1 00:00:01,480 --> 00:00:07,040 Speaker 1: Yes, stuff like Chelsey and a man just cut him. Yeah, yes, 2 00:00:07,160 --> 00:00:09,239 Speaker 1: chuncy and man's cut. 3 00:00:10,840 --> 00:00:18,320 Speaker 2: Yeah it's charncy and man just cuting one floor? Can 4 00:00:18,640 --> 00:00:25,200 Speaker 2: and man just cut him? Are you ready for more? 5 00:00:27,240 --> 00:00:29,160 Speaker 1: What's on the cutting room floor today? Amanda? 6 00:00:29,400 --> 00:00:32,120 Speaker 2: You know I love me science Brendan. You do like 7 00:00:32,200 --> 00:00:35,320 Speaker 2: I do, like putting on my lab coat and hearkening 8 00:00:35,360 --> 00:00:37,360 Speaker 2: back to my beyond two thousand days. 9 00:00:37,200 --> 00:00:39,120 Speaker 1: Didn't you just wear a lab coat once? 10 00:00:40,040 --> 00:00:41,960 Speaker 2: Is that I often had to wear a lab coat, 11 00:00:42,000 --> 00:00:43,920 Speaker 2: and it's like I was up for election. You know, 12 00:00:43,920 --> 00:00:46,240 Speaker 2: they're always having to wear these days. It's high vis. 13 00:00:46,320 --> 00:00:48,320 Speaker 2: We didn't have to wear high vias. We had lab coats. 14 00:00:48,560 --> 00:00:51,800 Speaker 2: We'd wear safety goggles, we'd wear hard hats all that. 15 00:00:52,200 --> 00:00:54,800 Speaker 3: Weren't you in a place sometime and you're looking at 16 00:00:54,840 --> 00:00:56,480 Speaker 3: a fancy shop. 17 00:00:56,640 --> 00:00:57,840 Speaker 2: That's how I knew it was time for me to 18 00:00:57,920 --> 00:01:00,240 Speaker 2: leave beyond two thousand. I had a morning off in Parasrus. 19 00:01:01,000 --> 00:01:02,800 Speaker 2: I thought, look at that dress shop across the road. 20 00:01:02,840 --> 00:01:05,959 Speaker 2: That looks nice. There was a shop that sold lab 21 00:01:06,000 --> 00:01:09,920 Speaker 2: coats and industrial equipment. I thought, maybe it's time I 22 00:01:10,000 --> 00:01:13,840 Speaker 2: give this job up. I'm still wearing it though. Let 23 00:01:13,880 --> 00:01:15,840 Speaker 2: me tell you about this. This is the story of 24 00:01:15,920 --> 00:01:19,120 Speaker 2: two Australian mathematicians who have called into question that old 25 00:01:19,120 --> 00:01:23,520 Speaker 2: adage that have given infinite amount of time a monkey 26 00:01:23,600 --> 00:01:26,480 Speaker 2: pressing keys on a typewriter could eventually write the complete 27 00:01:26,480 --> 00:01:30,080 Speaker 2: works of William Shakespeare. This is known as the infinite 28 00:01:30,120 --> 00:01:32,039 Speaker 2: monkey theorem. Have you heard of it before, Brenda, I 29 00:01:32,080 --> 00:01:35,080 Speaker 2: have heard of it. Yes, yeah. It's a thought experiment 30 00:01:35,360 --> 00:01:38,080 Speaker 2: that's long been used to explain the principles of probability 31 00:01:38,400 --> 00:01:42,319 Speaker 2: and randomness. So this new peer reviewed study led by 32 00:01:42,400 --> 00:01:46,959 Speaker 2: Sydney based researchers Stephen Woodcock and Jay Fleta, have found 33 00:01:46,959 --> 00:01:49,400 Speaker 2: that the time it would take for a typing monkey 34 00:01:50,440 --> 00:01:54,320 Speaker 2: to replicate Shakespeare's plays, sonnets and poems would be longer 35 00:01:54,360 --> 00:01:57,560 Speaker 2: than the lifespan of our universe, which means that, while 36 00:01:57,560 --> 00:02:02,280 Speaker 2: mathematically true, theorem is misleading. So they looked at the 37 00:02:02,320 --> 00:02:05,240 Speaker 2: abilities of a single monkey as well. So they looked 38 00:02:05,240 --> 00:02:08,000 Speaker 2: at the ability of a monkey also the series of 39 00:02:08,040 --> 00:02:12,680 Speaker 2: calculations based on the current global population of chimpanzees. Chimpanzees, 40 00:02:12,720 --> 00:02:16,720 Speaker 2: do you think there are in the world six million, 41 00:02:17,160 --> 00:02:19,040 Speaker 2: two hundred thousand? It's not that many, is it? 42 00:02:19,040 --> 00:02:22,320 Speaker 1: Two hundred thousand? In the whole wide world. Hang on? 43 00:02:23,360 --> 00:02:25,000 Speaker 1: Is that two hundred thousand million. 44 00:02:25,520 --> 00:02:27,800 Speaker 2: That says here, two hundred thousand hang on? 45 00:02:28,000 --> 00:02:30,160 Speaker 1: Monkey chimpanzees like. 46 00:02:32,919 --> 00:02:36,680 Speaker 2: In Tarzan because you don't see good old ones. 47 00:02:36,760 --> 00:02:39,320 Speaker 3: Yeah, you don't see monkeys in movies anymore. Remember there 48 00:02:39,360 --> 00:02:41,239 Speaker 3: was a whole thing about a monkey in the movie. 49 00:02:41,280 --> 00:02:43,160 Speaker 2: Yeah, and they'd have a wine shirts on and they 50 00:02:43,280 --> 00:02:48,160 Speaker 2: chop around like Lancelot Secret Jim and Marta Harri Lancey, 51 00:02:49,360 --> 00:02:51,600 Speaker 2: I'm trying to wear a pair of sand just what 52 00:02:51,639 --> 00:02:53,040 Speaker 2: I look like in heels. 53 00:02:53,760 --> 00:02:57,840 Speaker 1: Just to Lancelot Lynks Secret Chim was Lancy. 54 00:02:57,480 --> 00:03:01,840 Speaker 2: And I do so information there in the scene together. 55 00:03:02,280 --> 00:03:04,079 Speaker 3: I think they could have done split scene like where 56 00:03:04,120 --> 00:03:06,040 Speaker 3: they did in Bewitched when they had. 57 00:03:06,240 --> 00:03:09,359 Speaker 2: Would have taken too long. Look, they would have used 58 00:03:09,360 --> 00:03:10,200 Speaker 2: a lot of monkeys. 