1 00:00:00,600 --> 00:00:03,760 Speaker 1: You just heard the news. Now you'll find out what 2 00:00:03,880 --> 00:00:15,040 Speaker 1: it all means. Hey, smart simone on seven ten. Well, 3 00:00:15,080 --> 00:00:17,880 Speaker 1: we'll get to Donald Trump, Pam Bondy, we'll get to 4 00:00:18,000 --> 00:00:21,520 Speaker 1: bad Bunny and mom Donnie's in Albany asking for money. 5 00:00:21,520 --> 00:00:24,159 Speaker 1: We'll get hey, developments in Minnesota. We'll get to that. 6 00:00:24,239 --> 00:00:28,840 Speaker 1: We'll get to the Guthrie kidnapping. We'll get to Valentine's Day, 7 00:00:28,920 --> 00:00:31,680 Speaker 1: and a whole lot more coming up. It's thirty six 8 00:00:31,880 --> 00:00:36,240 Speaker 1: days until spring. It's not bad today, it'll be a 9 00:00:36,720 --> 00:00:38,720 Speaker 1: mid thirties maybe upper thirty is gonna be in the 10 00:00:38,760 --> 00:00:42,400 Speaker 1: forties over the weekends, forties next week, and then once 11 00:00:42,400 --> 00:00:45,160 Speaker 1: you get through next week, you'll only have like four 12 00:00:45,159 --> 00:00:48,760 Speaker 1: weeks till spring. So, hey, before we start, want to 13 00:00:48,800 --> 00:00:54,440 Speaker 1: thank Barrett Media. Now, in the radio business, Barrett Media 14 00:00:54,640 --> 00:00:57,480 Speaker 1: is like the Bible of the industry. It's the official 15 00:00:58,120 --> 00:01:01,520 Speaker 1: trade magazine of radio, talk, radio, music, radio, all kinds 16 00:01:01,520 --> 00:01:06,200 Speaker 1: of radio. It's the the trade magazine Barrett Media. It's 17 00:01:06,200 --> 00:01:08,240 Speaker 1: a website. You can go look at it, and you should. 18 00:01:08,600 --> 00:01:11,360 Speaker 1: It's actually got very interesting stuff if you're interested in 19 00:01:11,480 --> 00:01:14,840 Speaker 1: radio and news and talk, and they got all kinds 20 00:01:14,840 --> 00:01:18,800 Speaker 1: of great stories. Barrettmedia dot Com, two ours, two teas 21 00:01:18,959 --> 00:01:23,200 Speaker 1: Barrettmedia dot Com and then every year at this time 22 00:01:23,240 --> 00:01:26,960 Speaker 1: they do. This is like our equivalent of the Academy Awards, 23 00:01:28,080 --> 00:01:29,840 Speaker 1: and the best thing you can win is a number 24 00:01:29,880 --> 00:01:33,800 Speaker 1: one show. There's a number one show in America, morning show, 25 00:01:33,920 --> 00:01:37,360 Speaker 1: number one, afternoon show, number one midday show. And it 26 00:01:37,440 --> 00:01:40,080 Speaker 1: just came out today we won as the number one 27 00:01:40,120 --> 00:01:44,600 Speaker 1: show in America mid days, number one in America. This 28 00:01:44,680 --> 00:01:47,440 Speaker 1: is like winning the Oscar for Best Pictures. So it's 29 00:01:48,600 --> 00:01:50,480 Speaker 1: a great honor for all of us here that work 30 00:01:50,520 --> 00:01:53,920 Speaker 1: on the show, management, everybody in the control room, everybody here. 31 00:01:54,520 --> 00:01:56,720 Speaker 1: Number one. We won last year's number one. We're number 32 00:01:56,720 --> 00:01:59,280 Speaker 1: one again this year, so thanks to Barrett Media. But 33 00:01:59,320 --> 00:02:01,400 Speaker 1: start reading this site every day. I think you'll like it. 34 00:02:01,440 --> 00:02:04,160 Speaker 1: You'll learn a lot of stuff, not just about