Latest / Curtis Sliwa & Larry Mendte In The Morning / Hour 2: Recapping the primaries

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Hour 2: Recapping the primaries · Curtis Sliwa & Larry Mendte In The Morning

0:00
Speaker 1: Well, one of the most important primary days of the
0:03
Speaker 1: season just passed us by, and the star the race
0:09
Speaker 1: that got the most attention was in Wisconsin, and it
0:13
Speaker 1: got the most attention because there was a well, you know,
0:17
Speaker 1: I can say it now. I thought she was completely
0:20
Speaker 1: a lunatic, this assembly woman Francesca Hong, who became a
0:25
Speaker 1: national story just because of things she said in the past.
0:28
Speaker 1: She doesn't like the Fourth of July, she doesn't like Thanksgiving,
0:31
Speaker 1: she wants to get rid of the US Senate. Over
0:34
Speaker 1: and over again. She was espousing the DSA line.
0:38
Speaker 2: But she was.
0:39
Speaker 1: Winning constantly in the polls I had, and everybody thought,
0:44
Speaker 1: oh my god, this is going to be the death
0:46
Speaker 1: of the Democratic Party if they keep electing all of
0:49
Speaker 1: these unelectable socialists all across the country, especially in a
0:53
Speaker 1: purple state like Wisconsin. But the Democratic Party rallied and
1:00
Speaker 1: the Republican Party was actually supporting Hong.
1:03
Speaker 2: They wanted her to win.
1:04
Speaker 1: Because that would be a great pickup right there if
1:08
Speaker 1: she were to win, because the Republicans would definitely win
1:11
Speaker 1: that seat. But the Democrats were smart and they really
1:14
Speaker 1: got behind David Crowley, the Milwaukee County executive who had
1:17
Speaker 1: dropped out of the race, but got back in it
1:19
Speaker 1: after some of the other candidates had problems, and in
1:23
Speaker 1: the very end he won by point four percent of
1:29
Speaker 1: the vote. Now there could be a recount in this race.
1:33
Speaker 1: There might be a recount because she can't but she
1:35
Speaker 1: has to request it. If she requested it, she also
1:40
Speaker 1: has to.
1:40
Speaker 2: Pay for it.
1:42
Speaker 1: And the problem is she didn't have any money. Crowley
1:46
Speaker 1: had all the money in this race. They flooded the
1:49
Speaker 1: airwaves and at the very end they were able to
1:53
Speaker 1: maybe save the Democratic Party in Wisconsin because this would
1:59
Speaker 1: have been a disaster. I'll tell you what, Curtis, I
2:04
Speaker 1: was rooting for Hung. I was hoping so much she
2:08
Speaker 1: was gonna win because the Republicans would have made her
2:12
Speaker 1: the most famous person in America.
2:14
Speaker 3: Well, the Republicans loved her. In the end, they had
2:17
Speaker 3: a super pack. They poured two point two million dollars
2:21
Speaker 3: only into two areas in the Madison area in Milwaukee
2:25
Speaker 3: area because they knew that's where most of the progressive
2:28
Speaker 3: votes were, and their ad was a vote for Hung
2:32
Speaker 3: is a vote for socialism. She is too liberal, So naturally,
2:38
Speaker 3: if you happen to lean in that direction, progressive of
2:40
Speaker 3: socialism and I'll explain it a moment in Wisconsin is
2:43
Speaker 3: really where socialism in America was developed. That's going to
2:47
Speaker 3: aggravate you and make you want to get out there
2:50
Speaker 3: and vote against the African American. As you had mentioned Crowley,
2:53
Speaker 3: who is the county executive of Milwaukee County. Great story,
2:58
Speaker 3: I might add, actually, great story. Hung has a great story.
3:01
Speaker 3: He had a great story. They didn't have an easy
3:04
Speaker 3: life growing up. But as you pointed out, in the end,
3:09
Speaker 3: it's like zero point four percent differential and the last
3:14
Speaker 3: wave there were twenty eight thousand absentee ballots from the
3:17
Speaker 3: city of Milwaukee that were delayed the counting because of
3:21
Speaker 3: human era. Now, i'd have to tell you, having spent
3:25
Speaker 3: a lot of time in Milwaukee, I believe that would
3:27
Speaker 3: have favored Crowley because the north side is black, the
3:31
Speaker 3: south side is Hispanic, and all the white progressives lived
3:34
Speaker 3: downtown along Lake Michigan, you know where Marquette University is,
3:38
Speaker 3: where all the government buildings are and the corporation buildings.
3:43
Speaker 3: So I think he would have won it anyway. But
3:46
Speaker 3: it's only point four percent, and you're right, she can
3:50
Speaker 3: actually get a recount if she's willing to put up
3:53
Speaker 3: three million.
3:54
Speaker 2: Dollars, which she doesn't have.
3:56
Speaker 4: And remember this goes back to twenty sixteen. I remember
4:00
Speaker 4: how close it was with Hillary was she loses the state.
