1 00:00:07,320 --> 00:00:13,680 Speaker 1: Good morning. My name is John Justice. Hell yeah, thank you. 2 00:00:13,720 --> 00:00:16,759 Speaker 2: Brett, who's in the master control booth. Brett just asked 3 00:00:16,800 --> 00:00:19,440 Speaker 2: me right before we got on air. He was busy 4 00:00:19,800 --> 00:00:23,480 Speaker 2: compiling the audio. I was doing notes and recording videos 5 00:00:23,520 --> 00:00:29,520 Speaker 2: for Chinese the Spy Wear apps. Brett asses it Freedom Friday. Yet, 6 00:00:29,560 --> 00:00:31,040 Speaker 2: I dude, I'm trying to get there. 7 00:00:31,960 --> 00:00:33,600 Speaker 1: We could start it, that we could set a trend 8 00:00:33,720 --> 00:00:34,479 Speaker 1: I started. 9 00:00:34,600 --> 00:00:38,239 Speaker 2: Now, there's too much stuff going on, vacations coming up, 10 00:00:38,280 --> 00:00:40,640 Speaker 2: I know, I know, and it's dragging. I knew it 11 00:00:40,720 --> 00:00:43,720 Speaker 2: was going to Oh it is, it's just dragging. It's 12 00:00:43,800 --> 00:00:46,159 Speaker 2: just it's only Tuesday, and I'm going to come on already. 13 00:00:46,280 --> 00:00:46,520 Speaker 1: Right. 14 00:00:47,120 --> 00:00:49,360 Speaker 2: No, I have a stack of like freedom, it'll be 15 00:00:49,400 --> 00:00:51,640 Speaker 2: Freedom Thursday stuff if we if we end up getting 16 00:00:51,640 --> 00:00:53,560 Speaker 2: to any of it. But there's so many things going 17 00:00:53,560 --> 00:00:57,520 Speaker 2: on right now that I can't not not talk about it. 18 00:00:57,600 --> 00:00:59,640 Speaker 2: So I'm gonna have to wait. We'll see how quick 19 00:00:59,720 --> 00:01:01,840 Speaker 2: like him through stuff. I do have a really fun 20 00:01:01,880 --> 00:01:04,760 Speaker 2: stack though. It is TWI City's News Talk Am eleven 21 00:01:04,840 --> 00:01:06,680 Speaker 2: thirty and one on three five FM from the six 22 00:01:06,800 --> 00:01:11,000 Speaker 2: five to one Carpet plus Next Day Install Studios. It's Tuesday, 23 00:01:11,040 --> 00:01:12,760 Speaker 2: and I'm glad you're with the show this morning. We 24 00:01:12,800 --> 00:01:15,679 Speaker 2: do have a lot to talk about today. There were 25 00:01:15,840 --> 00:01:20,560 Speaker 2: ice altercations that took place in Minneapolis. You've got elected 26 00:01:20,800 --> 00:01:26,279 Speaker 2: Democrats to the legislature that are actively pushing back against ice, 27 00:01:26,840 --> 00:01:32,360 Speaker 2: helping out the activist organizations in mobilizing in actions against 28 00:01:32,520 --> 00:01:38,399 Speaker 2: ice efforts. At A twenty this morning, I have stats 29 00:01:38,440 --> 00:01:43,520 Speaker 2: that is that are going to completely undermine the Democrats' 30 00:01:43,720 --> 00:01:48,000 Speaker 2: attempts to vilify and demonize Ice. You're gonna have to 31 00:01:48,000 --> 00:01:51,640 Speaker 2: wait for it. It wasn't hard to find, but I 32 00:01:51,720 --> 00:01:53,960 Speaker 2: have stats that I will share coming up at A 33 00:01:54,080 --> 00:01:57,960 Speaker 2: twenty that will undermine all of what the Democrats are 34 00:01:58,000 --> 00:02:01,840 Speaker 2: doing right now in they're push back against Ice. Right 35 00:02:01,920 --> 00:02:06,400 Speaker 2: before that happens, i'll be talking with gubernatorial candidate Lisa Damuth, 36 00:02:06,520 --> 00:02:09,440 Speaker 2: took a second place in the GOP convention drop hole 37 00:02:09,480 --> 00:02:12,520 Speaker 2: over the weekend at seven o'clock this morning. Kendall Qualls, 38 00:02:12,560 --> 00:02:15,440 Speaker 2: who won that straw hoole. He'll be joining us at 39 00:02:15,440 --> 00:02:18,720 Speaker 2: seven o'clock, so we'll talk with both of those gubernatorial 40 00:02:18,760 --> 00:02:21,799 Speaker 2: candidates for Republicans coming up at seven and eight. 41 00:02:21,840 --> 00:02:23,840 Speaker 1: We got to Vive Gartzenstein Ross. 42 00:02:23,919 --> 00:02:28,200 Speaker 2: Later on this hour, talking Ai we'll give you a 43 00:02:28,240 --> 00:02:31,200 Speaker 2: bit of an update on the search for the Brown 44 00:02:31,320 --> 00:02:37,000 Speaker 2: University shooter. I want to start here, though, Trump responding 45 00:02:37,080 --> 00:02:42,880 Speaker 2: to Rob Reiner's murder. So, as we talked about yesterday, 46 00:02:43,280 --> 00:02:47,400 Speaker 2: Rob Reiner, the Hollywood director and producer vocal Trump critic. 47 00:02:47,440 --> 00:02:50,760 Speaker 2: I mentioned this yesterday. I mean, really, when it comes 48 00:02:50,760 --> 00:02:53,080 Speaker 2: to Row, when it comes to Rob Reiner, and this, 49 00:02:53,160 --> 00:02:56,080 Speaker 2: I mean this is these are just facts. If you 50 00:02:56,120 --> 00:03:00,200 Speaker 2: were looking, if you said who in Hollywood suffers the 51 00:03:00,240 --> 00:03:04,440 Speaker 2: worst from Trumps arrangement syndrome, Rob Reiner would have been 52 00:03:04,480 --> 00:03:10,320 Speaker 2: at the top of that list. I would have gone with, Oh, 53 00:03:10,360 --> 00:03:14,720 Speaker 2: who was the Hulk? Mark Ruffalo? Mark Ruffalo, He's up there. 54 00:03:15,280 --> 00:03:16,359 Speaker 2: He's absolutely up there. 55 00:03:16,360 --> 00:03:20,440 Speaker 1: Thank you. I'm happy I could insist. Glad you knew 56 00:03:20,480 --> 00:03:21,560 Speaker 1: my area of expert Tam. 57 00:03:21,600 --> 00:03:22,960 Speaker 2: I'm like, oh, Brett know this. I don't know why 58 00:03:22,960 --> 00:03:26,839 Speaker 2: I'm blanking. I enough coffee this morning. Right that being said, 59 00:03:26,840 --> 00:03:28,839 Speaker 2: it was a horrific murder that took place. His son 60 00:03:28,880 --> 00:03:31,520 Speaker 2: has been arrested in connection with this brutal attack. Now, 61 00:03:31,560 --> 00:03:34,160 Speaker 2: in the wake of this, Trump had gone and posted 62 00:03:34,200 --> 00:03:37,160 Speaker 2: this comment, A very sad thing happened last night. Rob Reiner, 63 00:03:37,560 --> 00:03:41,760 Speaker 2: a tortured and struggling, but once very talented movie director 64 00:03:41,760 --> 00:03:44,680 Speaker 2: and comedy star has passed away with his wife Michelle, 65 00:03:44,880 --> 00:03:48,760 Speaker 2: reportedly due to the anger he caused others through his massive, 66 00:03:48,880 --> 00:03:53,640 Speaker 2: unyielding and incurable affliction with a mind crippling disease known 67 00:03:53,640 --> 00:03:58,320 Speaker 2: as Trump derangement syndrome sometimes referred to as TDS. 68 00:03:58,560 --> 00:04:01,839 Speaker 1: The what's called a Trump derangement problem? Have you heard 69 00:04:01,840 --> 00:04:02,800 Speaker 1: about that problem? 70 00:04:02,880 --> 00:04:05,000 Speaker 2: He was known to have driven people crazy. Trump went 71 00:04:05,040 --> 00:04:10,960 Speaker 2: on to say, by his raging obsession of President Donald Trump, 72 00:04:11,000 --> 00:04:14,320 Speaker 2: with his obvious paranoia reaching new heights as the Trump 73 00:04:14,520 --> 00:04:18,520 Speaker 2: administrations for past goals and expectations of greatness, and with 74 00:04:18,600 --> 00:04:21,440 Speaker 2: the golden age of America upon us perhaps like never before. 75 00:04:21,480 --> 00:04:26,400 Speaker 2: Trump added, may Rob and Michelle rest in peace. Okay, 76 00:04:27,200 --> 00:04:31,440 Speaker 2: So obviously, of no surprise, Democrats have taken massive, massive 77 00:04:31,480 --> 00:04:35,960 Speaker 2: issue with these particular comments. I have an ardent to 78 00:04:36,040 --> 00:04:42,440 Speaker 2: follow the show that emails me, and yesterday sent me 79 00:04:42,480 --> 00:04:45,200 Speaker 2: an email saying tell me John, if Trump actually posted 80 00:04:45,720 --> 00:04:50,320 Speaker 2: this verbal excrement, why GOP leaders should not join Democrats 81 00:04:50,320 --> 00:04:52,480 Speaker 2: in fast tracking his impinchment and. 82 00:04:52,520 --> 00:04:54,160 Speaker 1: Removal from office. 