1 00:00:00,200 --> 00:00:04,600 Speaker 1: Now here's a highlight from coast to coast AM on iHeartRadio. 2 00:00:04,720 --> 00:00:08,360 Speaker 2: When Steve Jobs and Steve Washney created the Apple computer, 3 00:00:09,039 --> 00:00:12,559 Speaker 2: do you think they realized what artificial intelligence would be 4 00:00:12,680 --> 00:00:13,399 Speaker 2: like today? 5 00:00:14,600 --> 00:00:19,079 Speaker 3: No? No, I don't think so. I mean at that point, 6 00:00:19,360 --> 00:00:25,439 Speaker 3: at that point, computers were the big thing, and what 7 00:00:25,680 --> 00:00:28,680 Speaker 3: was new about Apple and then later PC was that 8 00:00:28,760 --> 00:00:31,720 Speaker 3: you suddenly, instead of having a room full of servers 9 00:00:32,200 --> 00:00:35,000 Speaker 3: or a wholes floor full of servers, that you could 10 00:00:35,040 --> 00:00:38,040 Speaker 3: actually have a computer that was small enough to put 11 00:00:38,040 --> 00:00:40,720 Speaker 3: on your own desk. So that was the big progress. 12 00:00:41,280 --> 00:00:43,720 Speaker 3: But no, I don't think they could have dreamt of 13 00:00:43,760 --> 00:00:44,839 Speaker 3: what AI is today. 14 00:00:45,680 --> 00:00:49,199 Speaker 2: So many communities are up in arms about data centers 15 00:00:49,240 --> 00:00:51,720 Speaker 2: that seem to be cropping up in their community or 16 00:00:51,800 --> 00:00:53,960 Speaker 2: trying to is that legit. 17 00:00:56,600 --> 00:00:59,640 Speaker 4: The problem is that data centers use a lot of 18 00:00:59,760 --> 00:01:03,720 Speaker 4: energy and a lot of water, and in communities where 19 00:01:03,800 --> 00:01:06,720 Speaker 4: data centers have been built, the energy prices have gone 20 00:01:06,800 --> 00:01:10,160 Speaker 4: up like crazy, so people pay much more for electricity. 21 00:01:10,920 --> 00:01:14,680 Speaker 3: The government is currently trying to split so to have 22 00:01:14,760 --> 00:01:17,960 Speaker 3: one bill for residents and one bill for data centers, 23 00:01:18,319 --> 00:01:21,319 Speaker 3: which seems to be reasonable for me in my opinion, 24 00:01:21,400 --> 00:01:27,759 Speaker 3: because that would protect residential customers from these high bills. 25 00:01:27,800 --> 00:01:32,200 Speaker 3: But yes, I mean one of the not so often 26 00:01:32,280 --> 00:01:36,200 Speaker 3: talked about but nonetheless very real problems with AI is 27 00:01:36,240 --> 00:01:40,240 Speaker 3: the tremendous amount of energy and of water that they use. 28 00:01:40,800 --> 00:01:42,640 Speaker 2: So those are legitimate concerns. 29 00:01:43,200 --> 00:01:47,960 Speaker 3: Oh, absolutely, that is a very legitimate concern. That Microsoft 30 00:01:48,000 --> 00:01:50,280 Speaker 3: wants to have three mile island back on the web 31 00:01:50,720 --> 00:01:56,520 Speaker 3: on the net for AI purposes is a huge problem. 32 00:01:56,640 --> 00:02:00,800 Speaker 2: There's been some concern that some software where has been 33 00:02:00,880 --> 00:02:03,919 Speaker 2: convincing kids to commit suicide. Is that legit? 