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Speaker 1: Pushkin, Welcome back to Risky Business, a show about making

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Speaker 1: better decisions. I'm Maria Kannakova and I'm Nate.

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Speaker 2: Silver today on the show. I mean, we have we

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Speaker 2: have some news.

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Speaker 3: It's not news that you'll be doing cartwheel Silver if

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Speaker 3: you're a loyal fan of this show, but yeah, this

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Speaker 3: is the last.

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Speaker 2: Episode of Risky Business. That's the news.

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Speaker 1: Yeah, that's the news. We have absolutely loved the last

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Speaker 1: few years with you guys and Pushkin and iHeart and

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Speaker 1: we hope you've enjoyed it as well. And we are

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Speaker 1: you know, we're both really excited to see what comes next.

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Speaker 1: You know where to follow us. We're both very easy

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Speaker 1: to reach. We both have substacks the Leap for me

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Speaker 1: and Silver Atend for Nate, where you can share feedback

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Speaker 1: about Risky Business, but also where we will be making

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Speaker 1: future announcements about where we head to next. So if

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Speaker 1: you've been a loyal listener, we hope you will follow

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Speaker 1: us along on the next stage of our journey. And

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Speaker 1: you know, we'd love to Nate. I think before we

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Speaker 1: get into the show for this final week, which will

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Speaker 1: include a look back at some of the predictions that

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Speaker 1: we made last year. This time last year and some

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Speaker 1: predictions for twenty twenty six. I think we owe it

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Speaker 1: to ourselves to kind of look back at two years

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Speaker 1: of Risky Business and what we've kind of accomplished here,

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Speaker 1: because I think it's pretty cool that we've been able

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Speaker 1: to do this podcast for two years together. Yeah.

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Speaker 3: No, Look, I think we are trying to carve out

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Speaker 3: a niche that's becoming more and more relevant in the world,

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Speaker 3: right from like sportscambling scandals.

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Speaker 2: You know, prediction markets act that. Like, you know, it

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Speaker 2: feels more and more like we're in a world where

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Speaker 2: if you kind of like sit idly by, then you

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Speaker 2: you lose around.

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Speaker 3: It feels more and more like I mean, my opinions

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Speaker 3: about a progress of waxed and waned over the show.

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Speaker 3: We talk about it a lot, but you know, feeling

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Speaker 3: like we're marching into a certain future and if you

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Speaker 3: are in mid career and have had some success, just

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Speaker 3: like maybe not a feeling of profound security necessarily, right,

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Speaker 3: We're moving into a world where people are maybe.

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Speaker 2: Becoming stupider important ways, Like I.

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Speaker 1: Wasn't sure where that I wasn't sure where that sentence

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Speaker 1: was gonna go.

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Speaker 2: No, I mean, I think I think.

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Speaker 4: I'm very worried about and the boomers and the boomers

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Speaker 4: getting addicted their fucking sub sacks and ship like that,

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Speaker 4: and like, I don't know, Maria, I don't know.

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Speaker 2: You know, I think they're more self righteous.

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Speaker 3: I mean they used to be adicted to Facebook, which

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Speaker 3: was stupid, but like sub second is kind of partisan,

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Speaker 3: and so I mean, anyway, you know, the poker world's

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Speaker 3: been a little weird.

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Speaker 2: You want to talk a little poker, Maria, Sure you so.

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Speaker 3: I am supposed to be full disclosure, audience. It's an

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Speaker 3: episode is airing in January. We're taping it in late

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Speaker 3: December before Christmas. I in fact was supposed to be

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Speaker 3: taping this from so called Paradise.

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Speaker 1: Nate, tell the audience how you really feel about the

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Speaker 1: WSP Paradise stuff.

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Speaker 2: I attended.

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Speaker 3: The World Series of Poker Paradise in Atlantis Resort on

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Speaker 3: Paradise Island, which is a sub island of New Providence

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Speaker 3: in the Bahamas, and I think I had probably the worst.

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Speaker 2: Time that I've had at like a.

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Speaker 3: Poker festival, as they're officially called. These poker receivers are

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Speaker 3: officially called festivals. Right, Like, nothing bad happened, right, I

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Speaker 3: got a couple of nights nights out with a friend

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Speaker 3: who was having his birthday. I met some fun people

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Speaker 3: at the tables, ranging from NBA legend Tony Parker to

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Speaker 3: barstool Nate any other Nate.

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Speaker 2: I'm usually a fan. I'm playing against Wright, but number one.

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Speaker 3: Like I, I just.

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Speaker 2: Felt really confined in this giant resort.

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Speaker 3: And furthermore, like there's been a clash between the World

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Speaker 3: Poker Tour and the World Series of Poker for the

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Speaker 3: slot in mid December.

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Speaker 1: And Poker Stars there's ept problem.

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Speaker 2: And Poker Stars is an ebt and in product.

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Speaker 3: Basically, mid December is a really good slot for a

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Speaker 3: poker tournament because like, you have to be fucking insane

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Speaker 3: to travel in between Thanksgiving and Christmas, and poker players

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Speaker 3: are insane, and so we'll, you know, it's a cheap

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Speaker 3: time of year actually to travel. So the World Poker

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Speaker 3: Tour spun what had once been a relatively sleepy I

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Speaker 3: think it was called five Diamond Classic at the Bellagio.

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Speaker 3: The Wind began hosting a slot instead put a big

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Speaker 3: guarantee out in twenty twenty two, I think it was

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Speaker 3: fifteen million dollarslew that away people really love that series, right,

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Speaker 3: I mean an even bigger guarantee forty million dollars in

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Speaker 3: twenty twenty three. And then the World Serio tooker keeam

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Speaker 3: and said, well, we're.

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Speaker 2: Doing our thing in.

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Speaker 3: The Atlantis. Whin did not hit its guarantee had to

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Speaker 3: pay some money out of the wind coffers. And then

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Speaker 3: after that World Seriece Houcker's are, well, fuck you, we'll

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Speaker 3: guarantee you fifty million dollars in the Bahamas last year,

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Speaker 3: and then.

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Speaker 2: Sixty million dollars.

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Speaker 3: Except this is a twenty five K actually twenty six

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Speaker 3: K tournament and not a ten K, and you can,

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Speaker 3: like you can enter the tournament very very often.

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Speaker 1: Yeah, some people were in for thirteen fourteen fifteen bullets.

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Speaker 1: There were a lot of re entries. Now think about

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Speaker 1: what that means twenty six thousand dollars times fifteen sixteen bullets,

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Speaker 1: Like these are expensive tournaments.

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Speaker 3: Yeah, I know, there were what they were like twenty

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Speaker 3: one hundred entries, but they were from like one thousand

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Speaker 3: ish unique participants, right, so the average person entered almost

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Speaker 3: three times, so it was really a seventy eight K

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Speaker 3: for them and not a twenty six K, which is

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Speaker 3: builds a twenty five k, right, The tables I played

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Speaker 3: were despite that pretty good. I booked originally seven nights

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Speaker 3: in the Bahamas. Some were covered by casino points, and

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Speaker 3: why not shortening that, But like you know, all the

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Speaker 3: seven nights I was scheduled there, I probably played, let

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Speaker 3: me think, eighteen actual hours of actual poker, when if

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Speaker 3: there have been a better schedule, it had.