radio, 35 00:02:04,240 --> 00:02:07,240 Speaker 1: but a lot of stuff about news and talk, and 36 00:02:07,280 --> 00:02:10,399 Speaker 1: they very good at covering cable news stuff. But it's 37 00:02:10,440 --> 00:02:15,600 Speaker 1: like the trade magazine of the radio industry. Barrettmedia dot Com. 38 00:02:15,720 --> 00:02:19,960 Speaker 1: Check it out. It's Jason Barrett and Barrettmedia dot Com. 39 00:02:20,000 --> 00:02:23,320 Speaker 1: It's a great honor and we're very happy about it, 40 00:02:23,360 --> 00:02:25,360 Speaker 1: which means we got to now, look, we got to 41 00:02:25,360 --> 00:02:27,760 Speaker 1: make room for another we have it. The last year's 42 00:02:27,800 --> 00:02:30,120 Speaker 1: framed over there. We got to put another one over there. 43 00:02:30,760 --> 00:02:33,880 Speaker 1: But that's a good problem to have. The latest on 44 00:02:33,960 --> 00:02:37,840 Speaker 1: the Guthrie kidnapping. They found the glove, as you know, 45 00:02:38,480 --> 00:02:40,280 Speaker 1: on the side of the road. But here's the part 46 00:02:40,320 --> 00:02:44,880 Speaker 1: you might not realize. You know, it's a huge area, 47 00:02:44,919 --> 00:02:47,200 Speaker 1: it's a lot of desert. It's an enormous area. Why 48 00:02:47,200 --> 00:02:50,040 Speaker 1: would they pull up there and find a glove there? Well, 49 00:02:51,040 --> 00:02:53,520 Speaker 1: they're not saying much. The feds are now running things, 50 00:02:53,560 --> 00:02:57,320 Speaker 1: not the locals, and the Feds keep everything very quiet. 51 00:02:57,360 --> 00:03:01,839 Speaker 1: They don't talk, they don't let on. But apparently they 52 00:03:01,880 --> 00:03:04,800 Speaker 1: have gone to looking at every car that was in 53 00:03:04,840 --> 00:03:09,760 Speaker 1: the area around that time, anywhere near that time that night. 54 00:03:10,000 --> 00:03:14,680 Speaker 1: You can get the GPS off cell phones. Your phone 55 00:03:14,800 --> 00:03:17,840 Speaker 1: has a GPS in it, and whether you want to, 56 00:03:18,040 --> 00:03:20,680 Speaker 1: whether you use it or not, that GPS is always working. 57 00:03:20,720 --> 00:03:22,679 Speaker 1: Even if you have your phone shut off, that GPS 58 00:03:22,760 --> 00:03:25,600 Speaker 1: is working because as soon as you turn it back on, 59 00:03:25,720 --> 00:03:29,440 Speaker 1: it'll upload the GPS information to somewhere. It's a place 60 00:03:29,480 --> 00:03:34,480 Speaker 1: where only federal authorities and really good you know, investigators 61 00:03:34,480 --> 00:03:38,160 Speaker 1: can get to it. But apparently they were tracking cars 62 00:03:38,200 --> 00:03:41,360 Speaker 1: that were going on certain routes, so that's where they 63 00:03:41,400 --> 00:03:43,800 Speaker 1: happened to see that glove. They were following the route 64 00:03:43,840 --> 00:03:45,720 Speaker 1: of a car that they had seen. They'd seen the 65 00:03:45,760 --> 00:03:48,360 Speaker 1: GPS on that car going that route, so they were 66 00:03:48,400 --> 00:03:51,320 Speaker 1: driving that route, looking going slow, looking out the window, 67 00:03:52,000 --> 00:03:53,920 Speaker 1: and they saw the glove. It appears to be the 68 00:03:53,960 --> 00:03:59,400 Speaker 1: glove that the invader there, the kidnapper, was wearing in 69 00:03:59,440 --> 00:04:03,760 