1 00:00:00,520 --> 00:00:03,960 Speaker 1: I'll get a team. It's Tiffany Ankle because David Brian Kevin, 2 00:00:04,000 --> 00:00:06,880 Speaker 1: Patrick Gillespie, it's the Bloody Project, that's you, it's us. 3 00:00:07,200 --> 00:00:10,719 Speaker 1: We're stumbling like piss blokes towards Christmas and I couldn't 4 00:00:10,720 --> 00:00:13,920 Speaker 1: be more excited. Speaking of booze, Hi tiv. 5 00:00:14,360 --> 00:00:16,240 Speaker 2: Speaking of booze. 6 00:00:16,160 --> 00:00:18,439 Speaker 1: You drink now and then, not much, every now and 7 00:00:18,480 --> 00:00:21,840 Speaker 1: then much? What's your no? I know you don't really 8 00:00:21,880 --> 00:00:24,400 Speaker 1: drink much, but if you do drink, what do you drink? 9 00:00:24,560 --> 00:00:24,639 Speaker 2: What? 10 00:00:24,800 --> 00:00:25,319 Speaker 1: You go to? 11 00:00:26,320 --> 00:00:30,160 Speaker 2: Gin tonic? Partial to a gin and tonic? Right? 12 00:00:30,520 --> 00:00:34,000 Speaker 1: Have you ever been legless? Shit faced? You know? It's 13 00:00:34,040 --> 00:00:35,680 Speaker 1: been a lot of my youth getting legless. 14 00:00:35,760 --> 00:00:36,000 Speaker 2: YEP. 15 00:00:37,159 --> 00:00:39,519 Speaker 1: I actually don't know if we're allowed to say that anymore. 16 00:00:39,640 --> 00:00:42,000 Speaker 1: But seeing as you and I you and I know you, 17 00:00:42,040 --> 00:00:45,880 Speaker 1: and I know Don Elgan, so I'm pretty sure who's 18 00:00:45,880 --> 00:00:48,760 Speaker 1: a one legged paralympian And he calls himself that. So 19 00:00:49,320 --> 00:00:52,640 Speaker 1: I'm blaming Don. Don's given us the green light? What 20 00:00:52,720 --> 00:00:56,800 Speaker 1: about you, Gilespo, I can't I can't see you drinking much, 21 00:00:56,840 --> 00:00:57,800 Speaker 1: if any booze. 22 00:00:58,800 --> 00:01:02,320 Speaker 2: I don't drink much, not because I have any particular 23 00:01:02,400 --> 00:01:06,319 Speaker 2: objection to it, but because my wife doesn't drink at all, 24 00:01:07,600 --> 00:01:13,960 Speaker 2: so you know, to drink it myself. Yeah, pretty much. Yeah, 25 00:01:14,319 --> 00:01:15,920 Speaker 2: it's yeah. 26 00:01:15,959 --> 00:01:16,720 Speaker 1: So I don't drink a lot. 27 00:01:16,920 --> 00:01:19,000 Speaker 2: You know. I'll have the occasional beer or glass of 28 00:01:19,000 --> 00:01:21,440 Speaker 2: wine if there's one open, but that's about it. Really. 29 00:01:22,040 --> 00:01:23,840 Speaker 1: How many times in your life do you reckon you've 30 00:01:23,840 --> 00:01:24,360 Speaker 1: been drunk? 31 00:01:25,000 --> 00:01:25,120 Speaker 2: Oh? 32 00:01:25,240 --> 00:01:25,640 Speaker 1: Quite a lot. 33 00:01:25,680 --> 00:01:31,640 Speaker 2: When I was younger, he's in university, I strunk a 34 00:01:31,720 --> 00:01:33,240 Speaker 2: fair amount of the time, I suspect. 35 00:01:33,959 --> 00:01:37,320 Speaker 1: Wow. Wow, he says that with some pride tip. That's 36 00:01:37,360 --> 00:01:40,440 Speaker 1: the this. 37 00:01:40,440 --> 00:01:44,160 Speaker 2: Is I am so old that I remember going to 38 00:01:44,200 --> 00:01:46,880 Speaker 2: the university what was called the rec Club at the 39 00:01:46,959 --> 00:01:49,080 Speaker 2: University of Queensland every Friday night and they used to 40 00:01:49,120 --> 00:01:54,040 Speaker 2: have fifty cent cans of Swan beer. Was I mean 41 00:01:54,480 --> 00:01:56,360 Speaker 2: you go in there with a five dollar night slapping 42 00:01:56,400 --> 00:01:58,800 Speaker 2: on the counter and that it do you for the night? Wow? 43 00:02:00,680 --> 00:02:02,960 Speaker 1: What ten? You'd drink ten cans? 44 00:02:04,400 --> 00:02:07,240 Speaker 2: Oh? Well, I try, Wow, I. 45 00:02:07,160 --> 00:02:09,520 Speaker 1: Don't know anything about beer? Is that a terrible beer? 46 00:02:09,600 --> 00:02:10,440 Speaker 1: And okay, I guess that. 47 00:02:10,520 --> 00:02:13,400 Speaker 2: When you're fifty cents is what it is? 48 00:02:13,880 --> 00:02:18,080 Speaker 1: Yes, yeaheah. How many times have you been drunk? Tiff? 49 00:02:18,919 --> 00:02:22,120 Speaker 2: I couldn't tell you, but yeah, grown up in tazzy 50 00:02:22,919 --> 00:02:23,200 Speaker 2: We did. 51 00:02:23,480 --> 00:02:25,079 Speaker 1: We did on weekends a few times. 52 00:02:25,280 --> 00:02:27,640 Speaker 2: Yeah, they'll get their bottle of passion pop and away 53 00:02:27,720 --> 00:02:28,079 Speaker 2: we go. 54 00:02:28,960 --> 00:02:31,680 Speaker 1: I've been the dress I've been. I've been the designated 55 00:02:31,760 --> 00:02:37,200 Speaker 1: driver for forty years. I'm just the boring bloke that 56 00:02:37,280 --> 00:02:40,400 Speaker 1: drives everyone to and from wherever they're going to get pissed. 57 00:02:41,160 --> 00:02:43,320 Speaker 2: That's what my wife does. I always have a built 58 00:02:43,320 --> 00:02:45,840 Speaker 2: in designated driver because she doesn't drink. 59 00:02:46,919 --> 00:02:54,000 Speaker 1: Does she not drink for moral reasons, ethical, religious, or health, 60 00:02:54,360 --> 00:02:55,960 Speaker 1: or she just doesn't like it. 61 00:02:56,760 --> 00:03:00,960 Speaker 2: She'll like it, sheill like taste of it, so unlike today, 62 00:03:01,000 --> 00:03:03,520 Speaker 2: where everything's got a ton of sugar in it and 63 00:03:03,680 --> 00:03:07,040 Speaker 2: the alcohol is a secondary consideration. Back in the day, 64 00:03:07,800 --> 00:03:10,639 Speaker 2: when I guess she was being tempted with alcohol, most 65 00:03:10,680 --> 00:03:12,920 Speaker 2: of her tasted pretty awful and she wasn't keen on it. 66 00:03:15,320 --> 00:03:17,440 Speaker 1: I think you told us in an episode not too 67 00:03:17,440 --> 00:03:20,480 Speaker 1: long ago that I'm sure you told us that the 68 00:03:20,639 --> 00:03:25,600 Speaker 1: youngies are drinking less than ever and having non alcoholic 69 00:03:25,760 --> 00:03:26,680 Speaker 1: kind of options. 70 00:03:28,160 --> 00:03:33,680 Speaker 2: Yeah, the stats are really interesting that today's teenagers drink 71 00:03:33,880 --> 00:03:38,160 Speaker 2: less than their parents did and less than their grandparents 72 00:03:38,160 --> 00:03:42,000 Speaker 2: did when they were the same age, considerably less and 73 00:03:42,600 --> 00:03:45,800 Speaker 2: the reason for that is likely to be that they 74 00:03:45,880 --> 00:03:48,480 Speaker 2: get both mean hits just from looking at their phone. 75 00:03:48,560 --> 00:03:50,880 Speaker 2: They don't need to go out and get messy in public. 