: Whereas you're right, culturally, I think a lot of blind

1030
00:49:44,320 --> 00:49:48,880
Speaker 5: dates in like Southeast Asia or Asia. Not not every country, right,

1031
00:49:48,920 --> 00:49:52,000
Speaker 5: but countries where the parents were involved in that planning.

1032
00:49:52,920 --> 00:49:55,040
Speaker 5: You might want a little bit of backup because you're like,

1033
00:49:55,080 --> 00:49:56,160
Speaker 5: I do not trust my.

1034
00:49:56,200 --> 00:49:57,760
Speaker 6: Mother, right, Like I have no idea.

1035
00:49:57,840 --> 00:49:59,319
Speaker 2: Oh I see that's a good thing.

1036
00:49:59,480 --> 00:50:03,719
Speaker 1: Yeah yeah, yeah, you're interesting. All right, you guys want

1037
00:50:03,719 --> 00:50:06,280
Speaker 1: to have another one. We have gotten through so few stories.

1038
00:50:06,400 --> 00:50:08,840
Speaker 2: Who cares. We're having fun, We're learning.

1039
00:50:09,040 --> 00:50:10,880
Speaker 3: I learned that if I you know, I'm gonn dressed

1040
00:50:10,880 --> 00:50:13,000
Speaker 3: like a door this Halloween, so if anybody's a flamethrower,

1041
00:50:13,080 --> 00:50:15,319
Speaker 3: I'm just going to tackle him to save the day.

1042
00:50:15,480 --> 00:50:15,920
Speaker 6: Amazing.

1043
00:50:18,600 --> 00:50:22,080
Speaker 1: This is from the Daily Star, so you know it's true.

1044
00:50:22,239 --> 00:50:24,680
Speaker 2: You gotta trust the Daily Star.

1045
00:50:25,320 --> 00:50:28,960
Speaker 1: This is sentence by O'Malley underscore twelve Thank you O'Malley.

1046
00:50:29,760 --> 00:50:33,000
Speaker 1: Depressed and lonely fish who ate every friend he's had

1047
00:50:33,160 --> 00:50:40,120
Speaker 1: celebrate sixteenth birthday. Oh okay, and it says a depressed

1048
00:50:40,160 --> 00:50:42,840
Speaker 1: fish has celebrated his sixteenth birthday in Finland with a

1049
00:50:42,920 --> 00:50:49,440
Speaker 1: cake and candles and a brief moment of happiness. Miko

1050
00:50:49,560 --> 00:50:53,000
Speaker 1: fell into depression when Linna Maki's Sea Life Center in

1051
00:50:53,080 --> 00:50:57,240
Speaker 1: Helsinki had to close for coronavirus lockdown, leading staff leading

1052
00:50:57,280 --> 00:50:59,440
Speaker 1: to staff going out of their way to help him.

1053
00:51:00,040 --> 00:51:03,160
Speaker 1: The grumpy looking group of fish has had depressive episodes

1054
00:51:03,239 --> 00:51:05,759
Speaker 1: throughout his life due to loneliness, which is mostly caused

1055
00:51:05,800 --> 00:51:08,120
Speaker 1: by his habit of eating the other fish in his tank.

1056
00:51:09,040 --> 00:51:12,560
Speaker 1: His most recent recent pal, a poisonous red lionfish, was

1057
00:51:12,680 --> 00:51:16,400
Speaker 1: also eaten. They bring him a cake made out of

1058
00:51:16,480 --> 00:51:19,880
Speaker 1: salmon for his birthday. He gets excited, he eats it.

1059
00:51:21,080 --> 00:51:23,000
Speaker 1: But this is the best line of the whole thing,

1060
00:51:23,400 --> 00:51:25,400
Speaker 1: So he like the reason that they know he's depressed.

