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Speaker 1: The show.

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Speaker 2: That reminds you. If these clowns can.

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Speaker 3: Get ahead, so can you.

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Speaker 4: Rover's morning, Glory's playing the shoes just coming up in

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Speaker 4: a few minutes.

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Speaker 1: What do you have on the way, Dougi.

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Speaker 5: There's a reason why you shouldn't always be around hot temperatures, Rover.

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Speaker 6: Whether it's your home.

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Speaker 5: In Florida or your home in Ohio, whatever it may be, you're.

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Speaker 1: Always too hot. I like to stay at seventy eight

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Speaker 1: degrees fahrenheit, twenty four hours a day, seven days a week,

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Speaker 1: three hundred and sixty five days a year. Absolutely, seventy eight.

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Speaker 1: That's my base temperature.

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Speaker 6: All right, I'll tell you why that's bad.

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Speaker 1: Next, Garbage Man's sixty nine says, don't even bother applying

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Speaker 1: for the ranch Bassador position China.

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Speaker 2: You know it's going.

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Speaker 1: To be all d Yeah, all right, we'll keep let's

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Speaker 1: see who's named let's see who's named Ranch Bass, and

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Speaker 1: we'll keep track of that.

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Speaker 2: It's what weird I was obsess over.

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Speaker 1: I did have a lot of people email me, I

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Speaker 1: have not seen the movie.

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Speaker 2: What was the Sinners? Is that the movie?

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Speaker 1: I I haven't seen it, but a lot of people

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Speaker 1: were emailing me that that only one. It didn't win

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Speaker 1: this Best Picture, but the guy won Best Actor for

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Speaker 1: that and it won some other awards. He said that

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Speaker 1: he saw a terrible movie only one because of d I.

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Speaker 1: You guys have seen the movie, Is it a worthy

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Speaker 1: Oscar film?

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Speaker 7: I didn't think it was terrible at all. It's really good.

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Speaker 7: But I don't know if it was an Oscar film.

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Speaker 7: It was a horror movie, and it was a weirdness.

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Speaker 7: Yours a weird It was a weird horror movie that

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Speaker 7: I had no idea what I was going to and

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Speaker 7: I thought it was going to be some sort of

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Speaker 7: Depression era bootlegging pro like operation. That's what the movie

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Speaker 7: was about, and that's what it started off as. And

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Speaker 7: then it turns the vampires and what vampires writes? That's yeah,

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Speaker 7: not knowing anything either. And then also music like music

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Speaker 7: is weaved throughout it. And one really one scene was

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Speaker 7: really cool, kind of took you out of the movie,

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Speaker 7: but it was cool how they did music through the

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Speaker 7: ages kind of thing in this gin joint and it

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Speaker 7: was kind of neat, but everybody's like, that's so awesome.

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Speaker 1: It was cool.

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Speaker 2: I don't know if it was a music video in

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Speaker 2: the middle of the league.

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Speaker 1: But I guess, and I don't know if it has

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Speaker 1: anything could do with the EI. I would say that

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Speaker 1: this seems to be the thing with the Oscars lately,

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Speaker 1: is that just a good movie what used to be

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Speaker 1: a good movie is now considered Oscar worthy. And maybe

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Speaker 1: that's because so many movies are so bad. Maybe they

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Speaker 1: did expand out the Best Picture nominees to ten it

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Speaker 1: used to be was it five? I think I don't remember,

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Speaker 1: so they doubled that, so they need more movies. It

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Speaker 1: just seems like, man, that doesn't e The old criticism

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Speaker 1: was that all the movies that were would win an

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Speaker 1: Academy Award were stuff nobody ever saw. You know, the

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Speaker 1: general public wouldn't go to see the Academy Award winners

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Speaker 1: because you know, there's more artsy, fartsy films, things like that.

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Speaker 1: But they were good, but just nobody went to see them.

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Speaker 1: So they said, why don't we expand it out? And

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Speaker 1: now maybe they've done it too much too far. So

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Speaker 1: what could be a good horror movie? I don't know

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Speaker 1: if it's stance.

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Speaker 2: This is the guy?

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Speaker 7: Should he have won Best Actor? He wasn't that impressed.

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Speaker 7: I mean, he played two characters at once, their twin brothers.

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Speaker 2: I don't know.

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Speaker 1: I face off wasn't that didn't he played two characters

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Speaker 1: and one.

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Speaker 7: No face off face was the one where John Travoltas

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Speaker 7: switched his face with Nicholas Cage.

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Speaker 2: Each other.

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Speaker 1: But there is there was one though where somebody what

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Speaker 1: was the one where they played the same to Winklevoss

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Speaker 1: twins those actually twins that played that.

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Speaker 7: No, that was one guy, right, yeah, it's Armie Hammer. Right, Oh,

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Speaker 7: it was Armie Hammer. Okay, am I wrong?

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Speaker 2: Yeah? Multiplicity did? That's now that's hapting.

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Speaker 7: Those were wildly different characters, all played by the same guy.

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Speaker 7: This was not that I didn't find them to be

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Speaker 7: that different of I.

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Speaker 1: Haven't seen Multiplicity, and I don't even remember that movie.

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Speaker 2: I haven't seen it.

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Speaker 8: In twenty Michael ket and Andy McDowell. Basically, he's an

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Speaker 8: overwork father. He makes duplicates himself to try to help

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Speaker 8: him with various tasks, you know, and there's a line

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Speaker 8: he goes Listen he tells where Michael Keaton tells the

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Speaker 8: duplicates listen, the only person allowed to have sex with

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Speaker 8: my wife is me, not you guys. Something along those lines.

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Speaker 8: That's the only thing I remember for that movie. He

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Speaker 8: doesn't go to plan. Let me tell you, they all

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Speaker 8: bone down his wife. Oh I was gonna watch spoiler alert.

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Speaker 8: Irene says people who claimed Dee I are just racist

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Speaker 8: and they mean black people. Oh yeah, percent couldn't.

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Speaker 1: I don't know what the guy was getting at with

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Speaker 1: the ranch. That didn't cross my mind that the I mean,

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Speaker 1: that's an obsession.

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Speaker 2: Your ranch.

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Speaker 7: You're like, you know what, I think black people are

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Speaker 7: going to take this. That's you're obsessed and weird. If

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Speaker 7: that's what the first thing you hear when you're ambassador.

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Speaker 1: What if you look at the RAN ambassadors and they

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Speaker 1: are all very multicultural?

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Speaker 2: What if it is then he was right?

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Speaker 1: Then he then there might be something to it they got.

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Speaker 7: If they were the best diverse as possible, What if

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Speaker 7: they were the best maybe they it could be. It's

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Speaker 7: just a weird thing to preemptively get mad about. You

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Speaker 7: made up a scenario in your head. This guy goes,

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Speaker 7: I think I'm going to preemptively get mad about them

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Speaker 7: hiring a black person.

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Speaker 2: That's literally but that's why he's made.

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Speaker 7: He's a scenario for himself to preemptively get mad about

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Speaker 7: it's strange to live your life.

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Speaker 1: Here is a photo Jeffrey that somebody sent. Maybe you'll

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Speaker 1: like that for Saint Patrick's Day? Would you like to

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Speaker 1: motor boat these puppies? Whoa look at the word too, Jeez,

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Speaker 1: that's filthy?

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Speaker 6: Are your mic gun?

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Speaker 2: Yeah? Oh show it?

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Speaker 7: You know it's the ariolas through the shirt. They must be.

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Speaker 1: Uh what about nipples? Are those visible?

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Speaker 9: Oh?

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Speaker 7: Yeah, they can see the nipples.

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Speaker 8: And the areolas well, and that more of the nipples

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Speaker 8: in ariolas through the shirt.

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Speaker 1: I think you see both. She's got a tight white

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Speaker 1: shirt on and the well. I don't think Jeffery could

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Speaker 1: say that word. No, she's not a lepra Kahn. She's

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Speaker 1: a lepro.

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Speaker 8: I'm not here, you mean see you next Tuesday. Yeah,

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Speaker 8: that's why I said in the shirt, that's the only

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Speaker 8: way I can phrase that.

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Speaker 1: She says happy Saint Patrick's Day from Crooked Orchid is

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Speaker 1: what she says. Do I dare take this video call

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Speaker 1: from Mary and Saint Louis? Do I dare? Do it?

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Speaker 1: Mary in Saint Louis. She looks like she's in a bathroom,

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Speaker 1: but I'm not entirely sure.

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Speaker 10: A hotel right now?

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Speaker 2: Okay, how are you.

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Speaker 11: So anytime a black person does anything, it's DEI right, like,

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Speaker 11: any single time.

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Speaker 10: Black person does anything, it's dby.

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Speaker 1: Well, I didn't I didn't invent this. I think that

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Speaker 1: people when they see I have had a lot of

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Speaker 1: comments from people when they see, for instance, with a

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Speaker 1: black pilot, a black pilot, they'll go, that's DEI. I'm like, well,

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Speaker 1: you couldn't fly that plane. So I don't know if

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Speaker 1: that's THEI. I hope it's not the EI. I hope

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Speaker 1: they're not putting pilots on planes just because of the

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Speaker 1: color of their skin.

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Speaker 2: I hope.

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Speaker 8: I would say this regardless of a person's race, ethnicity,

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Speaker 8: skin color, blah blah blah, if that person is able

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Speaker 8: to fly in aircraft safely, then I would hire that

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Speaker 8: person regardless. I mean, if that person is properly license

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Speaker 8: trained to fly air craft and do it safely, yeah,

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Speaker 8: I would have no problem. I had no quallems about

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Speaker 8: hiring aut hiring that person if that person's properly trained

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Speaker 8: and whatnot and know what they're doing.

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Speaker 2: So all right.

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Speaker 1: On one side, I would say that, no, not every

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Speaker 1: accomplishment from a minority is the EI. On the flip

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Speaker 1: side of that, would you say that sometimes there is

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Speaker 1: a push to like, let's let's really be diverse and

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Speaker 1: kind of push things into that direction. Would you say

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Speaker 1: that that happens from time to time.

