1 00:00:00,200 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,760 --> 00:00:09,080 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,160 --> 00:00:12,159 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,200 --> 00:00:19,760 Speaker 1: production of iHeartRadio. 5 00:00:25,840 --> 00:00:27,600 Speaker 2: Hello, welcome back to the show. 6 00:00:27,680 --> 00:00:29,360 Speaker 3: My name is Matt, my name is Noel. 7 00:00:30,000 --> 00:00:32,839 Speaker 4: They call me Ben. We're joined as always with our 8 00:00:32,960 --> 00:00:37,360 Speaker 4: super producer Dylan the Tennessee pal Fagan. Most importantly, you 9 00:00:37,640 --> 00:00:41,800 Speaker 4: argue you are here. That makes this the stuff they 10 00:00:41,920 --> 00:00:45,440 Speaker 4: don't want you to know. If you are joining us 11 00:00:45,680 --> 00:00:49,519 Speaker 4: for tonight's listener mail program, let us be the first 12 00:00:49,880 --> 00:00:54,880 Speaker 4: to welcome you to June twenty sixth. Guys, it's almost 13 00:00:54,920 --> 00:00:59,240 Speaker 4: the end of June, which means we are once again 14 00:00:59,440 --> 00:01:00,920 Speaker 4: in season. 15 00:01:01,000 --> 00:01:04,160 Speaker 3: Oh thank goodness, finally, Matt, I heard you got a 16 00:01:04,240 --> 00:01:06,360 Speaker 3: rude bega hanging out in your friends and you're gonna 17 00:01:06,640 --> 00:01:09,360 Speaker 3: dice up and delightfully roast. 18 00:01:09,400 --> 00:01:12,880 Speaker 2: Perhaps I do, indeed, but it needs me some more 19 00:01:12,959 --> 00:01:15,600 Speaker 2: route of begas. So let's see if we can find one. 20 00:01:15,640 --> 00:01:16,720 Speaker 3: Okay, sounds good. 21 00:01:17,360 --> 00:01:19,040 Speaker 4: Can you do some digging, Billy? 22 00:01:20,720 --> 00:01:26,959 Speaker 3: Oh, I'm sorry, we were looking for what is rudebega? 23 00:01:28,120 --> 00:01:30,679 Speaker 3: What is rude vega? Is the question? I believe, Ben, 24 00:01:30,720 --> 00:01:33,760 Speaker 3: you got some correspondence to shed some light on just 25 00:01:33,880 --> 00:01:34,720 Speaker 3: that very question. 26 00:01:35,440 --> 00:01:39,400 Speaker 4: All right, since it's just the five of us and 27 00:01:39,520 --> 00:01:44,759 Speaker 4: millions of other people, we will share the following correspondence 28 00:01:44,880 --> 00:01:49,400 Speaker 4: from our pal that I hope we can identify. His 29 00:01:49,680 --> 00:01:55,680 Speaker 4: title is chef. His name rhymes with ted. So this 30 00:01:56,000 --> 00:02:01,200 Speaker 4: fellow conspiracy realist says, spoilers, rude begas are not true turnips. 31 00:02:01,400 --> 00:02:05,120 Speaker 4: They're the unholy children of turnips and cabbages. 32 00:02:05,600 --> 00:02:07,040 Speaker 3: Okay, I'm holy indeed. 33 00:02:08,880 --> 00:02:14,280 Speaker 4: Well, we're obviously fans and Matt, thank you for doing 34 00:02:14,320 --> 00:02:19,760 Speaker 4: the research here on your case study of a rudabak. 35 00:02:19,960 --> 00:02:21,160 Speaker 4: How you planing to cook it. 36 00:02:23,040 --> 00:02:25,560 Speaker 2: Like any other root vegetable? Baby, put it in the 37 00:02:25,600 --> 00:02:27,240 Speaker 2: oven after being shopped in. 38 00:02:27,600 --> 00:02:29,720 Speaker 3: Get us some seasoning, yimmy. 39 00:02:29,800 --> 00:02:33,720 Speaker 4: I like that quiet storm voice, and we like your 40 00:02:33,840 --> 00:02:37,280 Speaker 4: voices as well. So we're going to take a quick 41 00:02:37,320 --> 00:02:40,800 Speaker 4: break for a word from our sponsors, and when we return, 42 00:02:40,919 --> 00:02:44,440 Speaker 4: we're going to explore synthetic estrogen. We're going to talk 43 00:02:44,480 --> 00:02:49,120 Speaker 4: about analog society versus a surveillance state. We're going to 44 00:02:49,200 --> 00:02:54,440 Speaker 4: study brain stuff for a second. But before we do 45 00:02:54,520 --> 00:02:56,840 Speaker 4: any of that, we're going to have a follow up 46 00:02:57,040 --> 00:03:02,000 Speaker 4: with our gas station episode stuff gas stations don't want 47 00:03:02,040 --> 00:03:06,239 Speaker 4: you to know. We asked you, fellow conspiracy realists, for 48 00:03:06,440 --> 00:03:10,280 Speaker 4: your first hand experiences, and gosh knows, we got some 49 00:03:10,440 --> 00:03:11,120 Speaker 4: great stuff. 