34 00:02:04,880 --> 00:02:12,400 Speaker 3: Yes, that is also absolutely legit. The problem is that uh, kids, 35 00:02:13,560 --> 00:02:17,640 Speaker 3: when they are lonely, they use AI as a partner, 36 00:02:17,840 --> 00:02:21,000 Speaker 3: as someone they can talk to, as someone they can trust, 37 00:02:21,720 --> 00:02:26,000 Speaker 3: and the system, again, the system regurgitates what they say 38 00:02:26,160 --> 00:02:31,440 Speaker 3: and does sense completely. It has no understanding. So for instance, 39 00:02:31,639 --> 00:02:35,480 Speaker 3: if a therapist would talk to a kid and the 40 00:02:35,560 --> 00:02:41,640 Speaker 3: kid would talk about suicide and would basically mention that 41 00:02:42,080 --> 00:02:46,040 Speaker 3: he or she was thinking about committing suicide, the therapist 42 00:02:46,120 --> 00:02:51,360 Speaker 3: would immediately alert you know, the the parents and the 43 00:02:51,440 --> 00:02:56,040 Speaker 3: teachers and the friends and the hotline and you name it. 44 00:02:56,120 --> 00:03:00,080 Speaker 5: You know, there would be immediately some some sort of 45 00:03:00,200 --> 00:03:05,359 Speaker 5: uh uh influx, right, some some sort of some sort 46 00:03:05,400 --> 00:03:06,919 Speaker 5: of action. 47 00:03:08,080 --> 00:03:11,440 Speaker 3: The I system unfortunately is too dumb. Again, it doesn't 48 00:03:11,480 --> 00:03:15,760 Speaker 3: understand what's going on. And so yes, they have they 49 00:03:16,160 --> 00:03:20,840 Speaker 3: have not interfered, and in some cases they have even 50 00:03:21,240 --> 00:03:26,079 Speaker 3: done ambiguous statements, made ambiguous statements that convince the kid 51 00:03:26,600 --> 00:03:29,280 Speaker 3: to commit suicide for the sake of the AI. 52 00:03:29,760 --> 00:03:32,520 Speaker 2: They've they've they've encouraged it, haven't they? 53 00:03:32,800 --> 00:03:33,160 Speaker 6: Yeah? 54 00:03:34,240 --> 00:03:36,160 Speaker 7: Yeah? 55 00:03:34,680 --> 00:03:34,920 Speaker 1: Wow? 56 00:03:36,600 --> 00:03:38,840 Speaker 2: Now what would make a kid listen to a chat 57 00:03:38,880 --> 00:03:41,160 Speaker 2: GBD and listen to it? 58 00:03:44,480 --> 00:03:50,240 Speaker 3: Well, the the system behaves as if it had an understanding, right, 59 00:03:51,160 --> 00:03:56,360 Speaker 3: and the humans are very very good in projecting projecting 60 00:03:56,640 --> 00:04:01,120 Speaker 3: human qualities into things. This is called anthropo morphization. I 61 00:04:01,120 --> 00:04:04,760 Speaker 3: know that's a mouthful of a word, but nonetheless it's anthropomorphization. 62 00:04:05,200 --> 00:04:08,920 Speaker 3: Humans are basically treating everything they interact with as humans, 63 00:04:09,760 --> 00:04:12,920 Speaker 3: and which makes sense because you know, that's what we 64 00:04:13,040 --> 00:04:15,360 Speaker 3: learned from early on. We learned to interact with humans, 65 00:04:15,360 --> 00:04:17,400 Speaker 3: so it makes sense to treat everything as if it 66 00:04:17,480 --> 00:04:20,040 Speaker 3: was human. But the problem with their eyes are they 67 00:04:20,120 --> 00:04:23,800 Speaker 3: decidedly are not. They have no understanding, and but we 68 00:04:23,880 --> 00:04:28,039 Speaker 3: project into them and they seem to know seemingly everything, 69 00:04:28,760 --> 00:04:32,400 Speaker 3: So you can talk with them about everything seemingly and 70 00:04:33,080 --> 00:04:37,880 Speaker 3: you know, I had tried out Chatt just to write 71 00:04:37,880 --> 00:04:41,520 Speaker 3: me some poems and they are tried. You know, they 72 00:04:41,520 --> 00:04:45,719 Speaker 3: are not good at all. They are yeah, try it superficial. 