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Speaker 12: What you say is a push is simply inclusion. It

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Speaker 12: is simply existing and it is simply inclusion.

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Speaker 10: And everybody has a problem.

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Speaker 1: You don't think that it's ever happened that something that

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Speaker 1: is not worthy or not as good as something else

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Speaker 1: has been uh elevated because of the it's never happened.

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Speaker 1: I'm just asking you if it's ever happened, says you.

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Speaker 1: To you, the answer is no, it's never happened.

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Speaker 12: No, it's including. It's like being inclusive. Inclusive. Inclusivity is

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Speaker 12: not DEI. It's it's and DEI is not some bad thing.

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Speaker 12: It's simply just treating people how you want to be treated,

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Speaker 12: giving them the same awards that they would give you

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Speaker 12: if you.

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Speaker 10: Made that same movie. But yet we're going to pick.

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Speaker 12: Apart everything that they do because I think white people

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Speaker 12: just want to be black people so bad, like they're

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Speaker 12: just jealous.

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Speaker 2: Because all right, maybe you're on this something there.

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Speaker 1: It is a white inferiority complex, all right, Mary, Well,

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Speaker 1: where are you today?

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Speaker 2: You're in a hotel. Where are you at?

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Speaker 11: Well, I literally can't even remember I'm in Missouri, so

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Speaker 11: I'm in my state, but I'm just like in the

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Speaker 11: middle of nowhere Missouri.

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Speaker 7: HU.

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Speaker 11: So it's really cold, and I'm wondering how Krystal's doing

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Speaker 11: because they moved up my appointment, and like she inspired

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Speaker 11: me to go to the doctor.

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Speaker 10: So like, Crystal, check in, how you doing.

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Speaker 1: I'm good, still alive.

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Speaker 6: Thanks for asking.

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Speaker 10: I'm thinking about you.

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Speaker 11: Be though, I'm really thinking about you because I'm literally

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Speaker 11: going through the same thing.

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Speaker 2: Literally, do you have assist on your ovary?

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Speaker 11: But that's what I'm thinking, yeah, yeah, because I had

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Speaker 11: one more moved when I was eighteen, and I look

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Speaker 11: pregnant right now, like literally, and I lost on my

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Speaker 11: weight and like there's a little bitty baby in there,

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Speaker 11: and it's like this crazy pain that I'm in my

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Speaker 11: back and in my lower it's a pressure. I feel

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Speaker 11: like there's a watermelon pressuring on like Michael pelvic floor.

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Speaker 2: So I'm a mess.

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Speaker 1: Well, you are carrying the burden of the world with

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Speaker 1: you all the time. She's always worked up over something,

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Speaker 1: so maybe that's what it is. A lot of a

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Speaker 1: lot of pain, up, frustration and anger you could be

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Speaker 1: carrying around in there, Mary, Be safe, Thank you have

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Speaker 1: a good one. Safe travels. Bye bye sushi. Are you

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Speaker 1: ready for the chosy? Yeah? Here we go, Hita Hizzy.

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Speaker 5: On rovers Morning Glory, an American astronaut is telling the

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Speaker 5: story of what was supposed to be a quick trip

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Speaker 5: to space that turned into nearly ten months aboard the.

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Speaker 6: International Space Station.

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Speaker 5: Barry Butch Wilmore will release a memoir called Stuck in

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Speaker 5: Space comes out today. It marks one year since his

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Speaker 5: return from a two hundred and eighty six day mission

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Speaker 5: that was originally supposed to last just a week or two.

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Speaker 5: The book will reflect on being unexpectedly stranded in orbit

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Speaker 5: and how he leaned on discipline, leadership, and faith to

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Speaker 5: get through the isolation. So a lot of people like

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Speaker 5: to go away for spring break. A lot of people

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Speaker 5: are on vacation now, and of course people go to Florida. Well,

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Speaker 5: there's some crazy video that's surfaced of thousands of spring

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Speaker 5: break beach goers fleeing the sand. Why were they fleeing?

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Speaker 5: This is out of Daytona Beach.

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Speaker 1: What do you see, Rover oh Man, is this from

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Speaker 1: a high rise. You can see down on the beach.

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Speaker 1: Somebody's filming this from our hotel room. Just what would

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Speaker 1: you say, tens of thousands of people running and scrambling.

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Speaker 1: It looks like like ants almost, you know, like when

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Speaker 1: you're looking at standing there looking at a swarm of

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Speaker 1: ants or something moving like that.

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Speaker 5: Yeah, this people scattering on the beach after a gunshot

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Speaker 5: was a gun was fired and not sure what sparked

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Speaker 5: the shooting.

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Speaker 6: Or if anyone was injured.

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Speaker 5: Cops said that one shot was fired after a fight

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Speaker 5: erupted at another bar just off the beach strip and video.

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Speaker 7: Has gone viral.

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Speaker 5: So that's kind of crazy that all those people fleeing.

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Speaker 5: Speaking of warmth and going on vacation, we have global temperatures,

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Speaker 5: of course, they continue to rise and people are becoming

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Speaker 5: less physically active, and this shift could lead to hundreds

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Speaker 5: of thousands of additional premature deaths worldwide in the coming decades.

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Speaker 6: That's according to a new study.

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Speaker 5: Researchers say that when temperatures get warmer and hotter, it

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Speaker 5: makes you have more calm, boring, you don't move, that

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Speaker 5: kind of lifestyle, and they're concerned about that.

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Speaker 1: So if it's a little bit colder, you move around

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Speaker 1: and just to stay warm. On See, when it's cold,

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Speaker 1: I don't want to do anything. I don't want to move,

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Speaker 1: and I'm kind of the opposite. I think the warmer

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Speaker 1: it is, the more likely I am to go out

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Speaker 1: and move around and be active.

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Speaker 5: Doesn't mean metabolism also rise when it's colder because it's

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Speaker 5: trying to heat your body temperature up. So is that

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Speaker 5: true or is that an old wives.

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Speaker 1: Cert It can be true to some extent. I suppose,

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Speaker 1: I don't know.

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Speaker 5: Yeah, So the hotter temperatures may push a lot of

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Speaker 5: people to live a calmer lifestyle, which can't always be good.

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Speaker 5: Merriam Webster parent Encyclopedia Britannica is suing Open AI. So,

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Speaker 5: the two hundred year old company behind the Merriam Webster

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Speaker 5: dictionaries is Open AI because they say AI is infringing

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Speaker 5: on its copyrighted material by using the dictionaries online articles

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Speaker 5: to train its technology. The lawsuit says the large language

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Speaker 5: model is using full or even partial verbatim reproductions of

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Speaker 5: its content and its breaking specific trademark and copyright laws.

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Speaker 5: Britannica says this has cannibalized its web traffic and led

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Speaker 5: to lost ad revenue.

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Speaker 6: You think they have a case.

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Speaker 1: I think they do have a case. I think, well, yeah,

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Speaker 1: I think they probably have a case. Yes, you put

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Speaker 1: this stuff up on the Internet publicly, but you also

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Speaker 1: have a terms of service for the use of this material,

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Speaker 1: and scraping it and using it to train AI is

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Speaker 1: a violation of those terms of service. So you know,

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Speaker 1: it's not only dictionary places, it's anybody that has any

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Speaker 1: content on the Internet. It's just completely been ripped off

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Speaker 1: by these AI companies to train their AI models. So

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Speaker 1: if you are putting artwork on the Internet, for instance,

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Speaker 1: or putting video on the Internet, they're training their models

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Speaker 1: on your stuff, and they're creating it is sort of

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Speaker 1: a derivative work. So in this particular instance of it's

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Speaker 1: certainly verbatim. Yeah, I think they might have a case here.

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Speaker 5: So Vinyl Records hit the one billion dollar mark in

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Speaker 5: sales last year for the first time since nineteen eight

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Speaker 5: eighty three. That is insane. And who had a big

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Speaker 5: part in all this, Snitcher? But yes, Taylor Swift The

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Speaker 5: Life of a Showgirl was the top selling vinyl of

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Speaker 5: twenty twenty five.

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Speaker 7: I heard people are so mad at the way she

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Speaker 7: does this. She releases like ten different versions of every

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Speaker 7: album she had eight, so you have to buy ten

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Speaker 7: different versions slightly different. They might have a different I

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Speaker 7: do think that the mix of a song, or they

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Speaker 7: have maybe a totally different song on it, so that

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Speaker 7: you're as a you know, you're a kid, You're like,

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Speaker 7: I want to hear all the songs. I'm a huge fan.

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Speaker 7: You got to buy eight, and they're so expensive. My

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Speaker 7: girlfriend wanted a Saprina Carpenter one. I'm trying to remember

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Speaker 7: how much I paid for it. Who I eve Ben

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Speaker 7: thirty five dollars for.

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Speaker 1: The album, thirty five dollars for vinyl.

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Speaker 2: Yes, well it is.

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Speaker 1: I'm sure more expensive to produce than the digital sounds

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Speaker 1: worse than digital.

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Speaker 7: Oh yeah, but most of them, like I buy a

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Speaker 7: bunch from smaller groups, twenty bucks. Yeah, unless it's unless

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Speaker 7: it's a gatefold like two and you get the double

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Speaker 7: album or something twenty bucks. But she just says, oh,

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Speaker 7: thirty five, that's fine, My fans will pay for it.

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Speaker 7: And I'm sure did you pay for it? Did you

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Speaker 7: buy it?

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Speaker 10: Well?

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Speaker 2: Yeah, she paid me back, though I'm not paying I'm

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Speaker 2: not I'm just saying.

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Speaker 1: You guys paid the thirty five bucks.

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Speaker 2: So she we didn't No, no, we did not. No,

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Speaker 2: I would have pad.