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Speaker 2: The capacity to play fifty hours.

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Speaker 1: Right, yeah, which is why n I went to the

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Speaker 1: WBT hat the win where the schedule is wonderful. The

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Speaker 1: win is one of the best places in the world

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Speaker 1: to play poker. Staff is a plus. I love the one.

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Speaker 1: Once again, this is the end of December. You'll be

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Speaker 1: hearing this in early January, so my series is not

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Speaker 1: over yet, so I have no idea how it's going

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Speaker 1: to go. But even if I end up losing a

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Speaker 1: shit ton of money, which actually isn't possible at this point,

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Speaker 1: but even if I lose more money than I want to,

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Speaker 1: I will be quite happy because this is a great

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Speaker 1: time of year in Vegas, and I'm happy to be

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Speaker 1: here in ept. Prog by the way, is also amazing.

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Speaker 1: I've been there many times. I didn't go this year

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Speaker 1: because it's far and it's cold, and Vegas is warm

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Speaker 1: and close.

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Speaker 2: So that was my that's got to Prague, right, and

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Speaker 2: you could have gone to pragu.

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Speaker 1: And it would have been a lot better. It would

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Speaker 1: have been a lot better.

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Speaker 3: And then you bust out, is there a EPT Paris

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Speaker 3: this year?

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Speaker 1: There is an APT Paris this year? I will be there.

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Speaker 1: So yeah, risky business listeners February Paris.

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Speaker 2: So you there, But in Paris you bust that. You're like,

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Speaker 2: I'm almost fucking happy about that. Right, it's going to go.

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Speaker 1: We had.

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Speaker 3: Right, you know, I mean that you know great that

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Speaker 3: you almost one of us, but you know, the baas

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Speaker 3: is in this like basically compound.

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Speaker 1: Yeah, this stopped. This stop was not paradise, is what

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Speaker 1: I'm hearing from you. And we hope, at least, I

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Speaker 1: sincerely hope that poker will go more in the direction

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Speaker 1: of what Poker Stars and WT are doing and less

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Speaker 1: in the Paradise direction, and that w s P. I

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Speaker 1: think a lot of people did not have a great

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Speaker 1: experience this yere and I do want to remind everyone

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Speaker 1: listening that at the end of the day, poker is

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Speaker 1: a game. If you're not having fun, why are you

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Speaker 1: even doing it? So when something isn't fun, just get

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Speaker 1: the fuck out of there. So let's let's just uh

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Speaker 1: talk about now are let's go into predictions. So we

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Speaker 1: we made some predictions last year, so exactly a year ago,

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Speaker 1: give or take a few days, we made predictions for

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Speaker 1: how twenty twenty five was going to go. Nate, I

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Speaker 1: didn't remember almost any of this. It's so funny, Like

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Speaker 1: I didn't remember what predictions we made. I didn't remember

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Speaker 1: how we were talking about this. So it's fun It

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Speaker 1: was a very different, uh, very different time, right, And

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Speaker 1: it's also very funny to see kind of what topics

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Speaker 1: seemed relevant, right, Like seemed like they were going to

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Speaker 1: be the big stories of the year, and it turned

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Speaker 1: out the year was very different from what we had

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Speaker 1: what we had thought. So we don't have to go

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Speaker 1: through every single prediction that we made, but we made

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Speaker 1: we made some interesting ones. So first prediction we made,

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Speaker 1: which I think is actually kind of funny, is we

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Speaker 1: were both predicting the highs and lows of bitcoin, and Nate,

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Speaker 1: you said it was going to be a one forty high.

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Speaker 1: I said one eighty, and then our lows were sixty

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Speaker 1: and seventy. We were so wrong, right, Like, our highs

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Speaker 1: were are way too high. You were closer, You were closer.

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Speaker 2: I'm close. That's good.

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Speaker 1: You were closer. Yeah, don't yeah, don't throw.

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Speaker 3: Me under This is a good group project. I did

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Speaker 3: my part of the project. Well, Marie, don't throw me

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Speaker 3: under the bus.

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Speaker 1: No, all I met was that our lows were too

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Speaker 1: low and our highs were too high.

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Speaker 2: Okay, well, look at the history of bit coin.

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Speaker 1: Is I was closer on the low because the low

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Speaker 1: was seventy eight point five and my low was seventy.

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Speaker 1: So come on, we both got this happened half. We

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Speaker 1: were correct though, on Trump nominees that how many would

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Speaker 1: be rejected or withdraw we said zero, and it was

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Speaker 1: in fact zero.

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Speaker 3: Yeah, so both predicted two press secretaries in twenty twenty five.

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Speaker 2: There's a limit one.

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Speaker 3: Caroline Levett has kept that job at least through the

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Speaker 3: late December day in which we're taking this.

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Speaker 2: You know, we go yeah tomorrow.

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Speaker 1: And you were correct that there was going to be

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Speaker 1: a national emergency to begin mass deportations. I said no,

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Speaker 1: and you said yes. I actually, according to the producer's

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Speaker 1: my exact language is probably yes. But I'm going to

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Speaker 1: say no because I don't want him to. My wishful

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Speaker 1: thinking did it work? So I tried to manifest it.

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Speaker 1: It did not manifest. There was, indeed, a national emergency

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Speaker 1: at the border declared. Musk did not become the first trillionaire.

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Speaker 1: We both got that right.

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Speaker 3: It can close six seventy seven billion as of December

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Speaker 3: fifteenth estimates Forbes.

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Speaker 1: Yes, pretty close, pretty close.

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Speaker 2: But no, well, you know, you know it shove me

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Speaker 2: a three hundred billion.

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Speaker 1: Anything above five hundred we round up to a trillion.

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Speaker 1: Is that the way it works?

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Speaker 2: Sixth seedment.

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Speaker 1: We can't. We can't do our tournament winnings, at least

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Speaker 1: I can't because we're still we're taking this in the

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Speaker 1: middle of a series format.

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Speaker 3: I predicted negative ten thousands for myself, it will be

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Speaker 3: this fucking that was within the realm of accurate before

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Speaker 3: this fucking Bahamas debacle. And I'm done for the year.

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Speaker 3: So yeah, at least I was directly correct. It would

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Speaker 3: be a negative year in tournament.

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Speaker 2: Poker, all right.

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Speaker 1: I have not done my calculation for the year yet,

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Speaker 1: so I cannot answer. My estimate was that I was

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Speaker 1: going to be up forty five thousand dollars. I'll report

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Speaker 1: back when I can. Oh, this was.

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Speaker 2: Good, Nate, you got a good bet. Ten thousand dollars.

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Speaker 3: You get bet any line in sports, what would you

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Speaker 3: bet that? Okay, I'm most say Shane Alexander would win

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Speaker 3: the MVP Award, which he did. I think it was

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Speaker 3: a little bit of a contrarian take back in January

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Speaker 3: probably a.

