1 00:00:00,480 --> 00:00:04,360 Speaker 1: You're listening to KFI AM six forty on demand. 2 00:00:07,360 --> 00:00:09,639 Speaker 2: More stimulating talk. We'll talk about AI and how it's 3 00:00:09,640 --> 00:00:13,080 Speaker 2: going to replace this all. Yeah, we're all doomed. It's 4 00:00:13,119 --> 00:00:14,400 Speaker 2: not so bad for those of us that are a 5 00:00:14,400 --> 00:00:16,120 Speaker 2: little bit older. But a boy, if you are young, 6 00:00:16,200 --> 00:00:20,080 Speaker 2: you are hosed right now. You are just absolutely you 7 00:00:20,160 --> 00:00:24,360 Speaker 2: are just in there, you are in the meet. I 8 00:00:24,360 --> 00:00:26,400 Speaker 2: don't know what that means. I was I couldn't come 9 00:00:26,480 --> 00:00:27,960 Speaker 2: up with it. It was I just I bet an 10 00:00:28,000 --> 00:00:30,080 Speaker 2: AI could have come up with me, would have done something. 11 00:00:30,080 --> 00:00:31,960 Speaker 2: I was reading a great article tonight too, I think 12 00:00:31,960 --> 00:00:34,240 Speaker 2: it was The New York Times was talking about AI writing, 13 00:00:34,880 --> 00:00:37,120 Speaker 2: and you know, I like to use AI to cheat 14 00:00:37,159 --> 00:00:40,320 Speaker 2: and sort of summarize my notes and things like that. Eh, 15 00:00:40,560 --> 00:00:43,600 Speaker 2: and boy, they were so right. AI loves the m dash, 16 00:00:43,640 --> 00:00:47,600 Speaker 2: it loves the it's not this, it's that it's just 17 00:00:47,680 --> 00:00:48,400 Speaker 2: so lazy. 18 00:00:48,520 --> 00:00:50,320 Speaker 3: And also I was turning your brain to much. Let 19 00:00:50,320 --> 00:00:52,920 Speaker 3: me just say this. I think by now you know 20 00:00:53,040 --> 00:00:54,560 Speaker 3: me well enough to know that I'm not a big 21 00:00:54,680 --> 00:00:58,080 Speaker 3: like company, but smoocher type of kiss up kind of guy. 22 00:00:58,400 --> 00:01:02,320 Speaker 3: I absolutely love the game guaranteed human thing that iHeart 23 00:01:02,360 --> 00:01:04,399 Speaker 3: is doing. I think it's smart and I think it's 24 00:01:04,480 --> 00:01:08,119 Speaker 3: good and nothing has made me prouder than that. Wow. 25 00:01:08,319 --> 00:01:11,720 Speaker 2: Yeah, okay, right, we just raise a million dollars for 26 00:01:11,800 --> 00:01:13,800 Speaker 2: a bunch of kids so they don't go hungry this year. 27 00:01:13,800 --> 00:01:16,080 Speaker 3: But no, that's cool, Mark, we're talking about the end 28 00:01:16,080 --> 00:01:16,759 Speaker 3: of civilization. 29 00:01:16,840 --> 00:01:18,360 Speaker 2: I'm glad this is the only thing that makes you 30 00:01:18,400 --> 00:01:19,800 Speaker 2: happen that that's wonderful. 31 00:01:19,840 --> 00:01:21,000 Speaker 3: I'm trying to save humanity. 32 00:01:21,000 --> 00:01:23,679 Speaker 2: Mark, glad to have a job. Sorry, your kid is 33 00:01:23,680 --> 00:01:25,920 Speaker 2: starving to death in the street. It's not an either 34 00:01:26,080 --> 00:01:28,160 Speaker 2: or A I would tell you that. A I would 35 00:01:28,160 --> 00:01:31,600 Speaker 2: say it's not just starving kids, it's having a job. 36 00:01:32,959 --> 00:01:33,640 Speaker 3: That's terrible. 37 00:01:33,720 --> 00:01:36,360 Speaker 2: By the way, postathon, the official totalize of last night 38 00:01:36,400 --> 00:01:37,960 Speaker 2: was nine hundred fifty five thousand. We got off the 39 00:01:38,000 --> 00:01:39,720 Speaker 2: air and somebody had sent a talk back and I 40 00:01:39,760 --> 00:01:41,039 Speaker 2: didn't see until after we got done. 41 00:01:41,040 --> 00:01:42,360 Speaker 3: They said, can you give us a total? 42 00:01:42,600 --> 00:01:44,959 Speaker 2: The total that we had from last night didn't change 43 00:01:45,000 --> 00:01:48,440 Speaker 2: since the end of the broadcast at the White House 44 00:01:48,440 --> 00:01:52,200 Speaker 2: and Anaheim it was nine hundred and fifty five thousand dollars. 45 00:01:52,640 --> 00:01:54,640 Speaker 2: So what we're still waiting on and there's still a 46 00:01:54,680 --> 00:01:57,480 Speaker 2: chance for you to donate. There's a like a million dollars. 47 00:01:57,680 --> 00:02:00,520 Speaker 2: That excuse me, it's not a million dollars. We'll go 48 00:02:00,600 --> 00:02:03,560 Speaker 2: over a million dollars when we get the totals from 49 00:02:03,560 --> 00:02:06,600 Speaker 2: our partners. So we've got like Wendy's and Smart and 50 00:02:06,640 --> 00:02:08,760 Speaker 2: Final in those places where you can do your roundup 51 00:02:08,760 --> 00:02:09,400 Speaker 2: and you can do. 52 00:02:09,320 --> 00:02:10,800 Speaker 3: Your your coupon book and things like that. 53 00:02:10,840 --> 00:02:15,560 Speaker 2: So you know, we're gathering those contributions as well, and 54 00:02:15,680 --> 00:02:20,480 Speaker 2: you can still donate CAFI AM six forty dot com 55 00:02:20,520 --> 00:02:24,799 Speaker 2: slash pastathon. There we go, Am six forty KFI AM 56 00:02:24,800 --> 00:02:26,640 Speaker 2: six forty dot com slash pastathon. 57 00:02:26,800 --> 00:02:27,680 Speaker 3: There you all right. 58 00:02:28,160 --> 00:02:29,680 Speaker 2: One of the things we talked about it last night 59 00:02:29,680 --> 00:02:31,959 Speaker 2: and I was so glad to see it. It was 60 00:02:31,960 --> 00:02:34,480 Speaker 2: a quick blurb, but KTLA was talking about the foushe 61 00:02:35,760 --> 00:02:38,320 Speaker 2: showing up there last night and then meeting the guys 62 00:02:38,320 --> 00:02:40,760 Speaker 2: that pulled him out of that horrendous wreck. Of course, 63 00:02:40,800 --> 00:02:45,240 Speaker 2: the Fush has been with KFI for I think Fush 64 00:02:45,320 --> 00:02:46,720 Speaker 2: is one of the first guys I ever worked with. 65 00:02:46,760 --> 00:02:48,840 Speaker 2: He's the tech director, so I mean that's been at 66 00:02:48,919 --> 00:02:51,160 Speaker 2: least ten years, so I think he's been there. Alex 67 00:02:51,160 --> 00:02:53,160 Speaker 2: Fush's been around Mark do you know, twelve fifteen years 68 00:02:53,200 --> 00:02:53,680 Speaker 2: something like that. 69 00:02:53,720 --> 00:02:55,960 Speaker 3: I don't know longer than me. I'm coming up on 70 00:02:56,200 --> 00:02:57,840 Speaker 3: five years, and he predates me. 71 00:02:57,880 --> 00:03:00,640 Speaker 2: I think, yeah, yeah, I know he does. Yeah, And 72 00:03:00,680 --> 00:03:02,640 Speaker 2: he's he's just always been such a solid dude. So 73 00:03:03,400 --> 00:03:05,560 Speaker 2: Fush if you missed the story, of course, Fush was 74 00:03:05,560 --> 00:03:11,040 Speaker 2: in this horrible car accident where the car was just 75 00:03:11,120 --> 00:03:13,120 Speaker 2: there's nothing left. I mean, it caught fire while he 76 00:03:13,200 --> 00:03:15,520 Speaker 2: was inside. His arm was crushed. They thought his arm 77 00:03:15,560 --> 00:03:19,440 Speaker 2: was going to be amputated, his id burned up in 78 00:03:19,560 --> 00:03:21,080 Speaker 2: the car. He was a John Doe when he went 79 00:03:21,080 --> 00:03:22,760 Speaker 2: to the hospital. He just didn't show up at work. 80 00:03:23,440 --> 00:03:26,360 Speaker 2: And because he's been here so long, that's not the 81 00:03:26,440 --> 00:03:28,280 Speaker 2: kind of thing that he does. He doesn't just not 82 00:03:28,360 --> 