1 00:00:00,320 --> 00:00:04,200 Speaker 1: You're listening to KFI AM six forty on demand. 2 00:00:05,800 --> 00:00:08,800 Speaker 2: Chris Merril caf AM six forty more stimulating talk and 3 00:00:08,800 --> 00:00:10,959 Speaker 2: on demand anytime in the iHeartRadio app. When you're on 4 00:00:10,960 --> 00:00:12,600 Speaker 2: that app, you can always hit the talk back button 5 00:00:12,960 --> 00:00:14,880 Speaker 2: and tell Mark how much you love him. 6 00:00:15,120 --> 00:00:17,480 Speaker 1: Mark love your laugh. 7 00:00:17,720 --> 00:00:19,480 Speaker 3: I have been wanting to tell you this for probably 8 00:00:19,680 --> 00:00:20,400 Speaker 3: the last year. 9 00:00:20,920 --> 00:00:23,480 Speaker 2: I love to hear you laugh. Man brings joy to 10 00:00:23,560 --> 00:00:23,919 Speaker 2: my heart. 11 00:00:24,200 --> 00:00:28,000 Speaker 3: Mary, Christmas to you guys, and Hey, do you think 12 00:00:28,080 --> 00:00:32,879 Speaker 3: Trump has a plan for that healthcare no? Or do 13 00:00:32,920 --> 00:00:34,200 Speaker 3: you think he's just waiting. 14 00:00:33,880 --> 00:00:34,479 Speaker 4: For it to come up? 15 00:00:34,560 --> 00:00:37,000 Speaker 2: Yeah? Good question. No, I don't. I don't think there's 16 00:00:37,000 --> 00:00:39,640 Speaker 2: a plan so much as because one thing about Trump 17 00:00:39,680 --> 00:00:41,920 Speaker 2: is that he loves to be the counterpuntry. He loves 18 00:00:41,960 --> 00:00:44,360 Speaker 2: to be reactionary. So no, I don't think he has 19 00:00:44,400 --> 00:00:46,000 Speaker 2: a plan. I think I think he's got the plan 20 00:00:46,040 --> 00:00:48,279 Speaker 2: for the Republicans to do a healthcare bill. But if 21 00:00:48,280 --> 00:00:51,120 Speaker 2: it backfires, it and it and the subsid he's run 22 00:00:51,159 --> 00:00:52,960 Speaker 2: out and all that other stuff. No, I don't. I 23 00:00:53,000 --> 00:00:55,400 Speaker 2: think he'll just he'll just try to counter I don't 24 00:00:55,440 --> 00:00:57,520 Speaker 2: think he I don't think he has a strategy going in. 25 00:00:58,280 --> 00:01:00,600 Speaker 2: Good question. Though apart from that, that was lovely call. 26 00:01:00,720 --> 00:01:03,680 Speaker 2: Thank you he likes your laugh. 27 00:01:03,760 --> 00:01:05,759 Speaker 5: Well, now I'm all self conscious, but that was nice week. 28 00:01:05,880 --> 00:01:08,080 Speaker 5: We need some nice stuff. It's it's it's been a 29 00:01:08,120 --> 00:01:08,880 Speaker 5: stressful week. 30 00:01:09,240 --> 00:01:12,280 Speaker 2: Yeah, fush next time, Mark lasts, Well, you just isolated 31 00:01:12,319 --> 00:01:15,240 Speaker 2: so we can just mock it, merciless leaves, don't. Yeah. 32 00:01:15,360 --> 00:01:16,720 Speaker 5: In fact, I think it's time for you to go 33 00:01:16,760 --> 00:01:21,400 Speaker 5: on another medical leaves. Yeah, I love that. 34 00:01:22,840 --> 00:01:27,000 Speaker 2: I was reading about this Venezuela stuff, which the President 35 00:01:27,040 --> 00:01:28,880 Speaker 2: did address the country earlier than I did, about a 36 00:01:28,920 --> 00:01:33,679 Speaker 2: twenty minute speech, and I thought, I thought, is this 37 00:01:33,760 --> 00:01:37,000 Speaker 2: where we've all been through it before, where something is 38 00:01:37,040 --> 00:01:39,920 Speaker 2: going on and the president does a speech and and 39 00:01:39,959 --> 00:01:42,720 Speaker 2: they go they basically take it to the country. Right. 40 00:01:42,800 --> 00:01:47,760 Speaker 2: I remember George H. W. Bush saying it's on in Iraq. Right, 41 00:01:47,800 --> 00:01:50,400 Speaker 2: I remember George W. Bush saying it's on in Iraq 42 00:01:50,480 --> 00:01:53,760 Speaker 2: and Afghanistan, uh, with with other presidents saying this is 43 00:01:53,760 --> 00:01:54,320 Speaker 2: what's happening. 44 00:01:55,480 --> 00:01:55,600 Speaker 5: Uh. 45 00:01:56,560 --> 00:01:59,120 Speaker 2: Presidents do, they'll do these addresses if there's military action 46 00:01:59,200 --> 00:02:01,120 Speaker 2: going on somewhere. And so the President said, I gotta 47 00:02:01,160 --> 00:02:02,680 Speaker 2: do this. I'm going to do this address, and I thought, 48 00:02:03,880 --> 00:02:05,640 Speaker 2: I'm going to say there's about a ten percent chance 49 00:02:05,640 --> 00:02:09,119 Speaker 2: that he's going to talk about taking action against Venezuela. 50 00:02:09,280 --> 00:02:11,440 Speaker 2: But he didn't really do that. He didn't really do that. 51 00:02:11,520 --> 00:02:14,360 Speaker 2: This was I think this was more of a he 52 00:02:14,400 --> 00:02:16,400 Speaker 2: did more of this in the first term, didn't he 53 00:02:16,400 --> 00:02:20,440 Speaker 2: where it was almost like a campaign speech. He just says, 54 00:02:20,440 --> 00:02:21,880 Speaker 2: I'm going to address the nation, and it kind of 55 00:02:22,000 --> 00:02:23,880 Speaker 2: is a here's what I'm doing, Here's where I'm going, 56 00:02:24,320 --> 00:02:27,400 Speaker 2: sort of a sort of a mini state of the Union, 57 00:02:27,680 --> 00:02:29,960 Speaker 2: so to speak. Well, maybe it was damage control. 58 00:02:30,040 --> 00:02:34,440 Speaker 5: That uh interview with Susie Wiles is still rippling across 59 00:02:34,520 --> 00:02:38,640 Speaker 5: all of news media, and the polls are what is he. 60 00:02:38,840 --> 00:02:42,960 Speaker 2: It's like approval. Yeah, so maybe that's what it is. 61 00:02:44,600 --> 00:02:47,360 Speaker 2: Side note on the Susie Wiles thing. Did you see 62 00:02:47,400 --> 00:02:52,040 Speaker 2: the photographs from Vanity Fair? I did, Oh my gosh. 63 00:02:52,200 --> 00:02:54,560 Speaker 2: So for those unfamiliar, Susie Wiles is the chief of 64 00:02:54,600 --> 00:02:57,720 Speaker 2: staff and she did this interview and she was she 65 00:02:57,760 --> 00:03:05,639 Speaker 2: was speaking very candidly and her quotes were not real flattering. However, 66 00:03:06,280 --> 00:03:07,639 Speaker 2: to the credit of the White House, they kind of 67 00:03:07,680 --> 00:03:10,200 Speaker 2: rallied and they said, no, no, this is the lamestream media. 68 00:03:10,320 --> 00:03:12,839 Speaker 2: Who's making who's twisting her words, and it's a hit piece. 69 00:03:12,840 --> 00:03:17,079 Speaker 2: Although nobody ever denied what she said. It's recorded, yeah, yeah, yeah, 70 00:03:17,080 --> 00:03:18,760 Speaker 2: but they said, oh, they framed this, this is a 71 00:03:18,840 --> 00:03:20,880 Speaker 2: hit piece. And and of course we all say, well, 72 00:03:21,560 --> 00:03:24,320 Speaker 2: if you don't trust the lamestream media, then why do 73 00:03:24,360 --> 00:03:26,520 Speaker 2: you why do you allow them to do the interviews? 