76 00:03:51,520 --> 00:03:56,360 Speaker 1: Yeah right. And I also heard on a podcast conversation 77 00:03:56,560 --> 00:04:00,840 Speaker 1: yesterday that the youngsters, and by youngsters I mean legally 78 00:04:01,600 --> 00:04:08,160 Speaker 1: eighteen plus youngsters shagging less than their parents and grandparents. 79 00:04:08,200 --> 00:04:12,760 Speaker 2: In general, pursuing risky behavior a lot less so, less violent, 80 00:04:14,120 --> 00:04:18,680 Speaker 2: less likely to have sex, less likely to have teenage pregnancy, 81 00:04:19,120 --> 00:04:22,599 Speaker 2: less likely to drink, basically, less likely to get dopamine 82 00:04:22,640 --> 00:04:25,640 Speaker 2: hits from things that require them to leave their bedroom, 83 00:04:26,080 --> 00:04:27,920 Speaker 2: and so because they don't need to. 84 00:04:29,040 --> 00:04:31,640 Speaker 1: So that's the upside of social media. Yeah, there's the. 85 00:04:31,680 --> 00:04:33,520 Speaker 2: Upside is you're not likely. 86 00:04:33,320 --> 00:04:36,360 Speaker 1: To get outside of Instagram, as we've got less boys 87 00:04:36,400 --> 00:04:39,800 Speaker 1: and girls making mating. Well, that was a faux pa, 88 00:04:41,279 --> 00:04:43,640 Speaker 1: That was something I said that it was accurate that 89 00:04:43,680 --> 00:04:48,120 Speaker 1: I didn't mean. But also, yeah, producing less offspring because 90 00:04:48,120 --> 00:04:51,960 Speaker 1: they're addicted to the gram and even if they were not, 91 00:04:52,640 --> 00:04:54,960 Speaker 1: they'd still be producing less offspring because, as you know, 92 00:04:55,080 --> 00:04:59,760 Speaker 1: the sperm counts are going so badly that getting someone pregnanty, 93 00:05:00,040 --> 00:05:03,240 Speaker 1: it is quite a quite a feat these days. And 94 00:05:03,279 --> 00:05:05,360 Speaker 1: in case you haven't been paying attention for the last 95 00:05:05,360 --> 00:05:07,880 Speaker 1: three years. To David Gillespie, everyone just a heads up. 96 00:05:07,920 --> 00:05:14,320 Speaker 1: This is probably the last century of humanity, so enjoy it. 97 00:05:14,320 --> 00:05:17,200 Speaker 1: It seems we're on the home straight. Either we're all 98 00:05:17,200 --> 00:05:19,839 Speaker 1: going to die because we can't produce, you know, the 99 00:05:19,839 --> 00:05:24,000 Speaker 1: bits and pieces that make new humans. Either that, or 100 00:05:24,600 --> 00:05:28,640 Speaker 1: we're all going to be robots, or we're all going 101 00:05:28,640 --> 00:05:31,880 Speaker 1: to be taken over by robots. Either way, enjoy the 102 00:05:31,880 --> 00:05:32,600 Speaker 1: next few years. 103 00:05:34,440 --> 00:05:37,080 Speaker 2: I was thinking about a conversation we had at the 104 00:05:37,200 --> 00:05:41,360 Speaker 2: last time we talked about the AI. You just listened 105 00:05:41,360 --> 00:05:46,840 Speaker 2: to a podcast I think it was something the something 106 00:05:46,880 --> 00:05:47,520 Speaker 2: or other CEO. 107 00:05:48,320 --> 00:05:50,719 Speaker 1: Oh, yeah, Diary of a CEO Stephen Bartlett. 108 00:05:51,160 --> 00:05:54,000 Speaker 2: Yeah, and he'd been interviewing someone to do with AI 109 00:05:54,320 --> 00:05:55,880 Speaker 2: and I went away and listened to that. You'll be 110 00:05:55,920 --> 00:05:57,880 Speaker 2: glad to know you well, I made. 111 00:05:57,760 --> 00:06:01,320 Speaker 1: These suggestions, I think, you know, I enter. Yeah, that's right. 112 00:06:01,360 --> 00:06:04,000 Speaker 2: That's why I bothered, because you know, it was so 113 00:06:04,040 --> 00:06:09,200 Speaker 2: important that you sent it to me long, so I 114 00:06:09,240 --> 00:06:11,599 Speaker 2: had to I had to have it on double speed 115 00:06:11,680 --> 00:06:14,840 Speaker 2: just to get through it. But it Yeah, it was 116 00:06:14,839 --> 00:06:20,760 Speaker 2: all right. One thing you asked me during the last conversation, 117 00:06:21,400 --> 00:06:23,120 Speaker 2: and I don't think I gave you a good answer, 118 00:06:24,040 --> 00:06:28,600 Speaker 2: which is how close are we to artificial general intelligence 119 00:06:28,680 --> 00:06:31,719 Speaker 2: or AGI is what they refer to in that, And 120 00:06:31,760 --> 00:06:33,520 Speaker 2: they say that's the big bad thing, that's where it 121 00:06:33,600 --> 00:06:37,200 Speaker 2: becomes essentially human in terms of its ability to think. Yeah, 122 00:06:38,200 --> 00:06:39,960 Speaker 2: And I don't think I gave you a really good 123 00:06:40,000 --> 00:06:43,960 Speaker 2: answer to that. And I want to Now, the thing 124 00:06:44,000 --> 00:06:46,720 Speaker 2: about the AI that we are all used to using, 125 00:06:46,839 --> 00:06:49,559 Speaker 2: like Gemini and chat GPT and all those sorts of things, 126 00:06:50,279 --> 00:06:52,960 Speaker 2: is that they sound human, and they behave human, and 127 00:06:52,960 --> 00:06:56,440 Speaker 2: they give us human like responses. But they are only 128 00:06:56,440 --> 00:06:59,480 Speaker 2: as good as the data they're trained on. So if 129 00:06:59,480 --> 00:07:03,000 Speaker 2: you were to try any of those AI on the 130 00:07:03,040 --> 00:07:06,400 Speaker 2: sum of human knowledge as it existed in eighteen hundred, yes, 131 00:07:07,560 --> 00:07:10,840 Speaker 2: and then ask it to improve transport, it wouldn't invent 132 00:07:10,880 --> 00:07:15,320 Speaker 2: the automobile because the only thing it knew was what 133 00:07:15,480 --> 00:07:18,440 Speaker 2: was available in eighteen hundred. So it might suggest to 134 00:07:18,480 --> 00:07:22,440 Speaker 2: you ways to improve the stagecoach, but it wouldn't invent 135 00:07:22,480 --> 00:07:25,400 Speaker 2: the automobile. And I guess that's probably to me the 136 00:07:25,480 --> 00:07:31,119 Speaker 2: defining difference between these chatbots and human intelligence today, which 137 00:07:31,200 --> 00:07:36,880 Speaker 2: is humans can invent things and do these ais cannot 138 00:07:36,880 --> 00:07:40,920 Speaker 2: invent anything. They can summarize things really really well and 139 00:07:41,000 --> 00:07:45,280 Speaker 2: make them easy to understand, but they can't invent anything. 140 00:07:46,200 --> 00:07:51,280 Speaker 1: So they can't create, like, they don't have creativity like 141 00:07:51,360 --> 00:07:54,920 Speaker 1: we when we talk about intelligence, obviously we're talking about 142 00:07:55,080 --> 00:07:59,040 Speaker 1: a spectrum of things. But that kind of intelligence, well, 143 00:07:59,080 --> 00:08:02,280 Speaker 1: it doesn't really have intelligence either. That's the irony. 