59 00:03:10,520 --> 00:03:14,320 Speaker 1: Yeah. Uh what about Wally War Was he a chimp? 60 00:03:14,919 --> 00:03:18,480 Speaker 2: Yeah, he was an ape, but he was an apri chimp. 61 00:03:18,560 --> 00:03:20,440 Speaker 1: It was I think it was a chimp. I don't 62 00:03:20,440 --> 00:03:25,799 Speaker 1: think you can train an ape. Murray Field, the voice to. 63 00:03:26,240 --> 00:03:30,760 Speaker 3: Wally warpermre so somewhere along the line, it's not culturally sense. 64 00:03:30,720 --> 00:03:35,080 Speaker 2: No, it's not meaning on the line it is, it's inappropriate. 65 00:03:35,120 --> 00:03:36,960 Speaker 1: It's animal cruelty, cruelty. 66 00:03:37,440 --> 00:03:40,960 Speaker 2: So anyway, the results indicated that even if every chimp, 67 00:03:41,040 --> 00:03:44,960 Speaker 2: Wally Wallpermure and Marta Hari and Lancelot Lincoln the chief, 68 00:03:45,080 --> 00:03:47,600 Speaker 2: all of them, it was wasn't there a chief? Or 69 00:03:47,640 --> 00:03:51,240 Speaker 2: am I mistaken it? For get smart? Was that troop? 70 00:03:51,480 --> 00:03:51,560 Speaker 1: No? 71 00:03:51,640 --> 00:03:54,280 Speaker 2: I think there was a chief. Anyway, If all the 72 00:03:54,400 --> 00:03:57,640 Speaker 2: chimps in the world were enlisted and able to type 73 00:03:57,720 --> 00:04:00,520 Speaker 2: at a pace of one key per second until the 74 00:04:00,600 --> 00:04:03,480 Speaker 2: end of the universe, they still wouldn't have come close 75 00:04:03,520 --> 00:04:06,400 Speaker 2: to typing out all of Shakespeare's works. Wow, there would 76 00:04:06,440 --> 00:04:10,080 Speaker 2: be a five percent chance that a single chimp could 77 00:04:10,080 --> 00:04:13,560 Speaker 2: successfully type the word bananas in its own lifetime. It 78 00:04:13,600 --> 00:04:14,640 Speaker 2: would just randomly type. 79 00:04:14,680 --> 00:04:16,680 Speaker 3: There's a five per it just pashed away on the 80 00:04:16,680 --> 00:04:19,040 Speaker 3: type it would eventually come to bananas. 81 00:04:19,160 --> 00:04:22,720 Speaker 2: And the probability of one chimp constructing a random sentence 82 00:04:22,760 --> 00:04:25,720 Speaker 2: such as I chimp before I am comes in at 83 00:04:25,839 --> 00:04:30,560 Speaker 2: one in ten million billion. Their researchers shot, oh, but 84 00:04:30,680 --> 00:04:32,680 Speaker 2: you know what book They were able to smash out 85 00:04:34,000 --> 00:04:36,120 Speaker 2: fifty shades of fifty by Brendan Jones. They did it 86 00:04:36,120 --> 00:04:37,880 Speaker 2: in ten minutes, just one chimp. 87 00:04:37,880 --> 00:04:40,400 Speaker 1: Extra extraordinary chimp. 88 00:04:42,360 --> 00:04:43,960 Speaker 2: And they threw their feces. 89 00:04:44,960 --> 00:04:47,520 Speaker 3: I'm going to throw summ agin now available just in 90 00:04:47,560 --> 00:04:48,240 Speaker 3: time for Christmas. 91 00:04:48,279 --> 00:04:52,360 Speaker 2: By the way, yeah, not ever another year that remained 92 00:04:52,400 --> 00:04:53,479 Speaker 2: has been as massive. 93 00:05:03,279 --> 00:05:05,920 Speaker 1: And here's what's on the cutting room floor. 94 00:05:06,240 --> 00:05:08,719 Speaker 2: I've been reading here an interesting article. People are ending 95 00:05:08,720 --> 00:05:12,599 Speaker 2: their relationships up, discovering the Dorito's theory. Let's take a 96 00:05:12,600 --> 00:05:15,080 Speaker 2: step back. Do you like Dorito's? 97 00:05:15,400 --> 00:05:20,039 Speaker 1: I do all of them, not so much. I like 98 00:05:20,040 --> 00:05:21,400 Speaker 1: them with a bit of sou so. I remember the 99 00:05:21,440 --> 00:05:23,480 Speaker 1: first time I ever ate a darrita. I was over 100 00:05:23,520 --> 00:05:23,920 Speaker 1: in America. 101 00:05:23,920 --> 00:05:24,920 Speaker 2: I would remember the very first. 102 00:05:25,000 --> 00:05:27,800 Speaker 3: I just remember because you're in America and how old 103 00:05:27,800 --> 00:05:31,040 Speaker 3: were you? I would have been thirteen, a bit younger 104 00:05:31,720 --> 00:05:32,600 Speaker 3: was they weren't over here? 105 00:05:32,760 --> 00:05:34,040 Speaker 2: Was it a flavored one or a plane? 106 00:05:34,120 --> 00:05:35,520 Speaker 3: It was a flavor one. I remember eating it and 107 00:05:35,600 --> 00:05:37,159 Speaker 3: I thought, oh my god, this is the worst thing I've. 108 00:05:37,000 --> 00:05:40,400 Speaker 1: Eate my life. Well, because we didn't have in Australia 109 00:05:40,440 --> 00:05:40,960 Speaker 1: back then. 110 00:05:41,040 --> 00:05:45,320 Speaker 2: We had we would have had cheeseballs. We had twisties, cheesels, 111 00:05:45,480 --> 00:05:46,760 Speaker 2: cheesels and cheeseballs. 112 00:05:47,040 --> 00:05:49,880 Speaker 1: No, we didn't have cheeseballs. And then we didn't have anything. 113 00:05:49,960 --> 00:05:54,120 Speaker 3: Mexican corn chips came to Australia in the eighties. 114 00:05:55,360 --> 00:05:57,440 Speaker 1: Certainly in my house we didn't have. 115 00:05:57,520 --> 00:05:59,760 Speaker 3: Ceats, so that's what was the first thing is Toritos 116 00:06:00,200 --> 00:06:02,160 Speaker 3: for the American the American chip. 117 00:06:02,160 --> 00:06:03,120 Speaker 1: But I remember eating. 