4:05
Speaker 3: She loses Michigan, she loses Pennsylvania by the bearer's minimum,
4:10
Speaker 3: and Wisconsin, and she wants recounts, recounts. But the Green
4:14
Speaker 3: Party candidate Jill Stein, who only got one percent, she
4:17
Speaker 3: was sort of the Ralph Nader in that race. She
4:20
Speaker 3: got the state to pay for the recount. It was
4:24
Speaker 3: all for nought because Trump won Wisconsin anyway. He actually
4:27
Speaker 3: got more votes in the recount. But then remember Trump
4:30
Speaker 3: in twenty twenty wanted a partial recount of Wisconsin because
4:34
Speaker 3: he knew some areas if the recount it might not
4:36
Speaker 3: have favored him. So he had a partial recount. So
4:39
Speaker 3: Wisconsin is a state that's used to doing recounts. They've
4:42
Speaker 3: changed the rules though. You want to recount, you got
4:46
Speaker 3: to put up the money. And you're right, she's down
4:48
Speaker 3: with like four hundred thousand dollars. She would have to
4:51
Speaker 3: have a special fundraiser and do it immediately. And I
4:54
Speaker 3: think she said yesterday just before her supporters went home,
4:59
Speaker 3: they hadn't yet what the results were whoever wins. You know,
5:03
Speaker 3: we're going to bridge the divide. We're gonna work for
5:05
Speaker 3: the Democratic candidate. So I think in her own mind
5:08
Speaker 3: she kind of recognized if I lose, I'm not going
5:12
Speaker 3: to challenge it, although I would have been urging her
5:14
Speaker 3: to challenge it.
5:15
Speaker 4: Are you kidding? A point full percentage? How close that is?
5:19
Speaker 1: The Democrats don't want her, They don't want her, so
5:23
Speaker 1: she is going in an uphill battle. Anyway, This might
5:26
Speaker 1: be the best thing that ever happened to her, because
5:29
Speaker 1: she was going to get almost no support except for
5:33
Speaker 1: this small but growing gang of Democratic Socialists. That's it.
5:38
Speaker 1: The Democrats saw that she was death and she, by
5:41
Speaker 1: the way, was an awful candidate.
5:44
Speaker 4: Awful.
5:45
Speaker 1: The only thing that got her support was DSA. The
5:49
Speaker 1: only thing that got her support was craziness.
5:52
Speaker 2: And the young.
5:52
Speaker 1: Oh the divide in the young and the and those
5:56
Speaker 1: over forty, Oh my god, in the state, they've already
5:59
Speaker 1: starting to break down. It was incredible. It was like
6:03
Speaker 1: sixty five percent of Democrats under a certain age voted
6:08
Speaker 1: for her. So, look, this is going to be playing
6:12
Speaker 1: out across the country, and every time it does, the
6:15
Speaker 1: Democrats have figured it out. They're going to squash this.
6:18
Speaker 3: Well, there's a little difference here. Let's look at the
6:21
Speaker 3: recent barely winning the Michigan primary where there was no recount.
6:27
Speaker 3: I thought there would have been a recount. They were
6:29
Speaker 3: talking like less than one percent between El Sayid and
6:34
Speaker 3: the congresswoman. But apparently the rules are no recount in primaries,
6:39
Speaker 3: but recount in the general election. But in this case,
6:43
Speaker 3: unlike L said, Bernie Sanders held rallies for L Sayed,
6:48
Speaker 3: AOC came in and stumped for L.
6:50
Speaker 2: Sayed.
6:51
Speaker 3: When I looked at the totals for hang legitimately, DSA
6:56
Speaker 3: can remember how L Sayed was saying, I'm not DSSA,
7:00
Speaker 3: I'm a capitalist, I'm not associalate. She remember how you
7:02
Speaker 3: was spinning that she's been loyal to the DSA. Her
7:07
Speaker 3: god is Bernie Sanders, her goddess is AOC. Do you
7:10
Speaker 3: know they would not endorse her because she's an awful candidate. Well,
7:13
Speaker 3: she was ahead of the polls, So I'm thinking it's
7:15
Speaker 3: a little bit more. I'm not sure they had conversations.
7:19
Speaker 3: Maybe there's something a little often there was nothing wrong
7:22
Speaker 3: in terms of improprieties. Just to give you an idea,
7:25
Speaker 3: I think people were trying to figure out where did
7:27
Speaker 3: this woman come from? She was an assembly woman from Madison,
7:30
Speaker 3: well known as a chef. But the reason that she
7:34
Speaker 3: elevated herself for three things. The first thing is she
7:37
Speaker 3: went to all the rural areas where everybody else stayed
7:40
Speaker 3: away from. This was the Chuck Schumer philosophy that beat
7:43
Speaker 3: al Domoto for the US Senate when Schumer was the
7:45
Speaker 3: congressman and Demotto was the sitting senator. He didn't go upstate.
7:49
Speaker 3: She went wherever they were plowing in fertilizer. Number two,
7:53
Speaker 3: she was the only candidate of any party against the
7:58
Speaker 3: AI data filing Senate know where Eric Adams was recently
8:01
Speaker 3: in that little town where they booed him.
8:03
Speaker 4: They welcomed her because she was opposed to that. And
8:06
Speaker 4: then the third thing is boy luck be a lady
8:09
Speaker 4: named ha.
8:10
Speaker 3: She gets into a race where you have the governor
8:14
Speaker 3: who has decided I'm not running for a third term.
8:16
Speaker 3: He's a popular government governor, a Democrat. The lieutenant governor
8:21
Speaker 3: is running a Hispanic would have been the first Hispanic governor.
8:25
Speaker 3: She has to drop out. It's the Democratic Kennedy because
8:29
Speaker 3: guess what a million dollars was stolen from her campaign
8:32
Speaker 3: and she blamed the campaign manager. Always blame the campaign manager.
