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Ep 902[Ep 903] Repelling the Ninjas [2:11:43]
Recorded: Sat, 2024-Sep-28 UTC
Published: Mon, 2024-Sep-30 03:36 UTC
Ep 904
On this week's Curmudgeon's Corner, Sam and Ivan argue about polls. But also there is of course more Election 2024 talk. But before that, some on Hurricane Helene and more generally about disaster preparedness, a look back at the book "Big Data" from 2013, and a discussion on the need to actually pay people a decent wage. Oh, and some celebration of the team's YouTube success!
  • 0:01:50 - But First
    • YouTube Success
    • Paying People
    • Book: Big Data (2013)
  • 0:55:18 - Hurricane Helene
    • Size of Storm
    • Building Standards
    • Preparedness
    • Power Outages
  • 1:22:58 - Election 2024
    • Election Graphs Update
    • Sanewashing
    • Trump Watch
    • Other Notes

Automated Transcript

Sam:
[0:00]
Hello, Yvonne. Hello. How's your doing?

Ivan:
[0:04]
Oh, well, I'm home.

Sam:
[0:07]
Oh, that's good. It's been a while.

Ivan:
[0:11]
Yeah.

Sam:
[0:12]
So let me boop, boop, boop.

Ivan:
[0:16]
Boop, boop, boop, boop, boop, boop, boop, boop. Yeah, exactly. One thing is that I am trying something radically different today to connect. I actually noticed when i went to the link that it said that there is a riverside application for mac oh.

Sam:
[0:35]
There's a mac app app now okay.

Ivan:
[0:37]
Yes and i saw the link and i'm like wait why the hell am i firing up a browser and doing this shit i downloaded the application and i am doing it from the application right now beautiful.

Sam:
[0:48]
That like is exciting and.

Ivan:
[0:51]
Tingling what's.

Sam:
[0:53]
No i was thing exciting and new love boat.

Ivan:
[0:56]
The love boat soon we'll be making another run the love boat exactly.

Sam:
[1:11]
Exactly i'm glad you sang it and not me but yeah yeah exactly shall we just jump in and go.

Ivan:
[1:17]
Sure okay here we go Go.

Sam:
[1:49]
Welcome to Curmudgeon's Corner for Saturday, September 28th, 2024. I'm Sam Minter, Yvonne Boas here. Hello, Yvonne. Let's go.

Ivan:
[2:00]
Let's go.

Sam:
[2:03]
There you go. So, uh, high energy. Our agenda, as usual, is we're going to have a segment where we talk about non-newsy stuff first, and then we will have a couple of segments on newsy stuff. Stuff one with stuff yvonne picks and one with stuff i pick and that's the plan that's the plan focus.

Ivan:
[2:22]
For some reason.

Sam:
[2:24]
You know the the people listening to the podcast can't tell the the lot if there was a they can't i mean that would be.

Ivan:
[2:32]
You know well apparently we have.

Sam:
[2:34]
People it just it just popped into focus okay there.

Ivan:
[2:38]
You go yeah we have you know you're saying that but yet we've discovered that we have had people that are watching this.

Sam:
[2:45]
Yeah let me let me check the stats on our youtube channel which by the way youtube.com slash at curmudgeons hyphen corner we are we are now up to seven subscribers there you go only five of them have names that i can see because they've made their subscriptions public but that's okay that's fine and let's Let's see. Let's see what our views have looked like on recent episodes. Okay.

Ivan:
[3:16]
Two million views. We're getting a check soon.

Sam:
[3:20]
Yes, that's it. No. So far on this live stream, no views. Last week's episode had one view.

Ivan:
[3:26]
Well.

Sam:
[3:27]
One view. Now, of course, that only means they like looked at a couple seconds, not that they watched the whole episode. so.

Ivan:
[3:33]
It doesn't necessarily mean okay well i mean you see the streaming stats i mean i don't.

Sam:
[3:40]
And then we then we had like our our august 31st show had five views okay 24th had six i can see on the dashboard by the way the uh let's now that only tells me last week which had no view that is anyway oh oh here we here we go oh oh the summary of our watch time from the last 28 days yeah yeah yeah in hours yeah 0.0 hours.

Ivan:
[4:12]
We're doing great.

Sam:
[4:14]
We're doing it.

Ivan:
[4:15]
Our money's going to be rolling in. I mean, we're going to be rich, Sam. We're going to be rich off of YouTube.

Sam:
[4:23]
You know, the Patreon wasn't making quite enough. So the YouTube is going to like make us billionaires because like, you know, the people are just like, they can't get enough.

Ivan:
[4:34]
You know, they're going to have to just turn over their stock to us. I mean, it's just a door. yet listen you owe so much money just just look just right so you know stock used to come to these certificates you could actually endorse and give get to somebody just you know they just print the stock certificates just just you know i.

Sam:
[4:54]
Have i have a better stat.

Ivan:
[4:56]
Oh oh oh oh okay i looked.

Sam:
[5:00]
It up the top content in the last 28 days the number one was the august 31st august 31st episode which which had five views, if you remember. Yeah. The average view duration.

Ivan:
[5:16]
Two minutes.

Sam:
[5:17]
15 seconds.

Ivan:
[5:19]
Wow. Damn. Impressive. Listen, they probably just popped in. They saw how sick I looked. And then they just said, well, we're done.

Sam:
[5:33]
Exactly.

Ivan:
[5:34]
We might just get sick just by looking at them through this screen, for God's sakes.

Sam:
[5:38]
Exactly. So, you know, and I look, I do put out the little mastodon too, that says we're live, but you know, no one cares. It's okay. I mean, okay. I know the time is not, like, good for this kind of thing, you know?

Ivan:
[5:55]
Oh, well. Anyway.

Sam:
[5:57]
We could be big in Japan.

Ivan:
[6:00]
Yeah.

Sam:
[6:00]
Sure.

Ivan:
[6:01]
Yeah, yeah, yeah. It's a good time to be watched in Asia. Sure. Sure, sure. Yeah. It's ideal.

Sam:
[6:08]
Yeah. So, anyway. But first. What do you have this week, Yvonne? Something good, non-newsy?

Ivan:
[6:16]
Well, I'll say about non-newsy. I mean, it's non-newsy just because it's something that, you know, I spoke about how I had that lunch last week. Two weeks. Was it? No, yes, it was last week.

Sam:
[6:32]
You mean the award thing that you got?

Ivan:
[6:34]
No, the one that I was in Napa, where I had first guy.

Sam:
[6:38]
Oh, yeah, you talked about that last week.

Ivan:
[6:39]
He told us a story about him just being an irresponsible idiot driving.

Sam:
[6:42]
Yes, yes. You talked about that last week. Do you have an update?

Ivan:
[6:45]
That but well no no the thing is that that lunch had so many wide-ranging things and there was another one that popped up i mean that was it another stupid person well it was the same guy this guy i will say it it seemed to be kind of a dick okay and so but one of the things that and i you know probably if i gave more details people could maybe like figure out who he is so I won't. Okay, no, yeah. But one thing that we were talking at the table about a whole bunch of different things. And, you know, we were talking about.

Ivan:
[7:22]
You know, that area got hit, you know, four years ago by some massive fires.

Ivan:
[7:27]
Right, okay. Napa and, like, for example, the hotel where I stayed at, at least half of it was destroyed by the fire. They still have not restored that part. And as I was going through there, and we're talking about four years later, so many trees and so many things were damaged that there's still work going on. I mean, we were at this minery, and you could hear trees getting chopped down. That were from the fire and how they're doing a lot of work and how honestly the damage is so extensive that it's taken years and years. I mean, they are, you know, you know, I would say they're not like paralyzed by it by any means, but there's a lot of things where, okay, we cleaned up the, you did probably 80, 90% of the work, but there's still a big, big pieces that are not done. Um you know and some things that you know aren't coming back there's a there is a very big hotel near the one that we were staying called the calistoga ranch that was completely destroyed by the fire and basically the owner got paid by the insurance company and he was just like.

Ivan:
[8:38]
Fuck it i'm not i'm i'm i'm taking the money and i'm not building this again you know right it it It was that extensive. And so we're talking a little bit about just the situation going on and some stuff. You know, we were talking about about this and we were talking about for some reason with natural disasters.

Ivan:
[9:01]
I was mentioning that, you know, that this guy that we knew from a long time ago, he he he was he owned quite a number of the duty free stores in the Caribbean. And one time back in around the early 90s.

Ivan:
[9:23]
A big part of his stores were shuttered for months because a massive hurricane hit the Virgin Islands. And one of the things that we were talking about, natural disasters and the conversation coming around with COVID and PPP funds, because people, some people are talking about that. A lot of the people there were business association taking PPP funds. We're talking about what people have done. Most of the people at the table, I will, I will say that for the most part, they did good, good use of it. And even like I mentioned that we hired more people. They said, no, yeah, we did the same and so forth. So most of the people at the table were, you know, I was like, this is good. And so I was mentioning the case of this guy back in the early 90s. And I think that he went and when all his stores got shut down by the hurricanes, instead of laying off anybody, he paid everybody their salaries for months and months and months until all the stores reopened. He did not lay off one single person. in in most of these cases that's not typical i i i can assure you that most yeah you know hotels are shut down a month late they're laying off everybody they're not paying anybody a dime.

Ivan:
[10:31]
And you know it's one of those things that a few times that you had met him and this guy, i didn't realize how much money this guy had okay it's just one of those things that you You meet him and he's such, you know, he was so affable, open, helping everybody, whatever. You know, you heard about this stuff, how he went and like basically out of his pocket. He was just like, fuck this, whatever. I'm paying everybody. You know, you guys can come and help. We'll do clean up, whatever, you know, whatnot. Until we're open back. None of you guys are going to miss a paycheck. OK, I don't care. Doesn't fucking matter. OK, I'm dead. Yeah. And so we're talking about how he was and we talked about that, that kind of stuff. And so Tesla boy was complaining because he owns a Tesla boy.

Sam:
[11:19]
Being the person you talked about last week who.

Ivan:
[11:21]
Like slept and yeah, who basically had an accident who put who put a weight on his car just would go to sleep to let it drive. Okay. Right.

Sam:
[11:29]
Right.

Ivan:
[11:30]
He, he was complaining that he has the, he does deliveries under contract for a very large company in the Pacific Northwest that ships a lot of things by. Yes. Yeah. Ships a lot of stuff.

Sam:
[11:48]
I wonder who you could possibly be.

Ivan:
[11:50]
I don't know. I don't know. You know, Costco probably. And then, yeah. And, you know, he was complaining that they had made him pay his drivers more money, you know, push it up from 20 to 22 bucks, you know, an hour. And he was bitching about it. And so a few of us at the table and actually there was there was another gentleman at the table who.

Ivan:
[12:12]
How owned a massive auto dealership group in the midwest okay and he was like he was almost like we looked at him and said dude how much you think a fucking employee costs what the hell how much do you want to pay him what what do you think what are you gonna they're gonna pay their living expenses with what like 10 bucks an hour nobody can afford you know nobody can afford a damn thing you know right out of that out of that money but it was just the the the damn attitude of you know hey you're in a major metro with very high costs and you think that you can get away with paying full-time people like you know 10 11 bucks an hour and then oh by the way expect them not to steal packages and do stuff or whatever you're paying them like you know wages that they can't afford anything, you know, it's just preposterous, you know, but, but obviously there, you know, that is an attitude that thankfully at the table, most people were like, they looked at him, they were like, dude, what planet are you living on, man? Nobody can afford anything on 10 bucks an hour. And somebody had posted a sign because I've seen this already.

Ivan:
[13:24]
Multiple people like complain, oh, we can't, we can't find workers. We can't find workers. We are short on workers. And then you look at the wages that they're trying to pay, but they're trying to pay. And you're like, dude, seriously? I mean, yeah, you're not going to get anybody, you know, at that rate. I mean, I talked about how, you know, what a higher maintenance guy like right now. Basically, that's what the goal and rate is north of 20 bucks an hour. Any damn job, you know, for the most part, you want to get somebody, you know. I mean, if you're not paying at least 20 bucks an hour, it really, you know, it's not. Financially affordable for these people to work.

Sam:
[14:06]
Now this does vary by part of the country but yes in general like the what people have expected in previous decades is just no longer relevant to the no any anywhere in the country now certain certain parts of the country are more expensive than others for sure but but still like what what what's the national minimum wage is still like Like $750 or something?

Ivan:
[14:29]
Yes, yes.

Sam:
[14:30]
It's like...

Ivan:
[14:31]
But nobody gets paid $750. It's ridiculous. I mean, I've seen... The base wages that I see people get paid right now are... I mean, they start... They're north of $10 an hour, okay? But it's just the entitled attitude is the thing. You know? Right. I just... It's just... from these people. It's just always aggravating. But what I will say is that I happen to be with a number of other business owners and people that.