00:03:29,840 Speaker 2: show up, you know. And then we couldn't get a 83 00:03:29,840 --> 00:03:31,560 Speaker 2: hold of him. His cell phone it you know, burned 84 00:03:31,639 --> 00:03:32,880 Speaker 2: up in the rack and that kind of stuff. So 85 00:03:32,919 --> 00:03:35,600 Speaker 2: it just horrible. But he was there last night at 86 00:03:35,600 --> 00:03:39,760 Speaker 2: the at the Pastathon broadcast and he was showing how 87 00:03:40,000 --> 00:03:43,000 Speaker 2: he's getting the dexterity and rebuilding the muscle in his arm, 88 00:03:43,040 --> 00:03:44,960 Speaker 2: and he was telling the story about how they thought 89 00:03:45,000 --> 00:03:47,680 Speaker 2: it was going to be amputated, but it was it 90 00:03:47,720 --> 00:03:51,280 Speaker 2: was not, which is good because he's left handed and 91 00:03:51,400 --> 00:03:52,240 Speaker 2: it was his left arm. 92 00:03:52,680 --> 00:03:55,160 Speaker 3: Yeah. I had been texting him sometime earlier and asking 93 00:03:55,200 --> 00:03:57,600 Speaker 3: him if he was getting some cool bionic stuff. That 94 00:03:57,600 --> 00:03:59,840 Speaker 3: would have been awesome, but apparently they managed just not 95 00:04:00,160 --> 00:04:02,400 Speaker 3: was And it was kind of an emotional thing last night. 96 00:04:02,440 --> 00:04:03,560 Speaker 3: It was really hard work. 97 00:04:03,600 --> 00:04:05,880 Speaker 2: It was so katy La caught up on that they 98 00:04:05,880 --> 00:04:08,560 Speaker 2: had this this little blurb on Channel five. 99 00:04:08,760 --> 00:04:09,760 Speaker 4: It's been four months. 100 00:04:09,720 --> 00:04:13,240 Speaker 5: Sivil Love, member of the AFI radio family, was severely 101 00:04:13,320 --> 00:04:16,760 Speaker 5: injured in a horrific car accident, and tonight he's making 102 00:04:16,800 --> 00:04:20,960 Speaker 5: a comeback. Thirty seven year old stephan Ca Bezos, affectionately 103 00:04:21,080 --> 00:04:23,039 Speaker 5: nicknamed the Foush, got a chance. 104 00:04:23,920 --> 00:04:24,560 Speaker 3: Oh that was it? 105 00:04:25,480 --> 00:04:29,960 Speaker 2: Okay, that's all that was posted. Okay, all right, well 106 00:04:29,960 --> 00:04:33,320 Speaker 2: that's all I got. I don't think we used the article. 107 00:04:33,320 --> 00:04:36,120 Speaker 2: We just call him fush. Yeah, we don't use uh 108 00:04:36,560 --> 00:04:40,800 Speaker 2: steffush or push. Yeah, that's it exactly. Did you see 109 00:04:40,800 --> 00:04:41,360 Speaker 2: his haircut? 110 00:04:41,800 --> 00:04:44,080 Speaker 3: I didn't. I was in the news booth here at 111 00:04:44,120 --> 00:04:44,360 Speaker 3: k SO. 112 00:04:44,400 --> 00:04:46,520 Speaker 2: I was watching the live broadcast because you know, I 113 00:04:46,560 --> 00:04:50,320 Speaker 2: was in my studio as well. And Fouish has always 114 00:04:50,320 --> 00:04:53,560 Speaker 2: had long hair and it is short, and he looks 115 00:04:53,640 --> 00:04:54,320 Speaker 2: really good. 116 00:04:54,440 --> 00:04:57,040 Speaker 3: He's a handsome fella. I like fush looking like the 117 00:04:57,120 --> 00:04:59,520 Speaker 3: dude from The Big Lebowski. That's he changed that. 118 00:05:00,279 --> 00:05:02,880 Speaker 2: Yeah that Yeah, he changed it. But that's exactly what 119 00:05:02,920 --> 00:05:07,120 Speaker 2: it is. Boy, you got it right too, That's exactly 120 00:05:07,160 --> 00:05:09,600 Speaker 2: what it is. He just looks like the dude abides 121 00:05:09,680 --> 00:05:13,240 Speaker 2: man predisposes you to be friendly with him kind of. 122 00:05:13,440 --> 00:05:16,719 Speaker 3: Yeah, but the new look is the new look is good. Okay, 123 00:05:16,760 --> 00:05:19,400 Speaker 3: I like it a lot. So he's coming back next week. 124 00:05:19,400 --> 00:05:20,680 Speaker 3: We'll have a chance to get used to it. 125 00:05:20,880 --> 00:05:23,359 Speaker 2: Yeah, I'm excited he'll be back next week. We'll make 126 00:05:23,400 --> 00:05:27,960 Speaker 2: a big deal of it. Probably cry men showing emotion. 127 00:05:28,839 --> 00:05:30,640 Speaker 2: That's what you come to the show for. You come 128 00:05:30,640 --> 00:05:32,159 Speaker 2: to the show because you go. You know what I 129 00:05:32,279 --> 00:05:38,760 Speaker 2: want dudes with big radio voices to cry? Oh yeah, 130 00:05:38,760 --> 00:05:40,760 Speaker 2: and I ugly cry like Claire Danes. 131 00:05:41,560 --> 00:05:46,719 Speaker 3: Oh that is the ugliest. I screw up my whole face. Yeah. 132 00:05:46,760 --> 00:05:48,640 Speaker 2: God, she just pulls that out all the time too, 133 00:05:48,680 --> 00:05:50,600 Speaker 2: doesn't she have every show? 134 00:05:50,720 --> 00:05:54,240 Speaker 3: Yeah, it's like, yeah, that's her money maker. What do 135 00:05:54,600 --> 00:05:54,880 Speaker 3: you want? 136 00:05:55,000 --> 00:05:57,520 Speaker 2: No, I get it, dude. What you're good with? Good 137 00:05:57,600 --> 00:06:02,920 Speaker 2: at Yeah. Oh I'm frantic melodry. I'm crying, but I'm overcoming. Look, 138 00:06:02,960 --> 00:06:09,680 Speaker 2: I'm strong foosh, which I wish we could get her 139 00:06:09,720 --> 00:06:11,200 Speaker 2: here for that, wouldn't they be? 140 00:06:11,200 --> 00:06:13,479 Speaker 3: God? I have no idea where she lives, but that 141 00:06:13,520 --> 00:06:15,600 Speaker 3: would be the best cameo of all time. I think 142 00:06:15,600 --> 00:06:17,400 Speaker 3: if she's listening, she's definitely not going to give us 143 00:06:17,480 --> 00:06:17,960 Speaker 3: the time of day. 144 00:06:18,000 --> 00:06:22,200 Speaker 2: Oh well, well, what are you gonna do? 145 00:06:22,360 --> 00:06:29,000 Speaker 3: You know? Well, what the hell with her? All right? 146 00:06:29,200 --> 00:06:31,800 Speaker 2: Uh? You think you're sitting in the car of the 147 00:06:31,839 --> 00:06:34,960 Speaker 2: future because you know from Mark he does not like change. 148 00:06:34,960 --> 00:06:37,160 Speaker 2: He doesn't like the future. He says, Nope, I don't 149 00:06:37,200 --> 00:06:39,360 Speaker 2: like any of it. I don't want I don't want anyone. 150 00:06:39,520 --> 00:06:42,960 Speaker 2: No humans replaced none, That's it. 151 00:06:43,839 --> 00:06:45,440 Speaker 3: Yeah. 152 00:06:45,600 --> 00:06:48,719 Speaker 2: The problem is and I hate to do this because 153 00:06:48,760 --> 00:06:51,159 Speaker 2: it's going to give Mark fuel for his own little fire. 154 00:06:51,200 --> 00:06:51,400 Speaker 3: There. 155 00:06:52,240 --> 00:06:55,480 Speaker 2: Your future could be drastically shortened because your Cabby just 156 00:06:55,520 --> 00:06:57,919 Speaker 2: pulled into an active crime zone. The future is actually 157 00:06:57,960 --> 00:07:01,760 Speaker 2: trying to kill you. How to avoid getting shot by 158 00:07:01,800 --> 00:07:05,360 Speaker 2: the future. Sounds like a bad promo for Looper is Next. 159 00:07:05,440 --> 00:07:07,760 Speaker 2: Chris Merril KFI AM six forty live everywhere in the 160 00:07:07,760 --> 00:07:08,520 Speaker 2: iHeartRadio app. 161 00:07:08,960 --> 00:07:12,400 Speaker 1: You're listening to KFI AM six forty on demand. 162 00:07:13,880 --> 00:07:18,160 Speaker 2: It's I'm Chris Merril kfi am six forty more stimulating talk. 163 00:07:19,040 --> 00:07:21,679 Speaker 2: I love it when we have a video go viral, 164 00:07:22,840 --> 00:07:26,239 Speaker 2: local video of things behaving badly. 