144 00:08:03,800 --> 00:08:05,200 Speaker 2: Well, if you were to think of if you were 145 00:08:05,240 --> 00:08:08,160 Speaker 2: to think about, say in human terms, they don't have 146 00:08:08,240 --> 00:08:10,840 Speaker 2: the research and development arm So a lot of companies 147 00:08:10,880 --> 00:08:15,160 Speaker 2: spend a fairly significant part of their budget on research 148 00:08:15,200 --> 00:08:18,880 Speaker 2: and development, and a company like Google, for example, spends 149 00:08:18,920 --> 00:08:23,680 Speaker 2: twenty percent of its budget on research and development. And 150 00:08:23,760 --> 00:08:28,360 Speaker 2: that's something that where there's no direct, measurable, sellable output 151 00:08:28,640 --> 00:08:31,600 Speaker 2: from what they're doing. They're just being asked to think 152 00:08:31,640 --> 00:08:34,400 Speaker 2: about new things and create them if they can, and 153 00:08:34,480 --> 00:08:38,320 Speaker 2: most of them will fail, but some of them won't. 154 00:08:39,800 --> 00:08:43,920 Speaker 2: And that capacity to invent is something that AI today 155 00:08:44,320 --> 00:08:44,800 Speaker 2: can't do. 156 00:08:46,840 --> 00:08:50,760 Speaker 1: And so when we talk about artificial general intelligence where 157 00:08:51,040 --> 00:08:54,520 Speaker 1: essentially for one of a better term it becomes conscious 158 00:08:54,679 --> 00:09:00,480 Speaker 1: or sentient or fill in the adjective, do you think 159 00:09:00,520 --> 00:09:01,400 Speaker 1: that will ever happen? 160 00:09:01,520 --> 00:09:07,320 Speaker 2: Firstly, it very well may happen. People have been predicting 161 00:09:07,360 --> 00:09:12,079 Speaker 2: it now for at least twenty years, but whether it 162 00:09:12,120 --> 00:09:15,760 Speaker 2: will happen from the existing set of technology is difficult 163 00:09:15,840 --> 00:09:19,280 Speaker 2: to say. To me, there's no obvious trajectory from the 164 00:09:19,360 --> 00:09:22,920 Speaker 2: chatbots we're dealing with today to artificial general intelligence other 165 00:09:23,000 --> 00:09:28,640 Speaker 2: than that they look human. Yes, And whereas oh, sorry, 166 00:09:28,920 --> 00:09:31,600 Speaker 2: I was just going to say, whereas as I said, 167 00:09:31,720 --> 00:09:34,880 Speaker 2: they're not capable of inventing something, Whereas an AGI is 168 00:09:34,920 --> 00:09:39,720 Speaker 2: a different thing altogether. It is capable of inventing. And 169 00:09:39,760 --> 00:09:43,480 Speaker 2: when you create something with that much firepower, with that capability, 170 00:09:44,120 --> 00:09:48,480 Speaker 2: that's why it's dangerous, because then it can solve problems 171 00:09:48,520 --> 00:09:52,920 Speaker 2: we haven't even invented and may not even think our problems. 172 00:09:53,679 --> 00:09:58,440 Speaker 2: And the step from where we are now to very 173 00:09:58,679 --> 00:10:02,360 Speaker 2: very fast development under AI of itself, which is what 174 00:10:02,440 --> 00:10:05,520 Speaker 2: an AGI would be able to do, is where we 175 00:10:05,559 --> 00:10:12,880 Speaker 2: are likely to get. You made surplus to requirements. 176 00:10:11,440 --> 00:10:13,720 Speaker 1: And you may or may not know the answer to this, 177 00:10:13,840 --> 00:10:17,880 Speaker 1: but you'll definitely know more than I know. How far 178 00:10:17,920 --> 00:10:22,240 Speaker 1: away away from quantum computing being a thing like I 179 00:10:22,280 --> 00:10:25,679 Speaker 1: know that I think there's a couple of quantum computers 180 00:10:25,720 --> 00:10:28,800 Speaker 1: in the world, I'm not sure, but where they become 181 00:10:29,840 --> 00:10:32,560 Speaker 1: for one of better term mainstream or just part of 182 00:10:32,640 --> 00:10:33,280 Speaker 1: our culture. 183 00:10:33,360 --> 00:10:35,720 Speaker 2: I don't know. I can't give you a definitive answer 184 00:10:35,760 --> 00:10:37,640 Speaker 2: to that. I know that it's a race, and it's on, 185 00:10:37,920 --> 00:10:42,839 Speaker 2: and we are progressing very quickly towards it. Yes, at 186 00:10:42,840 --> 00:10:46,360 Speaker 2: the moment, they're quite expensive and not highly distributed, but 187 00:10:47,400 --> 00:10:49,719 Speaker 2: that is unlikely to remain the case for very long. 188 00:10:49,760 --> 00:10:53,720 Speaker 1: I would have thought, and I mean, I can't remember, 189 00:10:53,720 --> 00:10:57,840 Speaker 1: but it's something crazy like it can solve problems that 190 00:10:57,880 --> 00:11:01,640 Speaker 1: would take a thousand is on a normal computer or 191 00:11:01,640 --> 00:11:05,920 Speaker 1: even a supercomputer that can solve that in thirty seconds. 192 00:11:05,559 --> 00:11:09,800 Speaker 2: Or some Yeah, they have significantly greater capacity than current computing. 193 00:11:10,559 --> 00:11:14,160 Speaker 1: Yeah, and do you understand I don't so, and I 194 00:11:14,240 --> 00:11:17,440 Speaker 1: know this is not your area of expertise, but your 195 00:11:17,559 --> 00:11:23,559 Speaker 1: expertise does stretch. Can you explain what a quantum computer 196 00:11:23,800 --> 00:11:25,959 Speaker 1: is compared to a regular computer. 197 00:11:26,480 --> 00:11:31,200 Speaker 2: So, quantum computers do their processing at the quantum level, 198 00:11:31,240 --> 00:11:35,360 Speaker 2: which is at the atomic and subatomic level, as opposed 199 00:11:35,360 --> 00:11:39,360 Speaker 2: to at the atomic level, which is what current computers do. 200 00:11:39,800 --> 00:11:45,000 Speaker 2: So they're manipulating electrons and so on, which allows them 201 00:11:45,000 --> 00:11:48,800 Speaker 2: to get a lot more into the physical space and 202 00:11:49,920 --> 00:11:54,080 Speaker 2: capacity than you would in a normal computer. Honestly, look, 203 00:11:54,080 --> 00:11:55,960 Speaker 2: if there is a computer nerd listening to this and 204 00:11:56,000 --> 00:11:58,600 Speaker 2: they go, oh my god, that's rubbish, then I suggest 205 00:11:58,600 --> 00:12:02,720 Speaker 2: google it, since I looked properly at this. 206 00:12:03,480 --> 00:12:06,080 Speaker 1: Well. Also, everyone keep in mind that I did ask him, 207 00:12:06,120 --> 00:12:08,880 Speaker 1: and I did throw him under the bus, and he 208 00:12:08,920 --> 00:12:11,000 Speaker 1: definitely knows. I don't know if he knows more than Tiff, 209 00:12:11,080 --> 00:12:13,560 Speaker 1: but he definitely knows. Tiff, do you want to tell 210 00:12:13,600 --> 00:12:14,920 Speaker 1: us what a quantum computer is? 211 00:12:16,080 --> 00:12:16,440 Speaker 2: Already? 