Ivan:
[15:06]
You know, pretty, you know, with big businesses that they were looking at. Thankfully, like most people at the table were looking at it. I was like, dude, you're nuts, you know? And so I felt relieved that it's not just me that thinks that, you know, why does it think this is nuts? It's like, you know, it's thankfully the generalized attitude is like, oh, dude, you got to pay people.

Ivan:
[15:29]
So and so i i do think that that i i i was just i realized that i was like damn it you know you you you tend to hear more of the complaining but i realized that it was a business table with about one two three four you know we're about five business people and basically four the consensus like 80 was like you know that that you know we were right that you know yeah you you can't be thinking of paying people 12 bucks an hour and expecting to get you know top-notch workers i i still will never forget i mean this is something that some guy at hp that i i will say that i had it's a conundrum to me because i had issues with him but i found out very much that he deeply respected my work okay and i i didn't think that he did but i i found out later holy shit that he He did. And I was just, it's one of those things where it's one of the last people I expected to, to, to do so. And, but one time he made this statement that I was just, my God, this is just the worst statement I've ever heard. He flat out went and said, in a meeting with a lot of people, we want to hire the best talent at the lowest possible wages. And I was just like, what? Come again? end.

Sam:
[16:50]
Well, yes. I mean, obviously you're not going to get the best at the lowest, but presumably it is, it is something competitive. Well, right. But presumably what you want to.

Ivan:
[17:02]
Right.

Sam:
[17:03]
But presumably what you're talking about is you want to optimize to get the, the, the, the peak of that curve, right? Where you're sort of your employee goodness per dollar is maximized.

Ivan:
[17:18]
You know, I will say that it's just that my philosophy with hiring people was very different. OK, I honestly, I went out and I set out to hire the best damn people I could find. And I would set out to pay them more than average. But the reality is that I usually wound up with less people on the team because I didn't believe that quantity of employees, you know, generally was a way to be productive. I figured, you know what, you give me six top guns instead of 15 average kind of people.

Sam:
[17:54]
Well, presumably this varies greatly based on the job, right?

Ivan:
[18:00]
I know, I know. Look, financial analysts. Look, you want to hire some person that, I mean, basically struggles with, because I've seen these in finance. Oh, yeah, he's got a degree, whatever.

Sam:
[18:15]
But but what?

Ivan:
[18:15]
But somebody else takes an hour because they are whatever. It takes this guy two days. What's the point of that? No, but no.

Sam:
[18:23]
But like your cashier at McDonald's. Well, you know, I mean.

Ivan:
[18:27]
It depends on the different kind of thing, but that's what I said. No, no, no, no. Not even at that. Look, let me tell you something. Same thing applies to the retail. Look, because one of the things that I that we did with what I had, like the better cashiers or the better people like at the store, you know what? They could multitask and do some other shit. OK, yeah, yeah. And so the thing is that I'm like, yeah, they could be OK. I use them at the cashier. But all of a sudden a vendor came in and they need to deal with them. If I hired the, you know, the person that didn't have the capacity to do that, they could deal with it. This guy could say, hey, I'm attending the cashier at a low point. The vendor comes in. I can check the order. I can sign it off. They can deliver it. And I can trust that person to do it. And we're not going to get screwed.

Sam:
[19:12]
The bottom line, especially these days, is the kind of roles where you really say, like, it's completely interchangeable. It's a brainless job are the ones that are all getting automated anyway.

Ivan:
[19:23]
But even though you know my whole point is that you know what you're better off getting the better talent and paying them more because a lot of people are just like ah we'll hire volume oh so we have 200 annual turnover shit you're just hiring you know you're paying shit and you're hiring bottom of the barrel they're all turning over the trainings you know you're burning so much money training and recycling people I remember.

Sam:
[19:54]
I remember a couple of years reading about, well, I think it was about one specific company, but it has occurred to more than one. Where basically because they were doing what you were saying and just rotating through people at the lowest volumes, they, they were starting to have problems because there were very few people left that they hadn't already hired and gotten rid of within their areas that they were trying to hide.

Ivan:
[20:27]
Right. You know, and so exactly.

Sam:
[20:32]
I mean, there's always more people, but But there's only a certain number that are within the geographic area you're looking for and blah, blah, blah, blah, blah. And they were just having trouble because it was like, oh, yeah, we are. You are already here and gone. And yeah, so, yeah.

Ivan:
[20:49]
I saw this at the damn copier business. OK, look, when I when I worked at Rico, dude, I mean, they there are places that had turnover that was like 400 percent, 500 percent annual turnover. You understand this, right? Right. They they basically I mean, 500 percent turnover, Sam. That means there was a team of 40 people. And basically to keep that team staffed, they basically went through 200 people in the whole fucking year. OK, right. It's nuts. OK. And yeah. And they got to a point that all of a sudden next year. Right. They'd already gone through all the fucking copier sales, but already a couple of times. All of a sudden, this asshole, they already had fired because he sucked. All of a sudden, he's being recycled through the damn thing because they couldn't find anybody else who was interested in selling fucking copiers.

Sam:
[21:36]
Right.

Ivan:
[21:37]
So, yeah, I just, no. It's a dumb strategy. I just think that you get, I think that when you make those teams that are better, the people are also better. They're more motivated. They're, they're more, you know, I mean, you know, having that kind of turnover gets, gets the moralizing after a certain point when you're, you know, when, when you're on a team and all of a sudden by in six months, you don't know anybody who was already there.

Sam:
[22:05]
Yeah. Well, and like you said, too, below a certain level, it's just like, you're not going to get anyone anyway, because no one can live off it. It's not worth the amount of time. Like sometimes you're not even paying them enough to pay for the cost of getting back and forth to work.

Ivan:
[22:23]
Yeah. I mean, that was literally a problem. That was literally a fucking problem. Yes.

Sam:
[22:28]
And so you have to adjust. I mean, and, you know, minimum wage conversations aside at this point, because we haven't raised the minimum wage, the market is taking care of it.

Ivan:
[22:41]
Oh, yeah, the market's taking care of it because it's ridiculous because it's just – I mean the minimum wage is just not possible.

Sam:
[22:49]
But even there, you do have – if you had like a set minimum wage that was thought about more, it might be a little bit higher than the going rates because you still sort of have a little bit of – for these employers who aren't thinking the way you're talking about and are just like, let's get the cheapest we can possibly get.

Ivan:
[23:09]
Well, they're trying to pay $11.12 an hour and they're like.

Sam:
[23:12]
There's always sort of a race to the bottom where there's, yes, at a certain point you won't get anybody, but you can get pretty low and still get sort of the most desperate of the desperate, you know, and, and that's not serving anyone well.

Ivan:
[23:29]
No, it's not. So, so anyway, so I, I just, you know, it was just, I realized that that for whatever reason that that, uh, the conversations that that table got pretty. We talked a wide range of things. It was just, I didn't expect that. I mean, you get set to sit at the table, you get assigned with people. And I, I did have my brother and my, my, my, and my sister-in-law at the table, but you get assigned like 10, 12 random people. And you, you're like, you know, you don't know what the heck you're going to find out. I mean, I found, I sat down with this other guy who I did have a lot, a lot of, a lot of fun with who, you know, confessed that he was there separated and he was like going on his fourth divorce. And I was like, Oh shit, your fourth divorce. Son of a bitch and then you know he was pretty drunk when he told me the next day we were making fun of him like shit i told you that yes you did so we had a lot yeah we but but i i will say that, being i was forced a little bit to like interact with people that i that i don't know which that is always harder i mean i'm good like a lot with people i know but i mean i i will admit that with with new people it's a little bit of a thing but i actually had a great time excellent so so there you go all right so sam what are we movie book book yeah and and also i will say not an audiobook a real book with you know like well or at least in digital form.

Sam:
[24:55]
Yeah this one i read on a kindle.

Ivan:
[24:57]
Okay all right but.

Sam:
[24:59]
I i do i do just say it's a book when i finish an audiobook i i mean i don't.

Ivan:
[25:04]
Well, no, no, no, they're books. I just, just checking which, which format is it in?

Sam:
[25:09]
This was a digital ebook on a Kindle.

Ivan:
[25:13]
Okay.

Sam:
[25:14]
And before I get into the book itself, I will say also, this is the last item I actually have on my backlog of media right now. Now that does not mean it's the last thing I've watched or read. Cause see what I do is like every two to three months. Okay, like, first of all, when I finish something, when I watch a movie, when I finish a TV show, when I finish a book, I take a screenshot on my phone. To commemorate the fact that I have finished the thing. And then once every two to three months, I go through all the screenshots and log them onto my wiki page and onto the backlog for curmudgeons corner. So at the moment it has been, let's see, I've got, uh, let's see, log.

Sam:
[26:05]
It has been 18 weeks, five days and 22 hours. Since the last time i did that okay so so anything that i have finished in the last 18 weeks isn't yet on my backlog list for curmudgeon's corner so like i don't off the top of my head know what's next after this book eventually i will go through and do this and the problem is when it gets to 18 weeks like the way i do this like okay my phone has lots and lots and lots and lots of images and things of various sorts on it including my son alex likes to take the phone and then just do like dozens of pictures of things he's eating and random crap like that with your phone not not his He'll do it with his phone, too. But if his phone isn't handy, he'll grab mine.

Ivan:
[27:01]
Oh, God.

Sam:
[27:02]
Okay. I, I, one of the reasons he has his own phone is so that he can do this stuff on his phone and not clog up my phone with these images.

Ivan:
[27:12]
I get that.

Sam:
[27:13]
Of course I, I, I, and I never delete anything. So they're all there. So like, I literally, when I go through this process, I'm opening up my photos app and going back one picture at a time and saying, is this a screenshot of something I read or watched? And so like, I have to go back through like 10 or 15,000.

Ivan:
[27:32]
Pictures. Yeah, so, okay, I'm sorry, but so you don't know that the phone automatically creates a folder with your screenshots.

Sam:
[27:39]
Right? Well, they're not all actually screenshots. Like, if something comes on TV, because there are two things I do here. Okay, no, no, no.

Ivan:
[27:49]
This is screenshots first. I'm just playing.

Sam:
[27:51]
Yeah, no, you're right. I said screenshots. screenshots generally speaking when i finish something it is a screenshot but i combine this process with the algorithm i use to add additional things to my list ai so for instance we need ai for sam sam it's ai yeah just just for example like if if i see an article well articles can sometimes be screenshots so let's if i see something on tv where like yeah they're interviewing an author of a book and I'm like, oh, okay, that sounds interesting. I will point my phone at the screen and take a picture of it.

Ivan:
[28:29]
Okay.

Sam:
[28:30]
And so then, so as I'm going back through this list, it's like only a very, very small fraction of what I'm logging are things I've actually completed. Most of it is books or movies or TV shows that I'm like, oh, that's interesting. I will add it to my list.

Ivan:
[28:48]
Okay.

Sam:
[28:49]
Does it, does it, does that make sense now? know.

Ivan:
[28:51]
Uh yes it does.

Sam:
[28:52]
I mean i know i'm insane but like well you understand but you know yes and for the for those of you who aren't on video yvonne is playing with the the ios slash mac auto reactions we're like what are you talking about i.

Ivan:
[29:07]
I wonder what i mean me i'm not i'm not doing anything i don't know what's going on over.

Sam:
[29:10]
Yeah yeah so so like on the video there's like balloons and thumbs up icons and all this kind of stuff i mean i don't know what you're Yes.

Ivan:
[29:18]
I don't know what you're talking about. I mean, anyway, anyway.

Sam:
[29:21]
So anyway, with all of those preliminaries out of the way, the book of the week that I finished in May is Big Data from 2013.

Ivan:
[29:35]
Big Data. Or 2014.

Sam:
[29:39]
Okay, so the author of this, let me bring it back up. I had the stupid web page up a second ago. Oh, here we go. It is by Victor Meyer Schoenberger and Kenneth Kukier.

Ivan:
[29:58]
Okay never heard of these people so what okay question.

Sam:
[30:01]
So this was this why why did you wind.

Ivan:
[30:04]
Up reading this book.

Sam:
[30:05]
Oh i don't know i like sometime many decades ago like i i saw it and was like many decades.

Ivan:
[30:13]
Ago it was only 11 years ago so that book came out.

Sam:
[30:16]
Okay i will i will tell you exactly it was added to my list on april 24th 2013 okay.

Ivan:
[30:23]
So yeah uh when was the book written.

Sam:
[30:25]
And and actually the i i have a note here uh-huh it was added to my list because i saw some random person on twitter mention it.

Ivan:
[30:34]
Okay there you go all right so that was it okay.

Sam:
[30:36]
But but actually i remember at the time this book was kind of like lots of people were sort of talking about it and stuff um i kind.

Ivan:
[30:45]
Of remember having heard it being mentioned yeah.

