1 00:00:00,120 --> 00:00:03,640 Speaker 1: It is freezing outside and a thousand degrees here in 2 00:00:03,680 --> 00:00:06,439 Speaker 1: the studio. I'm sitting here in a pool of sweat. 3 00:00:06,960 --> 00:00:09,760 Speaker 1: Why why can they never get a right Look. 4 00:00:09,560 --> 00:00:12,000 Speaker 2: I've worked in media for thirty years. I've worked in 5 00:00:12,039 --> 00:00:14,800 Speaker 2: a lot of radio and TV studios in my career. Yeah, 6 00:00:14,840 --> 00:00:18,040 Speaker 2: every single one of them is an HVAC disaster. It's 7 00:00:18,079 --> 00:00:20,880 Speaker 2: either thirty two degrees in the studio or one hundred 8 00:00:20,960 --> 00:00:22,360 Speaker 2: and thirty two degrees in the story. 9 00:00:22,920 --> 00:00:24,680 Speaker 1: Well, all I need to do is step outside to 10 00:00:24,720 --> 00:00:27,160 Speaker 1: cool off again and then run up the stairs into 11 00:00:27,200 --> 00:00:30,520 Speaker 1: the sauna and warm up. It'll be like that all 12 00:00:30,680 --> 00:00:35,839 Speaker 1: morning long. Okay. So snow began Saturday continued overnight into Sunday. 13 00:00:36,280 --> 00:00:39,360 Speaker 1: More than ten inches of snow fell in Indianapolis and 14 00:00:39,400 --> 00:00:42,840 Speaker 1: the surrounding areas. We do have some totals. Indianapolis International 15 00:00:42,880 --> 00:00:47,320 Speaker 1: Airport they're reporting eleven point one inches, Carmel eight point 16 00:00:47,479 --> 00:00:52,680 Speaker 1: five inches, and Speedway nine point eight inches. And it 17 00:00:52,720 --> 00:00:54,000 Speaker 1: was lovely from the window. 18 00:00:54,680 --> 00:00:56,480 Speaker 3: Yeah, we did not do much this weekend. 19 00:00:56,600 --> 00:01:00,360 Speaker 2: Look, we did what a good citizen would do. Our 20 00:01:00,640 --> 00:01:05,160 Speaker 2: city leaders and the and the law enforcement said, hey, is. 21 00:01:05,080 --> 00:01:07,800 Speaker 1: That where we're calling them? Ahead with your thoughts. 22 00:01:07,600 --> 00:01:10,640 Speaker 2: You know what, when somebody tells me stay home, you 23 00:01:10,640 --> 00:01:12,800 Speaker 2: don't have to go outside, just stay home, I listen 24 00:01:13,120 --> 00:01:15,120 Speaker 2: and so we were good citizens. They said, if you 25 00:01:15,120 --> 00:01:16,440 Speaker 2: don't have to go out and drive in this, you 26 00:01:16,480 --> 00:01:18,959 Speaker 2: shouldn't drive in it. And I was like, okay, fine, 27 00:01:19,000 --> 00:01:20,760 Speaker 2: I get to stay at home and watch TV all 28 00:01:20,840 --> 00:01:21,920 Speaker 2: weekend and eat snacks. 29 00:01:22,200 --> 00:01:23,080 Speaker 3: That sounds amazing. 30 00:01:23,240 --> 00:01:26,240 Speaker 1: Yeah, I think what. We got home Friday around two 31 00:01:26,520 --> 00:01:29,640 Speaker 1: and didn't leave the house until this morning on our 32 00:01:29,680 --> 00:01:30,720 Speaker 1: way and do work. 33 00:01:31,080 --> 00:01:32,600 Speaker 3: So I did do some stocking up. 34 00:01:32,640 --> 00:01:35,120 Speaker 2: So I ran out to ran out to Meyer on Friday, 35 00:01:35,280 --> 00:01:39,520 Speaker 2: and props to Meyer. The shelves were very well stocked. Yeah, 36 00:01:39,560 --> 00:01:41,399 Speaker 2: they were ready, very well stocked. I don't know what 37 00:01:41,440 --> 00:01:43,759 Speaker 2: it looked like Friday night and Saturday. The Friday afternoon 38 00:01:43,760 --> 00:01:45,480 Speaker 2: it was good. So of course we're going to be 39 00:01:45,520 --> 00:01:46,920 Speaker 2: trapped in house all weekend long. 40 00:01:47,080 --> 00:01:49,600 Speaker 3: What are we going to do? Buy nothing but snacks? 41 00:01:49,760 --> 00:01:52,000 Speaker 1: Yeah, it wasn't a bread and milk run. 42 00:01:52,360 --> 00:01:53,440 Speaker 3: What did you end up getting? 43 00:01:53,520 --> 00:01:57,520 Speaker 2: It was chips and candy and milk, soda and milk 44 00:01:57,920 --> 00:01:58,320 Speaker 2: and milk. 45 00:01:58,400 --> 00:02:00,520 Speaker 3: Day was every bit of garb food. 46 00:02:00,520 --> 00:02:02,480 Speaker 2: Because I knew that I was going to be sitting 47 00:02:02,480 --> 00:02:05,320 Speaker 2: around all weekend watching shows and movies and sports, and 48 00:02:05,360 --> 00:02:06,880 Speaker 2: I was going to have all the snacks in the. 49 00:02:06,800 --> 00:02:09,240 Speaker 1: World because when snow m again is hitting, what do 50 00:02:09,320 --> 00:02:10,359 Speaker 1: you need milk? 51 00:02:10,400 --> 00:02:13,880 Speaker 2: Does I need artificial cheese flavoring and milk duds? And 52 00:02:13,919 --> 00:02:17,000 Speaker 2: so bought all that stuff on Friday. Wonderful, great huh, 53 00:02:17,080 --> 00:02:20,000 Speaker 2: and snow didn't stuck. We didn't see the first snowflake 54 00:02:20,080 --> 00:02:24,720 Speaker 2: fall until Saturday afternoon. And in that twelve hour, twenty 55 00:02:24,720 --> 00:02:27,320 Speaker 2: four hour tip here from Friday afternoon to Saturday afternoon, 56 00:02:27,400 --> 00:02:29,720 Speaker 2: I think we had already demolished and eaten all the 57 00:02:29,800 --> 00:02:32,000 Speaker 2: snacks before any snow had come down. 58 00:02:32,120 --> 00:02:33,280 Speaker 1: I have a confession to make. 59 00:02:33,440 --> 00:02:36,000 Speaker 3: Yeah, okay, I. 60 00:02:36,000 --> 00:02:37,760 Speaker 1: Did even shower yesterday. 61 00:02:38,480 --> 00:02:40,720 Speaker 2: Now, for you, that's a big deal for a normal 62 00:02:40,840 --> 00:02:43,520 Speaker 2: human being to have a weekend day go by. And 63 00:02:43,520 --> 00:02:46,000 Speaker 2: I got an in shower yesterday, not that big of surprising, 64 00:02:46,120 --> 00:02:48,520 Speaker 2: But for you, that happens like once every ten years, 65 00:02:48,520 --> 00:02:50,480 Speaker 2: where you go for a whole day and don't shower. 66 00:02:50,600 --> 00:02:53,680 Speaker 1: Yeah. So we had a lot of flight cancelations, some 67 00:02:53,800 --> 00:02:57,400 Speaker 1: slick roads, extreme cold. Now let's talk about the drive 68 00:02:57,480 --> 00:02:59,760 Speaker 1: in this morning. I got stuck. 69 00:03:00,240 --> 00:03:02,320 Speaker 3: You got stuck, so and luckily you have a four 70 00:03:02,320 --> 00:03:04,640 Speaker 3: wheel drive vehicle, so it wasn't in. 71 00:03:04,520 --> 00:03:06,640 Speaker 1: Four wheel drive. We slammed it in a four wheel 72 00:03:06,720 --> 00:03:09,280 Speaker 1: drive and you got out of it, and that helped 73 00:03:09,360 --> 00:03:11,200 Speaker 1: us get out of that snow bank. But it was 74 00:03:11,280 --> 00:03:15,440 Speaker 1: a side street in Indianapolis which was not well paved. 75 00:03:15,639 --> 00:03:17,839 Speaker 1: In fact, I don't think it was paved at all. 76 00:03:18,280 --> 00:03:19,919 Speaker 3: A plowed yeah. Yeah. 77 00:03:20,160 --> 00:03:22,679 Speaker 2: If you've done any driving in Marion County in the 78 00:03:22,760 --> 00:03:26,839 Speaker 2: last twelve hours, yeah, godspeed, because there are there's still 79 00:03:26,880 --> 00:03:28,560 Speaker 2: a lot of snow, especially the side roads. 80 00:03:28,560 --> 00:03:30,440 Speaker 3: The main roads at least one. 81 00:03:30,600 --> 00:03:32,680 Speaker 2: Pass has gone by by the plows, but a lot 82 00:03:32,680 --> 00:03:35,000 Speaker 2: of these side streets looked like they haven't been touched 83 00:03:35,040 --> 00:03:37,640 Speaker 2: at all. And if you're driving around in your little 84 00:03:37,680 --> 00:03:41,080 Speaker 2: Chrysler seabring, that's not a good idea. You're going to 85 00:03:41,160 --> 00:03:44,640 Speaker 2: need some sort of larger SUV truck jeep with four 86 00:03:44,680 --> 00:03:45,280 Speaker 2: wheel drive. 87 00:03:45,680 --> 00:03:45,880 Speaker 3: Yeah. 88 00:03:46,320 --> 00:03:49,040 Speaker 2: We were just at an intersection, yeah, and an intersection 89 00:03:49,120 --> 00:03:52,080 Speaker 2: at a side street and the light turned green and 90 00:03:52,120 --> 00:03:54,080 Speaker 2: you had to hit the gas and the tires did nothing. 91 00:03:54,120 --> 00:03:56,440 Speaker 1: It's been yeah. So we were trying to get from 92 00:03:56,440 --> 00:03:59,520 Speaker 1: a side street onto tenth Street, which was a little 93 00:03:59,520 --> 00:04:04,200 Speaker 1: bit better, more passable. Of course, even if it's two lanes, 94 00:04:04,480 --> 00:04:06,680 Speaker 1: it's not one lane. So keep that in mind if 95 00:04:06,720 --> 00:04:10,080 Speaker 1: you're trying to venture out today, that you're best just 96 00:04:10,120 --> 00:04:11,840 Speaker 1: to follow the car in front of you. Now, at 97 00:04:11,880 --> 00:04:15,400 Speaker 1: one point there was another car on the other side 98 00:04:15,400 --> 00:04:18,200 Speaker 1: of the road and we were both headed down the middle. 99 00:04:18,560 --> 00:04:21,280 Speaker 1: It was like a serious game of chicken because one 100 00:04:21,320 --> 00:04:23,159 Speaker 1: of us was gonna have to get over as we 101 00:04:23,160 --> 00:04:25,520 Speaker 1: were both driving down the middle of the road. 102 00:04:25,600 --> 00:04:26,279 Speaker 3: Boiler alert. 