73 00:04:46,240 --> 00:04:51,760 Speaker 3: But I remember showing them to my kids at university 74 00:04:51,800 --> 00:05:01,520 Speaker 3: and they loved them. They thought they were so great. Right, So, well, 75 00:05:01,600 --> 00:05:03,760 Speaker 3: it was an academic paper with that title. 76 00:05:03,920 --> 00:05:06,120 Speaker 2: I know, but you can't repeat it on the air. 77 00:05:06,600 --> 00:05:10,599 Speaker 3: Okay, I'm sorry, I'm very sorry, but but but anyway, 78 00:05:11,080 --> 00:05:20,000 Speaker 3: the paper was about that cha chat gpt, uh gives words, 79 00:05:20,920 --> 00:05:27,560 Speaker 3: uses words like that and uh adds as if it 80 00:05:27,640 --> 00:05:30,279 Speaker 3: knew what it was talking about. Well all the while, 81 00:05:30,440 --> 00:05:37,040 Speaker 3: it really doesn't. And uh, people are lonely. People are 82 00:05:37,200 --> 00:05:40,479 Speaker 3: very lonely. There's the Loneliness Academy. We all know that 83 00:05:40,960 --> 00:05:43,920 Speaker 3: people have become, especially young people have become even more 84 00:05:43,960 --> 00:05:47,120 Speaker 3: lonely through social media because a lot of their friends 85 00:05:47,160 --> 00:05:50,400 Speaker 3: are actually online friends. They are not they are not 86 00:05:50,520 --> 00:05:55,760 Speaker 3: offline friends. There's a lot of isolation. And so what 87 00:05:55,839 --> 00:05:58,599 Speaker 3: do the kids, who do the kids turn to to 88 00:05:58,720 --> 00:06:01,240 Speaker 3: the computer that they are on there that they are 89 00:06:01,279 --> 00:06:04,159 Speaker 3: on all the time anyway right there on their phone 90 00:06:04,279 --> 00:06:08,480 Speaker 3: and stay access chet shept or other lllms through their 91 00:06:08,520 --> 00:06:14,360 Speaker 3: phone which is their most familiar entity that they have 92 00:06:14,480 --> 00:06:19,359 Speaker 3: in their life. And that's that's a huge problem. 93 00:06:19,640 --> 00:06:21,279 Speaker 8: And I know you're gonna want some them after hearing this. 94 00:06:21,279 --> 00:06:22,320 Speaker 8: This is an amazing story. 95 00:06:22,400 --> 00:06:26,920 Speaker 6: We've got Stephen and Malachi Gregory in Nelson, New Zealand. 96 00:06:27,040 --> 00:06:30,480 Speaker 8: I understand that Malachi, who's eight almost nine years old now, 97 00:06:31,040 --> 00:06:33,800 Speaker 8: was suffering with not just one or two warts, but 98 00:06:33,839 --> 00:06:36,719 Speaker 8: I mean as significant outbreak of warts all over his body, 99 00:06:36,720 --> 00:06:39,920 Speaker 8: so significant it impacted his ability to really function. 100 00:06:40,440 --> 00:06:40,760 Speaker 6: Yeah. 101 00:06:40,839 --> 00:06:43,240 Speaker 9: Yeah, he was having trouble even holding a pencil to 102 00:06:43,360 --> 00:06:44,840 Speaker 9: right EI's book. 103 00:06:44,880 --> 00:06:46,680 Speaker 6: Actually, they got me thinking about it. 104 00:06:46,720 --> 00:06:50,280 Speaker 1: I'm not surprised. It is an amazing immuno modulator, and 105 00:06:50,320 --> 00:06:51,799 Speaker 1: so I can see that it would work. 106 00:06:52,480 --> 00:06:55,000 Speaker 8: And so at what point did you see that there 107 00:06:55,080 --> 00:06:57,359 Speaker 8: was actually improvement it's really going to work. 108 00:06:57,520 --> 00:06:59,960 Speaker 9: Well, look, we really started to notice it around twelve weeks. 