Speaker 1: that video. We've all seen. It's a big, puffy, very 70 00:04:03,840 --> 00:04:07,320 Speaker 1: winter ski glove kind of thing, so not something anybody 71 00:04:07,320 --> 00:04:11,080 Speaker 1: in Tucson would ever own or wear. Very unusual, even 72 00:04:11,120 --> 00:04:14,560 Speaker 1: that big puffy coat. Tucson doesn't get that cold. So 73 00:04:14,640 --> 00:04:18,320 Speaker 1: they've found the glove, and because it's such a warm, 74 00:04:18,440 --> 00:04:21,719 Speaker 1: warm glove in such a hot climate, it's assumed that 75 00:04:21,760 --> 00:04:24,640 Speaker 1: the person must have sweated a lot wearing all that stuff, 76 00:04:25,279 --> 00:04:28,400 Speaker 1: and that sweat left a lot of DNA inside the glove. 77 00:04:28,440 --> 00:04:32,200 Speaker 1: It's possible there could be a fingerprint, although highly unlikely, 78 00:04:33,680 --> 00:04:36,560 Speaker 1: but they're looking at the glove looking for DNA. All 79 00:04:36,600 --> 00:04:40,320 Speaker 1: that sweat inside the glove could create some DNA. The 80 00:04:40,360 --> 00:04:42,360 Speaker 1: other thing they're looking at is the outside of the glove, 81 00:04:43,040 --> 00:04:46,159 Speaker 1: looking for any traces of blood because as we know, 82 00:04:46,800 --> 00:04:48,960 Speaker 1: Nancy Guthrie was bleeding as they took her out, and 83 00:04:49,000 --> 00:04:52,680 Speaker 1: it's possible the glove touched the touch the face or 84 00:04:52,720 --> 00:04:54,760 Speaker 1: wherever she was bleeding and got some blood on it, 85 00:04:54,800 --> 00:04:57,760 Speaker 1: so you'd have two sets of DNA on that glove. 86 00:04:57,839 --> 00:05:02,960 Speaker 1: So that's what they're looking at. Been somehow TMZ got 87 00:05:02,960 --> 00:05:06,560 Speaker 1: themselves a little too involved in this. If you have 88 00:05:06,640 --> 00:05:09,880 Speaker 1: anything to report, call the FBI. That's the best way 89 00:05:09,880 --> 00:05:11,080 Speaker 1: to do it. But a lot of people have been 90 00:05:11,120 --> 00:05:13,880 Speaker 1: going to TMZ, which they're very nice. Harvey Levin's a 91 00:05:13,880 --> 00:05:17,440 Speaker 1: great guy and tmzs a lot of fun to read, 92 00:05:17,520 --> 00:05:20,719 Speaker 1: but it's like, I don't mean this in a bad way, 93 00:05:20,720 --> 00:05:24,080 Speaker 1: but it's today's version of the National Inquirer, and they 94 00:05:24,160 --> 00:05:26,680 Speaker 1: print all kinds of stuff. They got all kinds of sources, 95 00:05:27,000 --> 00:05:28,880 Speaker 1: and a lot of times the stuff is true, but 96 00:05:28,920 --> 00:05:32,040 Speaker 1: sometimes it's not so true. I like the National Inquirer, 97 00:05:32,120 --> 00:05:34,240 Speaker 1: which broke a lot of big stories, but a lot 98 00:05:34,240 --> 00:05:37,440 Speaker 1: of stuff they broke didn't turn out to be exactly true. 99 00:05:37,440 --> 00:05:40,040 Speaker 1: So you got the same problem with TMZ. People are 100 00:05:40,040 --> 00:05:43,400 Speaker 1: going there. FBI is getting tips. Now. The tips are 101 00:05:43,520 --> 00:05:47,760 Speaker 1: very important because somebody might recognize something on that video. 102 00:05:48,080 --> 00:05:50,320 Speaker 1: The way the guy's eyes looked or something about his shape. 