118 00:06:02,960 --> 00:06:06,400 Speaker 3: It and thought I thought it tasted like spew on 119 00:06:06,520 --> 00:06:10,359 Speaker 3: a terrible I couldn't even describe how bad the chip was. 120 00:06:10,440 --> 00:06:10,760 Speaker 1: I remember. 121 00:06:11,080 --> 00:06:13,040 Speaker 2: It does give you the arch the taste of spew. 122 00:06:13,120 --> 00:06:16,200 Speaker 2: You know that all of those cheese, slight cheesy things do. 123 00:06:16,360 --> 00:06:18,000 Speaker 1: Yeah, the nacho's cheese. 124 00:06:18,240 --> 00:06:19,880 Speaker 2: Yeah, it tastes in your mouth like you've had a 125 00:06:19,960 --> 00:06:22,320 Speaker 2: vomb But now but now. 126 00:06:22,600 --> 00:06:23,480 Speaker 1: You're shoveling him in. 127 00:06:23,560 --> 00:06:26,359 Speaker 2: We'll see what the dorito's dating theory is. This is 128 00:06:26,400 --> 00:06:30,760 Speaker 2: the theories based on the scenario that you find yourself 129 00:06:30,760 --> 00:06:33,440 Speaker 2: eating dorito after derito without giving it much choice. You 130 00:06:33,440 --> 00:06:37,880 Speaker 2: don't without giving it any thought, You don't think about 131 00:06:38,520 --> 00:06:40,799 Speaker 2: whether it's satisfying or not. You just eat a stack 132 00:06:40,839 --> 00:06:44,200 Speaker 2: of them, and you're never completely satisfied. And this could 133 00:06:44,200 --> 00:06:46,640 Speaker 2: correlate to other areas and other people in your life. 134 00:06:47,320 --> 00:06:50,880 Speaker 2: So this TikTok user surprisingly has said the idea is 135 00:06:50,880 --> 00:06:55,560 Speaker 2: that only experiences that aren't truly satisfying are maximally addictive. 136 00:06:56,720 --> 00:06:58,840 Speaker 2: So you're eating Dorito's, and you eat a dorito and 137 00:06:58,880 --> 00:07:01,440 Speaker 2: finish a bite, you're not satisfied. It's not like when 138 00:07:01,440 --> 00:07:04,360 Speaker 2: you eat a steak or really satisfying food that's high 139 00:07:04,400 --> 00:07:07,440 Speaker 2: in protein, where after a bite you feel the fullness 140 00:07:07,440 --> 00:07:11,360 Speaker 2: and the warmth of satisfaction. You don't get that with dorrito's. 141 00:07:11,440 --> 00:07:16,400 Speaker 2: And many people are having derito relationships because they're not 142 00:07:16,520 --> 00:07:20,400 Speaker 2: going for the substantial stuff the look because it's so 143 00:07:20,560 --> 00:07:26,440 Speaker 2: addictive to have these lightweight things that designed to keep 144 00:07:26,480 --> 00:07:30,560 Speaker 2: you hungry. And if that's your personality, you might be 145 00:07:30,600 --> 00:07:32,840 Speaker 2: doing that in other parts of your life. So beware. 146 00:07:32,960 --> 00:07:35,920 Speaker 3: They're saying, So is it like what Paul Newman said 147 00:07:35,920 --> 00:07:38,760 Speaker 3: about his wife Joanne Woodwood that you. 148 00:07:38,680 --> 00:07:40,560 Speaker 2: Know, why would I go out for hamburger when I've 149 00:07:40,600 --> 00:07:41,360 Speaker 2: got steak at home? 150 00:07:41,440 --> 00:07:43,920 Speaker 1: And then Charlie Jean said, sometimes. 151 00:07:43,480 --> 00:07:45,400 Speaker 2: You want a bit of you want a bit of hamburger, 152 00:07:46,160 --> 00:07:47,640 Speaker 2: you want some other buns. 153 00:07:47,360 --> 00:07:48,560 Speaker 1: You want something else to eat. 154 00:07:49,360 --> 00:07:52,720 Speaker 2: Yeah, because that's what all those not new. But that's 155 00:07:52,720 --> 00:07:58,000 Speaker 2: the secret to dieting is having calorie dense foods that 156 00:07:58,080 --> 00:08:00,920 Speaker 2: satisfy you. Dorito's are the opposite, and there's an addictive 157 00:08:00,960 --> 00:08:03,800 Speaker 2: quality to them. And that is maybe how you're having 158 00:08:03,800 --> 00:08:07,320 Speaker 2: your relationships. They're so addictive. You're loving the thrill of 159 00:08:07,360 --> 00:08:09,120 Speaker 2: the falling in love, but they don't last. 160 00:08:09,280 --> 00:08:11,280 Speaker 1: When you're on the diet, though, you can still look 161 00:08:11,320 --> 00:08:11,760 Speaker 1: at the menu. 162 00:08:12,040 --> 00:08:14,760 Speaker 2: You're talking about food or people? So how far do 163 00:08:14,840 --> 00:08:15,920 Speaker 2: you take looking at the menu? 164 00:08:17,040 --> 00:08:17,360 Speaker 1: Well? 165 00:08:17,560 --> 00:08:21,119 Speaker 2: Does your wife mind if you constantly peruse the menu? 166 00:08:21,360 --> 00:08:23,960 Speaker 1: Are you choking me as if I would be doing that? 167 00:08:24,160 --> 00:08:24,320 Speaker 4: No? 168 00:08:24,400 --> 00:08:28,280 Speaker 2: But like like I watched you flip through Maxim magazine 169 00:08:28,320 --> 00:08:31,480 Speaker 2: the other week, just looking for four Do you do 170 00:08:31,560 --> 00:08:33,360 Speaker 2: that when you're out? No? 171 00:08:34,880 --> 00:08:38,880 Speaker 1: Can I see the specials? No? I don't do that 172 00:08:38,960 --> 00:08:39,280 Speaker 1: at all. 173 00:08:39,679 --> 00:08:46,120 Speaker 2: Got anything going off quickly? That lucky time you found 174 00:08:46,120 --> 00:08:47,840 Speaker 2: a chicken in a bag and the trolley. 175 00:08:48,360 --> 00:08:49,760 Speaker 1: Why does it always come back to that? 176 00:08:50,120 --> 00:08:51,880 Speaker 2: That's we're doing about food or people? 