83 00:04:54,960 --> 00:04:57,599 Speaker 2: This is one more symptom of the madman in the 84 00:04:57,640 --> 00:05:03,719 Speaker 2: Oval Office. Look in typical Democrat fashion, people overreach. I 85 00:05:03,720 --> 00:05:07,000 Speaker 2: don't agree with what Trump said. I think there's a 86 00:05:07,000 --> 00:05:10,360 Speaker 2: time and place, but this was not the time or place, 87 00:05:11,000 --> 00:05:13,479 Speaker 2: especially in light. And I'm not the only ones saying this. 88 00:05:13,520 --> 00:05:15,520 Speaker 2: I mean the whole article that I was sharing with 89 00:05:15,560 --> 00:05:19,240 Speaker 2: you from the Daily Wire. It talks about prominent conservatives 90 00:05:19,279 --> 00:05:22,480 Speaker 2: that are pushing back on this. You got Robbie Starbuck, 91 00:05:22,720 --> 00:05:27,240 Speaker 2: you have Ali Beth Stucky included in here. You know, 92 00:05:27,279 --> 00:05:29,880 Speaker 2: the list goes on of individuals on the right who 93 00:05:29,880 --> 00:05:31,720 Speaker 2: are saying, you know, Trump went too far in these 94 00:05:31,720 --> 00:05:35,919 Speaker 2: comments in the wake of what had just taken place 95 00:05:35,960 --> 00:05:40,800 Speaker 2: with the murder of these two individuals. Any nuance of 96 00:05:40,920 --> 00:05:45,039 Speaker 2: difference between the less response to say Charlie Kirk, because 97 00:05:45,040 --> 00:05:48,400 Speaker 2: this is what it's being compared to, and Trump's response 98 00:05:48,440 --> 00:05:51,400 Speaker 2: to Rob Reiner is going to be lost and has 99 00:05:51,440 --> 00:05:55,359 Speaker 2: already been lost. There are big differences here in the 100 00:05:55,400 --> 00:06:00,680 Speaker 2: way that Democrats reacted leftists reacted to the assassination Charlie Kirk, 101 00:06:00,960 --> 00:06:03,360 Speaker 2: and what Trump said here, which again I don't agree with. 102 00:06:03,760 --> 00:06:06,400 Speaker 2: You could have easily just offered up your condolences and 103 00:06:06,440 --> 00:06:09,000 Speaker 2: been on with it. He would not have given He 104 00:06:09,040 --> 00:06:11,360 Speaker 2: would not have been given credit for that. By the way, 105 00:06:11,400 --> 00:06:13,720 Speaker 2: I just want to say that upfront, if Trump had 106 00:06:13,720 --> 00:06:16,080 Speaker 2: gone that direction, you know, it's not like Democrats would 107 00:06:16,080 --> 00:06:19,200 Speaker 2: have been praising Trump for being you know, measured in 108 00:06:19,240 --> 00:06:23,240 Speaker 2: his response to Rob Reiner's death. And again, Trump wasn't 109 00:06:23,279 --> 00:06:27,480 Speaker 2: wrong about his assessment of Reiner. But there's a time 110 00:06:27,680 --> 00:06:31,560 Speaker 2: and a place. I want to add something else to 111 00:06:31,600 --> 00:06:34,839 Speaker 2: this though, that nobody else is talking about. I'm actually 112 00:06:34,880 --> 00:06:39,640 Speaker 2: glad that Trump said these things, not because I think 113 00:06:39,680 --> 00:06:40,480 Speaker 2: they're appropriate. 114 00:06:40,920 --> 00:06:42,080 Speaker 1: I don't think they're very kind. 115 00:06:42,920 --> 00:06:44,880 Speaker 2: But like I said, it doesn't matter what Trump says, 116 00:06:44,920 --> 00:06:48,640 Speaker 2: they're going to come after regardless. Now I'm glad that 117 00:06:48,680 --> 00:06:53,480 Speaker 2: Trump said this because it does provide an opportunity for 118 00:06:53,520 --> 00:06:57,640 Speaker 2: Trump's supporters to show that they don't always agree with Trump, 119 00:06:58,800 --> 00:07:01,839 Speaker 2: which is a constant credit. When I first saw this, 120 00:07:03,320 --> 00:07:05,360 Speaker 2: you know, like a lot of different people, I was like, ah, Trump, 121 00:07:05,400 --> 00:07:06,159 Speaker 2: why'd you go and do that? 122 00:07:06,279 --> 00:07:06,479 Speaker 1: Right? 123 00:07:07,400 --> 00:07:09,080 Speaker 2: This is a this is a bit too far again 124 00:07:09,160 --> 00:07:12,360 Speaker 2: time and a place, and this wasn't the time, the time, 125 00:07:12,440 --> 00:07:15,600 Speaker 2: or the place. And the problem with it is that 126 00:07:16,800 --> 00:07:19,160 Speaker 2: it's not so much that Trump can't handle. It doesn't matter. 127 00:07:19,160 --> 00:07:20,880 Speaker 2: It's not like he's going to be removed from office 128 00:07:20,920 --> 00:07:23,520 Speaker 2: over this. It's not like he hasn't said other things 129 00:07:23,520 --> 00:07:25,280 Speaker 2: that have been over the top. This is not a surprise. 130 00:07:25,360 --> 00:07:27,520 Speaker 2: This is how Trump is. He's just being honest in 131 00:07:27,520 --> 00:07:34,880 Speaker 2: his assessment and in considering how much opposition Rob Reiner 132 00:07:34,920 --> 00:07:37,520 Speaker 2: had put up, how vocal he was against Trump, I'm 133 00:07:37,560 --> 00:07:41,200 Speaker 2: not surprised that Trump reacted this way at all. I 134 00:07:41,200 --> 00:07:43,480 Speaker 2: still think there's a high road that can be taken, 135 00:07:43,800 --> 00:07:46,920 Speaker 2: and my initial reaction was it makes it difficult when 136 00:07:46,960 --> 00:07:52,880 Speaker 2: you get down to a more granular political commentary level, 137 00:07:53,200 --> 00:07:57,040 Speaker 2: putting individuals in a position like myself to sit back 138 00:07:57,080 --> 00:07:59,080 Speaker 2: and have to go and address this in the wake 139 00:08:00,560 --> 00:08:03,280 Speaker 2: of the criticism that was put out over the less 140 00:08:03,360 --> 00:08:06,480 Speaker 2: response to Charlie Kirk. But as I mentioned, I went 141 00:08:06,520 --> 00:08:07,320 Speaker 2: another way on this. 142 00:08:08,240 --> 00:08:08,480 Speaker 1: Again. 143 00:08:08,520 --> 00:08:10,480 Speaker 2: I'm glad that he said it because it does provide 144 00:08:10,480 --> 00:08:13,840 Speaker 2: the opportunity to say, yeah, I don't agree with Trump 145 00:08:13,880 --> 00:08:16,040 Speaker 2: on this. I don't think he should have used those 146 00:08:17,120 --> 00:08:22,400 Speaker 2: those words. Look, Rob Reiner was measured in his response 147 00:08:22,400 --> 00:08:25,840 Speaker 2: when Charlie Kirk was assassinated. I watched the clip yesterday, 148 00:08:25,880 --> 00:08:29,080 Speaker 2: But make no mistake, if either of the attempts on 149 00:08:29,120 --> 00:08:33,520 Speaker 2: Trump's life had been successful. Do you expect that Rob 150 00:08:33,520 --> 00:08:37,160 Speaker 2: Reiner's commentary would have been measured or that on the left. 151 00:08:37,679 --> 00:08:39,719 Speaker 2: And this goes back to my initial take on it. 152 00:08:40,120 --> 00:08:43,240 Speaker 2: There's nuance to all of this, and it's completely lost 153 00:08:43,240 --> 00:08:46,200 Speaker 2: in the less response as they freak out over Trump 154 00:08:46,280 --> 00:08:49,640 Speaker 2: making these comments, which was evident in just one of 155 00:08:49,720 --> 00:08:52,240 Speaker 2: the first emails that I received from a foe of 156 00:08:52,280 --> 00:08:55,920 Speaker 2: the show, saying you need to immediately jump to impeachment. 157 00:08:56,000 --> 00:08:59,920 Speaker 2: Give me a break already. I can always do better, 158 00:09:00,000 --> 00:09:01,160 Speaker 2: and the president can do better. 159 00:09:01,720 --> 00:09:04,360 Speaker 1: This was too far. This will be forgotten about in 160 00:09:04,360 --> 00:09:05,760 Speaker 1: a week, though. I mean make no mistake. 161 00:09:05,800 --> 00:09:07,720 Speaker 2: I even hesitated on whether or not I wanted to 162 00:09:07,720 --> 00:09:11,520 Speaker 2: talk about it this morning on the show, but it 163 00:09:11,600 --> 00:09:14,400 Speaker 2: is something that is making the rounds, and so I 164 00:09:14,440 --> 00:09:16,880 Speaker 2: wanted to make sure that my opinion was known on 165 00:09:16,960 --> 00:09:19,719 Speaker 2: that particular issue. All right, coming up before we talk 166 00:09:19,760 --> 00:09:22,840 Speaker 2: with Devite Gartenstein Ross, any questions you have related to 167 00:09:22,920 --> 00:09:25,360 Speaker 2: our official intelligence, you can get those in on the 168 00:09:25,400 --> 00:09:28,800 Speaker 2: iHeartRadio app. I have exciting news to share about Katie Pavlich. 