1 00:00:00,240 --> 00:00:04,600 Speaker 1: Now here's a highlight from Coast to Coast AM on iHeartRadio. 2 00:00:05,080 --> 00:00:08,080 Speaker 2: You are listening to Coast to Coast AM. Connie willis 3 00:00:08,160 --> 00:00:11,800 Speaker 2: here and join the music right there along with you. 4 00:00:11,920 --> 00:00:14,560 Speaker 2: I'm glad that you do like what we've got going on. Again, 5 00:00:14,600 --> 00:00:18,239 Speaker 2: Thanks for all the texting and the tweeting and all 6 00:00:18,280 --> 00:00:20,520 Speaker 2: that you do. I really do appreciate it. You are 7 00:00:20,720 --> 00:00:23,840 Speaker 2: very very kind. Just a reminder too, when I was 8 00:00:23,880 --> 00:00:26,840 Speaker 2: on last weekend for Richard Serett and prayer still going 9 00:00:26,880 --> 00:00:31,319 Speaker 2: to him and his family, I wanted we had on 10 00:00:31,480 --> 00:00:39,040 Speaker 2: the air Douglas James Cottrell and he he had website problems, 11 00:00:39,400 --> 00:00:41,480 Speaker 2: so he was talking about a class that he had 12 00:00:41,479 --> 00:00:45,120 Speaker 2: for fifty bucks you can learn about him and what 13 00:00:45,200 --> 00:00:47,520 Speaker 2: you can do and what he can do and all 14 00:00:47,520 --> 00:00:52,160 Speaker 2: that good stuff, which is an incredible price. So definitely 15 00:00:52,240 --> 00:00:55,480 Speaker 2: go to it. But I just wanted to clear up 16 00:00:55,760 --> 00:00:58,160 Speaker 2: the site to go to because a lot of you 17 00:00:58,240 --> 00:01:01,279 Speaker 2: contacted me on that, and it would be just go 18 00:01:01,400 --> 00:01:03,800 Speaker 2: to the store that he has, which would be Douglas 19 00:01:04,600 --> 00:01:07,520 Speaker 2: James Kytrell and that co O T, T R, E 20 00:01:07,720 --> 00:01:11,880 Speaker 2: L L store dot com and then right there on 21 00:01:11,920 --> 00:01:14,640 Speaker 2: the front it's got for his class. So I just 22 00:01:14,680 --> 00:01:17,240 Speaker 2: wanted to make that clear because he was having problems 23 00:01:17,240 --> 00:01:18,959 Speaker 2: with the site. So that's where you want to go. 24 00:01:19,080 --> 00:01:22,840 Speaker 2: Make sure it's the store, okay. Also, those of you 25 00:01:22,880 --> 00:01:25,399 Speaker 2: to go that go to Connie Willis dot com to 26 00:01:25,480 --> 00:01:28,200 Speaker 2: my site and join my shows, or even if you 27 00:01:28,319 --> 00:01:31,880 Speaker 2: just go to the email list, always make sure afterwards, 28 00:01:31,880 --> 00:01:35,640 Speaker 2: specially if you get involved in the email list and 29 00:01:36,160 --> 00:01:39,760 Speaker 2: put your name in and your your email address, what 30 00:01:39,880 --> 00:01:42,880 Speaker 2: happens is you should get an email right back directly. 31 00:01:43,360 --> 00:01:47,080 Speaker 2: So make sure you go immediately after you sign in, 32 00:01:47,160 --> 00:01:50,120 Speaker 2: you know, within a minute or so, and make sure 33 00:01:50,160 --> 00:01:52,600 Speaker 2: that you get the email that says thank you, we've 34 00:01:52,640 --> 00:01:56,240 Speaker 2: got you included. Because a lot of times these servers 35 00:01:56,320 --> 00:02:00,880 Speaker 2: will well say it's spam, and you know you got 36 00:02:00,880 --> 00:02:04,920 Speaker 2: to give it permissions to accept it. So if you 37 00:02:04,960 --> 00:02:06,800 Speaker 2: do go to Connie Willis dot com and say I 38 00:02:06,840 --> 00:02:09,240 Speaker 2: want to get on your email list, Connie, make sure 39 00:02:09,280 --> 00:02:13,400 Speaker 2: after you sign in, just go to your mail Okay, 40 00:02:13,560 --> 00:02:15,360 Speaker 2: just give it a minute or so and go in 41 00:02:15,400 --> 00:02:18,880 Speaker 2: there and if you don't see anything, check your trash, junk, spam, 42 00:02:19,000 --> 00:02:23,600 Speaker 2: whatever you have your mailing system, and if you see 43 00:02:23,600 --> 00:02:26,360 Speaker 2: it there, it will say do you trust this or 44 00:02:26,400 --> 00:02:28,640 Speaker 2: it'll ask you that and just say yes so you 45 00:02:28,680 --> 00:02:30,880 Speaker 2: can start getting Otherwise you'll miss all the good stuff. 