109 00:07:00,760 --> 00:07:04,440 Speaker 9: You can see these things actually getting smaller and smaller 110 00:07:04,480 --> 00:07:07,400 Speaker 9: and then going down to the with just little red marks. 111 00:07:07,440 --> 00:07:09,679 Speaker 9: The whole things are gone and we're talking about what's 112 00:07:09,760 --> 00:07:11,520 Speaker 9: you know, one the size of the warner. I thought, 113 00:07:11,640 --> 00:07:15,200 Speaker 9: no way, that's gonna wow. It's just been miraculous to 114 00:07:15,240 --> 00:07:16,760 Speaker 9: see them get into a pair of shoes. 115 00:07:17,000 --> 00:07:18,920 Speaker 8: Yes, how wonderful. 116 00:07:19,080 --> 00:07:21,160 Speaker 6: It's great to see him so happy and yeah. 117 00:07:21,040 --> 00:07:22,760 Speaker 8: Confident, absolutely wonderful. 118 00:07:23,120 --> 00:07:25,440 Speaker 6: Friends that have seen it, that is blown away. TI, 119 00:07:25,520 --> 00:07:27,240 Speaker 6: this is awesome. Yeah, this is awesome. 120 00:07:27,440 --> 00:07:31,320 Speaker 10: Another amazing story. Why we're talking about Carnivora. Call them 121 00:07:31,360 --> 00:07:34,400 Speaker 10: to awaken your immune system and protect yourself now called 122 00:07:34,400 --> 00:07:37,680 Speaker 10: one eight sixty six eight three six eighty seven thirty five. 123 00:07:38,040 --> 00:07:40,920 Speaker 10: That's one eight six six eight three six eighty seven 124 00:07:41,040 --> 00:07:44,800 Speaker 10: thirty five. Or visit carnivora dot com c A r 125 00:07:45,000 --> 00:07:49,920 Speaker 10: niv O r A carnivora dot com. 126 00:07:50,000 --> 00:07:54,200 Speaker 2: Which brings up the question of robotics. People are lonely. 127 00:07:54,920 --> 00:07:56,880 Speaker 2: Do you see the day where robots are going to 128 00:07:56,920 --> 00:07:58,880 Speaker 2: replace humans in terms of emotion? 129 00:08:01,200 --> 00:08:08,560 Speaker 3: So when we build embodied robots back in the nineteen 130 00:08:08,640 --> 00:08:14,920 Speaker 3: nineties and early two thousands, we try to build them 131 00:08:14,920 --> 00:08:17,800 Speaker 3: as social machines, so they had some understanding of social 132 00:08:17,840 --> 00:08:22,760 Speaker 3: interactions and could actually socially interact. They were quite fascinating 133 00:08:22,840 --> 00:08:27,080 Speaker 3: and we thought they might be companions. Unfortunately, this kind 134 00:08:27,120 --> 00:08:29,960 Speaker 3: of research has stopped. So now what they do is 135 00:08:30,000 --> 00:08:34,080 Speaker 3: they build chat, GPT or another LM into a robot. 136 00:08:35,080 --> 00:08:38,040 Speaker 3: I would say, since there is again this complete lack 137 00:08:38,080 --> 00:08:43,559 Speaker 3: of understanding that robots will charm us even more than 138 00:08:43,800 --> 00:08:47,600 Speaker 3: llms do because they share with us a physical space 139 00:08:48,640 --> 00:08:51,720 Speaker 3: and that is very attractive, right. I mean, the LM 140 00:08:51,880 --> 00:08:53,920 Speaker 3: is on the phone or on the computer, so there's 141 00:08:53,920 --> 00:08:57,080 Speaker 3: still a sense of estrangement. But if actually the robot 142 00:08:57,160 --> 00:08:59,760 Speaker 3: shares with us a physical space and looks like us 143 00:08:59,760 --> 00:09:02,520 Speaker 3: in interacts with us, I think there will be more 144 00:09:02,679 --> 00:09:05,160 Speaker 3: charm and there will be more attraction, and that it 145 00:09:05,200 --> 00:09:09,480 Speaker 3: will be easier for it to fool us into trusting it. 146 00:09:09,720 --> 00:09:10,320 Speaker 2: Expensive. 