8:35
Speaker 3: She drops out the next day. Then the guy was
8:37
Speaker 3: the former lieutenant governor who lost by one percent to
8:41
Speaker 3: Ron Johnson. Remember that was a really close race. This
8:44
Speaker 3: guy ran a great race, Mandela Barnes. I'll never forget
8:47
Speaker 3: that name, Mandela Barnes. You know why he dropped out,
8:50
Speaker 3: why he would have won. The Democrats were investigating charges
8:54
Speaker 3: of sexual harassment. I guess again saw Peter for all
8:58
Speaker 3: the guys out there, So now it's her. And then
9:01
Speaker 3: that's what prompted Crowley, who had dropped out, to get
9:05
Speaker 3: back in the race because the governor, Tony Evers clearly
9:08
Speaker 3: did not want a socialist and said I'll help you
9:10
Speaker 3: raise money and he did, and going.
9:12
Speaker 1: Forward they might be able to win this seat now,
9:15
Speaker 1: and that's what it was all about. And that's why
9:18
Speaker 1: Bernie Sanders didn't go and support her. That's why AOC
9:22
Speaker 1: didn't go to support her in the very end. In
9:25
Speaker 1: the matter, if you're a socialist and not a socialist,
9:28
Speaker 1: it's about winning and these races right now, because this
9:32
Speaker 1: is going to be close.
9:33
Speaker 2: It's going to be close across.
9:34
Speaker 1: The country because the Democrats can't get out of their
9:38
Speaker 1: own way with this socialism thing. It's always going to
9:42
Speaker 1: be about winning. And so when you look at it
9:45
Speaker 1: and you think to yourself, well, why is this person
9:47
Speaker 1: that report not supporting that person because they know they
9:50
Speaker 1: can lose. It's all about winning and losing. That's why
9:52
Speaker 1: everybody was supporting Plattner because they thought he could win.
9:56
Speaker 1: It didn't really matter. All of the skeletons in his
9:59
Speaker 1: closet thought he could win. I'm hung they thought she
10:03
Speaker 1: was gonna lose. I'm going to do a deeper dive
10:05
Speaker 1: on that because she was ahead in the polls. As
10:07
Speaker 1: you pointed out, the polls were wrong all night long.
10:09
Speaker 1: You're gonna get into all the races you know, in Minnesota,
10:13
Speaker 1: South Carolina, obviously Wisconsin, but they were wrong on every
10:17
Speaker 1: every level.
10:18
Speaker 3: But that's where socialism started in America was Wisconsin. They
10:23
Speaker 3: had the first socialist congress person. They ran as socialists.
10:27
Speaker 3: They didn't have like DSA or anything like.
10:29
Speaker 1: The way back in the past. It ain't that anymore.
10:31
Speaker 1: It's not that anymore. Had three mayors in Milwaukee. There
10:34
Speaker 1: were socialists. There are a lot of There are a
10:36
Speaker 1: lot of DSSA people there. I'm telling you, have you.
10:40
Speaker 2: Been to Wisconsin, I've been there a lot.
10:42
Speaker 5: I spent.
10:46
Speaker 3: I mean German concentration, Polish concentration. I spent a long
10:50
Speaker 3: time in Milwaukee organizing Guardian Angels. But I'll tell you
10:54
Speaker 3: this much, I believe that there was something that personally
10:59
Speaker 3: didn't click between her Bernie Sanders, the godfather of the
11:04
Speaker 3: DSSAY and the princess who maybe crowned the future presidential
11:08
Speaker 3: candidate of the DSSA AOC so I'm gonna I'm gonna
11:12
Speaker 3: gonna do a deeptail.
11:13
Speaker 1: No, it didn't click. The same thing that didn't click
11:15
Speaker 1: with the voter. She wasn't a good candidate. She was
11:17
Speaker 1: an awful, awful candidate.
11:19
Speaker 3: Thanksgiving, well, I would have suggested that was too much
11:25
Speaker 3: of a flip. You're opposed to Thanksgiving because it promotes colonialism,
11:29
Speaker 3: and then all of a sudden you come back and
11:31
Speaker 3: you say a pivot and shift a.
11:33
Speaker 4: Well, that's my favorite holiday. In fact, that's why I
11:36
Speaker 4: got an opportunity.
11:37
Speaker 3: To check out a test out all my culinary delights
11:40
Speaker 3: as a shit.
11:40
Speaker 1: Speaking of the polls, the internal polls must have shown
11:43
Speaker 1: that was a big mistake because She was asked going
11:46
Speaker 1: into the voting booth, what's the one thing that you
11:49
Speaker 1: want to want miss Wisconsinites to know before they vote?
11:53
Speaker 1: She said, I love Thanksgiving?
11:54
Speaker 3: You love Thanksgiving? Can we have in fact? What is
11:57
Speaker 3: that the bone you take out? The wishing bone? I'm
12:01
Speaker 3: missing it here? You know where you break the breastbone
12:04
Speaker 3: to see if you get luck and she did. Yeah,
12:06
Speaker 3: she probably would have went there, you want to break
12:08
Speaker 3: the wishbone here, see if I get luck in.
12:10
Speaker 4: And so she launched by zero point four percent.
12:13
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Speaker 1: They look great. We'll dig into it right after the show. Now,
13:58
Speaker 1: what do you think are the best states to live in?
14:01
Speaker 1: They put out this list every year on wawhoot hub
14:04
Speaker 1: and they go by affordability, economy, education, and health, quality
14:11
Speaker 1: of life and safety.
14:13
Speaker 2: That's what they do.
14:15
Speaker 1: And they whoever's number one, they put them in number
14:17
Speaker 1: one if you're in a fifty, and then it was
14:19
Speaker 1: the best score all the way through gets to be
14:22
Speaker 1: the top state in America.
