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Speaker 1: My kids said a Alexa alert yesterday, Like right when

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Speaker 1: we were about to start recording, I suddenly hear the

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Speaker 1: Alexa full blast in the kitchen, just being like alert reminder,

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Speaker 1: you are getting a dog. You are getting a dog.

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Speaker 1: They're trying to like trick me into thinking I had

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Speaker 1: set an alert to just some subtle gaslighting. Yeah, yeah, dad,

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Speaker 1: was what I was like, impressed? Did they just watch

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Speaker 1: Inception right? Alert? You are getting a dog right now?

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Speaker 1: Hello the Internet, and welcome to season three point fifty seven,

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Speaker 1: episode four of der Day's I Stay production of iHeartRadio.

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Speaker 1: This is a podcast where we take a deep dive

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Speaker 1: into America's share consciousness. And it is Thursday, September twenty sixth,

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Speaker 1: twenty twenty four.

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Speaker 2: Mm hmm, what's going on, Miles hey man. It's National

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Speaker 2: Compliance Officer Day. It's National Situational Awareness Day. It's National

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Speaker 2: dump It's National dumpling.

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Speaker 3: Day, It's National pancake Day, it's National Shamboo the Whale Day,

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Speaker 3: and also National Johnny apple Seed Day. Johnny apple Seed.

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Speaker 3: We had to sing that every day before lunch and

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Speaker 3: my Lutheran school, you had what we had to sing

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Speaker 3: Johnny apple Seed. There was a Johnny apple seed Christian

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Speaker 3: song that we would have to sing before we would

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Speaker 3: go like to the cafeteria for lunch. It was really stupid.

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Speaker 3: It was like always like this grace song that we say,

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Speaker 3: make sure.

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Speaker 1: That you were thanking Jesus for your apples.

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Speaker 3: No, it was about the about the Lord is good

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Speaker 3: to me, and so I thank the Lord for giving

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Speaker 3: me the things I need, the sun and the rain.

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Speaker 1: Of the apple seed. The Lord is far to me.

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Speaker 3: Omen I'm in amen. Let's see Taco Bell.

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Speaker 1: Oh man, did you have to Taco Bell?

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Speaker 3: We got it acasionally, but yeah, that was like when

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Speaker 3: like somebing went down with the cafeteria, like look, yo,

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Speaker 3: we got Wiener Schnitzel and Taco Bell.

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Speaker 1: So you know, my seventh grade cafeteria had the bean

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Speaker 1: burritos and they were consistently yeah yeah, like pretty regularly.

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Speaker 1: They also had icys. It was like it was in

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Speaker 1: that moment where like nobody knew what nutrition was.

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Speaker 3: Yeah yeah, yeah, yeah yeah, and they're like yeah, kids

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Speaker 3: like it, yeah yeah, they like frozen sugar.

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Speaker 1: Yeah. Dayton, Ohio. Shout out to Centerville Public Schools because

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Speaker 1: they were they were serving us Taco Bell burritos and

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Speaker 1: then Lexington Public School District in Kentucky. We had Chick

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Speaker 1: fil At so wow, had them all? You've had them all.

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Speaker 4: All right, Ryan and Jack O'Brien AKA Band Joe Eric

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Speaker 4: Gary Slime Band Joe Eric, Gary Slime. Banjo Eric had

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Speaker 4: a dog bam ba lamb. But Gary's sitting on a

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Speaker 4: log bam b lamb. But whoa that one?

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Speaker 1: Courtesy of Halsion Salamo Discord Forring two Hour Too New

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Speaker 1: acronym alter egos acronym Banjo Eric Miles, Gary Slime. I

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Speaker 1: feel like that's accurate that they would be. I I

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Speaker 1: added the last part that Banjo Eric would be walking

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Speaker 1: around with a dog and Gary Slime will be sitting

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Speaker 1: on a lug. They're like kind of you know, they

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Speaker 1: look they those names are giving ride the rails a

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Speaker 1: little bit. Yeah, yeah, yeah, for sure, for sure. But yeah,

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Speaker 1: I don't know, I could get behind this, Like I

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Speaker 1: feel like that's a a proud tradition unlike any others

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Speaker 1: in fiction. Is like people having acronym names. Doesn't that

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Speaker 1: happen in like one of the Harry Potter books that

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Speaker 1: I think like he's like going by a different alter

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Speaker 1: ego name or like a ka and then like when

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Speaker 1: you unscramble the letters, it's like, wait a second, it's

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Speaker 1: that guy the whole time, it's the bad guy hints

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Speaker 1: it was and Joe Eric all along the hints. Yeah.

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Speaker 1: I do love that tweet where people are like, all right,

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Speaker 1: we're ready to do nine to eleven tomorrow, but one

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Speaker 1: last thing, the hints the handles. Yes, anyways. The anagram's

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Speaker 1: courtesy of Moniche The Black Betty Ramble am aka courtesy

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Speaker 1: of Halsey on Salad, and I'm thrilled to be joined

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Speaker 1: as always by my co host, mister Miles Grass.

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Speaker 3: It's Miles Gray aka Exit thousand dollars.

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Speaker 1: Shut the fuck up. Old they eating pets now, Shut

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Speaker 1: the fuck up. Immigrits on the move, Shut the fuck up.

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Speaker 1: You think we're pitches on stools? Shut the fuck up.

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Speaker 1: Want to keep dog whistling? Shut the fuck up, WANTA

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Speaker 1: cabinet position? Shut the fuck up. Soon as I'm VP,

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Speaker 1: Shut the fuck up.

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Speaker 3: The black bags are free, Shut the fuck up.

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Speaker 5: Okay.

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Speaker 3: Shout out to halcyon Salad for referencing a very fantastic

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Speaker 3: Jada Kiss track Knock Yourself Out, produced by the Neptunes.

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Speaker 3: For those who don't know, you know, and for the

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Speaker 3: that do, shout out to you. Uh yeah, wonderful Helion

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Speaker 3: Salad doing the exact today backing track, Halseon Salad with

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Speaker 3: the EXACTA box. I think I had to do the

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Speaker 3: backing track or else I had to give people the reference.

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Speaker 3: Otherwise it would just been like a lot of screaming and.

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Speaker 1: Shut the fuck up. I wait, why is Miles so

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Speaker 1: mad at me? And why is he whispering to himself? Miles.

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Speaker 1: We are thrilled to be joined in our third seat

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Speaker 1: today by the best selling author of books like John

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Speaker 1: Dies at the End, Zoe Punches, The Future, and The

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Speaker 1: Dick and the new stand alone. I'm starting to worry

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Speaker 1: about this black box of doom available now that shit

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Speaker 1: just dropped yesterday Fresh. It's also one of the hosts

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Speaker 1: of the podcast Big Feats, which, if I'm reading this

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Speaker 1: New Yorker profile correctly, is the only Mountain Monsters podcast

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Speaker 1: officially endorsed by Big Feet. He's my former co worker

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Speaker 1: at Cracked and co creator of the Crack podcast. Welcome

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Speaker 1: back to the show. It's Terras and.

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Speaker 5: Pardon and congratulations again on getting renewed for season three

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Speaker 5: hundred and fifty seven. I saw the headline in Variety. Yeah,

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Speaker 5: immediately texted Jack and he was like, who is this?

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Speaker 1: Please?

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Speaker 5: You don't text each other if you like that.

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Speaker 1: We only talk as contact. Jason.

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Speaker 5: Yes, say it for the podcast. I'm not doing this

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Speaker 5: for free. You're not just I'm not just giving this out.

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Speaker 1: I'm doing this for free.

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Speaker 3: Thank you for the freak, Thank you for the kind words. Yeah,

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Speaker 3: it's a it's every week. It's we're we're on a

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Speaker 3: knife's edge every Friday.

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Speaker 1: Three fifty seven. Know got our ship the Simpsons. That's

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Speaker 1: the phrase eat our Yeah, eat eat my ship, Bart Simpson. Jason,

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Speaker 1: how are you doing? I imagine, especially because you told

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Speaker 1: me right before we started recording that the day the

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Speaker 1: day is leading up to and immediately after a book

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Speaker 1: launch pretty exhausting.

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Speaker 5: Yeah, because you've got to do a lot of the

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Speaker 5: publicity stuff yourself, because you know, you can't hire somebody

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Speaker 5: to do the interviews for you or to do TikTok

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Speaker 5: videos for you, unless I can find somebody who looks

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Speaker 5: and sounds exactly like me. But if that guy existed,

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Speaker 5: I can think of other uses for him, probably, right,

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Speaker 5: So it's not a real job in my opinion. It's

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Speaker 5: a very stupid job, but also extremely exhausting because if

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Speaker 5: you've ever talked about yourself or something you made over

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Speaker 5: and over and over again, hundreds and hundreds of times,

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Speaker 5: and you're trying to make sure that you don't just

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Speaker 5: start lying at some point or make a thing different

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Speaker 5: what I'm contradicting yourself, or because I'm not so famous

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Speaker 5: that if I said something that it would like offhand

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Speaker 5: that I read at Ama, that it would get pulled

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Speaker 5: out and become a headline. That if I said something

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Speaker 5: stupid enough, it could go viral. I gets I'm in

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Speaker 5: that area where it could become I could become a

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Speaker 5: main character the day if I went far enough off

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Speaker 5: the rails. And you know, Jenk, you've interacted with me

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Speaker 5: for a very long time. Sometimes I just say stuff

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Speaker 5: that isn't true because I think it's funny, but I

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Speaker 5: say it in a very serious way.

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Speaker 1: Yeah.

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Speaker 5: That's gotten me in trouble many times in my life,

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Speaker 5: and it's inevitable that that's going to lead to my downfall.

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Speaker 5: So it's like, I just have to get through this

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Speaker 5: week because once the book's out there, it's out there.

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Speaker 5: They can't you know, they can't stop it. But yeah,

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Speaker 5: I think we did that. I don't think I said

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Speaker 5: anything too controversial, but you know.

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Speaker 1: Yeah, we're we're coming through the redditt Ama looking for

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Speaker 1: something that could end you, and so far no luck.

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Speaker 1: But yeah, I mean we all aspire to be famous

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Speaker 1: enough that we you know, just saying the wrong thing

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Speaker 1: can make you make you the put you in the spotlight.

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Speaker 1: Cool quote worthy. By the way, your answer is suspiciously

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Speaker 1: similar to the answer of somebody who has a double

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Speaker 1: like doing this podcast. God, that would be great, huh,

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Speaker 1: but not me could be and someone it.

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Speaker 3: Wouldn't be for stuff like this anyway.

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Speaker 5: It was Andrew WK. They there's a conspiracy theory that

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Speaker 5: they replaced him with a different dude, like halfway through

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Speaker 5: his career. Have you is anybody familiar with that? No?

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Speaker 1: I because I am internet brained. I thought that was true.

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Speaker 1: I thought there were two Andrew Wks.

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Speaker 5: It may absolutely be true. I don't know. I was

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Speaker 5: never able to get to the bottom of it.

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Speaker 3: But yeah, wait, what what do they say is the

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Speaker 3: moment that the WK switched over? You know, is there

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Speaker 3: a thing where they're like, look at him in this album, now,

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Speaker 3: look at him in this album. It's not the same

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Speaker 3: guy or anything like that.

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Speaker 1: Yeah, I mean, so there's the online equivalent of that

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Speaker 1: with Drill, right, everybody thinks Drill got replaced by like

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Speaker 1: a bot at some point recently. I'm trying to find

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Speaker 1: the Andrew WK story.

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Speaker 5: Because the guy, the original guy, is very was always

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Speaker 5: very cryptic about the answer City gave when they asked him.

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Speaker 5: He would always be like, well, Andrew w WK was

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Speaker 5: never a person. It was always a multimedia experiment, explanation

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Speaker 5: of an exploration of a persona blah blah blah, and

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Speaker 5: so they kind of fed into it. But I actually

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Speaker 5: never found the answer.

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Speaker 1: Of yeah, I can't find it. I don't know why

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Speaker 1: I thought that was true.

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Speaker 3: I've I've met him a few times. Like when I

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Speaker 3: worked at Playboy. We made a video that we created

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Speaker 3: a fake third political party for him called the Party

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Speaker 3: Party that like I helped make him, Like we created

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Speaker 3: a website and stuff, so like we texted for a

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Speaker 3: little bit that.

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Speaker 1: I mean, he's very real.

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Speaker 3: And that guy also would use like a rite aid

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Speaker 3: plastic bag is like his briefcase. Like he'd come to

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Speaker 3: the offices and he's like, let me empty, Like you

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Speaker 3: have this like plastic shopping bag and like his phone

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Speaker 3: in it and keys and like a notebook. And I

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Speaker 3: was always like, this guy is very interesting. But yeah,

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Speaker 3: I never heard that he had been swapped out ever.

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Speaker 3: But now I'm gonna have to look into that a

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Speaker 3: little bit.

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Speaker 5: Listeners, there's a rabbit hole you can follow down. There

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Speaker 5: used to be a website dedicated entirely to this to track,

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Speaker 5: you know, all the evidence back when websites existed. I

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Speaker 5: maybe there's an app now or a YouTube video that

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Speaker 5: does the same thing, but it was, it was a

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Speaker 5: thing at one time.

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Speaker 1: Yeah. The WK stands for who knows, you know, could

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Speaker 1: be true? We can't can't be confirmed or denied at

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Speaker 1: this point, Jason, we are going to get to know

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Speaker 1: you a little bit better in a moment. First, we're

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Speaker 1: going to tell the listeners to a couple of things

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Speaker 1: we're talking about. We're going to talk about new details

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Speaker 1: the Bipartisan report on the first assassination attempt that happened

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Speaker 1: on July thirteenth, a mirror that's two months ago, a

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Speaker 1: little over two months ago. That seems like a lifetime ago.

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Speaker 1: They released the Bipartisan report, and the only suspicious thing

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Speaker 1: is just like the Secret Service, like bad at their job,

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Speaker 1: which seemed to be the read from the start. Yeah,

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Speaker 1: it's like a carnival of errors, I think, is what

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Speaker 1: the report was titled. We're going to talk about the

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Speaker 1: death penalty, a thing that Democrats used to be against

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Speaker 1: for very good reasons, no longer on the party platform

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Speaker 1: for some reason. So we'll talk about that. We'll talk

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Speaker 1: about the price of eggs. We might even talk about

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Speaker 1: James Cameron joining an AI company's board of directors, which

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Speaker 1: you know he's like, actually, guys, nothing to fear here.

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Speaker 3: Yeah, yeah, so remember Miles Dyson, all that plenty more.

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Speaker 1: But first, Jason, we like to ask our guest, what

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Speaker 1: is something from your search history?

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Speaker 5: Hawk to a podcast? Real? Right? So I had seen

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Speaker 5: a whole bunch of memes on Twitter where people were

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Speaker 5: photoshopping the hawk to a girl onto a set discussing

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Speaker 5: some extremely academic subject in a podcast, and I thought, oh, okay,

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Speaker 5: they're calling her dumb whatever, and then saw a headline

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Speaker 5: that the Hawk to a podcast called talk to a

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Speaker 5: Uh huh. It was the number the number four podcasts

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Speaker 5: in the United States. It's like, oh, hold on, so

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Speaker 5: the podcast part is real. It's just that the memes

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Speaker 5: you're making are fake, and if so, what's the show about?