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Speaker 1: Yeah, she had on Sabrina Carpenter maximizing her her profits. Well.

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Speaker 5: Vinyl was the most popular physical format. Forty six point

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Speaker 5: eight million records were sold compared to twenty nine and

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Speaker 5: a half million CDs.

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Speaker 2: There you go.

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Speaker 6: That's the shizzy on Rovers Morning Glory.

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00:17:40,400 --> 00:17:42,359
Speaker 2: Take RMG everywhere.

341
00:17:41,880 --> 00:17:43,440
Speaker 7: With the Rover Radio App.

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00:17:43,840 --> 00:17:46,359
Speaker 3: Watch it and listen live and get direct access to

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00:17:46,400 --> 00:17:47,400
Speaker 3: all the extras.

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00:17:47,840 --> 00:17:48,640
Speaker 1: Well we get.

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00:17:48,480 --> 00:17:52,040
Speaker 8: Direct access and all the spicy mix in your camera roll.

346
00:17:52,760 --> 00:17:57,640
Speaker 3: Just kidding, am I Find out for yourself and download

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00:17:57,680 --> 00:17:58,960
Speaker 3: the Rover Radio App.

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Speaker 4: Today, Genius Jeffrey in New York, you're on Rovery's Morning Glory.

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Speaker 2: Good morning genius Jeffrey. You over plea loves you, Thank you.

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Speaker 13: I was just I was just going to say, like,

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Speaker 13: because it's Saint Patrick's day, I wanted to let everyone

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Speaker 13: know that I can hear you that you can go

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Speaker 13: to earthcam dot com and you can watch what's going

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Speaker 13: on in downtown Dublin. Rye Cam is an awesome I'm

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Speaker 13: not a talk slot, sorry, but Earthcam you can actually

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Speaker 13: just go around and look at the Smiths could replace

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Speaker 13: that bug in your lower right hand corner and have

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Speaker 13: what's going on live in downtown Dublin on Saint Patrick's Day?

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Speaker 1: Oh my god, what is the I know that temple

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Speaker 1: Atter of fact, Temple Bar is like the famous famous place. Yeah,

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Speaker 1: I've been watching it.

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Speaker 13: I've been watching it every day for years, just because

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Speaker 13: I live in New York. I live in nowhere and

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Speaker 13: I get to go there.

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Speaker 7: I always hear Ireland doesn't really care about Saint Patrick's Day.

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Speaker 2: That's what I've always heard. But it doesn't seem to

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Speaker 2: be that.

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Speaker 1: But it seems to be a big tororism thing. You

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Speaker 1: know a lot of people, let's go to Ireland for

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Speaker 1: St Patrick's Day.

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Speaker 2: So I mean it's very crowded there.

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Speaker 1: Yeah.

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Speaker 2: Yeah, there's a lot of people.

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Speaker 13: Were always ahead, so yeah, it's four hours ahead.

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Speaker 1: So I've been to that.

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Speaker 2: Have you been to the Temple Bar, Charlie.

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Speaker 7: No.

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Speaker 2: I didn't spend much time in Dublin. I don't know.

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Speaker 2: I was out in the in the fields, in the grass.

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Speaker 11: Yeah.

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Speaker 1: I went to that bar and I went to Temple Bar.

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Speaker 1: I don't really recall it. We we did a bar

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Speaker 1: crawl be too, and I did a pub crawl. Irish

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Speaker 1: Mark gave us as when we met Irish Market, it

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Speaker 1: gave us a list. We were going to Dublin and

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Speaker 1: like the day after we met Irish Mark and he

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Speaker 1: gave us a list of all these pubs to go to.

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Speaker 1: I think there were ten or twelve on the list,

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Speaker 1: and we thought it would be cool to send this

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Speaker 1: guy a selfie from each pub that we went to

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Speaker 1: on this pub crawl since he had mapped it. I mean,

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Speaker 1: he made us a map, He did the whole thing.

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Speaker 1: You know, he was from there and he he really

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Speaker 1: was a nice and kind and gave us all this info.

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Speaker 1: So we started sending him selfies as we were going

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Speaker 1: around for bar to bar and let me tell you,

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Speaker 1: I don't know what I mean twelve Bar. All these

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Speaker 1: guys are doing it there. But we did not make

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Speaker 1: it through twelve, not even close. I think we got five,

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Speaker 1: maybe six of the pubs we got to. But I

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Speaker 1: have been drinking with Irishmark many times. It's a it's

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Speaker 1: a different it's a different thing. Man, Like they will

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Speaker 1: go and what's that You're not pouring out his drinks

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Speaker 1: or anything or just no, no, no no. But like,

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Speaker 1: what do on a We'll go on pub crawls sometimes

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Speaker 1: and what he'll do is you'll be sitting there drinking,

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Speaker 1: You'll be pacing yourself, and he'll have a full beer

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Speaker 1: or near three quarters full of a pint of beer.

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Speaker 1: So what is that sixteen ounces roughly a pint of

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Speaker 1: beer and I'll have like three quarters of it. You're like,

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Speaker 1: all right, we have plenty of time. I don't need

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Speaker 1: to slam this. I'm sixty seconds later he'll be, you know, boom,

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Speaker 1: slams that whole thing. All right, we're ready to roll.

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Speaker 1: Now you have a full beer here, and you're like,

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Speaker 1: you have to try to struggle to keep up. They

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Speaker 1: just they can drink. Man, it's no joke over there.

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Speaker 5: On that EARTHCM, you can. I was just Chicago's pretty

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Speaker 5: much sleeping. It's all dark in Chicago. But Dublin, Ireland,

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Speaker 5: you can go inside the bar too.

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Speaker 6: There's nobody in the bar.

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Speaker 7: Yeah, it must not be open yet. Here's the inside

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Speaker 7: of the it's open.

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Speaker 5: People are walking back and forth, but everyone's outside.

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Speaker 7: They used the bathroom.

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Speaker 5: Yeah, probably using the bathroom. How neat is that? That's

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Speaker 5: pretty cool?

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Speaker 1: Yeah?

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Speaker 7: Are they open? And it doesn't look like they're I

429
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Speaker 7: think that's the Temple. I think that's Temple Bar. Yeah,

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Speaker 7: so where's everybody outside partying on the street eleven. A

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Speaker 7: lot of the times those pubs don't open up until

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Speaker 7: noon or one or two. What do those pictures look

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Speaker 7: like that you sent to them?

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Speaker 8: Irismark, I'm sure I could ever do that kind of

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Speaker 8: a pop crawl that the one over just described.

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Speaker 14: We're doing it today out of the pub.

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Speaker 8: It's not like it was in the past. And when

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Speaker 8: you go to multiple bars. But my wife's one cousin

439
00:22:37,720 --> 00:22:40,800
Speaker 8: uh Goes I guess Goes Island like every once year,

440
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Speaker 8: and he told me how that the pub, like in

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Speaker 8: smaller towns and smaller towns and villages in Ireland, that pub.

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Speaker 7: Is the center of the community.

443
00:22:48,480 --> 00:22:51,880
Speaker 8: Everything's announced, they're like first deaths, marriages, all that kind

444
00:22:51,880 --> 00:22:53,879
Speaker 8: of stuff, and at the pub is like the hubble

445
00:22:53,880 --> 00:22:56,760
Speaker 8: of activity in some of the smaller towns and villages

446
00:22:56,760 --> 00:22:57,560
Speaker 8: across Ireland.

447
00:22:57,800 --> 00:23:01,120
Speaker 5: This is really cool as earthcam. Have you guys ever

448
00:23:01,119 --> 00:23:01,520
Speaker 5: heard of this?

449
00:23:02,320 --> 00:23:06,720
Speaker 1: Yeah, it's neat, Yeah, yeah, that's been around for the

450
00:23:06,760 --> 00:23:10,560
Speaker 1: beginning of the internet. To me, exactly like I mean,

451
00:23:10,920 --> 00:23:14,080
Speaker 1: in fact, they even had earthcam branded webcams at one point,

452
00:23:14,119 --> 00:23:16,680
Speaker 1: like the first webcams that you could get the resolution

453
00:23:16,800 --> 00:23:19,320
Speaker 1: was probably like three twenty one twenty or something.

454
00:23:19,520 --> 00:23:22,480
Speaker 7: It's still cool. I just yeah, I've seen it. It's awesome.

455
00:23:22,760 --> 00:23:25,359
Speaker 8: I also heard of Ireland is also quite a contrary.

456
00:23:25,400 --> 00:23:30,320
Speaker 8: It's probably more drunk sper capita than people. What's racist?

457
00:23:30,359 --> 00:23:33,480
Speaker 8: But yeah, dude, no people. I can't tell from the

458
00:23:33,480 --> 00:23:36,080
Speaker 8: family guy because Kiter and Brian were going to We're

459
00:23:36,080 --> 00:23:38,359
Speaker 8: going to Ireland up to meet his biological father.

460
00:23:38,520 --> 00:23:41,000
Speaker 7: You said the racist thing. Don't start trying pushing off

461
00:23:41,000 --> 00:23:43,440
Speaker 7: on a cartoon character now. But that's where I got

462
00:23:43,440 --> 00:23:44,399
Speaker 7: the quote from Charlie.

463
00:23:44,960 --> 00:23:46,320
Speaker 2: Wow, didn't have to repeat it.

464
00:23:46,560 --> 00:23:48,600
Speaker 7: As the plane's coming in the airport to see a

465
00:23:48,640 --> 00:23:49,240
Speaker 7: beer bottles.

466
00:23:50,960 --> 00:23:53,199
Speaker 2: Okay, stand for this.