212 00:12:18,040 --> 00:12:18,840 Speaker 1: It's happened out. 213 00:12:19,120 --> 00:12:19,200 Speaker 2: Ye. 214 00:12:20,760 --> 00:12:22,640 Speaker 1: I don't know how we got there because we started 215 00:12:22,679 --> 00:12:28,200 Speaker 1: with how much booze do you both drink? It's like, well, 216 00:12:28,320 --> 00:12:31,480 Speaker 1: we all know there's no logical kind of progression or 217 00:12:32,040 --> 00:12:35,640 Speaker 1: thread to any of our conversations, so we definitely don't 218 00:12:35,640 --> 00:12:39,520 Speaker 1: want to start being logical now. So you wrote recently, 219 00:12:41,160 --> 00:12:46,040 Speaker 1: you wrote an article called how to Uncure Cancer? What 220 00:12:46,360 --> 00:12:50,680 Speaker 1: prompted that? Firstly, and then maybe if you can unpack 221 00:12:50,720 --> 00:12:51,160 Speaker 1: it with us. 222 00:12:52,200 --> 00:12:55,120 Speaker 2: What prompted it was an announcement a couple of weeks 223 00:12:55,120 --> 00:12:57,880 Speaker 2: ago or a week ago now in the US that 224 00:12:58,000 --> 00:13:05,120 Speaker 2: they were making no longer suggesting that mothers have the 225 00:13:05,240 --> 00:13:10,560 Speaker 2: hep well that infants be given the hepatitis B vaccination 226 00:13:11,040 --> 00:13:15,120 Speaker 2: at birth. So since nineteen ninety one in the United States, 227 00:13:16,080 --> 00:13:20,840 Speaker 2: infants have been given the hepatitis B vaccination within twenty 228 00:13:20,840 --> 00:13:25,120 Speaker 2: four hours of birth. So it's in Australia, I think 229 00:13:25,120 --> 00:13:30,000 Speaker 2: it's since two thousand, in the UK since twenty seventeen. 230 00:13:30,000 --> 00:13:31,880 Speaker 2: We might talk about that an little bit more detail later, 231 00:13:31,960 --> 00:13:37,360 Speaker 2: but it's the only vaccination that is given so quickly. 232 00:13:37,679 --> 00:13:43,040 Speaker 2: So you might say, well, why are you vaccinating anybody 233 00:13:43,120 --> 00:13:45,960 Speaker 2: for anything, particularly a virus. So let's just step back 234 00:13:45,960 --> 00:13:47,640 Speaker 2: a bit and say what hepatitis B is. 235 00:13:48,320 --> 00:13:49,280 Speaker 1: So it's a. 236 00:13:49,320 --> 00:13:53,720 Speaker 2: Virus that infects the human liver, and if it infects 237 00:13:53,720 --> 00:13:58,439 Speaker 2: an adult, there's not a lot of downside. There are 238 00:13:58,480 --> 00:14:04,120 Speaker 2: some symptoms of adults clear it within weeks, so it's 239 00:14:04,760 --> 00:14:07,080 Speaker 2: a dose of the fluid style of symptoms with a 240 00:14:07,080 --> 00:14:09,959 Speaker 2: bit of jaundice in adults who are infected with it. 241 00:14:10,360 --> 00:14:15,800 Speaker 2: Our immune system is extremely efficient at dealing with it. 242 00:14:15,880 --> 00:14:19,680 Speaker 2: With babies, it's a different thing altogether. The stats flip 243 00:14:20,120 --> 00:14:24,240 Speaker 2: and ninety percent of infants who are infected with hepatitis 244 00:14:24,320 --> 00:14:31,160 Speaker 2: B never clear the virus, and the problem with that 245 00:14:31,400 --> 00:14:35,280 Speaker 2: is that this particular virus interferes with DNA in a 246 00:14:35,320 --> 00:14:40,560 Speaker 2: way that it can predictably result in liver cancer, so 247 00:14:41,880 --> 00:14:46,920 Speaker 2: not quickly, but a baby that's infected with it has 248 00:14:46,960 --> 00:14:51,320 Speaker 2: a higher, much higher probability than normal population of having 249 00:14:51,360 --> 00:14:56,880 Speaker 2: liver cancer in their forties. So that's why I call 250 00:14:56,920 --> 00:14:59,440 Speaker 2: it the article how to Uncure Cancer. So we've got 251 00:14:59,440 --> 00:15:03,560 Speaker 2: this thing that we know stops a baby becoming infected 252 00:15:03,600 --> 00:15:08,040 Speaker 2: with it if it's given within twenty four hours, and 253 00:15:08,920 --> 00:15:12,360 Speaker 2: we know that if we do that, we will significantly 254 00:15:12,400 --> 00:15:15,080 Speaker 2: reduce So the studies, the big randomized trials on this 255 00:15:15,160 --> 00:15:17,560 Speaker 2: say when I say significantly, I mean by eighty eighty 256 00:15:17,600 --> 00:15:22,000 Speaker 2: five percent reduction in rate of liver cancer in vaccinated 257 00:15:22,040 --> 00:15:24,920 Speaker 2: populations of babies. Now we've got really good data on 258 00:15:24,960 --> 00:15:28,840 Speaker 2: this stuff because it has been a significant thing in 259 00:15:28,840 --> 00:15:31,360 Speaker 2: the United States since nineteen ninety one, in Australia since 260 00:15:31,360 --> 00:15:34,240 Speaker 2: two thousand and there have been big trials on this. 261 00:15:34,400 --> 00:15:38,160 Speaker 2: There was a major trial in China eighty thousand babies, 262 00:15:38,240 --> 00:15:41,360 Speaker 2: randomized control, controlled trial, no one knew who was getting 263 00:15:41,360 --> 00:15:45,200 Speaker 2: it and who wasn't, and the rates of reduction in 264 00:15:45,240 --> 00:15:49,640 Speaker 2: cancer in that on follow up were consistent with everything 265 00:15:49,640 --> 00:15:56,360 Speaker 2: else eighty five percent. So we know this works. And 266 00:15:57,480 --> 00:15:59,640 Speaker 2: the reason it works is quite interesting, I think, because 267 00:16:00,000 --> 00:16:06,360 Speaker 2: so the reason a baby needs the vaccination so quickly 268 00:16:06,520 --> 00:16:09,720 Speaker 2: is that if the baby gets the virus from their mother, 269 00:16:09,760 --> 00:16:16,000 Speaker 2: which is primarily how they get it, then the immune 270 00:16:16,000 --> 00:16:20,160 Speaker 2: system at that point at birth thinks it's part of 271 00:16:20,200 --> 00:16:25,360 Speaker 2: the furniture. So the immune system thinks, oh, this isn't 272 00:16:25,520 --> 00:16:28,880 Speaker 2: something I need to be bothered with. This is actually 273 00:16:29,080 --> 00:16:30,840 Speaker 2: this is part of the human body. I won't be 274 00:16:30,840 --> 00:16:34,840 Speaker 2: attacking that. Whereas an adult that gets the virus, you know, 275 00:16:35,200 --> 00:16:37,640 Speaker 2: they've been going their whole life without it, and suddenly 276 00:16:37,720 --> 00:16:40,400 Speaker 2: it appears the immune system harks up and attacks it. 277 00:16:41,360 --> 00:16:43,760 Speaker 2: And