165 00:07:26,360 --> 00:07:32,120 Speaker 3: In this case, it's the Weaimo. So Waimo is running. 166 00:07:31,840 --> 00:07:35,240 Speaker 2: You know, the driverless taxi service right on. I don't 167 00:07:35,240 --> 00:07:37,680 Speaker 2: want what do you call it? You call it a taxi, 168 00:07:37,720 --> 00:07:41,080 Speaker 2: whatever it is. It's the Waymo just taking awaymo. So 169 00:07:41,160 --> 00:07:44,440 Speaker 2: they're doing the Weymo. So we've got the driverless service 170 00:07:45,960 --> 00:07:49,320 Speaker 2: happening in LA and it's not a question of if, 171 00:07:49,360 --> 00:07:53,040 Speaker 2: it's a question of when it's gonna end up doing 172 00:07:53,080 --> 00:07:57,160 Speaker 2: something dumb. You've seen videos of Waimo doing dumb things before, 173 00:07:57,240 --> 00:08:01,040 Speaker 2: turning the wrong direction, cutting people off, whatever it is. 174 00:08:01,560 --> 00:08:04,480 Speaker 2: You've seen the videos, so you know it does these 175 00:08:04,520 --> 00:08:10,480 Speaker 2: things a bit unfairly because people cut each other off 176 00:08:10,520 --> 00:08:12,960 Speaker 2: every day, people go down the wrong way and a 177 00:08:13,000 --> 00:08:15,400 Speaker 2: one way street. People do all of these things as well. 178 00:08:15,440 --> 00:08:19,240 Speaker 2: But we hold the machines to a higher standard because. 179 00:08:19,280 --> 00:08:21,240 Speaker 3: There's a scapegoat. 180 00:08:21,600 --> 00:08:26,040 Speaker 2: Say Waimeo does something dumb and smashes into you. There's 181 00:08:26,040 --> 00:08:29,880 Speaker 2: no person on the other side of that that holds responsibility. Instead, 182 00:08:30,760 --> 00:08:35,920 Speaker 2: it's some corporate leviathan that will buy their way out 183 00:08:35,960 --> 00:08:38,040 Speaker 2: of whatever it is. Oh goodness, okay, you assume them. 184 00:08:38,040 --> 00:08:39,800 Speaker 2: You get a few million dollars. It's a drop of 185 00:08:39,800 --> 00:08:44,240 Speaker 2: the bucket for Google, for alphabet right, it's nothing. Whereas 186 00:08:44,280 --> 00:08:45,760 Speaker 2: if it's a person on the other end, they got 187 00:08:45,880 --> 00:08:48,640 Speaker 2: they got skin in the game. You know that if 188 00:08:48,679 --> 00:08:50,040 Speaker 2: they turn the wrong way in a one way and 189 00:08:50,040 --> 00:08:54,760 Speaker 2: they end up hitting you like that has serious consequences. 190 00:08:55,160 --> 00:08:57,160 Speaker 2: So it's frustrating when we see the machines are doing 191 00:08:57,240 --> 00:08:59,520 Speaker 2: something wrong, even if the machines are better than humans 192 00:08:59,520 --> 00:09:00,040 Speaker 2: at it. 193 00:09:00,160 --> 00:09:02,320 Speaker 3: Frustrating when we see it because they got no skin 194 00:09:02,360 --> 00:09:02,800 Speaker 3: in the game. 195 00:09:04,600 --> 00:09:07,160 Speaker 2: We can't relate to it, but we're expected to put 196 00:09:07,160 --> 00:09:09,760 Speaker 2: our trust in that being on the roads. Well, now, 197 00:09:09,960 --> 00:09:12,760 Speaker 2: the video has gone viral for this reason. 198 00:09:12,800 --> 00:09:17,000 Speaker 6: In this video, taken in downtown LA, but the Wamo 199 00:09:17,160 --> 00:09:20,400 Speaker 6: doing you can see a line of police cars blocking 200 00:09:20,400 --> 00:09:23,440 Speaker 6: the road and a man lying on the ground. Entered 201 00:09:23,520 --> 00:09:27,280 Speaker 6: this Waimo driverless taxi, which, while servicing riders, proceeds to 202 00:09:27,320 --> 00:09:30,520 Speaker 6: take a left turn, driving right past the active police 203 00:09:30,559 --> 00:09:33,760 Speaker 6: stop and officers, two moments later, are seen walking towards 204 00:09:33,760 --> 00:09:35,319 Speaker 6: the subject with weapons drawn. 205 00:09:35,800 --> 00:09:40,000 Speaker 2: Yet not only did it drive through the standoff or 206 00:09:40,040 --> 00:09:40,760 Speaker 2: whatever you want to call it. 207 00:09:42,120 --> 00:09:45,720 Speaker 3: Uh, it just about drove over the suspect. 208 00:09:46,800 --> 00:09:48,680 Speaker 2: So the driver had gotten out of his out of 209 00:09:48,679 --> 00:09:50,520 Speaker 2: his I think it was a truck, gets out of 210 00:09:50,559 --> 00:09:52,840 Speaker 2: the truck, lies down of the ground like the police telling. 211 00:09:52,720 --> 00:09:55,280 Speaker 3: Me, good all of the vehicle, lay it out with 212 00:09:55,320 --> 00:09:55,920 Speaker 3: your hands. 213 00:09:55,679 --> 00:09:58,400 Speaker 2: Behind your head. That's what he's doing. All of a sudden, 214 00:09:58,400 --> 00:10:00,839 Speaker 2: the Weymo drives by and just about drives over him. 215 00:10:02,160 --> 00:10:02,960 Speaker 2: Good job, Waimo. 216 00:10:03,679 --> 00:10:07,160 Speaker 6: Waimo telling NBC News that when it's Robotaxi came across 217 00:10:07,160 --> 00:10:09,920 Speaker 6: the scene, it turned into an unblocked area where other 218 00:10:09,960 --> 00:10:13,000 Speaker 6: cars were also driving, and that it quickly left. In 219 00:10:13,040 --> 00:10:16,200 Speaker 6: a statement, the company saying safety is our highest priority 220 00:10:16,360 --> 00:10:18,920 Speaker 6: and that when we encounter unusual events like this one, 221 00:10:19,000 --> 00:10:21,840 Speaker 6: we learn from them. Will it ever be possible to 222 00:10:22,040 --> 00:10:26,160 Speaker 6: train a driverless car on every single potential traffic scenario? 223 00:10:27,240 --> 00:10:31,320 Speaker 2: Come on, No, it's impossible to train a humans on 224 00:10:31,440 --> 00:10:33,640 Speaker 2: every single possible traffic scenario. 225 00:10:34,520 --> 00:10:34,760 Speaker 3: Nope. 226 00:10:35,520 --> 00:10:37,959 Speaker 2: Although if we see flashing lights and somebody on the 227 00:10:37,960 --> 00:10:40,719 Speaker 2: ground and guns drawn, we know maybe don't drive through 228 00:10:40,760 --> 00:10:41,120 Speaker 2: that way. 229 00:10:41,440 --> 00:10:43,000 Speaker 3: And that's the catch with this technology. 230 00:10:43,760 --> 00:10:46,360 Speaker 6: The question is can you train it on enough that 231 00:10:46,440 --> 00:10:48,720 Speaker 6: it makes few enough mistakes that you're willing to tolerate 232 00:10:48,720 --> 00:10:49,240 Speaker 6: the mistakes. 233 00:10:49,360 --> 00:10:54,520 Speaker 2: Of course, I mean that's a good question. Here's here's 234 00:10:54,559 --> 00:10:57,880 Speaker 2: what I think is really interesting about the machine machine learning, 235 00:10:58,120 --> 00:10:59,880 Speaker 2: the training and all this stuff we're doing. Whether it's 236 00:10:59,880 --> 00:11:03,240 Speaker 2: a whether it's the driver's vehicles, whatever it is, it's 237 00:11:03,280 --> 00:11:06,760 Speaker 2: that we train it on logic. But logic is not 238 00:11:06,800 --> 00:11:11,360 Speaker 2: a substitute for sense. So we have common sense. Don't 239 00:11:11,400 --> 00:11:13,080 Speaker 2: stand in front of the cop that's pointing a gun 240 00:11:13,080 --> 00:11:18,360 Speaker 2: on a subject, right, common sense would tell you self 241 00:11:18,400 --> 00:11:21,240 Speaker 2: preservation kicks in here, and I'm not going to stand 242 00:11:21,240 --> 00:11:24,240 Speaker 2: in between the cop and the guy who the cop 243 00:11:24,280 --> 00:11:25,079 Speaker 2: is pointing the gun at. 244 00:11:25,920 --> 00:11:27,040 Speaker 3: That just makes sense. 