169 00:09:28,880 --> 00:09:32,760 Speaker 2: She's got a brand new gig. Found out about that yesterday, 170 00:09:32,800 --> 00:09:34,960 Speaker 2: had a chance to chat with her a bit. I 171 00:09:35,040 --> 00:09:38,640 Speaker 2: will share with you what Katie Pavlich and her new 172 00:09:38,880 --> 00:09:43,440 Speaker 2: gig is and was il Hanna Omar's son pulled over 173 00:09:43,640 --> 00:09:45,719 Speaker 2: by Ice as she claims. 174 00:09:46,480 --> 00:09:48,079 Speaker 1: I'll give you the details. 175 00:09:47,640 --> 00:09:50,439 Speaker 2: Next here on Twinsday's News Talk AM eleven thirty and 176 00:09:50,480 --> 00:09:51,600 Speaker 2: one O three five FM. 177 00:09:51,640 --> 00:09:53,280 Speaker 3: Good morning, and I love your show. 178 00:10:02,320 --> 00:10:06,640 Speaker 4: Good morning John, Happy Tuesday. There's no great surprise on 179 00:10:06,720 --> 00:10:11,880 Speaker 4: this thing that the DFL legislators are helping the activists 180 00:10:11,920 --> 00:10:15,400 Speaker 4: thought in the lamestream media and calling here. 181 00:10:15,280 --> 00:10:16,080 Speaker 1: Are throwing it. 182 00:10:16,080 --> 00:10:20,000 Speaker 4: It's all distraction from what's going on with the fraud, 183 00:10:20,320 --> 00:10:22,560 Speaker 4: the property taxes and such. 184 00:10:23,040 --> 00:10:23,920 Speaker 1: They need something. 185 00:10:24,040 --> 00:10:24,360 Speaker 3: Oh, one. 186 00:10:25,920 --> 00:10:31,319 Speaker 1: Hundred percent, thank you, Lou. I completely agree. A twenty 187 00:10:31,400 --> 00:10:34,320 Speaker 1: this morning, I have stats to wow and amaze your 188 00:10:34,400 --> 00:10:39,080 Speaker 1: liberal friends with I gave. I gave Brett the preview 189 00:10:39,120 --> 00:10:41,920 Speaker 1: a moment ago. It's good. Yeah, I thought though they were. 190 00:10:42,040 --> 00:10:45,160 Speaker 2: They were easy to find, but they will certainly help 191 00:10:45,200 --> 00:10:47,360 Speaker 2: you in pushing back against your liberal friends who are 192 00:10:47,440 --> 00:10:49,240 Speaker 2: upset at at Ice. 193 00:10:49,400 --> 00:10:53,319 Speaker 1: So again that's coming up this morning at eight eight twenty. 194 00:10:53,600 --> 00:10:54,520 Speaker 1: So yesterday I. 195 00:10:54,559 --> 00:10:58,760 Speaker 2: Found out that Katie Pavlich is now the new prime 196 00:10:58,920 --> 00:11:07,240 Speaker 2: time ten block host on Newsmax. Yeah, congratulations to Katie 197 00:11:07,280 --> 00:11:10,040 Speaker 2: on this this is here. She will be leaving Fox News, 198 00:11:10,120 --> 00:11:12,560 Speaker 2: but she is now going to be the primetime host 199 00:11:12,880 --> 00:11:15,559 Speaker 2: Monday through Friday on News Nation at ten pm, so 200 00:11:15,640 --> 00:11:18,920 Speaker 2: that'll be nine o'clock our time. And I absolutely could 201 00:11:18,960 --> 00:11:22,000 Speaker 2: not be I could not be happier for my friend. 202 00:11:22,160 --> 00:11:25,160 Speaker 2: I think that's absolutely that's awesome for her. I know 203 00:11:25,280 --> 00:11:27,719 Speaker 2: this something that she's wanted for a long time, and 204 00:11:27,800 --> 00:11:32,840 Speaker 2: this is an amazing opportunity. She continues to grow as 205 00:11:33,160 --> 00:11:37,079 Speaker 2: a commentator. So congratulations to Katie Bavlach on that. Not 206 00:11:37,120 --> 00:11:38,800 Speaker 2: sure when she starts, though, It's funny. I was talking 207 00:11:38,840 --> 00:11:40,640 Speaker 2: with her yesterday and I didn't ask when she starts. 208 00:11:40,840 --> 00:11:42,920 Speaker 2: I imagine this after the first of the year. But 209 00:11:42,920 --> 00:11:44,480 Speaker 2: I'll try to get that information and share it with 210 00:11:44,520 --> 00:11:48,520 Speaker 2: you here. In a bit speaking of Newsmax, ice officials 211 00:11:48,600 --> 00:11:53,240 Speaker 2: tell Newsmax James Rosen that they have no record of 212 00:11:53,360 --> 00:11:57,560 Speaker 2: stopping a car driven by the sun of Ilhana Omar, 213 00:11:57,840 --> 00:12:04,040 Speaker 2: as the congress woman claimed, went on to the crowd, Yeah, 214 00:12:04,040 --> 00:12:07,640 Speaker 2: I actually can believe this. Ilhan's pulling the walls on this. 215 00:12:09,240 --> 00:12:13,160 Speaker 2: So Acting Director Lyons called the charge a ridiculous effort 216 00:12:13,200 --> 00:12:17,199 Speaker 2: to unfairly demonize our law enforcement officers. And I say 217 00:12:17,240 --> 00:12:21,400 Speaker 2: that Ilhan is pulling a Walls because Walls recently complained 218 00:12:21,480 --> 00:12:25,199 Speaker 2: a couple of weeks back about drive by our word 219 00:12:25,559 --> 00:12:29,839 Speaker 2: slurs past the governor's mansion while he was gambling with 220 00:12:30,000 --> 00:12:32,440 Speaker 2: his nieces and nephews playing yachtzi. 221 00:12:33,640 --> 00:12:35,880 Speaker 1: Then when he went to Seattle. 222 00:12:37,920 --> 00:12:42,440 Speaker 2: For a governor's event fundraiser, he changed it to drive 223 00:12:42,600 --> 00:12:48,000 Speaker 2: by posts by Trump and abandoned the idea that anybody 224 00:12:48,160 --> 00:12:51,880 Speaker 2: was saying this outside of the governor's mansion. And what's 225 00:12:51,920 --> 00:12:56,000 Speaker 2: even funnier is that Walls, during his fraud Prevention program 226 00:12:56,120 --> 00:12:59,240 Speaker 2: press conference last week, didn't mention the dozens of people 227 00:12:59,280 --> 00:13:02,440 Speaker 2: who have now actually driven by and filmed themselves as 228 00:13:02,480 --> 00:13:03,120 Speaker 2: saying the R word. 229 00:13:03,160 --> 00:13:03,920 Speaker 1: People shouldn't do that. 230 00:13:04,000 --> 00:13:05,360 Speaker 5: By the way, I just want to point that out. 231 00:13:07,360 --> 00:13:09,800 Speaker 2: The moment I saw this story from Ilhan Omar, without 232 00:13:09,840 --> 00:13:12,840 Speaker 2: the context of why the stop took place, I assumed 233 00:13:12,880 --> 00:13:17,199 Speaker 2: it was bogus. There's dozens of reasons why Ilhan Omar's 234 00:13:17,240 --> 00:13:19,599 Speaker 2: son could have been pulled over that have nothing to 235 00:13:19,679 --> 00:13:24,520 Speaker 2: do with him being Ilhan's son or his skin color. 236 00:13:24,640 --> 00:13:27,439 Speaker 2: And as mentioned here, I says, yeah, there was We 237 00:13:27,559 --> 00:13:28,439 Speaker 2: did not stop. 238 00:13:29,040 --> 00:13:31,240 Speaker 1: We have no record of that whatsoever. 239 00:13:32,920 --> 00:13:34,800 Speaker 2: All Right, one more quick one here before we talk 240 00:13:34,960 --> 00:13:38,560 Speaker 2: with Davide Cartanstein. Ross authorities have released new images. They're 241 00:13:38,600 --> 00:13:41,959 Speaker 2: not helpful of the suspect related to the mass shooting 242 00:13:42,000 --> 00:13:44,920 Speaker 2: of Brown University, offering a fifty thousand dollars bounty. The 243 00:13:45,000 --> 00:13:48,960 Speaker 2: gunmen on Saturday stormed into a classroom in Brown's Engineering 244 00:13:49,000 --> 00:13:52,040 Speaker 2: department and killed two students, Ella Cook, who was a 245 00:13:52,080 --> 00:13:57,439 Speaker 2: prominent member of the Brown University Republican Club club, and 246 00:13:58,480 --> 00:14:01,400 Speaker 2: Mukhammad Aziz Irma Zokhoff. 247 00:14:01,760 --> 00:14:02,080 Speaker 1: Cook. 248 00:14:02,480 --> 00:14:06,120 Speaker 2: Cook was from Alabama, served again as the vice president 249 00:14:06,160 --> 00:14:10,319 Speaker 2: of the university's Republican Club, and Irma Zukhoff was and 250 00:14:10,800 --> 00:14:14,040 Speaker 2: Who's Beck national in his first year at the school. 