that doesn't happen in newborns who are born with 278 00:16:43,800 --> 00:16:47,840 Speaker 2: the virus or who contracted soon after birth. And so 279 00:16:48,520 --> 00:16:52,200 Speaker 2: the idea was, well, let's give the vaccination at that point, 280 00:16:52,760 --> 00:16:55,960 Speaker 2: teach the body that this is something that needs to 281 00:16:56,000 --> 00:16:58,520 Speaker 2: be dealt with, and do it. And so in the 282 00:16:58,600 --> 00:17:02,880 Speaker 2: United States, the statistics dramatic. You know, you go from 283 00:17:03,120 --> 00:17:07,080 Speaker 2: you know, less than one percent end up with the 284 00:17:07,160 --> 00:17:13,399 Speaker 2: virus after vaccination, So it dramatic. And for the US 285 00:17:13,440 --> 00:17:19,119 Speaker 2: to suddenly decide because they've convinced themselves of vaccines cause autism, 286 00:17:19,280 --> 00:17:21,720 Speaker 2: for which there is absolutely no proof by the way 287 00:17:23,160 --> 00:17:26,439 Speaker 2: they've convinced themselves of that. They've said, oh, you know 288 00:17:26,560 --> 00:17:30,320 Speaker 2: this thing that's been effectively reducing the incidence of liver cancer, 289 00:17:31,440 --> 00:17:34,359 Speaker 2: we're going to stop doing that now now we know 290 00:17:34,440 --> 00:17:37,080 Speaker 2: what this looks like when you do that. Because the 291 00:17:37,200 --> 00:17:41,240 Speaker 2: UK and Australia a little bit earlier on, but the 292 00:17:41,320 --> 00:17:44,840 Speaker 2: UK until twenty seventeen did it that way. The UK 293 00:17:45,040 --> 00:17:49,800 Speaker 2: had a policy of not vaccinating infants. Their policy was 294 00:17:49,880 --> 00:17:53,720 Speaker 2: to only vaccinate people at risk because it's cheaper. So 295 00:17:54,119 --> 00:17:56,159 Speaker 2: let's just talk about how this virus is transmitted in 296 00:17:56,200 --> 00:17:58,680 Speaker 2: the first place. So it's a blood blood transmission virus. 297 00:17:58,680 --> 00:18:01,720 Speaker 2: You can transmit it by you know, exposure to someone 298 00:18:01,760 --> 00:18:05,040 Speaker 2: else's blood. You know, Grannie kissing a wound on a 299 00:18:05,200 --> 00:18:08,720 Speaker 2: child's knee, if Grannie's infected child might get it from that, 300 00:18:10,240 --> 00:18:14,159 Speaker 2: from saliva, so bodily fluid exchange, also from sexual contact, 301 00:18:14,200 --> 00:18:16,919 Speaker 2: so it's transmitted that way. It's different from hepatitis A, 302 00:18:17,880 --> 00:18:22,160 Speaker 2: which is transmitted by eating food which has been you know, 303 00:18:23,280 --> 00:18:26,840 Speaker 2: infected with the virum. So hepatitis A is transmitted through 304 00:18:26,880 --> 00:18:30,359 Speaker 2: food and water. Hepatitis B is through blood, just like 305 00:18:30,440 --> 00:18:37,240 Speaker 2: hepatitis C. So the UK said, well, very few people 306 00:18:37,240 --> 00:18:39,040 Speaker 2: are actually at risk of this thing. Other people who 307 00:18:39,080 --> 00:18:43,440 Speaker 2: you know, the most common people, homosexual population, intravenous drug users, 308 00:18:43,440 --> 00:18:47,280 Speaker 2: et cetera. So will only vaccinate people who are obviously 309 00:18:47,280 --> 00:18:52,440 Speaker 2: at risk and and that should take care of it. 310 00:18:53,400 --> 00:18:58,800 Speaker 2: The result was that it did reduce the incidence of 311 00:18:58,840 --> 00:19:03,400 Speaker 2: liver cancer, but only by about fifty percent, So somehow 312 00:19:03,440 --> 00:19:06,280 Speaker 2: fifty percent was slipping through where people where infants were 313 00:19:06,280 --> 00:19:08,880 Speaker 2: getting it anyway, even though there was no obvious risk. 314 00:19:09,400 --> 00:19:12,080 Speaker 2: And that's just the accidents of everyday life. You know, 315 00:19:14,520 --> 00:19:17,520 Speaker 2: you're in a hospital, you're bumping into people, you're running it. 316 00:19:17,560 --> 00:19:19,920 Speaker 2: You know, it's all manner of ways that you might 317 00:19:20,400 --> 00:19:25,160 Speaker 2: somehow end up contracting the virus. And in an infant 318 00:19:25,560 --> 00:19:29,840 Speaker 2: that's a problem because if it's not addressed early, they 319 00:19:29,840 --> 00:19:34,600 Speaker 2: can end up with this virus for life. And it 320 00:19:34,640 --> 00:19:37,639 Speaker 2: was identified when when the vaccine for this was first 321 00:19:37,920 --> 00:19:40,120 Speaker 2: started to become a thing in the early nineteen seventies. 322 00:19:40,760 --> 00:19:46,159 Speaker 2: This was called the first cancer vaccination because it was 323 00:19:46,200 --> 00:19:50,000 Speaker 2: the first and only one at that point where we 324 00:19:50,119 --> 00:19:54,560 Speaker 2: knew that eliminating that virus would actually reduce the incidence 325 00:19:54,560 --> 00:19:58,680 Speaker 2: of cancer. And it's because the way that virus interacts 326 00:19:59,359 --> 00:20:02,760 Speaker 2: with protein in the liver, is that it produces mutations 327 00:20:02,800 --> 00:20:06,560 Speaker 2: which make the liver cells more prone to cancerous mutation. 328 00:20:07,440 --> 00:20:14,720 Speaker 1: Yeah, and so is RFK driving this or somebody else? 329 00:20:15,240 --> 00:20:22,480 Speaker 2: Yeah, So remember he thinks he thinks neurofin causes panadol. 330 00:20:22,520 --> 00:20:24,879 Speaker 2: I can't remember. It was probably panadol. Yeah, it was 331 00:20:24,920 --> 00:20:31,359 Speaker 2: panadol that he thinks causes autism. And this is another 332 00:20:31,440 --> 00:20:35,280 Speaker 2: of the things that he thinks causes autism. So there 333 00:20:35,359 --> 00:20:38,800 Speaker 2: is absolutely no evidence of that whatsoever. But you might 334 00:20:38,840 --> 00:20:40,800 Speaker 2: be thinking, well, but hold on, this is a vaccine 335 00:20:40,840 --> 00:20:43,080 Speaker 2: that we're giving to infants. Is there a risk in 336 00:20:43,119 --> 00:20:46,200 Speaker 2: giving it to infants? What is the risk? And there 337 00:20:46,320 --> 00:20:49,320 Speaker 2: is one. There's a risk of an anaphylactic reaction, which 338 00:20:49,320 --> 00:20:51,560 Speaker 2: is about one in one point one million, which so 339 00:20:51,800 --> 00:20:55,800 Speaker 2: is infinitesimally small, you know, off the scale small, but 340 00:20:56,600 --> 00:20:58,840 Speaker 2: on the upside. I don't know if you know anyone 341 00:20:58,880 --> 00:21:01,320 Speaker 2: who's ever had an anaphlectic reaction to something, but you know, 342 00:21:01,359 --> 00:21:03,719 Speaker 2: people have it to seafood, to peanuts and things like that. 343 00:21:03,720 --> 00:21:07,240 Speaker 2: It can be extremely life threatening. Their their lips swell 344 00:21:07,320 --> 00:21:12,880 Speaker 2: up that they can't breathe. It's very life threatening. So 345 00:21:12,920 --> 00:21:15,800 Speaker 2: it's not to be sneezed at, but it is one 346 00:21:15,840 --> 00:21:18,320 Speaker 2: in one point one million. On the upside, this thing 347 00:21:18,359 --> 00:21:21,640 Speaker 2: has been given to the child in a hospital, so 348 00:21:21,920 --> 00:21:24,639 Speaker 2: that's the best place to have an anaphylactic reaction. Hit 349 00:21:24,720 --> 00:21:29,960 Speaker 2: him with adrenaline, the quicker immediately sorted out. So there 350 00:21:30,000 --> 00:21:32,119 Speaker 2: is a risk, but it is very very small. 