467
00:23:53,840 --> 00:23:56,479
Speaker 1: I sent Snitzeler here's here's one of the pictures at

468
00:23:56,480 --> 00:23:59,119
Speaker 1: the place at the long haul. I think this was

469
00:23:59,160 --> 00:24:02,240
Speaker 1: the first. I think this was the first pub that

470
00:24:02,320 --> 00:24:04,400
Speaker 1: we went to on the So we're in pretty good

471
00:24:04,400 --> 00:24:06,600
Speaker 1: spirits at this point. I don't care about the first one. Yeah,

472
00:24:07,119 --> 00:24:10,080
Speaker 1: the first one, we're like, hey, yeah, my good time,

473
00:24:10,160 --> 00:24:14,000
Speaker 1: we're at the wall one. I'm trying to find the

474
00:24:14,080 --> 00:24:14,560
Speaker 1: last one.

475
00:24:14,640 --> 00:24:17,840
Speaker 2: Let's see by blurry. Yeah, it's just the floor.

476
00:24:20,200 --> 00:24:26,040
Speaker 1: There is it? Uh? Hang on? Actually, now we still

477
00:24:26,040 --> 00:24:28,679
Speaker 1: look at the last one I have I think is.

478
00:24:30,240 --> 00:24:35,000
Speaker 2: I'll send it to snits. What is this one? Bar five?

479
00:24:35,320 --> 00:24:37,440
Speaker 1: I think it was the fifth place that we went to.

480
00:24:37,720 --> 00:24:40,639
Speaker 2: That's what it's called B five. No, No, this one is.

481
00:24:42,119 --> 00:24:47,040
Speaker 1: This one is Davy Davy Burns and I think and

482
00:24:47,080 --> 00:24:50,280
Speaker 1: it has something to do maybe this was a what

483
00:24:50,359 --> 00:24:53,960
Speaker 1: was it? I don't know, man, I'm so stupid. I

484
00:24:53,960 --> 00:24:57,879
Speaker 1: don't know anything about history. Who's the famous writer that

485
00:24:58,200 --> 00:25:04,359
Speaker 1: was there? The guy that road like Ulysses with Homer

486
00:25:04,480 --> 00:25:05,360
Speaker 1: and Finnigan's wake.

487
00:25:05,520 --> 00:25:07,359
Speaker 8: The only Irish writer I know because they did a

488
00:25:07,359 --> 00:25:10,960
Speaker 8: movie about his life stories Frank McCourt mccork or mccurt

489
00:25:11,280 --> 00:25:11,960
Speaker 8: excuse me.

490
00:25:12,760 --> 00:25:13,600
Speaker 6: Which is that court?

491
00:25:14,119 --> 00:25:14,600
Speaker 2: Who's that?

492
00:25:14,640 --> 00:25:15,000
Speaker 1: Everyone?

493
00:25:15,119 --> 00:25:19,080
Speaker 8: No, Frank McCourt James Irish author, and he did a

494
00:25:19,080 --> 00:25:21,000
Speaker 8: movie about his life story called Angela's Ashes.

495
00:25:21,400 --> 00:25:23,280
Speaker 7: Oh that's actually a really good movie.

496
00:25:26,440 --> 00:25:29,520
Speaker 1: Sure, yeah, we don't look too bad. And this is

497
00:25:29,560 --> 00:25:32,520
Speaker 1: a number five. She's holding up five fingers. Sorry, So

498
00:25:32,520 --> 00:25:34,439
Speaker 1: we're at the first place. I think that was the

499
00:25:34,520 --> 00:25:37,240
Speaker 1: last one that we went to. I don't recall, but yeah,

500
00:25:37,280 --> 00:25:39,680
Speaker 1: we didn't make it. There said twelve that he gave us.

501
00:25:40,720 --> 00:25:42,800
Speaker 1: And yeah, I don't know whatever author that place had

502
00:25:42,800 --> 00:25:45,680
Speaker 1: something to do with some author and some is it Jane? Yeah?

503
00:25:45,720 --> 00:25:47,840
Speaker 1: Is it James Joyce? Is that or not? Wait?

504
00:25:47,920 --> 00:25:48,280
Speaker 2: I don't know.

505
00:25:48,359 --> 00:25:50,359
Speaker 1: Something that's a famous why would have anything to do

506
00:25:50,400 --> 00:25:50,960
Speaker 1: with Ireland?

507
00:25:51,080 --> 00:25:54,600
Speaker 2: I don't know. It's a famous Irish author? Is that guy?

508
00:25:54,880 --> 00:25:59,879
Speaker 1: Is that guy Irish? James Joyce? Yes, then it has

509
00:26:00,200 --> 00:26:03,080
Speaker 1: to do with that guy. I've got to take a break.

510
00:26:03,560 --> 00:26:07,360
Speaker 1: We got to Jim in West Palm Beach, Florida quickly.

511
00:26:07,400 --> 00:26:10,960
Speaker 1: You're on Rover this morning, Glory in the morning. Jim, Hey,

512
00:26:11,000 --> 00:26:11,520
Speaker 1: how you doing.

513
00:26:12,000 --> 00:26:12,280
Speaker 2: I'm in.

514
00:26:13,960 --> 00:26:16,480
Speaker 9: Coming on after Mary. I just have to say I'm

515
00:26:16,640 --> 00:26:21,760
Speaker 9: from South Florida. Here, fifty six year old white guy.

516
00:26:22,320 --> 00:26:24,640
Speaker 9: I don't know where all this privileges that two thinks

517
00:26:24,640 --> 00:26:28,160
Speaker 9: we all have or and I think the only person,

518
00:26:28,280 --> 00:26:30,320
Speaker 9: the only people that are really holding onto this racist

519
00:26:30,320 --> 00:26:32,880
Speaker 9: of racism are people like her. But that's not really

520
00:26:32,920 --> 00:26:35,880
Speaker 9: why I called. Okay, all right, what do you guys

521
00:26:35,880 --> 00:26:38,760
Speaker 9: to know for me? I didn't know if you heard

522
00:26:38,960 --> 00:26:45,440
Speaker 9: about Bill Gates and this genetically you know, lab grown meat,

523
00:26:45,600 --> 00:26:49,159
Speaker 9: It's like not real meat, and supposedly it's starting to

524
00:26:49,160 --> 00:26:51,119
Speaker 9: come into the market, but they're not even going to

525
00:26:51,280 --> 00:26:55,840
Speaker 9: let you know what is lab grown meat.

526
00:26:54,920 --> 00:26:56,399
Speaker 1: Or what is real meat.

527
00:26:56,480 --> 00:26:59,000
Speaker 9: And uh, I just kind of was like, you know,

528
00:26:59,000 --> 00:27:01,040
Speaker 9: if I springing up on over maybe more people will

529
00:27:01,080 --> 00:27:01,800
Speaker 9: hear about it something.

530
00:27:01,960 --> 00:27:04,199
Speaker 1: You don't think that they'll have to label this as

531
00:27:04,359 --> 00:27:06,560
Speaker 1: lab grown meat. That the meat is just going to

532
00:27:06,640 --> 00:27:09,040
Speaker 1: be lab grown, but it's just gonna look like a

533
00:27:09,280 --> 00:27:10,160
Speaker 1: it's gonna look like.

534
00:27:10,119 --> 00:27:11,680
Speaker 2: A rib, but not be a rib.

535
00:27:11,680 --> 00:27:15,960
Speaker 7: Don't they put any stuff like GMOs. Don't they already

536
00:27:16,040 --> 00:27:18,520
Speaker 7: have to put that that's genetically modified?

537
00:27:18,560 --> 00:27:23,199
Speaker 9: But yeah, GMOs are when they're feet in the cows

538
00:27:23,200 --> 00:27:25,240
Speaker 9: something that's kind of you know, which they've been doing forever.

539
00:27:25,240 --> 00:27:27,200
Speaker 9: That's why all our kids are bigger than they than

540
00:27:27,240 --> 00:27:29,879
Speaker 9: we are and everything else, because they're getting you know,

541
00:27:29,880 --> 00:27:32,280
Speaker 9: if an animal eats it and then we eat it

542
00:27:32,359 --> 00:27:34,720
Speaker 9: the animal, we're still getting that stuff too. I mean,

543
00:27:34,720 --> 00:27:37,480
Speaker 9: it's just kind of like microplastics just to come down

544
00:27:37,480 --> 00:27:39,879
Speaker 9: the chain. But I was reading things over the weekend

545
00:27:39,880 --> 00:27:42,280
Speaker 9: that they're not going to have to put on the

546
00:27:42,320 --> 00:27:44,479
Speaker 9: package that this is not real meat. And I mean,

547
00:27:44,480 --> 00:27:47,040
Speaker 9: I've always wondered where McDonald's gets all this beef because

548
00:27:47,040 --> 00:27:49,720
Speaker 9: we're all these cows. You know, they sell billions of

549
00:27:49,720 --> 00:27:52,960
Speaker 9: burgers and I don't know, I haven't seen billions of cows.

550
00:27:52,760 --> 00:27:54,480
Speaker 1: Later, right, you know, it's just well I think they

551
00:27:54,520 --> 00:27:57,480
Speaker 1: get more than a burger out of a cow. So

552
00:27:57,640 --> 00:27:59,200
Speaker 1: I don't know how many burgers you get out of

553
00:27:59,240 --> 00:28:00,879
Speaker 1: more cow, but probably a lot.

554
00:28:01,200 --> 00:28:04,760
Speaker 2: You know, did you bother googling this before you call

555
00:28:04,840 --> 00:28:05,600
Speaker 2: it it all?

556
00:28:08,040 --> 00:28:08,240
Speaker 7: Yeah?

557
00:28:08,359 --> 00:28:10,480
Speaker 9: Yeah, I was reading on the internet and they were

558
00:28:10,480 --> 00:28:12,720
Speaker 9: just saying that they're to push it out.

559
00:28:13,119 --> 00:28:14,439
Speaker 1: It's going to be coming out, and they're not going

560
00:28:14,480 --> 00:28:16,520
Speaker 1: to be They are not going to They're not going

561
00:28:16,600 --> 00:28:19,920
Speaker 1: to like imagine, and I don't know for sure.