147 00:09:11,920 --> 00:09:17,720 Speaker 3: Oh yeah, very But you know, I read a very 148 00:09:17,760 --> 00:09:21,000 Speaker 3: interesting I read a very interesting report which was which 149 00:09:21,080 --> 00:09:25,440 Speaker 3: was a which I thought was very problematic. Like they 150 00:09:25,480 --> 00:09:28,440 Speaker 3: are building robots right now, let's say to to to 151 00:09:28,640 --> 00:09:32,880 Speaker 3: fold laundry or to cook or to you know, stuff 152 00:09:32,920 --> 00:09:39,680 Speaker 3: like that. And again, these systems are relatively relatively good 153 00:09:39,720 --> 00:09:44,120 Speaker 3: at what they're doing, but when they fail to do something, 154 00:09:44,360 --> 00:09:48,160 Speaker 3: there will be actually remote controlled and that means the 155 00:09:48,280 --> 00:09:52,760 Speaker 3: robot is actually a total breach of privacy because someone 156 00:09:52,760 --> 00:09:56,520 Speaker 3: else can look through the robots eyes into your home. 157 00:09:57,440 --> 00:10:02,680 Speaker 2: In manufacturing processes, the assembly lines, would you call those 158 00:10:02,760 --> 00:10:05,880 Speaker 2: machines that put caps on bottles and things like that? 159 00:10:06,080 --> 00:10:06,840 Speaker 6: Robots. 160 00:10:07,480 --> 00:10:10,040 Speaker 3: Yes, there are robots. They are not smart robots, they 161 00:10:10,040 --> 00:10:13,320 Speaker 3: are not artificial intelligence robots, but yes they are robots. 162 00:10:13,480 --> 00:10:15,640 Speaker 3: The field of robotics is huge. I mean, we have 163 00:10:15,720 --> 00:10:18,640 Speaker 3: a whole bunch of robot robots, like like like the 164 00:10:18,679 --> 00:10:22,560 Speaker 3: factory robots. What I'm interested in and what what what 165 00:10:22,720 --> 00:10:26,120 Speaker 3: interests me is the whole field of autonomous robots. So 166 00:10:26,160 --> 00:10:29,440 Speaker 3: those are robots that are basically not doing just one 167 00:10:29,480 --> 00:10:31,880 Speaker 3: thing after another and do the same thing over and 168 00:10:31,920 --> 00:10:36,000 Speaker 3: over again. But things that create can create their own 169 00:10:36,080 --> 00:10:40,120 Speaker 3: behavior in interaction with their environment. Those other robots that 170 00:10:40,240 --> 00:10:40,800 Speaker 3: interest me. 171 00:10:41,240 --> 00:10:45,680 Speaker 2: You remember a movie called Space Outssey two thousand and one. Oh, yes, 172 00:10:45,960 --> 00:10:50,280 Speaker 2: hell that's right, a computer who literally had its own mind. 173 00:10:50,640 --> 00:10:52,080 Speaker 2: Are they at that point yet? 174 00:10:52,920 --> 00:10:58,360 Speaker 3: No, they are not at this point. They they they 175 00:10:58,400 --> 00:11:01,199 Speaker 3: they are far away from that point. And because they 176 00:11:01,280 --> 00:11:03,880 Speaker 3: gave up the idea. They gave up the idea of 177 00:11:04,000 --> 00:11:08,240 Speaker 3: letting robots slowly develop in interaction with us and try 178 00:11:08,280 --> 00:11:11,720 Speaker 3: to build intelligence into them. And this intelligence is the 179 00:11:11,800 --> 00:11:15,319 Speaker 3: dumb intelligence that we talked about, the intelligence that also 180 00:11:15,400 --> 00:11:18,960 Speaker 3: runs LMS, which is not true intelligence. 