46 00:02:30,880 --> 00:02:32,040 Speaker 2: And I don't want you to do that. I don't 47 00:02:32,040 --> 00:02:34,160 Speaker 2: want you to do that. So open lines. 48 00:02:34,280 --> 00:02:34,760 Speaker 3: We've got. 49 00:02:35,080 --> 00:02:37,079 Speaker 2: Our guest is going to stick around with us, Doctor 50 00:02:37,160 --> 00:02:40,840 Speaker 2: Eric Castletein that has done so many things in his life, 51 00:02:40,880 --> 00:02:42,959 Speaker 2: and he's going to continue on because he is just 52 00:02:43,040 --> 00:02:47,120 Speaker 2: that man. You know, one day you know it all, 53 00:02:47,240 --> 00:02:49,880 Speaker 2: you know, we meet our maker. You're going to be 54 00:02:49,919 --> 00:02:53,480 Speaker 2: working and having fun and smiling and inventing and doing 55 00:02:53,480 --> 00:02:56,000 Speaker 2: all this until that last second. I just know you're 56 00:02:56,040 --> 00:02:58,959 Speaker 2: one of them. I'm with you, and doctor Chris is 57 00:02:59,000 --> 00:03:02,840 Speaker 2: the same. And I appreciate that in you. I appreciate 58 00:03:02,880 --> 00:03:03,320 Speaker 2: that in you. 59 00:03:04,639 --> 00:03:09,280 Speaker 4: Well. Thanks. Like I say, I sometimes tell people I'm 60 00:03:09,919 --> 00:03:12,440 Speaker 4: Eric hazlteen PhD ADHD. 61 00:03:13,520 --> 00:03:18,360 Speaker 2: That's true. So before we hit the phones, I do 62 00:03:18,440 --> 00:03:22,280 Speaker 2: have a question that came to me that they won't 63 00:03:22,320 --> 00:03:23,760 Speaker 2: be able to call in, so I want to ask 64 00:03:23,800 --> 00:03:27,480 Speaker 2: you here. This is Tom Hill from Grain Valley, Missouri, 65 00:03:27,919 --> 00:03:30,040 Speaker 2: and he says he's got a question for you. He said, 66 00:03:30,080 --> 00:03:33,200 Speaker 2: how much of a voice sample would be needed to 67 00:03:33,400 --> 00:03:37,440 Speaker 2: recreate someone's voice? And he said, due to cancer surgery 68 00:03:37,480 --> 00:03:40,000 Speaker 2: and the follow up radiation treatment. I have lost my 69 00:03:40,160 --> 00:03:44,120 Speaker 2: voice and would love to have it back, even if artificial. 70 00:03:44,680 --> 00:03:47,040 Speaker 2: And it's interesting because you're saying, hey, there's so much 71 00:03:47,120 --> 00:03:49,520 Speaker 2: good and what a great reason why. 72 00:03:51,160 --> 00:03:54,680 Speaker 4: Yeah, well, it depends on what it is you wanted 73 00:03:54,760 --> 00:03:58,280 Speaker 4: to say and so forth. But generally, about ten minutes 74 00:03:59,480 --> 00:04:03,560 Speaker 4: is you need and the more variety there is, the better. 75 00:04:05,000 --> 00:04:08,720 Speaker 4: But I've seen people do a credible job with just 76 00:04:08,800 --> 00:04:12,520 Speaker 4: ten minutes. Some are less than that. They give you 77 00:04:12,720 --> 00:04:16,920 Speaker 4: specific words they want you to say. But I think 78 00:04:16,960 --> 00:04:19,760 Speaker 4: it would be definitely possible for him to if he 79 00:04:19,839 --> 00:04:26,520 Speaker 4: had samples of his voice from before. There are AI 80 00:04:26,640 --> 00:04:28,880 Speaker 4: platforms where you could train it up and then he 81 00:04:28,920 --> 00:04:31,520 Speaker 4: could just type in what he wants it to say 82 00:04:31,560 --> 00:04:33,760 Speaker 4: and it would come out in his voice. 