103 00:04:26,440 --> 00:04:30,920 Speaker 2: Yeah, you did not get over, which matches your personality 104 00:04:31,080 --> 00:04:33,280 Speaker 2: very well. And you were talking to me, You're like, hey, 105 00:04:33,680 --> 00:04:36,760 Speaker 2: I'm going you better get over, buddy, because I'm not 106 00:04:36,920 --> 00:04:37,520 Speaker 2: getting over. 107 00:04:37,880 --> 00:04:41,040 Speaker 1: One of us has to give way. Now, another thing 108 00:04:41,080 --> 00:04:44,680 Speaker 1: that happened on our way into the radio station this 109 00:04:44,760 --> 00:04:49,159 Speaker 1: morning is a huge tree branch fell right in front 110 00:04:49,200 --> 00:04:49,520 Speaker 1: of us. 111 00:04:49,839 --> 00:04:50,080 Speaker 3: Yeah. 112 00:04:50,160 --> 00:04:52,120 Speaker 2: So, I mean, we're joking about it and we got 113 00:04:52,160 --> 00:04:55,000 Speaker 2: in here safe, but there is a lot of danger 114 00:04:55,040 --> 00:04:57,360 Speaker 2: associated with that. And yeah, it was a fairly sizable 115 00:04:57,400 --> 00:05:00,640 Speaker 2: tree branch that just happened to fall as we were 116 00:05:00,720 --> 00:05:03,719 Speaker 2: driving right before it. And fortunately that didn't happen a 117 00:05:03,760 --> 00:05:06,120 Speaker 2: second later, or else you probably would have a good 118 00:05:06,160 --> 00:05:07,400 Speaker 2: dent on the hood of your car. 119 00:05:07,480 --> 00:05:09,080 Speaker 1: Right now, we were joking that I was going to 120 00:05:09,160 --> 00:05:10,920 Speaker 1: have to call the bosses and tell them that I 121 00:05:11,000 --> 00:05:13,440 Speaker 1: was stuck and couldn't make it in. Really, where are 122 00:05:13,480 --> 00:05:16,640 Speaker 1: you stuck in the parking lots? To the street? 123 00:05:16,880 --> 00:05:19,359 Speaker 3: Sorry, stuck in the parking lot. I can't do this, 124 00:05:19,640 --> 00:05:21,680 Speaker 3: can't make it in, make it in today. Now. 125 00:05:21,839 --> 00:05:25,600 Speaker 1: The nice thing about nobody being here except for the 126 00:05:26,480 --> 00:05:27,360 Speaker 1: essential employees. 127 00:05:27,520 --> 00:05:30,520 Speaker 2: Hey, congratulations, I was going to congratulate you. 128 00:05:30,520 --> 00:05:32,560 Speaker 1: You're now deemed an essential employee. 129 00:05:32,560 --> 00:05:33,000 Speaker 3: I don't know. 130 00:05:33,080 --> 00:05:35,480 Speaker 2: I don't even work here, so how can I be 131 00:05:35,520 --> 00:05:36,400 Speaker 2: an essential employee? 132 00:05:37,080 --> 00:05:40,640 Speaker 1: Day? There's a whole lot of parking spots available, which 133 00:05:40,680 --> 00:05:41,920 Speaker 1: is nice downtown. 134 00:05:42,080 --> 00:05:46,000 Speaker 2: And the good news is too you know, police have 135 00:05:46,120 --> 00:05:47,960 Speaker 2: been saying, hey, don't drive if you don't have to. 136 00:05:48,120 --> 00:05:49,560 Speaker 3: There were not a lot of cars on the road 137 00:05:49,560 --> 00:05:49,920 Speaker 3: this morning. 138 00:05:50,000 --> 00:05:51,520 Speaker 1: Yeah, a lot of people are a lot of people 139 00:05:51,560 --> 00:05:52,360 Speaker 1: seem to be obeyed. 140 00:05:52,400 --> 00:05:54,680 Speaker 2: A lot of businesses either shut down completely or they're 141 00:05:54,680 --> 00:05:57,520 Speaker 2: allowing their employees to work from home, and so there 142 00:05:57,600 --> 00:05:59,600 Speaker 2: was not a lot of traffic. Still took a long 143 00:05:59,640 --> 00:06:01,040 Speaker 2: time to get in because you just got to drive 144 00:06:01,360 --> 00:06:03,480 Speaker 2: slow because there's snow, walls, snow and ice all over 145 00:06:03,520 --> 00:06:03,800 Speaker 2: the road. 146 00:06:03,880 --> 00:06:07,719 Speaker 1: So Central Indiana, including Indianapolis still under that travel warning 147 00:06:07,760 --> 00:06:11,440 Speaker 1: and travel is limited to essential personnel only. And yeah, 148 00:06:11,440 --> 00:06:12,880 Speaker 1: I would say, if you don't have to go out, 149 00:06:13,320 --> 00:06:15,920 Speaker 1: just do what we did and not leave the house. 150 00:06:16,279 --> 00:06:19,120 Speaker 1: There's nothing good going on out there. You're fine inside. 151 00:06:19,320 --> 00:06:23,880 Speaker 2: I'm going to uh you certain you took don't leave 152 00:06:23,920 --> 00:06:25,960 Speaker 2: the house to another level. 153 00:06:26,040 --> 00:06:28,279 Speaker 3: So, yes, you did not leave the house. This right again. 154 00:06:28,839 --> 00:06:31,080 Speaker 1: But let's I was obeying, you know, all the warnings. 155 00:06:31,160 --> 00:06:33,159 Speaker 2: Let's drill down on that a little bit more. Let's 156 00:06:33,160 --> 00:06:36,720 Speaker 2: put let's put a finer point on that. You barely 157 00:06:36,880 --> 00:06:39,360 Speaker 2: left the bed all weekend. 158 00:06:41,720 --> 00:06:45,680 Speaker 3: It was I I have been pictick with those milk 159 00:06:45,760 --> 00:06:49,120 Speaker 3: dead with the snacks. It was Uh, it was a 160 00:06:49,160 --> 00:06:49,800 Speaker 3: sight to see. 161 00:06:49,920 --> 00:06:52,760 Speaker 2: I can't believe you're calling me out like, hey, I 162 00:06:52,880 --> 00:06:55,000 Speaker 2: was there with you, although I took. 163 00:06:54,920 --> 00:06:57,760 Speaker 1: Full advantage of it. I left the bed. 164 00:06:57,600 --> 00:07:00,000 Speaker 3: At one point. You left you. 165 00:07:00,200 --> 00:07:05,040 Speaker 2: I think you came downstairs once all weekend long. And 166 00:07:05,240 --> 00:07:08,080 Speaker 2: what did you do when you came downstairs and went 167 00:07:08,120 --> 00:07:08,800 Speaker 2: into the kitchen. 168 00:07:08,880 --> 00:07:09,920 Speaker 1: I made dessert. 169 00:07:10,120 --> 00:07:11,240 Speaker 3: You made dessert. 170 00:07:11,600 --> 00:07:15,640 Speaker 2: That's the only reason why you left bed and came 171 00:07:15,720 --> 00:07:18,920 Speaker 2: downstairs into the kitchen was to make Not granted you 172 00:07:19,000 --> 00:07:19,960 Speaker 2: crushed it. 173 00:07:19,800 --> 00:07:22,160 Speaker 3: It was. It was delicious. It was a. 174 00:07:22,200 --> 00:07:26,239 Speaker 2: Cherry crisp that was fabulous, and that didn't last twenty 175 00:07:26,280 --> 00:07:28,480 Speaker 2: four hours in our house with just the two of us. 176 00:07:29,320 --> 00:07:33,440 Speaker 2: But yeah, you left bed to one time all weekend, 177 00:07:33,720 --> 00:07:35,400 Speaker 2: and that was to make dessert. 178 00:07:35,640 --> 00:07:36,000 Speaker 3: Thank you. 179 00:07:36,960 --> 00:07:41,680 Speaker 1: I took full advantage of winter Storm Fern, which, by 180 00:07:41,760 --> 00:07:44,000 Speaker 1: the way, you know, people were like, really, did they 181 00:07:44,080 --> 00:07:46,360 Speaker 1: name it a winter storm? They did, yes, and normally 182 00:07:46,360 --> 00:07:49,960 Speaker 1: were used to being tropical storms or hurricanes being named, 183 00:07:49,960 --> 00:07:53,440 Speaker 1: and this time winter Storm Fern was named. You know 184 00:07:53,480 --> 00:07:54,560 Speaker 1: why they named it Fern. 185 00:07:55,280 --> 00:07:56,200 Speaker 3: I have no idea why. 186 00:07:56,520 --> 00:07:58,800 Speaker 1: It's just short for Fernando Boo. 187 00:07:58,920 --> 00:07:59,480 Speaker 3: That's right. 188 00:07:59,640 --> 00:08:01,720 Speaker 2: Hey, we had a storm down in Miami with the 189 00:08:01,800 --> 00:08:04,960 Speaker 2: National Championship and a storm around the rest of the country, 190 00:08:05,080 --> 00:08:06,440 Speaker 2: and it was her. 191 00:08:06,680 --> 00:08:12,760 Speaker 3: It was a winter storm Fern. Nando's right. Still with that. 192 00:08:13,120 --> 00:08:15,760 Speaker 1: Well, by the way, there are still many airports that 193 00:08:15,800 --> 00:08:19,960 Speaker 1: are closed and flights being canceled across the country, and 194 00:08:20,920 --> 00:08:22,920 Speaker 1: you had to know that was coming. My sister in law, 195 00:08:22,960 --> 00:08:25,800 Speaker 1: who's in Washington, d C. She was texting me last 196 00:08:25,840 --> 00:08:28,000 Speaker 1: night asking how you doing, and I said, well, you know, 197 00:08:28,400 --> 00:08:31,360 Speaker 1: we lived in northern Indiana for twenty five years. 198 00:08:31,600 --> 00:08:32,200 Speaker 3: We're used to. 199 00:08:32,240 --> 00:08:35,760 Speaker 1: Lake effect snow. So really, you know, we got the 200 00:08:35,760 --> 00:08:37,679 Speaker 1: four wheel drive vehicle. We knew we were going to 201 00:08:37,720 --> 00:08:39,960 Speaker 1: be okay, make it in. We didn't lose power. And 202 00:08:40,000 --> 00:08:43,080 Speaker 1: I asked her how she was doing, and she said, well, 203 00:08:43,320 --> 00:08:46,160 Speaker 1: everything shut down in the nation's capital. And I said, yeah, 204 00:08:46,400 --> 00:08:49,880 Speaker 1: I heard Reagan International has closed and she said, yeah, 205 00:08:50,040 --> 00:08:52,520 Speaker 1: I'm not going anywhere. I don't know if she left bed. 206 00:08:53,240 --> 00:08:56,280 Speaker 2: Did she take it to the Casey Daniels level of 207 00:08:56,400 --> 00:08:57,560 Speaker 2: winter storm fern? 208 00:08:57,840 --> 00:08:59,880 Speaker 3: Oh? Sure, Hey, they're saying it's dangerous. 