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Speaker 5: So I had to search and because I will admit

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Speaker 5: I cannot tell the difference between things people are just

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Speaker 5: joking about and things that actually happened. But yeah, apparently

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Speaker 5: successful podcast on I guess Jake Paul's work. And you've

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Speaker 5: probably covered all this. I was out of the loop.

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Speaker 1: Yeah no, I mean we've covered it in a sense

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Speaker 1: that we were, you know, really we were in a

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Speaker 1: bidding war with Jake Paul trying to bring this podcast

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Speaker 1: onto our network. I think we did, say, like the

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Speaker 1: week before it was announced that she had a podcast,

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Speaker 1: who were like, man, someone needs to give her a podcast.

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Speaker 3: Yeah, in there it is.

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Speaker 1: Because she, I mean, does seem to be a delight.

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Speaker 3: I know, Jason, you were seeing memes of it, like

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Speaker 3: the fake podcast, but then people were doing like memes

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Speaker 3: or comedy videos about the real talk to a thing.

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Speaker 3: It's like it was like all these bros getting together

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Speaker 3: like watching it on a big screen and be like, yeah,

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Speaker 3: it's like every single quip or funny line. And I

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Speaker 3: was like, okay, so now people are like kind of

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Speaker 3: leaning ironically into it and be like it's the fucking

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Speaker 3: sickest show.

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Speaker 1: I have not seen it. When I saw that this

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Speaker 1: was your search history, I assumed that it was they

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Speaker 1: were trying to book you onto the Hawk Tua podcast

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Speaker 1: Talk to to talk about your new rank. She's she's

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Speaker 1: a fan of novels and literature, so obviously it makes sense.

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Speaker 1: Is the story that there was one point where they

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Speaker 1: said that Donald Trump canceled his appearance on the Hawk

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Speaker 1: Tua podcast. Was that real or was that like a

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Speaker 1: fake story? I think it was right immediately after the

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Speaker 1: second assassination attempted Florida. One of the headlines that came

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Speaker 1: off of that in the days immediately after, where Trump

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Speaker 1: cancels appearance on Talk to Her if you put.

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Speaker 5: A gun to my head. I could not tell you

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Speaker 5: whether or not that was true.

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Speaker 1: Or the Express seems to be, oh the Express to

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Speaker 1: the Express Tribune, Well yeah, then of course, I mean

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Speaker 1: that seems weird. I mean, that's like a weird I mean,

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Speaker 1: like public use.

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Speaker 3: She she's she wasn't really speaking like fondly of Trump,

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Speaker 3: So I don't know where that would have happened.

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Speaker 1: But that was just like a fun thing for a

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Speaker 1: little while for people to do is have Trump on

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Speaker 1: your podcast, right, yeah, had him on and just told

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Speaker 1: him about cocaine. So yeah, I don't know.

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Speaker 3: And this Hawk too, Yeah, that just seems like such

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Speaker 3: a terrible pairing, like the Hawk to a girl and

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Speaker 3: Donald Trump and whatever. Like letting him just talk freely

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Speaker 3: in that context I feel like would lead to I

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Speaker 3: don't know what it would lead to led to, but

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Speaker 3: maybe it would help him, who.

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Speaker 5: Knows, I'm gonna say right now. Again, I don't know

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Speaker 5: if you discussed it when I came up. His appearance

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Speaker 5: on that THEO Vonn podcast that ironically fascinating because Deal

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Speaker 5: starts talking about doing cocaine and Donald Trump starts asking

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Speaker 5: him a bunch of probing questions and his first time

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Speaker 5: I'd seen him be like honestly interested in someone else

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Speaker 5: in their experiences. Yeah, and he's just being he wasn't

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Speaker 5: playing the character of Donald Trump that he's been playing

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Speaker 5: on TV for the last whatever fifty years and just

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Speaker 5: asking because he's genuinely because Trump Trump, you know, famously

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Speaker 5: does not drink or doesn't do drugs, I guess, And

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Speaker 5: it was just famously like fascinated by like what's the

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Speaker 5: mike and so you know, so so like what are you?

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Speaker 5: And there's THEO like, well, yeah.

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Speaker 1: You know, homie, Uh yeah, and uh being an l

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Speaker 1: out there man on your real street front port like

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Speaker 1: goddam be so heartbreaking for Donald Trump Junior because you

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Speaker 1: could have asked your own child about you know what

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Speaker 1: I mean and said, you're really interested in THEO Vaughn's

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Speaker 1: recap of doing that.

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Speaker 3: I'm flying out here right here, dad, you can ask

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Speaker 3: me about being an owl or a street land.

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Speaker 1: Or maybe he's like, I've been hearing about this cocaine

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Speaker 1: a lot lately. Not should I do it? Anyone close

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Speaker 1: to me? If your dad did it, would you think

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Speaker 1: he was cool?

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Speaker 5: What? No? Man?

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Speaker 1: Yeah? That That is one of the great things that

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Speaker 1: podcasting has brought us, as that conversation. Unfortunately, Jason, what

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Speaker 1: is something do you think? Is overrated?

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Speaker 5: I think all of the panic about like fake news

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Speaker 5: generated by AI and it was deep fakes for a while,

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Speaker 5: and all of that too, like generating a completely fake

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Speaker 5: story from whole cloth, is not and has never been

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Speaker 5: the real threat. I think the way that the news

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Speaker 5: media manipulates you will always be based on what stories

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Speaker 5: they choose to cover and not cover. Like all of

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Speaker 5: the news Autts choosing not to publish those hacked Trump

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Speaker 5: emails and side they're gonna sit on that. But like

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Speaker 5: the thing that you guys you referenced about the story

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Speaker 5: with the Haitian immigrants eating the pets, the reason that

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Speaker 5: fake story worked is because Fox News had been laying

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Speaker 5: the groundwork for years by just cherry picking actual crimes.

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Speaker 5: Because in a country of three hundred million people, you

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Speaker 5: can find a trend, whatever trend you want. So anytime

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Speaker 5: an illegal immigrant ran a stoplight, Fox News ran that

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Speaker 5: as a headline and creates by just carefully sorting through. Again,

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Speaker 5: you know, if a report comes out that says, well, actually,

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Speaker 5: you know, native born people are more likely to commit

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Speaker 5: crimes and immigrants, you simply you simply don't report it. Yeah,

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Speaker 5: And likewise, like this thing with the you know, the

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Speaker 5: governor North Carolina and that guy Mark Rappinsons his name

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Speaker 5: with all that crazy, like Fox News devoted like seven

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Speaker 5: minutes to that yesterday, Like they simply just bury it

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Speaker 5: and in their broadcast. That will always be the way

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Speaker 5: by which people get into bubbles and get programmed. It's not,

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Speaker 5: but it does not require the fake new stuff will

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Speaker 5: be a problem. It doesn't require a hoax. Just filtering

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Speaker 5: what you report and choose not to report will always,

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Speaker 5: by far be the most powerful thing, because for the

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Speaker 5: most part, you're sticking to things that are real. It's

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Speaker 5: just that they're not representative of what's going on, but

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Speaker 5: you can absolutely create the impression.

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Speaker 1: That they are. Yeah, just a wild selection bias has

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Speaker 1: always been the way that the US media tends to

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Speaker 1: operate because it's a big country and they know what

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Speaker 1: stories they can get a lot of eyeballs on because

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Speaker 1: they're scary and reinforced preconceived fears and beliefs.

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Speaker 3: And probably the easiest way to manufacture consent too, it

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Speaker 3: is just by being like, and what if we just

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Speaker 3: tell people about this all the time, and now when

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Speaker 3: the decision comes to do something awful, you're like, oh yeah, yeah, yeah, Okay,

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Speaker 3: that makes sense.

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Speaker 1: I didn't know that. Like they So they're just not

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Speaker 1: publishing the Trump emails because the.

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Speaker 3: Political The Washington Post, I think Judd Lugum, also at

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Speaker 3: Popular Information, said he was offered these documents, and he

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Speaker 3: said because he was involved in the Podesta emails, and

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Speaker 3: he just doesn't think that anything in the emails are

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Speaker 3: necessarily of note. Outside of just showing like a shitty

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Speaker 3: campaign that was like his logic. But then it's also like, well,

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Speaker 3: what's the logic of these other papers because they were

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Speaker 3: more than willing to publish the emails in the last

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Speaker 3: like in the twenty sixteen cycle. But it's yeah, it's

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Speaker 3: just kind of like, well, what what exactly like tell

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Speaker 3: us what the logic is of it? Yeah, but yeah,

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Speaker 3: that's that's sort of like where I feel like that

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Speaker 3: story is kind of out at the moment.

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Speaker 1: Yeah, we were talking about this a little bit last

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Speaker 1: week with regards to there was a Russian created fake

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Speaker 1: media like fake a local news story about Kamala Harris

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Speaker 1: like running someone over in her car and then like

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Speaker 1: driving away in San Francisco, and like people were just

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Speaker 1: you know, you could see that it was a fake

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Speaker 1: news site that doesn't actually exist. They created the URL

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Speaker 1: two days before. It wasn't overly convincing, and it didn't

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Speaker 1: seem to like get that much media attention other than

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Speaker 1: the debunking of it got a lot of attention. Whereas

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Speaker 1: you know, just Elon Musk having as many followers in

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Speaker 1: as much sway as he has just tweeting any dumb

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Speaker 1: bullshit absent mindedly is pretty I think, more influential than

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Speaker 1: I want to believe.

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Speaker 3: It is also well yeah, now, especially with the block

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Speaker 3: function being like, ah, even if you block me, you're

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Speaker 3: still going to see my bullshit.

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Speaker 1: Yeah yeah.

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Speaker 5: I think that the thing with Hillary's emails in twenty sixteen,

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Speaker 5: I think that is the perfect example of what I'm

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Speaker 5: talking about here, because that was the case where I

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Speaker 5: think if you interviewed one thousand people both sides, and said,

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Speaker 5: can you summarize what was scandalous about her emails the

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Speaker 5: whole but her emails them, which became the number one

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Speaker 5: story that entire campaign because those were released in a

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Speaker 5: drip feed where it's like a new revelation every day,

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Speaker 5: Can you summarize what the deal was with those emails

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Speaker 5: and why that should be a deciding factor in who

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Speaker 5: you vote for. I think not five people in a

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Speaker 5: thousand could accurately explain. But when The New York Times

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Speaker 5: has Hillary clinton emails as the a one story every day,

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Speaker 5: Hillary Clint't email scandal, by putting it at the top

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Speaker 5: of the front page, you are saying that it's important.

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Speaker 5: You are saying that it's huge and impactful and this

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Speaker 5: must be a terrible crime that's been Like, this must

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Speaker 5: be disqualifying. So even if you watching it don't fully

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Speaker 5: understand what's bad about it or what it means or whatever,

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Speaker 5: it doesn't matter because giving it that place on the

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Speaker 5: front page indicates that it matters, and it's a negative story.

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Speaker 5: So he's saying, Hey, all the other stuff in this

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Speaker 5: selection not important. This email server, your personal email server.

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Speaker 5: Security candidates using personal email for like, that's what matters.

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Speaker 5: That's the thing that's at stake in this election. And

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Speaker 5: they set the agenda that way. Again, the stuff they

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Speaker 5: were reporting wasn't fake, it's just the amount of spotlight

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Speaker 5: they chose to give to it as opposed to anything

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Speaker 5: else that created the impression that it is I think

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Speaker 5: as false as any something that was you know, that

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Speaker 5: had been gend up out of whole cloth.

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Speaker 3: Yeah, yeah, I mean I think, yeah. It gave a

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Speaker 3: look into like sort of what was going on in

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Speaker 3: the DNC.

434
00:23:30,880 --> 00:23:31,520
Speaker 1: But then people like.

435
00:23:31,560 --> 00:23:34,080
Speaker 3: John Podesta called a guy a prick and this is

436
00:23:34,080 --> 00:23:37,920
Speaker 3: his risotto recipe and what. But they're at the same time, like,

437
00:23:38,400 --> 00:23:40,880
Speaker 3: you know, Colin Powell also had a private email server.

438
00:23:40,920 --> 00:23:44,160
Speaker 3: A lot of people like what it, what's the emphasis

439
00:23:44,200 --> 00:23:46,600
Speaker 3: about But yeah, now it's just very.

440
00:23:46,560 --> 00:23:49,320
Speaker 1: Much like it's not in the public interest Jason. What's

441
00:23:49,320 --> 00:23:51,440
Speaker 1: something you think is underrated.

442
00:23:52,359 --> 00:23:55,159
Speaker 5: The degree to which the most important stuff And this

443
00:23:55,320 --> 00:24:01,040
Speaker 5: election probably has not happened yet twenty sixteen, the thing

444
00:24:01,040 --> 00:24:05,520
Speaker 5: with Hillary's emails that wasn't until October Trump's remember the

445
00:24:05,560 --> 00:24:09,760
Speaker 5: Access Hollywood tape grabbing by the Pussy tape that didn't

446
00:24:09,800 --> 00:24:13,800
Speaker 5: come out until October seventh. The James Comu letter that

447
00:24:14,320 --> 00:24:17,119
Speaker 5: we thought that that probably did throw the election to Trump,

448
00:24:17,119 --> 00:24:20,240
Speaker 5: that wasn't until October twenty eighth. So in an election

449
00:24:20,400 --> 00:24:22,639
Speaker 5: just close where it's going to be swayed by like

450
00:24:22,720 --> 00:24:26,960
Speaker 5: ten thousand people, it's probably going to it'll be determined

451
00:24:26,960 --> 00:24:29,640
Speaker 5: by something that happens between now and November fifth. There's

452
00:24:29,640 --> 00:24:32,800
Speaker 5: something probably in the month of October. That's when most

453
00:24:32,840 --> 00:24:36,199
Speaker 5: people actually finally start paying attention, and there will be

454
00:24:36,200 --> 00:24:38,880
Speaker 5: some story, some event, something's going to happen that will

455
00:24:38,880 --> 00:24:41,200
Speaker 5: probably tilt things one way or the other.

456
00:24:41,920 --> 00:24:44,840
Speaker 3: Yeah, I mean, yeah, it's the October surprise of it all.

457
00:24:45,000 --> 00:24:48,240
Speaker 3: And we're not even in October, so we'll see what. Yeah,

458
00:24:48,280 --> 00:24:51,200
Speaker 3: this cycle breaks, and I'm sure for people who are

459
00:24:51,240 --> 00:24:54,360
Speaker 3: like the ones trying to peddle as much like wacky

460
00:24:54,680 --> 00:24:58,200
Speaker 3: misinformation or whatever. They're probably sitting on like their most

461
00:24:58,280 --> 00:25:01,480
Speaker 3: potent you know, weapons. And yeah, like you're saying close,

462
00:25:01,600 --> 00:25:04,200
Speaker 3: much closer to the election, because that's really when Yeah,

463
00:25:04,280 --> 00:25:07,160
Speaker 3: like it has the most impact on people's at least

464
00:25:07,280 --> 00:25:08,399
Speaker 3: perception of what's happening.