83 00:04:35,160 --> 00:04:39,960 Speaker 2: Amazing that. You know, there's so much amazing things that 84 00:04:40,520 --> 00:04:42,120 Speaker 2: can't come out of this, Like you were saying that 85 00:04:42,160 --> 00:04:45,800 Speaker 2: we can't. I don't even think we can battle what's 86 00:04:45,839 --> 00:04:48,799 Speaker 2: out there. But I am concerned myself about the values 87 00:04:48,839 --> 00:04:51,480 Speaker 2: and the ethic part of it. Got to figure all 88 00:04:51,480 --> 00:04:53,719 Speaker 2: that out in all the laws, and I'm sure there'll 89 00:04:53,760 --> 00:04:56,200 Speaker 2: be some battles for that along the way. So let's 90 00:04:56,200 --> 00:05:04,080 Speaker 2: go to Wildcard line number one. Linn out of Orange County, California. Lynn, Welcome, 91 00:05:04,120 --> 00:05:07,800 Speaker 2: you're on coast to cos A in Yes, the doctor. 92 00:05:07,480 --> 00:05:10,080 Speaker 5: Said the past hour that we didn't have to worry 93 00:05:10,120 --> 00:05:15,200 Speaker 5: about AIS and emotions unless they were connected biologically to 94 00:05:15,839 --> 00:05:19,080 Speaker 5: sell that would create emotions, and then we'd have to 95 00:05:19,080 --> 00:05:22,880 Speaker 5: worry about that. But that could happen. It seems like 96 00:05:22,920 --> 00:05:26,039 Speaker 5: you should have said it has happened, because we've heard 97 00:05:26,080 --> 00:05:30,680 Speaker 5: all over the news already that they have cloned an embryo. 98 00:05:31,240 --> 00:05:33,599 Speaker 5: Don't worry. It doesn't have a brain and it doesn't 99 00:05:33,640 --> 00:05:37,440 Speaker 5: have a heart. But technically an AI doesn't need a 100 00:05:37,440 --> 00:05:40,600 Speaker 5: heart and it comes with its own brain. So technically, 101 00:05:40,680 --> 00:05:43,560 Speaker 5: if we're saying that now, we can pretty much be 102 00:05:43,680 --> 00:05:47,719 Speaker 5: guaranteed they've already created what would be equal to a terminator, 103 00:05:48,080 --> 00:05:53,240 Speaker 5: whether it's a robot with skin like embryo skin, it's 104 00:05:53,279 --> 00:05:57,440 Speaker 5: out there. So that's in the present tense. That's not 105 00:05:57,720 --> 00:06:00,479 Speaker 5: future tents could be. That's a present tense. 106 00:06:05,320 --> 00:06:08,200 Speaker 4: I don't think we're there yet. Yes, they have cloned 107 00:06:10,000 --> 00:06:15,000 Speaker 4: pretty significantly sized mammals like sheep, and there are rumors 108 00:06:15,040 --> 00:06:19,000 Speaker 4: of human cloning in Asian countries, but that's not the 109 00:06:19,040 --> 00:06:22,760 Speaker 4: same as giving them an AI. But I do think 110 00:06:22,800 --> 00:06:27,919 Speaker 4: you have a point, caller in that neuroprosthetics are a 111 00:06:27,960 --> 00:06:32,400 Speaker 4: big deal now where we have very sophisticated electrode implants 112 00:06:32,400 --> 00:06:37,080 Speaker 4: in the brain, primarily for diseases like parkinsonism, and they 113 00:06:37,080 --> 00:06:41,800 Speaker 4: both record and they stimulate. And I know a neurosurgeon 114 00:06:41,839 --> 00:06:44,360 Speaker 4: at Mayo Clinic who has an app on his phone 115 00:06:44,360 --> 00:06:47,840 Speaker 4: where he monitors the brain activity of patients he's implanted. 116 00:06:48,760 --> 00:06:51,239 Speaker 4: And I think it's certain that you're going to see 117 00:06:51,360 --> 00:06:57,479 Speaker 4: AIS connected to neuroprosthetics. And already we have neuroprosthetics that 118 00:06:57,680 --> 00:07:02,360 Speaker 4: can move artificial limbs, and you can transmit crude thoughts 119 00:07:02,400 --> 00:07:05,039 Speaker 4: over the Internet by thinking something and then it shows 120 00:07:05,120 --> 00:07:08,600 Speaker 4: up in someone else's brain. These experiments have already been done. 121 00:07:08,960 --> 00:07:10,760 Speaker 4: And so I think where you're going to see, what 122 00:07:10,800 --> 00:07:16,640 Speaker 4: you're talking about, is the interface between AI, neuroprosthetics and 123 00:07:17,080 --> 00:07:21,080 Speaker 4: the brain and what happens when an AI that has 124 00:07:21,160 --> 00:07:24,239 Speaker 4: no biological tissue is now plugged into a real brain. 