209 00:09:00,000 --> 00:09:01,760 Speaker 2: Better not leave my bed. You know what was great 210 00:09:01,760 --> 00:09:05,000 Speaker 2: about my favorite thing about the weekend? What's my tire favorite? 211 00:09:05,040 --> 00:09:06,959 Speaker 2: And you just mentioned we lived in northern Indiana for many, 212 00:09:07,000 --> 00:09:11,480 Speaker 2: many years. Did a lot lived in a single family house. Yeah, 213 00:09:11,760 --> 00:09:14,440 Speaker 2: the yard and a driveway, typical suburban house. 214 00:09:14,559 --> 00:09:14,760 Speaker 1: Yeah. 215 00:09:15,040 --> 00:09:18,280 Speaker 2: And now we live in a townhouse. And what was 216 00:09:18,440 --> 00:09:21,800 Speaker 2: wonderful is that I did not shovel, I did not 217 00:09:22,040 --> 00:09:27,599 Speaker 2: snow blow. I have no exterior maintenance responsibilities in our towns. 218 00:09:27,640 --> 00:09:30,559 Speaker 3: It was wonderful. Yeah, to see that. 219 00:09:30,679 --> 00:09:34,120 Speaker 1: So in the past forty eight hours, troopers in Indianapolis. 220 00:09:34,240 --> 00:09:37,480 Speaker 1: Now this number may have elevated since the last report, 221 00:09:37,559 --> 00:09:41,800 Speaker 1: but ninety six crashes, sixty seven slide offs, and two 222 00:09:41,880 --> 00:09:45,960 Speaker 1: hundred and forty nine motor assists. That is, vehicles that 223 00:09:46,040 --> 00:09:49,560 Speaker 1: have been stuck in the snow. So be careful if 224 00:09:49,600 --> 00:09:52,280 Speaker 1: you are heading out this morning. The roads aren't completely clear. 225 00:09:52,360 --> 00:09:55,040 Speaker 1: That is your warning. This is the Kendall and Casey Show. 226 00:09:55,080 --> 00:10:05,360 Speaker 1: It's ninety three WYBC. The two big stories over the weekend, 227 00:10:05,520 --> 00:10:09,240 Speaker 1: Ice and ice, and we'll get to the other ice 228 00:10:09,360 --> 00:10:12,079 Speaker 1: coming up in just a bit. But we've got this 229 00:10:12,160 --> 00:10:15,959 Speaker 1: pressing story. All right, all right, all right. Matthew McConaughey 230 00:10:16,440 --> 00:10:19,520 Speaker 1: trademarked his famous catchphrase, all right, all right, all right, 231 00:10:20,559 --> 00:10:25,559 Speaker 1: it's meant to protect against AI misuse and impersonation. This 232 00:10:25,600 --> 00:10:26,400 Speaker 1: is where we've come to. 233 00:10:27,200 --> 00:10:29,319 Speaker 2: So if you're not aware of this was from a 234 00:10:29,840 --> 00:10:32,000 Speaker 2: kind of a mid nineties cult movie. I think it 235 00:10:32,000 --> 00:10:35,679 Speaker 2: was the first movie Matthew McConaughey was ever in. I 236 00:10:35,679 --> 00:10:37,360 Speaker 2: think that was the very first for a lot of people. 237 00:10:37,400 --> 00:10:39,760 Speaker 2: It's called Days Didn't Confused. Yeah, came out about thirty 238 00:10:39,840 --> 00:10:40,280 Speaker 2: years ago. 239 00:10:41,840 --> 00:10:43,600 Speaker 1: Nineteen ninety three is when that movie came out. 240 00:10:44,000 --> 00:10:45,360 Speaker 3: Chase thirty three years ago now. 241 00:10:45,559 --> 00:10:49,920 Speaker 2: And so he plays this guy that just graduated high school, 242 00:10:50,000 --> 00:10:52,000 Speaker 2: but still hangs out in parties with all the high 243 00:10:52,000 --> 00:10:55,280 Speaker 2: school they moved on yet, and he's famously trying to, 244 00:10:55,360 --> 00:10:56,680 Speaker 2: you know, pick up some chicks. 245 00:10:56,720 --> 00:10:58,840 Speaker 3: And that was there was a line in the movie 246 00:10:58,880 --> 00:10:59,439 Speaker 3: where he just. 247 00:10:59,360 --> 00:11:02,880 Speaker 1: Said, into a parking lot, it's actually a fast food 248 00:11:02,960 --> 00:11:05,240 Speaker 1: joint where they you know, you drive up and somebody 249 00:11:05,280 --> 00:11:07,560 Speaker 1: brings you the food to your car windows like a sonic. 250 00:11:07,800 --> 00:11:09,920 Speaker 3: Not a drive through, but a drive in, right. 251 00:11:10,440 --> 00:11:14,360 Speaker 1: Right, And he says the famous scene here it is. 252 00:11:16,760 --> 00:11:19,920 Speaker 4: Hey, I've been man, Hey, man, he's car. 253 00:11:21,400 --> 00:11:21,679 Speaker 1: You know what. 254 00:11:22,600 --> 00:11:23,199 Speaker 4: How's it going? 255 00:11:23,280 --> 00:11:23,839 Speaker 3: Many? 256 00:11:25,320 --> 00:11:25,800 Speaker 5: Pretty good? 257 00:11:25,800 --> 00:11:28,840 Speaker 1: How's it going with you? Say? 258 00:11:28,920 --> 00:11:34,520 Speaker 3: Man, you got a joint? Uh no, not on me, man. 259 00:11:37,480 --> 00:11:48,560 Speaker 3: It'd be a lot cooler if he did. All right, 260 00:11:48,760 --> 00:11:50,040 Speaker 3: all right, all right. 261 00:11:50,080 --> 00:11:52,440 Speaker 1: Yeah, there they go. They're cruising around in their car. 262 00:11:52,840 --> 00:11:58,320 Speaker 2: How funny that that throwaway line, essentially from a movie 263 00:11:58,320 --> 00:12:01,400 Speaker 2: that wasn't supposed to turn into a classic which did, 264 00:12:01,840 --> 00:12:04,800 Speaker 2: that has now become famous thirty years later, to the 265 00:12:04,880 --> 00:12:08,000 Speaker 2: point that Matthew McConaughey has to trademarkt I'm actually a 266 00:12:08,040 --> 00:12:10,440 Speaker 2: little surprised that it took him thirty years to trademarket 267 00:12:10,559 --> 00:12:12,280 Speaker 2: and he didn't do it before now, But it sounds 268 00:12:12,360 --> 00:12:15,400 Speaker 2: like the possibility of people stealing it and using it 269 00:12:15,520 --> 00:12:17,640 Speaker 2: via AI is what the driver was for him to 270 00:12:17,679 --> 00:12:18,000 Speaker 2: do this. 271 00:12:18,120 --> 00:12:21,920 Speaker 1: It does include a specific pitch and rhythm details. There 272 00:12:21,960 --> 00:12:23,920 Speaker 1: have been seven additional trademarks. 273 00:12:23,960 --> 00:12:27,120 Speaker 3: Wait, wait, a specific pitch and rhythm. 274 00:12:27,280 --> 00:12:31,120 Speaker 2: Well, I think right exactly if I exact, if I 275 00:12:31,240 --> 00:12:34,200 Speaker 2: just sat here and said, all right, all right, all right, yeah, 276 00:12:34,240 --> 00:12:36,760 Speaker 2: that's not a copyright infringement, said, I'm not saying it 277 00:12:36,800 --> 00:12:38,280 Speaker 2: the way Matthew McConaughey would say. 278 00:12:38,360 --> 00:12:41,240 Speaker 1: Yeah. He's also got seven different additional trademarks that are 279 00:12:41,240 --> 00:12:43,599 Speaker 1: tied to his likeness, including a seven second video of 280 00:12:43,679 --> 00:12:46,360 Speaker 1: him standing on a porch, a three second video of 281 00:12:46,400 --> 00:12:48,880 Speaker 1: him sitting in front of a Christmas tree. Also another 282 00:12:48,920 --> 00:12:51,400 Speaker 1: audio clip where he says, just keep living. 283 00:12:52,440 --> 00:12:54,800 Speaker 3: Do you remember that one that was also from Dazed 284 00:12:54,840 --> 00:12:56,280 Speaker 3: and Confused? How much? 285 00:12:56,320 --> 00:12:59,120 Speaker 2: How many catchphrases came out of that movie from thirty 286 00:12:59,160 --> 00:12:59,640 Speaker 2: years ago. 287 00:13:00,040 --> 00:13:03,640 Speaker 1: Apparently it aims to stop any AI generated videos or 288 00:13:03,679 --> 00:13:08,920 Speaker 1: voices or misuse of his likeness, even if not selling products. 289 00:13:09,320 --> 00:13:13,360 Speaker 1: So this is just for everything you can't use all right, 290 00:13:13,400 --> 00:13:16,200 Speaker 1: all right, all right, in any AI generated content. 291 00:13:16,280 --> 00:13:19,520 Speaker 2: Now, good for him, he's protecting the content that he made. 292 00:13:19,720 --> 00:13:21,840 Speaker 2: I'm surprised it took thirty years for him to do that, 293 00:13:21,880 --> 00:13:24,880 Speaker 2: but that is a classic line from a movie that 294 00:13:25,040 --> 00:13:27,920 Speaker 2: is repeated and I mean has become his catchphrase still 295 00:13:27,920 --> 00:13:28,720 Speaker 2: thirty years later. 296 00:13:28,800 --> 00:13:30,679 Speaker 1: He used it. Do you remember he used it in 297 00:13:30,760 --> 00:13:35,160 Speaker 1: a twenty fourteen Oscar acceptance speech. He walked up and 298 00:13:35,200 --> 00:13:37,320 Speaker 1: he said the line. Crowd went crazy. 