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Speaker 1: Probably, John, did you actually put money on it?

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Speaker 2: I've had money in the OKAC thunder a fair bit. Actually.

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Speaker 4: Yeah.

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Speaker 1: Good. And this is hilarious because I'm obviously the one

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Speaker 1: who awarded the second annual Daniel Kneman Memorial Cognitive Bias

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Speaker 1: of the Year Award, and I had predicted that it

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Speaker 1: was going to be the recency effect, and that is

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Speaker 1: indeed what I chose, which is funny. I guess my

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Speaker 1: brain was the same way, but I totally forgot that

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Speaker 1: this was my prediction, and so this was not a

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Speaker 1: self fulfilling prophecy. We cared about TikTok. We don't really

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Speaker 1: care about it anymore.

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Speaker 3: Funny, what's gonna happen to ticktach? I thought it would

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Speaker 3: get banned and you didn't. And it didn't get banned

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Speaker 3: because Trump, Yes, cynical.

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Speaker 2: I don't know.

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Speaker 1: Yeah, So we both did a long shot bet for

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Speaker 1: twenty twenty five, and Nate yours was about drones.

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Speaker 2: Remember those drones were in New Jersey.

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Speaker 3: One of three chants that later reporting would say there

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Speaker 3: had been something.

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Speaker 2: Something we all there and I guess, sir, I guess.

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Speaker 3: I don't think that's happened. I don't think there's been

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Speaker 3: much reporting on anything apart from no. Yeah, okay, so

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Speaker 3: you know, but your launchots are supposed to lose most

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Speaker 3: of the time, right, you call with pocket force. You're

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Speaker 3: not going to flop a set all that often.

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Speaker 1: No, that's very true. My lawn shot was that twenty

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Speaker 1: twenty five will be the year that we see a

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Speaker 1: nuclear power resurgence. Countries that had brought the plants offline,

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Speaker 1: we'll bring them back online. We'll see the first nuclear

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Speaker 1: power plants open because of increased energy needs due to AI.

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Speaker 1: I was kind of right. So this is starting to happen.

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Speaker 1: It's a lot of the plants are on track, and

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Speaker 1: we see a lot of nuclear plant opening scheduled for

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Speaker 1: twenty twenty six. So I was directionally correct, but it

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Speaker 1: hasn't happened yet. The process has started, but the plants

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Speaker 1: are not actually open yet. So yeah, but mine was

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Speaker 1: I think less of a long shot than yours.

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Speaker 3: Yeah, a little, a little little, a little safe there, Maria.

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Speaker 1: But you know what, back a year ago, I think

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Speaker 1: people were people including you, did not think that nuclear

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Speaker 1: power was going to be as big as as it's

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Speaker 1: now becoming. So it was still somewhat contrarian.

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Speaker 3: And we'll be right back after this break.

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Speaker 1: All right, let's go to twenty twenty six, and let's

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Speaker 1: talk about some predictions for twenty twenty six. So, Nate,

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Speaker 1: where do you want to start. Do you want to

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Speaker 1: talk about some politics predictions? Do you want to talk

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Speaker 1: about sports? Ai, what's what's on your mind? We've got

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Speaker 1: some predictions in all these different categories.

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Speaker 2: I guess politics.

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Speaker 1: All right, let's start with politics.

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Speaker 2: We're going to an election year.

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Speaker 3: We are, indeed, so if you're hearing this, probably twenty six.

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Speaker 3: Welcome your election year. It never set exactly.

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Speaker 1: Welcome to an election year. Yeah, it seems like it's

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Speaker 1: been one giant election year. Nate. I am going to

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Speaker 1: seed the political prediction ground to you because all I

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Speaker 1: know is what I read in the news. I don't

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Speaker 1: have any insider models. Insider info you do, I mean,

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Speaker 1: this is what you do. You build these models.

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Speaker 2: I don't have inside because I think insider info makes you.

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Speaker 1: Stupider well not insider info, but you have the models

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Speaker 1: that can actually process this information in a more data.

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Speaker 3: We're still a few months from the models being turned

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Speaker 3: back on. But look, I think Democrats are pretty heavy

305
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Speaker 3: favorites to take the House in the neighborhood of.

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Speaker 2: Eighty five percent.

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Speaker 1: Yeah, I was going to say the same thing that

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Speaker 1: I do. Think they're going to retake the House. Are

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Speaker 1: we gonna What do we think about the Senate?

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Speaker 3: I think the Senate is plausible for Democrats, but like

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Speaker 3: but like, but not like, I mean, what do they

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Speaker 3: have to win?

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Speaker 2: They have to win four seats.

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Speaker 3: And so there are two that in principle are quote

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Speaker 3: unquote easy, which are main in North Carolina. In North Carolina, Cooper,

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Speaker 3: the former governor, is running.

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Speaker 2: It's a swing state.

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Speaker 3: So you think the formula would be no incumbent, strong

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Speaker 3: Democratic candidate usually in midterms, the environment and you can

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Speaker 3: look at like the generic ballot or Trump's pool ratings

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Speaker 3: usually as Democratics. So like, mathematically that should favor Democrats

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Speaker 3: in you know, Susan Collins has survived difficult electoral environments

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Speaker 3: before war. Democrats are having a big fight in their

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Speaker 3: primary between Graham Platner the the populist oyster fishermen who, unfortunately,

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Speaker 3: unfortunately this happens to the best of us, unfortunately got

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Speaker 3: a tattoo that some people might argue resembles a symbol

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Speaker 3: used by a division, a Nazi Panzer division.

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Speaker 2: The Nazis, of course, were a group of Germans during

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Speaker 2: World War Two who didn't preicre like Jews or any

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Speaker 2: other people who weren't Rian. But you know, look it happens. Look,

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Speaker 2: you know, look, I mean, what can you say? It happens.

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Speaker 2: He was a little drunk in Croatia.

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Speaker 3: You know, it's like, look at this fucking Bahamas tournament, right,

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Speaker 3: you know, I was bored enough. It's like fucking fire.

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Speaker 3: Another bullet was twenty five k go get like a tattoo.

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Speaker 3: If those are the choices, I might have wound up

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Speaker 3: with a tattoo myself.

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Speaker 2: Maria, Well, we're.

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Speaker 1: We're glad that there was a third option. Yeah, all right,

340
00:18:20,444 --> 00:18:25,964
Speaker 1: so we've got we've got a likely house retake, less likely.

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Speaker 3: At the at pollm markets when we're taping this. It's

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Speaker 3: seventy eight in the House for Democrats.

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Speaker 2: I think that's low. I would take the over on that.

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Speaker 3: In the Senate it's thirty five percent for Democrats. That

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Speaker 3: seemed roughly reasonable to me.

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Speaker 1: Yeah, that that makes sense. Thirty five percent is not zero,

347
00:18:47,764 --> 00:18:48,444
Speaker 1: but it's.

348
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Speaker 2: A long way from zero. It's it.