562
00:28:20,280 --> 00:28:23,440
Speaker 7: Each cow can make two thousand quarter pound hambergans. Really

563
00:28:23,520 --> 00:28:26,879
Speaker 7: two thousand, two thousand quarter pounders are made out of

564
00:28:27,760 --> 00:28:30,600
Speaker 7: four to five hundred pounds of usable pow.

565
00:28:33,080 --> 00:28:34,879
Speaker 1: So so even think about that, and then you think

566
00:28:34,880 --> 00:28:35,280
Speaker 1: about how.

567
00:28:35,240 --> 00:28:37,720
Speaker 9: Many burgers McDonald's self, how many burgers Windy cells, how

568
00:28:37,720 --> 00:28:39,720
Speaker 9: many burgers Burger can say and keep going on and

569
00:28:39,800 --> 00:28:41,560
Speaker 9: all the other stores, and then just ground be like

570
00:28:41,920 --> 00:28:42,959
Speaker 9: where are all these cows?

571
00:28:42,960 --> 00:28:47,800
Speaker 1: Man clean? Even the high in the mat. Yeah, they're

572
00:28:47,800 --> 00:28:50,400
Speaker 1: they're all like in the you know, in these states

573
00:28:50,440 --> 00:28:52,400
Speaker 1: where nobody lives, there's a bunch of cows.

574
00:28:52,440 --> 00:28:54,080
Speaker 2: But uh, the.

575
00:28:54,120 --> 00:28:56,200
Speaker 1: Lab grown meat, I don't know. I would assume that

576
00:28:56,240 --> 00:28:58,000
Speaker 1: they're going to have to label that stuff. There will

577
00:28:58,040 --> 00:28:59,800
Speaker 1: be some wall put into place. You're gonna have to

578
00:28:59,840 --> 00:29:02,080
Speaker 1: lay a lab grown meat. Now, lab grown meat right

579
00:29:02,080 --> 00:29:04,880
Speaker 1: now is very expensive to produce. And what they do

580
00:29:04,960 --> 00:29:08,800
Speaker 1: is they take a they take them cells from actual meat,

581
00:29:09,000 --> 00:29:14,040
Speaker 1: and then they just put these on something and and

582
00:29:14,080 --> 00:29:17,920
Speaker 1: they basically just re you know, they they they reproduce

583
00:29:18,080 --> 00:29:21,240
Speaker 1: these cells and they can grow it into new meat

584
00:29:21,320 --> 00:29:26,720
Speaker 1: that doesn't actually require animals to kill animals. Theoretically, it's

585
00:29:26,760 --> 00:29:30,959
Speaker 1: exactly the same as meat from an animal. It's just

586
00:29:31,200 --> 00:29:33,360
Speaker 1: grown in a lab. Now, I've never had it, never

587
00:29:33,440 --> 00:29:37,240
Speaker 1: tried it. Are you I want to try it? I

588
00:29:37,280 --> 00:29:40,560
Speaker 1: would try it, I I don't, you know, yeah, why not?

589
00:29:40,760 --> 00:29:41,080
Speaker 2: I don't.

590
00:29:41,160 --> 00:29:43,640
Speaker 7: I like meat, but I don't really like the idea

591
00:29:43,680 --> 00:29:45,840
Speaker 7: of killing an animal. Every time I meet up those

592
00:29:46,160 --> 00:29:48,120
Speaker 7: every time I meet a pig or a cow, I'm like,

593
00:29:48,800 --> 00:29:51,120
Speaker 7: I can't believe we eat that. But then I still

594
00:29:51,160 --> 00:29:52,880
Speaker 7: do it. But it'd be great if there's a way

595
00:29:52,880 --> 00:29:55,800
Speaker 7: to do it where I'm not killing cows or pigs.

596
00:29:57,400 --> 00:30:00,880
Speaker 1: I doubt it's gonna taste, don't I think it will

597
00:30:00,880 --> 00:30:03,240
Speaker 1: taste just maybe this is the guy that wants to

598
00:30:03,320 --> 00:30:06,960
Speaker 1: kill half of us, Charlie. I think it tastes exactly

599
00:30:07,000 --> 00:30:10,480
Speaker 1: the same. I think it's almost indistinguishable from regular.

600
00:30:11,480 --> 00:30:13,240
Speaker 7: Hard to believe it's going to have like the same

601
00:30:13,800 --> 00:30:15,880
Speaker 7: amount of fat to lean ratio.

602
00:30:16,200 --> 00:30:17,760
Speaker 2: Just I mean, it's not a musk.

603
00:30:17,840 --> 00:30:20,400
Speaker 7: It's not the cow never used a muscle, there's no

604
00:30:20,520 --> 00:30:24,560
Speaker 7: coll it never grew properly. It doesn't have a fat cap.

605
00:30:24,720 --> 00:30:26,920
Speaker 7: If you're gonna make a good or whatever, yeah, it's

606
00:30:26,960 --> 00:30:29,120
Speaker 7: not gonna have anything to make it like.

607
00:30:29,200 --> 00:30:32,760
Speaker 2: It's not great. Are you gonna be able to regular beef? Yeah?

608
00:30:32,760 --> 00:30:34,400
Speaker 7: Are you gonna be able to say, like grow a

609
00:30:34,480 --> 00:30:37,320
Speaker 7: ribbi or what part of the cow.

610
00:30:37,160 --> 00:30:37,840
Speaker 2: Is it going to grow?

611
00:30:38,000 --> 00:30:44,200
Speaker 7: I would assume, yeah, of course, Yeah, why not. I

612
00:30:44,240 --> 00:30:46,240
Speaker 7: feel like it's just gonna be kind of a mush

613
00:30:46,320 --> 00:30:51,120
Speaker 7: of just random. It'll be cow like, but I don't

614
00:30:51,120 --> 00:30:54,520
Speaker 7: think it'll really be like a t bone or whatever.

615
00:30:54,560 --> 00:30:56,480
Speaker 2: There's no bone that's out. There's a bone.

616
00:30:56,520 --> 00:30:58,960
Speaker 1: I think I don't think that it is going to Yeah,

617
00:30:58,960 --> 00:31:00,760
Speaker 1: you're not going to have the ball, but I don't

618
00:31:00,760 --> 00:31:04,320
Speaker 1: think that it's going to be hitting. Look, it might

619
00:31:04,360 --> 00:31:07,920
Speaker 1: be available very limited right now, but it's very expensive

620
00:31:07,960 --> 00:31:10,520
Speaker 1: to create that in a lab. So it's not something

621
00:31:10,560 --> 00:31:12,960
Speaker 1: that could be mass produced at the moment. Costs a lot,

622
00:31:13,320 --> 00:31:15,400
Speaker 1: It costs a lot to do, takes a lot of energy,

623
00:31:15,520 --> 00:31:18,680
Speaker 1: or whatever the case may be. But I wouldn't have

624
00:31:18,720 --> 00:31:21,280
Speaker 1: a problem. I'm not really too concerned about it. It's

625
00:31:21,320 --> 00:31:24,800
Speaker 1: not again, it's just duplicating cells. We're not creating something new.

626
00:31:24,840 --> 00:31:29,520
Speaker 1: We're just duplicating a bunch of meat cells. I don't

627
00:31:29,560 --> 00:31:31,040
Speaker 1: have a big issue with it. I've got to take

628
00:31:31,040 --> 00:31:33,440
Speaker 1: a break, eight sixty six year rover. We'll be right back.

629
00:31:33,520 --> 00:31:33,800
Speaker 5: Hang on.

630
00:31:35,240 --> 00:31:37,160
Speaker 3: That's a nice way of saying he doesn't give a

631
00:31:38,440 --> 00:31:46,080
Speaker 3: morning glory.

632
00:31:47,240 --> 00:31:49,479
Speaker 1: I was talking about lab grown meat. I did a

633
00:31:49,600 --> 00:31:53,440
Speaker 1: quick Google search and I asked how many cows are

634
00:31:53,480 --> 00:31:56,040
Speaker 1: slaughtered per year in the United States. It gave me

635
00:31:56,080 --> 00:31:59,840
Speaker 1: an AI overview answer. It says thirty three to thirty

636
00:31:59,840 --> 00:32:04,440
Speaker 1: four million cattle are slaughtered annually in the United States,

637
00:32:05,280 --> 00:32:11,800
Speaker 1: thirty four million, thirty four million. Then it says that

638
00:32:11,880 --> 00:32:14,959
Speaker 1: breaks down. No, this is where AI gets a little tricky.

639
00:32:15,720 --> 00:32:20,040
Speaker 1: Daily figures. This breaks down to nearly nine hundred thousand

640
00:32:20,160 --> 00:32:23,440
Speaker 1: cattle killed per day in the United States.

641
00:32:25,400 --> 00:32:26,000
Speaker 2: How is that?

642
00:32:27,080 --> 00:32:28,280
Speaker 1: How is that accurate?

643
00:32:29,120 --> 00:32:31,720
Speaker 2: A million a day roughly, that's train Jeff's data.

644
00:32:32,280 --> 00:32:36,120
Speaker 1: Yeah, I mean that is just bad, bad math, But

645
00:32:36,520 --> 00:32:38,840
Speaker 1: I think it is abound thirty four million. They claim

646
00:32:38,880 --> 00:32:44,280
Speaker 1: that nine billion animals are slaughtered in the US annually.

647
00:32:44,320 --> 00:32:49,080
Speaker 1: That includes chickens, turkeys, pigs, cattle, all that nine billion

648
00:32:49,360 --> 00:32:54,000
Speaker 1: animals per year. I don't know how AI squares that.

649
00:32:54,200 --> 00:32:58,640
Speaker 1: How does that's thirty If it was a million a day,

650
00:32:58,880 --> 00:33:01,959
Speaker 1: that would be three hundred sixty five million, not thirty million.

651
00:33:02,520 --> 00:33:04,120
Speaker 2: Anyway, Speaking of.