103 00:05:50,360 --> 00:05:55,960 Speaker 1: But they've gotten eighteen thousand tips. Now, it takes incredible 104 00:05:56,000 --> 00:05:58,120 Speaker 1: manpower because you got to run down each one of 105 00:05:58,160 --> 00:06:01,920 Speaker 1: them eighteen and tips have come in. That's why they 106 00:06:01,960 --> 00:06:05,240 Speaker 1: arrested that delivery guy the other day. Now, if you 107 00:06:05,279 --> 00:06:09,599 Speaker 1: look at that guy, his shape, his body, his shoulders, 108 00:06:09,600 --> 00:06:12,160 Speaker 1: the shape of his arms, his legs, he looks exactly 109 00:06:13,240 --> 00:06:15,160 Speaker 1: like the guy in the video, and his eyes look 110 00:06:15,240 --> 00:06:17,359 Speaker 1: like those guy's video. He has a mustache just like 111 00:06:17,440 --> 00:06:20,279 Speaker 1: the guy. The outline of him is exactly the same 112 00:06:20,279 --> 00:06:23,000 Speaker 1: as the guy in the video. They've determined it's not him. 113 00:06:23,000 --> 00:06:25,599 Speaker 1: I assume he could prove where he was and it 114 00:06:25,640 --> 00:06:28,080 Speaker 1: was nowhere near there that night. But he was a 115 00:06:28,120 --> 00:06:31,720 Speaker 1: delivery guy. And again they were checking the GPS's of 116 00:06:31,800 --> 00:06:36,040 Speaker 1: phones tracing the cars, and apparently his delivery route that 117 00:06:36,160 --> 00:06:39,000 Speaker 1: night took him somewhere near that house. That's why they 118 00:06:39,000 --> 00:06:40,039 Speaker 1: pulled this guy over. 119 00:06:40,279 --> 00:06:42,000 Speaker 2: And once they saw they were following me, I pulled over. 120 00:06:42,040 --> 00:06:44,040 Speaker 2: They didn't even have to put a traffic stopper any day. 121 00:06:44,080 --> 00:06:45,960 Speaker 2: I got off the car and they arrested me as 122 00:06:46,000 --> 00:06:46,920 Speaker 2: soon as I got off the car. 123 00:06:47,120 --> 00:06:48,919 Speaker 1: Yeah, he looked like the guy in the it's not 124 00:06:48,960 --> 00:06:50,600 Speaker 1: the guy in the video. They've determined, but he looked 125 00:06:50,600 --> 00:06:50,840 Speaker 1: like it. 126 00:06:50,880 --> 00:06:53,440 Speaker 2: And then the detective guy here was the FBI agent 127 00:06:53,520 --> 00:06:56,200 Speaker 2: in the Santa Cruz County and they told me I 128 00:06:56,360 --> 00:06:58,880 Speaker 2: was being detained for kidnapping. And I asked him, I 129 00:06:59,000 --> 00:07:01,920 Speaker 2: will kidnapping of who told me this? Eighty I don't 130 00:07:01,920 --> 00:07:06,560 Speaker 2: know her name and Nancy Guthrie, Yeah, sir, I told 131 00:07:06,640 --> 00:07:08,640 Speaker 2: him I worked it two or some for Glas. I 132 00:07:08,720 --> 00:07:10,280 Speaker 2: might have delivered a back at your house, but I 133 00:07:10,320 --> 00:07:12,840 Speaker 2: know cannaotp pay anybody. They hold me from from like 134 00:07:13,040 --> 00:07:14,440 Speaker 2: four to right now. 135 00:07:15,400 --> 00:07:17,640 Speaker 1: Yeah, but they were able to determine he's not the guy, 136 00:07:17,720 --> 00:07:21,720 Speaker 1: so we'll see what happens. I think something's gonna break. 