245 00:11:27,679 --> 00:11:29,760 Speaker 2: And I don't think this is something that we have 246 00:11:29,800 --> 00:11:33,040 Speaker 2: to train people on. This is not This is not Oh, 247 00:11:33,120 --> 00:11:35,560 Speaker 2: what are the are the what's the training data for this? 248 00:11:35,880 --> 00:11:36,040 Speaker 3: No? 249 00:11:36,120 --> 00:11:37,520 Speaker 2: If you tell a five year old a do you 250 00:11:37,559 --> 00:11:39,480 Speaker 2: want to stand between a cop who's pointing a gun 251 00:11:39,480 --> 00:11:41,360 Speaker 2: at a person who's on the ground or not, and 252 00:11:41,400 --> 00:11:45,680 Speaker 2: the five year old's gonna go No. The cars don't 253 00:11:45,720 --> 00:11:49,520 Speaker 2: have common sense, they only have logic. Logic says I 254 00:11:49,600 --> 00:11:53,800 Speaker 2: need to turn left. Going straight is blocked off, flashing lights, 255 00:11:53,840 --> 00:11:56,080 Speaker 2: avoid flashing lights, move on to the next. Whatever it 256 00:11:56,120 --> 00:11:59,319 Speaker 2: is doesn't have common sense the. 257 00:11:59,280 --> 00:12:02,400 Speaker 6: Way most data their self driving cars have ninety percent 258 00:12:02,600 --> 00:12:06,200 Speaker 6: fewer serious crashes compared to a human driver that I 259 00:12:06,240 --> 00:12:07,480 Speaker 6: believe that their vehicle. 260 00:12:07,600 --> 00:12:11,320 Speaker 2: Yeah, we suck at driving too older, I get the 261 00:12:11,360 --> 00:12:12,640 Speaker 2: less I want to be on the road. And I 262 00:12:12,720 --> 00:12:16,800 Speaker 2: used to love driving I did, I think probably because I. 263 00:12:16,800 --> 00:12:21,600 Speaker 3: Was the hazard. Yeah, now I drive safer. Driving safe 264 00:12:21,640 --> 00:12:23,480 Speaker 3: is boring and scary. 265 00:12:23,240 --> 00:12:26,760 Speaker 6: That their vehicles are still facing challenges. Earlier this year, 266 00:12:26,800 --> 00:12:29,200 Speaker 6: a passenger got stuck in a Weimo after the car 267 00:12:29,360 --> 00:12:32,600 Speaker 6: repeatedly circled around a parking lot at the Phoenix Airport. 268 00:12:33,160 --> 00:12:35,680 Speaker 3: This car is just going in circles, and. 269 00:12:35,760 --> 00:12:40,400 Speaker 6: The federal investigation is now underway into Weimo's repeatedly passing 270 00:12:40,400 --> 00:12:42,679 Speaker 6: stop school buses with lights flashing. 271 00:12:43,960 --> 00:12:46,520 Speaker 2: Yeah, but what's the stake in the game? If I 272 00:12:46,679 --> 00:12:49,800 Speaker 2: do that, if you do that, they're gonna track us down. 273 00:12:49,920 --> 00:12:53,120 Speaker 2: We're gonna take away our license. There's gonna be consequences. 274 00:12:53,679 --> 00:12:56,640 Speaker 2: If Google does that, they go Google, you shouldn't do that. 275 00:12:56,640 --> 00:13:00,000 Speaker 2: You should train your your your vehicles not to do that. 276 00:13:01,080 --> 00:13:02,840 Speaker 2: And if you keep doing it, we're going to find you, 277 00:13:04,360 --> 00:13:07,280 Speaker 2: where's the consequence? No consequence. 278 00:13:07,520 --> 00:13:09,959 Speaker 6: And as for this latest incident here in La Lap 279 00:13:10,080 --> 00:13:14,160 Speaker 6: details NBC News that the Waimo car did not impact 280 00:13:14,240 --> 00:13:17,840 Speaker 6: or impede any of the police officers' operations during that 281 00:13:17,920 --> 00:13:21,080 Speaker 6: traffic stop. But they did say that that turn that 282 00:13:21,120 --> 00:13:24,160 Speaker 6: the Robotaxi made did prompt the officers to go and 283 00:13:24,200 --> 00:13:26,880 Speaker 6: then shut down and block off that intersection. 284 00:13:27,200 --> 00:13:30,520 Speaker 2: Michael, okay, thank you very much. It was NBCLA that 285 00:13:30,600 --> 00:13:34,360 Speaker 2: was reporting on that. So where I get frustrated with 286 00:13:34,400 --> 00:13:38,000 Speaker 2: the machine learning and whatnot, Mark loves it. 287 00:13:38,040 --> 00:13:40,280 Speaker 3: When when I talk about AI, he loves it. I 288 00:13:40,280 --> 00:13:43,040 Speaker 3: can't get enough of it. Eyes light up. It pleases me. Now, 289 00:13:43,120 --> 00:13:45,720 Speaker 3: I had a nice conversation with my chat GPT tonight. 290 00:13:45,880 --> 00:13:49,679 Speaker 3: It wasn't a conversation, mil was No, it was can 291 00:13:49,720 --> 00:13:51,079 Speaker 3: we say the M word on the air? 292 00:13:51,679 --> 00:13:54,880 Speaker 2: I don't know what the M word is? Never mind 293 00:13:55,640 --> 00:14:01,720 Speaker 2: machine masochism? These oh wankin. 294 00:14:01,440 --> 00:14:03,480 Speaker 3: There you go. We can say the W word, but 295 00:14:03,520 --> 00:14:06,160 Speaker 3: not the M word. These things aren't thinking. They're programmed. 296 00:14:06,200 --> 00:14:09,040 Speaker 3: Programming isn't thinking. Okay. 297 00:14:09,120 --> 00:14:12,640 Speaker 2: So I was diving into the programming tonight. Yes, there 298 00:14:12,720 --> 00:14:14,560 Speaker 2: was an article in the New York Times and I 299 00:14:14,600 --> 00:14:16,280 Speaker 2: made mention of this in the first segment that was 300 00:14:16,400 --> 00:14:21,560 Speaker 2: talking about how the writing is predictable and wrote and 301 00:14:21,840 --> 00:14:25,480 Speaker 2: it leans on tropes that sure, we use these things 302 00:14:25,480 --> 00:14:28,000 Speaker 2: in real life, but we don't use them in every sentence. 303 00:14:29,160 --> 00:14:32,720 Speaker 2: It likes to say, uh, it's not X, it's y, 304 00:14:33,240 --> 00:14:35,120 Speaker 2: and it loves to use the M dash. 305 00:14:35,240 --> 00:14:38,440 Speaker 3: I can't stand it. So that's where you drop the line, 306 00:14:38,520 --> 00:14:41,600 Speaker 3: Oh my gosh, dude, I can't mark. I can't tell 307 00:14:41,640 --> 00:14:46,880 Speaker 3: you it's not wrong. Right. The M dash is fine. 308 00:14:46,920 --> 00:14:49,200 Speaker 2: It's a great substitute for somebody like I tend to 309 00:14:49,200 --> 00:14:51,760 Speaker 2: overuse ellipses, right, and M dash is a great substitute 310 00:14:51,760 --> 00:14:53,800 Speaker 2: for that, which is just a dash basically for those 311 00:14:54,000 --> 00:14:56,400 Speaker 2: that don't know what it is. But it's kind of 312 00:14:56,480 --> 00:14:59,040 Speaker 2: like talking to that person that puts exclamation points at 313 00:14:59,080 --> 00:15:03,240 Speaker 2: the end of every sense with their fingers or the sorry, 314 00:15:03,280 --> 00:15:05,760 Speaker 2: the fake quotation marks. Well, that's the person you're talking 315 00:15:05,800 --> 00:15:08,080 Speaker 2: to in real life. I'm just saying, imagine I send 316 00:15:08,120 --> 00:15:10,640 Speaker 2: you a message, and every message I send you just 317 00:15:10,720 --> 00:15:14,800 Speaker 2: as exclamation points. Are you working tonight? Exclamation boyd exclamation point? 318 00:15:14,800 --> 00:15:18,760 Speaker 2: Exclamation point? You go, well, it seems excessive. 