74 00:03:26,560 --> 00:03:30,320 Speaker 2: I mean, you ban people from from covering the Pentagon, 75 00:03:30,400 --> 00:03:33,320 Speaker 2: you ban certain places from being an air force one. 76 00:03:33,840 --> 00:03:35,880 Speaker 2: You know, don't don't do these, don't do these long 77 00:03:35,920 --> 00:03:38,720 Speaker 2: interviews these there's things where you allow reporters to follow 78 00:03:38,760 --> 00:03:41,720 Speaker 2: me a wrong. But they did whatever eleven of them, yeah, 79 00:03:41,920 --> 00:03:45,000 Speaker 2: which I thought was really weird. But anyway, the Vanity 80 00:03:45,000 --> 00:03:49,520 Speaker 2: Fair did it. And Vanity Fair did these photographs that 81 00:03:49,520 --> 00:03:52,480 Speaker 2: were they were black and white, and they were I 82 00:03:52,560 --> 00:03:55,840 Speaker 2: think supposed to be somewhat artistic, but they ended up 83 00:03:55,920 --> 00:04:03,840 Speaker 2: just kind of turning out creepy. They were extreme close ups. 84 00:04:04,080 --> 00:04:10,360 Speaker 2: I mean, like, look, here's our pores. And in one case, 85 00:04:10,480 --> 00:04:14,920 Speaker 2: I'm looking at the one from Caroline Levitt and it 86 00:04:14,960 --> 00:04:21,280 Speaker 2: is so close up you can see the you can 87 00:04:21,360 --> 00:04:24,839 Speaker 2: see the injection points on her lips from where she 88 00:04:24,920 --> 00:04:29,680 Speaker 2: got botox, and I thought that is really not flattering, 89 00:04:29,720 --> 00:04:30,120 Speaker 2: are you at. 90 00:04:30,040 --> 00:04:32,440 Speaker 5: All, daring to suggest that she had work done. How 91 00:04:32,520 --> 00:04:34,200 Speaker 5: dare you say, I don't think it's a suggestion. I 92 00:04:34,240 --> 00:04:35,839 Speaker 5: think the evidence is right there, you see it. 93 00:04:36,440 --> 00:04:38,279 Speaker 2: But then I was surprised to see that the same 94 00:04:38,320 --> 00:04:44,240 Speaker 2: thing happened with Susie Wiles, and she really doesn't have look, 95 00:04:44,360 --> 00:04:46,760 Speaker 2: it's just how she is. She doesn't have much in 96 00:04:46,760 --> 00:04:48,640 Speaker 2: the way of lips, and she's got the same markings 97 00:04:48,640 --> 00:04:55,040 Speaker 2: on her lips too, but also hers her photograph looks 98 00:04:55,160 --> 00:04:59,919 Speaker 2: like looks like she just walked in on her teenage 99 00:05:00,040 --> 00:05:01,520 Speaker 2: boy in an awkward moment. 100 00:05:02,080 --> 00:05:04,479 Speaker 5: Well, we need a chief of staff to have full, 101 00:05:04,600 --> 00:05:07,119 Speaker 5: pillowy lips. That was my chief complaint with John Kelly 102 00:05:07,520 --> 00:05:10,920 Speaker 5: yep affair. Yeah, I totally get that. Yeah, he really 103 00:05:10,960 --> 00:05:13,279 Speaker 5: he could have used a little, a little injection. 104 00:05:13,560 --> 00:05:16,840 Speaker 2: The other thought of of Susie Wiles is that, I mean, 105 00:05:16,880 --> 00:05:19,200 Speaker 2: it's like it's like her eyes are like pasted open, 106 00:05:19,760 --> 00:05:24,320 Speaker 2: almost like almost like she went into shock when she 107 00:05:24,400 --> 00:05:26,720 Speaker 2: was six years old and has been raised in an 108 00:05:26,800 --> 00:05:29,800 Speaker 2: institution and has never spoken a word, and then they 109 00:05:29,839 --> 00:05:32,240 Speaker 2: just put a camera right up on her face and 110 00:05:32,240 --> 00:05:34,640 Speaker 2: they're like, what does she look like later? Yeah, it 111 00:05:34,680 --> 00:05:37,039 Speaker 2: was weird. It was weird. 112 00:05:37,360 --> 00:05:39,920 Speaker 5: You know, I worked with Fair for years when I 113 00:05:40,000 --> 00:05:42,839 Speaker 5: was in my newspaper career. Career one point zero. Yeah, 114 00:05:42,920 --> 00:05:46,440 Speaker 5: And I'm not sure how much control Susie Wiles and 115 00:05:46,480 --> 00:05:48,720 Speaker 5: the rest of the people had over that. But they 116 00:05:48,720 --> 00:05:51,320 Speaker 5: can always say no. They can always say I'm not 117 00:05:51,360 --> 00:05:54,839 Speaker 5: comfortable with this, or I'm not posing this way or whatever. 118 00:05:55,360 --> 00:05:56,760 Speaker 2: Uh. I don't know if. 119 00:05:56,600 --> 00:05:59,320 Speaker 5: People really have much insight into how that works behind 120 00:05:59,360 --> 00:06:02,240 Speaker 5: the scenes. But photographers will get right the hell up 121 00:06:02,279 --> 00:06:05,760 Speaker 5: into your face unless you stop them. So somebody should 122 00:06:05,800 --> 00:06:07,599 Speaker 5: have Yeah, they could have said no, it's not a 123 00:06:07,600 --> 00:06:11,360 Speaker 5: good look. It's not a good look. Yeah. 124 00:06:11,400 --> 00:06:13,920 Speaker 2: So anyway, so that's what's going on there. In the meantime, 125 00:06:14,000 --> 00:06:18,000 Speaker 2: I'm looking at the LA Times and uh, President Trump 126 00:06:18,040 --> 00:06:21,479 Speaker 2: has ordered this partial blockade of oil tankers going to 127 00:06:21,560 --> 00:06:25,560 Speaker 2: and from Venezuela, and now he's claiming that Caracas stole oil, 128 00:06:25,760 --> 00:06:29,719 Speaker 2: land and other assets from the United States and that 129 00:06:29,800 --> 00:06:32,680 Speaker 2: we're going to get excuse me, the United States will 130 00:06:32,720 --> 00:06:37,440 Speaker 2: be getting and I'm quoting them, getting land, oil, getting land, 131 00:06:37,480 --> 00:06:40,680 Speaker 2: oil rights, and whatever we had. We want it back. 132 00:06:40,920 --> 00:06:49,159 Speaker 2: He said. He did not elaborate any further. Hmm, is 133 00:06:49,160 --> 00:06:51,839 Speaker 2: it did we occupy Venezuela at some point, and that 134 00:06:51,880 --> 00:06:55,279 Speaker 2: I'm unaware. Was I not taught that in my history class. Look, 135 00:06:55,320 --> 00:06:57,120 Speaker 2: I went to I went to American public school, so 136 00:06:57,160 --> 00:06:59,520 Speaker 2: I know that my history was my history teachings were 137 00:06:59,520 --> 00:07:03,400 Speaker 2: a bit in that. But I don't recall anything about 138 00:07:03,839 --> 00:07:08,440 Speaker 2: land in Venezuela my alone on that. Maybe you've been 139 00:07:08,480 --> 00:07:12,280 Speaker 2: reading all that woke history, I guess, so maybe that's 140 00:07:12,320 --> 00:07:15,760 Speaker 2: what it is. It's a little bizarre that we're making 141 00:07:15,800 --> 00:07:20,920 Speaker 2: a claim to it, though, hmm, yeah, I'm not so 142 00:07:20,960 --> 00:07:23,400 Speaker 2: sure about that. I did see that the Venezuelan navy 143 00:07:23,440 --> 00:07:28,880 Speaker 2: has begun escorting oil tankers, so that's sort of an 144 00:07:28,960 --> 00:07:31,560 Speaker 2: escalation because in the past we had, you know, the 145 00:07:31,600 --> 00:07:35,200 Speaker 2: Trump said as the largest armada ever assembled in that 146 00:07:35,240 --> 00:07:38,480 Speaker 2: part of the Caribbean. And now you've got Venezuela saying, 147 00:07:38,520 --> 00:07:40,160 Speaker 2: oh okay, well we've got a navy too, and we're 148 00:07:40,200 --> 00:07:42,239 Speaker 2: going to escort these ships out so that you can't 149 00:07:43,040 --> 00:07:48,120 Speaker 2: you can't take them. So I feel like I feel 150 00:07:48,160 --> 00:07:51,880 Speaker 2: like we're we're pushing some buttons here and I don't 151 00:07:51,920 --> 00:07:54,760 Speaker 2: know what the I don't know what the end goal is. 152 00:07:55,720 --> 00:07:58,480 Speaker 2: Because we've heard a few different stories. We heard oil 153 00:07:59,440 --> 00:08:01,200 Speaker 2: and say, and a number of the ships that are 154 00:08:01,200 --> 00:08:02,680 Speaker 2: in and out of there have been sanctioned by the 155 00:08:02,800 --> 00:08:07,280 Speaker 2: United States, and uh and and we can't look there's 156 00:08:07,320 --> 00:08:10,480 Speaker 2: there's legitimacy to saying those ships were sanctioned. They're not 157 00:08:10,520 --> 00:08:13,200 Speaker 2: supposed to be taking oil and uh and what they're 158 00:08:13,200 --> 00:08:17,160 Speaker 2: doing is illegal. Right, So I kind of understand that logic. 159 00:08:17,800 --> 00:08:19,840 Speaker 2: But the rest of it is Maduro stole the election, 160 00:08:20,760 --> 00:08:25,560 Speaker 2: and we're stopping. We're stopping fentanyl. Ventanyl doesn't come from venezuela. 