351 00:21:34,000 --> 00:21:36,879 Speaker 1: It seems astounding by the way tiff use to have 352 00:21:36,880 --> 00:21:41,600 Speaker 1: an anaphylactic reaction to men, but she's subsequently she's been 353 00:21:42,000 --> 00:21:47,159 Speaker 1: has been treated and adrenaline. Well, no, she was. She 354 00:21:47,240 --> 00:21:51,560 Speaker 1: had the Scotty Douglas vaccination and look it's things are going. 355 00:21:51,880 --> 00:21:54,919 Speaker 1: I mean, I'm no doctor, but fucking hell, she seems 356 00:21:54,960 --> 00:21:59,720 Speaker 1: to be healed anyway. Praise the Lord. 357 00:21:59,760 --> 00:22:02,399 Speaker 2: That's that new methodology, isn't it? Where they haven't they 358 00:22:02,440 --> 00:22:04,200 Speaker 2: had I haven't had a look at the numbers recently, 359 00:22:04,200 --> 00:22:09,880 Speaker 2: but where they expose children with to peanuts very very early, Yeah, 360 00:22:09,920 --> 00:22:12,320 Speaker 2: and frequently, so that you know there's a giving kids 361 00:22:12,320 --> 00:22:15,560 Speaker 2: peanut paste for example, so that you know they don't 362 00:22:15,600 --> 00:22:19,560 Speaker 2: develop a peanut anaphylaxis. It seems to be very very effective. 363 00:22:19,600 --> 00:22:20,639 Speaker 2: Is that what's going on here? 364 00:22:21,520 --> 00:22:24,280 Speaker 1: Exactly? So it started as with a minor interaction on 365 00:22:24,320 --> 00:22:27,800 Speaker 1: a podcast to graduated to bigger interactions on the podcast 366 00:22:27,800 --> 00:22:32,640 Speaker 1: than a brief human face to face interaction, no touching, 367 00:22:33,280 --> 00:22:35,680 Speaker 1: and apparently, I mean I haven't read the latest reports, 368 00:22:35,680 --> 00:22:38,600 Speaker 1: but it seems to have progressed somewhat, so I can't 369 00:22:38,640 --> 00:22:41,960 Speaker 1: update you on where we're at, you know, But like 370 00:22:42,080 --> 00:22:46,120 Speaker 1: the the feedback coming out of the lab is thumbs up. 371 00:22:46,320 --> 00:22:54,919 Speaker 1: So if congratulations on your progress's. 372 00:22:52,280 --> 00:22:57,919 Speaker 2: No longer carrying your fipin, that's. 373 00:22:57,800 --> 00:23:01,439 Speaker 1: Great, look at you, then fucking hilarious. Stop it. I 374 00:23:01,480 --> 00:23:03,600 Speaker 1: have to go and find myself myself a needle and 375 00:23:03,640 --> 00:23:07,639 Speaker 1: thread to sew up my size. So here's what I 376 00:23:07,640 --> 00:23:11,840 Speaker 1: don't get about, and back to the show. You're welcome, 377 00:23:12,240 --> 00:23:16,639 Speaker 1: You welcome listeners like it. There's so much data that 378 00:23:16,720 --> 00:23:20,240 Speaker 1: says this is so effective as a treatment or as 379 00:23:20,280 --> 00:23:28,520 Speaker 1: a preventative treatment, as a vaccination, then what's the rationale? Like, 380 00:23:28,960 --> 00:23:32,679 Speaker 1: surely even the dude who's the head of whatever is 381 00:23:32,720 --> 00:23:35,959 Speaker 1: the head of surely he's got to come up with 382 00:23:36,160 --> 00:23:42,240 Speaker 1: unequivocal evidence to make such a hugely impactful decision that's 383 00:23:42,240 --> 00:23:45,639 Speaker 1: going to affect every newborn child in a country of 384 00:23:45,680 --> 00:23:47,119 Speaker 1: three hundred and thirty million people. 385 00:23:47,840 --> 00:23:52,560 Speaker 2: You'd think wouldn't you you think, I mean, but no 386 00:23:52,640 --> 00:23:56,800 Speaker 2: sign of it so far. So a couple of the 387 00:23:56,880 --> 00:24:01,520 Speaker 2: US states, like the West Coast California and Washington and 388 00:24:01,560 --> 00:24:05,960 Speaker 2: maybe Oregon as well, have commed together and formed what 389 00:24:06,000 --> 00:24:10,919 Speaker 2: they're calling a health Alliance where they're maintaining the requirement 390 00:24:11,160 --> 00:24:17,520 Speaker 2: for infant vaccination, so ignoring the federal advice because they 391 00:24:17,760 --> 00:24:20,640 Speaker 2: feel that the evidence is so unequivocal and is so 392 00:24:20,800 --> 00:24:24,520 Speaker 2: dangerous to the unborn population that they are not prepared 393 00:24:24,520 --> 00:24:28,000 Speaker 2: to follow it. By the way, in the UK they 394 00:24:28,080 --> 00:24:32,560 Speaker 2: switched in twenty seventeen to doing what Australia is doing 395 00:24:33,040 --> 00:24:36,480 Speaker 2: and what the US is doing, and the results have 396 00:24:36,560 --> 00:24:41,480 Speaker 2: been just as impressive, the dramatic reductions in the incidents 397 00:24:41,960 --> 00:24:47,040 Speaker 2: of liver cancer. So it is there just isn't any evidence. 398 00:24:47,560 --> 00:24:50,520 Speaker 2: You might expect that there might be something that he 399 00:24:50,560 --> 00:24:53,840 Speaker 2: could point to that says that this is a problem, 400 00:24:54,560 --> 00:24:57,440 Speaker 2: but he doesn't seem to worry too much about evidence. 401 00:24:57,520 --> 00:25:01,119 Speaker 2: It's just, you know, it's the vibe, huh. 402 00:25:02,280 --> 00:25:06,000 Speaker 1: It's well, he's uncovered the conspiracy and he's brought it 403 00:25:06,040 --> 00:25:08,520 Speaker 1: out of the darkness into the light, and brothers and 404 00:25:08,560 --> 00:25:13,640 Speaker 1: sisters were just mm which don't worry about. Don't worry 405 00:25:13,640 --> 00:25:17,760 Speaker 1: about all the data everyone. It just seems anyway. It 406 00:25:17,840 --> 00:25:22,560 Speaker 1: reminds me of the fluoride conversation. I think he's an 407 00:25:22,600 --> 00:25:27,040 Speaker 1: opponent to fluoride in water as well. From memory, that 408 00:25:27,119 --> 00:25:27,800 Speaker 1: may be true. 409 00:25:27,920 --> 00:25:29,399 Speaker 2: I'm kind of with him on that, which is a 410 00:25:29,400 --> 00:25:32,480 Speaker 2: bit of a sad thing most of it. I don't 411 00:25:32,520 --> 00:25:37,560 Speaker 2: think we should be having mass medication in food supply. 