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Speaker 1: Yeah, it's it's the cherry. Yeah, it's it's very it's

350
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Speaker 1: very plausible. So what would how about uh, egg prices,

351
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Speaker 1: that's very that's funny political we can have.

352
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Speaker 2: I don't know it. Our producers suggested it. I look,

353
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Speaker 2: I don't. I don't. I don't know.

354
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Speaker 3: I don't really eat the many eggs, not really go

355
00:19:17,844 --> 00:19:20,084
Speaker 3: shotting for eggs. I'm probably the wrong person to ask

356
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Speaker 3: about this.

357
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Speaker 1: Yeah, yeah, well, it depends obviously on diseases and all

358
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Speaker 1: sorts of things. Let's say the highest egg prices in

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Speaker 1: twenty twenty six will be twelve dollars for a dozen eggs.

360
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Speaker 1: I have no idea it's going to be my prediction.

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Speaker 1: I'll say that's a dollar an egg, Nate, That's that's all.

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Speaker 2: I'll say. Eleven nine is the person is right? Shit,

363
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Speaker 2: I love it. I love gts this is GTO.

364
00:19:48,364 --> 00:19:51,684
Speaker 1: Yeah, this is this is the GTO. So we're going

365
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Speaker 1: to give you a GTO lesson on the prices. Right,

366
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Speaker 1: do you're the over under when you see people on

367
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Speaker 1: that game who actually don't know how to play, right,

368
00:20:00,644 --> 00:20:04,004
Speaker 1: and someone already guesses a number, and what are you

369
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Speaker 1: supposed to guess after that night?

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Speaker 2: You're supposed to guess a dollar under? Yeah?

371
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Speaker 1: Yeah, yeah, you just do not want to be the

372
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Speaker 1: person who if you can't go over. Yeah, it's it's

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Speaker 1: a it's a it's an interesting game theoretical lesson in

374
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Speaker 1: all of these games. I don't watch quiz show games,

375
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Speaker 1: but they all have game theory that you should study

376
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Speaker 1: if you're ever going to be on one of them.

377
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Speaker 1: Do you think anyone's going to be prosecuted with regards

378
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Speaker 1: to the Epstein files, I actually do not. I think

379
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Speaker 1: that this is oh maybe a Democrat, but this has

380
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Speaker 1: to be a prosecution that actually goes forward. Yeah, I

381
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Speaker 1: don't know. I mean, the.

382
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Speaker 2: GP eventually did sign a dispatch petition. I mean, people are.

383
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Speaker 3: I guess I'd say prosecuted by who? By the federal government? Right,

384
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Speaker 3: I guess No.

385
00:21:00,444 --> 00:21:02,884
Speaker 2: I think it's just too messy for Trump to like actually, like.

386
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Speaker 3: It's a little too cavalier for for him to like

387
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Speaker 3: target a Democrat. I mean I don't know, Yeah, I

388
00:21:10,884 --> 00:21:14,244
Speaker 3: just think it feels like then you're encouraging people to

389
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Speaker 3: discuss that story, which I think the White House does

390
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Speaker 3: not want to do.

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Speaker 2: Right. Yeah, I think.

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Speaker 1: That that's correct. That's why I think now sports, well,

393
00:21:23,284 --> 00:21:27,324
Speaker 1: which league, Nate, we'll have a major gambling scandal next?

394
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Speaker 1: I mean, are we allowed to say that, like they'll

395
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Speaker 1: also be repeats because I think that the you know,

396
00:21:34,164 --> 00:21:35,844
Speaker 1: or do we have to pick a league that hasn't

397
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Speaker 1: had a gambling scandal because I feel like at this point, like, man,

398
00:21:40,564 --> 00:21:42,244
Speaker 1: we're going to see these everywhere.

399
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Speaker 2: Oh. I think college sports are are.

400
00:21:47,884 --> 00:21:51,164
Speaker 3: Right for because they're like some of these students are

401
00:21:51,204 --> 00:21:56,564
Speaker 3: now making money with nil deals, but like they're you know,

402
00:21:56,964 --> 00:22:00,564
Speaker 3: there have valuable information that there's a lot of volume

403
00:22:00,564 --> 00:22:04,884
Speaker 3: in college football college basketball betting. Right, these kids are

404
00:22:04,884 --> 00:22:09,684
Speaker 3: not professionals, they could use some income and like ye, yeah,

405
00:22:09,724 --> 00:22:12,644
Speaker 3: I mean that seems to me almost statistically and there

406
00:22:12,684 --> 00:22:14,964
Speaker 3: are more teams than in the pros. Yeah, it seems

407
00:22:14,964 --> 00:22:17,444
Speaker 3: to be almost like statistically inevitable at some point.

408
00:22:17,924 --> 00:22:24,324
Speaker 1: Oh, absolutely, absolutely, whenever you have such a misalignment of

409
00:22:24,444 --> 00:22:28,044
Speaker 1: incentives right where you can make a lot more money

410
00:22:28,044 --> 00:22:33,364
Speaker 1: than you're making from from something that might be a

411
00:22:33,364 --> 00:22:37,204
Speaker 1: little bit not as above board as one would hope.

412
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Speaker 1: There's going to be there's going to be a scandal.

413
00:22:39,724 --> 00:22:43,044
Speaker 1: We see that in professional sports where athletes are underpaid.

414
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Speaker 1: It's why there's so much cheating in tennis, for instance,

415
00:22:46,364 --> 00:22:49,404
Speaker 1: because in tennis, you know, the top of the profession

416
00:22:49,524 --> 00:22:52,244
Speaker 1: is paid very well, but there's so many players, right

417
00:22:52,324 --> 00:22:57,124
Speaker 1: who are not that who are not that well compensated.

418
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Speaker 1: And tennis is expensive. You have to travel, you have

419
00:22:59,684 --> 00:23:01,724
Speaker 1: to do you know, there are lots and lots of

420
00:23:01,724 --> 00:23:04,324
Speaker 1: expenses for this, and unless you're at the very top,

421
00:23:04,364 --> 00:23:05,924
Speaker 1: you're just not going to make a lot of money.

422
00:23:06,044 --> 00:23:09,084
Speaker 1: And so people are incentivized to, you know, to cheat.

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00:23:09,524 --> 00:23:12,044
Speaker 1: They can because if you're playing singles, especially like, it's

424
00:23:12,044 --> 00:23:15,204
Speaker 1: so easy, right, you can actually throw matches, like, you

425
00:23:15,284 --> 00:23:19,164
Speaker 1: can manipulate serves, you can do so many different things

426
00:23:19,284 --> 00:23:22,444
Speaker 1: to get money. And if you're being paid nothing, but

427
00:23:22,484 --> 00:23:24,884
Speaker 1: the prediction markets and the betting markets and the sports

428
00:23:24,884 --> 00:23:28,364
Speaker 1: betting markets are so high, right, and there's so much

429
00:23:28,404 --> 00:23:32,364
Speaker 1: potential volume, there so much money there. Then you have

430
00:23:32,404 --> 00:23:35,364
Speaker 1: this misalignment that is going to cause scandals, and so

431
00:23:35,844 --> 00:23:38,644
Speaker 1: that's very very true in the college arena as well. So, Nate,

432
00:23:38,724 --> 00:23:41,204
Speaker 1: I think, I think that's a good, good prediction, and

433
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Speaker 1: I'm actually surprised that we haven't had a huge one yet,

434
00:23:44,644 --> 00:23:46,684
Speaker 1: But I think that that's probably because the rules have

435
00:23:46,724 --> 00:23:50,084
Speaker 1: only started to shift now and a lot of these

436
00:23:50,164 --> 00:23:52,244
Speaker 1: betting opportunities didn't exist before.