161 00:08:25,720 --> 00:08:30,000 Speaker 2: That is correct, right, which is a bit bizarre. It's 162 00:08:30,040 --> 00:08:32,080 Speaker 2: also a bit bizarre that we're going to continue on 163 00:08:32,200 --> 00:08:34,199 Speaker 2: the fentanyl path. And I don't know if these two 164 00:08:34,200 --> 00:08:35,959 Speaker 2: things are going to diverge into two different topics, or 165 00:08:35,960 --> 00:08:38,920 Speaker 2: if we're going to continue to to create an amalgamation 166 00:08:39,040 --> 00:08:44,000 Speaker 2: of drugs equals ventanyl equals venezuela. That doesn't make a 167 00:08:44,000 --> 00:08:45,559 Speaker 2: whole lot of sense to me. But we did just 168 00:08:45,679 --> 00:08:48,880 Speaker 2: step that whole argument up a notch. I'll find it. 169 00:08:48,960 --> 00:08:51,320 Speaker 2: You'll find out what the president's saying about fentanyl now, 170 00:08:51,520 --> 00:08:53,880 Speaker 2: which I think we're supposed to associate with venezuela. 171 00:08:54,880 --> 00:08:59,719 Speaker 1: I guess you're listening to KFI AM six forty on demand. 172 00:09:01,880 --> 00:09:05,120 Speaker 2: And we got a few talkbacks. People didn't like what 173 00:09:05,160 --> 00:09:08,120 Speaker 2: I thought. That's fine, great with that, love it. Appreciate 174 00:09:08,120 --> 00:09:11,079 Speaker 2: the input as always. Also, if you miss something on 175 00:09:11,120 --> 00:09:13,439 Speaker 2: tonight's program, you can always catch the podcast. It'll be 176 00:09:13,440 --> 00:09:16,120 Speaker 2: on the featured podcast section of Cafe am six forty 177 00:09:16,160 --> 00:09:22,520 Speaker 2: dot com. The President has signed an executive order now 178 00:09:23,960 --> 00:09:27,520 Speaker 2: that says that we have found weapons of mass destruction 179 00:09:29,080 --> 00:09:30,520 Speaker 2: and it's on the streets, but. 180 00:09:30,640 --> 00:09:34,679 Speaker 3: Formerly classifying fantola is a weapon of mass destruction. 181 00:09:35,080 --> 00:09:38,200 Speaker 6: We knocked out ninety six percent of the drugs coming 182 00:09:38,240 --> 00:09:40,720 Speaker 6: in by water, and now we're starting by land, and 183 00:09:40,760 --> 00:09:42,959 Speaker 6: by land is a lot easier, and that's going to 184 00:09:43,000 --> 00:09:43,760 Speaker 6: start happening. 185 00:09:43,960 --> 00:09:49,200 Speaker 2: President Donald Trump, whoa, we're stopping it by land? Does 186 00:09:49,200 --> 00:09:51,480 Speaker 2: he us just means across the border? Are we going 187 00:09:51,559 --> 00:09:53,559 Speaker 2: to start a land whar someone no need to talk 188 00:09:53,600 --> 00:09:56,520 Speaker 2: about the border? Right? President Donald Trumps high firm KJO. 189 00:09:56,640 --> 00:09:59,080 Speaker 4: You find an executive order classifying ventional as a weapon 190 00:09:59,080 --> 00:10:02,000 Speaker 4: of mass destruction he signed in the Oval Office on Monday. 191 00:10:02,040 --> 00:10:04,720 Speaker 4: Trump said his administration is formula classifying the drug as 192 00:10:04,720 --> 00:10:07,600 Speaker 4: a weapon of man destruction and added, no body. 193 00:10:07,320 --> 00:10:11,439 Speaker 2: I feel like this reporter is talking too quickly, so 194 00:10:11,559 --> 00:10:14,559 Speaker 2: much so that he said. 195 00:10:14,240 --> 00:10:16,680 Speaker 4: Listen signed in the Oval office on Monday, Trump said 196 00:10:16,679 --> 00:10:19,160 Speaker 4: his administration is formally classifying the drug as a weapon 197 00:10:19,200 --> 00:10:19,880 Speaker 4: of mat destruction. 198 00:10:20,640 --> 00:10:23,559 Speaker 2: Yeah, he was bumbling for it was he drug. He's 199 00:10:23,640 --> 00:10:25,000 Speaker 2: rushing through it, for sure. 200 00:10:25,000 --> 00:10:27,480 Speaker 4: Said his administration is formuda classifying the drug as a 201 00:10:27,520 --> 00:10:28,400 Speaker 4: weapon of man destruction. 202 00:10:29,640 --> 00:10:31,000 Speaker 2: Something that was in the editing. 203 00:10:31,040 --> 00:10:33,520 Speaker 7: Something's going on with we didn't even saying mass It 204 00:10:33,559 --> 00:10:36,439 Speaker 7: was like weapon of man destruction is formulately committing. 205 00:10:37,440 --> 00:10:40,360 Speaker 4: And added, no bomb does what this is doing. The 206 00:10:40,440 --> 00:10:43,480 Speaker 4: term weapon of mass destruction has a very specific history 207 00:10:43,520 --> 00:10:48,000 Speaker 4: in US policy. It is typically referred to nuclear, biological, chemical, 208 00:10:48,320 --> 00:10:52,240 Speaker 4: or other kinetic threats capable of causing overwhelming and lasting 209 00:10:52,320 --> 00:10:55,640 Speaker 4: damage to people, infrastructure, or the environment. Right now, it's 210 00:10:55,640 --> 00:10:58,679 Speaker 4: not immediately clear how this new designation will affect administration 211 00:10:58,760 --> 00:11:02,480 Speaker 4: policy or with illegal implications could be for people impacted 212 00:11:02,480 --> 00:11:04,240 Speaker 4: by fentyl use or drug traffickers. 213 00:11:04,440 --> 00:11:06,120 Speaker 2: I have another concern. I'll tell you what it is. 214 00:11:06,200 --> 00:11:09,360 Speaker 2: Minute and behind these numbers are real people fighting for 215 00:11:09,400 --> 00:11:11,359 Speaker 2: their lives every day. 216 00:11:11,520 --> 00:11:13,680 Speaker 4: We also have reporting from Ohio that shows what this 217 00:11:13,760 --> 00:11:16,720 Speaker 4: looks like on the ground. Oh in Lucas County specifically, 218 00:11:17,040 --> 00:11:20,080 Speaker 4: officials and investigators have tracked overdose deaths and a drop 219 00:11:20,080 --> 00:11:23,680 Speaker 4: in fentanyl related deaths, but they also stress there's more 220 00:11:23,720 --> 00:11:26,679 Speaker 4: work left to do good. The focus for first responders 221 00:11:26,679 --> 00:11:29,600 Speaker 4: and public health teams is keeping people alive long enough 222 00:11:29,760 --> 00:11:30,439 Speaker 4: to get help. 223 00:11:30,600 --> 00:11:32,680 Speaker 2: Our job is to keep them living long enough for 224 00:11:32,720 --> 00:11:35,560 Speaker 2: them to make those appropriate decisions. Okay, so this is 225 00:11:35,760 --> 00:11:38,280 Speaker 2: that's how they're dealing with things locally. But so here's 226 00:11:38,280 --> 00:11:43,560 Speaker 2: my concern. I kind of understand. I understand the logic 227 00:11:44,000 --> 00:11:46,160 Speaker 2: in the same way that in the eighties we declared 228 00:11:46,200 --> 00:11:49,440 Speaker 2: a war on drugs. Right, Drugs are killing our kids, 229 00:11:49,520 --> 00:11:51,760 Speaker 2: Drugs are killing people in the streets. Drugs have to stop. 230 00:11:51,800 --> 00:11:53,959 Speaker 2: And we've declared war on random things in the past, 231 00:11:54,040 --> 00:12:00,560 Speaker 2: war on poverty, war on I don't know politics, We'll say, 232 00:12:00,640 --> 00:12:02,040 Speaker 2: you let people on the left that will say, though 233 00:12:02,080 --> 00:12:04,240 Speaker 2: the Republicans have declared a war on women, this kind 234 00:12:04,280 --> 00:12:06,120 Speaker 2: of thing, like they love to use this high rhetoric. 