Sam:
[30:47]
So now normally when i do these things like if it's a movie i'll bring up the wikipedia page and i'll read the quick summary of it and then talk about it. There was no Wikipedia page for this book and the sort of Amazon listing was sort of like lame. So I have, as you just suggested a few minutes ago that I asked chat GPT to give me a two paragraph summary of this book.

Ivan:
[31:14]
Wow.

Sam:
[31:15]
So I'm going to read that to you and then I will discuss my thoughts on this book.

Ivan:
[31:19]
Okay. All right.

Sam:
[31:21]
Can I make these bigger? Okay. Big data, a revolution that will transform how we live, work, and think it, you know, it's both Amazon and this say it was 2014, but I had a 2013 date. I don't know. Maybe it is the difference between paperback and hardcover, or maybe I put it on my list in 2013, but it wasn't actually out till two, whatever. It doesn't matter. Anyway, by, by Victor Meyer Schoenberger and Kenneth Kukier, explores the profound shift brought about by the emergence of big data, analyzing vast amounts of information to uncover patterns and insights that were previously undetectable. The authors argue that the rise of big data is changing the way businesses, governments, and individuals make decisions, moving away from traditional small-scale analysis to focus on correlations within massive data sets. This approach allows for new predictive capabilities, even if it sometimes sacrifices understanding the why behind certain phenomena. By leveraging big data, organizations can optimize operations, forecast trends, and create more personalized services, ultimately reshaping industries. However, the book also warns of the potential risks and ethical challenges associated with big data. Big data. Meyer Schoenberger and Kukier. I don't know if I'm pronouncing that right. Kukier. Whatever. Cookie Monster.

Ivan:
[32:50]
Yeah. Okay. Whatever.

Sam:
[32:51]
C-U-K-I-E-R. I don't know if I'm pronouncing Schoenberger either correctly. S-C-H, the O with the little dots over it, N-B-E-R-G-E-R.

Ivan:
[33:03]
Sounds good to me.

Sam:
[33:04]
So discuss issues like privacy erosion, data ownership, and the danger of blindly trusting algorithms without human oversight. Gee, I don't know.

Ivan:
[33:19]
Yeah. It's amazing.

Sam:
[33:22]
Wonder what? They stress the importance of developing legal and regulatory frameworks to manage these risks while encouraging innovation. Despite the challenges, the authors believe that big data holds immense potential to revolutionize society, though it must be approached with caution to avoid unintended negative consequences. Now, that's the summary. This was from 2014. Obviously, things have moved quite a bit since 2014.

Sam:
[33:50]
I'll say, actually, it mentions that they talk about the risks. I actually like got the feeling while reading this that the section about risks was sort of thrown in like, oh, we got to talk about the risks, but it was mostly cheerleading. You know, it was mostly like, hey, this is going to be awesome. We can do all this stuff. And they were talking about all kinds of examples that were already at play. And while they did talk about risks, I feel like they, they sort of hand waved away the risks saying, oh yeah, but we can deal with those. And I think that there are a lot of places, even before we talk about AI, which obviously this gets into, but even before you get to that, there are so many places where they were saying things like, look, we don't have to worry about every example being correct. We just have to, on average, do a good job with all of this data and have it be, And often we can get better results than looking at all the stuff individually because you just like doing sort of statistical sampling. One of the primary themes of the book is like, you know, in the past you looked at individual examples and you did statistical sampling and you did detailed analysis of the statistics and you came up with conclusions. And they're like in the big data world, you don't have to do that sampling. You can actually look at everything.

Sam:
[35:18]
You don't have to sample. You just look at all the data and make some conclusions based on it. And then often this data is very noisy. It's often dirty data where some of it's incomplete or you don't have it. But it's still the sheer volume of it often makes it better than your sampling anyway.

Sam:
[35:42]
I actually saw it like, we'll undoubtedly talk about election polls later. I actually saw someone, an article, man, I only scanned it. I didn't read the summary and I didn't share it. So I'm not going to be able to find it. But there's a new firm that's trying to do election forecasting. And apparently they've gotten some elections already correct with accuracy unknown in the polling world. They forecast an election and gotten it right within a couple hundred votes. Like not just, and their methodology rather than polling people is just take the census data, model little AI agents for every person in the, in the census based on everything they can find out about that person, their demographics, their family, all of this information. And they make a little AI agent that tries to simulate being that person and predict how they're going to vote and whether they'll vote.

Ivan:
[36:45]
And whether they'll vote, because that's one of the most important things, right?

Sam:
[36:48]
Yes, whether they'll vote and if they vote, who they'll vote for. And apparently they've gotten some insane accuracy in some cases. And so this is an example of that kind of thing. But basically the idea is just look at everything. We've got the data now. You can just look at everything. Forget sampling and looking at this stuff.

Ivan:
[37:07]
I mean, this is something that's been going on in a whole bunch of different industries where... You've got so much more data from different sources now that you can, that it's, and it's not about, you know, correlation is not causation, okay?

Sam:
[37:25]
Right, but one of the main arguments that this book made was correlation is not causation, but it doesn't matter. You can make decisions based on the correlation.

Ivan:
[37:35]
No, but the thing is that it's not, it's not, to me, it's not so much about correlation. I think that the thing is about how you are able to synthesize a number of data points across from different sources and to understand what is happening a certain point in time. So, you know, for example, I was reading about retail patterns. Right. And so, you know, you correlate weather, you correlate temperature, you correlate how many people are coming in, what areas they are buying. The demographics of that person and you correlate those a certain time and and and there is a whole bunch of data that then allows you to predict what purchase patterns are going to happen on certain days and why and what and what products are going to sell more and which less man same thing i mentioned this airlines for example that one of the oh yeah.

Sam:
[38:30]
They they had a bunch of airline examples in this book they had a whole bunch other but like what one of the key elements in that is is the prediction doesn't have to be exact. Like you don't, like you can say that this thing is going to be, you know, rising and that you can take action on that. And it can be a probabilistic forecast. And that is still something that's actionable. Yeah, and you can get out of all this data. And so, I mean.

Ivan:
[38:57]
But there are things that correlate that do have effects. So don't get me wrong. It's not that. It's just that you can't automatically assume that you have to like, Go and double check that, you know, that, that, that the relationship is, there is a causal relationship and, you know, that, that.

Sam:
[39:13]
That happens, but it's. But again, one of the, one of the things in this book that they tried to argue, and I, I'm not sure I 100% buy it. I found myself a lot of times saying, come on guys, is that basically they were saying, look, proving causation is just too damn hard.

Ivan:
[39:33]
So don't even try if you've got the correlation go on it no no that's bullshit no no that that's ridiculous and it's not that you have to prove it it's not even that it's hard it's it's.

Sam:
[39:44]
That what they were arguing is it doesn't matter you can.

Ivan:
[39:47]
I don't agree because there's been so many times that i've seen people do stupid correlations on shit okay i mean i i bullshit i've seen this is so over and over and over. I mean, where you get these dumb correlations that make, you know, that you think work, but it's just then all of a sudden something breaks it like badly and then you realize, oh, they really weren't connected, huh? You know, you have to go through a lot of modeling and a lot of testing to make sure that that data pattern, the way that it's happening is related. And it's not just, you know, it's not just a coincidence. So I don't think.

Sam:
[40:25]
So, so there's, there's a famous website called spurious correlations. If you Google spurious correlations, you'll find it. It lets you pick like random things and it just finds things that have been correlated with. That aren't real. So I just hit the random button. So here's an example. From 2004 to 2022, the consumption of butter correlates to the amount of wind power generated in Lithuania very strongly. Okay. Viewing random. Here's another one. The popularity of the dumb ways to die meme correlates very strongly from 2006 all the way to 2022 with the number of electronics engineers in the state of Utah.

Ivan:
[41:14]
Ah, okay.

Sam:
[41:16]
One more, one more. um from 2002 to 2022 the number of public students in ninth grade yeah as a from the national center of education statistics correlates yeah i'm looking at the graph they line up like nearly perfectly with the stock price of bank of america, so you know now yeah you could take this and be like okay so let me do some demographic projections on the number of students that are going to be in ninth grade the next few years and based on that decide how much how much bank of america.

Ivan:
[42:02]
Is going to be worth yeah well good.

Sam:
[42:04]
Luck with that investment strategy okay all.

Ivan:
[42:06]
Right look yeah so anyway so all right.

Sam:
[42:10]
What are you going to give this book? What's your rating? Let me finish a couple thoughts. A couple more thoughts. Sorry, sorry. Throughout this whole thing, of course, this was like 10 years ago, the parallels to what's currently going on with AI development were obvious. The AI development, especially LLMs, are just taking this to the next level. They're sucking up huge amounts of data. They've got complicated algorithms trying to pop out conclusions for that. I summarized the damn book with an AI at the beginning of this. And even more sophisticated, or I shouldn't say more sophisticated, even different models that aren't LLM-based also are just, they feed on the massive amounts of data in order to make their conclusions. And I think the same thing is true here, where I think there's still the underestimation of the problems. Problems it's it in both of these cases both 10 years ago and now with ai it's like everybody's so excited about the thing and willing to run with it that there's the amount of.

Sam:
[43:26]
Just pause and slow down a little bit to make sure what you're doing makes sense and isn't harmful is for the most part getting thrown by the wayside and and maybe we'll get lucky and there's nothing really horrible is going to come of it and it's all going to be wonderful. I mean, I I'm, I'm at this point using various AI tools on a regular basis for one thing or another, and they are saving me tons of time and they're useful, but you know, I don't know. I feel like it's just the, the main thing about this book. And I think about a lot of the AI talk right now is there is so much cheerleading and, About how wonderful this is. And yeah, the skeptics are definitely making noise too, just to be clear. But the industry as a whole seems to just be like full speed ahead. This is a gold mine. Let's go.

Ivan:
[44:22]
And why, and why is that Sam? Why is it?

Sam:
[44:27]
Because it is undoubtedly true that there are going to be people making fortunes off this shit. Now it, Now, it may well crash after that, but in the meantime, there are people who are, you know, exactly like, you know, for all of these things, you know, I mean, the same thing has been said about a whole bunch of different phases of things. Like the most recent before this was crypto where everybody was like oh everything has to be crypto let's jump in with crypto on two feet and that is mostly faded out at this point let's see if it comes back but most most of the hype around that is like in hibernation at least at the moment i mean crypto is still around.

Ivan:
[45:14]
But it's not.

Sam:
[45:16]
Oh no i know i know i mean i know and.

Ivan:
[45:18]
And one of the the things and the biggest problems is that crypto has not proven to be a.

Sam:
[45:24]
Actually useful.

Ivan:
[45:26]
Well it's not an easy trend easily transactable medium of exchange.

Sam:
[45:30]
Right right right right and then.

Ivan:
[45:33]
And then the other thing is that one of the things that they were trying some people the idea was oh it's it's anonymous it's private it's not centralized and actually here's the reality it isn't at all.

Sam:
[45:46]
Yeah because everything is stored in a public fucking public blockchain that people can access that's right well and the thing is like and there's always leakage that can tie you back like the fbi has now gotten really good at figuring out who actually owns various wallets on blockchains and stuff like that uh it's not so that's why Yeah.

Ivan:
[46:10]
But yeah, that whole anonymity thing is all bullshit.

Sam:
[46:14]
But my point is, I used crypto as one example, but you have these hype cycles every few years where some new technology is going to be the big new thing. And sometimes it works out. Sometimes it's a bubble. You know, sometimes it's not. I mean, and even like going back to the original Internet bubble, right? Like that initial bubble popped. but at this point the entire damn world is built on that.

Ivan:
[46:41]
Anybody gonna question the value of a lot of this stuff? I mean, look, we talk about delivery of merchandise or whatever and one of the biggest flameouts that happened at that time was Webvan you know, which you know, they, well they were investing billions in warehouses and they never were able to monetize it or whatever, what a mistake that shit was never gonna work well.

Sam:
[47:05]
Yeah well now look well yeah i mean nobody can live.

Ivan:
[47:09]
Without their delivery of anything i mean you.

Sam:
[47:12]
Know a common phenomena in these cycles going going back hell all the way to railroads and stuff probably even earlier is that the first movers actually don't automatically they're not the winners they're not the winners they build out a bunch of infrastructure and go bankrupt and then the people who come in in the second wave and can build off of that they're the ones who end up being the the big the big money makers who become monopolies and all this kind of stuff i still remember.

Ivan:
[47:41]
What i still remember one of the greatest examples of that was in latin america during the 90s there was this huge investment surge in by telecoms across latin america.

Sam:
[47:54]
Yep i remember you using the example before and.

Ivan:
[47:56]
And they they invested heavily in whatever and man And I mean, there was this massive bankrupt flame out. You had Global Crossing, OptiGlobe. There was Bell South, Latin America. And all of these companies sold everything for pennies on the dollar. And Carlos Slim in Mexico scooped them up all on pennies at the dollar. And right now, Carlos Slim is one of the top 10 richest people in the world.