299 00:13:37,400 --> 00:13:37,679 Speaker 3: He did. 300 00:13:37,679 --> 00:13:40,760 Speaker 2: And in fact, he's a huge University of Texas football fan, 301 00:13:40,800 --> 00:13:43,760 Speaker 2: Texas Longhorns, and frequently for games he's on the sidelines 302 00:13:43,800 --> 00:13:44,560 Speaker 2: and I've seen him. 303 00:13:44,800 --> 00:13:46,120 Speaker 3: I've seen him being interviewed on. 304 00:13:46,120 --> 00:13:49,120 Speaker 2: The sidelines of a Texas football game too, where he's 305 00:13:49,240 --> 00:13:50,160 Speaker 2: let it rip as well. 306 00:13:50,240 --> 00:13:54,240 Speaker 1: So Paris Hilton has trademarked the phrase that's hot, and 307 00:13:54,320 --> 00:13:57,760 Speaker 1: Taylor Swift has also filed trademarks for several of her 308 00:13:58,120 --> 00:14:00,800 Speaker 1: song lyrics. But this is where we are right now, 309 00:14:00,840 --> 00:14:03,240 Speaker 1: and athletes, I have to imagine, are going to start 310 00:14:03,280 --> 00:14:09,800 Speaker 1: trademarking anything for nil purposes or at least have an 311 00:14:09,840 --> 00:14:13,160 Speaker 1: AI clause in their contracts for nil. 312 00:14:13,320 --> 00:14:16,040 Speaker 2: Yeah, and so obviously, you know, like you said, Paris 313 00:14:16,120 --> 00:14:18,880 Speaker 2: Hilton and Taylor Swift trademarking some of their phrases. 314 00:14:18,960 --> 00:14:21,200 Speaker 3: It wasn't as big of a deal to do this. 315 00:14:21,320 --> 00:14:24,720 Speaker 2: It wasn't necessary for them to do this before AI 316 00:14:24,840 --> 00:14:25,440 Speaker 2: came about. 317 00:14:25,760 --> 00:14:27,240 Speaker 3: So you can assume. 318 00:14:27,000 --> 00:14:29,440 Speaker 2: Going forward, we're going to hear a lot more about 319 00:14:29,440 --> 00:14:33,560 Speaker 2: this individual celebrities, companies, entities that are trademarking things that 320 00:14:33,560 --> 00:14:36,680 Speaker 2: they're specifically known for to try and give them some 321 00:14:36,720 --> 00:14:41,080 Speaker 2: sort of protection from it being compromised via AI. What'll 322 00:14:41,120 --> 00:14:44,600 Speaker 2: be fascinating is there hasn't been a challenge to any 323 00:14:44,640 --> 00:14:47,600 Speaker 2: of these copyrights as it relates to AI yet. It'll 324 00:14:47,600 --> 00:14:49,440 Speaker 2: be interesting to see if these hold up in court 325 00:14:49,760 --> 00:14:51,480 Speaker 2: the way they think they hope it is. 326 00:14:52,320 --> 00:14:54,360 Speaker 1: So a bill to allow the Who's Your Lottery to 327 00:14:54,400 --> 00:14:58,440 Speaker 1: sell tickets online and offer instant games that has been dropped. 328 00:14:58,960 --> 00:15:01,320 Speaker 1: That proposal is not going to to move forward this 329 00:15:01,480 --> 00:15:04,600 Speaker 1: legislative session. By the way, they're not working at the 330 00:15:04,640 --> 00:15:05,520 Speaker 1: state House today. 331 00:15:06,000 --> 00:15:07,560 Speaker 3: Oh, the State House is shut down today. 332 00:15:07,880 --> 00:15:11,040 Speaker 2: Your government tax dollars not being spent to keep the 333 00:15:11,080 --> 00:15:13,200 Speaker 2: government in operation at the state House today. 334 00:15:13,320 --> 00:15:15,760 Speaker 1: So there was a bill that passed a House committee 335 00:15:15,760 --> 00:15:18,280 Speaker 1: on January eighth, but it was never brought to the 336 00:15:18,360 --> 00:15:21,720 Speaker 1: House for a full vote, and it was removed from 337 00:15:21,720 --> 00:15:25,240 Speaker 1: the calendar, and they didn't have enough support to move 338 00:15:25,280 --> 00:15:29,720 Speaker 1: it forward. Online lottery sales have added between there was 339 00:15:29,800 --> 00:15:33,040 Speaker 1: potential to add between three hundred and fourteen six hundred 340 00:15:33,040 --> 00:15:35,720 Speaker 1: and twenty nine million dollars in revenue over three years, 341 00:15:36,160 --> 00:15:39,200 Speaker 1: but they're saying, no, we're not going to do that. 342 00:15:39,560 --> 00:15:44,120 Speaker 1: They remain hesitant about expanding online gambling here in Indima. 343 00:15:44,160 --> 00:15:47,960 Speaker 2: Isn't it fascinating that all of these quote unquote sins 344 00:15:48,040 --> 00:15:53,120 Speaker 2: that existed forever, whether it's gambling or anything else, not 345 00:15:53,160 --> 00:15:55,600 Speaker 2: only has it become legalized in a way that we've 346 00:15:55,640 --> 00:15:58,400 Speaker 2: always I kind of thought it probably never would. But 347 00:15:58,520 --> 00:16:01,840 Speaker 2: beyond that, right in your fingertips in your phone. So 348 00:16:01,880 --> 00:16:03,960 Speaker 2: let me give you an example of this. When we 349 00:16:04,080 --> 00:16:07,880 Speaker 2: lived in Michigan. We were there when sports book gambling 350 00:16:07,920 --> 00:16:10,560 Speaker 2: came online in the state of Michigan. But in addition 351 00:16:10,640 --> 00:16:14,640 Speaker 2: to sports book gambling, casino gambling can also be done 352 00:16:14,680 --> 00:16:16,480 Speaker 2: on your phone. Now that can't be done here in Indiana, 353 00:16:16,560 --> 00:16:19,640 Speaker 2: but I remember you could play craps, blackjack, slots, all 354 00:16:19,680 --> 00:16:23,560 Speaker 2: for real money as part of the normal sports betting app. 355 00:16:23,720 --> 00:16:27,560 Speaker 2: I remember we would see ads, commercials, billboards when we 356 00:16:27,560 --> 00:16:30,400 Speaker 2: were in Michigan, where recreational marijuana is legal. 357 00:16:30,360 --> 00:16:32,680 Speaker 3: Where they would deliver it to you. 358 00:16:32,920 --> 00:16:35,960 Speaker 2: So I could in Michigan legally order pot on my 359 00:16:36,080 --> 00:16:38,520 Speaker 2: phone and get it delivered to my house. I just 360 00:16:38,520 --> 00:16:41,880 Speaker 2: think that as a society, as we try and grapple 361 00:16:41,960 --> 00:16:46,000 Speaker 2: with medical marijuana and recreational marijuana and sports gambling and 362 00:16:46,040 --> 00:16:47,920 Speaker 2: all these other things that you used to have to 363 00:16:47,960 --> 00:16:50,640 Speaker 2: go somewhere else, it was difficult to get those things. 364 00:16:50,640 --> 00:16:52,560 Speaker 3: You used to have to fly to Vegas to place 365 00:16:52,560 --> 00:16:53,200 Speaker 3: a sports bet. 366 00:16:53,240 --> 00:16:55,640 Speaker 2: You used to have to go to Mexico or Jamaica 367 00:16:55,680 --> 00:16:57,680 Speaker 2: to get your pot if you wanted to smoke pot. 368 00:16:58,160 --> 00:17:01,480 Speaker 2: Not only has it become available, but available at the 369 00:17:01,520 --> 00:17:03,520 Speaker 2: touch of a button on your phone and you don't 370 00:17:03,560 --> 00:17:05,159 Speaker 2: even have to leave your house. 371 00:17:05,320 --> 00:17:09,520 Speaker 1: Well, eighteen states, including Illinois, Kentucky, and Michigan are surrounding neighbors. 372 00:17:09,640 --> 00:17:13,360 Speaker 1: They do allow online lottery sales, but the bill has 373 00:17:13,440 --> 00:17:17,320 Speaker 1: failed here in Indiana because of concerns about harm to 374 00:17:17,520 --> 00:17:20,439 Speaker 1: the actual physical casinos. They want you to have to 375 00:17:20,480 --> 00:17:24,440 Speaker 1: go to the actual casino, and also increased gambling addiction. 376 00:17:25,160 --> 00:17:29,320 Speaker 1: The lawmakers they also cite a different backlash because of 377 00:17:29,359 --> 00:17:33,119 Speaker 1: the online sports gambling, which you've mentioned, and there is starting. 378 00:17:32,920 --> 00:17:34,600 Speaker 2: To become a little bit of a backlash. You can 379 00:17:34,640 --> 00:17:37,080 Speaker 2: hear this talk about in certain circles. 380 00:17:37,240 --> 00:17:38,040 Speaker 3: That it is. 381 00:17:38,920 --> 00:17:41,400 Speaker 2: There are people that are not responsible with their sports gambling, 382 00:17:41,480 --> 00:17:43,199 Speaker 2: just like there are people that are not responsible with 383 00:17:43,240 --> 00:17:46,520 Speaker 2: their alcohol and it ends up doing serious damage to 384 00:17:46,560 --> 00:17:50,399 Speaker 2: their lives. And we're only three four five years now 385 00:17:50,480 --> 00:17:54,280 Speaker 2: into sports gambling on your phone, and I think everybody's 386 00:17:54,359 --> 00:17:56,359 Speaker 2: kind of taking a step back and saying, Okay, maybe 387 00:17:56,359 --> 00:17:59,040 Speaker 2: we should slow down here and not rush to put 388 00:17:59,280 --> 00:18:03,000 Speaker 2: everything everybody wants at the tip of their fingers on 389 00:18:03,040 --> 00:18:04,480 Speaker 2: their phone at any time of day. 390 00:18:04,640 --> 00:18:08,400 Speaker 1: Yeah, and it's probably not gonna move forward anytime soon. 391 00:18:08,840 --> 00:18:12,040 Speaker 1: This is the Kendall and Casey Show. It's ninety three WIBC. 392 00:18:18,280 --> 00:18:20,879 Speaker 1: President Trump has said that he is sending Tom Homan 393 00:18:21,040 --> 00:18:24,439 Speaker 1: to Minnesota tonight following that shooting of Alex Pretty in 394 00:18:24,520 --> 00:18:28,560 Speaker 1: that encounter Saturday with federal agents, and a federal court 395 00:18:28,600 --> 00:18:30,919 Speaker 1: hearing is set for today after that judge issued a 396 00:18:31,000 --> 00:18:36,240 Speaker 1: temporary restraining order blocking federal agencies. And everybody wants to 397 00:18:36,280 --> 00:18:38,200 Speaker 1: talk about Alex Pretty You know who I want to 398 00:18:38,240 --> 00:18:38,760 Speaker 1: talk about? 