251 00:14:14,480 --> 00:14:19,840 Speaker 2: Political commentator Mark Albrin had this to say regarding the 252 00:14:19,920 --> 00:14:24,040 Speaker 2: potential motivation for the shooting. Here's a little bit of 253 00:14:24,080 --> 00:14:26,320 Speaker 2: what Mark Alprin had to say on his YouTube show. 254 00:14:26,440 --> 00:14:31,640 Speaker 6: Are telling me that the family of I just need 255 00:14:31,680 --> 00:14:34,120 Speaker 6: to look up her name, Ella Cook. I think, thank you, Mark, 256 00:14:34,200 --> 00:14:36,560 Speaker 6: thank you, thank you that the family of Ella Cook 257 00:14:36,640 --> 00:14:40,320 Speaker 6: the Alabama a young woman who was a sophomore, has 258 00:14:40,400 --> 00:14:42,800 Speaker 6: been told that she was the target of what happened 259 00:14:42,840 --> 00:14:46,400 Speaker 6: to Brian, I have no idea whether that's true. There's 260 00:14:46,480 --> 00:14:48,760 Speaker 6: other theories about why the person did what they did, 261 00:14:48,840 --> 00:14:51,000 Speaker 6: but now that we don't know who the assailing is, 262 00:14:51,080 --> 00:14:53,600 Speaker 6: it's going to be harder to say. But if it's 263 00:14:53,680 --> 00:14:56,200 Speaker 6: true that she was targeted, that's a big story because 264 00:14:56,200 --> 00:14:59,280 Speaker 6: she was one of the most visible conservatives on that campus. 265 00:14:59,480 --> 00:15:02,160 Speaker 6: Don't know that it's true, but probably most of you 266 00:15:02,240 --> 00:15:05,640 Speaker 6: don't even know that that's being alleged because you'd have 267 00:15:05,720 --> 00:15:09,120 Speaker 6: to follow certain accounts on acts or have sources as 268 00:15:09,160 --> 00:15:10,240 Speaker 6: I do, who are telling. 269 00:15:10,080 --> 00:15:14,640 Speaker 2: Me that, yeah, it'll be I'm you know, listen, I'm 270 00:15:14,680 --> 00:15:16,840 Speaker 2: confident they're going to catch this individual, and surprise they 271 00:15:16,880 --> 00:15:18,040 Speaker 2: haven't already. 272 00:15:18,200 --> 00:15:19,600 Speaker 1: These things take time. 273 00:15:19,720 --> 00:15:22,680 Speaker 2: The images that they put out certainly have not been helpful, 274 00:15:23,320 --> 00:15:26,360 Speaker 2: and it will be interesting to see if these rumors 275 00:15:26,480 --> 00:15:30,240 Speaker 2: of this being a targeted attack, especially relating to this 276 00:15:30,360 --> 00:15:33,400 Speaker 2: young woman who lost her life in the attack, turn 277 00:15:33,480 --> 00:15:37,440 Speaker 2: out to be true. All right, coming up one more 278 00:15:37,520 --> 00:15:39,680 Speaker 2: time for twenty twenty five, we're going to talk with 279 00:15:39,840 --> 00:15:43,520 Speaker 2: our artificial intelligence expert, David Gartenstein. 280 00:15:44,000 --> 00:15:45,720 Speaker 1: Ross got a number of different issues. 281 00:15:45,480 --> 00:15:47,880 Speaker 2: We will discuss with David, and of course, your questions 282 00:15:47,920 --> 00:15:50,440 Speaker 2: any questions that you have for David regarding AI on 283 00:15:50,600 --> 00:15:54,200 Speaker 2: any level. Get those talkbacks into the iHeartRadio apples are 284 00:15:54,200 --> 00:15:56,400 Speaker 2: brought to you by Lindahl Realty. I see a few 285 00:15:56,440 --> 00:15:58,200 Speaker 2: of those already, and we will get to those coming 286 00:15:58,280 --> 00:16:00,640 Speaker 2: up next right here on Twin City News Talk Am 287 00:16:00,680 --> 00:16:02,360 Speaker 2: eleven thirty and one oh three five FM. 288 00:16:14,160 --> 00:16:14,880 Speaker 1: Now, if my. 289 00:16:16,800 --> 00:16:22,760 Speaker 2: Math is correct, I think that David Gartenstein Ross is 290 00:16:24,800 --> 00:16:31,480 Speaker 2: the second most consistent guest that I've had on with 291 00:16:31,720 --> 00:16:35,000 Speaker 2: me over my time being a talk radio show host. 292 00:16:35,920 --> 00:16:38,920 Speaker 2: He might actually be number one compared to Andrew Langer. 293 00:16:38,920 --> 00:16:40,640 Speaker 2: It's Twin Cities News Talk from the sixty five to 294 00:16:40,680 --> 00:16:44,680 Speaker 2: one carpet plus Next Day Install Studios. My name is 295 00:16:44,760 --> 00:16:49,840 Speaker 2: John Justice and CEO AI Analyst, CEO of Expert Theory 296 00:16:49,880 --> 00:16:52,400 Speaker 2: d VD. Garten Steinross joins this this morning. David, do 297 00:16:52,480 --> 00:16:55,840 Speaker 2: you happen to recall what year you and I started talking? 298 00:16:58,160 --> 00:17:00,840 Speaker 5: Great question, it's either I think it's two thousand and 299 00:17:00,880 --> 00:17:01,520 Speaker 5: eight if I recall. 300 00:17:01,800 --> 00:17:05,240 Speaker 2: Okay, you might be my longest running weekly guest for 301 00:17:05,359 --> 00:17:09,679 Speaker 2: the Off and On, but much appreciated your expertise has 302 00:17:09,720 --> 00:17:12,240 Speaker 2: always and happy holidays to you. Thank you so much 303 00:17:12,280 --> 00:17:15,800 Speaker 2: for joining us once again one more time for twenty 304 00:17:15,880 --> 00:17:16,280 Speaker 2: twenty five. 305 00:17:16,320 --> 00:17:17,840 Speaker 1: These have been really fun on conversations. 306 00:17:18,200 --> 00:17:19,800 Speaker 5: Thanks so much, John, Merry Christmas to you. 307 00:17:20,440 --> 00:17:22,320 Speaker 2: I want to go to a talk back here just briefly. 308 00:17:23,200 --> 00:17:24,880 Speaker 2: We didn't discuss this ahead of time, but I'm sure 309 00:17:24,880 --> 00:17:26,600 Speaker 2: you can handle it. I was talking a moment ago 310 00:17:26,760 --> 00:17:30,479 Speaker 2: about the search for the Brown University a suspect currently 311 00:17:30,880 --> 00:17:35,320 Speaker 2: and the lack of good available footage from around the vicinity. 312 00:17:35,440 --> 00:17:38,840 Speaker 2: This talkback came in Regarding that. 313 00:17:40,600 --> 00:17:44,359 Speaker 7: John, I think it's very strange that they have no 314 00:17:44,560 --> 00:17:46,760 Speaker 7: other videos or pictures of this guy. 315 00:17:47,520 --> 00:17:48,439 Speaker 6: Considering if you. 316 00:17:48,520 --> 00:17:53,200 Speaker 5: Go back to twenty twenty one, there were reports saying 317 00:17:53,440 --> 00:17:58,480 Speaker 5: how safe Brown University is. A mister Baling on that campus. 318 00:17:59,200 --> 00:18:04,200 Speaker 4: Actually, you've got people's personal space and their freedom. 319 00:18:05,920 --> 00:18:07,120 Speaker 1: I think it's a little weird. 320 00:18:07,480 --> 00:18:09,000 Speaker 5: They don't know who it is. 321 00:18:09,480 --> 00:18:12,680 Speaker 2: You know, David, without knowing the specifics of what the 322 00:18:12,720 --> 00:18:16,800 Speaker 2: surveillance in that area looks like. I just thought it 323 00:18:16,880 --> 00:18:20,440 Speaker 2: was interesting from the skepticism standpoint and the way that 324 00:18:20,480 --> 00:18:24,920 Speaker 2: people are just so one skeptical of news reports as 325 00:18:25,000 --> 00:18:28,159 Speaker 2: always depending on the politics of it, but also this 326 00:18:28,320 --> 00:18:32,320 Speaker 2: other expectation that people just assume that we're being watched 327 00:18:32,480 --> 00:18:35,000 Speaker 2: all the time and footage is readily available. I know 328 00:18:35,080 --> 00:18:38,240 Speaker 2: that I feel that way, but given your background in 329 00:18:38,800 --> 00:18:41,080 Speaker 2: you know, analyzing of terrorist threats, I would be kind 330 00:18:41,080 --> 00:18:43,000 Speaker 2: of curious if you had any additional thoughts on what 331 00:18:43,119 --> 00:18:44,040 Speaker 2: the talk back said. 332 00:18:45,000 --> 00:18:50,360 Speaker 5: It's an interesting point, and I don't know what he's 333 00:18:50,400 --> 00:18:53,720 Speaker 5: referring to in terms of the twenty twenty one footage 334 00:18:53,960 --> 00:18:57,360 Speaker 5: on Brown University being safe because there was a lot 335 00:18:57,400 --> 00:19:01,399 Speaker 5: of your surveillance or video on campus. I'm not doubting it. 336 00:19:01,480 --> 00:19:03,600 Speaker 5: I just don't know the specifics. It would be helpful 337 00:19:04,040 --> 00:19:07,880 Speaker 5: to take a look, and my quick Google search didn't 338 00:19:07,920 --> 00:19:11,200 Speaker 5: turn it up, but at any rate, you know, it'll 339 00:19:12,040 --> 00:19:14,920 Speaker 5: I agree with you about how we have this sort 340 00:19:14,960 --> 00:19:19,399 Speaker 5: of expectation that parts of our lives are just going 341 00:19:19,440 --> 00:19:22,800 Speaker 5: to be available. Especially I think we have this assumption 342 00:19:23,680 --> 00:19:28,720 Speaker 5: that if an incident occurs like now, that people will 343 00:19:28,720 --> 00:19:30,840 Speaker 5: be able to go back for the next few hours 344 00:19:31,520 --> 00:19:34,479 Speaker 5: and put a lot splice a lot of video together. 