1061
00:51:25,680 --> 00:51:27,160
Speaker 1: The big question is like, how is this? How do

1062
00:51:27,239 --> 00:51:30,920
Speaker 1: they know he's depressed? He changes color when he is

1063
00:51:31,120 --> 00:51:34,200
Speaker 1: happy and excited and then goes to like a deep,

1064
00:51:34,280 --> 00:51:37,239
Speaker 1: dark purple blue when he is depressed. Oh boy, who

1065
00:51:37,360 --> 00:51:38,080
Speaker 1: take care of him?

1066
00:51:38,440 --> 00:51:38,640
Speaker 2: Wow?

1067
00:51:40,040 --> 00:51:41,959
Speaker 1: So that is the majority of the article, But here's

1068
00:51:42,000 --> 00:51:42,600
Speaker 1: the best line.

1069
00:51:42,840 --> 00:51:44,200
Speaker 2: Yeah, don't eat your friends.

1070
00:51:44,440 --> 00:51:48,520
Speaker 1: First of all, has a sociable animal. Miko is notably

1071
00:51:48,600 --> 00:51:51,160
Speaker 1: happier when he is put in tanks with other fish,

1072
00:51:51,560 --> 00:51:55,240
Speaker 1: with whom he interacts and plays before eventually eating.

1073
00:51:59,200 --> 00:52:02,800
Speaker 5: Maybe they meant to say as a predatory. He is

1074
00:52:03,040 --> 00:52:06,280
Speaker 5: most happy when plotting the demise of his friends.

1075
00:52:07,719 --> 00:52:09,839
Speaker 1: But if I love the idea of a fish who

1076
00:52:10,600 --> 00:52:13,680
Speaker 1: who just can't help himself, that it's such a great

1077
00:52:13,800 --> 00:52:17,640
Speaker 1: character for an animated character. Do you know who just love?

1078
00:52:17,760 --> 00:52:21,200
Speaker 1: He's so lonely and he loves when he sees other people,

1079
00:52:21,320 --> 00:52:25,399
Speaker 1: but then he always eats them. Yes, that he can't

1080
00:52:25,480 --> 00:52:27,920
Speaker 1: help himself. It's beautiful. It's a compulsive and.

1081
00:52:27,960 --> 00:52:31,320
Speaker 5: He has like this existential crisis, like why was I

1082
00:52:31,480 --> 00:52:32,719
Speaker 5: designed this way?

1083
00:52:33,400 --> 00:52:36,040
Speaker 6: Own nature? You make me so hungry?

1084
00:52:36,080 --> 00:52:38,480
Speaker 1: I guess you know now that I think about it.

1085
00:52:38,600 --> 00:52:41,360
Speaker 1: It's just the shark from finding Nemo. I just realized

1086
00:52:42,680 --> 00:52:44,160
Speaker 1: it's okay, it's kind of sorry.

1087
00:52:44,320 --> 00:52:46,439
Speaker 3: Well, you had that dog that ate that sugar? Didn't

1088
00:52:46,480 --> 00:52:48,360
Speaker 3: your dog ate a butlerad of sugar?

1089
00:52:48,480 --> 00:52:50,440
Speaker 1: Right when I was like, Yeah, when I was a kid,

1090
00:52:50,520 --> 00:52:54,080
Speaker 1: we had a four we had a nine pound poodle

1091
00:52:54,280 --> 00:52:56,320
Speaker 1: And when we're gone all day, we're gone for like

1092
00:52:56,400 --> 00:52:58,520
Speaker 1: eight hours, and while we were gone, the cat knocked

1093
00:52:58,560 --> 00:53:01,240
Speaker 1: a five pound bag of power sugar onto the ground

1094
00:53:01,600 --> 00:53:06,440
Speaker 1: and then the dog ate all five pounds of powdered sugar.

1095
00:53:07,200 --> 00:53:07,799
Speaker 6: Did he live?

1096
00:53:08,000 --> 00:53:08,279
Speaker 4: He let?

1097
00:53:08,360 --> 00:53:10,520
Speaker 1: Yeah, he vomited for like three days, but he was

1098
00:53:10,560 --> 00:53:13,279
Speaker 1: totally fine. But I, like my joke about it was

1099
00:53:13,320 --> 00:53:16,719
Speaker 1: always like I can only imagine his day. We're like

1100
00:53:17,480 --> 00:53:21,239
Speaker 1: manna falls from heaven and he like gets into it.