235 00:12:06,120 --> 00:12:09,720 Speaker 2: But this is this is an actual executive order that 236 00:12:09,840 --> 00:12:13,200 Speaker 2: declares fentanyl as a weapon of mass destruction and based 237 00:12:13,200 --> 00:12:19,160 Speaker 2: on what based on the harm that it does to society. Okay, 238 00:12:20,640 --> 00:12:23,440 Speaker 2: I don't know if the president is using this And 239 00:12:24,559 --> 00:12:26,840 Speaker 2: time will tell as this plays out. Is the president 240 00:12:26,920 --> 00:12:31,280 Speaker 2: using this as an impetus to take action in Colombia 241 00:12:31,600 --> 00:12:36,000 Speaker 2: and which is more cocaine than fentanyl, but Mexico, fentanyl 242 00:12:36,200 --> 00:12:39,800 Speaker 2: is being the chemicals are coming in from Jina into 243 00:12:39,800 --> 00:12:43,080 Speaker 2: Mexico being mixed there, brought across the border. Right, So 244 00:12:43,200 --> 00:12:48,960 Speaker 2: is this are we saying, oh, you are facilitating drug cartels. 245 00:12:49,000 --> 00:12:52,520 Speaker 2: We've called drug cartels terrorist organizations, and now we're gonna 246 00:12:52,520 --> 00:12:56,600 Speaker 2: call fentanyl a weapon of mass destruction? Okay, So is 247 00:12:56,600 --> 00:13:01,199 Speaker 2: this a very clever way to sort of give yourself 248 00:13:01,240 --> 00:13:05,040 Speaker 2: the authority to take military action? You heard at the 249 00:13:05,080 --> 00:13:06,560 Speaker 2: very beginning he said We've done it by sea, now 250 00:13:06,559 --> 00:13:09,360 Speaker 2: we're gonna do it by land. So does that mean 251 00:13:09,400 --> 00:13:13,120 Speaker 2: we're putting boots on the ground somewhere? And again, we'll 252 00:13:13,160 --> 00:13:15,800 Speaker 2: have to see how this plays up. But here's my 253 00:13:15,840 --> 00:13:21,280 Speaker 2: concern with it. As you as you shift the definition, 254 00:13:22,400 --> 00:13:28,320 Speaker 2: what does that do for future administrations? Suppose that you 255 00:13:28,360 --> 00:13:35,160 Speaker 2: have a president AOC who suddenly decides that carbon tailpipe 256 00:13:35,160 --> 00:13:42,240 Speaker 2: emissions are weapons of mass destruction. Suppose that you have 257 00:13:43,040 --> 00:13:50,000 Speaker 2: President Newsome who declares that automatic weapons are weapons of 258 00:13:50,120 --> 00:13:53,480 Speaker 2: mass destruction or semi aut excuse me, semi automatic or 259 00:13:53,960 --> 00:13:57,760 Speaker 2: or what they call weapons of war? Right, what if 260 00:13:57,800 --> 00:13:59,720 Speaker 2: you just what if they decide that those are weapons 261 00:13:59,760 --> 00:14:04,760 Speaker 2: of man destruction? So as we loosen our definition, we 262 00:14:04,800 --> 00:14:08,200 Speaker 2: are giving more latitude to future administrations. And that's why 263 00:14:08,240 --> 00:14:12,079 Speaker 2: I worry about these things, and I think so often 264 00:14:12,520 --> 00:14:15,800 Speaker 2: when it comes to politics and policy, we either agree 265 00:14:16,120 --> 00:14:20,320 Speaker 2: or disagree based solely on the moment. We rarely have 266 00:14:20,440 --> 00:14:26,240 Speaker 2: the foresight. This is why so many people applaud the 267 00:14:26,320 --> 00:14:29,640 Speaker 2: work of the Founding fathers. They look back in history, 268 00:14:29,720 --> 00:14:32,280 Speaker 2: not just their immediate history. Obviously, there's some provisions in 269 00:14:32,360 --> 00:14:37,280 Speaker 2: the Constitution specific to that time, like the Third Amendment 270 00:14:37,320 --> 00:14:41,640 Speaker 2: that nobody ever remembers or or uses in court, which 271 00:14:41,680 --> 00:14:47,600 Speaker 2: is no quarter for foreign soldiers. But they took a 272 00:14:47,640 --> 00:14:49,600 Speaker 2: look back at history and then went, Okay, what are 273 00:14:49,640 --> 00:14:52,080 Speaker 2: some other mistakes that have been made throughout humanity that 274 00:14:52,120 --> 00:14:55,680 Speaker 2: we can guarantee we won't do, and we'll put it 275 00:14:55,680 --> 00:15:00,320 Speaker 2: in our constitution. So what happens then when you have 276 00:15:00,920 --> 00:15:03,360 Speaker 2: this sort of precedent being set where we go, oh, 277 00:15:03,480 --> 00:15:06,760 Speaker 2: fentanyl is a weapon of mass destruction. That's now we've 278 00:15:06,800 --> 00:15:10,040 Speaker 2: decided that's a problem. And so now we're gonna use 279 00:15:10,040 --> 00:15:11,720 Speaker 2: that we're going to issue an executive order. And if 280 00:15:11,760 --> 00:15:14,960 Speaker 2: that executive order stands, does that then allow for future 281 00:15:15,040 --> 00:15:19,000 Speaker 2: presidents to declare whatever it is that they're after, whether 282 00:15:19,120 --> 00:15:22,560 Speaker 2: noble or not, to be a weapon of mass destruction. 283 00:15:23,160 --> 00:15:25,000 Speaker 2: I don't think any of us would argue that, no, 284 00:15:25,040 --> 00:15:26,840 Speaker 2: fentanyl's a great thing to have in the streets. None 285 00:15:26,880 --> 00:15:28,880 Speaker 2: of us are going to argue that. Now, you might 286 00:15:28,960 --> 00:15:30,960 Speaker 2: argue that fentanyl is something that is useful in a 287 00:15:30,960 --> 00:15:34,360 Speaker 2: hospital setting, in a clinical setting, with UH, with the 288 00:15:35,040 --> 00:15:38,960 Speaker 2: licensed physicians who are administering, that that that drug on 289 00:15:39,000 --> 00:15:43,400 Speaker 2: a necessary basis great. I think that's one we can 290 00:15:43,440 --> 00:15:47,120 Speaker 2: probably agree on. However, I think we also all agree 291 00:15:47,160 --> 00:15:51,520 Speaker 2: on fentanyl industry is bad and deadly cool. But what 292 00:15:51,640 --> 00:15:54,240 Speaker 2: happens when the next president comes in and they go, Oh, 293 00:15:54,360 --> 00:15:58,040 Speaker 2: whether you agree or disagree, it doesn't matter, because climate 294 00:15:58,120 --> 00:16:02,440 Speaker 2: change is happening, and climate change is destroying civilizations. It 295 00:16:02,600 --> 00:16:07,960 Speaker 2: is the greatest weapon of mass destruction. No single thing 296 00:16:08,080 --> 00:16:11,040 Speaker 2: in the history of mankind, aside from an asteroid that 297 00:16:11,080 --> 00:16:14,200 Speaker 2: wiped out the dinosaurs, has been so destructive to Earth. 298 00:16:14,240 --> 00:16:18,000 Speaker 2: There is no bigger mass destruction than climate change that 299 00:16:18,080 --> 00:16:20,120 Speaker 2: has to be classified as a weapon of mass destruction, 300 00:16:20,200 --> 00:16:22,600 Speaker 2: and now we can take action against it. What happens 301 00:16:22,640 --> 00:16:26,560 Speaker 2: when President AOC decides that. So just be cautious that 302 00:16:26,880 --> 00:16:29,600 Speaker 2: we're not falling into this trap of I like or 303 00:16:29,640 --> 00:16:33,360 Speaker 2: dislike what this president is doing, Because for some of you, 304 00:16:33,360 --> 00:16:36,280 Speaker 2: you might be thinking, hey, merrily, you're making a lot 305 00:16:36,280 --> 00:16:39,320 Speaker 2: of sense. If we had a president AOC who said 306 00:16:39,320 --> 00:16:41,560 Speaker 2: climate change is a weapon of mass destruction, she'd be right. 307 00:16:41,640 --> 00:16:45,120 Speaker 2: You might be saying that. But then are you cool 308 00:16:45,240 --> 00:16:50,560 Speaker 2: when the next Republican president comes in and decides that 309 00:16:53,280 --> 00:16:55,960 Speaker 2: classic literature is a weapon of mass destruction. I don't know, 310 00:16:56,000 --> 00:16:59,200 Speaker 2: whatever it is. You get my point, right, Just be careful, 311 00:17:00,080 --> 00:17:03,840 Speaker 2: careful on the slippery slope. Hey, your told artificial intelligence 312 00:17:03,880 --> 00:17:07,120 Speaker 2: is the future. You're told that this bubble is different. 