14:23
Speaker 2: Who do you think tops the list?
14:25
Speaker 3: Oh, the at least crowded, So I'd say Wyoming, Montana, Idaho.
14:29
Speaker 1: Idaho's number one, Wyoming's number six. Montana is all the
14:33
Speaker 1: way down at number fourteen, which isn't bad, not the
14:36
Speaker 1: top half.
14:36
Speaker 3: Maybe those areas lots of place to roll around and
14:41
Speaker 3: have a good quality of life.
14:42
Speaker 1: Your theory doesn't work for number two, Hi, because it
14:46
Speaker 1: might be the most crowded state in America.
14:49
Speaker 2: Not New Jersey. New Jersey number two.
14:53
Speaker 3: New Jersey and News Tom kains there's no freaking way
14:58
Speaker 3: that Jersey should be finishing number two.
15:00
Speaker 4: Who did day Greece.
15:01
Speaker 1: It's a great state. I mean, it's a great state
15:03
Speaker 1: to live in. The problem is taxes and affordability in
15:06
Speaker 1: New Jersey. So you would think that that would kill them,
15:09
Speaker 1: and it should have. They were forty nine out of fifty.
15:13
Speaker 1: When it came to affordability, what they were number one
15:16
Speaker 1: in was safety. They are considered the safest state in
15:20
Speaker 1: America by wallet Hub and quality of life number nine,
15:25
Speaker 1: education number seven, which I'm surprised because in the rankings
15:28
Speaker 1: they are always number two, number one or number two.
15:30
Speaker 3: Number one, pay enough property taxes to be number.
15:33
Speaker 1: One, but their education is tremendous, and so even though
15:38
Speaker 1: affordability killed them, they were number two.
15:41
Speaker 4: Safety number one.
15:42
Speaker 3: Now they must not have spent much time in Pattison
15:45
Speaker 3: and NewYork right to Encampden and Trenton.
15:48
Speaker 1: That but most of the state I would agree with
15:51
Speaker 1: that gorgeous. And their crime rate for the state is
15:53
Speaker 1: pretty darn low. New York number twelve, by no way,
15:59
Speaker 1: number twelve.
16:00
Speaker 2: Uh, they finished first in quality of life.
16:04
Speaker 3: All these states that New York is and New Jersey
16:07
Speaker 3: heights are fleeing to Virginia, North Carolina, South Carolina, Georgia, Florida, Texas, Tennessee,
16:13
Speaker 3: and parts unknown.
16:15
Speaker 4: Where did a rate and all of this.
16:16
Speaker 1: Connecticut, by the way, twenty second, Florida's number ten. What
16:21
Speaker 1: else did you mention?
16:22
Speaker 4: Oh, well, you just go down the line.
16:23
Speaker 3: Georgia, North Carolina, South Carolina, Texas, Tennessee.
16:28
Speaker 2: I gotta find them.
16:29
Speaker 4: You would think they'd be right on up there, like
16:31
Speaker 4: one to ten.
16:32
Speaker 2: No, I keep going down. I'm not finding them.
16:34
Speaker 4: No, somebody got greased on this survey. Whoever did this survey?
16:38
Speaker 2: Who do you think is last? Oh?
16:39
Speaker 1: They greased wallet hub, a place called wallet hub exactly.
16:44
Speaker 1: By the way, who do you think was last?
16:48
Speaker 2: Uh? Hawaii? Oh that's interesting, you said Hawaii.
16:51
Speaker 6: No.
16:53
Speaker 2: Yeah, but apparently that doesn't hurt. It didn't hurt New Jersey.
16:56
Speaker 2: It's uh, it's New Mexico.
16:59
Speaker 7: Oh.
16:59
Speaker 4: A lot of a lot of crime in New Mexico. Oh, okay,
17:02
Speaker 4: I concur very good.
17:03
Speaker 2: Forty ninth Oh, not just.
17:06
Speaker 4: Albuquerque, not just Albuquerque.
17:08
Speaker 3: And there's a place, you know in Albuquerque where everybody
17:11
Speaker 3: fled years ago from New York because they wanted they
17:16
Speaker 3: wanted to avoid humidity. You know, they had asthma whatever,
17:19
Speaker 3: breathing issues, and they wanted that dry air.
17:23
Speaker 4: I don't remember what that was. It'll come to me momentary.
17:26
Speaker 2: Let's get a couple of talkbacks in.
17:29
Speaker 7: Larry Curtis. Listen, it's fate. If you're gonna win, don't
17:34
Speaker 7: spend all your money bye. One ticket. That's all it takes,
17:39
Speaker 7: and it's your turn. It's your turn to win, and
17:42
Speaker 7: if not so, the pod will go up again. You
17:46
Speaker 7: can try again next time.
17:48
Speaker 1: One ticket. The Natalie Vaka theory. By the way, if
17:51
Speaker 1: you're listening, Natalie would love to talk to you. She's
17:54
Speaker 1: that's up to a billion dollars now right, it is
17:57
Speaker 1: a billion dollars.
17:58
Speaker 2: Natalie's ghosting us.
18:00
Speaker 8: Hey, guys, why is nobody mentioning how much property taxes
18:04
Speaker 8: these properties are already paying? What is the property tax
18:08
Speaker 8: on a two hundred and fifty million dollar property? How
18:12
Speaker 8: much is he already paying?
18:13
Speaker 1: Oh, you're exactly right. No, no, no, this was a
18:16
Speaker 1: gift from the governor because she wasn't going to raise
18:19
Speaker 1: other taxes that he wanted raised. Never should have happened.