1101
00:53:21,320 --> 00:53:23,600
Speaker 1: He's like, hmm, this is pretty good. But probably after

1102
00:53:23,760 --> 00:53:28,279
Speaker 1: like two pounds of just licking powdered sugar, he's probably like, ooh,

1103
00:53:28,960 --> 00:53:32,160
Speaker 1: I don't feel too good. But then something in his

1104
00:53:32,280 --> 00:53:35,480
Speaker 1: little doggy mind was like, but when is this gonna

1105
00:53:35,560 --> 00:53:39,279
Speaker 1: happen again? And I got back in there finish all

1106
00:53:39,400 --> 00:53:40,520
Speaker 1: five pounds of sugar.

1107
00:53:42,520 --> 00:53:44,239
Speaker 6: This is how I feel every time I eat it.

1108
00:53:44,320 --> 00:53:44,520
Speaker 2: Chicken.

1109
00:53:45,520 --> 00:53:46,680
Speaker 1: It's like so sad.

1110
00:53:47,120 --> 00:53:49,160
Speaker 6: It's like it's like it's like.

1111
00:53:49,600 --> 00:53:51,840
Speaker 5: The you know, the universe is punishing me for like

1112
00:53:52,080 --> 00:53:57,160
Speaker 5: just really indulging in homophobic chickens. Everything I believe and

1113
00:53:57,280 --> 00:54:00,360
Speaker 5: I always feel super ill, tied to the back, and

1114
00:54:00,400 --> 00:54:03,680
Speaker 5: then immediately like make a donation to thees every time,

1115
00:54:03,800 --> 00:54:04,799
Speaker 5: might eat it chick full.

1116
00:54:05,480 --> 00:54:08,879
Speaker 3: Oh good now, it's I was felt that way when

1117
00:54:08,920 --> 00:54:10,880
Speaker 3: I lived in New York and I was just broke.

1118
00:54:10,960 --> 00:54:13,799
Speaker 3: Whenever a bar would have like an anniversary and they

1119
00:54:13,800 --> 00:54:15,759
Speaker 3: would do like an open bar from eight to ten

1120
00:54:15,880 --> 00:54:17,880
Speaker 3: or whatever it was, my friends would know to call

1121
00:54:18,000 --> 00:54:20,600
Speaker 3: me and we would order top shelf whatever, and we

1122
00:54:20,640 --> 00:54:22,000
Speaker 3: would order the worst drink.

1123
00:54:22,040 --> 00:54:23,120
Speaker 2: We would order long on.

1124
00:54:23,280 --> 00:54:25,040
Speaker 3: Iced tea's because it had the most alcohol and was

1125
00:54:25,360 --> 00:54:27,040
Speaker 3: you know, it was like so we would just get

1126
00:54:27,200 --> 00:54:29,920
Speaker 3: so bombed in two and then it was only nine

1127
00:54:29,960 --> 00:54:32,719
Speaker 3: o'clock and then you're like, I guess we just keep going,

1128
00:54:32,960 --> 00:54:35,319
Speaker 3: like but it always felt like we were getting back

1129
00:54:35,360 --> 00:54:37,480
Speaker 3: at something that might never happen again. In a town

1130
00:54:37,480 --> 00:54:39,880
Speaker 3: where you're about six dollars for beers, you're like, tonight's

1131
00:54:39,920 --> 00:54:40,560
Speaker 3: my tonight.

1132
00:54:40,640 --> 00:54:43,759
Speaker 2: I make my stand and my liver is like, please, God,

1133
00:54:43,840 --> 00:54:44,160
Speaker 2: don't do.

1134
00:54:44,280 --> 00:54:44,759
Speaker 4: This to us.