Sam:
[48:25]
Right. And so, anyway, to the rating of the book, I'm actually going to give it a thumbs up, even though it's like a decade old, because it's thought-provoking, and it has the interesting...

Sam:
[48:39]
Dual nature where on the one hand they're talking about examples where you know what's happened because it's like 10 years of history have gone past that so you know like in some cases where they're being very optimistic about what's going to happen and you know oh well that flamed out that didn't actually work out because because of xyz whereas these other things did work out And meanwhile, the parallelism to what is now going on with AI is completely obvious because AI is just taking the same big data mindset and moving it to yet another new level. So I'm giving it a thumbs up like it's interesting because you get that history you see what they're talking about and know what they got wrong wrong and right but also it is still relevant to this new cycle of stuff that's going on right now so thumbs up it was I liked it I enjoyed the book it was it was worth the read I should mention as usual like this is one of the things that And by the way, I read this out loud to Alex, like I do with all my books now, and only occasionally, every once in a while, reading for like half an hour, but not on an everyday basis or anything.

Sam:
[49:59]
And so this book, which was 244 pages long, took me 271 days to read, so 0.9 pages per day was the rate at which this book was read.

Ivan:
[50:11]
Well, there you go. There you go.

Sam:
[50:13]
And it's, I will also say like, you know, sometimes when reading books that are nonfiction, like to myself, I can find myself like reading a couple of pages and then going back and saying like, what was that again? I have to go back. Cause I, my mind started to drift and I was still reading. Yeah. Reading things out loud, every word, actually helps you stay paying attention to what the hell you're reading.

Ivan:
[50:43]
That's very slow, though.

Sam:
[50:44]
It is. Oh, even that, I will add one thing. My son is like the mini version of me and insists on being a completist, which means we also read every word of the bibliography index and footnotes.

Ivan:
[51:04]
Oh, fuck you guys. Fuck all of you. Jesus fucking Christ. God damn. Jesus. Fuck.

Sam:
[51:13]
Every word out loud. Reading the bibliography and the citation of like such and such book, page 46 through 47.

Ivan:
[51:22]
I recognize the pattern.

Sam:
[51:27]
Okay. Let's take a break and then talk newsy stuff. This is another Apple dream. Oh this this is abel dream 41 it is a little bit long it is it's like three and a half minutes so just a heads up warning for those of you don't like them you can fast forward yvonne is going to have to suffer through it so here we go i'm i'm hitting i'm hitting play, hold on i hit the button wait oh let me maybe this button.

Break:
[52:02]
Okay i don't like this dream at all, myself alex brandy and our dog jetski we're going to a park and we were gonna it was more park with like a lot of walking areas than like playgrounds and stuff.

Break:
[52:24]
But we turned a corner and i saw a bear it was a black bear so i'm like bear bear bear and i'm motioning for everybody to turn around and we all turn around and as we turn around a much bigger like grizzly bear kind goes running by now there's like a little fence between us and where the grizzly bear was but it was one of those like wooden slat fence not slat you know where they They put the little pieces of wood, like, next to each other and little things. Anyway, the kind you could get through easily. Like, it's... You could jump over it or somebody could get through it and we're heading back to the car, and trying to like the bear is still a little bit of ways and then we're like where's jet ski, and then we see like two bears off in the distance tossing something and we're like oh no jet ski got between the two bears and we make some loud noises and the bears run away but we go to get jet ski and his whole back half isn't working right he's still alive though and so then we're.

Break:
[53:32]
Like rushing to get him back into the car like I pick him up and like taking him back to the, trying to take him back to the car like I didn't fit I am like I don't know if I'm supposed to move him but I have no choice and I was picking him up and my wife was on the phone trying to figure out the right place to take him and whether our pet insurance would cover like being mauled by a bear.

Break:
[54:01]
And Jetski was still breathing but felt like he weighed like two pounds and he's a 150-pound dog.

Break:
[54:10]
And we get him to the car and we're trying to get him into the car. And someone who was in the way getting in the car and I yelled at them and I apologized for yelling at them and was like, but my dog. And as we're getting I think Randy was finding out that this kind of thing was not covered by insurance so we'd have to figure out the money things and it wasn't clear to me if Jet Ski was going to make it but he was struggling he fought against me he didn't want to get into the car I guess he wanted to go back to the Bears or something I was very upset, very worried, this was not a good dream, And then I woke up, and it was one of those where I was very, very relieved to discover that this was a dream, and it was not really happening. So, yeah. I'm gonna go find my dog. Well, no. He's asleep downstairs somewhere. I'm gonna leave him alone. I apologize. Going to go back to sleep in a second. Bye.

Sam:
[55:17]
And that's it.

Ivan:
[55:19]
You know, recently, I had a dream for some reason that my wife and I were in hand-to-hand combat with ninjas.

Sam:
[55:28]
Oh, okay. Yep.

Ivan:
[55:30]
And by the way, you know, at least we were kicking the ninjas' ass.

Sam:
[55:36]
Oh, good job. Okay.

Ivan:
[55:37]
We were repelling the ninjas. And i woke up and i'm like okay honey yeah you know hey apparently we're under ninja attack apparently we we're gonna kick their asses good.

Sam:
[55:52]
Job i mean it's your your training has paid off.

Ivan:
[55:55]
The training has paid off yes absolutely so anyway so i i don't know what that means but anyway all right so uh on to the things uh yeah let's see what do we want to cover first yeah.

Sam:
[56:07]
It's yeah Yeah, it's your pick first. I can do the traditional, like, I'm doing all the election stuff in my segment if you want to cover other stuff now. Or shake it up. You can do election stuff. I don't know.

Ivan:
[56:20]
Now let me see. I'm looking at what we've got here. Well, I had made some notes. So we've got Hurricane Helene. Yeah. So, you know, one thing that I didn't realize about this hurricane, And that was the discussion about this. And the storm was very large in terms of the wind area that was covered. It's not that it doesn't happen, but most hurricanes, usually the wind field itself is relatively small. So it only affects a pretty relatively narrow band around the storm. But in this case, I mean, the winds several hundred miles away were tropical storm winds. This was a very big storm, and it caused a lot of storm surge all across the west coast of Florida, and actually some difficult weather conditions even in the east coast of Florida.

Ivan:
[57:20]
The airports were impacted with a lot of delays and difficulties. The winds and the strength of the winds was pretty stiff, and the thing is that you had pretty strong steady winds, but you had very strong gusts, okay? And coming from the south, most of the runways at airports in the Florida east coast, whether it's Palm Beach, Fort Lauderdale, or Miami International Airport, have east to west running runways, okay? Okay. Except Miami, that does have a crossing runway, okay? Okay.

Ivan:
[58:00]
There is a lot of videos online of airplanes trying to land with what were crosswinds at about the maximum, you know, close to, you know, the maximum crosswind that you're allowed to land. Right. Struggling to do so. Okay. And a lot of flights got canceled. And Miami Airport did not gamble with that and was just using the crossing runway, which made the crosswind vector lower, but it limited then that you had an airport that normally operates with three runways down to one for both takeoffs and landings, okay? I saw some bigger airplanes say, fuck it, we're going to do it. So I did see that an A380 landed on the east-west runway, and they were like, fuck it. The Lufthansa was like, you know what, this beast will do it. Whatever. We're fucking, we're putting this thing down. But I happened to have been flying back yesterday from Puerto Rico. And it made it that it took what an approach to Miami. Once you're once we're inside of the airport, you'll be touching down in like 10 minutes. Max. All right.

Ivan:
[59:20]
We spent about almost 50 minutes to land because. Yeah. Since they were only using one runway, they had to make this massive line of airplanes that was stretching all the way to central Florida in order to make them, you know, line them up. You know, oh, you have to. It's like, listen, you have to go to the back of the line. Well, the back of the line kept getting longer and longer and longer and longer and longer at the airport. I kept going, and I'm like, how fucking far are we going away, for God's sakes? And yeah, it was like the furthest away I've ever started an approach into Miami International Airport ever in my life. And I will say this again. Also, that was one of the bumpiest fucking landings I've ever made at Miami International Airport in my life. Because even with the fact that we were on runway 12, the winds were coming from 180, 190 around there. That was still a strong fucking crosswind that was gusting up to 40, 50 knots. And that was a ride to get in. People on the plane were a little bit unnerved. The landing was hard, okay? And so that was going on. on in the west coast of florida the storm surge from the storm yeah let's just talk.

Sam:
[1:00:48]
About the actual start like enough about your plane stuff like those were.

Ivan:
[1:00:51]
Fine but well well yeah in the end it was fine but there was obviously a lot of people but but you know that was my my but my personal experience of the but but but the thing is that this was like hundreds and hundreds of miles away usually when it's that far away it doesn't fucking matter right and this thing was was so far away, and we're getting the effects of this thing, and I was like, holy shit, what the hell? But, man, you know, the storm surge was brutal, that they had all across the west coast of Florida, a lot of different places, and, This is the third major hurricane that has hit the panhandle in the last 13 months. Right. Okay.

Sam:
[1:01:35]
And this was by far the biggest of the three.

Ivan:
[1:01:38]
Yeah. And I mean, it's three of them. And one of the damn things about the panhandle and that area in northern Florida, which always just made me nervous. And I said, I'm never fucking buying a house in this area because even like newer houses there are not built to withstand even a cat one cat to hurricane.

Sam:
[1:02:05]
You know, this is this is what like you can understand maybe for like something built a long, long time ago. But new construction. Come on. There's no excuse now.

Ivan:
[1:02:17]
And there is no excuse. I went to, I had some friends or neighbors that moved to Jacksonville. They bought a new house over there. They moved up there because to be fair, it was a lot more affordable than now here. And I, and I get that. And the house is beautiful. But then I realized I'm looking at the fucking house. It's all wood. All the walls, every, I mean, yeah, it's, it's, it's just a poor, it's a concrete slab at the bottom and the fucking structure is all wood. I'm like, fuck this thing in a cat three cat four hurricane. It's like, you know, say bye bye, say bye bye to this fucker. It's not surviving this is a new construction in the last three or four years and so i'm like going i'm like what the fuck is with this shit and so you know they were showing videos of these communities they got wiped out and you see that every single fucking house uh you know was not elevated to accommodate for storm surge was made out of materials that basically like the bit wolf could have blown them down and i'm just like you know, what the hell people it's just i i mean it's like i don't and and and you know i know that a lot of those historically have been there for a long time people anything about it but i just always felt it's like i mean look you've had so many big hurricanes hit that area and i'm just like now there is a stat recently i saw that in florida right now of residences and a lot of these i assume are paid for because there are a number of these 25 of homes right now are completely uninsured. Okay.

Sam:
[1:03:44]
That's crazy.

Ivan:
[1:03:46]
Yeah. They're completely uninsured. So they basically, you know, they are running the risk that if they get hit by a, by a hurricane, they are out there. They're not going to have any, I mean, they're not going to have the resources to rebuild at all. And, you know, or.

Sam:
[1:04:02]
Or anything or anything, it's not, it's not just a hurricane. Like there are There are all kinds of things that could happen.

Ivan:
[1:04:07]
A fire, you know, yeah, absolutely. There's a lot of a lot of other things that could happen that that would wind up, you know, leaving them homeless. Yes, absolutely. So I, you know, this this state has been suffering through a series of issues related to insurance issues. The governor basically has just not really done anything about it. You know, the governor, obviously, right. Yesterday, I see him. I don't understand what, you know, there's another narcissist jerk off. Who the fuck wears a shirt with their name on it? Like, you're not even running for campaign right now. He was like with a sweater vest that has his name like printed in big DeSantis like here. Okay, like on his chest. chest.

Sam:
[1:04:58]
You know i.

Ivan:
[1:04:59]
I'm sorry to.

Sam:
[1:05:00]
Be fair i i have seen like i i've seen like.

Ivan:
[1:05:06]
Who who i i mean he's not running for re-election right now sam he's not running for president not running for re-election it's not like it's more like a it's.

Sam:
[1:05:14]
More like a name tag right.

Ivan:
[1:05:16]
No no i mean i know.

Sam:
[1:05:19]
It's embroidered but it serves that function right.

Ivan:
[1:05:21]
No i don't think so no no no i i don't think so i.

Sam:
[1:05:27]
Know all my clothes say sam you.

Ivan:
[1:05:29]
Know actually that would look nice i'll get you a nice little you know get a nice little sweater it says sam or.

Sam:
[1:05:38]
My logo my little abelsmay logo.

Ivan:
[1:05:40]
You know i get that on all my clothes yeah or an apple yeah that's another one i mean i get it i mean i work if you work those are those of you listening.

Sam:
[1:05:48]
Cannot see right now but ivan is currently wearing.

Ivan:
[1:05:53]
Something with.

Sam:
[1:05:54]
All kinds of corporate logos all over.

Ivan:
[1:05:58]
His shirt yes you know yes i am yes i am now it's.