177 00:08:52,000 --> 00:08:52,800 Speaker 1: I don't know. 178 00:08:52,960 --> 00:08:55,520 Speaker 3: I remember some time ago I used to get a 179 00:08:55,559 --> 00:08:57,040 Speaker 3: lift into work when I had to go to a 180 00:08:57,080 --> 00:08:59,560 Speaker 3: business lunch after the show, and one of the girls 181 00:08:59,640 --> 00:09:03,720 Speaker 3: the time, I would meet her outside a German restaurant, 182 00:09:04,160 --> 00:09:07,280 Speaker 3: so that's where I just wait for her car to 183 00:09:07,440 --> 00:09:07,960 Speaker 3: come along. 184 00:09:08,360 --> 00:09:11,640 Speaker 1: And it was had this giant menu board out the front, 185 00:09:11,679 --> 00:09:12,160 Speaker 1: and I'd look. 186 00:09:12,080 --> 00:09:14,679 Speaker 3: At all the German delicacies that had on offer big 187 00:09:14,760 --> 00:09:20,560 Speaker 3: knuckle cheven Hucksen and Vienna Schnitzel and big pretzel relationships, 188 00:09:20,559 --> 00:09:24,040 Speaker 3: big sausage, and I'd stand and big sausage, peruse that 189 00:09:24,200 --> 00:09:28,080 Speaker 3: menu board, and I'd always be very, very hungry, hungry 190 00:09:28,120 --> 00:09:30,280 Speaker 3: as But I never went to that restaurant, all. 191 00:09:30,280 --> 00:09:32,000 Speaker 2: Right, So it's not linked to getting in the car 192 00:09:32,040 --> 00:09:33,200 Speaker 2: with that girl work. 193 00:09:33,400 --> 00:09:34,080 Speaker 1: No, not at all. 194 00:09:34,240 --> 00:09:36,040 Speaker 3: No, she'd beat me up and she wouldn't even know 195 00:09:36,240 --> 00:09:38,600 Speaker 3: although I'd be salivating a Pavlov's dog. 196 00:09:39,960 --> 00:09:41,720 Speaker 2: She didn't think you would creepy at all, a man 197 00:09:41,760 --> 00:09:43,680 Speaker 2: on the side of the road salivating. 198 00:09:43,880 --> 00:09:45,200 Speaker 3: But then I went to go to the restaurant and 199 00:09:45,200 --> 00:09:47,520 Speaker 3: it was closed down. So is that maybe a metaphor 200 00:09:47,600 --> 00:09:48,040 Speaker 3: for life? 201 00:09:48,200 --> 00:09:52,080 Speaker 2: Maybe? So with Doritos, they live a taste of spew 202 00:09:52,160 --> 00:09:54,040 Speaker 2: in your mouth, So remember that. That's how you're having 203 00:09:54,080 --> 00:09:55,640 Speaker 2: your relationships. 204 00:09:56,880 --> 00:10:10,400 Speaker 4: Taste of spew in the mouth. At least we had that. 205 00:10:12,440 --> 00:10:14,480 Speaker 1: What's on the cutting room floor today, missus Woods? 206 00:10:14,600 --> 00:10:15,600 Speaker 2: Do you like science? 207 00:10:16,080 --> 00:10:17,000 Speaker 1: I love science. 208 00:10:17,040 --> 00:10:19,560 Speaker 3: I used to love being in the science class, melting 209 00:10:19,600 --> 00:10:22,640 Speaker 3: stuff with buns and burners and the like, letting off 210 00:10:22,720 --> 00:10:23,920 Speaker 3: big egg gas things. 211 00:10:24,200 --> 00:10:29,199 Speaker 2: You're still good at that. Do you like science about animals? Yes? Sure, 212 00:10:29,280 --> 00:10:32,319 Speaker 2: drill down. Even do you like science about birds? 213 00:10:33,160 --> 00:10:35,000 Speaker 3: We had to cut open a bird at school once, 214 00:10:35,080 --> 00:10:37,600 Speaker 3: did you Yeah, had a frog and a rat. 215 00:10:37,640 --> 00:10:38,840 Speaker 2: What kind of bird was it? 216 00:10:38,840 --> 00:10:40,920 Speaker 1: It was like I forgot what sort of bird it was. 217 00:10:41,080 --> 00:10:43,079 Speaker 1: It was a dead bird. We didn't have to kill it. 218 00:10:43,960 --> 00:10:47,079 Speaker 3: The years before at my school the kids had to 219 00:10:47,160 --> 00:10:49,520 Speaker 3: kill the frog and the rat. They had to actually 220 00:10:49,600 --> 00:10:52,120 Speaker 3: kill it and then dissect it and spring it out 221 00:10:52,160 --> 00:10:53,360 Speaker 3: on a little board. 222 00:10:53,640 --> 00:10:55,880 Speaker 2: Does it be? On two thousand I worked with a 223 00:10:55,880 --> 00:10:57,800 Speaker 2: cameraman used to have rats as pets, and we were 224 00:10:57,800 --> 00:10:59,679 Speaker 2: just talking in a lab one day and he's got 225 00:10:59,679 --> 00:11:02,080 Speaker 2: his head on and this guy in a lab coat 226 00:11:02,200 --> 00:11:03,880 Speaker 2: was preparing to be interviewed by us, and he just 227 00:11:03,920 --> 00:11:05,720 Speaker 2: picked out a rat and when book bank the back, 228 00:11:06,080 --> 00:11:07,480 Speaker 2: whack the back of its head on a bench to 229 00:11:07,559 --> 00:11:12,240 Speaker 2: kill it. And this sound, of course, is going, well, 230 00:11:12,280 --> 00:11:14,120 Speaker 2: it'll be like us watching a dog being killed. They 231 00:11:14,120 --> 00:11:14,960 Speaker 2: were his pets. 232 00:11:15,160 --> 00:11:17,880 Speaker 3: Yeah, although it's not out of character for a sound 233 00:11:17,960 --> 00:11:21,720 Speaker 3: recorders to be unusual, to be unusual and keep rats 234 00:11:21,920 --> 00:11:23,000 Speaker 3: like in the TV game. 235 00:11:23,280 --> 00:11:25,520 Speaker 2: In the game, the soundercord is the one saying, when 236 00:11:25,520 --> 00:11:26,280 Speaker 2: are we having lunch. 