313 00:17:07,640 --> 00:17:10,120 Speaker 2: That is exactly what investors were told before the dot 314 00:17:10,160 --> 00:17:13,000 Speaker 2: com bubble popped. Why the AI hype is starting to 315 00:17:13,000 --> 00:17:15,040 Speaker 2: look early familiar as next. 316 00:17:15,680 --> 00:17:19,080 Speaker 1: You're listening to KFI AM six forty on demand. 317 00:17:23,600 --> 00:17:27,720 Speaker 2: You know it's a it's crazy. I uh so, I 318 00:17:27,800 --> 00:17:29,840 Speaker 2: section the show off and I always I dedicate a 319 00:17:29,840 --> 00:17:31,879 Speaker 2: certain portion of the show that I'll talk about whatever 320 00:17:31,920 --> 00:17:35,600 Speaker 2: the latest big national thing is. If it's politics. And 321 00:17:35,640 --> 00:17:37,720 Speaker 2: my rule in politics is this, I don't talk about 322 00:17:37,760 --> 00:17:39,960 Speaker 2: politics unless there's something to talk about. There are a 323 00:17:39,960 --> 00:17:42,520 Speaker 2: few things the President spoke tonight. I thought that was interesting, 324 00:17:42,520 --> 00:17:44,479 Speaker 2: and I think also that what we see going on 325 00:17:44,600 --> 00:17:46,520 Speaker 2: in the Caribbean is worth talking about. But I'm not 326 00:17:46,560 --> 00:17:48,760 Speaker 2: going to spend a whole show on it unless, of course, 327 00:17:48,760 --> 00:17:52,840 Speaker 2: we have something really significant happening. But boy, oh boy, 328 00:17:53,280 --> 00:17:55,120 Speaker 2: we get the most, is it fair to say? Mark? 329 00:17:55,160 --> 00:17:57,840 Speaker 2: The most reaction? Of course is when it comes to politics. 330 00:17:57,880 --> 00:18:00,359 Speaker 2: It just goes to show how quickly divide did we 331 00:18:00,440 --> 00:18:06,840 Speaker 2: are and how much people react. Whenever you just mentioned politicians, 332 00:18:07,240 --> 00:18:10,040 Speaker 2: avoid can we can just talk about guild Gerard all night? 333 00:18:10,320 --> 00:18:13,120 Speaker 2: And then that would probably be sad. That's a great idea. Yeah, 334 00:18:13,280 --> 00:18:18,280 Speaker 2: what a great idea. Let's do Let's do a complete 335 00:18:18,400 --> 00:18:22,439 Speaker 2: recap of all the Twilight movies. Let's do that. 336 00:18:22,640 --> 00:18:29,399 Speaker 5: Yeah. Yeah, I'm I'm team Werewolf. That figures, I said, Jacob, 337 00:18:30,320 --> 00:18:30,919 Speaker 5: I can see that. 338 00:18:31,280 --> 00:18:34,840 Speaker 2: Yeah, I'm team Werewolf. Who were they? Jacob? Was that? 339 00:18:34,960 --> 00:18:39,080 Speaker 5: Jacob and Jacob and Edward alarmed? Foosh that you know this? 340 00:18:40,080 --> 00:18:42,680 Speaker 2: Rely on him because you you're the expert on these 341 00:18:42,720 --> 00:18:43,240 Speaker 2: sorts of things. 342 00:18:43,960 --> 00:18:44,040 Speaker 5: Up. 343 00:18:44,640 --> 00:18:46,640 Speaker 2: Yeah, because I had an ex who like was obsessed 344 00:18:46,680 --> 00:18:49,480 Speaker 2: with the movies. And have you considered dating somebody that 345 00:18:49,600 --> 00:18:51,359 Speaker 2: wasn't in middle school? Ah? 346 00:18:55,480 --> 00:18:58,920 Speaker 7: They got creepy fast. Yeah, yeah, yeah they didn't. By 347 00:18:58,960 --> 00:19:01,360 Speaker 7: the way, for. 348 00:19:01,200 --> 00:19:05,000 Speaker 2: The record, For the record, that's cool. I thought you 349 00:19:05,040 --> 00:19:06,399 Speaker 2: were going to say you had like a niece or 350 00:19:06,400 --> 00:19:08,240 Speaker 2: something that was really into it, and you're like, I 351 00:19:08,320 --> 00:19:11,160 Speaker 2: dated somebody. Well, I mean I didn't. 352 00:19:10,920 --> 00:19:13,879 Speaker 7: Even know about Like, I didn't know because some girl 353 00:19:13,920 --> 00:19:16,600 Speaker 7: that I worked with she told me about it and 354 00:19:16,640 --> 00:19:18,440 Speaker 7: it was just like the book at the time, and 355 00:19:18,480 --> 00:19:19,760 Speaker 7: I'm like, oh, and then they came out it was 356 00:19:19,800 --> 00:19:23,040 Speaker 7: this worldwide phenomenon and she was that was the book 357 00:19:23,040 --> 00:19:24,960 Speaker 7: I was reading, and that was like a year two 358 00:19:25,000 --> 00:19:27,840 Speaker 7: years before so, but then obviously, you know, blew up 359 00:19:27,840 --> 00:19:28,520 Speaker 7: into what it was. 360 00:19:28,680 --> 00:19:31,520 Speaker 2: Honestly, I've not watched any of those, and I don't 361 00:19:31,520 --> 00:19:33,840 Speaker 2: know how I avoided it because I had I had 362 00:19:33,960 --> 00:19:36,439 Speaker 2: kids right there. They're all adults now, but they were 363 00:19:36,520 --> 00:19:39,199 Speaker 2: kind of in that time period. The other one is 364 00:19:39,240 --> 00:19:41,880 Speaker 2: I've only seen one Hunger Games, the very first one, 365 00:19:42,800 --> 00:19:43,920 Speaker 2: and that was that was okay. 366 00:19:43,960 --> 00:19:46,160 Speaker 5: I always thought the first one too. Yeah, well, they're 367 00:19:46,200 --> 00:19:48,439 Speaker 5: not for you or for me. Not everything is. 368 00:19:49,119 --> 00:19:52,119 Speaker 2: Kids though, right I had I had teenagers at the 369 00:19:52,119 --> 00:19:54,359 Speaker 2: time that these tween movies were coming out. 370 00:19:55,480 --> 00:19:57,920 Speaker 7: But so did they read the Book of Hunger Games 371 00:19:58,040 --> 00:20:00,639 Speaker 7: or did they just don't know? Oh I don't pay 372 00:20:00,680 --> 00:20:03,080 Speaker 7: attention the kids even read anymore. They just wait for 373 00:20:03,080 --> 00:20:05,200 Speaker 7: the movie to come out. Well that's what I do. Yeah, 374 00:20:05,200 --> 00:20:06,640 Speaker 7: that's smart anyway. 375 00:20:07,040 --> 00:20:09,600 Speaker 2: Good deal of feedback positive, negative, You like what I say, 376 00:20:09,600 --> 00:20:11,280 Speaker 2: you hate what I say, whatever it is. I appreciate that. 377 00:20:11,320 --> 00:20:13,080 Speaker 2: Guys that did read all of the all of the 378 00:20:13,119 --> 00:20:16,040 Speaker 2: different talkbacks, so everybody that dropped the note, I appreciate that, 379 00:20:16,040 --> 00:20:18,479 Speaker 2: including one guy who said he's worked working for UPS 380 00:20:18,520 --> 00:20:21,520 Speaker 2: at a fourteen hour day and he appreciates listening. So 381 00:20:21,720 --> 00:20:23,640 Speaker 2: thanks man, I appreciate that. I appreciate all hard work 382 00:20:23,640 --> 00:20:24,800 Speaker 2: that you're putting in right now. I know it's a 383 00:20:24,840 --> 00:20:27,800 Speaker 2: tough time of year. Mark. I know how big a 384 00:20:27,840 --> 00:20:29,439 Speaker 2: fan you are of AI. So if you need to 385 00:20:29,440 --> 00:20:31,800 Speaker 2: put on earmuffs because I'm going to say something that 386 00:20:31,880 --> 00:20:34,600 Speaker 2: might not be so friendly about it, I'll just grin 387 00:20:34,600 --> 00:20:36,600 Speaker 2: and baron. Okay, all right, I try to deal with 388 00:20:36,640 --> 00:20:39,879 Speaker 2: this if you would. Are we at the precipice of 389 00:20:39,880 --> 00:20:43,960 Speaker 2: an AI bubble. A lot of money being poured into 390 00:20:43,960 --> 00:20:47,680 Speaker 2: AI and it feels very much like the dot com 391 00:20:47,880 --> 00:20:51,040 Speaker 2: in the nineteen nineties. In the nineties, for those of 392 00:20:51,119 --> 00:20:54,600 Speaker 2: you that are young, in the nineties, everyone was doing 393 00:20:54,600 --> 00:20:57,280 Speaker 2: a dot com. It didn't matter what they had, they'd do, 394 00:20:57,320 --> 00:20:59,800 Speaker 2: they'd get the the url, throw a dot com and 395 00:20:59,800 --> 00:21:02,080 Speaker 2: then they were advertising come join us. And it was 396 00:21:02,240 --> 00:21:05,000 Speaker 2: you know, pets dot com, and and uh and it 397 00:21:05,080 --> 00:21:08,720 Speaker 2: was uh car parts dot com and uh fingernails dot 398 00:21:08,760 --> 00:21:10,800 Speaker 2: com and I'm just thinking random thing. It was like, uh, 399 00:21:10,920 --> 00:21:13,600 Speaker 2: you know, uh man dot com, woman dot com, TV 400 00:21:13,720 --> 00:21:18,760 Speaker 2: dot com, camera dot com, people dot com. Don't think 401 00:21:18,800 --> 00:21:20,200 Speaker 2: too hard on that one. It was a deep cut. 402 00:21:20,680 --> 00:21:25,879 Speaker 2: But uh, eventually we all went, Okay, the dot coms 403 00:21:25,920 --> 00:21:28,480 Speaker 2: are not turning money right now, even the ones that 404 00:21:28,520 --> 00:21:33,040 Speaker 2: were successful. Probably Amazon is the biggest success story there. 405 00:21:34,240 --> 00:21:37,359 Speaker 2: Didn't Amazon take what was it eighteen years before it 406 00:21:37,400 --> 00:21:40,640 Speaker 2: finally turned a profit. But for the longest time, people went, 407 00:21:40,680 --> 00:21:42,320 Speaker 2: it's going to, it's going to, it's going to, it's 408 00:21:42,320 --> 00:21:44,760 Speaker 2: going to And then obviously it did and it turned 409 00:21:44,760 --> 00:21:47,920 Speaker 2: a massive profit. But in the early days you had 410 00:21:48,000 --> 00:21:52,080 Speaker 2: I think eBay turn to profit early. I want to 411 00:21:52,160 --> 00:21:56,000 Speaker 2: say that there were Amazon was just selling books at 412 00:21:56,000 --> 00:21:57,480 Speaker 2: the time, and I think that's part of the reason 413 00:21:57,520 --> 00:21:59,159 Speaker 2: they weren't turning a profit because they had, you know, 414 00:21:59,280 --> 00:22:03,080 Speaker 2: limited inventory. But there were a few that survived the 415 00:22:03,400 --> 00:22:06,800 Speaker 2: dot com bubble and it became massive, but most of 416 00:22:06,840 --> 00:22:10,320 Speaker 2: them got washed out. So are we seeing the same 417 00:22:10,359 --> 00:22:13,119 Speaker 2: thing when it comes to AI, Because if you'll notice, 418 00:22:14,240 --> 00:22:17,359 Speaker 2: every company out there is claiming that they are using 419 00:22:17,520 --> 00:22:23,000 Speaker 2: AI in their product, robot vacuum using AI. Are you 420 00:22:23,320 --> 00:22:25,280 Speaker 2: is that AI? Are you just using an algorithm to 421 00:22:25,320 --> 00:22:30,160 Speaker 2: map a room? Oh? It's AI. The concept of artificial 422 00:22:30,160 --> 00:22:35,800 Speaker 2: intelligence is so nebulous that even the creators can't even 423 00:22:35,800 --> 00:22:38,440 Speaker 2: tell you exactly how it works. They made the dumb thing. 424 00:22:38,480 --> 00:22:40,760 Speaker 2: They don't even know exactly how it works. It's kind 425 00:22:40,760 --> 00:22:42,600 Speaker 2: of like the human brain, Like we know a lot 426 00:22:42,600 --> 00:22:45,960 Speaker 2: about the human brain, but it's also the least understood 427 00:22:46,080 --> 00:22:50,199 Speaker 2: organ in the human body. Like we got an idea, 428 00:22:50,400 --> 00:22:53,040 Speaker 2: we just don't know exactly why. Okay, same thing with 429 00:22:53,160 --> 00:22:58,400 Speaker 2: artificial intelligence. And so everyone's saying AI AI AI. Oh, 430 00:22:58,480 --> 00:23:07,320 Speaker 2: this washing machine has AI. What Oh my iron uses AI? Huh, 431 00:23:07,480 --> 00:23:10,399 Speaker 2: everything's got an AI attached to it now. And then 432 00:23:10,400 --> 00:23:13,359 Speaker 2: the weird thing about AI is how much money is 433 00:23:13,400 --> 00:23:17,480 Speaker 2: being poured from one AI company into the next AI company. So, 434 00:23:17,640 --> 00:23:20,359 Speaker 2: for instance, and I don't know the exact numbers on this, 435 00:23:20,480 --> 00:23:23,240 Speaker 2: and I'm just gonna throw out a for instance, you'll 436 00:23:23,240 --> 00:23:26,120 Speaker 2: have a company like Microsoft that says we are going 437 00:23:26,160 --> 00:23:30,280 Speaker 2: to invest a billion dollars into open ai that's Chat GPT, 438 00:23:30,560 --> 00:23:33,399 Speaker 2: and Chat GPT says great, we've got to seed money. Oh, 439 00:23:33,440 --> 00:23:35,520 Speaker 2: you know what we're gonna do. We're gonna give money 440 00:23:35,800 --> 00:23:38,480 Speaker 2: to Nvidia so that Nvidia can help us develop more 441 00:23:38,520 --> 00:23:40,400 Speaker 2: chips to make our stuff work better. And then video 442 00:23:40,480 --> 00:23:42,320 Speaker 2: goes cool, this is great. And then video says, you 443 00:23:42,359 --> 00:23:45,399 Speaker 2: know what, We're gonna invest money into Microsoft so that 444 00:23:45,520 --> 00:23:49,200 Speaker 2: Microsoft can help us with our chip development and uh. 445 00:23:49,240 --> 00:23:51,720 Speaker 2: And then Microsoft goes cool. Now that we're making more money, 446 00:23:51,720 --> 00:23:54,040 Speaker 2: we're gonna invest more money into open Ai, and Opening 447 00:23:54,040 --> 00:23:56,200 Speaker 2: Eye says great, we're gonna invest more money into in video, 448 00:23:56,200 --> 00:23:57,879 Speaker 2: and then video says we're gonna invest and see how 449 00:23:57,920 --> 00:24:01,800 Speaker 2: this works. Well, at some point you gotta show a profit, 450 00:24:02,720 --> 00:24:06,040 Speaker 2: and unless that profit's coming in, that tap is going 451 00:24:06,080 --> 00:24:09,240 Speaker 2: to run dry. And this is why people were worried 452 00:24:09,320 --> 00:24:14,600 Speaker 2: last week when Oracle took a big hit from writers. 453 00:24:15,000 --> 00:24:17,919 Speaker 6: Shares of Oracle slumped as much as sixteen and a 454 00:24:17,920 --> 00:24:21,880 Speaker 6: half percent Thursday morning, as fresh worries over the company's 455 00:24:21,920 --> 00:24:26,720 Speaker 6: hefty spending on artificial intelligence sparked fears of an AI bubble. 456 00:24:27,119 --> 00:24:29,119 Speaker 2: Yeah, now, you got a lot of money wrapped up 457 00:24:29,160 --> 00:24:32,359 Speaker 2: into it, and have you figured out how to monetize 458 00:24:32,359 --> 00:24:32,879 Speaker 2: this yet? 459 00:24:33,520 --> 00:24:36,840 Speaker 6: If the losses hold, Oracle would shed more than ninety 460 00:24:36,880 --> 00:24:38,720 Speaker 6: billion dollars in market value. 461 00:24:38,800 --> 00:24:39,240 Speaker 7: Wow. 462 00:24:39,359 --> 00:24:42,560 Speaker 6: The tech giant a day earlier forecast sales and profit 463 00:24:42,680 --> 00:24:46,119 Speaker 6: that mist Wall Street estimates. It also warned that it 464 00:24:46,119 --> 00:24:50,480 Speaker 6: would likely spend fifteen billion dollars more than planned in 465 00:24:50,600 --> 00:24:55,320 Speaker 6: order to attract AI cloud computing customers. Investors saw it 466 00:24:55,359 --> 00:24:58,040 Speaker 6: as a sign that the massive amounts of money Oracle 467 00:24:58,160 --> 00:25:01,480 Speaker 6: is pouring into its AI efforts is not turning into 468 00:25:01,520 --> 00:25:03,760 Speaker 6: profit as fast as Wall Street had hoped. 469 00:25:04,200 --> 00:25:06,600 Speaker 2: Yeah, now this is a big issue. This is a 470 00:25:06,640 --> 00:25:09,359 Speaker 2: big problem for a couple of reasons. One Oracle, California company. 