137 00:07:21,720 --> 00:07:24,640 Speaker 1: They're getting eighteen thousand tips. Takes time to run him down, 138 00:07:25,520 --> 00:07:31,440 Speaker 1: but but something could happen. Also, you know this demanding 139 00:07:31,480 --> 00:07:35,400 Speaker 1: bitcoin we've saw the two days ago they made a 140 00:07:35,400 --> 00:07:38,880 Speaker 1: three hundred dollars deposit into that bitcoin account and yesterday 141 00:07:38,920 --> 00:07:42,320 Speaker 1: one hundred dollars deposit. Now what's that all about. Well, 142 00:07:42,720 --> 00:07:46,280 Speaker 1: you may not realize this, but bitcoin can be traced 143 00:07:46,880 --> 00:07:49,720 Speaker 1: if you're using crypto to hide from the authorities, if 144 00:07:49,720 --> 00:07:53,560 Speaker 1: you're a drug dealer, hedge fun guy paying off people 145 00:07:54,160 --> 00:07:58,200 Speaker 1: that you know, whoever uses crypto for nefarious purposes. It 146 00:07:58,640 --> 00:08:00,920 Speaker 1: can be traced. I hate to break it to you. 147 00:08:01,360 --> 00:08:04,040 Speaker 1: So the way you trace it, they'll send a little 148 00:08:04,320 --> 00:08:06,760 Speaker 1: amount in there, like three hundred bucks or yesterday these 149 00:08:06,880 --> 00:08:09,360 Speaker 1: one hundred dollars, and once you send it to a 150 00:08:09,360 --> 00:08:12,680 Speaker 1: bitcoin address, it goes through the chain. It goes through 151 00:08:12,680 --> 00:08:15,840 Speaker 1: the blockchain, and it leaves footprints all over the place. 152 00:08:15,880 --> 00:08:19,320 Speaker 1: You can you can't do it, but the most sophisticated 153 00:08:19,360 --> 00:08:23,920 Speaker 1: federal investigators can trace it through the blockchain and see 154 00:08:23,960 --> 00:08:27,400 Speaker 1: exactly where it lands. So it is traceable. It's been 155 00:08:27,400 --> 00:08:32,200 Speaker 1: done before, so they are tracing the bitcoin as we speak, 156 00:08:32,280 --> 00:08:35,520 Speaker 1: so we'll see what develops. He Hey, Tom Holman has 157 00:08:35,520 --> 00:08:39,840 Speaker 1: announced ICE is leaving Minnesota. It's over. They say they've 158 00:08:39,920 --> 00:08:43,880 Speaker 1: arrested about five six thousand dangerous criminals and they're getting 159 00:08:43,880 --> 00:08:46,120 Speaker 1: the hell out of there. They you know, they oughter 160 00:08:46,280 --> 00:08:50,480 Speaker 1: just to thank Minnesota for their horrifying, awful reception. They 161 00:08:50,559 --> 00:08:52,840 Speaker 1: ought to take the six thousand criminals and just dump 162 00:08:52,880 --> 00:08:55,160 Speaker 1: them right in the middle of Minneapolis. Here's your criminals back, 163 00:08:55,440 --> 00:08:58,760 Speaker 1: here's your dangerous criminals. You want them back here? They are, no, 164 00:08:58,880 --> 00:09:00,920 Speaker 1: but they're not going to do that. But it's the 165 00:09:01,000 --> 00:09:04,640 Speaker 1: end of ICE in Minnesota. They're leaving. They are, of course, 166 00:09:04,720 --> 00:09:07,720 Speaker 1: operating in many other cities on a much bigger scale 167 00:09:08,240 --> 00:09:13,720 Speaker 1: with no problem at all because local authorities cooperate. We 168 00:09:13,760 --> 00:09:16,400 Speaker 1: had Bruce Blakeman on the show the other day, who 169 00:09:16,440 --> 00:09:19,760 Speaker 1: should be the governor in November. He'd be the perfect governor. 170 00:09:19,800 --> 00:09:22,600 Speaker 1: But I said, you know, they're all over NASA. Kenna said, 171 00:09:22,600 --> 00:09:24,480 Speaker 1: how come we have no problems? He said, we cooperate. 