319 00:15:18,760 --> 00:15:20,800 Speaker 3: I would think you had some developmental issues, and I 320 00:15:20,800 --> 00:15:24,000 Speaker 3: would I would speak very carefully to you and slowly. Yeah, 321 00:15:24,040 --> 00:15:24,800 Speaker 3: that's what AI is. 322 00:15:25,400 --> 00:15:27,880 Speaker 2: So anyway, I asked AI would have thought about the article, 323 00:15:27,920 --> 00:15:29,880 Speaker 2: and it basically trashed the article. 324 00:15:30,560 --> 00:15:32,760 Speaker 3: Yeah, and I said, your response is interesting. 325 00:15:33,760 --> 00:15:35,800 Speaker 2: Your response uses a lot of the same tropes the 326 00:15:35,880 --> 00:15:39,160 Speaker 2: article says are telltale signs. And it's like, oh, good job, 327 00:15:39,480 --> 00:15:41,760 Speaker 2: you caught me. You've become self aware about my lack 328 00:15:41,800 --> 00:15:42,720 Speaker 2: of self awareness. 329 00:15:44,160 --> 00:15:45,720 Speaker 3: Yeah. And the thing is you can't even if they 330 00:15:45,760 --> 00:15:47,840 Speaker 3: if these things screw up, you can't have the satisfaction 331 00:15:47,880 --> 00:15:50,040 Speaker 3: of turning them off. Like hal nine thousand, No, that 332 00:15:50,120 --> 00:15:51,560 Speaker 3: in two thousand and one, Like you're not going to 333 00:15:51,600 --> 00:15:54,840 Speaker 3: sing Daisy slower and slower until you go to sleep forever. Hey, 334 00:15:55,560 --> 00:15:56,440 Speaker 3: there's Yeah. 335 00:15:56,560 --> 00:15:58,240 Speaker 2: The thing is like if I yell at you, I 336 00:15:58,240 --> 00:16:00,240 Speaker 2: get an emotional response one way and other. 337 00:16:00,320 --> 00:16:02,440 Speaker 3: Right, you're like, oh, wow, he's really upset. No, big 338 00:16:02,520 --> 00:16:05,360 Speaker 3: does not care. I wonder if they had focus groups 339 00:16:05,360 --> 00:16:07,960 Speaker 3: for WEIMO before they settled on WEIMO, because I would 340 00:16:07,960 --> 00:16:12,920 Speaker 3: like to call them dystopian robot cars. That was second 341 00:16:12,960 --> 00:16:16,560 Speaker 3: place okay on the on the focus group. Yeah. Yeah, 342 00:16:16,600 --> 00:16:19,440 Speaker 3: and it's more of a mouthful when you're using the app, 343 00:16:19,520 --> 00:16:24,080 Speaker 3: but it's a little more accurate. Dystopian Robot car yeah 344 00:16:24,480 --> 00:16:26,120 Speaker 3: or DRCS for short. Right. 345 00:16:26,960 --> 00:16:30,800 Speaker 2: Anyway, My point is is, I was, you know, wanking 346 00:16:30,920 --> 00:16:34,400 Speaker 2: with edgy PC. I'm gonna call a conversation you say 347 00:16:34,440 --> 00:16:38,360 Speaker 2: it was not uh huh uh. Basically I said, can 348 00:16:38,400 --> 00:16:40,760 Speaker 2: you learn from these criticisms? 349 00:16:41,000 --> 00:16:43,560 Speaker 3: And it basically said no, I can't. It has to 350 00:16:43,560 --> 00:16:44,320 Speaker 3: be programmed in. 351 00:16:44,880 --> 00:16:47,160 Speaker 2: So what concerns me is that when you've got weaymo 352 00:16:47,240 --> 00:16:48,960 Speaker 2: that's going through this intersection. 353 00:16:48,640 --> 00:16:49,160 Speaker 3: You can't go. 354 00:16:49,840 --> 00:16:55,240 Speaker 2: Don't do that because in all of our dystopian films, 355 00:16:55,840 --> 00:17:00,640 Speaker 2: the there's a neural network where if one one remote 356 00:17:00,680 --> 00:17:04,280 Speaker 2: server learns something, it passes it on right to the 357 00:17:04,400 --> 00:17:07,960 Speaker 2: centralized brain, and then the centralized brain learns from that. 358 00:17:08,080 --> 00:17:10,760 Speaker 2: Usually it's learning tactics of whoever's trying to destroy it 359 00:17:10,800 --> 00:17:13,160 Speaker 2: in our dystopian robot films. 360 00:17:14,280 --> 00:17:15,480 Speaker 3: But the Waimo doesn't do that. 361 00:17:16,080 --> 00:17:18,639 Speaker 2: It has to so it screws this stuff up at 362 00:17:18,640 --> 00:17:20,600 Speaker 2: the police traffic stop, or it screws this thing up, 363 00:17:20,640 --> 00:17:23,439 Speaker 2: it starts driving in circles, and it has to have 364 00:17:23,560 --> 00:17:25,600 Speaker 2: Somebody has to come to work the next day at 365 00:17:25,640 --> 00:17:29,080 Speaker 2: Google write code to tell it don't do that again. 366 00:17:29,359 --> 00:17:34,040 Speaker 2: So when they talk about machine learning, not really, it 367 00:17:34,359 --> 00:17:39,800 Speaker 2: just it doesn't really learn. It remembers instructions and it 368 00:17:39,920 --> 00:17:42,439 Speaker 2: employs new instructions on a one on one basis, but 369 00:17:42,480 --> 00:17:44,600 Speaker 2: it's not like there's a neural network where it is 370 00:17:44,680 --> 00:17:46,600 Speaker 2: actually learning things. 371 00:17:47,240 --> 00:17:50,439 Speaker 3: So many people are gonna lose their shirts when the 372 00:17:50,480 --> 00:17:53,080 Speaker 3: AI bubble bursts and it's going to the numbers bear 373 00:17:53,160 --> 00:17:57,360 Speaker 3: this out. I've never more wanted Captain Kirk to come 374 00:17:57,359 --> 00:18:01,320 Speaker 3: in and talk a computer into self destructing. Oh, yes, 375 00:18:01,840 --> 00:18:03,320 Speaker 3: because he did that. He would do that. He did 376 00:18:03,320 --> 00:18:05,120 Speaker 3: that like half a dozen different times. 377 00:18:05,160 --> 00:18:08,400 Speaker 2: Yeah, he would out logic the computer until it realized 378 00:18:08,400 --> 00:18:11,520 Speaker 2: that the only reasonable solution to whatever. 379 00:18:11,359 --> 00:18:12,720 Speaker 3: The issue is is self destruction. 380 00:18:12,880 --> 00:18:17,760 Speaker 2: Yeah at Rodenberry, he knew how to write, didn't he. 381 00:18:17,800 --> 00:18:21,719 Speaker 3: We need him. Yeah, well we've still got Shatner. We 382 00:18:21,760 --> 00:18:23,520 Speaker 3: do still have Shatner. That's a good point too. 383 00:18:23,640 --> 00:18:25,959 Speaker 2: Hey, you'd be forgiven for thinking that gen Z is broken, 384 00:18:26,000 --> 00:18:30,680 Speaker 2: that they're renting and waiting, But maybe, just maybe gen 385 00:18:30,800 --> 00:18:34,240 Speaker 2: Z has figured things out in a way that the 386 00:18:34,240 --> 00:18:37,400 Speaker 2: rest of us never could find out. What the Zoomers 387 00:18:37,480 --> 00:18:40,440 Speaker 2: might be onto next the Chris it's a Chris Merril 388 00:18:40,480 --> 00:18:42,920 Speaker 2: KF I am six forty. 389 00:18:43,000 --> 00:18:44,560 Speaker 3: I think, is that the one we're doing? 390 00:18:44,600 --> 00:18:45,679 Speaker 7: Next? 391 00:18:45,920 --> 00:18:47,920 Speaker 2: Oh no, that's the wrong teas. I read the wrong teas. 392 00:18:48,080 --> 00:18:49,760 Speaker 2: Uh oh yeah, no, we're not doing that one. 393 00:18:49,800 --> 00:18:53,200 Speaker 3: Next? What am I doing that one? Oh? Next hour? 394 00:18:54,480 --> 00:18:54,760 Speaker 2: All right? 395 00:18:54,840 --> 00:18:56,560 Speaker 3: Ignore that? Then? How about this? 396 00:18:56,720 --> 00:19:00,439 Speaker 2: The kissing club is turning into something very dirty and 397 00:19:00,440 --> 00:19:04,280 Speaker 2: it could cost one local school boku bucks? How kissing 398 00:19:04,280 --> 00:19:06,320 Speaker 2: turns into sexual assault in elementary school? 399 00:19:06,359 --> 00:19:06,679 Speaker 3: Gross? 400 00:19:06,800 --> 00:19:09,560 Speaker 2: Next, Chris merril k I am six forty live everywhere 401 00:19:09,560 --> 00:19:10,280 Speaker 2: in the iHeartRadio. 