18:23
Speaker 1: This never ever should have happened. And like everything that
18:25
Speaker 1: gets rolled out by this mayor.
18:28
Speaker 2: It was a disaster.
18:29
Speaker 1: Now let's get the seven thirty News with dari Albingerderia.
18:33
Speaker 9: Morning, guys, chance for a shower today. I have eighty
18:36
Speaker 9: eight degrees. Connecticut's primaries are in the books. The governor
18:40
Speaker 9: is going to run for reelection, but a long term
18:42
Speaker 9: congressman's career is over for now.
18:44
Speaker 10: In Connecticut's Democratic primary, NBC News is projecting Governor Ned
18:47
Speaker 10: Lamont the winner over Challenger Josh Elliott. Lamont will now
18:51
Speaker 10: faced republic and State Senator Ryan Fazio in the general election.
18:54
Speaker 8: I want to give a shout out to Josh ellentt.
18:56
Speaker 5: He ran a.
18:57
Speaker 8: Feisty campaign, raised very important issues. Look forward to working
19:01
Speaker 8: together as one into this fall what we can do together.
19:04
Speaker 10: Meanwhile, long time incumbent Congressman John Larson, he's out. NBC
19:08
Speaker 10: News is projecting the fourteen term Democrat was beaten by
19:11
Speaker 10: challenger Luke Bronan in Connecticut's first congressional district. Bronan is
19:15
Speaker 10: the former mayor of Hartford. I'm Skafpringle WRDWS.
19:18
Speaker 9: Today is a deadline for all ICE agents to have
19:21
Speaker 9: body cameras. We're also learning that they're going to be
19:24
Speaker 9: getting something else, gloves that can deliver painful shocks. The
19:27
Speaker 9: Department of Homeland Security is spending twenty million dollars on
19:30
Speaker 9: the gloves, which could be distributed as soon as next March.
19:34
Speaker 9: Violent crime is dropping in major cities. That from the
19:37
Speaker 9: Major Chiefs Association, which says homicides are down over seventeen percent,
19:42
Speaker 9: robberies down more than sixteen percent. The NYPD says three
19:46
Speaker 9: thousand guns have been removed from the city streets so
19:49
Speaker 9: far this year.
19:50
Speaker 11: That's three thousand fewer weapons that can be used to
19:54
Speaker 11: terrorize neighborhoods, and countless tragedies stop before they could happen
19:58
Speaker 11: because law enforcement took action.
20:01
Speaker 9: Commissioner Jessica Tish a candilight vigil will be held tonight
20:05
Speaker 9: in Queens for the victims of the deadly earthquake this
20:08
Speaker 9: week in Columbia. There's also going to be a collection
20:11
Speaker 9: drive this weekend in Elizabeth, New Jersey. Well, did you
20:14
Speaker 9: buy your Powerball tickets? Because the drawing is not going
20:18
Speaker 9: to be for a billion dollars. It's one point two
20:21
Speaker 9: billion dollars and it could be more depending on ticket sales.
20:25
Speaker 9: If you're opting for the cash option at this moment,
20:28
Speaker 9: it would be five hundred and fifty one point seven
20:31
Speaker 9: million dollars. Next News seven eight o'clock bulletins at once.
20:36
Speaker 9: I'm Daria Albinger on seven to ten wor.
20:40
Speaker 5: Ah.
20:40
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22:06
Speaker 1: We're talking about it a lot on this show about
22:09
Speaker 1: a massive national controversy. They just had hearings in the
22:14
Speaker 1: Senate in Connecticut over this over flock safety automated license
22:20
Speaker 1: plate readers, so a lot of people just call them
22:23
Speaker 1: flock cameras. There's a controversy over mass surveillance, over civil liberties,
22:28
Speaker 1: over data privacy, and so the perfect guy to talk
22:32
Speaker 1: to about all of this is on the phone right now,
22:34
Speaker 1: Rich DeMuro rich on Tech has heard Sunday nights from
22:37
Speaker 1: eight to eleven pm on WOOR and you can talk
22:41
Speaker 1: to him at rich on Tech on Instagram. Rich, this
22:46
Speaker 1: flock controversy, you know, has blown up now and there's
22:50
Speaker 1: there's over well over ten thousand of these across the
22:54
Speaker 1: country that have been used for a while. The controversy
22:58
Speaker 1: is over mass surveil and so what they're doing with
23:01
Speaker 1: your data. And I know that there's been a lot
23:04
Speaker 1: of problems in some local police departments where the police
23:07
Speaker 1: officers themselves have used them for personal reasons.
23:11
Speaker 2: What do you say, first of all, tell us how
23:13
Speaker 2: these work.
23:15
Speaker 5: So it's interesting. I had to look in my notes
23:17
Speaker 5: to see the first time I did a story on
23:19
Speaker 5: these cameras, it was back in twenty nineteen. We went
23:21
Speaker 5: to a neighborhood and they were so excited to install these.