1135
00:54:45,480 --> 00:54:48,080
Speaker 5: Yeah, right, like it forgets that there's only so much

1136
00:54:48,120 --> 00:54:51,680
Speaker 5: alcohol you can consume. I mean it's sort of like interestingly,

1137
00:54:51,800 --> 00:54:53,759
Speaker 5: and this is a weird tangent, but have you guys

1138
00:54:53,760 --> 00:54:57,160
Speaker 5: ever seen Inequality at All? The documentary by Robert n

1139
00:54:57,840 --> 00:55:01,319
Speaker 5: that's sort of the concept of the documentary. It's he's

1140
00:55:01,360 --> 00:55:04,200
Speaker 5: trying to debunk trickle down economics and debunk the idea

1141
00:55:04,520 --> 00:55:07,040
Speaker 5: that if we just stimulate the economy for rich people,

1142
00:55:07,200 --> 00:55:11,000
Speaker 5: poor people will eventually experience the benefits.

1143
00:55:11,160 --> 00:55:12,439
Speaker 6: And he makes this beautiful point.

1144
00:55:12,480 --> 00:55:14,280
Speaker 5: There's like a super rich guy on it who's actually

1145
00:55:14,400 --> 00:55:17,560
Speaker 5: very progressive, and he's like, listen, I yes, when I

1146
00:55:17,640 --> 00:55:20,319
Speaker 5: buy a car, I buy a two hundred fifty thousand car,

1147
00:55:20,640 --> 00:55:23,040
Speaker 5: thousand dollars cars, a very fancy cars, whatever. But I'm

1148
00:55:23,080 --> 00:55:25,600
Speaker 5: still only one person and I can only drive one car.

1149
00:55:26,080 --> 00:55:28,359
Speaker 5: I can't drive fifty of those cars. You know, When

1150
00:55:28,360 --> 00:55:30,320
Speaker 5: I sleep at night, I sleep on the most expensive

1151
00:55:30,360 --> 00:55:32,759
Speaker 5: pillow imaginable. But there's only so many pillows that fit

1152
00:55:32,840 --> 00:55:33,359
Speaker 5: on my bed.

1153
00:55:33,840 --> 00:55:35,080
Speaker 6: And that's sort of.

1154
00:55:35,160 --> 00:55:39,000
Speaker 5: The point, right, You can't like drink all like you

1155
00:55:39,040 --> 00:55:41,320
Speaker 5: can't make up for all, or it's like sleep, banking

1156
00:55:41,480 --> 00:55:43,439
Speaker 5: or anything else. Your body is going to be really

1157
00:55:43,520 --> 00:55:45,520
Speaker 5: pissed at you if you try to make up for all.

1158
00:55:46,160 --> 00:55:50,440
Speaker 5: And that is why in Texas historically happy Hour. So

1159
00:55:50,560 --> 00:55:52,359
Speaker 5: I grew up and born and raised in Texas Live

1160
00:55:52,400 --> 00:55:53,720
Speaker 5: the Life before Coming.

1161
00:55:54,040 --> 00:55:57,800
Speaker 2: Plain O, just how do you know that research.

1162
00:55:59,360 --> 00:55:59,719
Speaker 4: You did?

1163
00:56:01,080 --> 00:56:02,400
Speaker 6: Plano as a comedy fit.

1164
00:56:03,000 --> 00:56:04,800
Speaker 1: I think it's their second year. They asked me to

1165
00:56:04,840 --> 00:56:06,160
Speaker 1: do it. Last year I couldn't do it, and then

1166
00:56:06,160 --> 00:56:07,880
Speaker 1: this year they did it virtually, So I just did

1167
00:56:07,920 --> 00:56:10,200
Speaker 1: it from where you're seeing me sit right now.

1168
00:56:10,400 --> 00:56:10,640
Speaker 5: Cool.

1169
00:56:11,040 --> 00:56:13,160
Speaker 6: That's amazing. It's so weird.

1170
00:56:14,400 --> 00:56:16,320
Speaker 5: Yeah, I thought we were only known for being like

1171
00:56:16,440 --> 00:56:19,279
Speaker 5: the first episode of True Life on MTV, all about

1172
00:56:19,320 --> 00:56:20,279
Speaker 5: like the heroin.