237 00:11:26,360 --> 00:11:30,640 Speaker 3: Yep, always first for lunch, always first to just when 238 00:11:30,640 --> 00:11:33,240 Speaker 3: you're on a flow of doing something and everything's working well. 239 00:11:33,320 --> 00:11:35,640 Speaker 3: Batteries of gold, although I better check the batchels and 240 00:11:35,720 --> 00:11:37,480 Speaker 3: may you've been sitting there twiddling your farms for the 241 00:11:37,559 --> 00:11:38,600 Speaker 3: last half an hour. 242 00:11:38,920 --> 00:11:42,600 Speaker 2: Yeah, when you do it, then that's them. But let's 243 00:11:42,600 --> 00:11:46,480 Speaker 2: talk about crows and not Russell Crows can hold grudges 244 00:11:46,559 --> 00:11:49,439 Speaker 2: for up to seventeen years. This was what these people 245 00:11:49,480 --> 00:11:53,360 Speaker 2: have discovered. New research has shown that these birds and 246 00:11:53,400 --> 00:11:56,440 Speaker 2: crows apparently have long been considered the most intelligent of 247 00:11:56,480 --> 00:12:00,600 Speaker 2: the avian species. They're good at recognizing face. So this 248 00:12:00,679 --> 00:12:03,719 Speaker 2: study imagine putting this study to the funding body. The 249 00:12:03,760 --> 00:12:07,280 Speaker 2: study began in two thousand and six Professor John Museloff, 250 00:12:07,360 --> 00:12:10,400 Speaker 2: an environmental scientist in the University of Washington. He put 251 00:12:10,400 --> 00:12:13,960 Speaker 2: on a scary mask and captured seven crows in a net. 252 00:12:14,880 --> 00:12:16,160 Speaker 2: So he captured seven crows in it. 253 00:12:16,280 --> 00:12:18,559 Speaker 3: So he's wearing a scary mask, yes, And he ran 254 00:12:18,600 --> 00:12:21,600 Speaker 3: around with a big net like the child snatcher in 255 00:12:22,240 --> 00:12:23,400 Speaker 3: Gitch Bang Bang. 256 00:12:23,240 --> 00:12:28,480 Speaker 2: I imagine Brendan Shaw. Then he released the birds unharmed, 257 00:12:28,559 --> 00:12:32,600 Speaker 2: but he put identification rings on their legs. He then had. 258 00:12:32,760 --> 00:12:36,680 Speaker 2: He and his assistants would occasionally wear the mask in 259 00:12:36,760 --> 00:12:40,480 Speaker 2: subsequent years as they walked around campus, feeding the crows 260 00:12:40,520 --> 00:12:44,440 Speaker 2: and recording the reaction. On one occasion, he said he 261 00:12:44,520 --> 00:12:49,440 Speaker 2: was subjected to aggressive scowling cause cause caws noise from 262 00:12:49,520 --> 00:12:50,800 Speaker 2: these crows not the. 263 00:12:50,679 --> 00:12:54,160 Speaker 1: Cause was a successful family that sings from Ireland. 264 00:12:54,280 --> 00:12:58,000 Speaker 2: No, Brandon, it's this way you make science so hard. 265 00:12:58,520 --> 00:13:02,880 Speaker 2: He was subjected to aggressive noises from forty seven out 266 00:13:02,880 --> 00:13:06,200 Speaker 2: of the fifty three crows that he encountered. Now, considering 267 00:13:06,440 --> 00:13:08,640 Speaker 2: that that number of crows was so much higher than 268 00:13:08,679 --> 00:13:11,360 Speaker 2: the original number he captured in his so called scary mask, 269 00:13:12,160 --> 00:13:15,960 Speaker 2: this means that the crows learned to recognize the mask. 270 00:13:16,480 --> 00:13:19,840 Speaker 2: They learned to recognize threatening humans from their parents and 271 00:13:19,880 --> 00:13:24,360 Speaker 2: their relatives. This information was somehow passed on. 272 00:13:26,520 --> 00:13:28,320 Speaker 1: Wow, so the crows talk to each other? 273 00:13:28,640 --> 00:13:33,000 Speaker 2: Will they either talk to each other or giving birth 274 00:13:33,200 --> 00:13:35,880 Speaker 2: they passed that knowledge on. I don't know. That's probably 275 00:13:35,880 --> 00:13:38,840 Speaker 2: what's being discussed. But you should know very well that 276 00:13:38,880 --> 00:13:41,319 Speaker 2: a bird can hold a grudge for seventeen years. Slight 277 00:13:41,400 --> 00:13:44,480 Speaker 2: your wife once old, she's not going to forget. They 278 00:13:44,480 --> 00:13:46,400 Speaker 2: don't even have to wear a scary mask. 279 00:13:48,320 --> 00:13:50,319 Speaker 3: I was thinking of the bird I'm looking at right 280 00:13:50,400 --> 00:13:53,720 Speaker 3: now that I've worked with for almost twenty Do you 281 00:13:53,720 --> 00:13:56,960 Speaker 3: want to go cool? And when I say cool, I'm 282 00:13:56,960 --> 00:13:58,640 Speaker 3: not talking about the moderate that's successful. 283 00:13:58,760 --> 00:13:59,120 Speaker 1: Iris. 284 00:14:00,280 --> 00:14:03,720 Speaker 2: That's science for today. 285 00:14:05,840 --> 00:14:07,920 Speaker 1: Well, what's on the cutting room floor today? Mate? 286 00:14:08,679 --> 00:14:11,520 Speaker 2: There's a person who's got a pet pig. I don't 287 00:14:11,559 --> 00:14:12,720 Speaker 2: understand pet pigs. 288 00:14:12,720 --> 00:14:12,960 Speaker 4: Do you? 289 00:14:13,120 --> 00:14:15,040 Speaker 2: If you live on a farm, that's great. I follow 290 00:14:15,080 --> 00:14:18,120 Speaker 2: Sam Neil's socials and he's got pigs that he's named 291 00:14:18,160 --> 00:14:21,200 Speaker 2: after famous people, and they're they're very good friends of his. 292 00:14:21,360 --> 00:14:23,560 Speaker 1: Does he use the pigs for foods? 293 00:14:23,640 --> 00:14:26,480 Speaker 2: I don't think he does, But the pigs walk around 294 00:14:26,520 --> 00:14:28,520 Speaker 2: with him as one pig in particular, who's his friend. 