125 00:07:25,160 --> 00:07:30,480 Speaker 4: It's that could start to generate things like emotions. 126 00:07:32,480 --> 00:07:35,920 Speaker 2: Interesting, very interesting, Lenn, Thanks for the call. Walkard line 127 00:07:36,000 --> 00:07:39,160 Speaker 2: number two. I think it's my ed out of new York. 128 00:07:40,920 --> 00:07:45,280 Speaker 6: Yes, good morning, great program and great bump and music always. 129 00:07:45,400 --> 00:07:47,000 Speaker 2: Connie, thanks so much. 130 00:07:47,560 --> 00:07:51,040 Speaker 6: I want to briefly comment on Lyn's point because we 131 00:07:51,200 --> 00:07:57,600 Speaker 6: heard a headline from George about not using the gammys, 132 00:07:58,200 --> 00:08:05,080 Speaker 6: which are the over uh and the uh uh single sperm, 133 00:08:05,080 --> 00:08:08,160 Speaker 6: but creation of life. So I just wanna say, yay, yay, 134 00:08:08,280 --> 00:08:12,560 Speaker 6: len you you brought up an excellent, interesting point, but 135 00:08:13,880 --> 00:08:18,240 Speaker 6: a point of clarification and a main question. And I 136 00:08:18,400 --> 00:08:23,800 Speaker 6: listen over the air. I understand Chris does mind body books, 137 00:08:23,840 --> 00:08:26,720 Speaker 6: but I didn't get the uh title of at least 138 00:08:26,800 --> 00:08:32,040 Speaker 6: say her latest book. And the main question happens to 139 00:08:32,120 --> 00:08:36,120 Speaker 6: deal with some news. I was here in on public 140 00:08:36,320 --> 00:08:39,320 Speaker 6: radio again. I heard it when it first happened some 141 00:08:39,520 --> 00:08:45,880 Speaker 6: time ago, but through facial recognition, it seems that, you know, 142 00:08:46,200 --> 00:08:50,240 Speaker 6: we live kind of in a cast system, and a 143 00:08:50,440 --> 00:08:53,520 Speaker 6: Robert Williams in front of his wife and two young 144 00:08:53,679 --> 00:08:59,600 Speaker 6: daughters got arrested behind this facial recognition. A black man 145 00:09:00,559 --> 00:09:04,880 Speaker 6: spent like thirty hours on some crazy not even a bed, 146 00:09:05,080 --> 00:09:09,720 Speaker 6: and without any clean water, and of course it was 147 00:09:09,760 --> 00:09:16,560 Speaker 6: a mistake. So I'd like to know whether either one 148 00:09:16,600 --> 00:09:19,680 Speaker 6: of you have looked into that. And it seems like 149 00:09:20,600 --> 00:09:24,880 Speaker 6: there's gonna be sort of like a Scisifian type of 150 00:09:24,920 --> 00:09:28,280 Speaker 6: struggle because of the society that we live in. And 151 00:09:28,320 --> 00:09:30,600 Speaker 6: if my question, I'll listen over the air. 152 00:09:30,760 --> 00:09:33,200 Speaker 2: Thank you so much, Connie, Thanks man. 153 00:09:33,840 --> 00:09:37,280 Speaker 4: Very insightful question. I appreciate both of them. Well, first 154 00:09:37,320 --> 00:09:41,520 Speaker 4: of all, the book is The Listening Cure, and it's 155 00:09:42,080 --> 00:09:46,400 Speaker 4: the story of an unconventional doctor, and doctor Chris is 156 00:09:46,400 --> 00:09:49,920 Speaker 4: the main author and I'm a very small sub author 157 00:09:50,120 --> 00:09:52,720 Speaker 4: and talking about the brain. But getting to the point 158 00:09:52,960 --> 00:09:57,880 Speaker 4: of racially neutral facial recognition, this is a big problem 159 00:09:58,559 --> 00:10:03,400 Speaker 4: because most of the original face recognition systems were done 160 00:10:03,480 --> 00:10:07,720 Speaker 4: on Caucasians and so they didn't perform as well on 161 00:10:08,160 --> 00:10:12,600 Speaker 4: African Americans, and so they were more prone to missus 162 00:10:12,640 --> 00:10:17,360 Speaker 4: and false positives. And this is a known problem and 163 00:10:17,440 --> 00:10:20,000 Speaker 4: it stems from what we talked about earlier in the show, 164 00:10:20,040 --> 00:10:22,760 Speaker 4: where the AI is only as good as the data 165 00:10:22,800 --> 00:10:26,679 Speaker 4: you feed it, and if there's cultural bias in that, 166 00:10:26,760 --> 00:10:30,440 Speaker 4: then there will be cultural bias in the AI. And 167 00:10:30,559 --> 00:10:33,520 Speaker 4: so it's a very important point that's been brought up, 168 00:10:33,600 --> 00:10:38,640 Speaker 4: and the industry is trying to correct that weakness. I 169 00:10:38,720 --> 00:10:42,200 Speaker 4: can't say that they're one hundred percent yet, but they're 170 00:10:42,280 --> 00:10:43,040 Speaker 4: very aware of it. 171 00:10:45,160 --> 00:10:49,800 Speaker 2: Interesting question. Wild card line number three, Charles out of California. 172 00:10:49,960 --> 00:10:51,240 Speaker 2: Is it sebastible? 173 00:10:51,320 --> 00:10:51,840 Speaker 7: What is it? 174 00:10:52,000 --> 00:10:55,240 Speaker 2: I'm sorry? Oh, okay, there you go. 175 00:10:55,880 --> 00:10:56,280 Speaker 7: Welcome. 176 00:10:56,320 --> 00:10:56,960 Speaker 2: You're on a show. 177 00:10:58,440 --> 00:11:01,199 Speaker 3: Confusing. So one of the topic I spent many years 178 00:11:01,240 --> 00:11:03,640 Speaker 3: in AI myself. In fact, in the late nineties, I 179 00:11:03,679 --> 00:11:07,040 Speaker 3: was president to call the Virtual Humans Conference, and at 180 00:11:07,040 --> 00:11:09,679 Speaker 3: that time we're talking about things like existence, sovereignty, that's 181 00:11:09,679 --> 00:11:11,640 Speaker 3: sort of thing. How do you determine the boundaries of 182 00:11:11,679 --> 00:11:14,800 Speaker 3: who you are versus sometimes representing you? And we always 183 00:11:14,800 --> 00:11:16,880 Speaker 3: thought in theoretical turns that now we're here, I mean, 184 00:11:16,880 --> 00:11:18,679 Speaker 3: this is the real thing. But the thing I wanted 185 00:11:18,720 --> 00:11:22,760 Speaker 3: to ask you about now is in political elections and campaigns. 186 00:11:23,120 --> 00:11:26,040 Speaker 3: In other words, right now, we have thousands and thousands 187 00:11:26,040 --> 00:11:28,880 Speaker 3: of comments and all kinds of blogs and various websites 188 00:11:29,320 --> 00:11:33,520 Speaker 3: either being pro putin or claiming that Ukraine attacked Prussia 189 00:11:33,640 --> 00:11:36,040 Speaker 3: or just you know, crazy stuff like that. Yeah, people 190 00:11:36,080 --> 00:11:38,440 Speaker 3: believe it. They actually started to go along with this idea. 191 00:11:38,440 --> 00:11:40,880 Speaker 3: I mean, it's kind of scary actually, So I'm kind 192 00:11:40,880 --> 00:11:43,920 Speaker 3: of wondering how many of those comments are actually coming 193 00:11:43,960 --> 00:11:46,720 Speaker 3: from Russian AI bots that sort of thing numbers I 194 00:11:46,720 --> 00:11:50,080 Speaker 3: see over them where people's opinions can be heavily slaved, 195 00:11:50,440 --> 00:11:55,800 Speaker 3: but it's kind of fake opinions being driven emotions that 196 00:11:55,960 --> 00:11:59,080 Speaker 3: turn out to reflect in elections. Do you see that 197 00:11:59,200 --> 00:11:59,880 Speaker 3: sort of happening in the. 198 00:12:00,280 --> 00:12:04,360 Speaker 4: Oh, absolutely, it has happened. It happened starting in twenty sixteen. 