437
00:23:53,604 --> 00:23:56,564
Speaker 3: Yeah, let's remember if to the except there are these scandals,

438
00:23:56,564 --> 00:23:59,324
Speaker 3: the leagues aren't thrilled to have them come up, right,

439
00:23:59,364 --> 00:24:01,404
Speaker 3: So you don't know what's kind of going on and

440
00:24:01,444 --> 00:24:04,924
Speaker 3: being handled with quiet suspensions below the radar and things

441
00:24:05,004 --> 00:24:08,084
Speaker 3: like that. But like it's hard to imagine that and

442
00:24:08,124 --> 00:24:10,724
Speaker 3: given what you've seen in the NBA, and college has

443
00:24:10,764 --> 00:24:14,484
Speaker 3: traditionally been kind of a source of point shaving, dating

444
00:24:14,524 --> 00:24:16,924
Speaker 3: back to like the Boston College scandal of the seventies.

445
00:24:18,124 --> 00:24:22,524
Speaker 1: So, yeah, do you have any other sports ones that

446
00:24:22,604 --> 00:24:26,204
Speaker 1: you want to talk about other than let's give you

447
00:24:26,244 --> 00:24:27,324
Speaker 1: ten thousand dollars again?

448
00:24:28,244 --> 00:24:30,484
Speaker 3: I mean, look, I think I think the OKAC Thunder

449
00:24:30,804 --> 00:24:33,284
Speaker 3: are once again a good season long bet.

450
00:24:33,404 --> 00:24:33,604
Speaker 4: Right.

451
00:24:33,724 --> 00:24:35,124
Speaker 2: They have started out their season.

452
00:24:35,164 --> 00:24:37,684
Speaker 3: I think they're twenty four and two, have the best

453
00:24:37,724 --> 00:24:41,644
Speaker 3: point differentiate in basketball history, beating the record from last year.

454
00:24:41,684 --> 00:24:43,924
Speaker 3: Have done this with various injuries because they like, you know,

455
00:24:44,084 --> 00:24:46,404
Speaker 3: if you divide that team in half, they would both

456
00:24:46,444 --> 00:24:49,604
Speaker 3: be top four playoff seeds in the West. And like,

457
00:24:49,684 --> 00:24:53,044
Speaker 3: it just seems like it's never easy money in the NBA.

458
00:24:54,044 --> 00:24:56,724
Speaker 3: Their half court offense is merely good. That becomes more

459
00:24:56,724 --> 00:24:59,404
Speaker 3: important the place postseason. But like, but yeah, I know

460
00:24:59,684 --> 00:25:03,364
Speaker 3: this seems like a a I know it's not easy money,

461
00:25:03,364 --> 00:25:07,084
Speaker 3: but like, I think they're above fifty percent to win

462
00:25:07,124 --> 00:25:08,524
Speaker 3: the championship, is my view.

463
00:25:09,484 --> 00:25:11,524
Speaker 1: So that's what you would bet your ten thousand dollars on.

464
00:25:12,604 --> 00:25:14,684
Speaker 3: Well, I mean, look, it would depend on Yeah, I

465
00:25:14,684 --> 00:25:16,524
Speaker 3: think I think they'd be a good use of I

466
00:25:16,564 --> 00:25:18,084
Speaker 3: don't know what the odds are, actually, I should look

467
00:25:18,124 --> 00:25:21,924
Speaker 3: that up. It's about fifty to fifty in the betting markets, right.

468
00:25:21,844 --> 00:25:23,244
Speaker 1: Okay, so it is a good So it would be

469
00:25:23,244 --> 00:25:25,004
Speaker 1: a good use of your money, right if it's fifty

470
00:25:25,004 --> 00:25:28,764
Speaker 1: to fifty. Yeah, and you have a strong conviction one way.

471
00:25:29,364 --> 00:25:37,244
Speaker 1: All right, let's do it. We'll be back right after this.

472
00:25:47,084 --> 00:25:49,244
Speaker 1: All right, let's let's move on to AI, which is

473
00:25:49,244 --> 00:25:54,044
Speaker 1: something I actually know more about than sports. Over under

474
00:25:54,124 --> 00:25:59,644
Speaker 1: on Sora manifesting a major news event. So Sorah makes

475
00:25:59,684 --> 00:26:02,404
Speaker 1: a video which is a fake AI video, and then

476
00:26:02,604 --> 00:26:05,804
Speaker 1: the shit that's in the video actually happens. I mean,

477
00:26:05,884 --> 00:26:08,844
Speaker 1: I think that there's a decent chance of that.

478
00:26:11,644 --> 00:26:12,684
Speaker 2: How is this defined?

479
00:26:13,684 --> 00:26:15,844
Speaker 1: Yeah, I mean, I guess we get to define it, right,

480
00:26:15,884 --> 00:26:21,684
Speaker 1: this is our prediction. So defining there's something, well, first

481
00:26:21,764 --> 00:26:24,204
Speaker 1: major news event, right, so it can't be something minor

482
00:26:24,444 --> 00:26:27,644
Speaker 1: like oh, there's going to be a protest on you know,

483
00:26:27,724 --> 00:26:31,884
Speaker 1: Madison Avenue. Okay, fine, like that. That's not that that's

484
00:26:31,924 --> 00:26:36,204
Speaker 1: not a major news event, but something like, you know,

485
00:26:36,324 --> 00:26:40,964
Speaker 1: there's going to be I don't know, military coup. Well,

486
00:26:40,964 --> 00:26:44,004
Speaker 1: that would definitely be a major news event. But let's

487
00:26:44,084 --> 00:26:45,644
Speaker 1: let's hope Sory doesn't manifest anything.

488
00:26:45,644 --> 00:26:47,244
Speaker 2: I wonder have you seen.

489
00:26:48,724 --> 00:26:57,044
Speaker 3: These AI generated clips of where a fat person carries

490
00:26:57,124 --> 00:27:01,604
Speaker 3: a boulder onto a glass bridge right or into like

491
00:27:01,644 --> 00:27:05,244
Speaker 3: an infinity pool and then like jump on it to

492
00:27:05,324 --> 00:27:08,404
Speaker 3: destabilize the bridge and cause everyone to fall down into

493
00:27:08,404 --> 00:27:11,724
Speaker 3: the canyon of the river or whatever. Have you seen these?

494
00:27:12,444 --> 00:27:13,924
Speaker 1: I have not seen these. NT.