465
00:25:08,960 --> 00:25:12,960
Speaker 1: Yeah, an official like what was saying last week that

466
00:25:13,119 --> 00:25:15,600
Speaker 1: like the final forty eight hours before the election are

467
00:25:15,640 --> 00:25:21,080
Speaker 1: going to be absolute chaos on social media, right, But yeah,

468
00:25:21,200 --> 00:25:25,960
Speaker 1: that's really upsetting that the Access Hollywood tape wasn't until

469
00:25:25,960 --> 00:25:28,879
Speaker 1: October seventh, Like that that was one where it was

470
00:25:28,920 --> 00:25:31,560
Speaker 1: like a bombshell that people like got over.

471
00:25:32,160 --> 00:25:34,680
Speaker 5: Yeah, that's a thing where people in the wake it

472
00:25:34,840 --> 00:25:36,359
Speaker 5: was like, oh my gosh, she's gonna have to drop

473
00:25:36,359 --> 00:25:41,679
Speaker 5: out done because they still didn't understand how impervious, Like

474
00:25:41,760 --> 00:25:44,840
Speaker 5: he didn't lose a single vote from that, Like they didn't.

475
00:25:45,000 --> 00:25:46,600
Speaker 5: And this is why if I had to put money

476
00:25:46,600 --> 00:25:49,600
Speaker 5: on this election, I would bet on Trump because Kamala

477
00:25:49,680 --> 00:25:53,800
Speaker 5: Harris can be heard by a scandal. Trump is impervious

478
00:25:53,800 --> 00:25:57,120
Speaker 5: to scandal. Yeah, there is no headline that I can

479
00:25:57,280 --> 00:26:01,080
Speaker 5: imagine they would actually steer people away from Trump. He's

480
00:26:01,160 --> 00:26:04,000
Speaker 5: just he's been like, what would it even be about?

481
00:26:04,560 --> 00:26:08,720
Speaker 5: Nothing about sex, that stuff's already out there, nothing about racism,

482
00:26:08,800 --> 00:26:12,320
Speaker 5: nothing about financial wrongdoing. All of that stuff he's already

483
00:26:12,600 --> 00:26:15,120
Speaker 5: some of which he's been charged with in court and

484
00:26:15,160 --> 00:26:19,160
Speaker 5: found guilty. So it's like, what could come out that

485
00:26:19,280 --> 00:26:21,600
Speaker 5: hasn't already come out. It just feels like he has

486
00:26:21,640 --> 00:26:24,520
Speaker 5: an immunity that he's built up, and that seems to

487
00:26:24,560 --> 00:26:27,399
Speaker 5: be his superpower, because it's true that his support seems

488
00:26:27,400 --> 00:26:30,240
Speaker 5: to top out like forty seven percent or whatever in polls,

489
00:26:30,640 --> 00:26:34,800
Speaker 5: but nothing pushes it down. Nothing. Yeah, So it just

490
00:26:35,080 --> 00:26:38,120
Speaker 5: feels like such a double standard where only one candidate

491
00:26:38,240 --> 00:26:41,480
Speaker 5: is vulnerable to some bad story that they will come

492
00:26:41,520 --> 00:26:43,800
Speaker 5: out with something a week for the election or two

493
00:26:43,880 --> 00:26:47,439
Speaker 5: days before, and it seems like only one candidate is

494
00:26:47,560 --> 00:26:48,880
Speaker 5: vulnerable to that kind of thing.

495
00:26:49,640 --> 00:26:51,480
Speaker 3: Yeah, I mean, I think we've joked, we're like, what

496
00:26:51,680 --> 00:26:54,720
Speaker 3: could even be the thing that his own support is like, oh, well,

497
00:26:55,160 --> 00:26:56,919
Speaker 3: that's a bridge too far, Like it's like, would it

498
00:26:56,920 --> 00:27:00,520
Speaker 3: even be something like a super progressive policy see or

499
00:27:00,560 --> 00:27:02,240
Speaker 3: something like that, or then even then they're like no,

500
00:27:02,280 --> 00:27:04,520
Speaker 3: actually no, I'm actually for that. Actually I think climate

501
00:27:04,600 --> 00:27:07,240
Speaker 3: change is really important and we should we should stop fracking.

502
00:27:07,760 --> 00:27:10,440
Speaker 1: It's like, oh fuck, like what is it? But it's

503
00:27:10,440 --> 00:27:13,840
Speaker 1: definitely been rumors that he's on tape like calling his

504
00:27:14,200 --> 00:27:19,040
Speaker 1: supporters like, you know, horrible things and being very derisive

505
00:27:19,119 --> 00:27:21,960
Speaker 1: towards his own supporters they love. I don't think that would.

506
00:27:22,359 --> 00:27:23,960
Speaker 1: I don't think that would do it at all. Like

507
00:27:24,119 --> 00:27:26,800
Speaker 1: that's the closest I think even if it was.

508
00:27:26,840 --> 00:27:30,760
Speaker 3: It's like and Donald Trump has been Hillary Clinton all along,

509
00:27:31,160 --> 00:27:32,159
Speaker 3: people are like, I.

510
00:27:32,119 --> 00:27:38,720
Speaker 2: Don't know, man, I don't know even if she's yeah.

511
00:27:37,359 --> 00:27:40,320
Speaker 1: The yeah, if he literally was on tape being like

512
00:27:40,320 --> 00:27:43,440
Speaker 1: they are a basket of deplorables, I think they're discussed

513
00:27:43,680 --> 00:27:46,760
Speaker 1: like it would be the tape, like if there was

514
00:27:46,800 --> 00:27:50,240
Speaker 1: the tape that would undo the politician in the movie

515
00:27:50,400 --> 00:27:53,720
Speaker 1: about a corrupt politician. Whereas they're just like I hate

516
00:27:53,720 --> 00:27:57,040
Speaker 1: them all and I'm gonna kill them when I get

517
00:27:57,080 --> 00:27:59,760
Speaker 1: into office. We're gonna like take all their money away,

518
00:27:59,760 --> 00:28:03,760
Speaker 1: and like that probably wouldn't do it. Like they just

519
00:28:03,960 --> 00:28:05,520
Speaker 1: find a way to justify.

520
00:28:05,160 --> 00:28:07,320
Speaker 3: It well because they're like, well he's still he's still

521
00:28:07,320 --> 00:28:10,119
Speaker 3: going to bring the pain, right, yeah, yeah, they're like

522
00:28:11,000 --> 00:28:11,560
Speaker 3: ringing the pain.

523
00:28:11,800 --> 00:28:16,040
Speaker 1: Then we're that why can stomach anything. Yeah, all right,

524
00:28:16,680 --> 00:28:18,720
Speaker 1: let's take a quick break and we'll come back and

525
00:28:18,720 --> 00:28:32,639
Speaker 1: talk about some news, and we're back. We're and the

526
00:28:32,680 --> 00:28:36,960
Speaker 1: Senate has released their bipartisan report on what happened at

527
00:28:37,080 --> 00:28:42,120
Speaker 1: the July thirteenth Trump rally in Butler, And yeah, it

528
00:28:42,240 --> 00:28:46,280
Speaker 1: seems to be basically what we thought at the time

529
00:28:46,360 --> 00:28:50,800
Speaker 1: that like, the most noteworthy thing is the incompetence of

530
00:28:50,840 --> 00:28:54,960
Speaker 1: the Secret Service to kind of do their job.

531
00:28:55,360 --> 00:28:58,240
Speaker 3: And just like law enforcement, communicating seemed to be the

532
00:28:58,240 --> 00:29:01,680
Speaker 3: big thing that they Again, the main findings were Secret

533
00:29:01,720 --> 00:29:05,680
Speaker 3: Service failed to sufficiently coordinate with state and local law enforcement,

534
00:29:05,760 --> 00:29:09,240
Speaker 3: failed to adequately cover the building where Trump's attempted assassin

535
00:29:09,320 --> 00:29:13,000
Speaker 3: fired from, failed to address line of sight concerns, denied

536
00:29:13,040 --> 00:29:16,560
Speaker 3: requests for additional resources, and failed to pass on to

537
00:29:16,680 --> 00:29:19,560
Speaker 3: other law law enforcement that there was a there was

538
00:29:19,640 --> 00:29:24,200
Speaker 3: quote credible intelligence of a threat. And they also noted

539
00:29:24,200 --> 00:29:27,600
Speaker 3: in the report that the Secret Service denied responsibility or

540
00:29:27,640 --> 00:29:31,600
Speaker 3: tried to deflect blame when pressed about their individual roles.

541
00:29:32,040 --> 00:29:34,280
Speaker 3: So like again, so it sounds like the biggest errors

542
00:29:34,320 --> 00:29:37,640
Speaker 3: were there just weren't enough people available to secure all

543
00:29:37,680 --> 00:29:40,719
Speaker 3: the buildings that could have posed a potential threat. And

544
00:29:40,720 --> 00:29:44,680
Speaker 3: then sniper teams didn't tell Trump's details specifically to get

545
00:29:44,760 --> 00:29:48,200
Speaker 3: him off the stage when they had identified a potential threat,

546
00:29:48,240 --> 00:29:51,000
Speaker 3: like minutes had passed where they're like, like, I think

547
00:29:51,040 --> 00:29:52,960
Speaker 3: they're like, yeah, normally you would have just told him, yo,

548
00:29:53,040 --> 00:29:54,760
Speaker 3: get this guy off the stage, Like we have police

549
00:29:54,800 --> 00:29:58,000
Speaker 3: officers rushing a building, like with their guns drawn to something,

550
00:29:58,160 --> 00:30:00,280
Speaker 3: so that would immediately be like, okay, pull the lug

551
00:30:00,320 --> 00:30:00,520
Speaker 3: on this.

552
00:30:00,920 --> 00:30:03,600
Speaker 1: But that was not the case. You see them like

553
00:30:03,640 --> 00:30:06,080
Speaker 1: in the in that video draw down on the sniper

554
00:30:06,320 --> 00:30:09,520
Speaker 1: like and you know, starting to get serious as he's

555
00:30:09,600 --> 00:30:13,560
Speaker 1: like continuing to deliver his I guess you could call

556
00:30:13,560 --> 00:30:16,840
Speaker 1: it a stumps whatever his remark remarks. So yeah, that

557
00:30:16,960 --> 00:30:19,880
Speaker 1: was always the weirdest thing about their response was that

558
00:30:20,440 --> 00:30:24,480
Speaker 1: they just didn't They weren't like, hey, we have a snight,

559
00:30:24,600 --> 00:30:27,680
Speaker 1: you know, they didn't communicate the out loud.

560
00:30:28,200 --> 00:30:28,520
Speaker 5: Yeah.

561
00:30:28,560 --> 00:30:31,520
Speaker 1: And obviously also the weirdest thing is the water the

562
00:30:31,560 --> 00:30:33,960
Speaker 1: guy who was on the water tower who was clearly

563
00:30:35,760 --> 00:30:39,120
Speaker 1: fired yeah from two miles away, or how the person

564
00:30:39,160 --> 00:30:41,920
Speaker 1: who fired a shot. The conspiracy theory that this was

565
00:30:41,960 --> 00:30:45,280
Speaker 1: all staged one of one of them involves a guy

566
00:30:45,320 --> 00:30:47,640
Speaker 1: on a water tower two miles away who fired the

567
00:30:47,680 --> 00:30:53,840
Speaker 1: shot that grazed Trump's ear, So just an a supernatural

568
00:30:54,280 --> 00:30:59,160
Speaker 1: marksmanship being relied on to graze his ear so that

569
00:30:59,320 --> 00:31:05,360
Speaker 1: he wouldn't act actually be hurt. But yeah, yeah, where's

570
00:31:05,400 --> 00:31:06,200
Speaker 1: the report on that?

571
00:31:06,960 --> 00:31:09,400
Speaker 3: Well, I mean the House. The House is doing their

572
00:31:10,080 --> 00:31:13,920
Speaker 3: their version of investigation too. Since that's a Republican controlled body,

573
00:31:14,080 --> 00:31:16,920
Speaker 3: I'm sure you might get a slightly spicier take on

574
00:31:17,040 --> 00:31:19,440
Speaker 3: what is happening. But yeah, overall, it sounds like a big,

575
00:31:19,800 --> 00:31:23,959
Speaker 3: big boo boo, big failure since the Reagan assassination attempt.

576
00:31:24,560 --> 00:31:26,920
Speaker 5: Here's a good life lesson in this for any of

577
00:31:26,920 --> 00:31:29,000
Speaker 5: you young people out there, because you're going to find

578
00:31:29,000 --> 00:31:31,760
Speaker 5: this happen in your own life. You can have a

579
00:31:31,920 --> 00:31:37,239
Speaker 5: system in place that is deeply broken or neglected, and

580
00:31:37,280 --> 00:31:40,920
Speaker 5: it can take a long time to notice it because

581
00:31:41,640 --> 00:31:45,280
Speaker 5: the thing that it's predesigned to prevent just hasn't happened.

582
00:31:45,280 --> 00:31:47,920
Speaker 5: For example, whenever there's an earthquake, a whole lot of

583
00:31:47,920 --> 00:31:50,000
Speaker 5: buildings will fall over that it turns out we're not

584
00:31:50,200 --> 00:31:53,160
Speaker 5: up to code, because it turns out you build a

585
00:31:53,160 --> 00:31:55,920
Speaker 5: building and all the anti earthquakes stuff you're supposed to

586
00:31:55,920 --> 00:31:59,640
Speaker 5: do if you bribe an inspector. It's fine because it

587
00:31:59,680 --> 00:32:03,360
Speaker 5: may be fifty years before an earthquake happens. The whole

588
00:32:03,400 --> 00:32:06,920
Speaker 5: time that building looks fine. This is very similar to that.

589
00:32:07,400 --> 00:32:12,080
Speaker 5: It seems like their processes, they're staffing, their training, everything

590
00:32:12,200 --> 00:32:14,520
Speaker 5: had been degrading. They'd been kind of half asking it.