Sam:
[1:06:02]
Who's it's who's uh paying for him.

Ivan:
[1:06:04]
Yeah so it's me these are these are my corporate sponsors right now they're paying the bills yes absolutely you know i got ubs securities crowd strike of course crowd strike you know they're paying for their i mean you know we we had we we had the tapes so they basically had to pay us you know on on how they screwed it, everybody. So anyway... I it's just the thing is that this bastard is going out there just doing some more self-promotion. I guess maybe he's going to think that he's going to battle like take Marco Rubio Senate seat or some shit like this. I don't know who the hell knows. Maybe I mean, maybe. And, you know, he hasn't done anything about the fucking insurance insurance issue. He keep doing he keeps talking about climate change doesn't exist. You blah, blah, blah. Then he talks about resilience. He gives some money. But it's just that this guy just, he builds up straw man. He fights against them, but he doesn't fix anything. And the, and the insurance issue has been one that has, you know, dragged on and on. It's not fixed. You know, our premiums here are up 300% in the last five, six years.

Sam:
[1:07:16]
And part of this, we haven't said the words yet, but like this, there's a climate change component here.

Ivan:
[1:07:23]
Yes, and that's what I was saying.

Sam:
[1:07:25]
Storms are getting bigger, they're getting more frequent. Not every year. It's all statistical.

Ivan:
[1:07:34]
Here's the thing, we haven't gotten hit with them down here in South Florida, but the reality is that, you know, Down here, we're way better prepared than they are up there, okay? And unfortunately, the guys that are getting hammered with three of them in the last 15 months, there's a place that's way less prepared and the one that least believes in this being real. I mean, that's the problem.

Sam:
[1:07:58]
Well and the thing is like you know without without interventions of some sort it is very possible that certain areas it just doesn't make sense to rebuild and so insurance companies aren't going to want to voluntarily do business there because it's like we're not going to make our money back because of course this is going to get screwed up again sooner rather than later right Well.

Ivan:
[1:08:27]
It's like what I was mentioning earlier about the guy in California, though, because of the wildfires decided to just not rebuild.

Sam:
[1:08:32]
Yeah. Yeah.

Ivan:
[1:08:33]
You know, the mitigation that he had to do in order to ensure that he wouldn't get damaged again that way was so much. And part of the reason why the hotel was staying is still only half an operation is because of how much work that will take in order to do it. They're planning on doing it, but it's been four years of work and you're still not there yet. Yet so that is that is a that is a big issue and over here you're just not getting in a lot of places that stuff done it's just not happening this government isn't putting a focus on that or a priority because one of the things that you would have done already if you really took this seriously was upgrade the building codes right you wouldn't allow those damn house new houses that are being built, you know, out of.

Sam:
[1:09:25]
Out of regulation is bad.

Ivan:
[1:09:29]
Yes. That's the problem. Regulation is bad. Yes. All regulation is bad.

Sam:
[1:09:34]
No, but yeah, I think you're absolutely right. Like it, it's, it's one of those things where you're, you have to make a decision at some point that says either you take vast swaths of land and say, this is not actually inhabitable.

Ivan:
[1:09:48]
Yeah.

Sam:
[1:09:49]
You You can't live here. Maybe, maybe you could visit, make it a national park or something, but like, you're not going to build houses and stores and all this kind of stuff in there. Or you put requirements in place that say, if you're going to build here, you're going to build in a way that will survive any reasonably expectable event that might happen. And this goes for other parts of the country too. I mean, where you are, it's like hurricanes and stuff like that. In other places, it's the wildfires. In other places, it's earthquakes. In other places, it's landslides, whatever. But, you know, just saying like, hey, there are dangers in this spot. If you're going to build here, you have to account for them.

Ivan:
[1:10:36]
Right. And, you know, and if you're going to build there and despite the fact that we said no build, well, then, you know what? You get destroyed. It's your shit out of luck. You're getting nothing. I mean, forget it. I'm sorry, but I just we just can't, you know, the problem is if they build new, if they build new. What I'm saying is after a disaster. I mean, I get that certain people, you know, I've lived in some places that right now are 40, 50 years.

Sam:
[1:11:03]
Yeah, there's a difference between historical things and new construction. But even then, there's also the flip side of that, right? Like if you make new construction more expensive, then you're pricing certain people out of the market. And then what do those people do?

Ivan:
[1:11:15]
The thing is that the thing is that there are construction methods in order to build these, you know, that are more resilient, that don't add that much to the cost. But, you know, especially when you're talking about, man, we're not talking about $100,000 houses. We're talking about houses worth $450,000. Look, I bullshit.

Sam:
[1:11:36]
They're just goosing. They're just goosing. But you also you have to also talk about the apartment buildings and things like that. And maybe maybe maybe you shouldn't have trailer parks at all, you know, but like if you're going to build that.

Ivan:
[1:11:49]
Listen, I've said that. I mean, I'm sorry that all of those should be outlawed. I mean, I in the state of Florida. I mean, I just you cannot have those as permanent residences. Well, shit, we got people trying to ride out storms in every fucking time we get a storm. Right. I try to ride them out on fucking sailboats, man. And then all we do is fucking pick up the body, fish the bodies of these fucking people out of this game. okay it's just stupid it's just stupid there's suicide boxes you cannot ride a major storm out in a fucking sailboat.

Sam:
[1:12:22]
Right and yet you you end up in a situation by the way like you know when you when you are giving the okay everybody evacuate everybody get out this is going to be an unsurvivable situation if you don't also provide the support to actually get all of those people There are all kinds of people who have situations financially. They don't have the resources to get out. Or even if they do, like grandma doesn't, and they can't take grandma or the systems in place, don't let them take their pats or whatever. There's all kinds of things that make it hard. and you know you you i don't know yet there are ways to be prepared and ways to be resilient to these kinds of things but hey part of fixing these problems is indeed you know you have to provide the support so even your poorest people can live somewhere that's safe.

Ivan:
[1:13:22]
And but i i i think also So, you know, I've been used to living with this since I was a child.

Sam:
[1:13:30]
Okay.

Ivan:
[1:13:30]
Okay. I remember the first hurricanes that we had to prepare for when I was little that were massive storms, you know, that that most of them missed us. But, you know, when I was when I was a freshman in college, you know, Hurricane Hugo hit Puerto Rico. Hurricane Hugo is a category three, category four storm. I mean, you know, I remember that I could talk to my parents for weeks. I had no idea how they were. I mean, the phones died right as the storm approached, and I didn't know anything for two weeks.

Ivan:
[1:14:08]
So I've lived with this, but, you know, I don't get, like, the storms themselves, they don't scare me because I've lived with this my entire life. It's just one of those things that Mother Nature throws at you. I mean, if you're in the Midwest, you've got tornadoes, you know, if you're in the West Coast, you've got earthquakes, you got wildfires, you know, they're mother nature, no matter where the hell you are. As a way of getting you one way or another, you know, is the thinking about the flash floods in Texas, for example, that happen whenever they get a massive rain event. I mean, the flash flooding that happens so quickly, you know, it just overwhelms people. Like a couple of minutes before, there's nothing, and then all of a sudden, people are drowning. So it's crazy. So I just think that, you know, me, I, you know, to me, I see people how they are stressed and panicked. I was seeing somebody in the opinion page talking about it, but they didn't grow up with this, okay? They moved there when they were an adult. You know, I had to deal with this as a child. And so I, for some reason, my mentality is, look, with a hurricane, my feeling is, I know it's coming. I can prepare. And in my family, we take preparation seriously.

Ivan:
[1:15:33]
I know so many people that don't and then wind up in terrible situations. But the key to all of this and like why my parents, maybe there were two weeks in Comunicado, but you know what? We had generators. We had water stored. They had whatever. They had electricity. They had satellite. They had everything. The only thing they couldn't do was call out. But they had everything because they were prepared. And that's the one thing that people just, I don't know, they don't think in advance about it. You know, like I was explaining, I've got, I mean, we haven't had a hurricane threat. Yet this season, but I've got a whole bunch of massive water bottles stored in our laundry room.

Sam:
[1:16:14]
Right.

Ivan:
[1:16:14]
You know what? I have them there. They're already there. I have a gas stove in the garage ready to go. I got coolers to store stuff ready to go. Yeah. You know, I've got this shit. It's ready. Okay. I don't have to start from scratch to get prepared for a damn storm. But you see so many people that all of a sudden they see a storm bearing down and then all of a sudden they're freaking out trying to prepare for this thing. OK, and, you know, it's it's just always to me it's wild. OK, it's wild that they just have not taken one second to prepare. So why always, you know, they say this right before a hurricane season starts. Hey, get prepared to do whatever. Man, 90 percent of people don't do shit.

Sam:
[1:16:58]
Well yeah a lot of it is just not yeah no motivation but again i i keep coming back to there are also people who you know being prepared takes money you know well.

Ivan:
[1:17:11]
Some is cheap i mean.

Sam:
[1:17:13]
How much you think.

Ivan:
[1:17:14]
Like a whole bunch listen you think.

Sam:
[1:17:16]
I know i know i got i got like i got i.

Ivan:
[1:17:18]
Got five massive jugs of water in my thing what do you think 10 bucks.

Sam:
[1:17:22]
I i know but But for some people, 10 bucks is a big deal, you know? But yeah.

Ivan:
[1:17:28]
Fair enough.

Sam:
[1:17:29]
You know?

Ivan:
[1:17:30]
Yeah, it's a good point.

Sam:
[1:17:32]
But yeah, like, this is one of those things where, first of all, yes, people have to be more aware. People have to actually take these things seriously. But also, you have to assume that lots of people won't. And so, therefore, state and local governments need to be ready to take up the slack.

Ivan:
[1:17:52]
And that's where the government of the state of Florida, especially, I mean, I will say that more so than ever under this governor, has not taken their job with this shit seriously. Because I will say that we had a number of Republican governors before, and they took this way more seriously than this damn clown. This guy is definitely the worst fucking governor we have had in a long time.

Sam:
[1:18:16]
I said state and local, but of course the feds have FEMA, the Red Cross as a private organization does a lot of stuff. There are all sorts of things out there, but having all of them up and running and prepared and making sure they know what they're doing is important. And like you're saying, it does matter. If you've got somebody who doesn't take it seriously and says, ah, well, we'll deal with that when it happens, then you're just asking for it.

Ivan:
[1:18:45]
Yeah and that and that's the reality so so anyway a lot of people got got and thankfully the one thing at least thankfully about where it went the storm like right now through florida is that that is one of the least but we had the storm surge and it was you know it was damaged but it's not well that is still one of the least populated areas of the state, OK, and thankfully it veered off further east of Atlanta. It didn't actually go directly to Atlanta. I can't report, but I spoke to to Kathy and she told me that, yeah, they had a lot of down a mutual friend of ours.

Sam:
[1:19:24]
Who lives near it.

Ivan:
[1:19:25]
So it's on is on the slack. Usually, I don't know. I don't think she listens to show, but she for some reason somehow got on the slack. I don't know. But anyway, but she she she said that, you know, they had they had power, you know, flicker in and out. They had a lot of trees fallen there was flooding that kind of stuff but but you know thankfully nothing more than that but but the power was still on even though it had flickered on and off several times during the evening so.

Sam:
[1:19:50]
Yeah but as usual with these things there's lots of places without power there's lots of places without internet lots of places where cell service is gone you know you you mentioned like the hurricane when you were younger where you couldn't get a a hold of your parents for weeks uh you know there there are lots of people that don't have communications right now at this very second and we'll see how long it takes it to to get everything restored currently right.

Ivan:
[1:20:16]
Now based on the storm there is this really cool uh web website called poweroutage.us okay okay and it it shows uh it shows the details of a number of customers without power right now so florida has about 500 000 customers without power but the number one right now that got really hammered south carolina 1.1 million customers without power georgia has 800 000.

Sam:
[1:20:39]
And by the way south south carolina wasn't even one that like you know when you it's like this was in florida where's south carolina come in you know and yeah yeah you got west virginia tennessee illinois for god's sake yeah yeah.

Ivan:
[1:20:53]
Because because the weather system like really went into Tennessee and you know, all, all of these places. It was crazy.

Sam:
[1:21:02]
I noticed, I noticed looking at this website, there's some power outages in California too, but I think they're probably unrelated.

Ivan:
[1:21:11]
Yeah, I don't think that those are related.

Sam:
[1:21:13]
Yeah.

Ivan:
[1:21:14]
Yeah. Those are not related. Yeah. So but but yeah, but you've got but you've got I mean, basically Florida out of, you know, isn't, you know, hell, Ohio had 250,000 people without power because of this. So Ohio has half the people out of power than Florida. Now, it's because it hit an area less population, but I will say also because of, you know, because of how power, you know, the resilience has been built into some of the electrical grid in Florida because we've been hit by so many storms. So, you know, so that also, that also is a factor. So, but anyway, that's my report. Hurricane.