495
00:27:14,044 --> 00:27:15,564
Speaker 2: I don't know what you're talking about.

496
00:27:16,404 --> 00:27:19,284
Speaker 3: I know what makes you seem crazy, but it's a

497
00:27:19,564 --> 00:27:22,644
Speaker 3: genre of these videos, right, you know, so.

498
00:27:22,644 --> 00:27:24,844
Speaker 2: I guess I'm like, will there actually be copycats?

499
00:27:25,484 --> 00:27:29,164
Speaker 1: Are you seeing a therapist? Do we need to talk

500
00:27:29,204 --> 00:27:30,124
Speaker 1: about this?

501
00:27:30,124 --> 00:27:32,324
Speaker 2: This is a real thing, I mean, a real effect thing.

502
00:27:32,764 --> 00:27:35,284
Speaker 2: What I'm saying is like, it's interesting.

503
00:27:35,324 --> 00:27:36,604
Speaker 3: This is like one of the first thing is kind

504
00:27:36,604 --> 00:27:39,924
Speaker 3: of like emerge out of the randomness of AI models,

505
00:27:40,004 --> 00:27:42,484
Speaker 3: right and become kind of viral. I believe you have

506
00:27:42,564 --> 00:27:45,284
Speaker 3: you maybe you're not star have time on on on

507
00:27:45,604 --> 00:27:48,324
Speaker 3: X the everything platform, what does Helene call it?

508
00:27:50,164 --> 00:27:51,444
Speaker 1: That is most certainly true.

509
00:27:51,524 --> 00:27:54,284
Speaker 3: I would, you know, maybe I'll see some copycat attempts

510
00:27:54,324 --> 00:27:58,644
Speaker 3: to like to turn memes real that are originally.

511
00:27:58,284 --> 00:28:00,764
Speaker 1: Yeah, well that's that's that's an interesting I mean, I

512
00:28:01,004 --> 00:28:04,244
Speaker 1: think that there's a very good shot at that happening.

513
00:28:04,524 --> 00:28:07,084
Speaker 1: And by the way, I want to applaud myself on

514
00:28:07,524 --> 00:28:11,604
Speaker 1: saying not interested, not from me, not interested, not interested

515
00:28:11,724 --> 00:28:14,044
Speaker 1: enough on X that I don't get any of these

516
00:28:14,084 --> 00:28:18,964
Speaker 1: in my feet, so I get very few viral videos.

517
00:28:19,604 --> 00:28:25,444
Speaker 1: So I applaud my brain for for not being exposed

518
00:28:25,444 --> 00:28:30,244
Speaker 1: to at least that matter of slop. But there are

519
00:28:30,284 --> 00:28:34,204
Speaker 1: some viral videos that look incredibly real and that have

520
00:28:34,924 --> 00:28:38,564
Speaker 1: actually been used by real news organizations and by the

521
00:28:38,604 --> 00:28:41,804
Speaker 1: president obviously. So I think that there will be more

522
00:28:41,884 --> 00:28:44,844
Speaker 1: and more of that happening. Right where you have these

523
00:28:45,084 --> 00:28:51,244
Speaker 1: very plausible seeming videos. There was one one that went

524
00:28:51,364 --> 00:28:55,244
Speaker 1: viral which was a street interview in New York about

525
00:28:55,724 --> 00:28:59,524
Speaker 1: I think it was about Snap benefits and that went

526
00:28:59,604 --> 00:29:02,364
Speaker 1: viral and was picked up by actual media, and the

527
00:29:02,404 --> 00:29:04,604
Speaker 1: people didn't exist, right, It was a fake interview or

528
00:29:04,604 --> 00:29:08,164
Speaker 1: a fake interviewee, fake interview, fake everything. And I think

529
00:29:08,164 --> 00:29:09,724
Speaker 1: we're going to be seeing a lot more of that,

530
00:29:09,884 --> 00:29:14,524
Speaker 1: which is kind of craft the character that fits your storyline, right,

531
00:29:14,724 --> 00:29:17,284
Speaker 1: give them the dialogue that you think this type of

532
00:29:17,284 --> 00:29:20,004
Speaker 1: person should be saying, and here you go, here's a

533
00:29:20,084 --> 00:29:24,844
Speaker 1: video which is going to I think upset the balance

534
00:29:25,084 --> 00:29:28,764
Speaker 1: of how we consume news and how we can figure

535
00:29:28,764 --> 00:29:32,284
Speaker 1: out what is and isn't real, right, Like, are you

536
00:29:32,484 --> 00:29:35,364
Speaker 1: able to use video as proof that something did or

537
00:29:35,364 --> 00:29:39,564
Speaker 1: it did not happen and in the absence of sophisticated

538
00:29:39,604 --> 00:29:42,964
Speaker 1: technology to detect if something is real or fake, which

539
00:29:43,484 --> 00:29:46,844
Speaker 1: exists but not in the general viewers. You know, it's

540
00:29:46,884 --> 00:29:48,884
Speaker 1: not like I can see a video and immediately be like, oh,

541
00:29:48,964 --> 00:29:51,164
Speaker 1: this is fake, this is real. The better they get,

542
00:29:51,164 --> 00:29:54,964
Speaker 1: the less able, the just average user is to be

543
00:29:55,044 --> 00:29:58,724
Speaker 1: able to detect that. What we know from psychology is

544
00:29:58,724 --> 00:30:00,684
Speaker 1: that once you're exposed to it, even if it's then

545
00:30:00,724 --> 00:30:04,284
Speaker 1: debunked as fake, the you know, the effects linger right,

546
00:30:04,484 --> 00:30:08,884
Speaker 1: It's not like it magically disappears from your brain. It's

547
00:30:08,924 --> 00:30:11,724
Speaker 1: still kind of has this Oh but it's kind of

548
00:30:11,764 --> 00:30:15,004
Speaker 1: real type of primacy. And I think we're gonna be

549
00:30:15,044 --> 00:30:15,484
Speaker 1: so we talked.

550
00:30:15,524 --> 00:30:17,724
Speaker 2: I don't fast it much here. So like, yeah, when

551
00:30:18,284 --> 00:30:20,524
Speaker 2: Charlie Kirk was killed.

552
00:30:20,724 --> 00:30:23,924
Speaker 3: Uh, the assassin was someone who had grown up in

553
00:30:23,924 --> 00:30:28,884
Speaker 3: a conservative family but had become more more left wing

554
00:30:29,284 --> 00:30:32,044
Speaker 3: over time. But like you know, you know, people like

555
00:30:33,084 --> 00:30:38,004
Speaker 3: Helicos Richardson, the most prominent substacker, right kind of spread

556
00:30:38,004 --> 00:30:40,284
Speaker 3: misinformation or she didn't, And there's no kind of right

557
00:30:40,484 --> 00:30:44,364
Speaker 3: spread misinformation speculing that he was a griper, meaning somebody

558
00:30:44,444 --> 00:30:46,884
Speaker 3: who thought that like a Nick Finis type, who thought

559
00:30:46,884 --> 00:30:50,284
Speaker 3: that like Charlie Kirk wasn't conservative enough, it wasn't pure enough, right,

560
00:30:50,364 --> 00:30:54,284
Speaker 3: and that was just total misinformation. But like Jimmy Kimmel

561
00:30:54,564 --> 00:30:59,124
Speaker 3: said something similar, right in like polls of Democrats or

562
00:30:59,124 --> 00:31:01,284
Speaker 3: actually general voters, like a lot of people, if you

563
00:31:01,364 --> 00:31:04,404
Speaker 3: survey them, think that Charlie Kirk's killer was actually a

564
00:31:04,444 --> 00:31:08,084
Speaker 3: conservative Many people think that, so like, yeah, it is.