172 00:09:24,480 --> 00:09:28,400 Speaker 1: We have full cooperation. We coordinate with them, We lend 173 00:09:28,440 --> 00:09:31,480 Speaker 1: them local help, police detectives, we even lend them jail cells. 174 00:09:31,480 --> 00:09:34,600 Speaker 1: We cooperate, and it's very They do pick up dangerous criminals. 175 00:09:34,640 --> 00:09:37,679 Speaker 1: If we cooperate and coordinate with them, it's orderly, it's very, 176 00:09:37,800 --> 00:09:40,760 Speaker 1: very peaceful. Now that's Bruce Plakeman, who would be a 177 00:09:40,760 --> 00:09:44,880 Speaker 1: great governor. But you got that kookie new Jersey governor, 178 00:09:44,880 --> 00:09:47,839 Speaker 1: the new one, Mikey Cheryl, who sounds like she's a 179 00:09:47,920 --> 00:09:51,080 Speaker 1: fourteen years old, but she's not going to cooperate with ICE. 180 00:09:51,160 --> 00:09:55,120 Speaker 3: I'm signing an executive order to ban ICE from launching 181 00:09:55,240 --> 00:10:00,480 Speaker 3: actions from any state property. That means no ICE stage as, 182 00:10:00,960 --> 00:10:07,280 Speaker 3: no processing locations, no operating basis, no federal civil immigration 183 00:10:07,440 --> 00:10:12,240 Speaker 3: actions run from any state grounds, not our parks, not 184 00:10:12,360 --> 00:10:14,440 Speaker 3: our roadways, not our buildings. 185 00:10:14,520 --> 00:10:15,160 Speaker 2: Here you go. 186 00:10:17,080 --> 00:10:20,360 Speaker 1: Perfect. You want to come in here and arrest dangerous criminals, 187 00:10:20,400 --> 00:10:22,199 Speaker 1: you are not coming in here. We're not going to 188 00:10:22,320 --> 00:10:26,520 Speaker 1: let you do that here. Hey, the bad Bunny stuff continues. 189 00:10:26,600 --> 00:10:29,800 Speaker 1: I'm actually enjoying this bad Bunny stuff because listen, the 190 00:10:29,840 --> 00:10:31,839 Speaker 1: halftime show was pretty good. I don't know what Delly 191 00:10:31,920 --> 00:10:34,360 Speaker 1: was singing about. Who could tell what he was singing? Hey, 192 00:10:34,360 --> 00:10:36,480 Speaker 1: But half the music today I can't understand what they're 193 00:10:36,480 --> 00:10:40,560 Speaker 1: saying either. But and it looked good. It was colorful, 194 00:10:40,679 --> 00:10:44,720 Speaker 1: moving dancing, the sets, the scenery was very well done, 195 00:10:44,880 --> 00:10:49,920 Speaker 1: very well done. It was great. But I mean, it 196 00:10:49,960 --> 00:10:52,840 Speaker 1: wouldn't have been my first choice Bad Bunny, but it 197 00:10:52,920 --> 00:10:56,520 Speaker 1: was worth it. Just all these lefties, all these liberals, 198 00:10:56,559 --> 00:11:00,160 Speaker 1: all these Democrats now have to run around pretending that 199 00:11:00,160 --> 00:11:03,079 Speaker 1: they're bad Bunny fans. They never heard of the guy 200 00:11:03,080 --> 00:11:06,080 Speaker 1: two weeks ago, but they're all running around trying to 201 00:11:06,080 --> 00:11:08,559 Speaker 1: convince you they're bad Bunny fans. Oh I love bad Bunny. 202 00:11:08,600 --> 00:11:11,319 Speaker 1: I love bad Bunny. You do, Oh, I love bad Bunny. 203 00:11:11,520 --> 00:11:16,240 Speaker 1: Name one song by him, You're racist. They just go crazy. 204 00:11:16,280 --> 00:11:19,200 Speaker 1: Even Jimmy Kimmel admits it. This week, almost every liberal 205 00:11:19,240 --> 00:11:21,760 Speaker 1: I know suddenly really into Bad Bunny. 