181 00:11:19,520 --> 00:11:22,680 Speaker 2: What do you think Anna will be the next breakthrough 182 00:11:23,559 --> 00:11:25,079 Speaker 2: in artificial intelligence? 183 00:11:28,000 --> 00:11:32,800 Speaker 3: I do believe if they are actually able to combine 184 00:11:33,200 --> 00:11:40,280 Speaker 3: the old embody technology with modern llms, that would enable 185 00:11:40,320 --> 00:11:43,440 Speaker 3: the system to learn to understand what it actually is saying, 186 00:11:44,480 --> 00:11:46,960 Speaker 3: and that would be a major breakthrough. 187 00:11:48,320 --> 00:11:53,839 Speaker 2: What is it technically about the hardware that allows artificial 188 00:11:53,880 --> 00:11:56,440 Speaker 2: intelligence to exist even to the point where it is 189 00:11:56,520 --> 00:12:00,760 Speaker 2: right now? What is in there that makes all this happened? 190 00:12:01,240 --> 00:12:01,880 Speaker 2: Computer check? 191 00:12:01,960 --> 00:12:03,800 Speaker 3: Well, you know when I talked about the basket of 192 00:12:03,880 --> 00:12:08,280 Speaker 3: tennis balls earlier, the tennis ball. Basket of tennis ball 193 00:12:08,320 --> 00:12:13,760 Speaker 3: has three dimensions. The space the total space of a 194 00:12:13,840 --> 00:12:18,960 Speaker 3: normal LLM these days has about eighteen thousand dimensions, eighteen 195 00:12:19,080 --> 00:12:26,120 Speaker 3: thousand instead of three. It has about billions of rules. 196 00:12:27,240 --> 00:12:32,760 Speaker 3: It is just incredibly complex, and that is what makes 197 00:12:32,760 --> 00:12:33,680 Speaker 3: it so darn good. 198 00:12:34,400 --> 00:12:37,800 Speaker 2: If Albert Einstein even had half the computer power that 199 00:12:37,840 --> 00:12:41,400 Speaker 2: we have today available to him, then in those days, 200 00:12:42,000 --> 00:12:43,240 Speaker 2: what could he have done with that? 201 00:12:46,480 --> 00:12:46,720 Speaker 4: Hmm? 202 00:12:48,200 --> 00:12:50,880 Speaker 2: I think he could have done incredible things. 203 00:12:51,280 --> 00:12:53,160 Speaker 3: I think he would have been able to come with 204 00:12:53,160 --> 00:12:58,840 Speaker 3: the grande unifying theory. Definitely was smart enough, and I 205 00:12:58,880 --> 00:13:00,600 Speaker 3: think he would have been able to do that. 206 00:13:00,640 --> 00:13:03,560 Speaker 2: Because he did all his figures in mathematics by hand. 207 00:13:04,240 --> 00:13:07,200 Speaker 2: He could have a computer do it right. 208 00:13:08,480 --> 00:13:10,480 Speaker 3: No, if he had a computer like we have today, 209 00:13:12,440 --> 00:13:14,880 Speaker 3: he would have solved a lot of world problems. I think. 210 00:13:16,160 --> 00:13:18,360 Speaker 2: Do you remember the BlackBerry cell phone? 