565
00:31:08,204 --> 00:31:09,004
Speaker 2: It is hard to debunk.

566
00:31:09,124 --> 00:31:11,124
Speaker 3: So like, so I've just in a situation where I'm like,

567
00:31:11,524 --> 00:31:13,324
Speaker 3: I don't feel like I have anybody to trust on

568
00:31:13,364 --> 00:31:15,004
Speaker 3: certain types of stories right now.

569
00:31:15,084 --> 00:31:18,044
Speaker 1: Yeah, absolutely absolutely, And I think that that problem is

570
00:31:18,084 --> 00:31:20,564
Speaker 1: going to get only worse. I think that that's a

571
00:31:20,604 --> 00:31:24,164
Speaker 1: prediction that we can stand behind for for this coming year.

572
00:31:24,884 --> 00:31:27,004
Speaker 1: Who do you think will have the best AI model

573
00:31:27,404 --> 00:31:31,004
Speaker 1: by the end of the year. So this time next year,

574
00:31:31,084 --> 00:31:34,604
Speaker 1: which of the AI models is going to which company

575
00:31:34,644 --> 00:31:35,964
Speaker 1: is going to be ahead.

576
00:31:35,964 --> 00:31:38,244
Speaker 2: As judged by like general consensus or.

577
00:31:38,284 --> 00:31:42,044
Speaker 1: Like, yeah, I think so, I guess anthropic.

578
00:31:42,604 --> 00:31:44,964
Speaker 2: I mean, look, you can make a contrarian case.

579
00:31:45,004 --> 00:31:49,364
Speaker 3: So right now, I think the consensus of like super

580
00:31:49,404 --> 00:31:51,164
Speaker 3: AI super user nerds would.

581
00:31:50,964 --> 00:31:53,724
Speaker 2: Say probably Claude.

582
00:31:54,244 --> 00:31:59,124
Speaker 3: But people seem to like GPT five point two so far,

583
00:31:59,124 --> 00:32:03,124
Speaker 3: which was a pretty rapid progression from five point one.

584
00:32:03,444 --> 00:32:06,124
Speaker 3: Open AI has the most resources. You know, people seem

585
00:32:06,164 --> 00:32:09,844
Speaker 3: to think that Gemini is very literal I need, but

586
00:32:09,924 --> 00:32:11,684
Speaker 3: a very good model.

587
00:32:11,724 --> 00:32:15,004
Speaker 2: I wouldn't put anything past Google. I don't know, maybe

588
00:32:15,044 --> 00:32:20,844
Speaker 2: up in AI is like undervalued resources they have.

589
00:32:21,484 --> 00:32:23,604
Speaker 1: I'm gonna go with Google Deep Mind. I think that

590
00:32:23,644 --> 00:32:28,084
Speaker 1: they're gonna be the winners at the end of this year. Okay,

591
00:32:28,404 --> 00:32:31,884
Speaker 1: in dumbest with trust, I wonder if you're a little rescued.

592
00:32:31,964 --> 00:32:34,804
Speaker 2: But no people, but it's you know, I'll go with Claude.

593
00:32:34,844 --> 00:32:37,364
Speaker 1: I guess all right, let's uh, do do you want

594
00:32:37,364 --> 00:32:41,684
Speaker 1: to do one New York specific one zoron? Uh? What

595
00:32:41,764 --> 00:32:43,604
Speaker 1: do we think? Do you wanna do you wanna do

596
00:32:43,644 --> 00:32:46,244
Speaker 1: a zoron prediction or do you want to just see

597
00:32:46,244 --> 00:32:46,804
Speaker 1: what happens?

598
00:32:46,884 --> 00:32:48,364
Speaker 2: Well you get his free buses this year?

599
00:32:51,204 --> 00:32:55,524
Speaker 1: Uh? Maybe maybe I don't think so, though I give

600
00:32:55,524 --> 00:32:57,284
Speaker 1: it like a I'll get it. I'll give it a

601
00:32:57,324 --> 00:32:58,484
Speaker 1: thirty five per chance.

602
00:32:59,164 --> 00:33:02,084
Speaker 2: So one free. But I think there'll be a pilot program, right,

603
00:33:02,164 --> 00:33:03,084
Speaker 2: because who can not.

604
00:33:03,244 --> 00:33:04,684
Speaker 1: The entire city.

605
00:33:05,284 --> 00:33:12,964
Speaker 3: Yeah, they'll make like a second avenue by free or something. Right, Yeah,

606
00:33:13,004 --> 00:33:15,284
Speaker 3: they'll make a couple of buses free, I predict, and

607
00:33:15,284 --> 00:33:15,884
Speaker 3: we'll see how it go.

608
00:33:15,924 --> 00:33:16,244
Speaker 1: All right.

609
00:33:16,564 --> 00:33:18,004
Speaker 2: I'm not that I post the free buses.

610
00:33:18,524 --> 00:33:19,684
Speaker 1: No, I think it's a great idea.

611
00:33:20,004 --> 00:33:20,924
Speaker 2: I think it's early today.

612
00:33:21,004 --> 00:33:24,204
Speaker 3: Yeah, but like I mean, the problem is, like you

613
00:33:24,244 --> 00:33:27,604
Speaker 3: give people who want to sit and ride a bus

614
00:33:27,604 --> 00:33:29,444
Speaker 3: all day and an opportunity to do that, you know what

615
00:33:29,484 --> 00:33:29,804
Speaker 3: I mean.

616
00:33:30,164 --> 00:33:32,364
Speaker 2: This might not be people you want on the bus necessarily,

617
00:33:32,644 --> 00:33:34,364
Speaker 2: but yeah.

618
00:33:33,764 --> 00:33:35,324
Speaker 1: Well I think that. I think that a lot of

619
00:33:35,324 --> 00:33:37,564
Speaker 1: places have tried it, not a lot, A few places

620
00:33:37,564 --> 00:33:40,284
Speaker 1: have tried it and it's worked pretty well so and

621
00:33:40,364 --> 00:33:43,484
Speaker 1: it might help with congestion. So let's see. Yeah, let's

622
00:33:43,524 --> 00:33:47,804
Speaker 1: see what happens, all right, Nate, do you think that, well,

623
00:33:47,844 --> 00:33:49,164
Speaker 1: how many days do you think you're going to make

624
00:33:49,164 --> 00:33:50,564
Speaker 1: it in the WSOP Maine event?