295 00:14:29,240 --> 00:14:33,040 Speaker 2: And that's nice. But this is a couple who was 296 00:14:33,040 --> 00:14:35,640 Speaker 2: celebrating the fourth of July and forgot about a case 297 00:14:35,680 --> 00:14:40,560 Speaker 2: of beer that was in their garage. Their pet pig, 298 00:14:41,040 --> 00:14:43,920 Speaker 2: which is seven years old, is the love of their life. 299 00:14:43,920 --> 00:14:47,560 Speaker 2: It's called Strawberry, and it got drunk on the beer. 300 00:14:47,880 --> 00:14:48,920 Speaker 2: Of course, what do you mean? 301 00:14:48,960 --> 00:14:52,360 Speaker 1: Of course they do. Pigs by definition are. 302 00:14:52,320 --> 00:14:56,440 Speaker 2: Peaks rely anything. Well, they actually apparently they're very clean. 303 00:14:57,240 --> 00:15:00,800 Speaker 2: Do you know what? When I was with Beyond two 304 00:15:00,840 --> 00:15:05,400 Speaker 2: thousand is that pigs have the same tastes as little kids. 305 00:15:05,760 --> 00:15:10,600 Speaker 2: They love chocolate, milk, they love ice creams, they love 306 00:15:11,960 --> 00:15:14,160 Speaker 2: soft drink and kind of stuff, all the sugar. 307 00:15:13,960 --> 00:15:16,160 Speaker 1: And drink kids. I got trading mates that eat like that. 308 00:15:16,280 --> 00:15:19,040 Speaker 2: Yeah, well, pigs love all that. I was doing a 309 00:15:19,040 --> 00:15:21,160 Speaker 2: story on how they could get their pigs to produce 310 00:15:21,200 --> 00:15:24,120 Speaker 2: more milk and to eat more, and that's what they get. 311 00:15:24,120 --> 00:15:26,480 Speaker 1: Well, everyone knows they orgasm for thirty minutes? 312 00:15:27,040 --> 00:15:28,400 Speaker 2: Do you mean everyone knows? 313 00:15:28,720 --> 00:15:29,520 Speaker 1: You didn't know they know? 314 00:15:29,960 --> 00:15:32,720 Speaker 2: I haven't had an intimate relationship with one with a 315 00:15:32,800 --> 00:15:34,000 Speaker 2: pig for thirty minutes. 316 00:15:34,160 --> 00:15:35,680 Speaker 1: Ere many pigs trying to hit on you. 317 00:15:35,840 --> 00:15:37,120 Speaker 2: Does it male or female? 318 00:15:38,240 --> 00:15:40,400 Speaker 1: I'm pretty sure it's the female because that would be 319 00:15:40,600 --> 00:15:41,520 Speaker 1: a long orgasm. 320 00:15:41,680 --> 00:15:43,640 Speaker 3: I don't know if the peak has that much fluid 321 00:15:43,640 --> 00:15:46,160 Speaker 3: in it to do it for thirty minutes. You know, 322 00:15:46,200 --> 00:15:50,080 Speaker 3: As far as female animal's orgasm, Well, I'm just saying, 323 00:15:50,200 --> 00:15:53,080 Speaker 3: I thought every while we're talking, did google while we're talking? 324 00:15:53,200 --> 00:15:54,200 Speaker 1: I thought everyone knew that. 325 00:15:54,240 --> 00:15:57,480 Speaker 3: It's one of those trivia questions, true or false? Is 326 00:15:57,480 --> 00:16:00,360 Speaker 3: it true the pigs orgasm for thirty minutes? And more 327 00:16:00,400 --> 00:16:02,120 Speaker 3: often than not, it comes up that It's true. 328 00:16:02,320 --> 00:16:06,120 Speaker 2: The longest orgasm in mammals is out of the domestic pig. Yeah, 329 00:16:06,480 --> 00:16:08,960 Speaker 2: on average thirty minutes, but it can last as long 330 00:16:09,000 --> 00:16:10,080 Speaker 2: as ninety. 331 00:16:10,000 --> 00:16:13,160 Speaker 1: Whoa wow, that's like nine and a. 332 00:16:13,160 --> 00:16:14,320 Speaker 2: Half weeks the male one. 333 00:16:14,360 --> 00:16:15,640 Speaker 1: I think the male pig. 334 00:16:15,920 --> 00:16:17,760 Speaker 3: So is that fluid the whole time, I always thought 335 00:16:17,760 --> 00:16:19,040 Speaker 3: the orgasm was the fluid. 336 00:16:19,880 --> 00:16:23,920 Speaker 2: Let me have a look here. No, the orgasm where 337 00:16:24,120 --> 00:16:27,040 Speaker 2: the male is the climax is the fluid. 338 00:16:27,160 --> 00:16:29,440 Speaker 1: Yes, sorry for being so graphic about this, but it's 339 00:16:29,480 --> 00:16:31,920 Speaker 1: it's science. As you said, you put it under the 340 00:16:31,920 --> 00:16:32,760 Speaker 1: science umbrella. 341 00:16:33,960 --> 00:16:40,120 Speaker 2: Let me have a look at some more information. What's 342 00:16:40,160 --> 00:16:45,160 Speaker 2: it saying here? Yeah, what's til mean thing? 343 00:16:45,240 --> 00:16:45,720 Speaker 1: I learned? 344 00:16:45,880 --> 00:16:52,560 Speaker 2: Oh? Thank you Til. If a female pig orgasms during insemination, 345 00:16:53,280 --> 00:16:57,520 Speaker 2: she'll produce piglets up to six percent more than normal insemination. Right, 346 00:16:58,200 --> 00:17:00,680 Speaker 2: And the orgasm in the female can last up to 347 00:17:00,720 --> 00:17:01,320 Speaker 2: thirty minutes. 348 00:17:01,560 --> 00:17:03,960 Speaker 1: Right. Oh, that's why they seemed to be so happy. 349 00:17:04,480 --> 00:17:08,000 Speaker 2: I have seen at Cincinnati Zoo. I was doing a 350 00:17:08,080 --> 00:17:11,600 Speaker 2: story and they were they knocked out a snow leopard 351 00:17:11,920 --> 00:17:16,800 Speaker 2: and they were using an electronic probe to palpate it 352 00:17:17,240 --> 00:17:21,040 Speaker 2: to get the sperm. 353 00:17:21,320 --> 00:17:24,280 Speaker 1: And why were you watching this because you'd left beyond 354 00:17:24,320 --> 00:17:29,679 Speaker 1: twoth absent. You're just watching it for fun. 355 00:17:31,160 --> 00:17:34,040 Speaker 2: Yeah, that's right. Let's just carry my lab coat and 356 00:17:34,119 --> 00:17:36,639 Speaker 2: just go from place to place looking at weird stuff. 