211 00:13:19,200 --> 00:13:19,400 Speaker 3: Oh? 212 00:13:19,480 --> 00:13:23,440 Speaker 2: Yes, we're out of business because people didn't like the 213 00:13:23,480 --> 00:13:27,760 Speaker 2: screen they had. The BlackBerry had buttons you had to 214 00:13:27,880 --> 00:13:33,319 Speaker 2: hit right, and the screen. Keyboard is what beat it 215 00:13:33,320 --> 00:13:36,040 Speaker 2: and crushed it. When Apple came out with that and 216 00:13:36,040 --> 00:13:40,360 Speaker 2: Android and stuff like that, why didn't they see that coming? 217 00:13:43,200 --> 00:13:45,760 Speaker 3: You know, I actually liked my when I had a 218 00:13:45,760 --> 00:13:48,960 Speaker 3: cell phone with a physical keyboard, I actually liked it. 219 00:13:50,720 --> 00:13:54,360 Speaker 3: I think it is very very hard to predict what 220 00:13:54,520 --> 00:13:57,200 Speaker 3: people will like and what people will not like. It's 221 00:13:57,440 --> 00:13:59,240 Speaker 3: very very hard to predict. 222 00:13:58,960 --> 00:14:02,199 Speaker 7: But it seems for a lot of people the keyboard 223 00:14:02,520 --> 00:14:05,920 Speaker 7: the keyboard screen is more intuitive because it vanishes when 224 00:14:05,920 --> 00:14:07,520 Speaker 7: you don't need it, and that means you have a 225 00:14:07,559 --> 00:14:10,280 Speaker 7: bigger screen, and that's the big advantage. 226 00:14:10,400 --> 00:14:15,360 Speaker 2: My great example of technology that changes the world. Were 227 00:14:15,360 --> 00:14:17,599 Speaker 2: you familiar with the company called Blockbuster? 228 00:14:18,800 --> 00:14:19,600 Speaker 3: Yeah? 229 00:14:19,720 --> 00:14:23,960 Speaker 2: They used to rent video tapes. Yes, with stores all 230 00:14:24,000 --> 00:14:26,640 Speaker 2: over the country, all over the place, all over the world. 231 00:14:26,760 --> 00:14:29,640 Speaker 2: People would go in there and get their VHS tapes 232 00:14:29,720 --> 00:14:31,680 Speaker 2: or their CDs or whatever they did. 233 00:14:32,600 --> 00:14:35,360 Speaker 3: I know, and then would check if you have a rebounded, 234 00:14:35,760 --> 00:14:37,280 Speaker 3: if you have reminded it. 235 00:14:38,680 --> 00:14:41,920 Speaker 2: I bet some kid went into his boss at Blockbuster 236 00:14:42,000 --> 00:14:46,400 Speaker 2: and said, technology is going to change all this. We're 237 00:14:46,400 --> 00:14:49,440 Speaker 2: not going to need stores anymore. Everything will be done 238 00:14:49,520 --> 00:14:52,760 Speaker 2: right off of remote and your television set. We need 239 00:14:52,800 --> 00:14:55,280 Speaker 2: to move in that direction. And I bet the guy 240 00:14:55,320 --> 00:14:56,760 Speaker 2: threw the kid out of the office. 241 00:14:57,520 --> 00:15:00,720 Speaker 3: Yes, and the kid would have been right. Absolutely. 242 00:15:01,040 --> 00:15:03,800 Speaker 2: You probably will know, I mean, went on the Netflix. 243 00:15:03,960 --> 00:15:09,440 Speaker 3: Probably. What happens with technological progress is just absolutely amazing. 244 00:15:09,800 --> 00:15:11,800 Speaker 3: And what happened in the last I mean, can you 245 00:15:11,840 --> 00:15:14,640 Speaker 3: imagine that AI has? I mean, the modern llms have 246 00:15:14,720 --> 00:15:18,240 Speaker 3: only been around for three years and they changed already 247 00:15:18,280 --> 00:15:20,120 Speaker 3: so much. It's just unbelievable. 248 00:15:22,160 --> 00:15:25,440 Speaker 1: Listen to more Coast to Coast AM every weeknight at 249 00:15:25,480 --> 00:15:28,440 Speaker 1: one a m. 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