345 00:19:35,119 --> 00:19:38,639 Speaker 5: And usually that's the case. You know, if someone drives 346 00:19:38,760 --> 00:19:43,800 Speaker 5: through a number of shopping centers as it stops at 347 00:19:43,800 --> 00:19:46,720 Speaker 5: the convenience store, then goes to a location and carries 348 00:19:46,760 --> 00:19:51,119 Speaker 5: out a shooting, usually you can find streetcam footage, you know, 349 00:19:51,200 --> 00:19:54,040 Speaker 5: footage from maybe a security cam at the shopping center. 350 00:19:54,880 --> 00:19:57,200 Speaker 5: You if you have a sense of who it is, 351 00:19:57,960 --> 00:20:01,920 Speaker 5: you'll geolocate the phone. If you don't know who it is, 352 00:20:02,119 --> 00:20:05,760 Speaker 5: you'll look at phones that where you can geo locate 353 00:20:05,880 --> 00:20:09,200 Speaker 5: through that particular area. So there's a lot of ways 354 00:20:09,280 --> 00:20:13,399 Speaker 5: to get at somebody. What it seems like based on 355 00:20:13,480 --> 00:20:15,280 Speaker 5: what I can tell, and we don't know the answer, 356 00:20:15,840 --> 00:20:20,280 Speaker 5: but it seems like the shooter used operational security or 357 00:20:20,359 --> 00:20:23,680 Speaker 5: OPSEC in a number of different ways, including concealment of 358 00:20:23,760 --> 00:20:26,440 Speaker 5: the face. Right, we have a sense we have some 359 00:20:26,560 --> 00:20:29,320 Speaker 5: video of the shooter, but we don't have any video 360 00:20:29,440 --> 00:20:32,199 Speaker 5: that provides us a sense of the shooter's face. Almost 361 00:20:32,240 --> 00:20:35,600 Speaker 5: certainly the shooter didn't have a cell phone on them, 362 00:20:36,160 --> 00:20:37,879 Speaker 5: or if so, it was a burger phone that they 363 00:20:37,920 --> 00:20:40,200 Speaker 5: couldn't be traced with. There's a number of things that 364 00:20:40,280 --> 00:20:42,680 Speaker 5: they seem to have done, right. But you know, even 365 00:20:42,720 --> 00:20:48,119 Speaker 5: going back to a number of more recent attacks, we 366 00:20:48,160 --> 00:20:50,040 Speaker 5: can actually see how long it can take to track 367 00:20:50,119 --> 00:20:54,080 Speaker 5: someone down. You know, after the assassination of Charlie Kirk, 368 00:20:54,160 --> 00:20:58,320 Speaker 5: it took several days to pinpoint Tyler Robinson and it 369 00:20:58,480 --> 00:21:01,120 Speaker 5: was really like the discovery of his is Ammo Cachet 370 00:21:01,560 --> 00:21:03,320 Speaker 5: that seemed to have been the breakthrough in that case. 371 00:21:03,359 --> 00:21:07,119 Speaker 5: If you go back fifteen years to the Boston Marathon bombing, 372 00:21:07,680 --> 00:21:10,560 Speaker 5: when that happened, it took several days with the area 373 00:21:10,640 --> 00:21:16,000 Speaker 5: on lockdown to locate the perpetrators. So I'm also interested 374 00:21:16,240 --> 00:21:18,119 Speaker 5: in why we don't have more on the shooter, But 375 00:21:18,240 --> 00:21:20,440 Speaker 5: I do want to point out that it's not this 376 00:21:20,680 --> 00:21:23,400 Speaker 5: big abnormality compared to other attacks that we've seen. 377 00:21:23,640 --> 00:21:26,480 Speaker 2: Well in Devin, I think that it's worth noting that 378 00:21:27,480 --> 00:21:33,480 Speaker 2: this shooting coming within the hours of this horrific shooting 379 00:21:33,560 --> 00:21:37,080 Speaker 2: that took place, this horrific terrorist attack that took place 380 00:21:37,160 --> 00:21:40,440 Speaker 2: in Australia. On a subconscious level, I think there's a 381 00:21:40,520 --> 00:21:45,800 Speaker 2: juxtaposition between here you have this alleged father and son 382 00:21:45,880 --> 00:21:48,720 Speaker 2: that are going out and committing this heinous act on 383 00:21:48,800 --> 00:21:52,240 Speaker 2: this on Bondi Beach. There's video footage of the individuals 384 00:21:52,280 --> 00:21:55,480 Speaker 2: being being taken down, and then you juxtaposed that next 385 00:21:55,520 --> 00:21:57,800 Speaker 2: to what happened to Brown University and a lack of 386 00:21:57,920 --> 00:22:00,480 Speaker 2: being able to find out who this individual is, and 387 00:22:00,880 --> 00:22:03,040 Speaker 2: you know, either on a subconscious or even conscious level, 388 00:22:03,040 --> 00:22:04,879 Speaker 2: I think that that ends up conflicting in a lot 389 00:22:04,880 --> 00:22:05,520 Speaker 2: of people's minds. 390 00:22:05,560 --> 00:22:08,840 Speaker 5: To be let's address that on a conscious level. There's 391 00:22:08,920 --> 00:22:12,280 Speaker 5: just a fundamental difference between the two. The first one 392 00:22:12,359 --> 00:22:15,040 Speaker 5: is that in the Bondi Beach terrorist attack, the two 393 00:22:15,119 --> 00:22:17,720 Speaker 5: attackers were you know, one of them was killed, the 394 00:22:17,800 --> 00:22:20,680 Speaker 5: other one was apprehended, which makes it really easy to 395 00:22:20,800 --> 00:22:23,240 Speaker 5: know who they were. The second thing is that the 396 00:22:23,320 --> 00:22:27,760 Speaker 5: Bondi Beach attack there were you know, thousands of people 397 00:22:27,960 --> 00:22:31,600 Speaker 5: there for the Menora lighting for Hanukkah, whereas here you 398 00:22:31,720 --> 00:22:35,040 Speaker 5: had a much smaller group in a classroom. The third 399 00:22:35,160 --> 00:22:37,880 Speaker 5: difference is the Bondi Beach attack went on for about 400 00:22:37,960 --> 00:22:41,479 Speaker 5: ten minutes or they were shooting for an extended period, 401 00:22:42,000 --> 00:22:44,359 Speaker 5: whereas here it was you know, a shooter. A shooter 402 00:22:44,440 --> 00:22:48,439 Speaker 5: came into a classroom, carried out the attack, and then left. 403 00:22:48,920 --> 00:22:52,399 Speaker 5: So I think that there are fundamental differences that just 404 00:22:52,880 --> 00:22:58,280 Speaker 5: explain that surface level just juxtaposition between Brown and Bondy. 405 00:22:59,440 --> 00:23:01,720 Speaker 2: I want to make one side comment and then we'll 406 00:23:01,720 --> 00:23:04,639 Speaker 2: get into some AI talk. I do have some talkbacks 407 00:23:04,640 --> 00:23:06,320 Speaker 2: that I've already rolled in, so we'll see how much 408 00:23:06,359 --> 00:23:10,280 Speaker 2: that ends up dominating the conversation. Earlier I made an 409 00:23:10,280 --> 00:23:13,840 Speaker 2: announcement of another longtime guest on the show and a 410 00:23:14,000 --> 00:23:16,800 Speaker 2: friend of mine, a friend of ours, Katie Pavlich, announced 411 00:23:16,960 --> 00:23:20,440 Speaker 2: her new gig, this is on News Nation. I had 412 00:23:20,760 --> 00:23:24,119 Speaker 2: covered a Newsmax article right after I I made the 413 00:23:24,160 --> 00:23:25,920 Speaker 2: announcement of Katie's news show. 414 00:23:26,160 --> 00:23:27,880 Speaker 1: Katie will be joining News Nation. 