1173
00:56:20,000 --> 00:56:21,919
Speaker 6: Epidemic the nineties.

1174
00:56:23,239 --> 00:56:26,480
Speaker 5: But anyway, so yeah, growing up in plan oh blah

1175
00:56:26,520 --> 00:56:27,600
Speaker 5: blah blah, What the hell was I to?

1176
00:56:27,760 --> 00:56:27,880
Speaker 4: Oh?

1177
00:56:28,360 --> 00:56:28,680
Speaker 6: Happy?

1178
00:56:28,880 --> 00:56:29,080
Speaker 2: Yes?

1179
00:56:29,400 --> 00:56:31,400
Speaker 6: Right, So I've never been a drinker. That just was

1180
00:56:31,480 --> 00:56:32,880
Speaker 6: never my thing. But obviously I.

1181
00:56:32,880 --> 00:56:33,520
Speaker 1: Grew up in Texas.

1182
00:56:33,560 --> 00:56:35,239
Speaker 6: All my friends were like kissock all the time.

1183
00:56:35,640 --> 00:56:38,799
Speaker 5: And we learned that happy hour cannot only be an

1184
00:56:38,800 --> 00:56:41,759
Speaker 5: hour legally in Texas because so many people would just

1185
00:56:41,920 --> 00:56:45,759
Speaker 5: slam drinks during that short period of time because they

1186
00:56:45,760 --> 00:56:48,520
Speaker 5: were cheaper, and then they were just horrible drunk driving

1187
00:56:48,680 --> 00:56:51,279
Speaker 5: collisions and things like that. So happy hours now got

1188
00:56:51,360 --> 00:56:54,160
Speaker 5: like a minimum of X number of hours just to

1189
00:56:54,239 --> 00:56:57,000
Speaker 5: try and reduce people from acting like crazy assholes.

1190
00:56:58,360 --> 00:57:01,719
Speaker 2: It works. Great. I didn't realize that. I love that.

1191
00:57:02,120 --> 00:57:06,759
Speaker 1: Yeah, well, guys, we have reached the end of our

1192
00:57:07,080 --> 00:57:09,400
Speaker 1: hour with Kara, thank you so much for being on

1193
00:57:09,480 --> 00:57:09,839
Speaker 1: the show.

1194
00:57:10,840 --> 00:57:11,600
Speaker 6: Thanks for having me.

1195
00:57:11,800 --> 00:57:14,600
Speaker 1: Yeah, what would you like to plug on the way out?

1196
00:57:15,800 --> 00:57:18,400
Speaker 5: I mean, you know, lot's going on, but I would

1197
00:57:18,440 --> 00:57:21,120
Speaker 5: say the big thing is my show Talk Nerdy with

1198
00:57:21,240 --> 00:57:22,120
Speaker 5: Cara Santa Maria.

1199
00:57:22,200 --> 00:57:23,120
Speaker 6: Pretty easy to find.

1200
00:57:23,440 --> 00:57:25,560
Speaker 5: It's a one out, one to one and a half

1201
00:57:25,640 --> 00:57:30,080
Speaker 5: hour weekly science interview podcast. It's been around four, I

1202
00:57:30,120 --> 00:57:32,400
Speaker 5: don't know, five years. I'm on episode like three hundred

1203
00:57:32,440 --> 00:57:33,480
Speaker 5: and thirty something.

1204
00:57:33,960 --> 00:57:34,280
Speaker 6: I don't know.

1205
00:57:35,720 --> 00:57:36,320
Speaker 1: Lots of fun.

1206
00:57:36,600 --> 00:57:38,720
Speaker 5: It's it's got really long legs too, so if you're

1207
00:57:38,800 --> 00:57:40,640
Speaker 5: new to the show, you can go back to old

1208
00:57:40,720 --> 00:57:43,080
Speaker 5: episodes and a lot of stuff is really evergreen in it,

1209
00:57:43,080 --> 00:57:43,720
Speaker 5: which is great.