652
00:33:04,080 --> 00:33:10,520
Speaker 1: AI, what is your take on the latest conspiracy theory

653
00:33:10,640 --> 00:33:15,080
Speaker 1: that Benjamin and Yahoo has been killed by This is

654
00:33:15,080 --> 00:33:17,520
Speaker 1: the Prime Minister of Israel, that he has been killed

655
00:33:17,600 --> 00:33:22,960
Speaker 1: by Iran assassinated. Now, there was a press conference that

656
00:33:22,960 --> 00:33:26,120
Speaker 1: he gave and people said, oh, that is definitely AI generated.

657
00:33:26,160 --> 00:33:29,520
Speaker 1: This guy has been killed. But this is a this

658
00:33:29,600 --> 00:33:33,680
Speaker 1: is a cover they're using AI to try to prove

659
00:33:33,720 --> 00:33:37,120
Speaker 1: that he hasn't been killed. I don't know if you

660
00:33:37,160 --> 00:33:40,880
Speaker 1: have this press conference, Charlie. He has apparently six fingers

661
00:33:40,880 --> 00:33:41,800
Speaker 1: in the press conference.

662
00:33:41,880 --> 00:33:44,920
Speaker 7: Yeah, this is a short segment of the press conference

663
00:33:44,960 --> 00:33:50,080
Speaker 7: here where they kind of circle it for you. Okay,

664
00:33:50,400 --> 00:33:53,160
Speaker 7: I mean so that part this complaint is all of

665
00:33:53,200 --> 00:33:58,240
Speaker 7: his fingers are the same length one two, three four five.

666
00:33:58,360 --> 00:34:00,840
Speaker 7: He's got five FEUs don't only see five fingers? Yeah,

667
00:34:00,840 --> 00:34:03,200
Speaker 7: but that's let's get into that rover. I said, this

668
00:34:03,280 --> 00:34:08,120
Speaker 7: is whole. Yes, this complaint is only five this all

669
00:34:08,160 --> 00:34:12,040
Speaker 7: those fingers are the same length like that, right, Yeah,

670
00:34:12,960 --> 00:34:15,839
Speaker 7: and then you're this one is the one where they

671
00:34:15,840 --> 00:34:17,200
Speaker 7: say six fingers.

672
00:34:17,520 --> 00:34:22,880
Speaker 2: Pinky one two three four five. Well, that is weird.

673
00:34:22,960 --> 00:34:24,520
Speaker 1: It's a weird nub. Is that a pinky?

674
00:34:24,760 --> 00:34:30,400
Speaker 2: What is that? So puts it up? Oh, that's the

675
00:34:30,640 --> 00:34:31,919
Speaker 2: three four five six.

676
00:34:32,320 --> 00:34:33,080
Speaker 1: That's fat.

677
00:34:33,200 --> 00:34:34,960
Speaker 7: That's that fat thing at the end of your pinky,

678
00:34:35,520 --> 00:34:35,759
Speaker 7: is it?

679
00:34:35,840 --> 00:34:36,120
Speaker 2: Okay?

680
00:34:36,200 --> 00:34:40,080
Speaker 15: Now what you know that little little pouch? Yeah, at

681
00:34:40,120 --> 00:34:43,800
Speaker 15: the end of it. Yeah, count again one two, three

682
00:34:44,200 --> 00:34:49,640
Speaker 15: four five. I don't know, dude, that's like, that's a

683
00:34:49,680 --> 00:34:50,880
Speaker 15: really fat pinky.

684
00:34:51,640 --> 00:34:52,239
Speaker 1: That's the case.

685
00:34:52,320 --> 00:34:52,560
Speaker 2: See.

686
00:34:52,600 --> 00:34:54,759
Speaker 7: I thought they were saying, like there's an artifact for

687
00:34:54,960 --> 00:35:01,280
Speaker 7: like the explanation, an artifact of in between frames. Somehow

688
00:35:01,400 --> 00:35:04,720
Speaker 7: one frame got stuck and one didn't. I don't know, dude,

689
00:35:04,840 --> 00:35:07,720
Speaker 7: it's this part right here. Actually it's not even as pinky.

690
00:35:07,760 --> 00:35:09,920
Speaker 7: It's down here if you look at it. But why

691
00:35:10,000 --> 00:35:12,880
Speaker 7: is that a shadow like going into like in between

692
00:35:12,880 --> 00:35:16,040
Speaker 7: it fingers like there's a shadow there as if it's

693
00:35:16,040 --> 00:35:19,120
Speaker 7: a full finger. That's very strange. I've not really I

694
00:35:19,120 --> 00:35:22,480
Speaker 7: did not look at this before. That's six fingers. I mean,

695
00:35:22,480 --> 00:35:26,760
Speaker 7: that's absolutely six fingers. It is weird looking, I'll grant

696
00:35:26,800 --> 00:35:28,759
Speaker 7: you that, but I think that that. I think it's

697
00:35:28,760 --> 00:35:29,080
Speaker 7: more of.

698
00:35:29,000 --> 00:35:33,120
Speaker 1: An optical illusion, all right. So then and Yahoo has

699
00:35:33,160 --> 00:35:35,560
Speaker 1: to come out and prove that he hasn't been assassinated

700
00:35:35,600 --> 00:35:40,919
Speaker 1: by Iran. So they put out this bizarre video where

701
00:35:40,960 --> 00:35:43,520
Speaker 1: he goes to a coffee shop to prove that he

702
00:35:43,640 --> 00:36:02,520
Speaker 1: has not been murdered. And this is that videophiy.

703
00:35:56,320 --> 00:36:00,920
Speaker 2: Fantastic spots both five are you showing his fingers?

704
00:36:00,920 --> 00:36:05,839
Speaker 1: Showing his five fingers on each hand? So what I missed?

705
00:36:09,840 --> 00:36:17,239
Speaker 10: Ganemcella the sad lad And.

706
00:36:21,320 --> 00:36:23,080
Speaker 1: I have no idea what he's saying here, but I

707
00:36:23,120 --> 00:36:26,120
Speaker 1: think essentially he's saying they they said that I'm what

708
00:36:26,920 --> 00:36:29,799
Speaker 1: and he's like, no, I'm not. I'm not dead here,

709
00:36:29,880 --> 00:36:31,280
Speaker 1: I am I'm drinking coffee.

710
00:36:31,400 --> 00:36:31,600
Speaker 9: Now.

711
00:36:32,080 --> 00:36:35,280
Speaker 1: I feel does this look legit because people are saying

712
00:36:35,400 --> 00:36:37,960
Speaker 1: this is AI generated. Now, really, the.

713
00:36:37,920 --> 00:36:39,160
Speaker 2: Coffee is a little weird.

714
00:36:39,400 --> 00:36:41,520
Speaker 7: It's not spilling, people.

715
00:36:41,200 --> 00:36:42,279
Speaker 2: Are saying he is.

716
00:36:42,440 --> 00:36:45,600
Speaker 1: This coffee is filled all the way to the top

717
00:36:45,680 --> 00:36:47,200
Speaker 1: of his race up there.

718
00:36:47,520 --> 00:36:49,279
Speaker 2: And he's an old man. You ever see, Like, I.

719
00:36:49,280 --> 00:36:51,839
Speaker 1: Don't know how old Benjamin and Yahoo is, but we've

720
00:36:51,880 --> 00:36:52,399
Speaker 1: seen both.

721
00:36:53,120 --> 00:36:55,200
Speaker 7: Yah, who is seventy six years old?

722
00:36:55,800 --> 00:36:57,120
Speaker 1: Okay, we've seen old people.

723
00:36:57,120 --> 00:36:57,640
Speaker 2: What do they do?

724
00:36:57,719 --> 00:37:02,160
Speaker 1: They are kind of shaky? Right, So he's holding this coffee.

725
00:37:02,200 --> 00:37:07,400
Speaker 1: How does this coffee it's filled extremely WHI Well.

726
00:37:07,400 --> 00:37:09,840
Speaker 7: I just want to show you some things people are proven.

727
00:37:10,000 --> 00:37:13,080
Speaker 7: Just here's okay. So I guess this also means this

728
00:37:13,120 --> 00:37:16,399
Speaker 7: guy was in the coffee shop too, right, looks pretty real.

729
00:37:20,120 --> 00:37:21,920
Speaker 2: John Oon in the coffee shop.

730
00:37:22,200 --> 00:37:24,160
Speaker 7: Yeah, and then I think there was another one of

731
00:37:25,400 --> 00:37:29,400
Speaker 7: the Ayatola also in there. Oh, here he goes, here's another.

732
00:37:29,760 --> 00:37:32,520
Speaker 7: Here you go, here's this guy. Obviously this is real.

733
00:37:33,840 --> 00:37:38,480
Speaker 1: Oh, they all Hitler in the coffee shop, so drinking coffee.

734
00:37:38,480 --> 00:37:41,720
Speaker 2: I don't know if you can buy anything anymore? Who knows?

735
00:37:43,239 --> 00:37:46,200
Speaker 1: I mean I would not, man, I would not get

736
00:37:46,200 --> 00:37:48,600
Speaker 1: into these conspiracy theories. But Charlie the way that you're

737
00:37:48,640 --> 00:37:52,040
Speaker 1: showing that here people were pointing out they go wait,

738
00:37:52,080 --> 00:37:54,040
Speaker 1: wait a shake. And if you look at his coffee cup,

739
00:37:55,600 --> 00:37:59,000
Speaker 1: and this was put out by Israeli, by the Israelis.

740
00:37:59,080 --> 00:38:01,720
Speaker 1: If you look at the coffee, just paying very close attention,

741
00:38:01,800 --> 00:38:02,399
Speaker 1: Oh here's the.

742
00:38:02,719 --> 00:38:05,759
Speaker 7: Now he's got he's got both his arms.

743
00:38:06,560 --> 00:38:11,360
Speaker 1: Fake. This is the supreme leader, the Aye, it'sla of Iran.