412 00:25:39,600 --> 00:25:41,520 Speaker 2: What are we trying to fix with fluoride? What we're 413 00:25:41,520 --> 00:25:45,399 Speaker 2: trying to fix fixed? There is cavities in children's teeth, 414 00:25:46,000 --> 00:25:48,520 Speaker 2: and we know what causes the cavities. There's only one 415 00:25:48,520 --> 00:25:51,240 Speaker 2: thing that causes it, and that's a little molecule called fructose, 416 00:25:51,280 --> 00:25:53,440 Speaker 2: and we find that added to most of the food 417 00:25:53,480 --> 00:25:56,760 Speaker 2: on the supermarket shells. It's one half of sucros or 418 00:25:56,760 --> 00:26:00,399 Speaker 2: table sugar. It's also one half of high fructose corn syrup, 419 00:26:00,440 --> 00:26:02,600 Speaker 2: which is the shoe where they're use in the United States, 420 00:26:02,840 --> 00:26:05,000 Speaker 2: and it's what causes cavities and teeth. When you look 421 00:26:05,000 --> 00:26:07,920 Speaker 2: at populations that don't have access to it, they don't 422 00:26:07,960 --> 00:26:12,919 Speaker 2: have cavities so easy. The solution is stop doing that, 423 00:26:14,560 --> 00:26:17,440 Speaker 2: and instead what we're doing is applying a band aid 424 00:26:17,440 --> 00:26:19,680 Speaker 2: where We're going to put a substance in the water 425 00:26:19,720 --> 00:26:24,600 Speaker 2: supply of everybody in the hope that we can somehow 426 00:26:24,680 --> 00:26:27,160 Speaker 2: patch up some of the damage that's being done now. 427 00:26:27,160 --> 00:26:29,960 Speaker 2: It does work. It does reduce the incidence of cavities 428 00:26:30,000 --> 00:26:32,400 Speaker 2: by about one per child, so it drops it from 429 00:26:32,400 --> 00:26:34,520 Speaker 2: about four and a half to about three and a half. 430 00:26:35,720 --> 00:26:40,280 Speaker 2: But it's to do that, you're dosing everybody with something 431 00:26:40,440 --> 00:26:43,119 Speaker 2: where we're not entirely certain about the outcomes, and we 432 00:26:43,200 --> 00:26:45,720 Speaker 2: have no real way of knowing how much of this 433 00:26:45,760 --> 00:26:49,080 Speaker 2: stuff people are ingesting. We do know flo ride works 434 00:26:49,080 --> 00:26:51,359 Speaker 2: when you apply it topically, so put it in a 435 00:26:51,400 --> 00:26:53,480 Speaker 2: toothpaste and scrub it on your teeth and then rinse 436 00:26:53,480 --> 00:26:56,000 Speaker 2: your mouth out and spit it out. We're not so 437 00:26:56,040 --> 00:26:58,679 Speaker 2: certain about what it does to your skeleton when you 438 00:26:58,880 --> 00:27:04,240 Speaker 2: ingest it. So I think that's a risky approach to 439 00:27:04,280 --> 00:27:07,359 Speaker 2: public health. And I sort of wrote a tongue in 440 00:27:07,440 --> 00:27:10,200 Speaker 2: cheek thing a few weeks ago. 441 00:27:10,400 --> 00:27:12,760 Speaker 1: I was going to bring that up. Zemp in the water. 442 00:27:13,040 --> 00:27:16,199 Speaker 2: Yeah, yeah, but why not if that's a viable solution. 443 00:27:16,240 --> 00:27:20,360 Speaker 2: Why I put a zempic in the water supply. It's 444 00:27:20,480 --> 00:27:23,040 Speaker 2: taking the same approach to public health, and I don't 445 00:27:23,080 --> 00:27:25,880 Speaker 2: think that's a good way to do it, but it is. 446 00:27:25,960 --> 00:27:28,720 Speaker 2: I can see why your mine might leap there from 447 00:27:28,800 --> 00:27:31,240 Speaker 2: vaccination programs like the one we're talking about, but I 448 00:27:31,240 --> 00:27:36,760 Speaker 2: don't think they're the same in any degree. What we're 449 00:27:36,800 --> 00:27:40,159 Speaker 2: talking about with that is a very specific population who 450 00:27:40,359 --> 00:27:43,520 Speaker 2: require a very specific treatment, not something put in their 451 00:27:43,560 --> 00:27:46,520 Speaker 2: food supply, something where someone is actually going up to 452 00:27:46,560 --> 00:27:49,840 Speaker 2: them and putting a needle into them to prevent a 453 00:27:50,000 --> 00:27:56,400 Speaker 2: well known and easily connected disease state which is ultimately fatal. 454 00:27:59,119 --> 00:28:02,640 Speaker 2: If what we were talking about here was a hep 455 00:28:02,720 --> 00:28:05,200 Speaker 2: B vaccine being dumped into the water supply, then I'd 456 00:28:05,240 --> 00:28:09,520 Speaker 2: probably have similar concerns about Yeah, do you. 457 00:28:09,440 --> 00:28:11,800 Speaker 1: Know off the top of your head, just back to 458 00:28:11,880 --> 00:28:16,720 Speaker 1: the the correlation between the vaccination and cancer for the minute. 459 00:28:16,840 --> 00:28:20,879 Speaker 1: So the kids who say don't get the vaccination and 460 00:28:20,960 --> 00:28:25,880 Speaker 1: get hip B as infants, Are there any numbers on 461 00:28:26,760 --> 00:28:32,360 Speaker 1: there the correlation between that and the incidents of liver 462 00:28:32,440 --> 00:28:33,440 Speaker 1: cancer down the track? 463 00:28:33,800 --> 00:28:36,840 Speaker 2: Oh? Look, these will be off the top of my head, 464 00:28:36,840 --> 00:28:39,680 Speaker 2: but I think it's like five percent developed zerosis and 465 00:28:39,720 --> 00:28:43,160 Speaker 2: then of those five percent, five percent develop developed liver cancer. 466 00:28:43,640 --> 00:28:47,160 Speaker 1: Right, I mean that's still that's still a fair few 467 00:28:47,240 --> 00:28:49,680 Speaker 1: that don't need significant It is signifant. 468 00:28:49,720 --> 00:28:54,400 Speaker 2: It's not. This is not something that's remote in any sense. 469 00:28:55,000 --> 00:28:58,520 Speaker 2: This is something that that is a very real risk. 470 00:28:59,720 --> 00:29:06,600 Speaker 1: Yeah, yeah, it's yeah. It's the fact that things get 471 00:29:07,040 --> 00:29:11,720 Speaker 1: put into i don't know, put into law or get 472 00:29:11,760 --> 00:29:15,320 Speaker 1: mandated that really from a scientific point of view, don't 473 00:29:15,400 --> 00:29:20,280 Speaker 1: make make any sense. As somewhat terrifying, is it. You 474 00:29:20,360 --> 00:29:23,720 Speaker 1: said that some states were pushing back. So it's not 475 00:29:24,880 --> 00:29:28,120 Speaker 1: it's not illegal to vaccinate kids. It's not. It's just 476 00:29:28,520 --> 00:29:31,480 Speaker 1: it's just a recommendation or it's going to be a 477 00:29:31,520 --> 00:29:33,520 Speaker 1: recommendation to not do it. Is that correct. 