471 00:25:09,400 --> 00:25:13,040 Speaker 2: That's Larry Ellison, right, Larry Ellison is funding a lot 472 00:25:13,040 --> 00:25:14,879 Speaker 2: of David Ellison's stuff that's going on too with the 473 00:25:14,880 --> 00:25:20,680 Speaker 2: paramount sky Dance. And maybe most importantly, isn't it Larry 474 00:25:21,359 --> 00:25:24,960 Speaker 2: Larry Ellison's girlfriend. That's the fan of University of Michigan 475 00:25:25,000 --> 00:25:26,680 Speaker 2: that convinced him to give a bunch of money to 476 00:25:26,760 --> 00:25:29,480 Speaker 2: the quarterback to get the best quarterback there. Yeah, now 477 00:25:29,520 --> 00:25:32,399 Speaker 2: that's a major concern to me. I can't have that 478 00:25:32,480 --> 00:25:36,479 Speaker 2: nil money dry up just because AI isn't working out. 479 00:25:37,200 --> 00:25:39,080 Speaker 2: I hope I have my celebrities correct on that, otherwise 480 00:25:39,080 --> 00:25:44,679 Speaker 2: I'm gonna feel foolish. But at some point we're going 481 00:25:44,720 --> 00:25:49,199 Speaker 2: to see some billionaires lose about everything. Look at how 482 00:25:49,280 --> 00:25:53,200 Speaker 2: much Elon Musk has put into Grock. Now he's diversified, 483 00:25:53,680 --> 00:25:57,200 Speaker 2: so if Grock doesn't work out X, I don't think 484 00:25:57,280 --> 00:25:58,600 Speaker 2: is ever going to turn him a profit. But he's 485 00:25:58,640 --> 00:26:01,240 Speaker 2: still got SpaceX and Tesla and things like that. But 486 00:26:01,359 --> 00:26:03,520 Speaker 2: for a number of others, they are putting all of 487 00:26:03,560 --> 00:26:06,879 Speaker 2: their eggs in the AI basket, and that is going 488 00:26:06,920 --> 00:26:10,360 Speaker 2: to be a problem. Back to Reuter's. 489 00:26:10,600 --> 00:26:14,800 Speaker 6: Oracles, warnings come amid investor fears of a broader AI bubble, 490 00:26:15,200 --> 00:26:20,000 Speaker 6: stoked by sky high valuations, limited real world productivity gains, 491 00:26:20,320 --> 00:26:24,960 Speaker 6: and complex circular investments, even as companies raise billions in 492 00:26:25,040 --> 00:26:27,280 Speaker 6: debt to build AI infrastructure. 493 00:26:27,480 --> 00:26:29,800 Speaker 2: The circular investments is what I was talking about earlier 494 00:26:29,800 --> 00:26:34,480 Speaker 2: complex circular investments. That's one way to put it. Yeah, 495 00:26:34,600 --> 00:26:37,000 Speaker 2: I mean, I don't know. I'm not going to say 496 00:26:37,000 --> 00:26:41,159 Speaker 2: that it's not like money laundering, but if you're a cynic, 497 00:26:41,200 --> 00:26:45,280 Speaker 2: you might say that it's unscrupulous business practices. You might 498 00:26:45,359 --> 00:26:48,199 Speaker 2: do that. And I don't know if you've noticed this. 499 00:26:48,280 --> 00:26:50,240 Speaker 2: I find this really interesting. You've got tech bros that 500 00:26:50,320 --> 00:26:53,639 Speaker 2: are pouring billions into anything that is AI and the 501 00:26:53,640 --> 00:26:56,600 Speaker 2: companies that are creating this tech, and then they're also 502 00:26:56,680 --> 00:26:58,840 Speaker 2: pouring a bunch of money into all the cloud computing 503 00:26:58,840 --> 00:27:01,919 Speaker 2: companies and the information storage companies on all this other stuff. 504 00:27:02,160 --> 00:27:04,919 Speaker 2: And they're racing now to build these massive data centers. 505 00:27:04,920 --> 00:27:07,679 Speaker 2: And you might you might even be coming to a 506 00:27:07,720 --> 00:27:10,919 Speaker 2: neighborhood near you, and communities are starting to fight back. 507 00:27:11,480 --> 00:27:14,240 Speaker 2: Why can't these super rich modern companies convince people the 508 00:27:14,280 --> 00:27:16,920 Speaker 2: developments are good things. You're gonna find out why. 509 00:27:17,080 --> 00:27:21,400 Speaker 1: Next you're listening to KFI AM six forty on demand. 510 00:27:22,640 --> 00:27:25,720 Speaker 2: There is a battle royale going on with some of 511 00:27:25,760 --> 00:27:30,160 Speaker 2: the big dollars, the big dollars in Hollywood, and you'll 512 00:27:30,280 --> 00:27:33,879 Speaker 2: find out what the latest is that after Mark's at 513 00:27:33,920 --> 00:27:37,160 Speaker 2: nine o'clock, is it almost nine o'clock already, baby, almost 514 00:27:37,200 --> 00:27:45,920 Speaker 2: getting there? Who time flies when you're drinking tequila? Jealous? 515 00:27:46,440 --> 00:27:50,120 Speaker 2: So ronn Or I know you. You had to struggle 516 00:27:50,119 --> 00:27:52,520 Speaker 2: there to keep quiet because I know how much you 517 00:27:52,600 --> 00:27:55,280 Speaker 2: like the AI and you didn't like me talking bad 518 00:27:55,320 --> 00:27:56,840 Speaker 2: about your your favorite tech. 519 00:27:56,960 --> 00:27:58,880 Speaker 5: No, no, you're in the driver's seat. I always try 520 00:27:58,920 --> 00:28:01,840 Speaker 5: to follow your lead and defer to you and crap 521 00:28:01,960 --> 00:28:02,280 Speaker 5: like that. 522 00:28:02,680 --> 00:28:05,480 Speaker 2: You know why you here a complete pro? You're a 523 00:28:05,520 --> 00:28:10,359 Speaker 2: complete pro. So now that we find out that we 524 00:28:10,400 --> 00:28:14,600 Speaker 2: have complicated circular investments going on which are giving some 525 00:28:14,600 --> 00:28:18,080 Speaker 2: people the hebgb's going into the new year, are we 526 00:28:18,160 --> 00:28:20,960 Speaker 2: at the point of seeing a bubble and a collapse? Well, 527 00:28:21,000 --> 00:28:22,760 Speaker 2: if we take a look back at the dot com bubble, 528 00:28:22,760 --> 00:28:26,080 Speaker 2: it took a few more years than what we're seeing 529 00:28:26,119 --> 00:28:28,880 Speaker 2: with the AI bubble. The AI bubble seems to be 530 00:28:29,240 --> 00:28:32,920 Speaker 2: only about two maybe three years old, whereas the dot 531 00:28:32,920 --> 00:28:34,840 Speaker 2: com bubble felt like it was sort of festering for 532 00:28:34,880 --> 00:28:38,320 Speaker 2: about five or six years. However, you can also argue 533 00:28:38,360 --> 00:28:43,320 Speaker 2: that everything moves faster nowadays, Everything goes faster. One of 534 00:28:43,360 --> 00:28:45,520 Speaker 2: the things that I think is really fascinating to see, 535 00:28:45,520 --> 00:28:47,520 Speaker 2: and I think this is going to be indicative of 536 00:28:48,200 --> 00:28:52,680 Speaker 2: sort of consumer sentiment when it comes to AI AI adoption. 