591
00:32:15,160 --> 00:32:19,040
Speaker 5: But it you just don't know, because there aren't that

592
00:32:19,240 --> 00:32:24,200
Speaker 5: many serious assassination attempts. There's lots of nut jobs, like

593
00:32:24,280 --> 00:32:26,800
Speaker 5: some idiot with a flare gun tried to climb the

594
00:32:26,840 --> 00:32:29,560
Speaker 5: fence at the White House and the President wasn't even there,

595
00:32:29,680 --> 00:32:33,360
Speaker 5: but where somebody planned it, found a spot, was good

596
00:32:33,400 --> 00:32:36,360
Speaker 5: with the weapon, knew we you know, studied where to go,

597
00:32:36,520 --> 00:32:40,120
Speaker 5: how to get up there undetected. That's rare. And when

598
00:32:40,160 --> 00:32:44,440
Speaker 5: someone finally tries it, they find a process that is broken,

599
00:32:45,040 --> 00:32:48,640
Speaker 5: the process of that whole perimeter they're supposed to clear

600
00:32:48,680 --> 00:32:51,240
Speaker 5: and cooperating with the local cops to clear that perimeter,

601
00:32:51,320 --> 00:32:53,960
Speaker 5: to communicate about the spons and where somebody needed to

602
00:32:54,000 --> 00:32:57,080
Speaker 5: be all that that process was. And you will find

603
00:32:57,240 --> 00:33:01,479
Speaker 5: in your business or in your marriage or anything, stuff

604
00:33:01,480 --> 00:33:08,160
Speaker 5: that looks fine for years until the bad thing happens

605
00:33:08,200 --> 00:33:11,360
Speaker 5: and you realize how unprepared you were this is this

606
00:33:11,520 --> 00:33:13,520
Speaker 5: was almost a and it's funny enough because we're like

607
00:33:13,560 --> 00:33:16,600
Speaker 5: doing this report and it's you know, page three news.

608
00:33:16,640 --> 00:33:20,680
Speaker 5: It's like, okay, we're in some alternate universe where this

609
00:33:20,800 --> 00:33:25,400
Speaker 5: man's head exploded in four K in front of the world.

610
00:33:26,400 --> 00:33:28,680
Speaker 5: That there would be you know, like we would know

611
00:33:28,760 --> 00:33:31,320
Speaker 5: the names of these Secret Service agents like we would

612
00:33:31,360 --> 00:33:34,080
Speaker 5: all they would be household names of which guy allowed

613
00:33:34,080 --> 00:33:37,680
Speaker 5: this failure, which person failed to you know, report the

614
00:33:37,720 --> 00:33:40,680
Speaker 5: guy on the roof and so on. And instead of

615
00:33:40,880 --> 00:33:44,040
Speaker 5: just like yeahs and yeah they could we could have

616
00:33:44,040 --> 00:33:46,520
Speaker 5: done better, guys, we kind of fumbled it, kind of

617
00:33:46,520 --> 00:33:48,080
Speaker 5: biffed it there. Yeah.

618
00:33:48,200 --> 00:33:51,080
Speaker 1: The I mean the two things that earthquake prevention and

619
00:33:51,400 --> 00:33:55,719
Speaker 1: like checking every possible threat and eye line have in

620
00:33:55,760 --> 00:34:01,240
Speaker 1: common is they're both so annoying to do and it

621
00:34:02,960 --> 00:34:06,120
Speaker 1: probably won't even happen, So like, what is your fucking deal?

622
00:34:06,360 --> 00:34:09,920
Speaker 1: So you have that, you have that dynamic combined with

623
00:34:10,360 --> 00:34:13,960
Speaker 1: I feel like anytime the Secret Service is involved in

624
00:34:14,680 --> 00:34:18,560
Speaker 1: a action movie, like they're pretty locked up. Like even

625
00:34:18,560 --> 00:34:20,440
Speaker 1: when the plot is like this is the guy who

626
00:34:20,520 --> 00:34:23,400
Speaker 1: allowed JFK to be assassinated like in the Line of Fire,

627
00:34:24,000 --> 00:34:27,600
Speaker 1: it's still like he is Clint Eastwood, and he's like

628
00:34:27,920 --> 00:34:32,680
Speaker 1: a super heroic like badass who that they ultimately saved

629
00:34:32,719 --> 00:34:35,560
Speaker 1: the president this time around. And I feel like it,

630
00:34:35,960 --> 00:34:38,920
Speaker 1: don't they like White House Down and like those movies?

631
00:34:38,960 --> 00:34:42,200
Speaker 1: Isn't their Secret Service involved in those? I feel like

632
00:34:42,360 --> 00:34:46,160
Speaker 1: just generally, yeah, I feel like the branding being done

633
00:34:46,200 --> 00:34:48,239
Speaker 1: for the Secret Service is pretty strong.

634
00:34:48,280 --> 00:34:51,320
Speaker 3: Yeah, for the most rather than like sex worker scandals

635
00:34:51,360 --> 00:34:54,040
Speaker 3: like when during Obama's presidency and shit like that, Like

636
00:34:54,080 --> 00:34:56,000
Speaker 3: these guys sound like a bunch of frat guys.

637
00:34:56,680 --> 00:35:00,479
Speaker 1: Yeah no, no, no, no, no, no, they're Gerard Butler. They're Gerard Butler. Yeah.

638
00:35:00,960 --> 00:35:04,280
Speaker 1: Like so they described this as the biggest Secret Service

639
00:35:04,280 --> 00:35:07,840
Speaker 1: failure since the Reagan assassination attempt, but like even the

640
00:35:07,880 --> 00:35:12,319
Speaker 1: Reagan assassination attempt, I the thing I remember is like

641
00:35:12,360 --> 00:35:14,759
Speaker 1: a guy standing there with like a tiny Uzi in

642
00:35:14,840 --> 00:35:18,440
Speaker 1: his hand, looking bad ass, like being a Milwaukie talkie, you know,

643
00:35:18,719 --> 00:35:20,520
Speaker 1: and like, yeah, he got shot though, he got shot,

644
00:35:20,680 --> 00:35:22,440
Speaker 1: and then the other guy who got the guy who

645
00:35:22,440 --> 00:35:26,960
Speaker 1: got shot in paralyzed who Brady right that who they

646
00:35:27,120 --> 00:35:30,840
Speaker 1: named laws after. And I did not, truly did not

647
00:35:31,000 --> 00:35:33,520
Speaker 1: know the Reagan assassination attempt was seen as a secret

648
00:35:33,520 --> 00:35:34,600
Speaker 1: service failure.

649
00:35:34,560 --> 00:35:37,400
Speaker 5: Totally forgotten, like we don't remember it that way, you know.

650
00:35:37,760 --> 00:35:41,240
Speaker 1: Yeah, I had a fucking little uzzi, like a cute uzy.

651
00:35:41,800 --> 00:35:45,959
Speaker 1: That's unbelievable. It's unbelievable that they gave them that too,

652
00:35:46,680 --> 00:35:50,840
Speaker 1: especially man, Yeah, especially when you know what happened with JFK,

653
00:35:51,000 --> 00:35:53,839
Speaker 1: What actually happened with JFK. Tell him, tell him Jack.

654
00:35:54,719 --> 00:35:57,360
Speaker 1: I can't do it, Miles. We have other stories to

655
00:35:57,400 --> 00:36:00,600
Speaker 1: get to. All right, I think that's another podcast accidentally

656
00:36:00,680 --> 00:36:04,400
Speaker 1: delivered the kill shot. All right, let's talk about the

657
00:36:04,440 --> 00:36:08,400
Speaker 1: death penalty. Yeah, because so yeah.

658
00:36:08,000 --> 00:36:11,640
Speaker 3: Yeah, it's an arcane feature of our car sol system

659
00:36:11,760 --> 00:36:13,399
Speaker 3: that should be done away with.

660
00:36:13,560 --> 00:36:13,759
Speaker 5: You know.

661
00:36:14,360 --> 00:36:16,560
Speaker 3: The reason I think it's important to talk about because

662
00:36:16,719 --> 00:36:20,040
Speaker 3: on Tuesday Marcellus Williams was put to death in Missouri.

663
00:36:20,120 --> 00:36:23,960
Speaker 3: And he's a man that even prosecutors thought was innocent

664
00:36:24,080 --> 00:36:27,640
Speaker 3: of a nineteen ninety eight murder. Williams and his lawyers

665
00:36:27,640 --> 00:36:29,600
Speaker 3: had been in like a long fight to clear his

666
00:36:29,719 --> 00:36:31,759
Speaker 3: name and to prevent him from being put to death

667
00:36:31,840 --> 00:36:34,840
Speaker 3: by the state for the murder of woman Felicia Gale.

668
00:36:35,120 --> 00:36:38,120
Speaker 3: They had previously been granted stays twice due to the

669
00:36:38,200 --> 00:36:42,759
Speaker 3: murky nature of the conviction, and like, despite mishandling of evidence,

670
00:36:42,840 --> 00:36:47,480
Speaker 3: reliance on like jailhouse snitch testimony, a racist jury selection process,

671
00:36:47,480 --> 00:36:50,520
Speaker 3: and a total lack of DNA evidence that tying him

672
00:36:50,520 --> 00:36:53,759
Speaker 3: to the crime scene whatsoever, Governor Mike Parson let the

673
00:36:53,800 --> 00:36:58,120
Speaker 3: execution go forward. The NAACP has described it as a lynching,

674
00:36:58,560 --> 00:37:00,799
Speaker 3: and you know, the death penalty is again I think

675
00:37:00,840 --> 00:37:02,600
Speaker 3: this is why it's important to look at it in

676
00:37:02,680 --> 00:37:04,640
Speaker 3: a like a sort of larger context in terms of

677
00:37:04,680 --> 00:37:07,239
Speaker 3: like policy, right, because it's not only just a waste

678
00:37:07,280 --> 00:37:09,960
Speaker 3: of resources, but it's also a glaring example of how

679
00:37:10,000 --> 00:37:14,080
Speaker 3: our carcial system disproportionately again affects people of color. You

680
00:37:14,120 --> 00:37:16,680
Speaker 3: look at, you know, the death row population is forty

681
00:37:16,719 --> 00:37:19,120
Speaker 3: one percent black, even though black people make up about

682
00:37:19,160 --> 00:37:22,640
Speaker 3: thirteen percent of the US population. You look at just

683
00:37:22,719 --> 00:37:25,960
Speaker 3: even how you know, like when victims are white and

684
00:37:26,160 --> 00:37:29,440
Speaker 3: the accused is a person of color, like the people

685
00:37:29,440 --> 00:37:32,880
Speaker 3: like seeking the death penalty goes up exponentially. But if

686
00:37:32,920 --> 00:37:35,120
Speaker 3: you like have a victim that is a person of color,

687
00:37:35,440 --> 00:37:39,879
Speaker 3: and even if the perpetrator or the accused is white,

688
00:37:39,080 --> 00:37:43,280
Speaker 3: the figures are much less in favor of the death penalty.

689
00:37:43,320 --> 00:37:46,280
Speaker 3: So there's like example after example and study after study

690
00:37:46,360 --> 00:37:49,000
Speaker 3: just shows like the inherent racism that the system is

691
00:37:49,000 --> 00:37:51,520
Speaker 3: built on. And I think this example in Missouri is

692
00:37:51,520 --> 00:37:54,839
Speaker 3: just another you know, it just encapsulates how black men

693
00:37:54,920 --> 00:37:57,560
Speaker 3: are viewed by our you know, quote unquote justice system.

694
00:37:57,920 --> 00:38:00,600
Speaker 3: Because the victim's family even wanted, will you life to

695
00:38:00,640 --> 00:38:03,560
Speaker 3: be spared? You know, they're like, we like, for us

696
00:38:03,600 --> 00:38:06,000
Speaker 3: closure would be for his life to be spared. And

697
00:38:06,160 --> 00:38:08,400
Speaker 3: they're like we would love to have his sentence commuted

698
00:38:08,520 --> 00:38:12,000
Speaker 3: or whatever, just please like spare his life. But the

699
00:38:12,040 --> 00:38:15,840
Speaker 3: governor of Missouri, Parson, he just has a really terrible

700
00:38:15,920 --> 00:38:18,480
Speaker 3: track record when it comes to clemency and that he

701
00:38:18,520 --> 00:38:21,200
Speaker 3: has never granted it when it comes to the death penalty,

702
00:38:21,320 --> 00:38:23,160
Speaker 3: like he wouldn't even like not even people were in

703
00:38:23,200 --> 00:38:25,799
Speaker 3: death row, Like he wouldn't even pardon people that were

704
00:38:25,880 --> 00:38:29,759
Speaker 3: proven innocent. And there was even someone actually who they

705
00:38:29,800 --> 00:38:33,040
Speaker 3: found who was guilty of the crime, literally serving a

706
00:38:33,120 --> 00:38:35,960
Speaker 3: sentence for that crime. He wouldn't even pardon those people

707
00:38:36,280 --> 00:38:38,759
Speaker 3: and they were black. But you know, you know where

708
00:38:38,760 --> 00:38:40,600
Speaker 3: this is going. You know who he does give pardons

709
00:38:40,600 --> 00:38:44,000
Speaker 3: to a white cop who murdered a black man in

710
00:38:44,040 --> 00:38:48,080
Speaker 3: twenty nineteen and one of our favorite characters from the

711
00:38:48,120 --> 00:38:52,080
Speaker 3: summer of twenty twenty, the mccloskey's like the white couple

712
00:38:52,440 --> 00:38:55,359
Speaker 3: on the log with the guns who pulled guns on

713
00:38:55,440 --> 00:38:57,760
Speaker 3: like those protesters outside of their house, and the woman

714
00:38:57,800 --> 00:39:00,600
Speaker 3: who was just very loosely holding up pistol.

715
00:39:00,760 --> 00:39:05,160
Speaker 1: Yeah, yeah, they they received part like a like a

716
00:39:05,200 --> 00:39:09,160
Speaker 1: fifth glass of Chardonay, just like loosely in her hand.

717
00:39:09,080 --> 00:39:11,759
Speaker 3: Just arrating it. Yeah, just got it, just to let

718
00:39:11,800 --> 00:39:14,640
Speaker 3: it breathe a little bit. I gotta let this thing breathe. So,

719
00:39:15,000 --> 00:39:17,759
Speaker 3: I mean, oddly enough, then this is why this sort

720
00:39:17,800 --> 00:39:20,280
Speaker 3: of relates to the election too, is the death penalty

721
00:39:20,360 --> 00:39:23,480
Speaker 3: was another one of those planks of the Democrats platform

722
00:39:23,520 --> 00:39:26,640
Speaker 3: that just went poof this year. Like in twenty sixteen,

723
00:39:26,680 --> 00:39:29,560
Speaker 3: the platform said we will abolish the death penalty, which

724
00:39:29,600 --> 00:39:32,840
Speaker 3: has proven to be a cruel and unusual form of punishment.

725
00:39:33,640 --> 00:39:35,240
Speaker 1: And you're like, what the fuck happened?

726
00:39:35,360 --> 00:39:38,080
Speaker 3: Like Joe Biden even ran on being against the death

727
00:39:38,080 --> 00:39:41,560
Speaker 3: penalty in twenty twenty, but now it's completely different. And

728
00:39:42,040 --> 00:39:44,919
Speaker 3: Kamala Harris, to her credit, actually is a decent track

729
00:39:45,000 --> 00:39:47,400
Speaker 3: record on this too, Like as Da, She's like, I

730
00:39:47,400 --> 00:39:50,560
Speaker 3: will not seek the death penalty, and she didn't. Her

731
00:39:50,640 --> 00:39:53,960
Speaker 3: twenty nineteen campaign website said, quote, Kamala believes the death

732
00:39:54,000 --> 00:39:57,680
Speaker 3: penalty is immoral, discriminatory, ineffective, and a gross misuse of

733
00:39:57,760 --> 00:40:02,840
Speaker 3: taxpayer taxpayer dollars. So like, recently journalists reached out to

734
00:40:02,840 --> 00:40:05,560
Speaker 3: the campaign and asked about their like their her specific

735
00:40:05,560 --> 00:40:08,640
Speaker 3: stance and the death penalty. They got no response at all,

736
00:40:09,160 --> 00:40:11,719
Speaker 3: And it's just like, what, like, you know, yeah again,

737
00:40:11,840 --> 00:40:14,400
Speaker 3: Joe Biden ran didn't seem risky for Joe Biden.