Sam:
[1:21:54]
Okay, done with the hurricane. We'll take a break in just one second and then we will talk election and politics and all of that kind of stuff let's see which break am i supposed to play now, which one this one this one we will be back after this.

Break:
[1:22:42]
In the box that you found upon my face. What? Bye.

Sam:
[1:22:58]
Okay, that's that. So before we get into other stuff, I will mention that while Yvonne was talking about the hurricane, we had a breaking news alert. That North Carolina Lieutenant Governor Mark Robinson, who we talked about, he's the one who was posting on the porn site about being a black Nazi last week, has been hospitalized after an incident at a campaign event. There's not really a lot of detail on that. I've been looking while Yvonne was talking for news stories. There are a bunch of news stories on a bunch of sites. So this has been confirmed, but nobody's really got any detail yet as of the time that we are recording in terms of what the incident is, what his condition is, etc. But something happened.

Ivan:
[1:23:51]
Oh, well, couldn't have happened to a nicer guy.

Sam:
[1:23:56]
Yeah. So I don't know if he had like a health issue or somebody attacked him or like this is literally breaking news. By the time you listen to this, you'll know what's what happened and if it ended up being serious or not. Wait. Oh, treated for burns.

Ivan:
[1:24:12]
What? Burns.

Sam:
[1:24:14]
Burns.

Sam:
[1:24:16]
He's currently being treated for burns after the incident. He's in good spirit. Did somebody throw some hot coffee on him or something? I don't know. Anyway, like, obviously, we don't know. By the time you listen to this, you'll probably know what happened. But and I guess he's going to recover. So but I don't know. Weird. Okay. So as usual, I will start with my election graphs update just to see where things are. And I will note at the moment that we are recording, there are like two or three polls that have come out in the last few hours that I have not had a chance to enter in yet. But I don't think there are anything that significantly changes the picture. And the picture is actually pretty damn static from where it's been the last few weeks. stakes, Harris's position is actually a little bit better than it was last time we talked, I think. Well, it depends on the metric. But look, the bottom line is we still have all of these damn states that are really, really close. And so the range of reasonable possibilities goes from a fairly healthy Trump win to a fairly healthy Harris win. Win you might even call it you might even call it landslides on each side although i landslide to me still means like ronald reagan style landslide landslide to.

Ivan:
[1:25:45]
Me is like that harris vance poll that's uh that's out there at like plus 21.

Sam:
[1:25:49]
Yeah i i noted on the curmudgeon's corner slack right before we started recording that or a little bit before we started recording uh somebody actually polled Harris versus Vance instead of Harris versus Trump and Harris versus Trump was a head by a few percent. Harris versus Vance was a head by like 21%. It was crazy. But the bottom line is we still have, you know, all of these super, uh, close states in the polls. And I did want to make the distinction between like toss up, which is where we are. Like if you want to predict this as a toss up, you could get a Harris win. You could get a Trump win versus close. Like it's not necessarily predicting that the actual result on election night will be super, super close. It might be, it might be super, super close.

Ivan:
[1:26:47]
It could be all over the place.

Sam:
[1:26:49]
It could be all over the place. Here's the thing. Like I said, it is not unreasonable to have, given what we know and given the uncertainty, especially in the damn Electoral College, where all of these close states, if you add them up, are a huge number of electoral votes. So we just don't know is the answer. It's not that, oh my God, this is going to be super, super close on election night and every single one of these states will be waiting days and weeks for the count and the recount. It might happen that way, but it also could easily happen that, hey, the polls are underestimating Harris systematically by 2% or 3%, in which case she wins by a landslide. Or they could be underestimating trump again by two or three percent in which case he wins by a damn healthy margin it's just it's not that it's necessarily this is going to be super super close it's just we don't know we like we do not have the precision of information no listen.

Ivan:
[1:28:01]
I know that the the average is especially one of the things about the averages is that we have only been been tracking Harris versus Trump for really a relatively short time. Okay. It's been only a couple of months. Yeah. And that we've, this has really been, been tracked, but there is an interesting thing that I've seen about recent polling.

Sam:
[1:28:23]
Yes.

Ivan:
[1:28:24]
It's the number of polls that show Harris ahead by five points or more in the national.

Sam:
[1:28:31]
There have been more. Well, and I will say this is important. Wait, wait, let me say this. This is important. Popular vote-wise... I think I would be shocked if Harris loses the popular vote like that one is not close. That one is not like margin of error. Like, but she's she's significantly had that.

Ivan:
[1:28:56]
But the thing is, but beyond that, one of the things because we know that state polls always lagged the national polls. OK, and the one thing is that, look, the bigger the margin you have on the national polls, the likelier is that, you know, that you're going to be able to pull a number of states that are closer into into your orbit. It's just, you know, it's just we don't have the data yet because obviously it takes a lot longer. It's just it's just the fact that in in recent weeks, whereas in August, how many polls had her ahead by, you know, more than four points? it was like almost none.

Sam:
[1:29:30]
But like still if it's still if it's.

Ivan:
[1:29:33]
Been a lot i mean it's not just.

Sam:
[1:29:35]
No there have been there's been a lot of them and we we talked last week too that like what the hell is like are the polling averages doing because like right now rcp oh sorry right now 538 has the polling average at harris plus 2.8 but if you look at the recent polls plus six plus six six 6 plus 2 plus 5 plus 7 plus 4, 5, 5, 3, 3, 7, 3, 6, 6. How the hell do you get 2.8 out of that?

Ivan:
[1:30:05]
Hell, is it 2.9? I don't know. I don't get it. But I mean, literally.

Sam:
[1:30:08]
All the polls, the majority of them are 5+. I know the answer to that, and they say it right there on their website, is it's not actually an average of those polls. They're factoring in some fundamentals. They're factoring in state polls as well. They're doing some nonsense with it, but it means it's not the average. Now, RCP theoretically is a straight average, but they still have Harris up by 2.0.

Ivan:
[1:30:38]
The one that has moved much further away, because I know that Decision Desk with the Hill does do more of an average. They have Harris up to a 4.2.

Sam:
[1:30:49]
I looked into their methodology statement. They also do a lot of fundamentals just differently.

Ivan:
[1:30:55]
Just differently. But they have Harris at the highest margin that she's had periods as we've been tracking this at four point two. If she has in in their average she has definitely opened up the the lead is the biggest it has been.

Sam:
[1:31:10]
Right so Biden dropped out what what I will say again is like I don't think there's any question in popular vote I I would be shocked if Harris loses the popular vote well I'm more talking and wait wait wait let me say like we're you and you talk about this the state polls lagging. And that's, that's true. That's less true now that we're in the home stretch in the last few weeks, because there, the volume of state polls in the, in the close states is now massive. Like with my five poll averages, most of my five poll averages at this point are only taken about a week of, of, of the last week of polls.

Sam:
[1:31:56]
Right. And the, the thing is, it's not that it's that there's a lot of, like, if I had to say, like, if I look at the whole race overall, what I would say is there's actually a bunch of, there's a, I'm looking at my tipping point graph and there's a lot of motion up and down in it, but I actually think most of that motion is not real. Most of that motion is just pollsters coming in and out, coming into the various states. And the real situation is that after we had that big move towards Harris, when she first started, since then, we've been really bouncing around in a range with Harris ahead between zero and 2%. But like, but it's just bouncing in that range. It's not like, I don't think there's real motion of that's been very significant.

Sam:
[1:32:54]
And that sort of ties in with what we're seeing in the national averages too, which is she's ahead. She's ahead by a decent margin, but at least in like, again, like 538 is doing some magic. I think you're absolutely right. She's increasing that margin nationally, but it's unclear to me, like, is she running up the score in blue states as opposed to making the moves that she needs in the swing states?

Ivan:
[1:33:23]
Well, let's be clear, to be fair, those national polls aren't just also, they're trying to do in a national picture what, you know, what we're looking at state by state. Okay.

Sam:
[1:33:39]
Well, no, they're not just. No, they are.

Ivan:
[1:33:41]
They're not just.

Sam:
[1:33:43]
There's differences. Like the national poll averages are trying to predict the popular vote, period, end of story. The forecasts that these sites build off them are trying to do the electoral college. But like that, when you look at national poll averages, no, they're, they're predicting popular vote. They are not predicting the election.

Ivan:
[1:34:02]
I, I, well, well, I really, what happens.

Sam:
[1:34:07]
What happens though, is like, except in really close scenarios, those follow each other, you know, like you, we've, we've had, we've We've had two examples recently in our lifetimes where the popular vote in electoral college went different ways, but that's actually pretty rare. Like usually the winner of the popular vote wins the electoral college too. It's just that we've had a particular configuration recently where if the popular vote margin is less than a couple percent, it could go the other way.

Ivan:
[1:34:43]
Well, you know, when they're trying to build these, you know, they're trying to find out who's going to win the election. OK, well, no, it's not just.

Sam:
[1:34:51]
No, no, no.

Ivan:
[1:34:52]
That's a distinction.

Sam:
[1:34:53]
All of these places, 538, a DDHQ, all of these places, they have election models that try to do what you're doing. But that is not the poll average. The national poll average is the national poll average. It's popular.

Ivan:
[1:35:07]
No, no, no.

Sam:
[1:35:08]
That's their model. Their model. No, no, no, no.

Ivan:
[1:35:10]
No. No, I'm not talking about the national poll average. I'm talking about, say you're Bloomberg, you're doing state by state poll and you're doing a national poll. OK. All right. You're trying to model that to try to tell you who's going to win the election when they're even we're not doing a model. They're not doing it just, you know, they're not going and like, oh, let's just let's weigh in.

Sam:
[1:35:35]
No, the models that are built on top of the polls do what you're talking about. The national polls are looking for the popular vote end of story the the what the things that are trying to predict who wins are the models that are built off that like i like i i 5 30 no like a national poll is meant to predict the national popular vote end of story the model the electoral models these guys do something before like.

Ivan:
[1:36:04]
20 years ago we basically we didn't do this shit with these fucking models and each state and any of this shit back then honestly we we only.

Sam:
[1:36:15]
Relied on these fucking that that's that's because that's because before before 2000 the last time the electoral college and the popular vote went in different directions was in the early 1800s so no one thought it was going to happen oh yeah so like the the reason we had this outburst of of, oh, crap, we have to pay attention state by state, is because of the year 2000 and then 2016. Both of those years are where they went other directions, and that's where people realized, hey, actually, we're in a universe where the popular vote winner can lose the electoral college, so we have to pay attention on a state by state basis.

Ivan:
[1:36:59]
All right. So you're trying. I pulled up the methodology at a Bloomberg poll.

Sam:
[1:37:05]
Yeah.

Ivan:
[1:37:05]
Okay. All right. Ah, Bob, Bob, Bob said it everywhere. Okay, that's not what this says. I could read the whole blurb. That's not what this says.

Sam:
[1:37:18]
Send me the URL.

Ivan:
[1:37:19]
It says that they are trying to go. Our 2020 turnout forecasts are generated by a series of predictive models built in historic turnout.

Sam:
[1:37:26]
Wait, wait, wait, wait. That's not a poll. You just said it's a forecast model. That's different.

Ivan:
[1:37:32]
No, no, no. This is the... No, this is the... Well, okay, this is the election model. Okay, you're right.

Sam:
[1:37:38]
Yeah, exactly.

Ivan:
[1:37:38]
This is on the model. Hang on, hang on. Where is... OK, Bloomberg's national poll. Here we go. OK, sorry, because I did pull up the model. They have a whole they got too much shit going on over here.

Sam:
[1:37:49]
See, it's just that these are two different things. If you want to, where they are doing a forecast of the election, that's when you take into account the electoral structure. But if you're doing a national poll, you're doing a national poll. You're seeing where people are going to vote on a nationwide basis. And that's why, like, we don't usually want to pay attention to those national polls because they don't tell you who's going to win. Well, they tell you who's going to win the popular vote, but that doesn't matter. I mean, that's the whole reason all of these sites, including Bloomberg, have forecast models.

Ivan:
[1:38:26]
Well, we went to the fucking forecast models because we really went out, you know, because of what's happened. But let's be clear about this. Most of those, okay, when you look at it, say, you know, for example, a couple of years ago, Hillary won the popular vote by 2%, 3%, whatever the heck it was. All those were within the margin of error. The reality is that when you're looking at, if you're looking at the margins that we've had, they've been between the plus minus four. The reality is what we talked about, you know, when you're looking at the national poll, is that any of those results, even if you look at the national poll, have been within the margin of error where one or the other. Yeah.

Sam:
[1:39:07]
Well, here's the thing. Like if, if current polling, like forget the weird five 38 average that has hair at 2.8, if she's really at six or 7% nationally, then it, the chances of it going in a different direction than the electoral college are really small. Like if she's only at two and a half, 3%, the chances of it going the other direction are decent.

Ivan:
[1:39:35]
Right.