206 00:11:21,920 --> 00:11:24,959 Speaker 2: I mean people I've never heard say the words bad 207 00:11:25,200 --> 00:11:28,080 Speaker 2: or Bunny in their lives, like I can't wait for 208 00:11:28,160 --> 00:11:31,559 Speaker 2: Bad Bunny. Oh, what's your. 209 00:11:34,000 --> 00:11:36,439 Speaker 1: What's your favorite Bad Bunny song? I don't know, but 210 00:11:36,600 --> 00:11:40,280 Speaker 1: I love them. I love that. It's true. They never 211 00:11:40,320 --> 00:11:42,000 Speaker 1: heard of this guy three weeks ago. When was the 212 00:11:42,080 --> 00:11:45,160 Speaker 1: last time you heard anybody, any Democrat, any liberal friend 213 00:11:45,200 --> 00:11:47,960 Speaker 1: of yours say we're going to the Bad Bunny concert 214 00:11:48,040 --> 00:11:50,160 Speaker 1: though we're gonna see Bad Bunny in two weeks. They've 215 00:11:50,200 --> 00:11:56,760 Speaker 1: never heard of this guy ever, ever, ever, So uh, Mom, 216 00:11:56,800 --> 00:12:01,280 Speaker 1: Donnie went to Albany to ask for more taxes. It's 217 00:12:01,320 --> 00:12:04,679 Speaker 1: already the highest tax place in America. Taxes are already 218 00:12:04,720 --> 00:12:07,480 Speaker 1: out of control. He's asking for more taxes. Nobody can 219 00:12:07,520 --> 00:12:13,000 Speaker 1: figure out why. When asked, he gave some ridiculous explanation about, well, 220 00:12:13,000 --> 00:12:15,400 Speaker 1: we're already the most expensive place and might as well. 221 00:12:15,800 --> 00:12:19,080 Speaker 1: They can't figure out how to run things. You know, 222 00:12:19,120 --> 00:12:22,120 Speaker 1: we have the most out of controlled budget in New 223 00:12:22,200 --> 00:12:23,880 Speaker 1: York City and New York State. You know, the New 224 00:12:23,920 --> 00:12:28,600 Speaker 1: York state budget is double the budget of Florida. Double. 225 00:12:30,240 --> 00:12:32,600 Speaker 1: Florida is a bigger state, it has more major cities. 226 00:12:32,840 --> 00:12:35,840 Speaker 1: Our budget is double. Florida has a bigger population. Our 227 00:12:35,880 --> 00:12:38,960 Speaker 1: budget is twice the budget of Florida. New York studies 228 00:12:38,960 --> 00:12:41,400 Speaker 1: budget is like one hundred and twenty billion. It should 229 00:12:41,440 --> 00:12:45,240 Speaker 1: be forty billion. It's all waste, fraud, bloat. You could 230 00:12:45,280 --> 00:12:48,400 Speaker 1: easily cut it now, he implied yesterday, he's done some cutting. 231 00:12:48,720 --> 00:12:51,920 Speaker 1: We had a twelve billion dollar deficit coming up. We 232 00:12:51,960 --> 00:12:54,880 Speaker 1: have lowered that twelve billion dollar gap to seven billion 233 00:12:54,920 --> 00:12:58,720 Speaker 1: dollars over two fiscal years. Well that's a three billion 234 00:12:58,760 --> 00:13:02,080 Speaker 1: dollar cut every year. But again, you could cut half 235 00:13:02,160 --> 00:13:05,840 Speaker 1: the budget out without affecting anything. Just stop the waist, 236 00:13:06,000 --> 00:13:08,599 Speaker 1: the fraud, the bloat. It'd be very easy enough for 237 00:13:08,640 --> 00:13:11,280 Speaker 1: a guy like mom Donnie. I mean, in his defense, 238 00:13:11,840 --> 00:13:14,240 Speaker 1: he's thirty two years old, he never had a