402 00:19:10,880 --> 00:19:16,720 Speaker 1: You're listening to KFI AM six forty on demand, more. 403 00:19:18,720 --> 00:19:24,280 Speaker 3: Stimulating talk. What have we here? Oh? Look, first blush? 404 00:19:24,359 --> 00:19:27,520 Speaker 3: I thought, what's the big deal? A kissing club? All right? 405 00:19:27,640 --> 00:19:28,840 Speaker 3: Kids are kids? Now? 406 00:19:29,720 --> 00:19:32,800 Speaker 2: Kissing club assaults an eight year old hidden by LA's 407 00:19:32,840 --> 00:19:37,159 Speaker 2: elite Sierra Canyon School, According to a lawsuit, Fox eleven 408 00:19:37,200 --> 00:19:39,360 Speaker 2: had the story and I was like, Oh, how bad 409 00:19:39,359 --> 00:19:39,800 Speaker 2: could it be? 410 00:19:40,040 --> 00:19:42,639 Speaker 3: Oh? God, it's bad. 411 00:19:42,960 --> 00:19:45,600 Speaker 8: Tierra Canyon is a pre k through twelfth grade school 412 00:19:45,640 --> 00:19:48,320 Speaker 8: located in Chatsworth. Tuition can be as high as thirty 413 00:19:48,400 --> 00:19:51,520 Speaker 8: nine thousand dollars per year for the lower grades. The 414 00:19:51,600 --> 00:19:54,200 Speaker 8: parents of a young girl enrolled her there with the 415 00:19:54,240 --> 00:19:58,480 Speaker 8: school's promise of a seller education and a secure environment. However, 416 00:19:58,800 --> 00:20:02,040 Speaker 8: when details a bullet and more serious issues emerged, the 417 00:20:02,119 --> 00:20:05,240 Speaker 8: parents claimed that the school did nothing to protect their daughter. 418 00:20:05,680 --> 00:20:08,320 Speaker 8: So far, there has been no response from Sierra Canyon 419 00:20:08,440 --> 00:20:11,920 Speaker 8: regarding what is reported to be the second lawsuit alleging 420 00:20:11,920 --> 00:20:15,560 Speaker 8: that older girls bullied younger girls and engaged in even 421 00:20:15,560 --> 00:20:16,920 Speaker 8: more serious misconduct. 422 00:20:17,320 --> 00:20:21,399 Speaker 2: Yeah, the serious misconduct gets a little so earmuffs kids. 423 00:20:21,760 --> 00:20:24,440 Speaker 8: This lawsuit was filed on behalf of a now nine 424 00:20:24,480 --> 00:20:27,800 Speaker 8: year old girl. According to the documents, the victim, who 425 00:20:27,880 --> 00:20:31,080 Speaker 8: was then seven, was allegedly bullied into joining what was 426 00:20:31,119 --> 00:20:34,359 Speaker 8: referred to as the Kissing Club. Over time, the activities 427 00:20:34,359 --> 00:20:38,960 Speaker 8: in the unsupervised restroom reportedly escalated. E K was pressured 428 00:20:39,040 --> 00:20:41,840 Speaker 8: into the group to kiss the others in the bathroom. 429 00:20:42,000 --> 00:20:44,520 Speaker 8: Soon thereafter, she was forced by the older girls to 430 00:20:44,600 --> 00:20:46,320 Speaker 8: kiss and touch their genital area. 431 00:20:46,520 --> 00:20:50,760 Speaker 7: Okay, they involved the actual kissing of young girls amongst 432 00:20:50,800 --> 00:20:56,840 Speaker 7: each other, but it led to sexual touching of sexual. 433 00:20:56,359 --> 00:20:57,360 Speaker 3: Body part healthy. 434 00:20:57,560 --> 00:21:00,959 Speaker 7: And that's the most disturbing thing is it took some 435 00:21:01,119 --> 00:21:04,719 Speaker 7: time for it to develop, and there was this kissing 436 00:21:04,720 --> 00:21:08,159 Speaker 7: club just grew and got more bolder because there was 437 00:21:08,240 --> 00:21:09,560 Speaker 7: complete lack of supervision. 438 00:21:09,560 --> 00:21:09,600 Speaker 3: It. 439 00:21:10,160 --> 00:21:13,440 Speaker 2: Yeah, that's terrifying, and it continued to get worse and worse. 440 00:21:13,640 --> 00:21:16,040 Speaker 2: So I mean, were they were grounding the bases? Is 441 00:21:16,080 --> 00:21:18,199 Speaker 2: what was happening with these kids in elementary school? And 442 00:21:18,200 --> 00:21:22,600 Speaker 2: it's look, I think everyone at a young age is 443 00:21:22,640 --> 00:21:27,720 Speaker 2: discovering themselves and probably has stories of kissing the neighborhood 444 00:21:27,760 --> 00:21:30,760 Speaker 2: boy or girl or whatever it was. I think, I 445 00:21:30,760 --> 00:21:33,800 Speaker 2: think that's something that many, many, many people shared and experienced, 446 00:21:33,800 --> 00:21:36,479 Speaker 2: many of us shared in our formative years. So when 447 00:21:36,480 --> 00:21:38,040 Speaker 2: I heard okay there was a kissing club, I thought, 448 00:21:38,040 --> 00:21:40,879 Speaker 2: all right, inappropriate. You know, adults, you step in, you 449 00:21:40,880 --> 00:21:42,280 Speaker 2: break it up. But then when I find out that 450 00:21:42,320 --> 00:21:47,600 Speaker 2: it turns into basically sexual assault, it's horrifying. And here 451 00:21:47,640 --> 00:21:52,560 Speaker 2: you are at the private school, so no pun intended, 452 00:21:53,240 --> 00:21:59,520 Speaker 2: high profile private institution. So where is the supervision? And 453 00:21:59,600 --> 00:22:01,520 Speaker 2: I don't know if they're talking about older girls, what 454 00:22:01,560 --> 00:22:02,200 Speaker 2: do they mean nine? 455 00:22:02,240 --> 00:22:02,600 Speaker 3: Do I mean? 456 00:22:02,840 --> 00:22:05,120 Speaker 2: This girl was what seven at the time, I guess, 457 00:22:05,119 --> 00:22:07,399 Speaker 2: and now she's older. But so when you had ten 458 00:22:07,520 --> 00:22:09,679 Speaker 2: year olds eleven year olds, at what point do you 459 00:22:09,840 --> 00:22:11,879 Speaker 2: not have an aid or a teacher going into the 460 00:22:11,920 --> 00:22:14,000 Speaker 2: bathroom with the with the kids. 461 00:22:14,880 --> 00:22:16,399 Speaker 3: I really don't know the answer. 462 00:22:16,200 --> 00:22:21,040 Speaker 2: To that, and I think we're very attuned to these 463 00:22:21,040 --> 00:22:23,600 Speaker 2: sorts of things happening today. That's not to say they 464 00:22:23,600 --> 00:22:25,560 Speaker 2: didn't happen in the past, but in the past, I 465 00:22:25,560 --> 00:22:28,720 Speaker 2: think it was more likely to be swept under the rug. Sadly, 466 00:22:29,760 --> 00:22:31,239 Speaker 2: I think there's probably a lot of people who were 467 00:22:31,320 --> 00:22:35,000 Speaker 2: victims of sexual assault in the past where it was thought, oh, 468 00:22:35,000 --> 00:22:37,600 Speaker 2: you know, kids will be kids. No, no, no, again, 469 00:22:38,200 --> 00:22:40,040 Speaker 2: if this were like a kissing club, you break it up, 470 00:22:40,040 --> 00:22:41,479 Speaker 2: you go with the kids will be kids. But this 471 00:22:41,520 --> 00:22:47,959 Speaker 2: turned into something far worse, and that is inexcusable. And then, sadly, 472 00:22:48,040 --> 00:22:52,560 Speaker 2: we've got this this culture of silence that goes on. 473 00:22:52,640 --> 00:22:54,720 Speaker 2: As they said, it's not the first time that there's 474 00:22:54,720 --> 00:22:57,520 Speaker 2: been people and you know, complaints about this sort of stuff, 475 00:22:58,720 --> 00:23:01,800 Speaker 2: and we would be the last or more kids going 476 00:23:01,880 --> 00:23:03,239 Speaker 2: to come forward. 477 00:23:04,280 --> 00:23:05,879 Speaker 3: There's the That's the other question. 