399 00:18:38,800 --> 00:18:39,119 Speaker 3: Who's that? 400 00:18:39,359 --> 00:18:43,440 Speaker 1: The other nurse Lake and Riley? How about Rachel Morin? 401 00:18:43,560 --> 00:18:48,480 Speaker 1: How about Rudy Garcia, how about Laura Wilkinson, how about 402 00:18:48,520 --> 00:18:52,400 Speaker 1: Kayla save us? I mean, all of these other individuals 403 00:18:52,560 --> 00:18:56,800 Speaker 1: were shot or killed by illegals, and everybody wants to 404 00:18:56,840 --> 00:19:00,000 Speaker 1: talk about the guy who was protesting ICE from doing 405 00:19:00,119 --> 00:19:00,560 Speaker 1: their job. 406 00:19:01,160 --> 00:19:03,879 Speaker 2: Yeah, and here is I think if we take a 407 00:19:03,920 --> 00:19:07,800 Speaker 2: step back from this and do our best to remove 408 00:19:07,880 --> 00:19:09,960 Speaker 2: the emotion from this and look at this from a 409 00:19:10,119 --> 00:19:13,520 Speaker 2: just kind of a fact based scenario, all of us 410 00:19:13,560 --> 00:19:16,160 Speaker 2: should let this play out. Look, I don't know what happened. 411 00:19:16,520 --> 00:19:19,520 Speaker 2: That's for the investigators to find out. And and let's 412 00:19:19,520 --> 00:19:22,840 Speaker 2: hope that investigation takes place by what happened in Minneapolis 413 00:19:22,840 --> 00:19:27,080 Speaker 2: over the weekend, that investigators interview witnesses, look at all 414 00:19:27,080 --> 00:19:29,880 Speaker 2: the evidence that's there. And if it turns out that 415 00:19:29,920 --> 00:19:34,120 Speaker 2: the you know, that ICE broke the law, then prosecutors 416 00:19:34,160 --> 00:19:36,520 Speaker 2: can decide that they may face charges or not. But 417 00:19:36,600 --> 00:19:39,679 Speaker 2: I think for everybody to start jumping to conclusions on 418 00:19:39,800 --> 00:19:43,439 Speaker 2: either side before any investigation has taken place is the 419 00:19:43,440 --> 00:19:46,720 Speaker 2: wrong way to go about this. Let the justice system 420 00:19:46,880 --> 00:19:49,760 Speaker 2: work the process. Here's the other part about this too. 421 00:19:50,359 --> 00:19:53,359 Speaker 2: You know, we've seen these issues with ICE in Chicago 422 00:19:53,560 --> 00:19:57,040 Speaker 2: and now in Minneapolis. ICE is operating right now in 423 00:19:57,080 --> 00:20:03,000 Speaker 2: Texas and deporting way more or illegals from Texas than 424 00:20:03,000 --> 00:20:06,040 Speaker 2: they are in Chicago or Minneapolis. There's no stories about that, 425 00:20:06,800 --> 00:20:10,359 Speaker 2: and the reason is because the governor and mayors in 426 00:20:10,400 --> 00:20:13,040 Speaker 2: the state of Texas have ordered their law enforcement to 427 00:20:13,080 --> 00:20:16,040 Speaker 2: cooperate with ICE, and so their law enforcement are there 428 00:20:16,040 --> 00:20:18,440 Speaker 2: that when there aren't ICE protesters, you've got local law 429 00:20:18,480 --> 00:20:21,800 Speaker 2: enforcement and state law enforcement there to manage crowd control, 430 00:20:22,040 --> 00:20:24,439 Speaker 2: to show up as a sign of force, and to 431 00:20:24,520 --> 00:20:27,640 Speaker 2: potentially arrest people when they attack ICE officers or break 432 00:20:27,680 --> 00:20:29,679 Speaker 2: the law in any other manner. But what you have 433 00:20:29,720 --> 00:20:33,040 Speaker 2: in Chicago and what you have in Minneapolis are governors 434 00:20:33,359 --> 00:20:37,280 Speaker 2: and mayors that have specifically told local law enforcement not 435 00:20:37,400 --> 00:20:40,879 Speaker 2: to participate, not to cooperate with ICE. So when ICE 436 00:20:40,920 --> 00:20:44,879 Speaker 2: is running a mission in Minneapolis, they've got no local 437 00:20:44,880 --> 00:20:49,080 Speaker 2: support from law enforcement whatsoever. And you've got these agitators 438 00:20:49,119 --> 00:20:52,680 Speaker 2: that are trying to agitate. 439 00:20:52,119 --> 00:20:53,880 Speaker 3: And protest ICE in every way level. 440 00:20:53,920 --> 00:20:56,200 Speaker 2: And that's why we're seeing these issues in cities like 441 00:20:56,320 --> 00:21:00,600 Speaker 2: Chicago in Minneapolis, and we're not seeing them in Houston, Dallas, 442 00:21:00,640 --> 00:21:01,600 Speaker 2: and San Antonio. 443 00:21:01,680 --> 00:21:03,200 Speaker 3: Here's the other big part of this too. 444 00:21:05,520 --> 00:21:08,000 Speaker 2: So Axios just came out with this and Axios is 445 00:21:08,000 --> 00:21:10,879 Speaker 2: a news website, and nobody has ever accused Axios of 446 00:21:10,920 --> 00:21:13,639 Speaker 2: being conservative. In fact, they usually get lumpter and on 447 00:21:13,720 --> 00:21:15,760 Speaker 2: the left too. But they put out a report that 448 00:21:16,160 --> 00:21:19,439 Speaker 2: came out on Friday, and this is some preliminary data. 449 00:21:20,240 --> 00:21:23,960 Speaker 2: The murder rate in the United States has dropped to 450 00:21:24,040 --> 00:21:27,760 Speaker 2: the lowest level since nineteen hundred, one hundred and twenty 451 00:21:27,760 --> 00:21:29,720 Speaker 2: five years. And this goes really for the most part, 452 00:21:29,720 --> 00:21:34,080 Speaker 2: across all violent crimes. Aggravated assaults are down by nine percent, 453 00:21:34,160 --> 00:21:37,240 Speaker 2: gun assaults down by twenty two percent, robbery down by 454 00:21:37,240 --> 00:21:40,760 Speaker 2: twenty three percent. Murders fell in the United States last 455 00:21:40,800 --> 00:21:43,800 Speaker 2: year by twenty one percent. 456 00:21:44,520 --> 00:21:47,520 Speaker 3: And so I remember when I was filling in last. 457 00:21:47,400 --> 00:21:49,840 Speaker 2: Year in twenty twenty four, you know, during the election, 458 00:21:49,920 --> 00:21:52,639 Speaker 2: and I said, look, Donald Trump's going to be crazy. 459 00:21:52,720 --> 00:21:55,240 Speaker 2: He's he's bringing a lot of you know, cabinet members 460 00:21:55,280 --> 00:21:57,080 Speaker 2: in that you know, you kind of shrug your shoulders 461 00:21:57,200 --> 00:21:59,879 Speaker 2: RFK Junior. Okay, I don't know if he's crazy or not. 462 00:22:00,160 --> 00:22:02,159 Speaker 2: But the point of all of this is what we 463 00:22:02,320 --> 00:22:05,479 Speaker 2: had been doing in this country wasn't working. We had 464 00:22:05,560 --> 00:22:09,679 Speaker 2: violent crime out of control, insane inflation, and our enemies 465 00:22:09,720 --> 00:22:11,800 Speaker 2: running rampant across the rest of the world, and I 466 00:22:11,800 --> 00:22:13,560 Speaker 2: said there at the time, I said, look, Donald Trump's 467 00:22:13,560 --> 00:22:15,160 Speaker 2: going to move fast, and he's going to break things, 468 00:22:15,320 --> 00:22:18,000 Speaker 2: and some of this is going to be really sloppy. 469 00:22:18,240 --> 00:22:22,439 Speaker 2: But we can't continue doing the same thing we've always 470 00:22:22,520 --> 00:22:25,560 Speaker 2: been doing and expect a different result. Here's one of 471 00:22:25,600 --> 00:22:28,920 Speaker 2: the most interesting parts of that crime statistic that Axios 472 00:22:28,960 --> 00:22:32,880 Speaker 2: put out. They went through some individual cities. Murder has 473 00:22:33,000 --> 00:22:37,840 Speaker 2: fallen in twenty twenty five, fallen by forty percent in Washington, DC. 474 00:22:38,359 --> 00:22:40,240 Speaker 2: So you could sit here and talk about, oh, you know, 475 00:22:40,480 --> 00:22:42,439 Speaker 2: Donald Trump, it was awful for him to send in 476 00:22:42,480 --> 00:22:45,679 Speaker 2: the National Guard to Washington, d C. This is fascism, 477 00:22:45,760 --> 00:22:48,680 Speaker 2: This isn't the way a democracy works. Yet you heard 478 00:22:48,680 --> 00:22:50,880 Speaker 2: many residents from Washington, DC saying. 479 00:22:50,800 --> 00:22:51,399 Speaker 3: This is great. 