job before, 239 00:13:14,240 --> 00:13:16,920 Speaker 1: he's never worked, he's never run anything. But if you're 240 00:13:16,960 --> 00:13:20,840 Speaker 1: brought in a top ceo, if you brought the other thing, 241 00:13:20,960 --> 00:13:23,280 Speaker 1: you know, in New York City, you probably have the 242 00:13:23,280 --> 00:13:27,400 Speaker 1: two hundred greatest CEOs in America. They're all happy to help. 243 00:13:27,440 --> 00:13:29,079 Speaker 1: You know, if you call a guy like Jamie Diamond, 244 00:13:29,080 --> 00:13:30,640 Speaker 1: if you're in New York City, we need your help. 245 00:13:30,679 --> 00:13:33,120 Speaker 1: Could you come down to city. Guys like that would 246 00:13:33,120 --> 00:13:36,920 Speaker 1: come right down and help you. Be happy to help you. 247 00:13:36,920 --> 00:13:38,480 Speaker 1: If he said, you know, our budget's got all kinds 248 00:13:38,480 --> 00:13:40,280 Speaker 1: of waist and fraud and bloat. Could you take a 249 00:13:40,320 --> 00:13:42,839 Speaker 1: look at it. One of these CEOs would send in 250 00:13:42,920 --> 00:13:45,400 Speaker 1: a team the next day of twenty top guys in 251 00:13:45,440 --> 00:13:48,080 Speaker 1: the world to go through your budget and get rid 252 00:13:48,120 --> 00:13:50,400 Speaker 1: of the waist the fraud. It'd be easy to do, 253 00:13:50,559 --> 00:13:55,080 Speaker 1: but they're politicians. They're they're not going to they don't 254 00:13:55,080 --> 00:13:57,440 Speaker 1: want any help. They kind of like that wasist and 255 00:13:57,520 --> 00:14:01,000 Speaker 1: fraud and bloat. You know, guys like Schumer and Mom Donnie, 256 00:14:01,040 --> 00:14:03,439 Speaker 1: all these politicians, and they are Republicans too, they can be 257 00:14:03,600 --> 00:14:06,760 Speaker 1: just as bad. These The waste, fraud and bloat comes 258 00:14:06,760 --> 00:14:10,400 Speaker 1: out comes from giving out contracts everywhere and kind of 259 00:14:10,440 --> 00:14:12,719 Speaker 1: winking and nodding. You know you're gonna overcharge us by 260 00:14:12,880 --> 00:14:16,200 Speaker 1: three thousand percent. Go ahead, when you're fixing the road 261 00:14:16,280 --> 00:14:19,360 Speaker 1: or whatever, you want to take five years longer. Go ahead, 262 00:14:19,440 --> 00:14:22,000 Speaker 1: you want to put three times as many peopil as 263 00:14:22,000 --> 00:14:24,720 Speaker 1: you need to go ahead. A lot of winking and nodding. 264 00:14:25,120 --> 00:14:28,560 Speaker 1: Contracts are handed out, and in exchange the politicians get 265 00:14:29,080 --> 00:14:32,960 Speaker 1: massive donations when they want to run for something or 266 00:14:33,000 --> 00:14:36,120 Speaker 1: when they got those political packs. So that's always the deal. 267 00:14:36,880 --> 00:14:39,240 Speaker 1: We'll get to Pam Bondi coming up. That was pretty good, 268 00:14:40,920 --> 00:14:45,160 Speaker 1: and lots more just ahead, and uh oh, Jimmy Fayla 269 00:14:45,200 --> 00:14:47,600 Speaker 1: will be with us a little later. We'll get to 270 00:14:47,600 --> 00:14:50,760 Speaker 1: the economy just ahead. We'll take some calls next. Eight 271 00:14:50,840 --> 00:14:54,680 Speaker 1: hundred three two one zero seven ten is the number. 272 00:14:54,760 --> 00:14:58,040 Speaker 1: Eight hundred three two one zero seven ten