478 00:23:07,840 --> 00:23:11,240 Speaker 2: Is this a widespread issue where you've got multiple victims 479 00:23:11,400 --> 00:23:14,239 Speaker 2: and we're only at the beginning. That's terrifying. And I 480 00:23:14,240 --> 00:23:16,000 Speaker 2: also don't think this is the only place that this 481 00:23:16,040 --> 00:23:20,080 Speaker 2: sort of thing is happening. So again, hopefully we can 482 00:23:20,119 --> 00:23:22,960 Speaker 2: break this culture of silence. You know, we went through 483 00:23:22,960 --> 00:23:24,480 Speaker 2: the Me Too era, and I thought we shined a 484 00:23:24,560 --> 00:23:26,800 Speaker 2: light on a lot of poor behavior. But the stuff's 485 00:23:26,800 --> 00:23:30,240 Speaker 2: happening in our schools, and I don't know that everybody 486 00:23:30,280 --> 00:23:32,680 Speaker 2: learned the lesson when we went through that, So maybe 487 00:23:32,720 --> 00:23:34,320 Speaker 2: we need to make sure we're protecting the kids. 488 00:23:34,560 --> 00:23:36,480 Speaker 3: Good lord, you think we'd be protecting the kids of all. 489 00:23:36,400 --> 00:23:40,360 Speaker 2: The talk about billionaire pedophiles and all that other garbage 490 00:23:40,400 --> 00:23:42,880 Speaker 2: is going on. Things to Epstein and the other questions. 491 00:23:42,880 --> 00:23:45,160 Speaker 2: But oh no, it wouldn't happen to my neighborhood. 492 00:23:45,200 --> 00:23:47,800 Speaker 3: No, it is. It is. It's horrifying. 493 00:23:48,800 --> 00:23:50,480 Speaker 2: I can't even imagine if you're a parent you find 494 00:23:50,480 --> 00:23:52,919 Speaker 2: out that this is happening to your kid, I cannot imagine. 495 00:23:53,840 --> 00:23:57,040 Speaker 2: I'm sorry, parents, I'm so sorry you're dealing with that. 496 00:23:57,080 --> 00:24:00,280 Speaker 2: I don't even know where you start, all right, Him 497 00:24:00,320 --> 00:24:04,880 Speaker 2: is the most lovable, cuddly and vicious officer being laid 498 00:24:04,880 --> 00:24:08,000 Speaker 2: to rest the community morning. Rightfully so, because this officer's 499 00:24:08,000 --> 00:24:11,840 Speaker 2: whole life was meant to do one thing, protect other officers. 500 00:24:11,840 --> 00:24:14,560 Speaker 2: You're about to hear the incredible story of Officer Spike. 501 00:24:15,359 --> 00:24:15,639 Speaker 3: Next. 502 00:24:15,640 --> 00:24:18,000 Speaker 2: I'm Chris Merrill. I am six forty Live everywhere in 503 00:24:18,000 --> 00:24:18,639 Speaker 2: the iHeartRadio. 504 00:24:19,520 --> 00:24:22,960 Speaker 1: You're listening to KFI AM six forty on demand. 505 00:24:27,320 --> 00:24:29,359 Speaker 2: If you're looking for the show, will you old podcast 506 00:24:29,480 --> 00:24:31,520 Speaker 2: is going to be available on demand k if I 507 00:24:31,560 --> 00:24:35,480 Speaker 2: AM six forty dot com. Slash featured podcasts or don't 508 00:24:35,480 --> 00:24:35,960 Speaker 2: slash it. 509 00:24:36,080 --> 00:24:38,960 Speaker 3: Just look for it. Just featured. Just go just go 510 00:24:38,960 --> 00:24:41,719 Speaker 3: to the website, look for featured podcast. Just do that. 511 00:24:42,359 --> 00:24:46,600 Speaker 3: Just do that. Okay. What's happening in the job market? 512 00:24:46,600 --> 00:24:47,200 Speaker 3: Things to ai? 513 00:24:48,520 --> 00:24:52,000 Speaker 2: Well, if you are one person on the program, you 514 00:24:52,000 --> 00:24:54,359 Speaker 2: believe that there's a massive bubble that's going to burst 515 00:24:54,520 --> 00:24:56,560 Speaker 2: and the whole world is going to come crashing down, 516 00:24:56,640 --> 00:25:00,680 Speaker 2: there still won't be any jobs. You're just a bundle 517 00:25:00,720 --> 00:25:01,120 Speaker 2: of joy. 518 00:25:01,240 --> 00:25:05,840 Speaker 3: Ronner. Oh you were talking about me, Okay, all right, yeah, 519 00:25:05,880 --> 00:25:07,000 Speaker 3: I actually don't disagree with you. 520 00:25:07,720 --> 00:25:09,320 Speaker 2: We'll dive a little bit deeper into that coming up 521 00:25:09,320 --> 00:25:11,119 Speaker 2: here after marks eight o'clock news. I didn't want to 522 00:25:11,119 --> 00:25:13,879 Speaker 2: make mention of this today. They were they did a 523 00:25:14,000 --> 00:25:19,240 Speaker 2: service for the canine, the dog that got killed in 524 00:25:19,280 --> 00:25:20,240 Speaker 2: the line of duty. 525 00:25:20,320 --> 00:25:21,920 Speaker 3: ABC seven had the story he is. 526 00:25:21,840 --> 00:25:24,320 Speaker 9: Being called a hero because he gave the ultimate sacrifice 527 00:25:24,320 --> 00:25:27,199 Speaker 9: to protect his partner and other officers that night. But 528 00:25:27,359 --> 00:25:30,600 Speaker 9: the apartment says behind Spikes canine badge was just a 529 00:25:30,640 --> 00:25:31,800 Speaker 9: good boy. 530 00:25:31,720 --> 00:25:44,040 Speaker 4: Oh who wanted to make his people, especially his partner, proud. 531 00:25:45,600 --> 00:25:48,200 Speaker 2: Those last call those you know the radio, the last 532 00:25:48,200 --> 00:25:51,919 Speaker 2: calls on the radio. I cry every time anyway, and 533 00:25:51,960 --> 00:25:55,119 Speaker 2: now it's for a dog. 534 00:25:57,359 --> 00:25:59,240 Speaker 3: What are they saying that? 535 00:26:01,480 --> 00:26:01,680 Speaker 5: Boy? 536 00:26:06,040 --> 00:26:09,960 Speaker 3: Brave boy. I told you to have. 537 00:26:11,520 --> 00:26:14,639 Speaker 2: Big guys with big, deep radio voices crying tonight. I 538 00:26:14,680 --> 00:26:18,160 Speaker 2: told you that was going to happen. It makes me sad. 539 00:26:18,480 --> 00:26:22,040 Speaker 9: An emotional tribute to a courageous canine cop. You gave 540 00:26:22,080 --> 00:26:27,560 Speaker 9: this community absolutely everything you had, and your legacy will 541 00:26:27,600 --> 00:26:31,919 Speaker 9: remain with us always. The City of Burbank honoring Spike, 542 00:26:32,240 --> 00:26:36,080 Speaker 9: known for his bravery, loyalty, and love. Sky five overhead 543 00:26:36,080 --> 00:26:40,359 Speaker 9: the procession from the Burbank Animal Shelter, the dogs flag 544 00:26:40,440 --> 00:26:43,679 Speaker 9: drap body brought into the police department for the last time. 545 00:26:44,119 --> 00:26:47,000 Speaker 9: A crowd including officers and their dogs from all over 546 00:26:47,080 --> 00:26:51,560 Speaker 9: southern California stood watch, remembering Spike's actions and impact. The 547 00:26:51,600 --> 00:26:55,320 Speaker 9: department grateful for the support from those grieving this loss. 548 00:26:55,280 --> 00:26:58,679 Speaker 3: And it just shows how tightened it this community in 549 00:26:58,680 --> 00:26:59,600 Speaker 3: the City of Burbank is. 550 00:27:00,040 --> 00:27:02,720 Speaker 2: Those are tough guys that are crying too. I'm not alone, 551 00:27:05,320 --> 00:27:09,199 Speaker 2: so sad. I cry more for the animals than I 552 00:27:09,240 --> 00:27:12,199 Speaker 2: do for people. The animals all they want to do 553 00:27:12,240 --> 00:27:18,240 Speaker 2: is protect their protect their person. So they had one mission. 554 00:27:19,200 --> 00:27:19,680 Speaker 3: That was it. 555 00:27:19,960 --> 00:27:22,479 Speaker 9: On November twenty second, Spike was shot and killed by 556 00:27:22,480 --> 00:27:24,399 Speaker 9: a suspect running from a traffic stop. 557 00:27:24,520 --> 00:27:25,440 Speaker 3: The four year old. 558 00:27:25,240 --> 00:27:28,280 Speaker 9: Belgian Malinwa spent just under two years with the department. 