738
00:40:14,480 --> 00:40:15,600
Speaker 1: He won in twenty twenty.

739
00:40:15,640 --> 00:40:18,320
Speaker 3: I mean it was close, but was was it down

740
00:40:18,360 --> 00:40:21,399
Speaker 3: to the pro death penalty vote that.

741
00:40:21,440 --> 00:40:22,560
Speaker 1: Would have swayed things?

742
00:40:22,800 --> 00:40:25,160
Speaker 3: And I think that's just kind of like another odd thing,

743
00:40:25,200 --> 00:40:28,640
Speaker 3: an example of like shifting to this like courting a

744
00:40:28,719 --> 00:40:31,040
Speaker 3: voter that I'm I'm like, who is this voter you're

745
00:40:31,040 --> 00:40:33,719
Speaker 3: trying to court by like removing this plank of the

746
00:40:33,719 --> 00:40:35,920
Speaker 3: Democratic platform because again.

747
00:40:36,000 --> 00:40:40,160
Speaker 1: Your positions, like that changing your positions doesn't help you,

748
00:40:40,320 --> 00:40:42,919
Speaker 1: even though I like, I get the logic, it's been

749
00:40:43,040 --> 00:40:46,880
Speaker 1: the logic of the mainstream Democratic Party since the Clintons,

750
00:40:47,239 --> 00:40:50,560
Speaker 1: but it doesn't work because it makes it seem like

751
00:40:50,680 --> 00:40:55,200
Speaker 1: you don't have the courage of your convictions or any

752
00:40:55,719 --> 00:40:59,440
Speaker 1: like any strong beliefs like which seems to be what

753
00:41:00,080 --> 00:41:03,400
Speaker 1: people respond to. They want to have a sense of

754
00:41:03,440 --> 00:41:05,320
Speaker 1: like who you are on these things.

755
00:41:05,719 --> 00:41:07,839
Speaker 5: But I was really curious about this because I had

756
00:41:07,840 --> 00:41:09,840
Speaker 5: looked up I wanted to see if the death penalty

757
00:41:09,880 --> 00:41:12,959
Speaker 5: had gotten more popular or why they would go away

758
00:41:12,960 --> 00:41:16,560
Speaker 5: from being anti. And it's really interesting because back as

759
00:41:16,600 --> 00:41:19,719
Speaker 5: recently as the mid nineties, the death penalty on. They

760
00:41:19,719 --> 00:41:22,399
Speaker 5: have like Gallup polls in this In nineteen ninety four,

761
00:41:23,080 --> 00:41:26,840
Speaker 5: eighty percent of Americans were in favor of the death penalty.

762
00:41:26,840 --> 00:41:29,440
Speaker 5: That was like at the apex of the crime, the

763
00:41:29,560 --> 00:41:32,239
Speaker 5: nineties crime epidemic and the crack epidemic and all of

764
00:41:32,239 --> 00:41:36,600
Speaker 5: that stuff. And it has been slowly declining ever since

765
00:41:36,680 --> 00:41:38,919
Speaker 5: the point now it's like fifty three to forty four,

766
00:41:39,000 --> 00:41:42,359
Speaker 5: fifty three in favor forty four percent against. The death

767
00:41:42,400 --> 00:41:45,839
Speaker 5: penalty is less popular now than pretty much at any

768
00:41:45,880 --> 00:41:50,839
Speaker 5: point in history in terms. So and we don't you know,

769
00:41:50,880 --> 00:41:53,600
Speaker 5: there's like camp the states still have the death penalty,

770
00:41:54,080 --> 00:41:56,680
Speaker 5: but a lot of those that do have gone into

771
00:41:56,719 --> 00:42:01,279
Speaker 5: a moratorium. They haven't executed anybody in decades. Nationwide, we

772
00:42:01,360 --> 00:42:05,440
Speaker 5: executed twenty four people last year, which is a lot

773
00:42:05,640 --> 00:42:08,400
Speaker 5: if you think in terms of the state killing people,

774
00:42:08,440 --> 00:42:10,279
Speaker 5: but in terms of the total number of people we

775
00:42:10,360 --> 00:42:12,960
Speaker 5: have like in prison and on death row, it's not

776
00:42:12,960 --> 00:42:16,440
Speaker 5: that many. We don't like to do it very often.

777
00:42:16,480 --> 00:42:19,920
Speaker 5: The federal government hadn't executed anybody in almost two decades

778
00:42:19,960 --> 00:42:22,640
Speaker 5: prior to Trump becoming president, and then they turned that

779
00:42:22,840 --> 00:42:26,440
Speaker 5: back on. But I don't know, it's interesting because it

780
00:42:26,440 --> 00:42:28,719
Speaker 5: feels like one of those things that has just been

781
00:42:28,800 --> 00:42:33,080
Speaker 5: kind of fading from the system anyway. So to now

782
00:42:33,239 --> 00:42:35,880
Speaker 5: be afraid of coming out as being anti death penalty

783
00:42:35,880 --> 00:42:38,880
Speaker 5: when this seems like the safest time to do it,

784
00:42:38,920 --> 00:42:40,840
Speaker 5: I don't know that I get.

785
00:42:40,640 --> 00:42:42,759
Speaker 3: It well, especially on the back of this story, Like

786
00:42:42,800 --> 00:42:44,719
Speaker 3: you can be like this is why we need to

787
00:42:44,760 --> 00:42:47,480
Speaker 3: rethink this, like we're just putting people to death, or

788
00:42:47,480 --> 00:42:49,960
Speaker 3: even the prosecution is like I have we got serious

789
00:42:50,000 --> 00:42:53,440
Speaker 3: doubts about this conviction honestly, like that that we're still

790
00:42:53,760 --> 00:42:57,040
Speaker 3: moving forward with this, And you know, Hillary good Friend

791
00:42:57,080 --> 00:42:59,480
Speaker 3: and Jacobin like raised the point in terms of how

792
00:42:59,520 --> 00:43:02,560
Speaker 3: Democrats this was specific to immigration, how like they are

793
00:43:02,600 --> 00:43:05,399
Speaker 3: now sounding pretty similar to Republicans, Like if you look

794
00:43:05,400 --> 00:43:08,200
Speaker 3: at the ads that the Harris campaign is taking out

795
00:43:08,280 --> 00:43:10,880
Speaker 3: in like Arizona at there sort of she's like she

796
00:43:11,080 --> 00:43:14,400
Speaker 3: was a border state DA and she knows how to

797
00:43:14,400 --> 00:43:17,960
Speaker 3: be tough on the border and like illegal immigration, and

798
00:43:18,000 --> 00:43:21,080
Speaker 3: it's basically just echoing very similar rhetoric in terms of

799
00:43:21,120 --> 00:43:24,080
Speaker 3: like the we have to secure the border from immigrants

800
00:43:24,480 --> 00:43:27,480
Speaker 3: rhetoric that comes out of Republicans, and like she's sort

801
00:43:27,520 --> 00:43:29,640
Speaker 3: of positive. She's like, if voters are attracted by like

802
00:43:29,680 --> 00:43:32,680
Speaker 3: a candidate like that stands for the corolest punishments, Like

803
00:43:32,719 --> 00:43:35,880
Speaker 3: why why would they settle for second best? Especially when

804
00:43:35,920 --> 00:43:37,759
Speaker 3: you have Trump who's like, I'm going to expand the

805
00:43:37,760 --> 00:43:41,000
Speaker 3: death penalty to fucking haters and drug deal like anybody.

806
00:43:41,480 --> 00:43:44,600
Speaker 3: And it's just like what I'm I'm just fail again

807
00:43:44,640 --> 00:43:48,440
Speaker 3: to understand, like this, it's it's fine, why remove that?

808
00:43:48,880 --> 00:43:52,760
Speaker 3: Just just keep You're like, to Jason's point, their support

809
00:43:52,760 --> 00:43:54,480
Speaker 3: for this is dwindling, and I get that it's a

810
00:43:54,520 --> 00:43:56,799
Speaker 3: small majority, but this doesn't seem like the kind of

811
00:43:56,880 --> 00:44:00,600
Speaker 3: issue voter. They're like, we gotta really be careful with

812
00:44:00,680 --> 00:44:02,640
Speaker 3: the death penalty. And I get why they would be

813
00:44:02,640 --> 00:44:05,000
Speaker 3: with like things like fracking or whatever that's more top

814
00:44:05,040 --> 00:44:06,839
Speaker 3: of mind, but the death penalty just seems like such

815
00:44:06,880 --> 00:44:10,319
Speaker 3: an odd thing to just sort of just ignore now,

816
00:44:10,480 --> 00:44:14,160
Speaker 3: given again that we're seeing this is something that affects

817
00:44:14,400 --> 00:44:16,000
Speaker 3: the community that Takamma.

818
00:44:15,640 --> 00:44:17,279
Speaker 1: Herself is like a part of.

819
00:44:17,480 --> 00:44:19,279
Speaker 3: So I feel like this should be an afterthought to

820
00:44:19,280 --> 00:44:20,920
Speaker 3: be like yeah, man, and fuck the death penalty too,

821
00:44:20,960 --> 00:44:21,960
Speaker 3: Like that's it is what it is.

822
00:44:22,160 --> 00:44:25,400
Speaker 1: I think it's because of that, Like I think they

823
00:44:25,640 --> 00:44:29,399
Speaker 1: would say, like they're playing defense against like Willie Horton shit,

824
00:44:29,680 --> 00:44:32,320
Speaker 1: and like a good portion of the voting population is

825
00:44:32,440 --> 00:44:34,879
Speaker 1: racist and she's a woman of color and they need

826
00:44:34,920 --> 00:44:38,839
Speaker 1: to like counterbalance that and like do this like you know,

827
00:44:39,080 --> 00:44:45,160
Speaker 1: strategic triangulation so that she is like protected against attacks

828
00:44:45,200 --> 00:44:50,080
Speaker 1: on that. But it's just it takes the humanity out

829
00:44:50,120 --> 00:44:53,160
Speaker 1: of it. It's not an effective way to run a campaign.

830
00:44:53,400 --> 00:44:57,040
Speaker 1: And we've seen that year after year with the Democratic Party.

831
00:44:57,600 --> 00:45:00,239
Speaker 5: And while I've seen people tons of people run being

832
00:45:00,239 --> 00:45:03,719
Speaker 5: tough on crime, I can't remember anybody running specifically on

833
00:45:04,040 --> 00:45:06,480
Speaker 5: more death penalty. The death penalty is great, Like it

834
00:45:06,520 --> 00:45:10,200
Speaker 5: doesn't the pro death penalty side doesn't have like an

835
00:45:10,320 --> 00:45:13,439
Speaker 5: anti abortion like an equivalent of that movement where there's

836
00:45:13,480 --> 00:45:16,560
Speaker 5: like a death penalty voter other than you have tons

837
00:45:16,600 --> 00:45:19,200
Speaker 5: of anti death penalty voters. But in terms of there

838
00:45:19,200 --> 00:45:22,520
Speaker 5: being like pro I don't know. I don't see people

839
00:45:22,560 --> 00:45:25,680
Speaker 5: taking to the streets like demanding this guy being killed

840
00:45:25,719 --> 00:45:30,640
Speaker 5: despite you know, everything about the case being shaky. I

841
00:45:30,680 --> 00:45:33,120
Speaker 5: don't know. I don't get it. But also a side note,

842
00:45:33,920 --> 00:45:36,040
Speaker 5: if you're a fan of true crime and you read

843
00:45:36,120 --> 00:45:38,160
Speaker 5: a lot or listen to a lot of podcasts about

844
00:45:38,400 --> 00:45:43,880
Speaker 5: famous murder cases, so many trials are just like this, right, yeah,

845
00:45:43,920 --> 00:45:47,759
Speaker 5: where the only testimony is from somebody who got their

846
00:45:47,800 --> 00:45:51,600
Speaker 5: own sentence reduced, where the DNA stuff is like kind

847
00:45:51,600 --> 00:45:53,840
Speaker 5: of shaky and it looked like it's actually kind of

848
00:45:53,840 --> 00:45:57,000
Speaker 5: matched somebody who wasn't there and actually his wasn't technically

849
00:45:57,160 --> 00:46:00,600
Speaker 5: at the scene, and the one person who thought they

850
00:46:01,239 --> 00:46:04,680
Speaker 5: saw him at the scene their testimony actually contradicted. That

851
00:46:04,920 --> 00:46:08,439
Speaker 5: is common. Yeah, and you see something like we group

852
00:46:08,520 --> 00:46:10,840
Speaker 5: people like my age grew up with the OJ case

853
00:46:11,040 --> 00:46:14,040
Speaker 5: back in the nineties and watched when you actually have

854
00:46:14,239 --> 00:46:17,319
Speaker 5: high class lawyers who can pick through every little bit

855
00:46:17,440 --> 00:46:19,520
Speaker 5: of the house of cards of evidence and to a

856
00:46:19,600 --> 00:46:22,239
Speaker 5: jury can make it look like, yeah, this is a

857
00:46:22,239 --> 00:46:25,759
Speaker 5: bunch of circumstantial crap. They've cobbled together. Nobody saw them there.

858
00:46:25,800 --> 00:46:28,600
Speaker 5: We don't have a murder weapon, you don't have a

859
00:46:28,600 --> 00:46:32,399
Speaker 5: direct witness. Now the rest of it's all questionable. It's like, hey,

860
00:46:32,520 --> 00:46:36,320
Speaker 5: that's every case. It is so rare that they've got

861
00:46:36,560 --> 00:46:38,960
Speaker 5: a guy on camera doing it or whatever, and so

862
00:46:39,000 --> 00:46:40,880
Speaker 5: they piece together a case. I'm sure they get it

863
00:46:40,960 --> 00:46:43,759
Speaker 5: right most of the time because a lot of times

864
00:46:43,760 --> 00:46:46,360
Speaker 5: it is obvious, you know, husband kills his wife. Whatever,

865
00:46:46,400 --> 00:46:49,160
Speaker 5: there's not you're gonna claim that, like, no, actually a

866
00:46:49,200 --> 00:46:51,880
Speaker 5: serial killer broke in and then left no traces behind.

867
00:46:51,920 --> 00:46:55,880
Speaker 5: But in still many cases like this, they've pieced together

868
00:46:55,920 --> 00:46:58,280
Speaker 5: what looks like a strong case, but you start pulling

869
00:46:58,320 --> 00:47:01,640
Speaker 5: at any of the individual thread it's so shaky.