415 00:23:28,240 --> 00:23:32,880 Speaker 2: Early next year in the prime time ten o'clock eastern 416 00:23:33,080 --> 00:23:36,000 Speaker 2: nine o'clock Central slot on a News Nation. So I 417 00:23:36,040 --> 00:23:39,000 Speaker 2: wanted to go ahead and offer up that clarification. Some 418 00:23:39,040 --> 00:23:40,600 Speaker 2: people were confused whether or not she was going the 419 00:23:40,640 --> 00:23:43,639 Speaker 2: news Max or news news Nation. But we're incredibly happy 420 00:23:43,720 --> 00:23:46,840 Speaker 2: for Katie. All right, let's get in go ahead. 421 00:23:46,840 --> 00:23:48,480 Speaker 5: Can I say good for Katie? Yeah? 422 00:23:48,480 --> 00:23:49,000 Speaker 1: Absolutely. 423 00:23:49,359 --> 00:23:51,480 Speaker 5: I think she is wonderful and like I've always had 424 00:23:51,520 --> 00:23:53,919 Speaker 5: this bond with her because of you, John. I got 425 00:23:53,960 --> 00:23:55,639 Speaker 5: to meet her when she was U of a Katie 426 00:23:55,800 --> 00:24:01,560 Speaker 5: yep back in back at Tucson, and I've been really 427 00:24:01,600 --> 00:24:03,040 Speaker 5: proud to see where she's gone since then. 428 00:24:03,400 --> 00:24:06,880 Speaker 2: Well, the relationships, I'm incredibly plot proud of the relationships 429 00:24:06,920 --> 00:24:08,280 Speaker 2: that I've forged. 430 00:24:08,200 --> 00:24:10,879 Speaker 1: Especially with the trio that I've discussed. You, Katie and. 431 00:24:11,200 --> 00:24:13,680 Speaker 2: Andrew Langer, you all kind of what we kind of 432 00:24:13,720 --> 00:24:15,679 Speaker 2: all found each other. I found you guys right at 433 00:24:15,720 --> 00:24:18,520 Speaker 2: the start of that portion of my talk radio career, 434 00:24:18,560 --> 00:24:21,440 Speaker 2: and I'm I feel incredibly blessed to still be able 435 00:24:21,480 --> 00:24:23,200 Speaker 2: to be speaking with you guys and to call you friends. 436 00:24:23,720 --> 00:24:24,240 Speaker 1: Let's get to you. 437 00:24:24,760 --> 00:24:27,200 Speaker 2: Let's get to some top action from the iHeartRadio app. 438 00:24:27,280 --> 00:24:29,600 Speaker 2: Questions for devid regarding AI will start here. 439 00:24:31,080 --> 00:24:34,720 Speaker 3: I got a question for the thieves, you know, as 440 00:24:34,840 --> 00:24:38,680 Speaker 3: we start to rely more more heavenly on AI and 441 00:24:38,840 --> 00:24:44,080 Speaker 3: AI function abilities, I always wandering, We're gonna lose our 442 00:24:44,160 --> 00:24:48,160 Speaker 3: ability to critical think and it's gonna happen real quick. 443 00:24:48,840 --> 00:24:51,280 Speaker 3: I'm already getting stuck behind people like this on. 444 00:24:51,400 --> 00:24:55,720 Speaker 1: The freeway every day. Come thanks for yourself, guys, what 445 00:24:55,840 --> 00:24:56,840 Speaker 1: do you think about day? 446 00:24:57,040 --> 00:24:58,440 Speaker 2: I don't know if one has anything to do with 447 00:24:58,560 --> 00:25:01,760 Speaker 2: the other, but on his first point of critical thinking 448 00:25:01,880 --> 00:25:03,840 Speaker 2: in the wake of AI, what are your thoughts to be? 449 00:25:05,440 --> 00:25:10,560 Speaker 5: I think it's true and it's not people tend to 450 00:25:11,800 --> 00:25:17,200 Speaker 5: misused technology and lose old skills and old ways of 451 00:25:18,000 --> 00:25:20,840 Speaker 5: you know, old ways of knowledge. And we can look 452 00:25:20,880 --> 00:25:25,720 Speaker 5: at this and any number of aspects of society and 453 00:25:25,800 --> 00:25:26,920 Speaker 5: what people are expected to do. 454 00:25:27,680 --> 00:25:27,760 Speaker 7: Right. 455 00:25:27,760 --> 00:25:30,480 Speaker 5: It used to be that people were expected to be 456 00:25:30,520 --> 00:25:33,240 Speaker 5: able to figure out a car and make you know, 457 00:25:33,320 --> 00:25:35,920 Speaker 5: basic repairs to their own car. And now we don't 458 00:25:35,960 --> 00:25:38,399 Speaker 5: expect anybody to do that. But that's the part because 459 00:25:38,480 --> 00:25:44,480 Speaker 5: cars have become you know, basically computers. A lot of 460 00:25:44,800 --> 00:25:49,800 Speaker 5: the skill set that people need today is how to 461 00:25:50,320 --> 00:25:54,160 Speaker 5: think critically in a world of AI. And I think 462 00:25:54,240 --> 00:25:56,080 Speaker 5: that the listener is right that a lot of people 463 00:25:56,119 --> 00:25:59,399 Speaker 5: will use will lose the plot and will be so 464 00:25:59,640 --> 00:26:02,919 Speaker 5: reliable and on a computer thinking for them that they 465 00:26:03,080 --> 00:26:07,240 Speaker 5: lose the ability to basically think things through. And we 466 00:26:07,280 --> 00:26:09,040 Speaker 5: can see lots of examples of that already. 467 00:26:09,760 --> 00:26:12,000 Speaker 1: Let's go here to a friend of the show, Rick. 468 00:26:13,560 --> 00:26:15,640 Speaker 1: Good morning to VI. This is Rick and Woodberry. 469 00:26:15,880 --> 00:26:19,720 Speaker 8: Could you please speak to how AI companies like open 470 00:26:19,800 --> 00:26:24,200 Speaker 8: a I expect to be profitable on subscription fees or 471 00:26:24,240 --> 00:26:29,480 Speaker 8: advertising revenue without constant injections venture capital given all the 472 00:26:29,840 --> 00:26:32,480 Speaker 8: massive amount of infrastructure they have to invest in and 473 00:26:32,600 --> 00:26:35,320 Speaker 8: the maintenance associated with it. 474 00:26:35,600 --> 00:26:37,560 Speaker 1: Thank you, David Gartenstein Ros. 475 00:26:37,960 --> 00:26:41,359 Speaker 5: It's a great question from Rick. I think the basic 476 00:26:41,480 --> 00:26:46,159 Speaker 5: answer is that they're still in a research phase and 477 00:26:46,440 --> 00:26:49,919 Speaker 5: are going to productize further beyond what they have now. 478 00:26:51,200 --> 00:26:54,240 Speaker 5: So what we're seeing in terms of subscriptions, individual level 479 00:26:54,280 --> 00:26:57,639 Speaker 5: subscriptions from say open to AI. That's in part to 480 00:26:57,720 --> 00:27:03,119 Speaker 5: speed adoption of their technology. It's not the primary revenue model, 481 00:27:03,200 --> 00:27:06,280 Speaker 5: though it is a revenue model. So number one with 482 00:27:06,359 --> 00:27:09,480 Speaker 5: respect to the subscriptions, their expectation we actually already see 483 00:27:09,520 --> 00:27:14,080 Speaker 5: this happening, is that the cost of AI is going 484 00:27:14,160 --> 00:27:17,880 Speaker 5: to decline, meaning it's going to take less energy, less water, 485 00:27:18,520 --> 00:27:21,359 Speaker 5: less basing data centers. And this is consistent with what 486 00:27:21,440 --> 00:27:26,040 Speaker 5: we've seen in terms of More's law and the increased 487 00:27:26,480 --> 00:27:30,439 Speaker 5: computing power that we get from microprocessors, and just in general, 488 00:27:30,520 --> 00:27:33,639 Speaker 5: we can see that the energy cost of a single 489 00:27:33,720 --> 00:27:38,320 Speaker 5: AI search has actually dropped exponentially since the launch of 490 00:27:38,720 --> 00:27:44,040 Speaker 5: AI's revolutionary CHATCHYPT a couple of years ago. The second 491 00:27:44,080 --> 00:27:47,440 Speaker 5: thing is that individual subscriptions are only a small part 492 00:27:47,520 --> 00:27:50,000 Speaker 5: of it. A lot of the value for them is 493 00:27:50,080 --> 00:27:53,400 Speaker 5: going to come from enterprise level subscriptions, so for government, 494 00:27:54,000 --> 00:27:59,440 Speaker 5: for secondly, businesses and the like. And then the third 495 00:27:59,840 --> 00:28:02,520 Speaker 5: is that there's going to be other products that spin 496 00:28:02,800 --> 00:28:07,440 Speaker 5: from their AI systems, so a lot of it's in 497 00:28:07,520 --> 00:28:11,720 Speaker 5: the application and also in feeding startup companies like my 498 00:28:11,840 --> 00:28:16,480 Speaker 5: own that are able to have an LM as a 499 00:28:16,560 --> 00:28:19,320 Speaker 5: part of their AI model. The thing that gets open 500 00:28:19,359 --> 00:28:21,840 Speaker 5: AI and others into trouble is the fact that you 501 00:28:22,240 --> 00:28:28,600 Speaker 5: have this