Sam:
[1:39:35]
You know, so it really depends, like, you know, like, because really like it is only close selections where it could go the other way. And right now, the way the states are configured, it's really only 538 actually has a chart of like their simulations for their model that shows like, you can see what percentage of the time, you know, Republican wins the electoral college, but Democrat wins the popular vote and vice versa. But really the chances of the other way around of like Trump winning the popular vote, but losing the electoral college is tiny, tiny, tiny at the moment.

Ivan:
[1:40:18]
Exactly.

Sam:
[1:40:19]
So the risk is a narrow popular vote win for Harris could fairly easily still end up with a electoral college win for Trump. Now, that's not automatic. It's not saying if the popular vote win is narrow, she will automatically lose. It is possible. It is realistically possible that you could have a situation where if Harris's national margin is only like, you know, say less than 3%, you could still get reasonable scenarios that lead to a Trump win in the electoral college.

Sam:
[1:40:58]
Okay. So, so my, my, my, my overall point though, we went off on major tangents there from my original point because, you know, we never do that here on this show, but that the overall summary of the situation is still that it's a toss-up. Within the skill that pollsters have, either outcome for the electoral college is reasonably possible. And like I said, that doesn't necessarily mean it's necessarily close. Harris could still win by a really healthy margin. It's just that we don't know based on the data we have right now. And then also like, you know, and this gets back to the whole, we've talked many times about all the reasons where we might think that this time around.

Sam:
[1:41:51]
Polls are underestimating the Democrat, and there's a lot you can convince yourself on that. But if you try hard, you can convince yourself the other direction, too. So we'll know when we know, you know, which way the polls are wrong.

Ivan:
[1:42:04]
OK, by the way, the Reuters Ipsos poll specifically says that they are not trying to do what you said. As a matter of fact, it says the Reuters Ipsos poll is designed to be nationally representative. Representative this can limit utility in projecting the outcome of presidential elections but they don't mean they're not trying to do it it just can limit the utility okay it's specifically they just said what i said no no no no no no no no no no what they said is that it's not the most exact measure of it but it doesn't say that they're not they're trying to predict but they're The reason it's not exact is because they're predicting the popular vote. No, no, no. That's not what they said. As a matter of fact, you go back further.

Sam:
[1:42:53]
Send me the link. Send me the link right now.

Ivan:
[1:42:54]
I'll send you the link so you can read it. They're not trying to model the fucking, they're trying to model what the fuck the outcome of the election is.

Sam:
[1:43:03]
Not the popular vote. They're modeling the outcome of the popular vote. Nationally representative sample by definition means they're looking at the popular vote if they wanted to model the outcome rather than the popular vote then they no no explicitly not do a popular no they do.

Ivan:
[1:43:23]
Both but the thing is that they're saying you're saying again that this is.

Sam:
[1:43:28]
Indicative but.

Ivan:
[1:43:29]
It's not the.

Sam:
[1:43:30]
Best predictor no no it's like it's like look it's like it's like Yvonne, Yvonne, by definition, if it's nationally representative, then it is not taking into account the structure of the Electoral College. You would have to intentionally bias it to give more weight to certain states than others.

Ivan:
[1:43:49]
Yes.

Sam:
[1:43:50]
Which would make it not. If they do that, then it's not a representative sample nationwide.

Ivan:
[1:43:55]
It represents. It's it's. You you have.

Sam:
[1:44:00]
You sent me the links yet i'm yes it's on general it's on general oh you can read.

Ivan:
[1:44:05]
It later we could we could we could oh.

Sam:
[1:44:07]
No hell no i'm gonna read it right now oh god no way no way, are we.

Ivan:
[1:44:16]
Gonna talk about are we gonna talk about the fact that the major of new york got indicted or something.

Sam:
[1:44:20]
No no wait why why is this because i'll continue without supporting us damn it okay blah blah blah projection of national opinion blah blah blah what about registered and likely blah blah blah further down i i is designed to be yeah this is exactly what you read the an important part. The Reuters-Ipsos poll is designed to be nationally representative. That means it's looking.

Ivan:
[1:44:53]
It's representative of- It represents the nation of what the result is going to be. It's not that it's- No.

Sam:
[1:44:59]
It's representative of the national voting population. Then it specifically says the reason it limits its utility is because presidential elections are decided on a state by state basis this is they are not so it is it's by definition of the word nationally representative by definition means you're modeling the popular vote no yes no if you were modeling you're making.

Ivan:
[1:45:26]
One massive leap.

Sam:
[1:45:27]
No if you were modeling the nationally representative.

Ivan:
[1:45:30]
Means that you're trying to figure out what the hell the.

Sam:
[1:45:32]
Nation is.

Ivan:
[1:45:33]
Going to do what they have like the president not fucking figure out what a damn meaningless number that has no meaning Eating.

Sam:
[1:45:39]
No, nationally representative means you are sampling the national population and you are trying to figure out what they will do. That gives you the popular vote. If you are, if you are, if you want to, if you want to predict, this is a prediction of the election outcome in terms of popular vote. It is specifically, they specifically say it's not, it limits the utility for the presidential election because it's state by state instead. If you want to predict the state by state, if you want to wait.

Ivan:
[1:46:09]
Okay, these models by nature, subjective and pollsters take multiple factors into account by determining who to include, including respondents, self-reported level of enthusiasm to come over there and pass voting behavior. Like any attempt to predict future behavior, those models can have flaws that they're overestimate, underestimate, estimated group balance at the end.

Sam:
[1:46:28]
That's the standard way for determining, that applies to every poll forever.

Ivan:
[1:46:36]
All right. Anyway, let's move on. Okay.

Sam:
[1:46:38]
Not until you admit you are completely wrong, Yvonne, then we will move on. We will continue this argument until you capitulate and admit that I am right about everything and you are always wrong about everything thing because you don't understand anything that.

Ivan:
[1:46:59]
Sounds great okay there you go beautiful.

Sam:
[1:47:01]
Okay okay fine we can move on like fine fine just so long as you know i'm right okay.

Ivan:
[1:47:10]
Can i ask a question.

Sam:
[1:47:11]
What is.

Ivan:
[1:47:12]
The sane washing thing.

Sam:
[1:47:13]
Okay sane washing okay let me take a deep breath, okay uh sane washing is just the term that people have been using for what a lot of media has been doing for donald trump's speeches and such where and this depends on which media you're talking about of course but basically lately in a lot of of a lot of trump speeches a lot of trump Trump interviews, a lot of whatever he's been rambling incoherently a lot.

Ivan:
[1:47:49]
And so he doesn't even know where the fuck he is.

Sam:
[1:47:52]
Right. Often.

Ivan:
[1:47:54]
Regularly. I mean, this has happened every fucking week. I'm like, but now Sona, he thinks he's in Pennsylvania. He's in North Carolina. He thinks it's a Michigan. I'm like, what the fuck?

Sam:
[1:48:03]
I mean, but a lot of places, and this includes major media like Washington Post, New York Times, et cetera. What they try to do when they present an article about, hey, Donald Trump gave a speech is They try to figure out, what the hell did he really mean? Then they frame it around that rather than talk about he's being incoherent. Here's one example. Oh, man, can I remember it? The education one that we talked about the other day is an example. He was asked to talk about how do you solve child care, and his answer was all about tariffs, right? There was another case where he was asked some sort of economic question, and his answer to it was, we will deport millions of people. And that was his answer to the economic question. And so and but you get sometimes descriptions in the media of like, you know, Donald Trump presents an interesting economic plan, you know, and it's like the interest.

Ivan:
[1:49:20]
Oh, my God, I've seen more than one of those. I mean, I'm like, what the fuck are you guys talking? You know, the crazy I do agree that one of the crazy things is is and I I actually believe that there is a large group of people that take this seriously. I mean, because it's not, You know, I know that people are saying it's sane washing, but I see all these business people literally like, you know, business executives saying, well, he said he's going to do this about the taxes and the tariffs and so forth and so on. And I am like, why? What the fuck are you guys talking about? I mean, there is no thing that he has ever said on day like today that is going to be what he's going to carry out in two months. Right.

Sam:
[1:50:07]
And I think this is the fundamental thing of sane washing is it's basically, you know, he's got, he spits out some sort of incoherent word salad. And then you have the reporters who are dealing with that, just trying really, really hard to translate that into something a serious politician who knew what they were talking about might say, and then evaluate it according to that, as opposed to what he actually said. And the criticism of this is if you only were paying attention to that, then you might get an impression of Donald Trump as, oh, he's making serious economic proposals, he's doing this, he's doing that. Whereas if you actually watched him or read an exact transcript of what he said you'd be like what what what's he what listen.

Ivan:
[1:51:06]
Listen he's now hawking one hundred thousand dollar watches.

Sam:
[1:51:11]
Yes okay.

Ivan:
[1:51:12]
Along with a cheaper version for 599 dollars.

Sam:
[1:51:16]
Right.

Ivan:
[1:51:18]
I did place my order.

Sam:
[1:51:20]
Oh, of course. And there's new coins as well.

Ivan:
[1:51:24]
Oh, there's new coins!

Sam:
[1:51:25]
There's new coins.

Ivan:
[1:51:27]
I mean, Sam, you want to talk about sane washing? If any other candidate during this period of the election campaign had been hawking this many scams leading up to the election, I mean, the Republican Party would have thrown him out by now.

Sam:
[1:51:48]
Well, and also, all of these things are just potential— They're all scams! Well, they're scams, but they're potential vehicles for bribery and such, too. It's like where people don't actually expect to get the benefit. They just want a way to shovel money to Donald Trump.

Ivan:
[1:52:06]
Listen, the most direct vehicle of bribery right now, DJT, to a guess, 100 percent. You want to fucking bribe Trump, pump up DJT stock. That's all you got to do. That's all you got to do. When you go in and you just shovel money in there, just buy, you know, announce that you bought 100, you know, whatever, millions of shares. Fuck it. you know and you're just shoveling money in his pocket i mean now i i you know speaking of djt i happen to think that you own it's thinking because yes yes i i'm accumulating a controlling position in djt as we speak i know it's that he he he, the as his odds of winning keep diminishing yes then the people that have been trying to funnel money by basically currying favor with him by buying djt are basically saying well i don't you know what maybe it's just up to shit i mean it's just tanking so i might as well flee too you know speaking speaking of odds.

Sam:
[1:53:16]
I just want to say i did i i forgot to include this on my election update. I currently give Harris odds between 50 and 60%. That's my range, somewhere between 50 and 60%. Election betting odds has it at 52, so right in that area too. And I think most of the people who are giving odds are in that ballpark. I think Nate Silver this time is an outlier. At least last time I looked, which was at least a week ago, He was actually still favoring Trump, but, you know, anyway, it's a toss up anyway. Sorry, you said something about odd. So I had to say that.

Ivan:
[1:53:58]
No, but but but it's just that, you know, the the all of these people have all these methods of just funneling money to it to his pockets by either buying his NFTs or buying his trading cards or buying the the the damn watches or Bibles or whatever. Ever not jesus christ what i mean there is this cycle of being in the middle of a fucking election and then all of a sudden another ad that he's records where he's pawning you know he's trying to pawn off some other scam product okay and by the way i.

Sam:
[1:54:36]
Can almost guarantee you well from from what i've heard that hundred thousand dollar watch isn't really the quality you would expect from a $100,000 watch.

Ivan:
[1:54:47]
Listen, I looked at that watch, okay? It's not worth $1,000.

Sam:
[1:54:51]
Okay?

Ivan:
[1:54:54]
I mean, just from the pictures, it's, you know, I mean, you know, listen, I was last week with some people that were wearing some watches that were worth $100,000. Let me tell you something. Donald Trump's watch doesn't look like that one. No. Okay. So no, it's, they were.

Sam:
[1:55:17]
They were, they were picking the watches up at target and just rebranding them.

Ivan:
[1:55:21]
I, I wouldn't be surprised. I mean, you know, although I think that they went to some, look, there are a number of, I, I, I, I can guarantee you that watch is made in China. Okay.

Sam:
[1:55:33]
But wait, what about, what about the massive tariffs on China?

Ivan:
[1:55:37]
I mean, you know, what, what does that matter? I think I saw a lot of the Trump hats and benefit. They're all made in China too. Yeah.

Sam:
[1:55:43]
Yeah. Yeah, I, yes.

Ivan:
[1:55:44]
Yeah, so, you know, like that fucking matters. But, you know, China does make a lot of knockoffs, okay? You know, I mean, you go over there, and they do make some decent ones, but it's just, you know, it is one shitty-looking watch. I mean...