870
00:47:02,080 --> 00:47:04,160
Speaker 3: Yeah, And I mean like whenever we've had you know,

871
00:47:04,200 --> 00:47:07,200
Speaker 3: like public defenders on as guests too, that we always

872
00:47:07,280 --> 00:47:10,040
Speaker 3: are reminded of how like, you know, when the prosecutors

873
00:47:10,040 --> 00:47:11,839
Speaker 3: they think they have someone or the cops think they

874
00:47:11,840 --> 00:47:13,640
Speaker 3: have someone, like they just got to go all in

875
00:47:13,680 --> 00:47:15,640
Speaker 3: on it. Or other times, just like in the process

876
00:47:15,640 --> 00:47:18,719
Speaker 3: of interrogating people, it's like wear them the fuck down

877
00:47:18,840 --> 00:47:21,759
Speaker 3: until they kind of break and admit maybe they had

878
00:47:21,800 --> 00:47:22,920
Speaker 3: something to do with it. And at least we can

879
00:47:23,000 --> 00:47:26,520
Speaker 3: run with that. But yeah, again, it's like it's just odd.

880
00:47:26,640 --> 00:47:28,879
Speaker 3: It feels like low hanging fruit or just the very

881
00:47:28,920 --> 00:47:33,200
Speaker 3: least something that wasn't controversial. But I think because everything

882
00:47:33,239 --> 00:47:36,640
Speaker 3: needs to be, No, this person isn't a liberal, even

883
00:47:36,680 --> 00:47:39,399
Speaker 3: though they're running as a Democrat, like they're actually tough

884
00:47:39,440 --> 00:47:41,799
Speaker 3: on crime in the border. You just get this like

885
00:47:41,840 --> 00:47:44,800
Speaker 3: weird dissonance that I think for even like like longtime

886
00:47:44,880 --> 00:47:48,520
Speaker 3: Democratic voters like wait, what the what what what is

887
00:47:49,040 --> 00:47:51,399
Speaker 3: this the Republican Party or what the fuck is going on?

888
00:47:51,800 --> 00:47:54,680
Speaker 3: But again, this this is clearly the strategy for that

889
00:47:54,880 --> 00:47:57,040
Speaker 3: campaign to try and figure out how do we pick

890
00:47:57,080 --> 00:47:59,480
Speaker 3: off the most people in the middle to try and

891
00:47:59,520 --> 00:48:03,840
Speaker 3: deny M a win. And I mean, the polling is

892
00:48:04,000 --> 00:48:07,640
Speaker 3: it's it's it seems very close. But we again, we

893
00:48:07,760 --> 00:48:09,879
Speaker 3: will see where that goes. But I just don't it's

894
00:48:09,920 --> 00:48:12,719
Speaker 3: just a really weird thing to sort of like shy

895
00:48:12,800 --> 00:48:15,600
Speaker 3: away from. It doesn't seem like I get why you'd

896
00:48:15,680 --> 00:48:18,359
Speaker 3: probably be like I don't know about universal healthcare because

897
00:48:18,360 --> 00:48:21,279
Speaker 3: they're gonna say I'm a socialist or whatever. But the

898
00:48:21,320 --> 00:48:25,440
Speaker 3: death penalty is like again but just it's it's fucking stupid.

899
00:48:25,480 --> 00:48:26,640
Speaker 3: And we don't need it anymore.

900
00:48:26,960 --> 00:48:30,200
Speaker 1: Yeah, I don't appreciate you disparaging the al theory from

901
00:48:30,239 --> 00:48:33,240
Speaker 1: the staircase, but I agree with everything else he said.

902
00:48:33,840 --> 00:48:46,799
Speaker 1: Let's take a quick break, we'll be right back, and

903
00:48:46,960 --> 00:48:51,200
Speaker 1: we're back. We're back, And James Cameron just made headlines.

904
00:48:51,560 --> 00:48:55,560
Speaker 1: And this time it's not for announcing like the fourteenth

905
00:48:55,640 --> 00:49:01,120
Speaker 1: Avatar film. This time he is joining the board equally dispiriting,

906
00:49:01,239 --> 00:49:04,759
Speaker 1: he's joining the board of directors for Stability AI. By

907
00:49:04,800 --> 00:49:07,560
Speaker 1: the way, I enjoyed both Avatar movies. I don't know

908
00:49:07,560 --> 00:49:11,000
Speaker 1: why I turned into Trump there, but I wish and

909
00:49:11,080 --> 00:49:15,160
Speaker 1: I think he is making a different film that I'll

910
00:49:15,200 --> 00:49:17,440
Speaker 1: look up what the other film is. But this is

911
00:49:17,600 --> 00:49:20,600
Speaker 1: just a bummer because you know, he's always been at

912
00:49:20,600 --> 00:49:24,920
Speaker 1: the forefront of special effects. And the board that he's

913
00:49:25,040 --> 00:49:29,279
Speaker 1: joining is the AI firm that developed the Stable Diffusion

914
00:49:29,440 --> 00:49:34,319
Speaker 1: Text to Image generative AI model, which is where like

915
00:49:34,400 --> 00:49:39,920
Speaker 1: a image and video focused model that I think creates

916
00:49:39,960 --> 00:49:44,360
Speaker 1: like some of the wild like this is AI videos

917
00:49:44,440 --> 00:49:47,799
Speaker 1: that look like an acid trip, like that you put

918
00:49:47,960 --> 00:49:51,640
Speaker 1: a camera on someone's brain during an acid trip. What's

919
00:49:51,719 --> 00:49:54,680
Speaker 1: the what does he gain from this exactly?

920
00:49:54,760 --> 00:49:57,080
Speaker 3: I mean, like I know, he's always into like technology

921
00:49:57,200 --> 00:49:59,880
Speaker 3: in terms of filmmaking like that. He always prides himself

922
00:50:00,120 --> 00:50:01,879
Speaker 3: being on the cutting edge of stuff like that. But

923
00:50:02,000 --> 00:50:06,000
Speaker 3: like with this, is he of the cool version, like

924
00:50:06,080 --> 00:50:08,520
Speaker 3: he'll bring it down from the inside.

925
00:50:09,239 --> 00:50:13,520
Speaker 1: But he's always been more acutely aware of anyone of

926
00:50:13,600 --> 00:50:16,000
Speaker 1: the dangers of artificial intelligence.

927
00:50:16,320 --> 00:50:20,239
Speaker 3: So right, yeah, exactly, i'man like a cautionary tale. All

928
00:50:20,280 --> 00:50:21,400
Speaker 3: gave us a terminator.

929
00:50:22,440 --> 00:50:24,960
Speaker 1: But maybe if we take a new look at that

930
00:50:25,040 --> 00:50:27,799
Speaker 1: movie and it's secretly like, oh I want I want

931
00:50:27,840 --> 00:50:31,000
Speaker 1: a robot that would be so sick, is like the

932
00:50:31,000 --> 00:50:32,240
Speaker 1: thesis of that movie.

933
00:50:32,719 --> 00:50:36,800
Speaker 5: His quote here is saying that the intersection of generative

934
00:50:36,800 --> 00:50:40,120
Speaker 5: AI and CGI image creation maybe the next wave. That

935
00:50:40,239 --> 00:50:43,200
Speaker 5: means the ability to effects with that having to pay

936
00:50:43,920 --> 00:50:45,680
Speaker 5: people to do the effects.

937
00:50:46,440 --> 00:50:50,440
Speaker 1: Oh he likes money, Okay.

938
00:50:50,800 --> 00:50:53,960
Speaker 5: So it will be phrased as to make the process

939
00:50:54,040 --> 00:50:58,400
Speaker 5: more efficient, right whatever, So you can just have a

940
00:50:58,440 --> 00:51:00,600
Speaker 5: server room and a piece of software that instead of

941
00:51:00,600 --> 00:51:03,839
Speaker 5: because I remember back in Titanic that was nineteen ninety seven,

942
00:51:03,880 --> 00:51:06,000
Speaker 5: the movie came out, you know, shot ninety five ninety six.

943
00:51:06,040 --> 00:51:08,319
Speaker 5: When they were doing all those effects, that stuff was

944
00:51:08,360 --> 00:51:11,440
Speaker 5: rendered frame by frame, like those water droplets that were

945
00:51:11,440 --> 00:51:13,399
Speaker 5: coming off the hull of the boat, that was all

946
00:51:13,520 --> 00:51:17,080
Speaker 5: cgi and that was a person painting those in So

947
00:51:17,239 --> 00:51:19,680
Speaker 5: I do not doubt that when you know the budget

948
00:51:19,680 --> 00:51:22,160
Speaker 5: of that film, a lot of that went to artist,

949
00:51:22,239 --> 00:51:26,279
Speaker 5: talented artists spending many thousands of hours doing work by

950
00:51:26,360 --> 00:51:29,000
Speaker 5: hand to make it look just right, because it was

951
00:51:29,040 --> 00:51:31,040
Speaker 5: hard to beat the human eye when it comes to

952
00:51:31,120 --> 00:51:34,719
Speaker 5: making something like that look good. But if that was

953
00:51:34,800 --> 00:51:36,920
Speaker 5: just a piece of software that you could tell it

954
00:51:37,400 --> 00:51:39,680
Speaker 5: make water run off the side of this thing, and

955
00:51:39,719 --> 00:51:42,759
Speaker 5: then it runs overnight and then boom, there you go,

956
00:51:42,840 --> 00:51:45,040
Speaker 5: and you did not have to pay a single person,

957
00:51:46,640 --> 00:51:49,360
Speaker 5: I don't know. I guess like that's how all automation works.

958
00:51:49,400 --> 00:51:52,520
Speaker 5: But to have a creative person want to bring that

959
00:51:52,560 --> 00:51:56,880
Speaker 5: to the creative world, I don't know.

960
00:51:57,840 --> 00:52:01,000
Speaker 3: I mean, you're great when you make millions of dollars,

961
00:52:01,080 --> 00:52:02,960
Speaker 3: I guess that's just what will happen to you, you know,

962
00:52:03,040 --> 00:52:04,839
Speaker 3: like we're just sort of like I can imagine too,

963
00:52:05,000 --> 00:52:07,080
Speaker 3: is like how much is it gonna cost? All I

964
00:52:07,120 --> 00:52:09,360
Speaker 3: want is the fucking guy to fall off the boat,

965
00:52:09,640 --> 00:52:12,279
Speaker 3: hit the big propeller blade and then flop.

966
00:52:11,920 --> 00:52:12,839
Speaker 5: Into the fucking water.

967
00:52:13,560 --> 00:52:16,799
Speaker 1: What fifty thousand dollars just for that. Now fuck this.

968
00:52:17,000 --> 00:52:19,240
Speaker 1: And then this is where like I'll drop a fucking

969
00:52:19,239 --> 00:52:22,360
Speaker 1: guy off of the drop a guy off the Titanic

970
00:52:22,880 --> 00:52:24,680
Speaker 1: shot is the practical set still up?

971
00:52:24,719 --> 00:52:27,120
Speaker 3: Do we still have the setup in Mexico? Fuck it, dude,

972
00:52:27,160 --> 00:52:29,200
Speaker 3: I'll do it. Just fucking drop. I'll fucking get the

973
00:52:29,200 --> 00:52:32,279
Speaker 3: propeller blade. Man, I don't want to fucking pay that. Yeah, man, yeah,

974
00:52:32,320 --> 00:52:35,239
Speaker 3: well I need this shit, so yeah, I mean, it's

975
00:52:35,239 --> 00:52:37,600
Speaker 3: just it's a again, like to your point, like Jason's,

976
00:52:37,600 --> 00:52:40,440
Speaker 3: like when someone who values creativity and it has like

977
00:52:40,560 --> 00:52:44,120
Speaker 3: always talked about his own love of imagination and like

978
00:52:44,440 --> 00:52:47,000
Speaker 3: always exploring all the ways that you can express like

979
00:52:47,040 --> 00:52:49,840
Speaker 3: your ideas in cinema to then be like, yeah, but

980
00:52:49,880 --> 00:52:52,319
Speaker 3: that other person who's integral to that and me even

981
00:52:52,320 --> 00:52:55,360
Speaker 3: getting to where I am totally fuck that person completely

982
00:52:55,840 --> 00:52:58,520
Speaker 3: because it's too expensive, and like that's just not just

983
00:52:58,760 --> 00:52:59,840
Speaker 3: just it's just too.

984
00:52:59,719 --> 00:53:02,760
Speaker 1: Much, man, it's just slow shit down. Well, the company

985
00:53:02,840 --> 00:53:06,080
Speaker 1: is not currently building liquid metal killing machines. It is

986
00:53:06,160 --> 00:53:09,600
Speaker 1: being sued for copyright infringement and just laid off a

987
00:53:09,600 --> 00:53:13,360
Speaker 1: bunch of staff members, so they're already doing the work

988
00:53:13,400 --> 00:53:16,680
Speaker 1: that they will probably be helping James Cameron do.

989
00:53:17,239 --> 00:53:20,400
Speaker 5: Yeah, And because to be clear, the way this thing

990
00:53:20,440 --> 00:53:23,400
Speaker 5: will make special effects is you will have it scan

991
00:53:23,640 --> 00:53:28,200
Speaker 5: a bunch of existing movies, including effects humans created, and

992
00:53:28,239 --> 00:53:29,799
Speaker 5: it will say, oh, I know how to do that.

993
00:53:29,840 --> 00:53:33,279
Speaker 5: Now you need like a spaceship flying up out of water.

994
00:53:33,320 --> 00:53:36,160
Speaker 5: You eat all those water droplets like some person did

995
00:53:36,200 --> 00:53:40,640
Speaker 5: by hand when whatever movie came out fifteen years ago. Well,

996
00:53:40,640 --> 00:53:43,640
Speaker 5: guess what I've got that in the database. Could you

997
00:53:43,680 --> 00:53:46,200
Speaker 5: imagine scanned that movie right?

998
00:53:46,320 --> 00:53:46,560
Speaker 1: Right?

999
00:53:46,920 --> 00:53:49,880
Speaker 3: And like movies just start looking like sampled music tracks

1000
00:53:49,880 --> 00:53:51,560
Speaker 3: and stuff where you're like, bro, I'm pretty sure that's

1001
00:53:51,600 --> 00:53:54,640
Speaker 3: the wave from the Perfect Storm in this movie, Like

1002
00:53:54,680 --> 00:53:56,680
Speaker 3: what the fuck? And like, yeah, do you see that

1003
00:53:56,719 --> 00:53:58,440
Speaker 3: guy fall off the boat? I think that was the

1004
00:53:58,480 --> 00:54:02,640
Speaker 3: propeller guy from Titanic. They just recontextualize it for this film.

1005
00:54:02,680 --> 00:54:05,840
Speaker 5: It's just there, like the will just extreme. Yes, Like

1006
00:54:05,920 --> 00:54:08,360
Speaker 5: that's the explosion. Look, they used it. They used the

1007
00:54:08,400 --> 00:54:09,880
Speaker 5: explosion from Armygeddon.