23:25
Speaker 5: And back in the day when these first started, basically,
23:27
Speaker 5: if you were a homeowner's association or a neighborhood, you
23:31
Speaker 5: would pay, you would gather everyone together pay for these cameras,
23:34
Speaker 5: pay for the maintenance, and you would install them at
23:36
Speaker 5: the opening of your street, at the two ends of
23:38
Speaker 5: basically the opening and closing of your street, so that
23:41
Speaker 5: every license play, every car that would come into your neighborhood,
23:44
Speaker 5: you had a log, and so if there was ever
23:46
Speaker 5: a crime in your neighborhood, is there ever a problem,
23:48
Speaker 5: you could just go into that log and you can
23:50
Speaker 5: find the car. You can actually slice and dice a
23:52
Speaker 5: lot of different ways, but one of them is, hey,
23:55
Speaker 5: show me all the cars that came into this neighborhood
23:57
Speaker 5: this week that don't typically come into this neighborhood, and
23:59
Speaker 5: then you can now down from there. Since then, obviously
24:02
Speaker 5: the popularity of these cameras have exploded, and I think
24:05
Speaker 5: the really interesting aspect to what flock is doing is
24:09
Speaker 5: the kind of network they are building. So when you
24:12
Speaker 5: have a camera system in you somewhere in Chicago, or
24:15
Speaker 5: somewhere in Florida, or somewhere in Minneapolis wherever, you can
24:19
Speaker 5: potentially link all of those together if you decide to
24:22
Speaker 5: share your data, and that's what makes this giant database
24:26
Speaker 5: that then people can tap into and say, let me
24:28
Speaker 5: find out where this license plate has gone in the
24:30
Speaker 5: past week. And according to all these different cameras in
24:33
Speaker 5: different places, you may be able to track that.
24:36
Speaker 3: Oh so maybe your boyfriend, girlfriend, wife a hushman. They
24:42
Speaker 3: could tap into that too if they're a little suspicious
24:45
Speaker 3: of their mate.
24:47
Speaker 5: I mean theoretically, because these things are typically run by
24:51
Speaker 5: homeowner association. So yeah, probably if you wanted to see
24:54
Speaker 5: what's going on. I mean, look, we have cameras. Are
24:57
Speaker 5: not new. We have so many cameras in cities all
25:00
Speaker 5: across the world. New York City has a lot of cameras.
25:03
Speaker 5: The difference here, I think is that the cities run
25:07
Speaker 5: purpose built systems for what they need, right like the
25:10
Speaker 5: LAPD or the NYPD or whatever department, they have cameras
25:15
Speaker 5: for their specific needs. Right, we want to cover this area,
25:17
Speaker 5: we want to watch this. With Flock, it's a private
25:20
Speaker 5: company that is putting cameras in sometimes private or public places.
25:25
Speaker 5: But that network effect of hey, we could theoretically link
25:29
Speaker 5: up all of these cameras across the nation for one
25:32
Speaker 5: giant mass surveillance. I think that's the aspect people have
25:35
Speaker 5: an issue with. We've got ring cameras on doorbells across
25:38
Speaker 5: the nation right now. There's not one major database that
25:41
Speaker 5: you can just say, let me type something into this
25:43
Speaker 5: database and check every ring camera in America. Is that possible? Sure?
25:48
Speaker 5: Is it happening right now?
25:49
Speaker 1: No? And with the advent of AI, I think that's
25:52
Speaker 1: what the concern is, how quickly they can get so
25:55
Speaker 1: much information on you and then share it. And I
25:59
Speaker 1: think a lot of the municipalities say, Okay, we're not
26:01
Speaker 1: going to share it with the federal government. We're just
26:03
Speaker 1: going to share it with the states that are around us.
26:06
Speaker 1: I'm not sure that's enough, But you know what, Rick,
26:09
Speaker 1: I'm torn on this a little bit because ten thousand
26:12
Speaker 1: missing children have been found by these things, and they
26:15
Speaker 1: say the twenty five percent of the crimes these Flock
26:19
Speaker 1: cameras have helped law enforcement crack the cases, So I
26:23
Speaker 1: would think there has to be some kind of in
26:25
Speaker 1: between here.
26:27
Speaker 5: Oh absolutely. I mean, look, these cameras, they solve crimes,
26:30
Speaker 5: they reunite people with the ring cameras, they reunite pets
26:34
Speaker 5: with their owners. I think they're doing last I checked
26:36
Speaker 5: like an average of one pet a day. I mean,
26:39
Speaker 5: these are real impacts on people. And the other aspect is, hey, look,
26:42
Speaker 5: if you're not doing anything wrong, do you really care?
26:44
Speaker 5: It's not a big deal. You're finding bad guys. But
26:46
Speaker 5: you know, do we want to live in a society
26:48
Speaker 5: where if something happened and they say, let's put out
26:50
Speaker 5: an APB for rich Tamiro, you can find me in
26:53
Speaker 5: twenty seconds because every single camera in the world can
26:56
Speaker 5: use AI to search for my face. Do we want
26:58
Speaker 5: that reality in our world, in our America? I'm not sure.
27:02
Speaker 5: Do we want to solve crimes? Do you want to
27:03
Speaker 5: get bad guys behind bars? Do we want to catch
27:05
Speaker 5: people that do think bad things? Of course? But where
27:08
Speaker 5: does it end? And I think with AI it opens
27:11
Speaker 5: up a lot of questions because it can be instantaneous
27:15
Speaker 5: on how fast you could track someone anywhere in the
27:18
Speaker 5: States where you might have cameras that are linked together.
27:20
Speaker 3: Well, Rich DeMuro sounds very O'wellian, sounds just like Red
27:25
Speaker 3: China to me, fluck the flock. But let's move to AI.
27:31
Speaker 3: Steve Hilton is the Republican candidate for governor. He knows
27:35
Speaker 3: about technology. His wife used to be the communications chief
27:40
Speaker 3: of Google and full Facebook. He carries a flip phone
27:44
Speaker 3: because he says, I don't need all the clutter. Just
27:46
Speaker 3: calls and texts, That's it. But he said that Open AI,
27:50
Speaker 3: sam Oltman and the Anthropic CEO are spreading doom and
27:56
Speaker 3: gloom and that's why there's so much negative feedback SAI.