559 00:27:28,400 --> 00:27:31,719 Speaker 9: The canine was a dependable partner, catching bad guys and 560 00:27:31,760 --> 00:27:36,320 Speaker 9: going into dangerous situations ahead of others. It's good a 561 00:27:36,400 --> 00:27:40,200 Speaker 9: bond built on countless hours of training. Only other handlers 562 00:27:40,240 --> 00:27:41,119 Speaker 9: can understand. 563 00:27:41,320 --> 00:27:43,600 Speaker 7: All of our partners are partners with us more than 564 00:27:43,920 --> 00:27:44,879 Speaker 7: with our own families. 565 00:27:45,160 --> 00:27:49,880 Speaker 2: Yeah, believe it so, And honestly, they're probably easier to tolerate. 566 00:27:51,040 --> 00:27:52,560 Speaker 2: That's not an insult. I just know what it's like 567 00:27:52,600 --> 00:27:54,520 Speaker 2: being around the same person all day long. We all 568 00:27:54,560 --> 00:27:56,719 Speaker 2: went through COVID. If you had families when you were 569 00:27:56,720 --> 00:27:59,440 Speaker 2: going through Covido, it was tough. 570 00:28:00,160 --> 00:28:01,680 Speaker 3: The only saw us you had was the dog. 571 00:28:02,160 --> 00:28:04,640 Speaker 7: Oh, it's very hard when one of us loses one 572 00:28:04,680 --> 00:28:05,400 Speaker 7: of our partners. 573 00:28:05,640 --> 00:28:06,119 Speaker 3: It's hard. 574 00:28:07,000 --> 00:28:09,400 Speaker 7: We send these dogs into places that we wouldn't want 575 00:28:09,400 --> 00:28:11,719 Speaker 7: to go as as a human. Yeah, and it's just 576 00:28:11,800 --> 00:28:13,919 Speaker 7: what we live with every day, knowing we may not 577 00:28:13,960 --> 00:28:14,439 Speaker 7: bring them home. 578 00:28:14,840 --> 00:28:16,680 Speaker 1: It wasn't just a police canine. 579 00:28:16,720 --> 00:28:19,159 Speaker 9: He was a beloved member of the family for a 580 00:28:19,200 --> 00:28:22,640 Speaker 9: Banks Police chiefs spoke on behalf of Spike's partner, Officer 581 00:28:22,760 --> 00:28:24,200 Speaker 9: Corey Sallas. 582 00:28:24,000 --> 00:28:28,119 Speaker 10: His passing has left an unimaginable void in our hearts 583 00:28:28,560 --> 00:28:30,919 Speaker 10: that can never truly be filled. 584 00:28:32,320 --> 00:28:35,600 Speaker 2: Oh, you've ever had if you've ever lost an animal, 585 00:28:36,480 --> 00:28:37,760 Speaker 2: I used to have an argue. I had a program 586 00:28:37,840 --> 00:28:42,680 Speaker 2: director that was like, oh, dogs have no souls. You're 587 00:28:43,000 --> 00:28:47,000 Speaker 2: you're a curmudgeon. Love this PD But he didn't like dogs, 588 00:28:47,240 --> 00:28:51,000 Speaker 2: and that's a red flag. So we used to argue 589 00:28:51,000 --> 00:28:53,520 Speaker 2: about it all the time. But if you ever lost 590 00:28:53,520 --> 00:28:56,880 Speaker 2: an animal, and you know that, the heartbreak I mean 591 00:28:56,960 --> 00:29:01,080 Speaker 2: it is it's like losing a child. It is absolutely devastating, 592 00:29:01,600 --> 00:29:08,520 Speaker 2: devastating the thought of losing the animal because it was 593 00:29:08,560 --> 00:29:14,000 Speaker 2: protecting you from a danger has to compound that exponentially. 594 00:29:14,440 --> 00:29:17,240 Speaker 10: When you think of Spike, please remember him as a 595 00:29:17,360 --> 00:29:21,000 Speaker 10: hero that he is rust easy, our dear Spikey, Oh 596 00:29:21,120 --> 00:29:24,160 Speaker 10: you will always be loved and forever missed. 597 00:29:24,800 --> 00:29:27,320 Speaker 9: And the department says that Spike service serves as a 598 00:29:27,360 --> 00:29:31,640 Speaker 9: testament to the dedication, discipline, and heart that define a 599 00:29:31,760 --> 00:29:33,560 Speaker 9: true police canine. 600 00:29:33,800 --> 00:29:35,200 Speaker 3: Ah paupers. 601 00:29:36,560 --> 00:29:38,360 Speaker 2: Anyway, I wanted to make sure that we paid a 602 00:29:38,400 --> 00:29:41,280 Speaker 2: little bit of homage to the pup tonight makes me 603 00:29:41,320 --> 00:29:45,480 Speaker 2: so sad. It's all the way around, makes me so sad. 604 00:29:47,160 --> 00:29:48,800 Speaker 2: I really have nothing else to say, guys, I'm just 605 00:29:48,880 --> 00:29:50,320 Speaker 2: are we good? Well? 606 00:29:50,360 --> 00:29:52,440 Speaker 3: No, you went on a thing last night about how 607 00:29:53,120 --> 00:29:56,560 Speaker 3: broken hard you were when your dog died, and when 608 00:29:56,600 --> 00:30:00,000 Speaker 3: my cats died, I cried more than when my mother died. Yeah, 609 00:30:00,200 --> 00:30:02,040 Speaker 3: so I think that's a fairly common thing. 610 00:30:02,360 --> 00:30:04,800 Speaker 2: And imagine if the cat died in this case of 611 00:30:04,880 --> 00:30:08,480 Speaker 2: the dog while it was protecting you, like, oh, took 612 00:30:08,520 --> 00:30:11,440 Speaker 2: a bullet so that the assailant wasn't shooting at you. 613 00:30:11,560 --> 00:30:14,120 Speaker 3: Oh yeah, we don't deserve dogs. They're too No, we don't. 614 00:30:14,320 --> 00:30:14,800 Speaker 3: We don't. 615 00:30:15,280 --> 00:30:17,760 Speaker 2: They're gonna, is this right, They're gonna do something for 616 00:30:17,840 --> 00:30:19,960 Speaker 2: him in the Rose Parade. Yeah, that's what I'm saying too. 617 00:30:21,120 --> 00:30:25,680 Speaker 2: Larger makeshift memorial formed outside of police headquarters, Burbank trees, 618 00:30:25,680 --> 00:30:30,040 Speaker 2: handwritten notes, spikes, end of watch on the Facebook page. 619 00:30:30,080 --> 00:30:33,280 Speaker 2: And then I'm gonna be memorialized in Burbank's twenty twenty 620 00:30:33,280 --> 00:30:39,000 Speaker 2: six Rose Parade float themed All Pause on Deck, so 621 00:30:39,040 --> 00:30:41,920 Speaker 2: that will highlight animal rescue work and feature tributes to 622 00:30:42,120 --> 00:30:46,320 Speaker 2: Spike's bravery. I know those of you who are not 623 00:30:46,360 --> 00:30:49,080 Speaker 2: animal lovers, you're like, why is this SAP crying on 624 00:30:49,120 --> 00:30:53,960 Speaker 2: the radio over a dog he's never met? Well, what 625 00:30:54,080 --> 00:30:59,360 Speaker 2: can I say? I'm a big softy. You probably have 626 00:30:59,400 --> 00:31:03,520 Speaker 2: heard the the liners that we have running. They say, 627 00:31:03,560 --> 00:31:07,480 Speaker 2: you know, one hundred percent human, guaranteed human. Mark went 628 00:31:07,520 --> 00:31:09,360 Speaker 2: off on this earlier in the show too, where he 629 00:31:09,400 --> 00:31:11,880 Speaker 2: was saying he was very proud of the company because 630 00:31:11,880 --> 00:31:14,160 Speaker 2: the company is committed to having one hundred percent human, 631 00:31:14,680 --> 00:31:18,520 Speaker 2: and I think that's outstanding. I wish more companies were 632 00:31:18,520 --> 00:31:21,480 Speaker 2: doing that because they're not. And when you find out 633 00:31:21,520 --> 00:31:25,400 Speaker 2: how many could replace us, it's going to blow your mind. 634 00:31:25,680 --> 00:31:29,240 Speaker 2: That is next. Chris Merrill KFI AM six forty. We're 635 00:31:29,280 --> 00:31:30,880 Speaker 2: live everywhere in the iHeartRadio app 636 00:31:31,360 --> 00:31:33,920 Speaker 1: KFI AM six forty on demand