478 00:29:33,520 --> 00:29:36,360 Speaker 2: It's going to be up to the parents to decide 479 00:29:36,400 --> 00:29:38,640 Speaker 2: whether to do it. So you go from a situation 480 00:29:38,720 --> 00:29:40,840 Speaker 2: where a doctor is saying you should do this, this 481 00:29:40,920 --> 00:29:43,720 Speaker 2: is on the vaccination schedule and this is why you 482 00:29:43,760 --> 00:29:47,360 Speaker 2: should do this, to ah, sort yourself out, make up 483 00:29:47,360 --> 00:29:53,000 Speaker 2: your own mind. Yeah, yeah, yeah, I wonder And that's 484 00:29:53,040 --> 00:29:55,840 Speaker 2: a difficult that's a difficult place to be. It's like, 485 00:29:55,960 --> 00:29:58,720 Speaker 2: for example, with this this whole under sixteenth thing in 486 00:29:58,840 --> 00:30:02,000 Speaker 2: social media, people often say to me, oh, you know, 487 00:30:02,040 --> 00:30:03,920 Speaker 2: that's not going to work. Kids these days, they can 488 00:30:03,960 --> 00:30:09,080 Speaker 2: circumvent that stuff, and yeah, they can. But the difference 489 00:30:09,240 --> 00:30:13,160 Speaker 2: is that when it's the law, it's the law. And 490 00:30:13,200 --> 00:30:15,720 Speaker 2: that means that a parent can sit down at a 491 00:30:15,800 --> 00:30:18,400 Speaker 2: kitchen table with a kid and say I'm not letting 492 00:30:18,440 --> 00:30:21,120 Speaker 2: you do this because it's against the law. Now, not 493 00:30:21,160 --> 00:30:24,720 Speaker 2: every parent will do that, but it gives many parents 494 00:30:24,840 --> 00:30:29,200 Speaker 2: the backbone they require to say something that desperately needs 495 00:30:29,240 --> 00:30:32,440 Speaker 2: to be said. And it's in a similar situation here. 496 00:30:32,720 --> 00:30:34,640 Speaker 2: If you go from a position where a doctor says 497 00:30:34,640 --> 00:30:38,120 Speaker 2: you really really should be doing this to not what 498 00:30:38,200 --> 00:30:41,560 Speaker 2: evs do whatever you want to do, it's a very 499 00:30:41,560 --> 00:30:42,400 Speaker 2: different situation. 500 00:30:43,360 --> 00:30:46,160 Speaker 1: Yeah, all right. My last question is a little bit 501 00:30:46,200 --> 00:30:49,600 Speaker 1: clunky and very a huge departure from what we've been 502 00:30:49,640 --> 00:30:53,880 Speaker 1: talking about. But and I don't really want to know 503 00:30:54,240 --> 00:30:56,360 Speaker 1: your thoughts. It will make sense when I ask it. 504 00:30:56,440 --> 00:31:01,480 Speaker 1: But as you're a lawyer work in the legal system, 505 00:31:01,880 --> 00:31:06,240 Speaker 1: would you ever write anything about what we saw or 506 00:31:06,280 --> 00:31:09,880 Speaker 1: what transpired at Bondai on Sunday. I don't want to 507 00:31:09,880 --> 00:31:12,920 Speaker 1: start a new conversation now, but how do you know? 508 00:31:13,040 --> 00:31:19,200 Speaker 1: Obviously that's a very volatile, very emotional, very multi factorial 509 00:31:19,440 --> 00:31:23,200 Speaker 1: kind of conversation, and I just like, even for me, 510 00:31:24,320 --> 00:31:26,640 Speaker 1: I wrote I wrote something that was just going to 511 00:31:26,640 --> 00:31:28,600 Speaker 1: be a post and I'm like, well, nobody needs to 512 00:31:28,640 --> 00:31:33,720 Speaker 1: hear what I think. And it had ended up being 513 00:31:33,800 --> 00:31:36,400 Speaker 1: quite a long piece and I'm like, it's too big 514 00:31:36,440 --> 00:31:38,280 Speaker 1: to put on social media, and then I went, I'm 515 00:31:38,360 --> 00:31:41,560 Speaker 1: just going to post it as a podcast. And I 516 00:31:41,600 --> 00:31:43,680 Speaker 1: said at the start, look, this is me just thinking 517 00:31:43,680 --> 00:31:47,360 Speaker 1: out loud about because I want to understand the drivers 518 00:31:47,440 --> 00:31:50,480 Speaker 1: and the mechanisms and the motivations and the reasons underneath 519 00:31:50,520 --> 00:31:53,520 Speaker 1: it all. But even then I was quite wary. So 520 00:31:53,640 --> 00:31:57,080 Speaker 1: my long winded question is, would you write anything about it? 521 00:31:58,320 --> 00:32:03,760 Speaker 2: Oh? If I wore it wouldn't be now because it 522 00:32:03,880 --> 00:32:04,800 Speaker 2: is just too raw. 523 00:32:06,200 --> 00:32:06,520 Speaker 1: Yes. 524 00:32:08,040 --> 00:32:13,400 Speaker 2: But in general, standing back from the current circumstance, something 525 00:32:13,400 --> 00:32:17,160 Speaker 2: that has always fascinated me is the transition of the 526 00:32:17,360 --> 00:32:25,280 Speaker 2: transmission of memes. How prone humans are to being infected 527 00:32:25,840 --> 00:32:33,200 Speaker 2: with ideas, and some of those ideas are very malevolent, 528 00:32:33,840 --> 00:32:38,440 Speaker 2: and some of them are kpop. But there's a similar 529 00:32:38,600 --> 00:32:45,040 Speaker 2: mechanism going on, and I find that fascinating about it. 530 00:32:45,360 --> 00:32:50,160 Speaker 2: What about the human mind is allowing that to happen, 531 00:32:50,720 --> 00:32:57,520 Speaker 2: What facilitates it? And how do we stop it? I 532 00:32:57,520 --> 00:33:02,280 Speaker 2: think once we know that we are more likely to 533 00:33:02,360 --> 00:33:06,360 Speaker 2: be able to vaccinate if you want against dangerous memes, 534 00:33:07,880 --> 00:33:09,800 Speaker 2: which we really need to be able to do. 535 00:33:10,840 --> 00:33:15,200 Speaker 1: Yeah. Yeah, yeah, Well when you write that, whenever that is, 536 00:33:15,440 --> 00:33:16,880 Speaker 1: I want to read it, I want to hear it. 537 00:33:17,200 --> 00:33:21,760 Speaker 1: I will say goodbye, fair but mate, appreciate you. Thank you, Tiff, 538 00:33:21,760 --> 00:33:24,840 Speaker 1: Congratulations on the medical breakthrough. Keep working on that and 539 00:33:25,280 --> 00:33:28,720 Speaker 1: keep us updated with the research. Scott knows he's just 540 00:33:28,760 --> 00:33:31,200 Speaker 1: an experiment, doesn't he. Have you filled him in? 541 00:33:31,880 --> 00:33:35,560 Speaker 2: Can't know how you can't tell this subject of the 542 00:33:35,640 --> 00:33:39,280 Speaker 2: experiment that it's an experiment. Hopefully he's not listening. 543 00:33:40,000 --> 00:33:47,320 Speaker 1: Yeah, hopefully thinks it's legit. Thanks Tiff, Thanks David, Thank you,