480 00:22:51,520 --> 00:22:53,679 Speaker 2: I now have the ability to walk by myself at 481 00:22:53,760 --> 00:22:56,439 Speaker 2: night and not be fearful, and now there's rock solid 482 00:22:56,520 --> 00:22:59,359 Speaker 2: data to back it up. In twenty twenty five, murders 483 00:22:59,359 --> 00:23:02,679 Speaker 2: in Washington fell by forty This is not going to 484 00:23:02,680 --> 00:23:05,399 Speaker 2: be clean and easy. And anytime you try and do 485 00:23:05,480 --> 00:23:08,840 Speaker 2: something that is difficult and fixed difficult problems, it is 486 00:23:08,920 --> 00:23:11,560 Speaker 2: going to be hard. And with Donald Trump, it's going 487 00:23:11,640 --> 00:23:14,560 Speaker 2: to be messy, but the data we've got so far 488 00:23:14,880 --> 00:23:17,040 Speaker 2: is showing that in a lot of areas, so far, 489 00:23:17,200 --> 00:23:18,520 Speaker 2: it's working the way. 490 00:23:18,320 --> 00:23:18,920 Speaker 3: We wanted it to. 491 00:23:19,160 --> 00:23:22,240 Speaker 1: So here's Democratic Senator John Fetterman, and he's saying that 492 00:23:22,359 --> 00:23:24,960 Speaker 1: ICE agents were just doing their job, and that he 493 00:23:25,119 --> 00:23:25,800 Speaker 1: supports that. 494 00:23:26,400 --> 00:23:32,640 Speaker 4: Absolutely unacceptable, terrible, awful. ICE agents are just doing their job. 495 00:23:33,160 --> 00:23:39,679 Speaker 4: And I fully support that. And for me and people 496 00:23:40,880 --> 00:23:43,280 Speaker 4: in my party, might you know, want to abolish it 497 00:23:43,720 --> 00:23:46,879 Speaker 4: or you know, treat them as criminals or anything that's 498 00:23:46,920 --> 00:23:55,520 Speaker 4: that's inappropriate and outrageous. ICE performs an important, an important job. 499 00:23:55,359 --> 00:23:55,960 Speaker 3: For our nation. 500 00:23:57,200 --> 00:23:59,840 Speaker 1: So one of the things that this is triggering is 501 00:23:59,840 --> 00:24:04,120 Speaker 1: a partial government shut down because there is that DHS 502 00:24:04,119 --> 00:24:08,040 Speaker 1: funding bill, and you've got now a wide swath of 503 00:24:08,040 --> 00:24:11,080 Speaker 1: Democrats who are opposing that, and now you even have 504 00:24:11,280 --> 00:24:15,200 Speaker 1: some Republicans that are joining that. But to your point, 505 00:24:15,240 --> 00:24:19,600 Speaker 1: you've got the Deputy Attorney General down in Texas and 506 00:24:19,880 --> 00:24:23,720 Speaker 1: he's saying that they deport ten times the number of 507 00:24:23,840 --> 00:24:27,480 Speaker 1: illegals out of Texas. Then what happens in Minnesota, and 508 00:24:27,640 --> 00:24:29,719 Speaker 1: he explains what the difference is. 509 00:24:30,160 --> 00:24:32,800 Speaker 6: I'm very confused about why the conversation is about what 510 00:24:32,840 --> 00:24:35,600 Speaker 6: you're talking about instead of focusing on what really matters, 511 00:24:35,720 --> 00:24:38,520 Speaker 6: which is why in one city, in one. 512 00:24:38,359 --> 00:24:42,840 Speaker 3: Place do we have these problems. We deport ten times. 513 00:24:42,440 --> 00:24:44,840 Speaker 6: A number of illegal aliens out of Texas than we 514 00:24:44,880 --> 00:24:47,880 Speaker 6: do out of Minneapolis. Why do we hear nothing out 515 00:24:47,880 --> 00:24:50,119 Speaker 6: of Texas about any of the same problems that we 516 00:24:50,160 --> 00:24:51,200 Speaker 6: have in Minneapolis. 517 00:24:51,320 --> 00:24:52,159 Speaker 3: I'll tell you why. 518 00:24:52,359 --> 00:24:54,960 Speaker 6: Because in Texas we have the cooperation and support of 519 00:24:55,000 --> 00:24:58,320 Speaker 6: local law enforcement so that we can do these operations safely, 520 00:24:58,440 --> 00:25:02,399 Speaker 6: keeping US citizens and others protected and safe. That is 521 00:25:02,480 --> 00:25:04,800 Speaker 6: not what we have in Minneapolis. And the fact that 522 00:25:04,840 --> 00:25:08,920 Speaker 6: it's the administration that's being blamed for the utter failure 523 00:25:09,720 --> 00:25:13,480 Speaker 6: of leadership in Minneapolis is not right. It's not appropriate 524 00:25:13,640 --> 00:25:15,119 Speaker 6: use of saying those officers. 525 00:25:15,840 --> 00:25:18,040 Speaker 1: So a lot of people are saying that Tim Walls 526 00:25:18,119 --> 00:25:21,320 Speaker 1: has been fanning the flames of this he has been 527 00:25:21,359 --> 00:25:23,359 Speaker 1: instigating this behavior all along. 528 00:25:23,640 --> 00:25:26,880 Speaker 2: Well, yeh, he's been doing that, not only verbally through 529 00:25:26,920 --> 00:25:29,600 Speaker 2: his press conferences, but also in the way he's managing 530 00:25:29,600 --> 00:25:32,080 Speaker 2: his state and telling his state officers and local law 531 00:25:32,119 --> 00:25:33,800 Speaker 2: enforcement not to participate in this. 532 00:25:33,840 --> 00:25:34,080 Speaker 3: Look. 533 00:25:34,240 --> 00:25:37,600 Speaker 2: I don't know if any of these recent ice shootings 534 00:25:39,320 --> 00:25:41,680 Speaker 2: are something that rises to the level where those off 535 00:25:41,720 --> 00:25:45,320 Speaker 2: ice officers should be prosecuted, and if it does, then absolutely, 536 00:25:45,359 --> 00:25:49,800 Speaker 2: I'm not justifying them either saying that the violence was 537 00:25:49,880 --> 00:25:53,600 Speaker 2: justifiable or not. I'm saying, let the legal process play out. 538 00:25:53,680 --> 00:25:55,480 Speaker 2: That's what we need to do in this and kind 539 00:25:55,480 --> 00:25:58,160 Speaker 2: of back down from the emotional aspect that we're seeing 540 00:25:58,160 --> 00:26:00,240 Speaker 2: at this and look at it from a logical standpoint. 541 00:26:00,320 --> 00:26:04,480 Speaker 2: Each of these instances will be investigated, they'll talk to witnesses, 542 00:26:04,640 --> 00:26:07,280 Speaker 2: they'll look at video evidence, and then they can decide 543 00:26:07,320 --> 00:26:09,679 Speaker 2: if ICE is doing the proper thing and following the 544 00:26:09,760 --> 00:26:11,800 Speaker 2: law or not, and then take action from there. 545 00:26:11,880 --> 00:26:14,399 Speaker 1: Now, Christinoam is saying that none of this turned violent 546 00:26:14,520 --> 00:26:18,199 Speaker 1: until they uncovered the fraud in Minneapolis, So she's pointing 547 00:26:18,200 --> 00:26:22,360 Speaker 1: her finger to that. Other people are saying that DHS's 548 00:26:22,680 --> 00:26:26,400 Speaker 1: message has not been good as well, that they need 549 00:26:26,440 --> 00:26:30,120 Speaker 1: to tone things down. But here you've got Joe Rogan and 550 00:26:30,960 --> 00:26:33,919 Speaker 1: he's saying that there's other people that we should be 551 00:26:33,960 --> 00:26:35,120 Speaker 1: talking about. 552 00:26:35,400 --> 00:26:38,200 Speaker 5: With the ICE thing. What you're only seeing and you're 553 00:26:38,200 --> 00:26:42,119 Speaker 5: only hearing about American citizens that have been arrested, the 554 00:26:42,200 --> 00:26:44,600 Speaker 5: lady that got shot, You're hearing about all these negative 555 00:26:44,640 --> 00:26:48,240 Speaker 5: hotteror which you're not hearing about is the number of 556 00:26:48,400 --> 00:26:51,600 Speaker 5: violent criminals that they've caught, and it's a lot. It's 557 00:26:51,640 --> 00:26:53,160 Speaker 5: in the thousands. 558 00:26:53,560 --> 00:26:54,360 Speaker 3: It's not like. 559 00:26:54,880 --> 00:26:58,639 Speaker 5: Thousands of American citizens have been shipped out to other country. 560 00:26:58,680 --> 00:27:03,119 Speaker 5: That's no, it's like net positive if you look at 561 00:27:03,119 --> 00:27:03,600 Speaker 5: it that way. 562 00:27:04,920 --> 00:27:06,040 Speaker 3: It's just exactly what I said. 563 00:27:06,040 --> 00:27:08,080 Speaker 2: I'm gonna go back to this Axios article and read 564 00:27:08,080 --> 00:27:10,560 Speaker 2: this data again because I think it's really important and 565 00:27:10,600 --> 00:27:14,120 Speaker 2: it supports exactly what Joe Rogan just said. The benefits 566 00:27:14,200 --> 00:27:17,920 Speaker 2: of these deportations aren't being talked about. In twenty twenty five, 567 00:27:18,240 --> 00:27:21,400 Speaker 2: murder in this country fell twenty one percent. Aggravated assaults 568 00:27:21,400 --> 00:27:24,280 Speaker 2: were down by nine percent, gun assaults down by twenty 569 00:27:24,320 --> 00:27:28,000 Speaker 2: two percent, robbery down by twenty three percent. 570 00:27:28,280 --> 00:27:31,560 Speaker 3: Those are massive historic. 571 00:27:31,520 --> 00:27:35,159 Speaker 2: Drops in violent crime that have taken place in twenty 572 00:27:35,200 --> 00:27:37,960 Speaker 2: twenty five. It is not a coincidence that had happened 573 00:27:38,040 --> 00:27:40,480 Speaker 2: as soon as Donald Trump came into office. It's not 574 00:27:40,560 --> 00:27:42,639 Speaker 2: a coincidence that had happened as soon as we started 575 00:27:42,680 --> 00:27:45,320 Speaker 2: actively deporting a lot of violent criminals. 576 00:27:45,480 --> 00:27:48,720 Speaker 1: And it is the lowest number since nineteen hundred. As 577 00:27:48,760 --> 00:27:51,320 Speaker 1: you mentioned, this is the Kendall and Case show it's 578 00:27:51,400 --> 00:28:02,800 Speaker 1: ninety three WYBC. None of them are busy today, many 579 00:28:02,840 --> 00:28:05,400 Speaker 1: of them are shut down. But let's talk about airports 580 00:28:05,440 --> 00:28:09,639 Speaker 1: across the country, and you've got what. Atlanta was always 581 00:28:09,680 --> 00:28:11,800 Speaker 1: known as the busiest airport in the country because it 582 00:28:11,840 --> 00:28:14,280 Speaker 1: was a hub for Southwest right. 