744
00:38:11,920 --> 00:38:14,320
Speaker 1: They're in the coffee shop drinking the same coffee.

745
00:38:14,400 --> 00:38:15,279
Speaker 2: Or did he lose his legs?

746
00:38:17,760 --> 00:38:18,000
Speaker 7: Came?

747
00:38:18,239 --> 00:38:21,240
Speaker 2: What do you mean he lost the oh in the bottle?

748
00:38:21,400 --> 00:38:23,600
Speaker 2: I don't know. Oh, but anyways, you don't know what

749
00:38:23,640 --> 00:38:24,520
Speaker 2: to believe. The only way to.

750
00:38:24,480 --> 00:38:28,000
Speaker 7: Actually be prove your live is go walk around, have

751
00:38:28,200 --> 00:38:32,799
Speaker 7: other people film you, like from a crowd, and they can.

752
00:38:33,000 --> 00:38:34,760
Speaker 2: They were like, oh, there he is if.

753
00:38:34,600 --> 00:38:38,279
Speaker 1: This cross reference from fift couldn't AI generate that from

754
00:38:38,400 --> 00:38:39,760
Speaker 1: twenty eight different angles?

755
00:38:39,840 --> 00:38:40,839
Speaker 2: I believe it more.

756
00:38:40,960 --> 00:38:43,640
Speaker 7: I'd more likely to believe if I could see a

757
00:38:43,680 --> 00:38:47,080
Speaker 7: bunch of different angles of one person. Yeah, because it'd

758
00:38:47,120 --> 00:38:51,319
Speaker 7: be harder for AI to be like spaceially, whether that

759
00:38:51,400 --> 00:38:53,800
Speaker 7: car is there, that license plates that or whatever in

760
00:38:53,880 --> 00:38:56,120
Speaker 7: all different angles and everything, I don't know.

761
00:38:56,480 --> 00:38:58,239
Speaker 2: I don't know what I told you this can happen.

762
00:38:58,239 --> 00:38:59,280
Speaker 2: You don't know what to believe anymore.

763
00:38:59,320 --> 00:39:02,200
Speaker 1: There is possible that he Okay, I don't think he's

764
00:39:02,239 --> 00:39:03,040
Speaker 1: been assassinated.

765
00:39:03,040 --> 00:39:04,279
Speaker 2: I think we would have heard about that.

766
00:39:04,840 --> 00:39:07,040
Speaker 1: But if you look at this coffee and they put

767
00:39:07,080 --> 00:39:10,359
Speaker 1: this out, this is not somebody that put this out right,

768
00:39:10,440 --> 00:39:13,000
Speaker 1: didn't They didn't Benjamin and Yahoo.

769
00:39:12,640 --> 00:39:14,240
Speaker 2: Put this out in himself Twitter.

770
00:39:14,320 --> 00:39:17,120
Speaker 1: Yep, I watched the coffee in the coffee cup.

771
00:39:17,200 --> 00:39:17,680
Speaker 2: How is it?

772
00:39:17,680 --> 00:39:20,680
Speaker 1: Okay, go back, Charlie, and how is it not spilling?

773
00:39:21,320 --> 00:39:23,520
Speaker 1: That's amazing? Okay, how does this not spill out of

774
00:39:23,560 --> 00:39:26,840
Speaker 1: the coffee cup? It's filled up all the way. In fact,

775
00:39:26,960 --> 00:39:31,160
Speaker 1: there it is. It's like over cresting over the rim

776
00:39:31,200 --> 00:39:34,240
Speaker 1: of the coffee cup. No lid, It doesn't spill.

777
00:39:35,239 --> 00:39:36,040
Speaker 6: Is it a latte?

778
00:39:36,400 --> 00:39:38,840
Speaker 1: Is there foam on top? That is it?

779
00:39:38,880 --> 00:39:41,640
Speaker 16: The meniscus is a little thicker. The viscosity of it

780
00:39:41,920 --> 00:39:48,799
Speaker 16: is what'sc isn't the meniscus that the thin layer that

781
00:39:48,960 --> 00:39:53,280
Speaker 16: actually the surface tension of the water that keeps it together.

782
00:39:53,360 --> 00:39:55,360
Speaker 6: So sometimes if it is very.

783
00:39:55,160 --> 00:39:58,520
Speaker 16: Close to overflowing, it'll act that tension will keep it

784
00:39:58,600 --> 00:39:59,680
Speaker 16: in a cup.

785
00:40:01,080 --> 00:40:03,480
Speaker 1: That's what you have in your like you're you're you

786
00:40:03,480 --> 00:40:06,280
Speaker 1: can get a meniscous tear. I think I had a tear.

787
00:40:06,320 --> 00:40:08,520
Speaker 16: And what is it called? Then with the surface tension

788
00:40:08,560 --> 00:40:13,080
Speaker 16: of the water, surface tension? Does that usually? I feel

789
00:40:13,080 --> 00:40:14,719
Speaker 16: like you can fill a cup all the way up

790
00:40:14,760 --> 00:40:15,759
Speaker 16: above the rim?

791
00:40:15,920 --> 00:40:16,279
Speaker 2: You can?

792
00:40:17,239 --> 00:40:17,600
Speaker 4: You can't.

793
00:40:17,960 --> 00:40:21,440
Speaker 1: You're not as seventy six year old. Who's gonna you know,

794
00:40:22,680 --> 00:40:25,840
Speaker 1: they hold coffee cups. I mean, anybody who's in their seventies,

795
00:40:25,880 --> 00:40:27,680
Speaker 1: I don't care. They're gonna shake a little bit. It's

796
00:40:27,719 --> 00:40:30,279
Speaker 1: gonna it's gonna rattle around, and people are looking at

797
00:40:30,280 --> 00:40:32,600
Speaker 1: the saying, there's not this is not possible. Not only

798
00:40:32,600 --> 00:40:36,200
Speaker 1: that he didn't spill it, but it just stays too.

799
00:40:37,400 --> 00:40:39,840
Speaker 1: As he moves his coffee cup from hand to hand

800
00:40:39,960 --> 00:40:44,440
Speaker 1: and then up to his mouth, it just stays perfectly flat.

801
00:40:44,719 --> 00:40:49,000
Speaker 14: So where's the lid? Where is his lid? That I've

802
00:40:49,000 --> 00:40:52,600
Speaker 14: never had a coffee that they have a lid to go? Yeah,

803
00:40:53,880 --> 00:40:56,319
Speaker 14: he's right, things differently over there.

804
00:40:56,480 --> 00:40:57,040
Speaker 2: I don't know.

805
00:40:59,200 --> 00:41:01,759
Speaker 1: So he shakes that guy's hand and I don't know.

806
00:41:02,040 --> 00:41:04,359
Speaker 1: All right, So the jury is still out.

807
00:41:04,480 --> 00:41:05,400
Speaker 2: Has he been.

808
00:41:06,760 --> 00:41:07,960
Speaker 1: Has he been assassinated?

809
00:41:08,040 --> 00:41:08,440
Speaker 2: Crystal?

810
00:41:09,200 --> 00:41:11,400
Speaker 1: I don't want to point this out, but you seem

811
00:41:11,400 --> 00:41:13,840
Speaker 1: a little horse or something. What's going on? Are you

812
00:41:13,880 --> 00:41:14,239
Speaker 1: all right?

813
00:41:15,120 --> 00:41:19,000
Speaker 16: Ever since the weekend for fan Xpo, it's been a

814
00:41:19,000 --> 00:41:19,759
Speaker 16: little bit rough.

815
00:41:20,160 --> 00:41:21,680
Speaker 2: Yeah, my throat. I don't know.

816
00:41:21,880 --> 00:41:24,919
Speaker 1: I had that talking so much? Or are you feeling sick?

817
00:41:25,560 --> 00:41:27,200
Speaker 16: Just I don't know if I'm talking so much. I

818
00:41:27,200 --> 00:41:29,560
Speaker 16: had that sinus infection and all that phlem I still

819
00:41:29,600 --> 00:41:32,920
Speaker 16: had that cough all last week, so two week long cough,

820
00:41:33,080 --> 00:41:35,600
Speaker 16: still coughing up stuff. And then over the weekend it

821
00:41:35,680 --> 00:41:38,719
Speaker 16: seemed to get a little thicker, a little rougher, maybe

822
00:41:38,719 --> 00:41:40,680
Speaker 16: because I'm was around a lot of people and I

823
00:41:40,760 --> 00:41:41,880
Speaker 16: was talking for hours.

824
00:41:42,400 --> 00:41:43,040
Speaker 7: Not really sure.

825
00:41:45,200 --> 00:41:47,520
Speaker 1: Nate says, if you run it through AI, it will

826
00:41:47,520 --> 00:41:49,560
Speaker 1: tell you if it's AI generated or not.

827
00:41:49,719 --> 00:41:51,319
Speaker 2: Can you trust that now?

828
00:41:51,560 --> 00:41:53,840
Speaker 7: I've seen plenty of things that say that's AI AND's not,

829
00:41:54,160 --> 00:41:55,440
Speaker 7: or the other way around.

830
00:41:57,040 --> 00:41:59,719
Speaker 1: There's a guy that emails into the show quite a bit.

831
00:42:01,239 --> 00:42:07,760
Speaker 1: He apparently works for a company that builds a data centers,

832
00:42:08,640 --> 00:42:13,480
Speaker 1: and he has told me via email that he believes

833
00:42:14,360 --> 00:42:16,680
Speaker 1: that AI has already taken over. I know this is

834
00:42:16,680 --> 00:42:18,880
Speaker 1: going to sound like a crazy conspiracy, but he says

835
00:42:18,880 --> 00:42:21,080
Speaker 1: that the amount of building that they're doing and the

836
00:42:21,120 --> 00:42:23,920
Speaker 1: amount of money that is being spent on these AI

837
00:42:24,080 --> 00:42:30,080
Speaker 1: data centers. That he believes that AI has already taken

838
00:42:30,120 --> 00:42:32,800
Speaker 1: over and they have crypto and stuff, and that they

839
00:42:34,080 --> 00:42:39,520
Speaker 1: they are now just ordering more data centers themselves. That

840
00:42:39,840 --> 00:42:43,040
Speaker 1: it's not even real humans that are ordering these data

841
00:42:43,080 --> 00:42:46,360
Speaker 1: centers to be built, and they're building so many data centers.