1008
00:54:09,960 --> 00:54:12,760
Speaker 1: They it's a guy, but they have to like change

1009
00:54:12,760 --> 00:54:14,640
Speaker 1: things so like it's a guy running down the street,

1010
00:54:14,719 --> 00:54:17,160
Speaker 1: but they're using the guy falling off the Titanic and

1011
00:54:17,160 --> 00:54:19,040
Speaker 1: they're like and then he hits this thing and starts

1012
00:54:19,040 --> 00:54:20,799
Speaker 1: spinning for something different plane.

1013
00:54:20,840 --> 00:54:23,960
Speaker 3: Yeah, just a different gravitational plane. Full You're like, is

1014
00:54:23,960 --> 00:54:25,080
Speaker 3: that physically possible?

1015
00:54:25,160 --> 00:54:26,640
Speaker 1: Yeah, he's being blown down the street. It was a

1016
00:54:26,640 --> 00:54:29,640
Speaker 1: big wind. They just have like a voiceover, guy coming,

1017
00:54:30,880 --> 00:54:32,120
Speaker 1: Can I Can.

1018
00:54:32,000 --> 00:54:34,879
Speaker 5: I ask you guys a question because you you are

1019
00:54:34,920 --> 00:54:37,640
Speaker 5: obviously covering the news every single day, You've probably done

1020
00:54:37,760 --> 00:54:40,560
Speaker 5: many stories about AI and stuff like that. Yeah, why

1021
00:54:40,680 --> 00:54:43,000
Speaker 5: is it that in the cultural imagination? Why is it

1022
00:54:43,040 --> 00:54:46,040
Speaker 5: then the headlines all of the examples of AI, it's

1023
00:54:46,160 --> 00:54:49,960
Speaker 5: all this nonsense. It's it can create a very bad

1024
00:54:50,000 --> 00:54:52,600
Speaker 5: photograph with too many fingers. It can create a very

1025
00:54:52,640 --> 00:54:57,040
Speaker 5: trippy video that has the worst uncanny valley thing you've

1026
00:54:57,080 --> 00:55:00,480
Speaker 5: ever seen in your life. We think that maybe someday

1027
00:55:00,560 --> 00:55:02,759
Speaker 5: it will make movies for you, So that why is

1028
00:55:02,800 --> 00:55:05,240
Speaker 5: it all the one thing none of us want AI

1029
00:55:05,320 --> 00:55:08,640
Speaker 5: to do instead of Hey, we think in the future,

1030
00:55:08,680 --> 00:55:11,239
Speaker 5: it can diagnose cancer faster than a doctor, can't. We

1031
00:55:11,280 --> 00:55:14,120
Speaker 5: think in the future, it can you know, help genetically

1032
00:55:14,200 --> 00:55:17,520
Speaker 5: engineer crops. It can survive drought and climate change. Like,

1033
00:55:17,640 --> 00:55:21,360
Speaker 5: why is there like an image issue or a marketing

1034
00:55:21,400 --> 00:55:24,080
Speaker 5: issue on the side of these AI people, or is

1035
00:55:24,080 --> 00:55:26,480
Speaker 5: that really where they're putting their money right now, Like,

1036
00:55:26,600 --> 00:55:28,960
Speaker 5: is all the work actually going into all of this

1037
00:55:29,400 --> 00:55:33,720
Speaker 5: media stuff instead of like it's solving people's everyday problems

1038
00:55:33,719 --> 00:55:35,239
Speaker 5: that would get them excited about it.

1039
00:55:35,560 --> 00:55:37,480
Speaker 3: I think all this stuff is kind of part of

1040
00:55:37,520 --> 00:55:41,000
Speaker 3: like this this sort of circus aspect of it that

1041
00:55:41,120 --> 00:55:45,680
Speaker 3: keeps people like interested on a general level and be like, oh, whoa,

1042
00:55:45,680 --> 00:55:47,880
Speaker 3: it does this. It does that because it like for

1043
00:55:47,920 --> 00:55:49,840
Speaker 3: the people that they're really trying to appeal to, like

1044
00:55:50,000 --> 00:55:53,080
Speaker 3: on Wall Street, it's probably easier for them to connect

1045
00:55:53,080 --> 00:55:54,600
Speaker 3: the dots rather than like, oh, it can do really

1046
00:55:54,640 --> 00:55:58,720
Speaker 3: complex computations that could maybe like make cause breakthroughs for science.

1047
00:55:59,160 --> 00:56:03,160
Speaker 3: It's like, hey men, articles can be written quicker without people,

1048
00:56:03,360 --> 00:56:06,560
Speaker 3: or it can make a little video for your advertising company.

1049
00:56:06,800 --> 00:56:08,960
Speaker 3: But then I think what they're also showing is like

1050
00:56:09,040 --> 00:56:11,439
Speaker 3: it's they're like how it's getting better, And that's also

1051
00:56:11,480 --> 00:56:13,040
Speaker 3: part of the process. Like, look, do you remember when

1052
00:56:13,040 --> 00:56:15,879
Speaker 3: Will Smith was eating spaghetti all weird, like a couple

1053
00:56:16,000 --> 00:56:19,799
Speaker 3: months ago. Now Will Smith eats spaghetti even like a

1054
00:56:19,840 --> 00:56:20,920
Speaker 3: little less weird.

1055
00:56:21,200 --> 00:56:23,520
Speaker 1: So it's getting better, y'all. And who knows where this

1056
00:56:23,800 --> 00:56:24,840
Speaker 1: who knows what Will.

1057
00:56:24,640 --> 00:56:26,880
Speaker 3: Smith can do in the next iteration of this and

1058
00:56:26,880 --> 00:56:29,040
Speaker 3: people like, oh shit, yeah, yeah, it's getting better and

1059
00:56:29,080 --> 00:56:31,920
Speaker 3: better and better, while at the same time, like people

1060
00:56:31,960 --> 00:56:33,840
Speaker 3: on Wall Street, I'm like, dude, this it's all this

1061
00:56:33,840 --> 00:56:36,040
Speaker 3: stuff is horseshit, Like it's not even close to doing

1062
00:56:36,080 --> 00:56:38,439
Speaker 3: the kinds of things that they wanted to freak people

1063
00:56:38,520 --> 00:56:41,360
Speaker 3: out about with. It's just sort of becoming an energy

1064
00:56:41,440 --> 00:56:43,960
Speaker 3: drain and something that isn't actually creating any kind of

1065
00:56:44,000 --> 00:56:46,880
Speaker 3: financial return. So it's just I think, just all like

1066
00:56:46,960 --> 00:56:49,160
Speaker 3: spectacle at this point to try and you know, cover

1067
00:56:49,280 --> 00:56:51,400
Speaker 3: for the fact that it's it's not really doing like

1068
00:56:51,480 --> 00:56:52,600
Speaker 3: the sky neet kind of shit.

1069
00:56:52,680 --> 00:56:54,440
Speaker 1: Sam Altman wants you to think of it, Yeah, it

1070
00:56:54,520 --> 00:56:57,759
Speaker 1: can answer the question how many rs are in strawberry,

1071
00:56:57,960 --> 00:57:04,120
Speaker 1: and so instead they're putting a very sexy, exciting possibility

1072
00:57:04,280 --> 00:57:08,560
Speaker 1: on the horizon of like what it could be doing, which, again, yeah,

1073
00:57:08,600 --> 00:57:11,160
Speaker 1: to your point, nobody wants it to do that. It

1074
00:57:11,200 --> 00:57:14,080
Speaker 1: can do those scientific things. It does feel like that

1075
00:57:14,160 --> 00:57:18,160
Speaker 1: should be where they're focusing. Like the thing about figuring

1076
00:57:18,160 --> 00:57:22,080
Speaker 1: out the structure of proteins, like years before we would

1077
00:57:22,080 --> 00:57:24,160
Speaker 1: have been able to do that with just humans is

1078
00:57:24,720 --> 00:57:27,880
Speaker 1: really cool and like feels like they should just focus

1079
00:57:28,000 --> 00:57:32,880
Speaker 1: on that, but I think that idea is a little abstract.

1080
00:57:33,120 --> 00:57:36,480
Speaker 1: And then I also think because of the way money

1081
00:57:37,160 --> 00:57:40,760
Speaker 1: is spent in the entertainment industry, you can have not

1082
00:57:41,160 --> 00:57:44,040
Speaker 1: very much and get a lot of people to spend

1083
00:57:44,080 --> 00:57:46,760
Speaker 1: a lot of money, like based, you know, so they

1084
00:57:46,800 --> 00:57:51,800
Speaker 1: can just promise great things while actually having absolute bullshit

1085
00:57:51,960 --> 00:57:55,080
Speaker 1: and trick a lot of people. It's if you google

1086
00:57:55,080 --> 00:57:57,160
Speaker 1: how many ares in the word strawberry? Right now, it's

1087
00:57:57,160 --> 00:57:59,880
Speaker 1: still coming back. The word strawberry has two rs. It's

1088
00:58:00,120 --> 00:58:04,480
Speaker 1: did search over you, like even right now, it's still

1089
00:58:04,520 --> 00:58:07,160
Speaker 1: doing it. But then it's like, however, AI models can

1090
00:58:07,200 --> 00:58:10,640
Speaker 1: sometimes make mistakes when answering the question about this word,

1091
00:58:10,680 --> 00:58:12,520
Speaker 1: and then like makes an excuse and you like, then

1092
00:58:13,320 --> 00:58:15,560
Speaker 1: the fuck, dude, you can't count three rs in a word?

1093
00:58:15,920 --> 00:58:18,919
Speaker 5: Yeah, right, because it's not it's not thinking. People keep

1094
00:58:19,360 --> 00:58:23,120
Speaker 5: assuming that it is thinking. It's not. It's just predicting

1095
00:58:23,200 --> 00:58:27,360
Speaker 5: the next string of text. It's it's this is what

1096
00:58:27,400 --> 00:58:29,720
Speaker 5: I've never gotten. I realized that I am a ludite

1097
00:58:29,720 --> 00:58:33,320
Speaker 5: here when it comes to AI. But an ai has

1098
00:58:33,480 --> 00:58:37,440
Speaker 5: never lived in the world, So when an AI is

1099
00:58:37,480 --> 00:58:40,880
Speaker 5: trying to describe something to you, it has never experienced

1100
00:58:40,960 --> 00:58:45,360
Speaker 5: that thing. It's grabbing some text that doesn't mean anything

1101
00:58:45,440 --> 00:58:49,040
Speaker 5: to it and just stringing it together and maybe it

1102
00:58:49,080 --> 00:58:51,840
Speaker 5: will be it will form a coherence since maybe it won't.

1103
00:58:51,920 --> 00:58:55,240
Speaker 5: But it's you know, you can an AI can go

1104
00:58:55,360 --> 00:58:58,480
Speaker 5: find you a recipe for cornbread, because there's a million

1105
00:58:58,520 --> 00:59:00,680
Speaker 5: recipes for cornbread on the internet. They can go grab

1106
00:59:00,720 --> 00:59:04,000
Speaker 5: you one. It has never eaten corn bread. It cannot

1107
00:59:04,320 --> 00:59:06,479
Speaker 5: It cannot tell you how to improve your corn bread

1108
00:59:06,480 --> 00:59:09,040
Speaker 5: recipe because it has no concept of what that should

1109
00:59:09,040 --> 00:59:12,520
Speaker 5: taste like, or it's never touched it. It's I don't know.

1110
00:59:12,560 --> 00:59:15,000
Speaker 5: I get such a disconnect from people. It's like, well, someday,

1111
00:59:15,360 --> 00:59:17,400
Speaker 5: you know, you'll have an AI friend that can if

1112
00:59:17,400 --> 00:59:19,240
Speaker 5: your lonely can talk to It's like yeah, but it's

1113
00:59:20,120 --> 00:59:21,960
Speaker 5: you won't be able to talk to it about anything

1114
00:59:22,000 --> 00:59:26,240
Speaker 5: because it has never lived a life. If it's joking

1115
00:59:26,280 --> 00:59:28,840
Speaker 5: with you, it's just grabbing a joke it found in

1116
00:59:28,880 --> 00:59:31,560
Speaker 5: its database that somebody else told somewhere on the internet

1117
00:59:31,600 --> 00:59:33,840
Speaker 5: and it just stole it. But it can't it can't

1118
00:59:33,920 --> 00:59:37,160
Speaker 5: observe something about the world because it doesn't live in

1119
00:59:37,360 --> 00:59:40,640
Speaker 5: the world. So you're not having You're just talking to

1120
00:59:40,760 --> 00:59:41,840
Speaker 5: your yourself.

1121
00:59:42,400 --> 00:59:45,920
Speaker 1: Yeah, and we we have talked about this so frequently

1122
00:59:46,040 --> 00:59:49,600
Speaker 1: that our listeners are like, yeah, no, we guys, shut

1123
00:59:49,640 --> 00:59:50,120
Speaker 1: the fuck up.

1124
00:59:51,400 --> 00:59:53,120
Speaker 5: I do not listen to the show. Guys, Yeah I

1125
00:59:53,200 --> 00:59:53,640
Speaker 5: didn't know.

1126
00:59:53,640 --> 00:59:56,600
Speaker 1: That, and that is unacceptable. But we'll talk about that

1127
00:59:56,640 --> 01:00:00,000
Speaker 1: off Mike. But yeah, I mean we've just so if people,

1128
01:00:00,040 --> 01:00:02,520
Speaker 1: well haven't heard those episodes we've had, like people who

1129
01:00:02,560 --> 01:00:05,600
Speaker 1: aren't experts in AI come on and say the same

1130
01:00:05,640 --> 01:00:08,440
Speaker 1: thing that Jason was just saying, like, these are the

1131
01:00:08,560 --> 01:00:13,720
Speaker 1: same basic idea as the autocomplete in your phone. Just

1132
01:00:13,760 --> 01:00:16,080
Speaker 1: predicting the next word, that's all it's doing. It's just

1133
01:00:16,120 --> 01:00:19,840
Speaker 1: doing it at a higher level that requires the.

1134
01:00:20,080 --> 01:00:21,439
Speaker 5: Burning of lots of fossil fuels.

1135
01:00:21,640 --> 01:00:24,080
Speaker 3: Yeah, hey, and it's just it's it's spectacle that will

1136
01:00:24,120 --> 01:00:28,560
Speaker 3: hopefully inspire increased investment. And that's really what it's all

1137
01:00:28,560 --> 01:00:29,760
Speaker 3: boiling down to at the moment.

1138
01:00:30,120 --> 01:00:32,760
Speaker 1: I mean, Amazon named one of their companies of the

1139
01:00:32,760 --> 01:00:36,400
Speaker 1: mechanical turk, like they're they know their fucking well, they

1140
01:00:36,480 --> 01:00:39,439
Speaker 1: know their fucking well. It's a fucking guy inside. There's

1141
01:00:39,440 --> 01:00:42,200
Speaker 1: a guy in there, dumb dumbs, it's not fucking real.