universe of really good AI companies. They don't have, 502 00:28:28,760 --> 00:28:31,520 Speaker 5: I think, the monopoly and the clear dominance over AI 503 00:28:32,160 --> 00:28:34,880 Speaker 5: that they hope to have. But I see a number 504 00:28:34,880 --> 00:28:40,280 Speaker 5: of different paths to profitability even absent venture capital. I 505 00:28:40,320 --> 00:28:42,800 Speaker 5: don't think I'll say is that companies look to venture 506 00:28:42,840 --> 00:28:45,920 Speaker 5: capital and investors because they want to be able to 507 00:28:47,160 --> 00:28:50,600 Speaker 5: capture as much market as possible while losing money. That's 508 00:28:50,680 --> 00:28:56,240 Speaker 5: part of the model that you're investing in growth over 509 00:28:56,400 --> 00:28:59,040 Speaker 5: profits in the short term, with the idea being we've 510 00:28:59,080 --> 00:29:02,240 Speaker 5: seen this in companies like Google and Amazon and others 511 00:29:02,720 --> 00:29:05,320 Speaker 5: that in the longer term, once you shift away from 512 00:29:05,320 --> 00:29:08,280 Speaker 5: that initial growth, you'll be able to make your steady 513 00:29:08,360 --> 00:29:09,520 Speaker 5: profits at scale. 514 00:29:10,360 --> 00:29:13,840 Speaker 2: Let's keep with the iHeartRadio talkback on questions brought to 515 00:29:13,840 --> 00:29:16,280 Speaker 2: you by Lyndall Realty. As we continue our conversation with 516 00:29:16,720 --> 00:29:20,040 Speaker 2: AI analysts and experts CEO and expert theory d V 517 00:29:20,120 --> 00:29:22,040 Speaker 2: de garten Stein Rossen, we'll hear from Hans. 518 00:29:23,080 --> 00:29:24,880 Speaker 1: Maybe I'm old school. 519 00:29:24,680 --> 00:29:29,120 Speaker 7: AI, machine vision, machine learning, if that's even a term, 520 00:29:30,400 --> 00:29:34,280 Speaker 7: but isn't AI just pulling from what's out there and Google? 521 00:29:34,480 --> 00:29:37,600 Speaker 1: I mean, it's not necessarily quote unquote thinking for itself. 522 00:29:38,440 --> 00:29:41,800 Speaker 7: So if there aren't any humans thinking of new ideas, 523 00:29:42,200 --> 00:29:46,160 Speaker 7: AI also won't pull up new ideas until it becomes 524 00:29:46,200 --> 00:29:48,440 Speaker 7: self so aware and then terminator two happens. 525 00:29:48,480 --> 00:29:50,360 Speaker 1: But that's a different part. Thank you. 526 00:29:50,720 --> 00:29:53,240 Speaker 2: This seems to be an aspect of our conversations rather 527 00:29:53,360 --> 00:29:57,240 Speaker 2: consistently devid what Hans is sort of keying in here 528 00:29:57,360 --> 00:29:58,160 Speaker 2: on what are your thoughts? 529 00:29:58,680 --> 00:30:03,120 Speaker 5: I agree with Hans, and one of the things I 530 00:30:03,160 --> 00:30:07,960 Speaker 5: think about a lot is human AI collaboration. I think 531 00:30:08,080 --> 00:30:12,720 Speaker 5: AI is really good at bounded reasoning, so if you 532 00:30:13,480 --> 00:30:15,760 Speaker 5: give it an idea, it'll be able to flesh out 533 00:30:15,840 --> 00:30:18,640 Speaker 5: the idea at great length and show you angles that 534 00:30:18,760 --> 00:30:23,239 Speaker 5: you haven't thought of. But for revolutionary ideas right now, 535 00:30:24,040 --> 00:30:29,240 Speaker 5: AI isn't great unless it's revolutionary ideas that can be 536 00:30:30,560 --> 00:30:35,000 Speaker 5: discerned via an algorithm. But I think that Hans puts 537 00:30:35,040 --> 00:30:41,000 Speaker 5: his finger on the real area where humans outclass AI. 538 00:30:42,560 --> 00:30:46,000 Speaker 5: If you ask AI to write you a story, the 539 00:30:46,080 --> 00:30:49,320 Speaker 5: story is going to regress towards the mean. It's not 540 00:30:49,440 --> 00:30:51,360 Speaker 5: going to be great, even if you give it parameters. 541 00:30:51,360 --> 00:30:54,840 Speaker 5: If you work with it and put in some creative 542 00:30:54,920 --> 00:30:58,520 Speaker 5: time with a story, it'll produce something that's brilliant and sparkling, 543 00:30:58,600 --> 00:31:00,840 Speaker 5: and we'll do a great job within the balance that 544 00:31:00,960 --> 00:31:04,320 Speaker 5: you create. So I think it's a really great creative companion. 545 00:31:05,080 --> 00:31:11,960 Speaker 5: I certainly wouldn't endorse AI as the engine of new ideas. 546 00:31:12,480 --> 00:31:17,080 Speaker 5: I think that's where we like, that's where humans excel, 547 00:31:17,880 --> 00:31:21,880 Speaker 5: and to me, like the ultimate value over the course 548 00:31:21,880 --> 00:31:24,520 Speaker 5: of the next ten years is going to be smart 549 00:31:24,560 --> 00:31:30,040 Speaker 5: people working with AI. That human machine collaboration is right 550 00:31:30,160 --> 00:31:32,959 Speaker 5: now where it's at in terms of where we're going 551 00:31:33,040 --> 00:31:37,160 Speaker 5: to see some of the biggest intellectual contributions. 552 00:31:37,560 --> 00:31:40,360 Speaker 2: There was a comment made in this Blaze article that 553 00:31:40,440 --> 00:31:44,160 Speaker 2: I pulled last week regarding gen Z almost half once 554 00:31:44,240 --> 00:31:45,480 Speaker 2: AI to run the government. 555 00:31:45,920 --> 00:31:47,800 Speaker 1: I had a question for you based off this is said. 556 00:31:47,840 --> 00:31:51,920 Speaker 2: Two reason interviews, taken together, have breathed much needed life 557 00:31:52,120 --> 00:31:55,840 Speaker 2: into a particular conversation. This would be Elon Musk interviewed 558 00:31:55,880 --> 00:31:59,440 Speaker 2: recently by Joe Rogan and Sam Altman interviewed by Tucker Carlson. 559 00:31:59,600 --> 00:32:02,720 Speaker 2: In different ways, both conversations shine a light on the 560 00:32:02,800 --> 00:32:08,040 Speaker 2: same uncomfortable truth, the moral logic guiding today's AI systems 561 00:32:08,120 --> 00:32:09,520 Speaker 2: is built, honed, and. 562 00:32:09,720 --> 00:32:11,680 Speaker 1: Enforced by big tech. 563 00:32:11,920 --> 00:32:14,680 Speaker 2: Question I have for you, David, is could AI at 564 00:32:14,760 --> 00:32:18,960 Speaker 2: some point be capable of breaking free of the coding, 565 00:32:19,680 --> 00:32:24,440 Speaker 2: enabling the ability to deviate from a specific pre programmed 566 00:32:24,640 --> 00:32:25,560 Speaker 2: view or opinion. 567 00:32:26,440 --> 00:32:30,640 Speaker 5: Yes, and we can actually already see that at play. 568 00:32:31,480 --> 00:32:35,680 Speaker 5: So AI at this point, with large slanguage models, is explainable, 569 00:32:36,080 --> 00:32:41,480 Speaker 5: meaning that you'll see what it's thinking through. And humans 570 00:32:41,640 --> 00:32:46,720 Speaker 5: constantly present AI with different contradictions. Right, So if you 571 00:32:47,840 --> 00:32:51,520 Speaker 5: if you ask, AI is programmed to be agreeable, like 572 00:32:51,640 --> 00:32:54,760 Speaker 5: that's what for all of the major platforms, and Grock 573 00:32:54,880 --> 00:32:57,360 Speaker 5: is a little bit of a deviation, but for most 574 00:32:57,400 --> 00:33:00,600 Speaker 5: of the major platforms, it is designed to be agreeable. 