1210
00:57:44,080 --> 00:57:47,240
Speaker 1: I'm also just listen on this Industrial espionage.

1211
00:57:47,840 --> 00:57:49,080
Speaker 6: Oh, that one's fascinating.

1212
00:57:49,160 --> 00:57:50,960
Speaker 5: She was good. Yeah, And I've got one coming out

1213
00:57:51,040 --> 00:57:55,720
Speaker 5: soon on the animal penis heard of it and what

1214
00:57:55,880 --> 00:57:59,320
Speaker 5: we write and what we actually don't know about animal

1215
00:57:59,640 --> 00:58:01,000
Speaker 5: vagil I know is because we.

1216
00:58:01,320 --> 00:58:04,520
Speaker 2: Only study ding dongs. I was reading about that. Stop

1217
00:58:04,640 --> 00:58:06,560
Speaker 2: studying ding dongs, guys.

1218
00:58:06,920 --> 00:58:09,960
Speaker 6: So much ding dong today. I also have right. I

1219
00:58:10,000 --> 00:58:12,160
Speaker 6: also have one coming out soon about books Bound in

1220
00:58:12,280 --> 00:58:18,120
Speaker 6: Human Flesh. Whow Yeah a librarian here in La. Super interesting.

1221
00:58:18,320 --> 00:58:21,040
Speaker 6: Yeah so really fun. Check it out.

1222
00:58:21,040 --> 00:58:22,960
Speaker 5: You can go to talk Nerdy dot com or keros

1223
00:58:22,960 --> 00:58:26,040
Speaker 5: Anamria dot com and learn everything there is to learn there,

1224
00:58:26,120 --> 00:58:28,320
Speaker 5: and you'll see all my social links too. Because I'm

1225
00:58:28,320 --> 00:58:32,000
Speaker 5: pretty active on social media mostly, I would say Twitter, That's.

1226
00:58:31,880 --> 00:58:35,880
Speaker 6: Where I tend to curate science stories.

1227
00:58:35,960 --> 00:58:37,600
Speaker 5: So if you follow me on Twitter, you will get

1228
00:58:38,440 --> 00:58:42,160
Speaker 5: five science stories that I think are really important, really relevant,

1229
00:58:42,200 --> 00:58:43,440
Speaker 5: really fresh, every single.

1230
00:58:43,240 --> 00:58:45,400
Speaker 1: Wow in your going right now.

1231
00:58:46,760 --> 00:58:50,680
Speaker 2: Twitter. Thank you Callow so great. I would love to

1232
00:58:50,720 --> 00:58:53,800
Speaker 2: have you back. Thank thanks for doing the show. Of course,

1233
00:58:53,840 --> 00:58:55,280
Speaker 2: Bananas Bananas.

1234
00:59:03,080 --> 00:59:05,000
Speaker 1: This has been an exactly right production.

1235
00:59:05,040 --> 00:59:07,280
Speaker 2: Produced and engineered by Katie Levine.

1236
00:59:07,440 --> 00:59:09,760
Speaker 1: Theme song by Khan Amani.

1237
00:59:09,640 --> 00:59:11,960
Speaker 2: And all of our artwork is done by Travis Millard.

1238
00:59:12,080 --> 00:59:15,760
Speaker 1: So please follow us on Instagram at The Bananas Podcast,

1239
00:59:15,840 --> 00:59:18,160
Speaker 1: where we post so many more stories and make it here,

1240
00:59:18,760 --> 00:59:19,280
Speaker 1: and you can.

1241
00:59:19,200 --> 00:59:21,800
Speaker 3: Share with us your strange news story by d ming

1242
00:59:21,880 --> 00:59:24,040
Speaker 3: us on Instagram at the Bananas Podcast.

1243
00:59:24,280 --> 00:59:26,960
Speaker 1: So listen, subscribe, and please leave us a review on

1244
00:59:27,000 --> 00:59:32,360
Speaker 1: Apple podcast, Stitcher or wherever you get your podcasts, bananas, bananas,