199 00:12:05,679 --> 00:12:07,600 Speaker 4: And the Russians, by the way, are really good at 200 00:12:07,600 --> 00:12:12,400 Speaker 4: computer science, really good and so absolutely, and I've read 201 00:12:12,440 --> 00:12:17,640 Speaker 4: that in some cases the majority of material on certain 202 00:12:17,679 --> 00:12:21,680 Speaker 4: social media sites was by these trolling bots, and they're 203 00:12:21,720 --> 00:12:25,559 Speaker 4: just going to get better and better, and quantity does matter. 204 00:12:25,640 --> 00:12:30,760 Speaker 4: Stalin himself said, quantity has its own quality. So if 205 00:12:30,760 --> 00:12:32,960 Speaker 4: you have zillions of these things and they're cheap and 206 00:12:33,320 --> 00:12:39,920 Speaker 4: basically free to spawn, you can sway opinion on social 207 00:12:40,000 --> 00:12:44,480 Speaker 4: media sites. And it actually has happened, and it's just 208 00:12:44,520 --> 00:12:46,240 Speaker 4: going to get worse because the bots are going to 209 00:12:46,240 --> 00:12:50,480 Speaker 4: get smarter and smarter and know how to work around 210 00:12:50,600 --> 00:12:53,400 Speaker 4: the AI detectors that are trying to weed them out. 211 00:12:54,559 --> 00:12:58,440 Speaker 4: It says I said in Arms Race, Charles, are you 212 00:12:58,480 --> 00:12:59,280 Speaker 4: still there with us? 213 00:12:59,360 --> 00:13:01,400 Speaker 3: By gentle though, I think I am okay there? 214 00:13:01,679 --> 00:13:04,600 Speaker 2: What you said that you are in AI a long 215 00:13:04,640 --> 00:13:06,760 Speaker 2: time ago? What what were you involved in? 216 00:13:06,920 --> 00:13:10,160 Speaker 3: Oh my goodness, well, uh, this is a little more esoteric. 217 00:13:10,480 --> 00:13:12,040 Speaker 3: One of the things I was actually involved with something 218 00:13:12,080 --> 00:13:15,200 Speaker 3: called evolutionary computing, and that is where you used genetic 219 00:13:15,200 --> 00:13:18,640 Speaker 3: algorithms to actually design or make something come come to 220 00:13:18,720 --> 00:13:22,200 Speaker 3: pass they would otherwise be able to do naturally. There 221 00:13:22,280 --> 00:13:26,720 Speaker 3: was something called the how I says, the Evolvable Hardware conference, 222 00:13:27,440 --> 00:13:31,679 Speaker 3: where we used genetic algorithms to construct really complex objects 223 00:13:31,920 --> 00:13:34,679 Speaker 3: like antennas, for instance, which is a from an art 224 00:13:34,679 --> 00:13:37,920 Speaker 3: form itself. And I was at Pasadena actually of one time. 225 00:13:37,920 --> 00:13:40,160 Speaker 3: It was a few years ago, and they showed an example 226 00:13:40,400 --> 00:13:42,520 Speaker 3: of an antenna that was being designed for a spacecraft, 227 00:13:42,559 --> 00:13:45,880 Speaker 3: you know, very beautiful orthogonos structure. Then they showed when 228 00:13:45,920 --> 00:13:49,320 Speaker 3: I was designed by the evolutionary computer or the EC platform. 229 00:13:49,720 --> 00:13:52,640 Speaker 3: The EC platform worked much better. It looks like a 230 00:13:52,640 --> 00:13:55,760 Speaker 3: bird's nest, but nobody explaining why it actually weren't. 231 00:13:56,720 --> 00:14:00,360 Speaker 4: Over I've designed optics that way that came out way 232 00:14:00,400 --> 00:14:03,560 Speaker 4: better than I could have done, and the computer did it. 233 00:14:04,040 --> 00:14:07,360 Speaker 4: But we call those evolutionary neural nets, for example, and 234 00:14:07,400 --> 00:14:12,200 Speaker 4: they're really good at creating art and they're different in 235 00:14:12,280 --> 00:14:16,360 Speaker 4: many respects from supervised learning in that they don't have 236 00:14:16,440 --> 00:14:18,520 Speaker 4: to be trained by a human in the same way 237 00:14:18,559 --> 00:14:22,240 Speaker 4: and they can produce pretty amazing results. 