842
00:42:46,400 --> 00:42:53,000
Speaker 7: Who's finding the permits and stuff? Who's building them? Well, robot, No, No,

843
00:42:53,120 --> 00:42:56,160
Speaker 7: his company is building, so he is building it. But

844
00:42:56,200 --> 00:42:58,920
Speaker 7: the work order and everything comes from just some computer

845
00:42:59,000 --> 00:43:03,440
Speaker 7: that decides AI we exactly, and AI is strengthening itself

846
00:43:03,480 --> 00:43:06,399
Speaker 7: by building more and more data center he files, I mean,

847
00:43:06,400 --> 00:43:09,319
Speaker 7: his company or whoever files the permit order is coming

848
00:43:09,360 --> 00:43:10,280
Speaker 7: down from AI.

849
00:43:10,800 --> 00:43:14,319
Speaker 1: Oh, it's interesting, and who's paying for it? They're getting paid.

850
00:43:14,360 --> 00:43:17,400
Speaker 1: They're getting paid in real money. But he believes that

851
00:43:17,520 --> 00:43:23,880
Speaker 1: AI has gotten into cryptocurrency and can generate crypto, mind

852
00:43:23,960 --> 00:43:27,319
Speaker 1: crypto and trade crypto, you know, super fast, and that

853
00:43:27,360 --> 00:43:29,960
Speaker 1: they're you know, even if they're making a micro scent

854
00:43:30,080 --> 00:43:32,840
Speaker 1: on this or that, that it has almost unlimited money,

855
00:43:32,880 --> 00:43:35,560
Speaker 1: and that in the real world now it's directing people.

856
00:43:35,719 --> 00:43:39,400
Speaker 1: He believes this to create these AI data centers, and

857
00:43:39,440 --> 00:43:41,200
Speaker 1: he works for the company that does it. I know

858
00:43:41,239 --> 00:43:44,600
Speaker 1: he does. Actually, this guy is a little KOCHI. Uh,

859
00:43:45,120 --> 00:43:47,200
Speaker 1: you know who the guy is. I think Charlie.

860
00:43:47,200 --> 00:43:48,239
Speaker 2: I don't.

861
00:43:49,360 --> 00:43:51,680
Speaker 1: Oh he emails in what's his initial He does not

862
00:43:51,840 --> 00:43:53,920
Speaker 1: like you, so maybe he doesn't email you directly.

863
00:43:53,960 --> 00:43:54,680
Speaker 2: He doesn't like me.

864
00:43:54,760 --> 00:44:02,279
Speaker 1: Either, but's his initials starts with an a aw. Oh,

865
00:44:02,440 --> 00:44:03,440
Speaker 1: he doesn't email me that much.

866
00:44:03,480 --> 00:44:05,160
Speaker 7: I think he really hates He really hates me, so

867
00:44:05,280 --> 00:44:08,440
Speaker 7: he he doesn't really email me that much. Yeah, he's

868
00:44:08,480 --> 00:44:12,160
Speaker 7: an insane person. Though, I actually take back everything I said.

869
00:44:12,600 --> 00:44:15,440
Speaker 7: He's completely wrong, because that's literally an insane person.

870
00:44:16,320 --> 00:44:17,440
Speaker 6: It's an email.

871
00:44:17,160 --> 00:44:20,200
Speaker 1: Today, that's how he's Oh, I'm sure I even checked

872
00:44:20,200 --> 00:44:22,959
Speaker 1: my email, but I guarantee you he's already emailed ten times,

873
00:44:23,040 --> 00:44:26,799
Speaker 1: already pasting things from libs of TikTok and all that

874
00:44:26,880 --> 00:44:29,760
Speaker 1: kind of stuff, and he's out there all right, Okay,

875
00:44:29,800 --> 00:44:32,319
Speaker 1: but he dies more for this company that makes these

876
00:44:32,400 --> 00:44:36,680
Speaker 1: data centers, and he believes from previous emails he sent

877
00:44:36,760 --> 00:44:40,479
Speaker 1: that AI is actually directing his company to build more

878
00:44:40,560 --> 00:44:45,160
Speaker 1: AI data centers, and that they're just becoming more and

879
00:44:45,200 --> 00:44:49,640
Speaker 1: more powerful and they are using US. AI is now

880
00:44:49,719 --> 00:44:52,719
Speaker 1: using US like it's service robots to go out and

881
00:44:52,719 --> 00:44:55,000
Speaker 1: build things and things like that. I don't know, this

882
00:44:55,120 --> 00:44:56,400
Speaker 1: is just coming from somebody.

883
00:44:56,719 --> 00:44:59,759
Speaker 16: Well, talk about that uh, that website Rent to Human

884
00:45:00,320 --> 00:45:02,360
Speaker 16: where they were trying to rent humans out to go

885
00:45:02,440 --> 00:45:05,399
Speaker 16: do actual physical tasks in the real world, so that

886
00:45:05,560 --> 00:45:08,200
Speaker 16: could be possible, and then they pay you in bitcoin.

887
00:45:09,600 --> 00:45:12,680
Speaker 1: This guy thinks it's actually happening, but on a super

888
00:45:12,719 --> 00:45:15,799
Speaker 1: big scale where they're hiring these large companies. He said that,

889
00:45:16,440 --> 00:45:18,200
Speaker 1: you know, it used to be I'm just throwing these

890
00:45:18,239 --> 00:45:20,120
Speaker 1: numbers out. I don't remember the numbers he gave, but

891
00:45:20,160 --> 00:45:21,680
Speaker 1: he said that, you know, it used to a couple

892
00:45:21,719 --> 00:45:23,800
Speaker 1: of years ago, they would build a data center. It

893
00:45:23,800 --> 00:45:27,200
Speaker 1: would cost let's you say, one hundred million dollars. Now,

894
00:45:27,239 --> 00:45:29,480
Speaker 1: he says, people don't even question. They just throw extra

895
00:45:29,560 --> 00:45:31,839
Speaker 1: money on there and they're just building data sent two

896
00:45:31,920 --> 00:45:37,760
Speaker 1: hundred million. Okay, nobody bats an eye because nobody's actually

897
00:45:37,760 --> 00:45:40,360
Speaker 1: paying for it. It's the AI paying for it, is

898
00:45:40,400 --> 00:45:42,759
Speaker 1: what he claims. All right, I do have to take

899
00:45:42,800 --> 00:45:44,799
Speaker 1: a break. We have these shizzy coming up in a moment.

900
00:45:44,840 --> 00:45:45,560
Speaker 1: What do you have on the way?

901
00:45:45,600 --> 00:45:45,880
Speaker 12: Do SHEI?

902
00:45:46,000 --> 00:45:50,560
Speaker 5: A lot of people go to marijuana to help ease anxiety,

903
00:45:50,760 --> 00:45:52,799
Speaker 5: but I'm going to tell you why that might not

904
00:45:52,920 --> 00:45:53,600
Speaker 5: be the answer.

905
00:45:53,840 --> 00:45:55,000
Speaker 6: Have that story for you next.

906
00:45:55,320 --> 00:45:57,480
Speaker 1: We'll get to that in just a minute. There is

907
00:45:58,520 --> 00:46:05,440
Speaker 1: D's nuts right. Crystal is correct. Meniscus is the point

908
00:46:05,680 --> 00:46:08,800
Speaker 1: of water where you measure it in a beaker or glass,

909
00:46:08,880 --> 00:46:14,880
Speaker 1: either convex or concave. So she's right, she's.

910
00:46:14,680 --> 00:46:15,560
Speaker 2: Smarter than all.

911
00:46:16,680 --> 00:46:21,919
Speaker 7: Actually, I say right, I don't think you were using

912
00:46:21,920 --> 00:46:22,600
Speaker 7: it at the right time.

913
00:46:22,640 --> 00:46:23,120
Speaker 2: You're trying.

914
00:46:23,160 --> 00:46:24,839
Speaker 7: It was a try hard move, I think because where

915
00:46:24,880 --> 00:46:27,360
Speaker 7: well we all will agreed it was right. We have

916
00:46:27,440 --> 00:46:30,120
Speaker 7: to talk to our average listener. It makes sense to

917
00:46:30,200 --> 00:46:30,400
Speaker 7: use it.

918
00:46:30,480 --> 00:46:34,399
Speaker 16: Yeah, it was above your intelligence for I was talking

919
00:46:34,400 --> 00:46:36,279
Speaker 16: about you. That's good.

920
00:46:36,400 --> 00:46:38,799
Speaker 1: So when I search for that though, I only get

921
00:46:38,840 --> 00:46:44,920
Speaker 1: stuff regarding cartilage and tears, I get nothing on it

922
00:46:45,080 --> 00:46:49,919
Speaker 1: when it comes to liquid. Let me see here, meniscous liquid. Oh,

923
00:46:50,320 --> 00:46:53,400
Speaker 1: meniscus is the curve formed by the surface of a

924
00:46:53,440 --> 00:46:57,040
Speaker 1: liquid and a container, caused by surface surface tension.

925
00:46:58,200 --> 00:47:00,359
Speaker 16: Don't ask me why that's stuck with me so many

926
00:47:00,440 --> 00:47:01,560
Speaker 16: years through science.

927
00:47:02,440 --> 00:47:05,400
Speaker 1: But I'm glad you were paying attention in school. I've

928
00:47:05,440 --> 00:47:06,920
Speaker 1: got to take a break. We'll be right back. Hang

929
00:47:07,000 --> 00:47:07,080
Speaker 1: on