28:01
Speaker 3: And I'm saying, Rich, isn't this because these are the
28:04
Speaker 3: two guys in the lead of the race and developing
28:07
Speaker 3: AI with the billions that are pouring in, and this
28:10
Speaker 3: doom and gloom statements that they keep mating making will
28:14
Speaker 3: actually force the Senate and government to input regulations while
28:19
Speaker 3: they're ahead, which would hurt the competition.
28:23
Speaker 5: I mean, it's a very good theory, and a lot
28:25
Speaker 5: of people may think that because, yes, if they put
28:29
Speaker 5: regulations in place, Open AI, Anthropic who's right there trying
28:33
Speaker 5: to help the government with these regulations. The two biggest
28:37
Speaker 5: companies that are set to really benefit from being the
28:42
Speaker 5: front runners and saying, Okay, all your little guys, all
28:44
Speaker 5: the other people trying to do stuff, you know, let's
28:46
Speaker 5: make sure you can't. Look. There is so much when
28:50
Speaker 5: it comes to AI on both sides. Some people say
28:53
Speaker 5: it's going to be end of all humanity. Some people
28:55
Speaker 5: say it's going to be the best thing that's ever
28:57
Speaker 5: happened to humanity, And so we don't know yet. I mean,
29:02
Speaker 5: I really think at this point we cannot stop the progress.
29:05
Speaker 5: We have to let these companies do things, but we
29:08
Speaker 5: also can't let them go unchecked the way that we
29:11
Speaker 5: let all of the big social media networks Facebook, Instagram
29:15
Speaker 5: go un checked for so many years. And look what
29:17
Speaker 5: they're doing when it comes to mental health when it
29:18
Speaker 5: comes to teenagers. So we can't let that happen. But
29:21
Speaker 5: we also cannot let China, who, by the way, is
29:25
Speaker 5: already putting out a lot of open source models that
29:28
Speaker 5: people in the US are using, and they're coming from
29:30
Speaker 5: China because guess what, they're free and they're easy to
29:32
Speaker 5: use versus the paid stuff from open AI and anthropic.
29:35
Speaker 5: We cannot let that happen in a big way because
29:38
Speaker 5: it does have implications for these companies that I've spent
29:40
Speaker 5: so much money investing in what they're doing.
29:42
Speaker 2: Rich DeMuro, we never have enough time with you.
29:44
Speaker 1: I have a whole list of things I wanted to
29:46
Speaker 1: talk to you about that we can't wait to talk
29:49
Speaker 1: to you next week because I'll take the same list out.
29:52
Speaker 1: Rich DeMuro has heard Sunday nights from eight to eleven
29:55
Speaker 1: pm on WOOR. You can reach out to them on
29:58
Speaker 1: richontech dot com.
30:00
Speaker 2: Rich thanks again, you were enlightening. Thank you very.
30:03
Speaker 5: Much, Thanks Larry, Thanks Curtis.
30:06
Speaker 1: When we come back, Oh, Natalie mgleory is going to
30:10
Speaker 1: be here, we'll find out what you know what.
30:12
Speaker 3: Yes, you'll be telling us how you can be cool
30:15
Speaker 3: on the subway platforms when it's one hundred degrees upstairs
30:20
Speaker 3: in the shade.
30:22
Speaker 2: Wait a second, the city's promising that, why are you laughing?
30:26
Speaker 2: Promising that.
30:28
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Speaker 3: Now it's sevent ten wrs Beat on the street with
32:18
Speaker 3: Natalie Migliori. Oh, and out of the hot, sweltering, stinky
32:24
Speaker 3: subway platforms and into these magnificent suites of iHeart and
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32:38
Speaker 3: to paradise.
32:40
Speaker 12: Yes, especially with the air conditioning up in here. Okay,
32:43
Speaker 12: because everybody knows. You go down into the New York
32:46
Speaker 12: City subway system and sometimes instead of standing on the platform,
32:50
Speaker 12: you'd rather be on the street because the temperature rises upwards.
32:54
Speaker 2: Of five to not maybe thirty degrees.
32:57
Speaker 12: Sometimes if you're down there, it's hotter than just standing
33:01
Speaker 12: in the direct sun, sometimes suffocating, Okay, And the city
33:05
Speaker 12: knows this, and that's why they're considering a new initiative
33:08
Speaker 12: that could change all of that.
33:11
Speaker 4: Okay, if it works.
33:12
Speaker 12: The NCAA talking about exploring thermal energy network that would
33:17
Speaker 12: cool the subway platforms, take all the excess heat, store
33:22
Speaker 12: it underground, and then use it to warm nearby offices
33:26
Speaker 12: or apartment buildings in the winter. That's above my pay grade, okay, Okay.
33:32
Speaker 3: What about the stink though, Does it absorbed that with
33:35
Speaker 3: the heat.
33:37
Speaker 12: That is something they're gonna have to study, okay, right,
33:40
Speaker 12: and we're gonna get into how much that study is
33:42
Speaker 12: gonna cost. But what do subway riders suffering on the
33:46
Speaker 12: platform think about this initial idea?
33:49
Speaker 13: I mean it sounds good in theory. I'm always like
33:51
Speaker 13: a little scared of like the plans when it comes
33:53
Speaker 13: to like the subway stations and things, because sometimes it
33:56
Speaker 13: doesn't work out, like it kind of like turns into
33:59
Speaker 13: something we're not thinking it is.