583 00:28:14,400 --> 00:28:17,520 Speaker 2: Delta, and so yeah, yeah, for the last jeez, ten, fifteen, 584 00:28:17,600 --> 00:28:20,359 Speaker 2: twenty years, Atlanta Hartsfield Airport has been the busiest not 585 00:28:20,400 --> 00:28:22,760 Speaker 2: only in the country but in the world because it's 586 00:28:22,800 --> 00:28:24,800 Speaker 2: a hub for Delta, which is one of the largest 587 00:28:24,800 --> 00:28:27,240 Speaker 2: it's the main hub for Delta, but it's also a 588 00:28:27,320 --> 00:28:29,600 Speaker 2: hub for a lot of other airlines. And so when 589 00:28:29,680 --> 00:28:32,359 Speaker 2: you've got that, everybody making their connecting flight on the 590 00:28:32,359 --> 00:28:35,320 Speaker 2: East Coast has to fly and connect through Atlanta. And 591 00:28:35,359 --> 00:28:37,679 Speaker 2: so yeah, Atlanta's been the busiest airport in the world 592 00:28:37,720 --> 00:28:39,520 Speaker 2: for decades now not anymore. 593 00:28:39,760 --> 00:28:40,600 Speaker 3: Lost the crown. 594 00:28:40,800 --> 00:28:44,920 Speaker 1: Yeah, there's a new busier airport and it is Chicago's 595 00:28:45,200 --> 00:28:49,040 Speaker 1: O'Hare International Airport, now the busiest airport in the country, 596 00:28:49,160 --> 00:28:54,280 Speaker 1: and that's based on total aircraft takeoffs and landings. O'Hare 597 00:28:54,320 --> 00:28:57,520 Speaker 1: has had eight hundred and fifty seven thousand, three hundred 598 00:28:57,560 --> 00:29:01,480 Speaker 1: and ninety two takeoffs and landings whereas Atlanta eight hundred 599 00:29:01,520 --> 00:29:05,080 Speaker 1: and seven thousand, six hundred and twenty five. Atlanta held 600 00:29:05,120 --> 00:29:08,720 Speaker 1: that busiest airport title for many years, but not nomore. 601 00:29:08,920 --> 00:29:13,120 Speaker 1: O'Hara is a major hub for American airlines and also 602 00:29:13,480 --> 00:29:14,720 Speaker 1: United Airlines. 603 00:29:14,800 --> 00:29:18,120 Speaker 2: Yeah, again another reason, massive hub. It's the hub for 604 00:29:18,320 --> 00:29:21,200 Speaker 2: United Airlines, one of the largest hubs for American airlines. 605 00:29:21,240 --> 00:29:23,800 Speaker 2: And so you've got so many question connections going through 606 00:29:24,040 --> 00:29:27,200 Speaker 2: Chicago's O'Hare Airport. It's kind of too bad in a 607 00:29:27,240 --> 00:29:29,920 Speaker 2: way because O'Hare the city of Chicago. 608 00:29:30,320 --> 00:29:32,200 Speaker 3: So I was living in the Chicago. 609 00:29:31,920 --> 00:29:34,480 Speaker 2: Land area in the early eighties when O'Hare had their 610 00:29:34,640 --> 00:29:38,040 Speaker 2: massive makeover. It was a complete rebuild of the terminals 611 00:29:38,040 --> 00:29:44,160 Speaker 2: and it was this modern, new, beautiful terminal airport in Chicago, 612 00:29:44,840 --> 00:29:47,240 Speaker 2: and they essentially haven't touched it for forty years and 613 00:29:47,280 --> 00:29:48,360 Speaker 2: it's pretty much sat like that. 614 00:29:48,480 --> 00:29:50,400 Speaker 3: So we did our job and they moved on exactly. 615 00:29:50,480 --> 00:29:52,640 Speaker 2: And I had a connection through Chicago not too long ago, 616 00:29:52,680 --> 00:29:55,080 Speaker 2: and man, that airport looks like it hasn't been touched 617 00:29:55,080 --> 00:29:55,880 Speaker 2: in forty years. 618 00:29:55,960 --> 00:29:59,680 Speaker 1: Yeah, so let's see. Oh the mayor, of course, Brandon 619 00:29:59,720 --> 00:30:02,040 Speaker 1: John he's going to take full credit for this. 620 00:30:02,120 --> 00:30:03,920 Speaker 3: The mayor of Chicago, right in Chicago. 621 00:30:04,200 --> 00:30:06,760 Speaker 2: Thank god Brandon Johnson's the mayor, else they wouldn't have 622 00:30:06,800 --> 00:30:08,000 Speaker 2: gotten that title back and over. 623 00:30:08,240 --> 00:30:11,080 Speaker 1: I'm sure he called it a sign of Chicago's growth 624 00:30:11,120 --> 00:30:14,400 Speaker 1: and momentum. If that's true, why do the Chicago Bears 625 00:30:14,400 --> 00:30:15,960 Speaker 1: want to get the h out. 626 00:30:15,760 --> 00:30:18,400 Speaker 2: Of there right go to northern Indiana instead of being 627 00:30:18,440 --> 00:30:21,200 Speaker 2: in Chicago. I think this is just this is a 628 00:30:21,280 --> 00:30:23,440 Speaker 2: little bit of just a I don't want to say, 629 00:30:23,480 --> 00:30:26,360 Speaker 2: an accident, but just kind of happenstance. By the way, 630 00:30:26,360 --> 00:30:29,479 Speaker 2: the airlines are routing a routing their traffic and their 631 00:30:29,480 --> 00:30:31,720 Speaker 2: connections as it happens around the area in the country. 632 00:30:31,800 --> 00:30:34,160 Speaker 1: The mayor of Chicago said that the city is open 633 00:30:34,200 --> 00:30:37,920 Speaker 1: for business and also global travel. Now here's the thing. 634 00:30:38,120 --> 00:30:41,120 Speaker 1: There's a little asterisk with this story. The little caveat 635 00:30:41,680 --> 00:30:49,920 Speaker 1: O'Hare now leads aircraft movement. However, Atlanta leads in total passengers. 636 00:30:49,440 --> 00:30:53,360 Speaker 3: Where number one no where number one, no where number one. 637 00:30:53,520 --> 00:30:57,680 Speaker 1: Some more more people are flying through Atlanta. However, more 638 00:30:57,720 --> 00:31:01,719 Speaker 1: planes are flying through Chicago, which means it's more shipping. 639 00:31:01,800 --> 00:31:03,640 Speaker 2: Now, I was gonna say that has to be then 640 00:31:04,000 --> 00:31:09,520 Speaker 2: more fedexups and cargo traffic coming through Chicago than through Atlanta, 641 00:31:09,560 --> 00:31:12,800 Speaker 2: where Atlanta has more passenger traffic. Look, Atlanta Airport's not 642 00:31:12,840 --> 00:31:14,760 Speaker 2: that great either. If you've ever been to the Atlanta 643 00:31:14,800 --> 00:31:18,080 Speaker 2: airport when it's busy, you are shoulder to shoulder with 644 00:31:18,120 --> 00:31:21,400 Speaker 2: people walking down the concourse. It is incredible how many 645 00:31:21,440 --> 00:31:23,840 Speaker 2: bodies that they can put through that airport at one time. 646 00:31:23,920 --> 00:31:28,400 Speaker 1: Indianapolis Airport, of course winning awards for mid size airports 647 00:31:28,520 --> 00:31:29,560 Speaker 1: being the best. 648 00:31:29,360 --> 00:31:31,480 Speaker 2: Again won that award this year is being the best 649 00:31:31,520 --> 00:31:33,520 Speaker 2: mid sized airport in the country. And as somebody who 650 00:31:33,840 --> 00:31:35,960 Speaker 2: somebody who flew around the country for a living for 651 00:31:36,000 --> 00:31:38,520 Speaker 2: a number of years, I can confirm Indianapolis one of 652 00:31:38,520 --> 00:31:41,720 Speaker 2: the best airports just because everything works. You know, even 653 00:31:41,720 --> 00:31:43,440 Speaker 2: when you have to park here, it doesn't take you 654 00:31:43,480 --> 00:31:47,040 Speaker 2: forever to take the shuttle bus in planes fly on time, 655 00:31:47,240 --> 00:31:48,880 Speaker 2: you're not shoulder to shoulder. 656 00:31:48,480 --> 00:31:49,240 Speaker 3: With other people. 657 00:31:49,280 --> 00:31:51,880 Speaker 2: There are good shopping and restaurants and amenities that happen 658 00:31:51,920 --> 00:31:54,280 Speaker 2: in the airport. That's really what most travelers are looking 659 00:31:54,320 --> 00:31:57,920 Speaker 2: for in an airport. Do things just work? Is it reasonable, 660 00:31:58,040 --> 00:32:00,400 Speaker 2: is it clean? Are things on time if I need 661 00:32:00,440 --> 00:32:02,600 Speaker 2: to buy something? Or the stores that offer that service, 662 00:32:02,840 --> 00:32:05,320 Speaker 2: And Indianapolis has done a great job at checking all 663 00:32:05,360 --> 00:32:05,920 Speaker 2: those boxes. 664 00:32:05,960 --> 00:32:08,720 Speaker 1: Surprisingly, Detroit Airport also gets time marks. 665 00:32:08,760 --> 00:32:11,440 Speaker 2: I've always said this, my favorite thing about the entire 666 00:32:11,480 --> 00:32:14,400 Speaker 2: city of Detroit is their airport. Look, somebody who lived 667 00:32:14,400 --> 00:32:16,440 Speaker 2: in Detroit for a long time lived everywhere. Not a 668 00:32:16,480 --> 00:32:18,760 Speaker 2: lot to love about the city of Detroit, but the 669 00:32:18,760 --> 00:32:21,400 Speaker 2: Detroit Metro Airport is absolutely spectacular. 670 00:32:21,640 --> 00:32:23,200 Speaker 1: It's the only good thing they got going. 671 00:32:23,360 --> 00:32:23,720 Speaker 3: It's great. 672 00:32:23,760 --> 00:32:26,880 Speaker 2: They've got great restaurants in the Detroit Airport, wonderful shops. 673 00:32:26,920 --> 00:32:29,000 Speaker 2: You've got you know, the people movers, so you know, 674 00:32:29,280 --> 00:32:31,800 Speaker 2: those moving walkways so you don't have to run all 675 00:32:31,800 --> 00:32:34,600 Speaker 2: over the place. They've got a great shuttle train that 676 00:32:34,760 --> 00:32:36,360 Speaker 2: runs up on the topping walkways. 