537 00:28:52,840 --> 00:28:55,480 Speaker 2: What it means to us is how much we're starting 538 00:28:55,520 --> 00:28:58,160 Speaker 2: to get communities that are pushing back and they're saying, 539 00:28:58,760 --> 00:29:02,520 Speaker 2: not in my backyard. Because when it comes to AI, 540 00:29:02,680 --> 00:29:04,200 Speaker 2: when it comes to data centers, when it comes to 541 00:29:04,240 --> 00:29:10,040 Speaker 2: cloud computing, all of these places require huge footprints, massive 542 00:29:10,680 --> 00:29:14,440 Speaker 2: uh server farms, and the server farms require a great 543 00:29:14,440 --> 00:29:19,240 Speaker 2: deal of energy and a great deal of water to cool. 544 00:29:20,160 --> 00:29:22,440 Speaker 2: And so depending on where you are and there are 545 00:29:22,600 --> 00:29:25,160 Speaker 2: there are these these data centers that are being built 546 00:29:25,200 --> 00:29:30,600 Speaker 2: all over the country, including here. Northern Virginia has got 547 00:29:30,640 --> 00:29:33,520 Speaker 2: a huge concentration of these data centers. Chicago's got a 548 00:29:33,560 --> 00:29:38,040 Speaker 2: big concentration of data centers today, Dallas, Texas big concentration, 549 00:29:38,320 --> 00:29:41,560 Speaker 2: Phoenix big concentration, and of course the Bay Area, but 550 00:29:41,640 --> 00:29:46,280 Speaker 2: we have some here too. Oh and also central Washington 551 00:29:46,360 --> 00:29:49,120 Speaker 2: State where isn't that where they're getting all the flooding 552 00:29:49,160 --> 00:29:52,240 Speaker 2: right now too? The mark that's in the west, well 553 00:29:52,240 --> 00:29:59,440 Speaker 2: this is sort of centralized like like near the mountainous area. Okay, yeah, right, anyway, 554 00:29:59,640 --> 00:30:01,840 Speaker 2: so that that's all happening. Oh, and Reno, Nevada has 555 00:30:01,840 --> 00:30:04,160 Speaker 2: a bunch so all of these different places. Some of 556 00:30:04,200 --> 00:30:07,080 Speaker 2: these places are flushed with water. Water's not an issue. 557 00:30:07,240 --> 00:30:10,000 Speaker 2: You know, if you're in Montana where they've got a 558 00:30:10,000 --> 00:30:12,640 Speaker 2: few data centers, not an issue. Obviously, Washington dealing with 559 00:30:12,640 --> 00:30:14,920 Speaker 2: some flooding right now. Water's not an issue. Portland, Water's 560 00:30:14,960 --> 00:30:18,640 Speaker 2: not really an issue. Power prices though, are an issue. 561 00:30:19,000 --> 00:30:22,320 Speaker 2: And for some places Dallas, Texas, Texas has got some 562 00:30:22,360 --> 00:30:24,959 Speaker 2: water issues, Phoenix has got some water issues. That's going 563 00:30:25,000 --> 00:30:26,960 Speaker 2: to be a concern. And so when you have these 564 00:30:27,280 --> 00:30:29,520 Speaker 2: big companies that are coming forward and they're saying, we'd 565 00:30:29,520 --> 00:30:30,840 Speaker 2: like to build here, we'd like to put it in 566 00:30:30,880 --> 00:30:33,000 Speaker 2: a data center, and they start saying it's going to 567 00:30:33,080 --> 00:30:37,520 Speaker 2: create so many jobs, the truth is it does. It 568 00:30:37,560 --> 00:30:41,080 Speaker 2: creates a lot of jobs for a very short period 569 00:30:41,160 --> 00:30:43,840 Speaker 2: of time. The data centers come in and they create 570 00:30:44,080 --> 00:30:48,600 Speaker 2: a massive number of construction jobs because these warehouses are huge. 571 00:30:49,120 --> 00:30:52,720 Speaker 2: I mean huge. They're like the size of four or 572 00:30:52,760 --> 00:30:55,880 Speaker 2: five walmarts stacked on top of each other or side 573 00:30:55,880 --> 00:30:59,640 Speaker 2: by side. They're massive. But once they're up and running, 574 00:31:00,160 --> 00:31:03,760 Speaker 2: it takes very few people to operate them. So there 575 00:31:03,760 --> 00:31:05,200 Speaker 2: are a lot of people that are saying, wait a minute, 576 00:31:05,240 --> 00:31:08,840 Speaker 2: you're using our resources. You're sucking up all the power, 577 00:31:10,360 --> 00:31:12,880 Speaker 2: you're taking the water, especially in the places that need water, 578 00:31:13,720 --> 00:31:15,120 Speaker 2: and what do we get out of it. You're not 579 00:31:15,280 --> 00:31:18,800 Speaker 2: really doing much for our economy. And so places are 580 00:31:18,800 --> 00:31:22,160 Speaker 2: pushing back against this. And so the supersized data centers 581 00:31:22,600 --> 00:31:25,160 Speaker 2: may transform America. That's if they can get them built. 582 00:31:25,240 --> 00:31:27,120 Speaker 2: Jim Kramer was talking about it. 583 00:31:27,240 --> 00:31:32,000 Speaker 3: Wall Street has concluded that companies involved in artificial intelligence 584 00:31:32,200 --> 00:31:36,480 Speaker 3: are paying too much money to build out the data centers. 585 00:31:37,160 --> 00:31:40,000 Speaker 3: The hundreds of billions of dollars that they're all spending 586 00:31:40,280 --> 00:31:43,160 Speaker 3: has turned off money matters and driven them for other 587 00:31:43,600 --> 00:31:48,760 Speaker 3: companies or even other growth companies from different sectors, including industrials, drugs, 588 00:31:49,080 --> 00:31:51,920 Speaker 3: anything that has nothing to do with data. 589 00:31:52,720 --> 00:31:56,800 Speaker 2: So what does that mean if we're talking about a bubble, right, 590 00:31:56,800 --> 00:31:59,200 Speaker 2: if you've got investors that are going the return is 591 00:31:59,240 --> 00:32:02,040 Speaker 2: not there, it's just you know what, I'd rather put 592 00:32:02,040 --> 00:32:04,360 Speaker 2: my money somewhere else. I'm gonna go put my money 593 00:32:04,440 --> 00:32:06,560 Speaker 2: into Eli Lilly. They've got a new weight loss drug. 594 00:32:06,600 --> 00:32:09,520 Speaker 2: I'm gonna go do that rather than investing in data centers, 595 00:32:10,080 --> 00:32:13,440 Speaker 2: because where's when am I get my money back on that? 596 00:32:14,880 --> 00:32:16,960 Speaker 2: And not only that, but you've You've got a number 597 00:32:16,960 --> 00:32:19,560 Speaker 2: of politicians, including Bertie Bernie Sanders who put out a 598 00:32:19,600 --> 00:32:23,240 Speaker 2: statement and said this moratorium talking about a moratorium on 599 00:32:23,280 --> 00:32:27,360 Speaker 2: the construction of data centers. This moratorium will give democracy 600 00:32:27,360 --> 00:32:31,360 Speaker 2: a chance to catch up with the transformative changes that 601 00:32:31,400 --> 00:32:34,680 Speaker 2: we all witnessing and make sure that the benefits of 602 00:32:34,720 --> 00:32:38,680 Speaker 2: these technologies worked for us, not just the wealthiest people 603 00:32:38,800 --> 00:32:42,960 Speaker 2: on earth. Honestly, his accent is one of the easier 604 00:32:42,960 --> 00:32:44,360 Speaker 2: ones to do. You've been working on that one for 605 00:32:44,400 --> 00:32:47,440 Speaker 2: a while. Yeah, Yeah, when he was running for president 606 00:32:47,440 --> 00:32:48,840 Speaker 2: and I used to pretend I had him in the 607 00:32:48,840 --> 00:32:52,040 Speaker 2: studio and I did a bit called Yo Bernie Raps 608 00:32:52,360 --> 00:32:54,600 Speaker 2: where Bernie would come in and try to connect with 609 00:32:54,640 --> 00:32:57,320 Speaker 2: the younger demographic and just sing rap songs. You are 610 00:32:57,360 --> 00:33:02,160 Speaker 2: a modern phil Henry. It was so bad. That's what 611 00:33:02,200 --> 00:33:04,720 Speaker 2: you have to understand about my impersonations. They're so bad. 612 00:33:04,800 --> 00:33:07,440 Speaker 2: That's why they're humorous. Like, no one's gonna believe that 613 00:33:07,480 --> 00:33:11,200 Speaker 2: it's so terrible. All right, here we go, uh, hostile letters, 614 00:33:11,240 --> 00:33:13,760 Speaker 2: billionaire trust funds, pull outs, and a tungue of war 615 00:33:13,880 --> 00:33:16,320 Speaker 2: making for far more entertainment than anything that you're streaming. 616 00:33:16,360 --> 00:33:19,200 Speaker 2: But the board just told investors which team they don't 617 00:33:19,240 --> 00:33:22,960 Speaker 2: want to bet on. Why this is gonna affect Hollywood? 618 00:33:23,040 --> 00:33:25,160 Speaker 2: Is next? Chris Merril k I am six forty. We 619 00:33:25,240 --> 00:33:27,120 Speaker 2: live everywhere in the iHeartRadio app 620 00:33:28,000 --> 00:33:30,560 Speaker 1: KFI AM six forty on demand