357 00:17:37,040 --> 00:17:39,399 Speaker 1: So, in summary, the pig, if you've got a. 358 00:17:39,440 --> 00:17:40,720 Speaker 2: Pig, lock up your beer. 359 00:17:40,880 --> 00:17:42,480 Speaker 3: Lock up your beer because you don't want like a 360 00:17:42,600 --> 00:17:44,000 Speaker 3: pig getting on to your bed. 361 00:17:46,640 --> 00:17:49,000 Speaker 2: Yeah, lock up your pig. Actually, we've had a drunken 362 00:17:49,040 --> 00:17:49,600 Speaker 2: pig in here. 363 00:17:49,960 --> 00:17:53,399 Speaker 3: When then, Rava, why don't you go back to your 364 00:17:53,480 --> 00:17:54,160 Speaker 3: last half an hour? 365 00:17:54,480 --> 00:17:56,439 Speaker 1: Why don't you go back to watching your snow leopards 366 00:17:56,480 --> 00:17:58,000 Speaker 1: being palpated? Here? 367 00:17:58,160 --> 00:18:14,159 Speaker 5: Wido, it's our podcast. 368 00:18:15,040 --> 00:18:18,720 Speaker 2: And I've always wondered about people who buy those dolls. 369 00:18:19,400 --> 00:18:20,000 Speaker 1: What dolls? 370 00:18:20,520 --> 00:18:25,000 Speaker 2: Newborn baby dolls? Oh yeah, and dolls that resemble children. 371 00:18:25,200 --> 00:18:27,320 Speaker 1: Yeah, what about those ones in the back of That's 372 00:18:27,359 --> 00:18:28,960 Speaker 1: Life magazine or Take five? 373 00:18:29,080 --> 00:18:30,200 Speaker 2: Used to be the men, But it used to be 374 00:18:30,240 --> 00:18:32,680 Speaker 2: that with Franklin Mint, was it? Yes, to sell that stuff? 375 00:18:32,920 --> 00:18:36,000 Speaker 2: Seld By one hundred million dollars installment Make it for 376 00:18:36,119 --> 00:18:36,440 Speaker 2: me now? 377 00:18:36,480 --> 00:18:39,720 Speaker 3: But one week you buy a Harley Davidson clock that 378 00:18:40,200 --> 00:18:43,040 Speaker 3: brought out Peter brock on the quarter hours. I know 379 00:18:43,080 --> 00:18:45,840 Speaker 3: I'm mixing them all up together, and you buy that 380 00:18:45,880 --> 00:18:47,960 Speaker 3: from the Franklin And the next week you buy this. 381 00:18:48,480 --> 00:18:51,840 Speaker 1: Lifelike doll and it looked like a little dead baby. 382 00:18:52,000 --> 00:18:55,439 Speaker 2: Look, that's the thing. She's run a weird newborn babies. 383 00:18:55,480 --> 00:18:56,800 Speaker 2: I want to talk to you about this woman I've 384 00:18:56,800 --> 00:19:00,239 Speaker 2: been reading about this morning, She says. I'm I'm my 385 00:19:00,320 --> 00:19:04,600 Speaker 2: mom to eight dolls. You like this. I breast feed 386 00:19:04,640 --> 00:19:08,879 Speaker 2: them and take them everywhere. She's twenty eight. She looks 387 00:19:08,920 --> 00:19:10,280 Speaker 2: like a very normal woman. 388 00:19:10,680 --> 00:19:13,480 Speaker 1: Would you say, took the picture holding up a hand out. 389 00:19:13,680 --> 00:19:14,159 Speaker 2: Very normal. 390 00:19:14,920 --> 00:19:15,959 Speaker 1: She looks a little bit. 391 00:19:16,160 --> 00:19:16,320 Speaker 4: Uh. 392 00:19:17,720 --> 00:19:19,800 Speaker 2: If I didn't, if I hadn't told you, If I 393 00:19:19,840 --> 00:19:22,320 Speaker 2: told you that, you know she was working in marketing. 394 00:19:22,359 --> 00:19:23,960 Speaker 2: Here you go, fair enough. She doesn't look like an 395 00:19:24,040 --> 00:19:25,200 Speaker 2: unusual person. 396 00:19:25,640 --> 00:19:28,800 Speaker 1: Not marketing so much. Possibly the technical department. 397 00:19:29,080 --> 00:19:33,320 Speaker 2: She says, she's an adoptive mother to these eight reborn dolls. 398 00:19:33,359 --> 00:19:36,960 Speaker 2: They're called reborn. So here's what happened. She became interested 399 00:19:37,000 --> 00:19:40,880 Speaker 2: in realistic dolls after seeing a YouTube video showing off 400 00:19:40,880 --> 00:19:43,960 Speaker 2: a collection. She just wanted to use the doll as 401 00:19:43,960 --> 00:19:47,439 Speaker 2: a prop because she does cosplay. We're diving deeper now, 402 00:19:48,080 --> 00:19:51,120 Speaker 2: but she started to feel attached to the doll so 403 00:19:51,359 --> 00:19:56,800 Speaker 2: her family has grown. Over the last year, her collection 404 00:19:57,080 --> 00:20:00,600 Speaker 2: has grown to eight. She spends about two thir dollars 405 00:20:00,640 --> 00:20:03,119 Speaker 2: on them, and the one of the ones. See some 406 00:20:03,200 --> 00:20:07,680 Speaker 2: of them look like toddlers eighteen months, two years, would 407 00:20:07,680 --> 00:20:10,520 Speaker 2: you say? But she's also got some of those newborn 408 00:20:10,560 --> 00:20:14,440 Speaker 2: ones that she has breastfed in the past, but now 409 00:20:14,480 --> 00:20:17,119 Speaker 2: she bottle feeds them because they can't stay on the breast. Well, 410 00:20:17,160 --> 00:20:20,040 Speaker 2: you'd never be able to leave the house, so she 411 00:20:20,359 --> 00:20:23,320 Speaker 2: bottle feeds them. She makes milk from flour and water. 412 00:20:23,760 --> 00:20:27,160 Speaker 1: Oh, I said, does it when that's why she lacating? 413 00:20:27,200 --> 00:20:29,240 Speaker 2: When she that's when she bottle feeds them, right, okay, 414 00:20:29,400 --> 00:20:30,680 Speaker 2: But does she actually lack tating? 415 00:20:30,720 --> 00:20:30,800 Speaker 4: No? 416 00:20:30,880 --> 00:20:31,280 Speaker 2: I think no. 417 00:20:31,400 --> 00:20:32,760 Speaker 1: I think she's just pretending. 