625
00:33:51,124 --> 00:33:54,364
Speaker 2: So it was five this year and six two years ago?

626
00:33:54,804 --> 00:33:56,084
Speaker 2: I guess two before?

627
00:33:56,164 --> 00:33:59,324
Speaker 3: Yeah, I mean the median the median is three, And

628
00:33:59,524 --> 00:34:01,804
Speaker 3: I do think now, I do think there is some

629
00:34:03,564 --> 00:34:06,484
Speaker 3: particular advantage in that tournament if you've played it a

630
00:34:06,484 --> 00:34:10,844
Speaker 3: lot and run deep before, right, But it would be

631
00:34:11,484 --> 00:34:15,644
Speaker 3: you know, the correct answer, siskally is is two or three?

632
00:34:15,764 --> 00:34:17,964
Speaker 3: And I think I'm I think three is probably the

633
00:34:18,004 --> 00:34:21,564
Speaker 3: actually correct answer, And I think to predict four or

634
00:34:21,604 --> 00:34:24,644
Speaker 3: more would be quite arrogant and unrealistic.

635
00:34:25,924 --> 00:34:28,764
Speaker 1: When how many days does it last? When it's the

636
00:34:28,804 --> 00:34:32,284
Speaker 1: final table, it's nine days?

637
00:34:32,324 --> 00:34:33,524
Speaker 2: Nine or ten? Yeah?

638
00:34:33,884 --> 00:34:35,684
Speaker 1: Okay, so I'm going to predict I make it to

639
00:34:35,764 --> 00:34:39,844
Speaker 1: day ten. Okay, I'm gonna manifest it. I'm manifested it.

640
00:34:40,564 --> 00:34:45,244
Speaker 1: I fuck it, fuck it, Nate. So I'm I'm making

641
00:34:45,244 --> 00:34:48,004
Speaker 1: the final table this year. You know, Leo did it

642
00:34:48,084 --> 00:34:50,324
Speaker 1: last year. She was a great guest on this podcast,

643
00:34:51,364 --> 00:34:54,564
Speaker 1: and I think it's it's you know, the time for

644
00:34:54,804 --> 00:34:57,204
Speaker 1: and Chrissy almost did it the year before. So I

645
00:34:57,204 --> 00:35:00,484
Speaker 1: think women women have been getting further and further, so

646
00:35:00,564 --> 00:35:03,684
Speaker 1: this year, why not me for our last episode? If

647
00:35:03,724 --> 00:35:06,404
Speaker 1: I'm going to make a prediction, I you know, if

648
00:35:06,444 --> 00:35:08,684
Speaker 1: there's a less than one percent chance, that's still fine.

649
00:35:08,804 --> 00:35:16,124
Speaker 1: I am vision board manifesting. So on that note, let's

650
00:35:16,164 --> 00:35:19,844
Speaker 1: just end the predictions with me winning the doublesp made event.

651
00:35:19,844 --> 00:35:21,764
Speaker 1: I think that's it's a great one, or at least

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00:35:21,804 --> 00:35:23,924
Speaker 1: final tabling. I'm not gonna get too ergon. I don't

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00:35:23,964 --> 00:35:26,204
Speaker 1: have to win it our final table. I'd like to

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00:35:26,244 --> 00:35:29,004
Speaker 1: win it, but final tabling, you know, I'll take it.

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00:35:29,044 --> 00:35:30,404
Speaker 1: I'll take it, you know.

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00:35:30,364 --> 00:35:33,244
Speaker 2: I would take it. I take a day seven. How

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00:35:33,244 --> 00:35:33,604
Speaker 2: about that?

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00:35:34,204 --> 00:35:34,564
Speaker 4: All right?

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00:35:34,804 --> 00:35:38,964
Speaker 1: Sounds good? And with that, thank you Risky Business listeners

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00:35:39,004 --> 00:35:43,084
Speaker 1: for being an amazing audience and again follow us on

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00:35:43,124 --> 00:35:47,084
Speaker 1: our substacks and stay tuned for more news about where

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00:35:47,164 --> 00:35:48,884
Speaker 1: Nate and I will be heading next.

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00:35:49,124 --> 00:35:51,444
Speaker 2: Yeah, I guess the end has to come somewhat awkwardly here.

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00:35:51,884 --> 00:35:54,684
Speaker 3: Yeah, at the end, I don't know if you know,

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00:35:54,484 --> 00:35:57,484
Speaker 3: if you want to like sing a theme song or

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00:35:57,724 --> 00:35:58,724
Speaker 3: no or whatever, you.

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00:35:58,804 --> 00:36:02,644
Speaker 1: Know, absolutely not you can sing, Nate, I'm gonna I'm

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00:36:02,644 --> 00:36:03,364
Speaker 1: gonna listen.

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00:36:03,124 --> 00:36:07,564
Speaker 3: All the memories all alone, and I don't even know

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00:36:07,644 --> 00:36:08,364
Speaker 3: what song that is.

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00:36:09,084 --> 00:36:16,324
Speaker 1: Thanks, We're ending on an Andrew Lloyd Weber classic flop.

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00:36:16,684 --> 00:36:19,444
Speaker 3: Let's do not like not like musicals. By the way,

673
00:36:19,444 --> 00:36:21,204
Speaker 3: don't get any wrong ideas.

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00:36:23,604 --> 00:36:23,964
Speaker 4: All right.

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00:36:24,004 --> 00:36:26,244
Speaker 1: We hope we've made some good memories here with you,

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00:36:26,364 --> 00:36:29,004
Speaker 1: and we look forward to making more memories with you

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00:36:29,124 --> 00:36:44,324
Speaker 1: in the future, wherever that may be. Let us know

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00:36:44,364 --> 00:36:46,204
Speaker 1: what you think of the show. Reach out to us

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00:36:46,244 --> 00:36:50,404
Speaker 1: at Risky Business at pushkin dot FM. Risky Business is

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00:36:50,444 --> 00:36:53,004
Speaker 1: hosted by me Maria Kanakova.

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00:36:52,404 --> 00:36:55,124
Speaker 3: And by me Nate Silver. The show was a Cool

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00:36:55,164 --> 00:36:59,164
Speaker 3: production of Pushing Industries and iHeartMedia. This episode was produced

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00:36:59,164 --> 00:37:03,484
Speaker 3: by Isaac Carter. Our associate producer is Sonya gerwit Lydia

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00:37:03,604 --> 00:37:06,484
Speaker 3: Jean Kott and Daphney Chen are our editors. And our

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00:37:06,524 --> 00:37:10,284
Speaker 3: executive producer is Jacob Goldstein. Mixing by Sarah Bruguer.

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00:37:10,884 --> 00:37:13,084
Speaker 1: If you like the show, please rate and review us

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00:37:13,124 --> 00:37:15,804
Speaker 1: so other people can find us too, but once again,

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00:37:15,924 --> 00:37:17,764
Speaker 1: only if you like us. We don't want those bad

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00:37:17,804 --> 00:37:19,964
Speaker 1: reviews out there. Thanks for tuning in,