677 00:32:36,360 --> 00:32:39,160 Speaker 1: Though they're very much like the McDonald's ice cream machine. 678 00:32:39,160 --> 00:32:40,520 Speaker 1: They always seem to be broken. 679 00:32:40,680 --> 00:32:44,280 Speaker 2: Okay, sure there are some technical problems, but when they're working, yeah, 680 00:32:44,320 --> 00:32:45,880 Speaker 2: that's the best ice cream you're ever going to have. 681 00:32:46,080 --> 00:32:47,880 Speaker 2: And those are the best moving walkways you're going to 682 00:32:47,920 --> 00:32:49,400 Speaker 2: find in an airport Detroit Metro. 683 00:32:49,640 --> 00:32:53,120 Speaker 1: Speaking of airlines, the Wall Street Journal says the airlines 684 00:32:53,160 --> 00:32:56,440 Speaker 1: are going to be the winners from America's weight loss boom. 685 00:32:56,800 --> 00:32:59,720 Speaker 1: You know, all the widespread use of the GLP ones, 686 00:33:00,280 --> 00:33:04,600 Speaker 1: the weight loss airlines will be saving on their fuel. 687 00:33:05,440 --> 00:33:08,920 Speaker 2: Who did this calculation? Okay, so let's say so think 688 00:33:08,960 --> 00:33:11,080 Speaker 2: about this. So if you've got a typical a large 689 00:33:11,120 --> 00:33:14,040 Speaker 2: jumbo jet seats, what two hundred people will say and 690 00:33:14,080 --> 00:33:16,880 Speaker 2: if everybody I mean the public school math here, if 691 00:33:16,920 --> 00:33:20,680 Speaker 2: everybody lost, If you have two hundred people and everybody lost, 692 00:33:20,680 --> 00:33:23,360 Speaker 2: what how much of people losing on GLP ones on average? 693 00:33:23,360 --> 00:33:24,520 Speaker 1: With thirty to fifty pounds? 694 00:33:24,520 --> 00:33:27,280 Speaker 2: Okay, so we'll do fifty pounds? Yeah, oh boy, Okay, 695 00:33:27,320 --> 00:33:28,400 Speaker 2: maybe that is true. 696 00:33:28,920 --> 00:33:31,280 Speaker 3: That's two hundred people, two hundred people. 697 00:33:31,200 --> 00:33:34,600 Speaker 2: Always on average fifty pounds less because of GLP ones. 698 00:33:34,680 --> 00:33:35,840 Speaker 3: That's ten thousand pounds. 699 00:33:35,920 --> 00:33:38,440 Speaker 2: Yeah, I'm gonna I'm gonna say that ten thousand pounds 700 00:33:38,640 --> 00:33:41,520 Speaker 2: less on an aircraft is gonna use a lot less fuel. 701 00:33:41,560 --> 00:33:43,520 Speaker 2: Maybe this really is something. I was kind of laughing 702 00:33:43,560 --> 00:33:46,200 Speaker 2: at this headline when I first saw it, but maybe 703 00:33:46,240 --> 00:33:47,320 Speaker 2: there really is something there. 704 00:33:47,440 --> 00:33:49,840 Speaker 1: Well, they say that Delta has lost an average of 705 00:33:50,280 --> 00:33:54,240 Speaker 1: two point eight percent of their weight United three and 706 00:33:54,280 --> 00:33:58,920 Speaker 1: a half percent, Southwest four point two percent. And you've 707 00:33:58,920 --> 00:34:03,680 Speaker 1: got the aircrafts have major weight restrictions on them when 708 00:34:03,720 --> 00:34:08,840 Speaker 1: they take off. So the weight is divided between fuel, passengers, baggage, 709 00:34:08,880 --> 00:34:13,000 Speaker 1: and cargo. And if you've got the lower passenger weight, yeah, 710 00:34:13,080 --> 00:34:15,360 Speaker 1: that's going to improve some fuel efficiency. 711 00:34:15,800 --> 00:34:18,120 Speaker 2: I have have you ever been I've been on a 712 00:34:18,120 --> 00:34:20,640 Speaker 2: plane before, one of the smaller regional planes. 713 00:34:20,360 --> 00:34:21,920 Speaker 3: Where there's usually like maybe. 714 00:34:23,120 --> 00:34:25,239 Speaker 2: Two seats on one side and another seat on the 715 00:34:25,239 --> 00:34:28,040 Speaker 2: other side, where they have Actually before we taked off said. 716 00:34:28,960 --> 00:34:31,280 Speaker 3: We need to help out with weight distributions. 717 00:34:31,640 --> 00:34:34,080 Speaker 2: We need three people who are sitting on the left 718 00:34:34,160 --> 00:34:38,000 Speaker 2: side to sit on the right side. Now, I get 719 00:34:38,040 --> 00:34:40,440 Speaker 2: that weight distribution is a lot when it comes to flying, 720 00:34:40,480 --> 00:34:43,760 Speaker 2: and I guess how much weight the plane is. 721 00:34:43,040 --> 00:34:44,839 Speaker 3: Is going to affect how much fuel you use. 722 00:34:44,960 --> 00:34:47,640 Speaker 2: So with less fat people on the plane, less fuel, 723 00:34:47,719 --> 00:34:48,440 Speaker 2: I guess. 724 00:34:49,200 --> 00:34:52,320 Speaker 1: I can't they do on a smaller plane, that's gonna 725 00:34:52,360 --> 00:34:54,840 Speaker 1: make more sense the weight distribution. 726 00:34:54,960 --> 00:34:56,879 Speaker 2: I wonder if we can apply this to any other 727 00:34:57,000 --> 00:35:01,720 Speaker 2: industry outside of airlines, where where if all of a sudden, 728 00:35:01,760 --> 00:35:05,319 Speaker 2: America America's losing crazy amount of way because GLP one. 729 00:35:05,440 --> 00:35:08,160 Speaker 2: Do you think mattress manufactures people won't have to buy 730 00:35:08,160 --> 00:35:10,480 Speaker 2: a mattress as often because they're not as fat. 731 00:35:10,400 --> 00:35:13,160 Speaker 1: Or perhaps their shoes maybe they're. 732 00:35:12,960 --> 00:35:13,880 Speaker 3: Wearing out their shoes. 733 00:35:14,280 --> 00:35:17,520 Speaker 1: New industry not making as much money. Big shoe has 734 00:35:17,560 --> 00:35:19,640 Speaker 1: a problem with GLP one. 735 00:35:20,320 --> 00:35:21,319 Speaker 3: Don't you do? 736 00:35:21,440 --> 00:35:24,080 Speaker 2: Not want to get on the wrong side of Big 737 00:35:24,120 --> 00:35:28,520 Speaker 2: Birkenstock and Big Nike. Those are some mean and nasty people, 738 00:35:28,719 --> 00:35:31,080 Speaker 2: and they'll fight you tooth and nail the whole way, 739 00:35:31,360 --> 00:35:32,360 Speaker 2: maybe roadways. 740 00:35:32,440 --> 00:35:32,799 Speaker 3: I don't know. 741 00:35:32,840 --> 00:35:35,840 Speaker 2: Are you saying you sam saving gas in your car 742 00:35:36,000 --> 00:35:38,160 Speaker 2: because you're not as fat as you used to be. 743 00:35:38,840 --> 00:35:42,600 Speaker 1: Possibly the clothing industry will get a boon, though. 744 00:35:42,920 --> 00:35:46,800 Speaker 2: I figure give it five years and every single person, 745 00:35:46,920 --> 00:35:49,200 Speaker 2: every single person in America will be on a GLP 746 00:35:49,360 --> 00:35:50,120 Speaker 2: one in five years. 747 00:35:50,120 --> 00:35:50,560 Speaker 1: Do you think so? 748 00:35:50,719 --> 00:35:52,439 Speaker 3: I think it's going to be. It's good. 749 00:35:52,640 --> 00:35:55,880 Speaker 2: They It's really surprising how fast this is moved, the 750 00:35:55,960 --> 00:35:58,360 Speaker 2: g LP one revolution. I mean, it's only been like 751 00:35:58,520 --> 00:36:00,799 Speaker 2: two years since I think I first heard of it. 752 00:36:01,080 --> 00:36:03,560 Speaker 1: And they come out with and new and improved versions 753 00:36:03,600 --> 00:36:04,400 Speaker 1: all the time. 754 00:36:04,320 --> 00:36:06,640 Speaker 2: And the price keeps dropping on them. And Trump even 755 00:36:06,640 --> 00:36:09,239 Speaker 2: had a big announcement about GLP ones. And now I 756 00:36:09,280 --> 00:36:11,560 Speaker 2: don't even have to really see a doctor in person. 757 00:36:11,600 --> 00:36:13,759 Speaker 2: I can just go to a website and get a 758 00:36:13,840 --> 00:36:16,759 Speaker 2: virtual doctor's appointment and get the GLP ones mailed to 759 00:36:16,800 --> 00:36:17,280 Speaker 2: my house. 760 00:36:17,400 --> 00:36:18,399 Speaker 3: I mean, it's become so. 761 00:36:18,520 --> 00:36:22,040 Speaker 2: Easy, it's become so popular. The price because of all 762 00:36:22,080 --> 00:36:25,240 Speaker 2: of this keeps getting driven down farther and farther and farther. 763 00:36:25,480 --> 00:36:27,880 Speaker 2: It just seems like more and more people will just 764 00:36:28,000 --> 00:36:29,040 Speaker 2: take GLP one. 765 00:36:29,280 --> 00:36:32,520 Speaker 1: Now, if the airlines have to use less fuel because 766 00:36:32,560 --> 00:36:35,239 Speaker 1: there are not as many fat people on board, does 767 00:36:35,239 --> 00:36:38,120 Speaker 1: that mean that the price of flying will go lower. 768 00:36:38,239 --> 00:36:41,640 Speaker 2: I'm gonna guess that any savings from those airlines are 769 00:36:41,680 --> 00:36:44,480 Speaker 2: going to go right into the pocket of that CEO. 770 00:36:44,320 --> 00:36:46,919 Speaker 1: Right They're the ones that are making the most off 771 00:36:46,960 --> 00:36:50,319 Speaker 1: of the GLP one weight loss. It is something to 772 00:36:50,360 --> 00:36:54,080 Speaker 1: consider how it will change all sorts of industries. This 773 00:36:54,120 --> 00:36:57,080 Speaker 1: is the Kennerly Casey Show. It's ninety three WYBC 774 00:37:01,680 --> 00:37:08,120 Speaker 3: At no