238 00:14:23,880 --> 00:14:28,880 Speaker 2: Good stuff, Charles, thanks for calling in. Let's yeah, yeah, 239 00:14:29,160 --> 00:14:30,760 Speaker 2: Let's see if we can do one more here before 240 00:14:30,800 --> 00:14:34,320 Speaker 2: the break. Wild Card line number four Carl out of Boston. 241 00:14:35,200 --> 00:14:38,680 Speaker 7: You're on the air by Connie. I haven't go on 242 00:14:38,800 --> 00:14:42,440 Speaker 7: with you for months, but I always missed the spot. 243 00:14:42,480 --> 00:14:44,840 Speaker 7: I knway I got a good I mean, Lynn kind 244 00:14:44,840 --> 00:14:47,320 Speaker 7: of hit on it earlier. I think it was their name. 245 00:14:47,960 --> 00:14:53,400 Speaker 7: But my question basically is is it possible now that 246 00:14:53,440 --> 00:14:58,040 Speaker 7: we have quantum computing computers size of atoms to implement 247 00:14:58,640 --> 00:15:03,320 Speaker 7: things like serotonin in dopamine into computers and something of 248 00:15:03,360 --> 00:15:09,080 Speaker 7: that nature to make them beal emotions or I know 249 00:15:09,120 --> 00:15:12,760 Speaker 7: they're not your wonderful call screen or Donna told me 250 00:15:12,840 --> 00:15:15,920 Speaker 7: that's not possible, but I was just wondering from a 251 00:15:15,960 --> 00:15:21,480 Speaker 7: brain doctor, is that even the possibility that you could 252 00:15:21,600 --> 00:15:28,600 Speaker 7: interject or maybe an AI could detect a certain level 253 00:15:28,720 --> 00:15:37,520 Speaker 7: of serotonin or dopamine or whatever neurochemical reaction to make 254 00:15:37,600 --> 00:15:39,720 Speaker 7: up their mind and how to react towards you. 255 00:15:40,600 --> 00:15:44,760 Speaker 4: Thank you well. I think it would depend on the 256 00:15:44,800 --> 00:15:50,560 Speaker 4: actual physical structure of the AI computer if it's silicon 257 00:15:51,200 --> 00:15:54,120 Speaker 4: microchips as it is today, I think the answer is no, 258 00:15:54,920 --> 00:15:57,440 Speaker 4: although I wouldn't rule out the possibility that you couldn't 259 00:15:57,440 --> 00:16:02,720 Speaker 4: come up with a digital virtual equivalent of stimulant and 260 00:16:02,840 --> 00:16:09,080 Speaker 4: neurotransmitter that would change the mood. But I think that 261 00:16:10,080 --> 00:16:15,080 Speaker 4: there is a fast growing field of biological computing where 262 00:16:15,880 --> 00:16:19,640 Speaker 4: biological tissue, neural tissue and other things are used for 263 00:16:19,760 --> 00:16:27,960 Speaker 4: computation and also self assembling biological systems that do automation 264 00:16:28,120 --> 00:16:31,800 Speaker 4: and things like that. There's nothing that says a computer 265 00:16:31,920 --> 00:16:35,160 Speaker 4: has to be made of silicon. We have an existence 266 00:16:35,200 --> 00:16:37,600 Speaker 4: proof that you can make it of neurve cells, for example, 267 00:16:38,600 --> 00:16:41,720 Speaker 4: and there's some interesting experiments working in that direction. So 268 00:16:42,280 --> 00:16:45,080 Speaker 4: I'll just repeat what I said before. It's an opinion. 269 00:16:45,160 --> 00:16:47,800 Speaker 4: It's not based on any data because nobody really knows 270 00:16:48,640 --> 00:16:52,520 Speaker 4: what the substrate of emotion is. But my opinion is 271 00:16:52,560 --> 00:16:55,800 Speaker 4: that the underlying computer would have to itself be biological. 272 00:16:56,680 --> 00:16:59,840 Speaker 1: Listen to more Coast to Coast AM every weeknight at 273 00:16:59,840 --> 00:17:02,800 Speaker 1: one a m. 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