1142
01:00:42,600 --> 01:00:45,160
Speaker 1: Jason Pargen as always, what a pleasure having you where

1143
01:00:45,160 --> 01:00:46,360
Speaker 1: can people find you?

1144
01:00:46,560 --> 01:00:47,120
Speaker 5: Follow you?

1145
01:00:47,840 --> 01:00:50,520
Speaker 1: Uh, and also read your new book.

1146
01:00:51,280 --> 01:00:54,160
Speaker 5: The book is called I'm Starting to worry about this

1147
01:00:54,320 --> 01:00:58,240
Speaker 5: Black Box of Doom. It is not political, but it

1148
01:00:58,360 --> 01:01:01,320
Speaker 5: is relevant. And this about a bunch of people on

1149
01:01:01,360 --> 01:01:03,840
Speaker 5: the Internet who'd think that they have gotten one of

1150
01:01:03,880 --> 01:01:06,720
Speaker 5: a domestic terror attack and they're going to try to

1151
01:01:06,760 --> 01:01:09,720
Speaker 5: stop it. But it is a bunch of strangers on

1152
01:01:09,840 --> 01:01:14,600
Speaker 5: the Internet with Internet poisoned brained uh, Internet poisoned brains,

1153
01:01:14,640 --> 01:01:16,960
Speaker 5: and it goes just as badly as you would expect.

1154
01:01:17,840 --> 01:01:20,440
Speaker 5: So yeah, that book is available now in all formats,

1155
01:01:20,440 --> 01:01:23,120
Speaker 5: including audio. I do not read the audiobook. They hired

1156
01:01:23,160 --> 01:01:24,360
Speaker 5: a professional to do that.

1157
01:01:25,760 --> 01:01:29,520
Speaker 1: And it isn't me for some reason. It's a very

1158
01:01:29,520 --> 01:01:32,120
Speaker 1: good read. Everybody shoul check it out. Is there a

1159
01:01:32,200 --> 01:01:34,440
Speaker 1: work of media, Jason that you've been enjoying.

1160
01:01:35,120 --> 01:01:38,480
Speaker 5: I've got a tweet that I like. That's from Twitter

1161
01:01:38,640 --> 01:01:44,280
Speaker 5: user PJ Evans says, Paul Thomas Anderson. Sounds like something

1162
01:01:44,320 --> 01:01:48,040
Speaker 5: your mom says to you when you're acting up. Paul

1163
01:01:48,040 --> 01:01:49,160
Speaker 5: Thomas Anderson.

1164
01:01:48,840 --> 01:01:52,800
Speaker 1: Getting here right now. Mom. That's not even my name.

1165
01:01:53,160 --> 01:01:53,760
Speaker 1: I don't give it.

1166
01:01:54,320 --> 01:01:55,440
Speaker 5: Richard, would you do?

1167
01:01:55,520 --> 01:01:56,360
Speaker 1: Dude?

1168
01:01:58,000 --> 01:01:58,240
Speaker 5: Still?

1169
01:01:58,240 --> 01:01:58,520
Speaker 1: Do that?

1170
01:01:58,600 --> 01:02:00,280
Speaker 5: Use your middle name when they're mad. I don't know

1171
01:02:00,280 --> 01:02:02,960
Speaker 5: if that's a reference, that's an old time you reference it.

1172
01:02:03,960 --> 01:02:07,080
Speaker 1: My parents definitely did it, okay, but I can't speak

1173
01:02:07,080 --> 01:02:09,880
Speaker 1: to whether parents do it anymore because I'm.

1174
01:02:09,920 --> 01:02:13,000
Speaker 3: Yeah, I think culturally specific to to do the three

1175
01:02:13,080 --> 01:02:13,760
Speaker 3: name call out.

1176
01:02:14,160 --> 01:02:17,280
Speaker 1: Yeah yeah. They suddenly start treating you like an assassin.

1177
01:02:17,440 --> 01:02:19,479
Speaker 3: Yeah yeah, Like my mom would just be like buck

1178
01:02:19,520 --> 01:02:22,400
Speaker 3: ah yeah, stupid in Japanese.

1179
01:02:22,440 --> 01:02:27,520
Speaker 1: I'm like, oh yea, yeah, what John Christopher O'Brien, what

1180
01:02:27,800 --> 01:02:29,760
Speaker 1: I knew I was. I was in some ship.

1181
01:02:29,960 --> 01:02:32,080
Speaker 3: When I heard that, I knew I was in some

1182
01:02:32,080 --> 01:02:34,320
Speaker 3: ship with my mom yelled out my social security dude,

1183
01:02:34,520 --> 01:02:37,920
Speaker 3: That's why I fucking knew all my identifying information.

1184
01:02:38,360 --> 01:02:42,640
Speaker 1: If I if I did ever assassinate any anyone, that

1185
01:02:42,680 --> 01:02:45,440
Speaker 1: would be what I'd go down as. John Christopher O'Brien,

1186
01:02:45,680 --> 01:02:48,959
Speaker 1: you know, oh right, right right, yeah, hey man, he's

1187
01:02:48,960 --> 01:02:52,600
Speaker 1: our JC man. You know, Hey, Miles, Yeah, where can

1188
01:02:52,600 --> 01:02:54,800
Speaker 1: people find you as their work media you've been enjoying?

1189
01:02:55,160 --> 01:02:56,480
Speaker 1: Uh yeah, let's see.

1190
01:02:56,760 --> 01:02:59,640
Speaker 3: I'm on Twitter and Instagram at Miles of Gray you

1191
01:02:59,680 --> 01:03:03,480
Speaker 3: can find and Jack and I on the basketball podcast.

1192
01:03:02,920 --> 01:03:04,160
Speaker 1: Miles and Jack got my boosties.

1193
01:03:04,160 --> 01:03:07,120
Speaker 3: They can find me talking about ninety day fiance on

1194
01:03:07,240 --> 01:03:08,280
Speaker 3: for twenty Day fiance.

1195
01:03:08,880 --> 01:03:12,040
Speaker 1: Uh tweet I like is from at Falca. It says, Yo,

1196
01:03:12,080 --> 01:03:13,800
Speaker 1: what's up. It's your Spotify DJ.

1197
01:03:14,360 --> 01:03:17,240
Speaker 3: Damn you got some fire taste, nef Well, let me

1198
01:03:17,280 --> 01:03:19,760
Speaker 3: put you onto something I ain't think you heard before

1199
01:03:20,240 --> 01:03:25,880
Speaker 3: now playing million Dollar Baby, the biggest hits that Spotify

1200
01:03:26,000 --> 01:03:28,680
Speaker 3: DJ is sometimes so off. I'm like, please, just I

1201
01:03:28,800 --> 01:03:31,440
Speaker 3: don't know why I aerently hit that button. I saw

1202
01:03:31,480 --> 01:03:34,040
Speaker 3: that tweet and I was unaware of this product. So

1203
01:03:34,080 --> 01:03:37,720
Speaker 3: there's a there's a an AI DJ. Oh, it's like,

1204
01:03:37,920 --> 01:03:40,400
Speaker 3: what's up, Jack, It's me your DJ. We're gonna get

1205
01:03:40,400 --> 01:03:43,040
Speaker 3: into some grooves that you were really messing with last year,

1206
01:03:43,240 --> 01:03:45,280
Speaker 3: and let's start the vibe off with one of your

1207
01:03:45,320 --> 01:03:48,680
Speaker 3: favorite artists outcast and it will do something like based

1208
01:03:48,720 --> 01:03:50,680
Speaker 3: on what you play a lot, and they're like, all right,

1209
01:03:50,760 --> 01:03:54,840
Speaker 3: let's switch gears. Here's some Vietnamese Christmas music and you're like, uh,

1210
01:03:55,080 --> 01:03:56,880
Speaker 3: all right, but I don't know if that was the

1211
01:03:57,080 --> 01:04:01,080
Speaker 3: vibe I was looking for, but cool, so yeah, but

1212
01:04:01,120 --> 01:04:01,720
Speaker 3: shout out.

1213
01:04:01,560 --> 01:04:03,960
Speaker 1: The AI DJs all around the world.

1214
01:04:03,720 --> 01:04:05,440
Speaker 3: And it's just another piece of media that I do like,

1215
01:04:05,880 --> 01:04:08,840
Speaker 3: is I'm a big fan of the game Ghost of Tsushima,

1216
01:04:09,120 --> 01:04:12,320
Speaker 3: and today there was an announcement trailer for the follow

1217
01:04:12,440 --> 01:04:14,800
Speaker 3: up called Ghost of Yote, and.

1218
01:04:14,760 --> 01:04:17,000
Speaker 1: It looks fucking really good.

1219
01:04:17,160 --> 01:04:20,520
Speaker 3: But I'm preparing myself for troll backlash because the main

1220
01:04:20,600 --> 01:04:23,520
Speaker 3: character is a woman, and inevitably people would be like,

1221
01:04:23,760 --> 01:04:26,000
Speaker 3: women can't do Samurai sword.

1222
01:04:26,720 --> 01:04:28,280
Speaker 1: But yeah, the fucking trailer looks great.

1223
01:04:28,320 --> 01:04:30,120
Speaker 3: So anyone who is a fan of Ghost of Tushima

1224
01:04:30,240 --> 01:04:32,200
Speaker 3: check that trailer out because it.

1225
01:04:32,160 --> 01:04:34,680
Speaker 1: Looks pretty cool. You can find me on Twitter at

1226
01:04:34,760 --> 01:04:39,680
Speaker 1: Jack Underscore O'Brien. Like a couple tweets, We'll just go

1227
01:04:39,760 --> 01:04:43,440
Speaker 1: with this one. Cybershell at Cybershell tweeted this section of

1228
01:04:43,520 --> 01:04:46,560
Speaker 1: Jim Carrey's Wikipedia article cracks me up. Then I'm just

1229
01:04:46,600 --> 01:04:49,520
Speaker 1: going to read a paragraph from Jim Carrey's Wikipedia article.

1230
01:04:49,800 --> 01:04:52,560
Speaker 1: In April twenty twenty two, Carrie announced that he was

1231
01:04:52,640 --> 01:04:56,480
Speaker 1: considering retirement from the film industry, explaining I have enough,

1232
01:04:56,720 --> 01:04:59,520
Speaker 1: I've done enough, I am enough. When I asked if

1233
01:04:59,520 --> 01:05:03,120
Speaker 1: he would come back, his response was, it depends if

1234
01:05:03,160 --> 01:05:06,120
Speaker 1: the Angels bring some sort of script that's written in

1235
01:05:06,160 --> 01:05:08,320
Speaker 1: gold ink that says to me that it's going to

1236
01:05:08,360 --> 01:05:11,600
Speaker 1: be really important for people to see. I might continue

1237
01:05:11,600 --> 01:05:14,920
Speaker 1: down the road, but I'm taking a break. In February

1238
01:05:14,920 --> 01:05:17,840
Speaker 1: twenty twenty four, it was announced that Carrie would reprise

1239
01:05:17,960 --> 01:05:21,000
Speaker 1: his role as Doctor Robot and Sonic the Hedgehog three

1240
01:05:22,440 --> 01:05:26,760
Speaker 1: now trailer. Yeah that was wild. Yeah. Oh my kids

1241
01:05:26,840 --> 01:05:31,160
Speaker 1: are fuck they're ready psyched for Sonic the Hedgehog three. Unfortunately.

1242
01:05:31,640 --> 01:05:34,480
Speaker 1: You can find us on Twitter at daily Zeikeeist, where

1243
01:05:34,480 --> 01:05:36,320
Speaker 1: at the Daily es i Guist on Instagram, we have

1244
01:05:36,400 --> 01:05:39,040
Speaker 1: Facebook fan page and a website, Daily zeikeist dot com,

1245
01:05:39,040 --> 01:05:42,280
Speaker 1: where we post our episodes and our foot note when

1246
01:05:42,320 --> 01:05:44,000
Speaker 1: we link off to the information that we talked about

1247
01:05:44,040 --> 01:05:46,400
Speaker 1: in today's episode, as well as a song that we

1248
01:05:46,440 --> 01:05:49,280
Speaker 1: think you might enjoy. Hey, Miles, is there a song

1249
01:05:49,320 --> 01:05:50,960
Speaker 1: that you think people might enjoy?

1250
01:05:51,040 --> 01:05:53,520
Speaker 3: Hey, it's your Spotify DJ, and I think you should

1251
01:05:53,520 --> 01:05:55,320
Speaker 3: listen to one of the biggest songs of the summer,

1252
01:05:55,400 --> 01:05:58,600
Speaker 3: million Dollar Baby by my boy Tommy Richmond. Though it's

1253
01:05:58,720 --> 01:06:00,480
Speaker 3: a song that I think we should go out on

1254
01:06:00,800 --> 01:06:03,040
Speaker 3: if you like. I was just listening to some new

1255
01:06:03,120 --> 01:06:05,040
Speaker 3: jab best who's like, you know, obviously one of the

1256
01:06:05,080 --> 01:06:08,600
Speaker 3: most like iconic beat makers from Japan and really kicked

1257
01:06:08,600 --> 01:06:11,320
Speaker 3: off like the chill beat scene like the interstitials of

1258
01:06:11,480 --> 01:06:15,640
Speaker 3: like Adult Swim. You know, Samurai Shamploo is on that soundtrack.

1259
01:06:15,800 --> 01:06:19,320
Speaker 3: And there's another Japanese producer I stumbled upon called Pigeon

1260
01:06:19,400 --> 01:06:24,080
Speaker 3: Dust and also has a very like similar vibe which

1261
01:06:24,120 --> 01:06:28,160
Speaker 3: is really like enjoyable, jazzy sort of sample beats, easy

1262
01:06:28,200 --> 01:06:30,520
Speaker 3: to listen to. It's called nothing but Jazz Loops and

1263
01:06:30,760 --> 01:06:32,320
Speaker 3: artist is Pigeon Dust.

1264
01:06:32,720 --> 01:06:34,960
Speaker 1: All right, we will. I don't I don't like the

1265
01:06:35,040 --> 01:06:37,280
Speaker 1: idea of pigeon dust because I've been hails fuite a

1266
01:06:37,280 --> 01:06:39,720
Speaker 1: bit of it living in New York City. But yeah,

1267
01:06:40,360 --> 01:06:45,840
Speaker 1: pigeon dander, so anyways, but go listen to that and

1268
01:06:46,160 --> 01:06:48,840
Speaker 1: enjoy it. The Daily zeitgeis is the production of iHeartRadio.

1269
01:06:48,880 --> 01:06:51,480
Speaker 1: For more podcasts from my heart Radio, visit the iHeartRadio app,

1270
01:06:51,520 --> 01:06:53,680
Speaker 1: Apple podcast, or wherever you listen to your favorite show.

1271
01:06:53,840 --> 01:06:56,840
Speaker 1: That's gonna do it for us this morning. We're back

1272
01:06:56,880 --> 01:06:59,240
Speaker 1: this afternoon to tell you what is trending, and we'll

1273
01:06:59,240 --> 01:07:01,240
Speaker 1: talk to you all then five