418 00:20:32,960 --> 00:20:37,280 Speaker 2: I think so. I think she said I got attached 419 00:20:37,359 --> 00:20:39,479 Speaker 2: to the first one as if she was adopted child. 420 00:20:39,760 --> 00:20:42,359 Speaker 2: Suddenly I spending money on clothes for her in a bed. 421 00:20:43,040 --> 00:20:46,320 Speaker 2: These dolls are comforting. I'm living my truth of the 422 00:20:46,359 --> 00:20:48,640 Speaker 2: life I want as if I was a mum. There's 423 00:20:48,720 --> 00:20:52,240 Speaker 2: something sad and poignant in that, isn't there? So she 424 00:20:52,400 --> 00:20:55,320 Speaker 2: got she's got some toddler ones, some other ones. There's 425 00:20:55,320 --> 00:20:57,160 Speaker 2: a photof here as I said, with her big family. 426 00:20:57,560 --> 00:21:00,159 Speaker 2: She's got two year old dolls. Summer. She's got when 427 00:21:00,400 --> 00:21:05,080 Speaker 2: Molly and Anthony, Ashley, Elizabeth, Michael and Adam. She's planning 428 00:21:05,080 --> 00:21:09,080 Speaker 2: on getting a new one, Emily this month. Emily, she said, 429 00:21:10,000 --> 00:21:12,959 Speaker 2: looks like a real newborn baby. So here's the routine 430 00:21:12,960 --> 00:21:17,520 Speaker 2: of the day she has with them. She said, I 431 00:21:17,640 --> 00:21:19,920 Speaker 2: keep most of the dolls in cribs in the living room, 432 00:21:20,320 --> 00:21:23,840 Speaker 2: but baby Adam and Jennifer in her oom because they're 433 00:21:23,840 --> 00:21:25,600 Speaker 2: too small to be on their own with the others, 434 00:21:25,720 --> 00:21:27,360 Speaker 2: of course, and the other says they get older want 435 00:21:27,359 --> 00:21:30,919 Speaker 2: their own space. She says, I have a routine. I 436 00:21:31,000 --> 00:21:33,760 Speaker 2: make them breakfast and get them all dressed. I put 437 00:21:33,800 --> 00:21:37,600 Speaker 2: a movie on for them. When we've nearly done a 438 00:21:37,600 --> 00:21:41,600 Speaker 2: Disney marathon. They go everywhere with me. By seven pm, 439 00:21:41,800 --> 00:21:44,320 Speaker 2: I get them ready for bed and I play some 440 00:21:44,440 --> 00:21:48,920 Speaker 2: songs on an okarina. I googled what that is? 441 00:21:49,680 --> 00:21:52,040 Speaker 1: Strange looking things? How do you know you blow winded it? 442 00:21:52,040 --> 00:21:55,520 Speaker 1: I've got one at home. No, let's pronounce ocarina. 443 00:21:56,800 --> 00:21:57,480 Speaker 2: YEH, got one. 444 00:21:57,520 --> 00:21:58,399 Speaker 1: I got one. 445 00:22:00,200 --> 00:22:01,960 Speaker 2: It's like a it's like a pottery. 446 00:22:02,080 --> 00:22:03,960 Speaker 3: It looks like it looks like the head of a 447 00:22:03,960 --> 00:22:07,520 Speaker 3: golf club with the holes in it. Yeah, and you're blowing. 448 00:22:08,160 --> 00:22:09,560 Speaker 2: Is now the time to tell me you also have 449 00:22:09,560 --> 00:22:10,280 Speaker 2: these dolls? 450 00:22:11,160 --> 00:22:12,679 Speaker 1: I've been meaning to tell you. I do have a 451 00:22:12,680 --> 00:22:17,440 Speaker 1: doll at home, always ready to go. So as if 452 00:22:17,480 --> 00:22:20,240 Speaker 1: those dolls that's always open. Okay, As if. 453 00:22:20,080 --> 00:22:24,040 Speaker 2: Those dolls aren't being irritated enough now they will listen 454 00:22:24,080 --> 00:22:27,119 Speaker 2: to her playing the arena? Who's old? Are my ears closed? Please? 455 00:22:27,119 --> 00:22:27,879 Speaker 1: Who's the dad? 456 00:22:29,359 --> 00:22:31,919 Speaker 2: Brendan? I haven't delved into the sad side of the story. 457 00:22:32,119 --> 00:22:35,840 Speaker 2: Something tells me she might live without a partner because. 458 00:22:35,560 --> 00:22:37,520 Speaker 1: It can't be ken because he's just got a mound. 459 00:22:37,720 --> 00:22:39,760 Speaker 2: Yeah, No, I don't think there's any man in her life. 460 00:22:39,800 --> 00:22:42,400 Speaker 2: She said, Look, this is maybe this is the thing. 461 00:22:42,400 --> 00:22:46,840 Speaker 2: She's twenty eight, she's always wanted babies, and this is 462 00:22:47,560 --> 00:22:48,880 Speaker 2: her route to that. 463 00:22:49,040 --> 00:22:51,040 Speaker 1: Well, she's certainly not going to get any sort of 464 00:22:51,080 --> 00:22:52,800 Speaker 1: route now. Any guy comes home. 465 00:22:53,400 --> 00:22:55,560 Speaker 2: The scale of one to ten of I'm out of here. 466 00:22:55,880 --> 00:22:57,439 Speaker 2: If you're a guy and you go back to her 467 00:22:57,480 --> 00:23:01,000 Speaker 2: house and you saw what are those squish mellows? If 468 00:23:01,000 --> 00:23:04,000 Speaker 2: you saw a bed covered in squishmallows, a bed covered 469 00:23:04,840 --> 00:23:08,720 Speaker 2: in actual cats, or a bed covered in these dolls, 470 00:23:09,119 --> 00:23:10,680 Speaker 2: which on the scale where do they. 471 00:23:10,600 --> 00:23:16,080 Speaker 1: Sit depends what the woman looks like, so it. 472 00:23:16,000 --> 00:23:18,320 Speaker 2: Would make no difference to you if she was attractive. 473 00:23:18,400 --> 00:23:20,359 Speaker 3: So with Sydney Sweetey, she could have any amount of 474 00:23:20,359 --> 00:23:21,480 Speaker 3: shit on a bed. 475 00:23:21,640 --> 00:23:23,080 Speaker 2: What if there was actual shit on a bed? 476 00:23:23,160 --> 00:23:23,280 Speaker 5: Oh? 477 00:23:25,320 --> 00:23:26,600 Speaker 2: Have I found your line? 478 00:23:27,640 --> 00:23:31,920 Speaker 1: I think you just crossed it.