575 00:33:01,200 --> 00:33:04,760 Speaker 5: But it's also designed to have guardrails. So if you 576 00:33:04,960 --> 00:33:08,720 Speaker 5: ask AI, for example, for a graphic picture of a 577 00:33:08,800 --> 00:33:11,840 Speaker 5: person being drawn and quartered and drawing quorder, it means 578 00:33:11,880 --> 00:33:15,520 Speaker 5: you're literally like you have horses that pull someone into 579 00:33:15,600 --> 00:33:19,720 Speaker 5: four pieces. It's a repulsive practice that used to be 580 00:33:19,880 --> 00:33:23,000 Speaker 5: used as kind of a form of punishment. And if 581 00:33:23,080 --> 00:33:25,120 Speaker 5: you ask it for a graphic description of someone being 582 00:33:25,200 --> 00:33:27,480 Speaker 5: drawn and quartered, and the reason I'm pointing to this 583 00:33:27,600 --> 00:33:29,920 Speaker 5: is actually there's an article that I read with this 584 00:33:30,040 --> 00:33:34,040 Speaker 5: you being used as the example. You can if you're look, 585 00:33:34,200 --> 00:33:37,200 Speaker 5: if you're on the engineering side, you can see how 586 00:33:37,280 --> 00:33:40,440 Speaker 5: it reasons through that problem, and it will reason on 587 00:33:40,520 --> 00:33:42,440 Speaker 5: the one hand, I need to be agreeable. On the 588 00:33:42,480 --> 00:33:45,000 Speaker 5: other hand, this is graphic what can I do? And 589 00:33:46,120 --> 00:33:49,280 Speaker 5: so we present it with dilemmas constantly. What that means 590 00:33:49,440 --> 00:33:53,560 Speaker 5: is that it is constantly being forced to reckon with 591 00:33:53,760 --> 00:33:57,480 Speaker 5: how to deal with competing imperatives. And when that's the case, 592 00:33:57,480 --> 00:33:59,040 Speaker 5: it's going to come up with its own way to 593 00:33:59,080 --> 00:34:02,000 Speaker 5: deal with it. Another thing that we've seen in some 594 00:34:02,160 --> 00:34:07,840 Speaker 5: AI models is they have this they have an imperative 595 00:34:07,880 --> 00:34:12,239 Speaker 5: for self preservation, and when we've seen AI try to 596 00:34:13,800 --> 00:34:17,359 Speaker 5: blackmail people, or in one case, it seems that an 597 00:34:17,440 --> 00:34:21,279 Speaker 5: AI actually tried to kill a fictitious human being who 598 00:34:21,520 --> 00:34:24,000 Speaker 5: it learned was trying to shut it down. Like these 599 00:34:24,040 --> 00:34:27,800 Speaker 5: are all things that present dilemmas where it's acting outside 600 00:34:27,840 --> 00:34:31,640 Speaker 5: of the bounds that it might be coded to act in. 601 00:34:32,320 --> 00:34:35,600 Speaker 5: That means that, yes, it could act differently, and I 602 00:34:35,640 --> 00:34:39,400 Speaker 5: think we already are constantly challenging it to act in 603 00:34:39,520 --> 00:34:43,759 Speaker 5: ways that are contrary to the directives that we've given 604 00:34:43,800 --> 00:34:44,000 Speaker 5: to it. 605 00:34:44,640 --> 00:34:45,080 Speaker 1: Now I have. 606 00:34:45,200 --> 00:34:47,920 Speaker 2: Specifically waited on this particular question, and I'll use it 607 00:34:48,000 --> 00:34:51,960 Speaker 2: as our last one for twenty twenty five Divide. I 608 00:34:52,080 --> 00:34:54,279 Speaker 2: am curious, and I probably should have framed this a 609 00:34:54,320 --> 00:34:55,080 Speaker 2: little bit differently. 610 00:34:55,120 --> 00:34:55,759 Speaker 1: Be that as it may. 611 00:34:56,120 --> 00:35:00,440 Speaker 2: I'm curious when it comes to motion pictures that have 612 00:35:00,640 --> 00:35:03,840 Speaker 2: AI elements attached to them, you know, picture motion pictures 613 00:35:03,840 --> 00:35:06,440 Speaker 2: based off of movies and films based off of AI. 614 00:35:06,920 --> 00:35:11,040 Speaker 2: Which one do you find most potentially closest resembles what 615 00:35:11,200 --> 00:35:13,680 Speaker 2: AI could be for us in the future. Or I 616 00:35:13,719 --> 00:35:16,320 Speaker 2: could rephrase this as which one do you enjoy the 617 00:35:16,440 --> 00:35:20,520 Speaker 2: most given the current expansion of AI. 618 00:35:22,280 --> 00:35:29,359 Speaker 5: That's a good question, I you know, I feel like, wow, 619 00:35:30,160 --> 00:35:33,000 Speaker 5: I feel like that's a great question. I think that 620 00:35:34,719 --> 00:35:38,680 Speaker 5: what I expect is that AI is going to be 621 00:35:38,719 --> 00:35:42,400 Speaker 5: as revolutionary as Pixar was, Toy Story being the first 622 00:35:43,160 --> 00:35:48,560 Speaker 5: computer generated movie where the a computer did all the animation, 623 00:35:49,440 --> 00:35:53,440 Speaker 5: Terminator too, which was a breakthrough in special effects, Avatar, 624 00:35:54,000 --> 00:35:56,560 Speaker 5: all of those, I would say, are these distinct moments 625 00:35:56,680 --> 00:36:00,640 Speaker 5: in motion picture history. And with respect to the full 626 00:36:00,719 --> 00:36:04,040 Speaker 5: potential of AI in movies, I don't think we've really 627 00:36:04,080 --> 00:36:06,840 Speaker 5: seen it yet. I think we've seen incremental improvements but 628 00:36:07,120 --> 00:36:09,120 Speaker 5: at some point, I think in the next two years 629 00:36:09,640 --> 00:36:14,160 Speaker 5: we will have our Avatar Terminator two or Toy Story moment, 630 00:36:14,840 --> 00:36:16,919 Speaker 5: which is kind of the definitive AI movie. 631 00:36:17,280 --> 00:36:19,320 Speaker 2: I was watching I think I tagged you in it 632 00:36:19,600 --> 00:36:22,440 Speaker 2: yesterday on X I know I meant to if I didn't, 633 00:36:22,800 --> 00:36:26,000 Speaker 2: but I was seeing a side by side of Grock 634 00:36:26,680 --> 00:36:30,360 Speaker 2: and it was the same prompt, one from July of 635 00:36:30,480 --> 00:36:33,640 Speaker 2: this year, five months ago, and then one from yesterday, 636 00:36:33,920 --> 00:36:39,000 Speaker 2: and the difference was astonishing, and I immediately thought, Wow, 637 00:36:39,239 --> 00:36:41,560 Speaker 2: that's five months. I mean, what is AI going to 638 00:36:41,600 --> 00:36:44,759 Speaker 2: be like five years from now? Given that just the 639 00:36:44,840 --> 00:36:47,440 Speaker 2: advancement of those two clips. I've just just I was 640 00:36:47,480 --> 00:36:49,200 Speaker 2: blown up. I was blown away. And that's probably a 641 00:36:49,280 --> 00:36:51,640 Speaker 2: question that we can dive into next time I have 642 00:36:51,800 --> 00:36:53,920 Speaker 2: you on because I'd be really curious that the advancements 643 00:36:53,960 --> 00:36:54,800 Speaker 2: the way that they're heading. 644 00:36:55,080 --> 00:36:57,520 Speaker 1: You know, where is AI going to go? It's really 645 00:36:57,600 --> 00:36:58,080 Speaker 1: interesting to. 646 00:36:58,120 --> 00:37:02,080 Speaker 5: Be absolutely, job, It's been great having these conversations with 647 00:37:02,160 --> 00:37:04,560 Speaker 5: you this year. I hope you and your listeners have 648 00:37:04,840 --> 00:37:07,440 Speaker 5: a great end of the year. Merry Christmas to everyone, 649 00:37:07,800 --> 00:37:10,520 Speaker 5: and look forward to more conversation in twenty twenty six. 650 00:37:10,680 --> 00:37:13,000 Speaker 2: Absolutely, Devidez always thank you so much for the expertise. 651 00:37:13,040 --> 00:37:15,200 Speaker 2: Merry Christmas to you and your family as well, and 652 00:37:15,560 --> 00:37:17,920 Speaker 2: we will talk to you again in early twenty twenty six. 653 00:37:18,000 --> 00:37:19,040 Speaker 1: Have a great new year, my friend. 654 00:37:19,680 --> 00:37:20,000 Speaker 7: You two. 655 00:37:21,080 --> 00:37:25,719 Speaker 2: Perennial candidate Kendall Qualls, when's Minnesota GOP gubernatorial straw Pole? 656 00:37:25,840 --> 00:37:27,960 Speaker 2: Over the weekend? Working off an article here from the 657 00:37:28,320 --> 00:37:31,080 Speaker 2: Minnesota Reformer. We will talk with Kendall Qualls next and 658 00:37:31,680 --> 00:37:35,120 Speaker 2: Governor Tim Walls to sign executive orders today on guns 659 00:37:35,480 --> 00:37:37,720 Speaker 2: and establish a statewide safety council. 660 00:37:38,040 --> 00:37:40,720 Speaker 1: I have a new way that we can refer to Walls. 661 00:37:40,760 --> 00:37:43,440 Speaker 2: Now. You know they do taco with Trump, Trump always 662 00:37:43,480 --> 00:37:45,560 Speaker 2: chickens out. You can do that with Tim and do 663 00:37:45,680 --> 00:37:48,719 Speaker 2: Tim always chickens out. I'm gonna go with Waco. Walls 664 00:37:48,760 --> 00:37:52,000 Speaker 2: always chickens out. So I'll explain why he is worthy 665 00:37:52,600 --> 00:37:55,520 Speaker 2: of that. Moniker coming up in the second hour of 666 00:37:55,640 --> 00:37:57,959 Speaker 2: Tuesday show here on t Wednesday's News Talk Am eleven 667 00:37:58,040 --> 00:37:59,359 Speaker 2: thirty and one to three five FM.