Sam:
[1:56:02]
Real quick, we're over our target time, so I just want to blow through a couple things real quick just to get them mentioned on here. One, I had made a note, and this is just something to keep an eye out, for, but for the last few weeks, Vance has been a lot more visible than Trump himself is. You know, he's holding more events. He's on TV more. I mean, I'm not saying Trump has been absent entirely. He was for a few weeks after the first assassination attempt. He was, he like didn't come out for a little while, but Trump has been around, but it seems like Vance is out more and he's actually getting a little bit more attention because you know he says stupid stuff like trump says stupid stuff too but vance is getting negative attention for his comments more often it seems and so you gotta wonder a, How much of this is planned by Trump that he's like, he's actually holding back and not campaigning as much as he would otherwise? And also, is he getting pissed at Vance for getting more attention? I don't know.

Ivan:
[1:57:09]
Oh, I'm sure he is. But also, look, let's say him. I mean, how is he going to be out there if he's recording all these fucking commercials for more grifts every fucking week? I mean, every Sam, every fucking week, there is a new commercial for some new grift.

Sam:
[1:57:24]
Yes.

Ivan:
[1:57:24]
Whether it's the trading card or the watch or whatever.

Sam:
[1:57:27]
He has to get all this stuff in before he loses. Because then his value is going to go down. There's been a lot of speculation, too. We talked about how close this is. But there's been speculation that Trump's internal polling shows that he's losing. For sure.

Ivan:
[1:57:48]
Oh, I'm sure.

Sam:
[1:57:49]
Listen. And that he is. And honestly, if I had to bet, I'm betting on Harris right now. The enthusiasm gap seems obvious, but like this, despite whatever polling numbers, because I also talked the other day about like the conservative pollsters have been out in force and they're like pushing the numbers up towards, but towards Trump.

Ivan:
[1:58:08]
But listen, I even saw some Trafalgar polls showing Harris like I had certain things that I was like, and I was like, whoa, what the fuck?

Sam:
[1:58:17]
Yeah, there were a couple of those. but like i and so does trump is has trump gone into an oh crap i'm gonna lose so i might as well just grift as much as i can and then i mean how he talked about if he loses he wants to go live in venezuela you know he also.

Ivan:
[1:58:36]
Said recently which i don't know if i believe that he said he if he lost he wasn't gonna run again.

Sam:
[1:58:42]
Yeah yeah by.

Ivan:
[1:58:44]
The way curiously the new trump watches which are are available for pre-order.

Sam:
[1:58:47]
Later this fall are.

Ivan:
[1:58:50]
Not being advertised as luxury type pieces, but rather as collectible items for individual enjoyment only. Okay uh oh the joy that i get from looking at my fake gold watch that has the words trump on it oh my god every day is just pure joy yes that has to be you know what kind of a fucking loser are you that would get this and say that they are getting individual enjoyment.

Sam:
[1:59:29]
My goodness. Well, look, especially for the $100,000 one, and we implied this before, but nobody who can spend $100,000 on that gives a crap about the watch at all. They just see this as a way to give him. They just want to give him money.

Ivan:
[1:59:45]
Give Donald Trump $100,000.

Sam:
[1:59:46]
And get around any financial restrictions, anything like that.

Ivan:
[1:59:49]
They probably will get the watch and then just once they get it, they'll toss it in the garbage or give it to the give it to the pool guy or whatever or something, you know, some, you know, here, here, here.

Sam:
[1:59:59]
They don't want the damn watch.

Ivan:
[2:00:00]
I'm not wearing this piece of shit.

Sam:
[2:00:04]
Now, of course, all of these two, though, I don't know specifically about the watch, but these are all licensing deals like, you know, so it's it's also like Trump probably has his money up front anyway from the licensing.

Ivan:
[2:00:17]
Yes. So, yeah, yeah, yeah. Yeah.

Sam:
[2:00:19]
So he's not necessarily like getting a certain percentage.

Ivan:
[2:00:22]
He probably gets it up from pain and then gets a percentage.

Sam:
[2:00:26]
Yeah. I'm sure he does. I'm sure he does.

Ivan:
[2:00:28]
Otherwise that way he put, he goes and he hawks them.

Sam:
[2:00:31]
Okay. A note. The waltz Vance debate is coming up on October 1st. That's a two next this coming Tuesday. So keep keeping a watch out for that. It'll be fun. I'm sure. I'm not entirely sarcastic. I want to see those two go up against each other. It should be an interesting thing. I think Walsh will probably kick Vance's ass as much as Harris kicked Trump's ass. That's my prediction right now.

Ivan:
[2:00:59]
I mean, I agree.

Sam:
[2:01:01]
Uh, we'll, we'll see, but that's my prediction also. Oh, and we, since we were talking Vance, I can't, the Vance dossier that was apparently hacked by the Iranians and they've been trying to hawk to all kinds of journalists, but nobody has been publishing. It was finally published by somebody a couple of days ago.

Ivan:
[2:01:19]
I wanted to get the cliff notes. I haven't seen anybody do like the cliff notes.

Sam:
[2:01:24]
So, so actually the guy, the guy who published it gave a really high level. Basically it it just the the reason that none of the major news companies are have not published it before one is of course they're like hey we were fooled by all this stuff against clinton we're not going to be fooled again which is a little unfair but still um but but i get it yeah but it's when you when you look at there's nothing really all that newsworthy in here It has, it's like a standard oppo research from what I read of things that are public anyway. So like it's got a list of all the times Vance said Trump was stupid or an idiot or whatever.

Ivan:
[2:02:05]
Which we knew about.

Sam:
[2:02:06]
Which we knew they've got a number of places where Vance was involved in one thing or another that might be embarrassing. And I mean, none of them are even as good as the couch thing, you know? So, you know, yeah so like it's basically all normal stuff there's no smoking gun that says like oh my god vance was doing this thing that we had no idea about that's going to completely change the campaign there's nothing like that now of course when they were going over the stolen clinton stuff they were talking about like podesta's risotto recipe and crap like that so that that wasn't particularly newsworthy either, but they still were having an hour a day talking about the new revelations.

Ivan:
[2:02:52]
Yeah, but I was... I never understood why anybody cared about those kind of innocuous emails, but whatever. Anyway, all right.

Sam:
[2:03:02]
And then the other thing is that special counsel did submit his 180-page document to Judge Chunkin. Chunkin? Is that how you say Chunkin? Chunkin? I don't know.

Ivan:
[2:03:14]
I'll butcher the name.

Sam:
[2:03:16]
The judge. The judge in the January 6th case out of D.C., apparently the earliest possible that we could see redacted versions of that filing are also next Tuesday. But there are chances that it'll be longer because the Trump people have until Tuesday to file their objections to a redacted version coming out. And so depending on what you know the judge may take more time to decide on that the judge may the judge may decide not to release redacted versions and apparently she's making separate decisions on the main document and the appendices the appendices are all where a whole bunch of goodies are in terms of actual witness testimony and stuff like that so it's possible we'll get redacted views of some of this. It's possible that we won't until after the election or even until some eventual trial in 2028 or something. My expectation is like a lot of people have been sort of holding their breath and saying, this is the one thing we might get before the election is this document. My prediction is even if we get a redacted version, it's not going to have Some massive new revelations that change anything. It's going to be more of the same kind of stuff we already know, and it's not going to change anybody's mind on anything.

Ivan:
[2:04:42]
By the way, two tidbits before we forget, Fed cut interest rates.

Sam:
[2:04:46]
Oh, yeah.

Ivan:
[2:04:47]
And inflation came in lower than expected.

Sam:
[2:04:51]
Yes absolutely oh and update we do now oh.

Ivan:
[2:04:55]
Wait number three the economy in the second quarter grew faster than.

Sam:
[2:04:58]
And and there were decent inflation numbers too i think yeah yeah.

Ivan:
[2:05:02]
That was what i said inflation came in below.

Sam:
[2:05:04]
Okay we are wrapping up but we do now know what happened to mark robinson i have the update okay what happened uh this is mark robinson attended a truck show in Mount Airy, North Carolina tonight. He burned his hand leaning against a truck and was taken to the hospital. An official source says he is fine and home now. Oh, well, so yeah, it's not somebody through scalding water on him. It wasn't some attack. It was an.

Ivan:
[2:05:37]
Those truck events are crazy. I just saw a news story related to some guy that went into a rage and just Not a monster truck, but close to it. Then basically, I mean, he was arrested because he tried to run over about six people. But the guard did run over a couple of cars and people had to run and flee from being run over. So, okay.

Sam:
[2:05:56]
Yeah. So, but yeah, he just leaned on a hot part of a truck and burnt his hand. That's, that's all. Okay. And you mentioned Mayor Adams was indicted for all sorts of corruption in New York. And it may not be over yet. There may be more to come. So, okay. With that, the stuff to end the show, go to curmudgeons-corner.com. You can find all the ways to contact us. You can find our archives, including transcripts in the last year or so. You can find a link to our YouTube. What else? And a link to our Patreon where you can give us money. And at $2 a month or more, at Patreon, you can get at various levels or all kinds of stuff. We'll mention you on the show. We'll send you a postcard. We'll send you a mug. We'll blah, blah, blah, blah, blah, blah, blah, blah. At $2 a month or more. Or if you just ask us, we'll invite you to the curmudgeon's corner slack where Yvonne and I and others are chatting throughout the week, sharing news links, sharing funny links, sharing whatever. So Yvonne, do you have something to highlight from the curmudgeon's corner slack?

Ivan:
[2:07:01]
Well, something you just posted. Childless congressional candidate in Virginia borrows his friend's family, his friend's wife and children for campaign photo op.

Sam:
[2:07:13]
Yeah.

Ivan:
[2:07:13]
What do you think? That if he won, what, they're going to find out this wasn't his fucking family? What the fuck is this?

Sam:
[2:07:21]
Well, apparently he said.

Ivan:
[2:07:23]
You know, I just want to be surrounded by some nice looking people.

Sam:
[2:07:27]
Well, yeah, essentially. and and look honestly the thing is it makes it look like it's his family like like right you know my my that.

Ivan:
[2:07:37]
Picture is fed to the sea that's not just me sitting with some random people hey whatever no.

Sam:
[2:07:44]
Yeah because because like look my wife on her campaign stuff there there is a picture with me and the family but there are also pictures with her with other random people right like so So, okay, you can have campaign pictures with random people in it. That's a thing. That's not a big deal. But this picture is posed so it looks like this is my family. And it's not his family. It's his friend's wife and kids. And apparently he does have a fiancee, it says, but they don't have a family yet. And apparently he didn't want to be in a picture with his fiancee, I guess. I don't know. But, like, yeah.

Ivan:
[2:08:21]
That's bizarre. bizarre i mean i'm like i mean the right thing would have been to just pose with his fucking, fiancee i mean what the hell hey we just brand them kids hey come on i mean might as well just gonna fucking photoshop them but it was a brand of i mean funnier would have been right if he had done an ai generated image of him in a fake family there you go.

Sam:
[2:08:41]
So just to note as well this is his opponent in this race is uh eugene vinman you know if you remember the.

Ivan:
[2:08:49]
Vinman brothers yes Yes, yes, yes.

Sam:
[2:08:51]
So, uh, Eugene is not the one who's been on TV the most and the key player was his brother, but, but Eugene Vindman is his brother and he's running, it's at Virginia's seventh district. And so, yeah. So yeah. Anyway. I don't know. There you go. And we are done. Thanks, everybody. Have a great week. Have fun. Stay safe. Blah, blah, blah, blah, blah, blah, blah, blah.

Ivan:
[2:09:20]
Blah, blah, blah, blah, blah, blah, blah, blah.

Sam:
[2:09:23]
Blah, blah, blah, blah.

Ivan:
[2:09:25]
Blah, blah, blah. I already sang at the beginning. I'm not singing again.

Sam:
[2:09:28]
Yeah. And, and, and, and so, yeah, as we're recording this, let's see, how many days do we have left? 38.8 days left until the first election results start coming out, except for Dixville notch or whatever that comes in like a few hours before that. So we're running out of time. By the time you listen to this, it'll probably be a day less than that. Like, not much time left, you know, one way or another, This whole thing will be done. And then, or, or it could be, it could be like 2020 where we have weeks until we have election results. And then we have people fighting on January 6th at the Capitol, you know, who the hell knows and all kinds of lawsuits. But hopefully we actually, hopefully we have a clear Harris win like on election night. That would be nice, right?

Ivan:
[2:10:22]
Well, we didn't have one with Biden clear.

Sam:
[2:10:24]
I know, I know it took like a week. i'm hoping like like but if it actually ends up close that allows all kinds of shenanigans to happen no i know i don't want it to be close i want the clear win i mean i i want to be hearing that harris is winning florida by like 9 p.m on election night you know because then if that's happening it's a blowout okay it's all it's all yeah yeah yeah so anyway now i'm not like betting on that but i'm hoping but that.

Ivan:
[2:10:57]
Would be nice to hear.

Sam:
[2:10:58]
Okay we are done thank you everybody i said that already yeah here's the outro music enjoy oh say goodbye yvonne bye bye Bye. Thank you. Okay, that's it. I'm hitting stop.


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