34:00
Speaker 6: That might be a good idea, just because I think
34:03
Speaker 6: heating bill even cooling bills this summer is like a
34:06
Speaker 6: really big aspect, and I think I'm gonna use this
34:08
Speaker 6: heat that we're experiencing. We're do sing it and then
34:11
Speaker 6: putting into the winds sur if you really.
34:12
Speaker 3: Helped ul I actually don't know how they're able to
34:15
Speaker 3: do that, but I like how they're trying to find
34:17
Speaker 3: new ways to do that kind of stuff.
34:19
Speaker 4: All right now.
34:19
Speaker 12: The city would test this out at the Brooklyn Bridge
34:22
Speaker 12: City Hall and Chamber Street stations, which gets some major
34:26
Speaker 12: complaints about being some of the hottest platforms in the city.
34:30
Speaker 12: A lot of New York are selling me just go
34:32
Speaker 12: to any platform in the city and you'll know what
34:34
Speaker 12: they're talking about. Though, a lot of people I talk
34:37
Speaker 12: to actually holding fans, well they wait on the platform.
34:41
Speaker 12: One guy so nice. As I asked him the question,
34:44
Speaker 12: he would turn the fan on me, and then when
34:45
Speaker 12: he would go to talk, he would turn the fan
34:47
Speaker 12: on himself.
34:47
Speaker 2: Oh so sweet?
34:49
Speaker 4: Was she flirting with you? Who knows?
34:51
Speaker 2: I batted my eyes a couple of times. More fan,
34:55
Speaker 2: get me, more fan?
34:56
Speaker 5: Anything?
34:58
Speaker 4: Blow early?
35:00
Speaker 2: My eyelashes were getting in the way.
35:02
Speaker 12: Anyway, it's saying people saying it's about time the city
35:06
Speaker 12: do something about there's unbearable heat.
35:09
Speaker 14: I'm not just thinking about myself, but also like the
35:11
Speaker 14: older generation as well too, that may you know, have
35:14
Speaker 14: like any like underlying conditions where the heat might even
35:18
Speaker 14: allow them to, you know, just to pass out. So
35:20
Speaker 14: for me, I would say that that would be incredible
35:22
Speaker 14: if an opportunity were to be presented for us to
35:25
Speaker 14: be you know, in a more ventilated train station or platform.
35:30
Speaker 4: Wow, what an optimist.
35:32
Speaker 3: Yeah, how about we just start on the train cars
35:34
Speaker 3: themselves on the weekends, disaster. I would estimate on the
35:39
Speaker 3: trains that I've taken in the subway, one out of
35:41
Speaker 3: every four cars, the air conditioning is not working.
35:44
Speaker 12: There were some complaints in the conversations I had with people,
35:47
Speaker 12: But the idea to them is, in the time that
35:52
Speaker 12: they've been taking these trains, they've realized that there is
35:57
Speaker 12: more air conditioning than when they first started.
35:59
Speaker 4: When they were kids were telling me.
36:01
Speaker 12: So they've seen the strides in that now they want
36:03
Speaker 12: to somewhat see the platform stackle. Now the NTA is
36:07
Speaker 12: studying the possibility of this thermal technology. It'll cost him
36:11
Speaker 12: eight hundred thousand dollars just for the study. The agency
36:15
Speaker 12: says the money's coming from congestion pricing. We all know it,
36:19
Speaker 12: leaving some writers wondering where that money has been going
36:24
Speaker 12: this whole time.
36:25
Speaker 13: I think how h is a spend our money is
36:27
Speaker 13: just a little confusing because it's like tax dollars, and
36:29
Speaker 13: then it's also like just transit prices in general and
36:32
Speaker 13: how they're like going up and things like that. So
36:34
Speaker 13: it is like it is like a curiosity for me,
36:36
Speaker 13: like where money is really going and what's really being prioritized.
36:40
Speaker 14: I'm just contemplating on actually where the money's going. If
36:43
Speaker 14: the trains are exactly the same as they were ten
36:46
Speaker 14: to fifteen years ago. If the platforms are the same
36:48
Speaker 14: as well too, so what exactly are they doing with
36:51
Speaker 14: the money both.
36:51
Speaker 6: My uncle drives a lot and he always talked out
36:54
Speaker 6: condres to be so high. So I think if food
36:56
Speaker 6: can be put into like a more effective use, it
36:58
Speaker 6: would be really helpful. I think more people might be
37:00
Speaker 6: more willing to pay for if they actually see like
37:02
Speaker 6: an effect from the conduction.
37:04
Speaker 4: I know where it goes.
37:05
Speaker 3: The acronym MTA money taking agency goes.
37:09
Speaker 4: In and you never see it actually surface.
37:13
Speaker 12: But I think it's interesting to hear. Especially young people
37:16
Speaker 12: who I talk to, want to know where this money
37:18
Speaker 12: is going, right, and they want to see the books
37:20
Speaker 12: in a sense. I just got a text as somebody
37:22
Speaker 12: is listening, my brother says fiftieth Street is so hot,
37:27
Speaker 12: So everybody says, some guy listed out forty second, thirty fourth.
37:31
Speaker 12: You would think the main veins that they would want
37:33
Speaker 12: people to come in.
37:35
Speaker 1: Yeah, this thermal cooling system has been used before across
37:38
Speaker 1: the world.
37:38
Speaker 2: So it's a good idea. It might work.
37:41
Speaker 1: When we come back, we're going to talk more about
37:44
Speaker 1: the primaries. But first area Albinger with the eight o'clock
37:47
Speaker 1: News