50 00:03:16,480 --> 00:03:19,679 Speaker 3: And we've returned with a listener coming to us from 51 00:03:19,919 --> 00:03:25,320 Speaker 3: rural Bartow County, Georgia. Fellas, where's Bartow County in relation 52 00:03:25,400 --> 00:03:26,119 Speaker 3: to where we are? 53 00:03:27,040 --> 00:03:28,320 Speaker 4: Is this an official inquort? It? 54 00:03:29,320 --> 00:03:31,480 Speaker 3: I guess I could google it myself. I know I've 55 00:03:31,520 --> 00:03:35,360 Speaker 3: heard the name, but I don't. I'm really bad at geography. 56 00:03:35,480 --> 00:03:39,280 Speaker 3: It looks pretty Cartersville near Kansas, so really not that 57 00:03:39,360 --> 00:03:43,839 Speaker 3: far from us at all, about an hour drive from 58 00:03:43,840 --> 00:03:47,400 Speaker 3: where we currently sits. And if there's anything like where 59 00:03:47,400 --> 00:03:49,880 Speaker 3: we live, we talked about this openly on the episode. 60 00:03:50,520 --> 00:03:53,080 Speaker 3: There's gonna be some sketchy gas stations, and sure enough, 61 00:03:53,440 --> 00:03:58,560 Speaker 3: our listener and Ominous told us about just that very thing. Hi, guys, 62 00:03:58,640 --> 00:04:00,840 Speaker 3: been listening forever, and I've been looking forward to the 63 00:04:00,880 --> 00:04:03,320 Speaker 3: gas station episode since y'all first mentioned it. I live 64 00:04:03,320 --> 00:04:07,280 Speaker 3: in rural Bartow County, Georgia, and nearly every gas station 65 00:04:07,360 --> 00:04:10,160 Speaker 3: around that isn't a quick trip, which a big chain 66 00:04:10,320 --> 00:04:12,800 Speaker 3: around here or a racetrack, which I think is a 67 00:04:12,840 --> 00:04:18,360 Speaker 3: little more national has slot machines. Locally, everyone refers to 68 00:04:18,400 --> 00:04:21,960 Speaker 3: them as the ding Dings. Really love that, Gonna co 69 00:04:22,040 --> 00:04:24,640 Speaker 3: op that my own daily life the ding Dings. Part 70 00:04:24,640 --> 00:04:26,880 Speaker 3: of the reason that the sketchy gas stations often have 71 00:04:27,080 --> 00:04:31,880 Speaker 3: lots of random items is to use as prizes for playing. 72 00:04:32,160 --> 00:04:34,960 Speaker 3: According to the official store policy, you can only cash 73 00:04:35,040 --> 00:04:39,080 Speaker 3: out for store credit, and having those items around makes 74 00:04:39,120 --> 00:04:42,200 Speaker 3: it appear more legit. One place that used to be 75 00:04:42,279 --> 00:04:44,599 Speaker 3: near me had a whole side building they called the 76 00:04:44,640 --> 00:04:48,239 Speaker 3: Game Room, which I've mentioned seeing around me as well, 77 00:04:49,080 --> 00:04:52,040 Speaker 3: just slap full of ding Dings and a bunch of 78 00:04:52,080 --> 00:04:55,200 Speaker 3: prizes that you could win. The thing is you could 79 00:04:55,279 --> 00:04:58,440 Speaker 3: always get cash. I don't play often, but the handful 80 00:04:58,480 --> 00:05:00,839 Speaker 3: of times I've played in won I was able to 81 00:05:00,920 --> 00:05:04,160 Speaker 3: get cash, whether or not I was a regular or not. 82 00:05:04,839 --> 00:05:08,480 Speaker 3: There's no chance those machines would be so popular otherwise. 83 00:05:08,720 --> 00:05:11,200 Speaker 3: The sketchiest gas station I know of is also the 84 00:05:11,240 --> 00:05:13,719 Speaker 3: one closest to me. I'm in the middle of nowhere 85 00:05:13,760 --> 00:05:15,479 Speaker 3: and it's right at the end of my street. Over 86 00:05:15,520 --> 00:05:17,760 Speaker 3: the years, the amount of products in the store has 87 00:05:17,880 --> 00:05:22,839 Speaker 3: dwindled to next to nothing. They have gas, cigarettes, beer, soda, lottery, 88 00:05:22,920 --> 00:05:26,320 Speaker 3: and then shells with some random dusty items and candy. 89 00:05:26,640 --> 00:05:29,320 Speaker 3: The weird and sketchy part. They used to have four 90 00:05:29,560 --> 00:05:34,159 Speaker 3: older slot machines. They've recently upgraded to four huge, brand new, 91 00:05:34,240 --> 00:05:37,800 Speaker 3: fancy ones, while the rest of the store is absolutely depleted. 92 00:05:38,120 --> 00:05:41,080 Speaker 3: What's weirder about this is that hardly anyone plays them. 93 00:05:41,279 --> 00:05:43,600 Speaker 3: Every once in a while, I'll see a local tweaker 94 00:05:43,760 --> 00:05:47,400 Speaker 3: on a machine, but it's not laughing at addiction problems. 95 00:05:47,400 --> 00:05:50,760 Speaker 3: It's the term tweaker always. It makes me giggle, but 96 00:05:50,839 --> 00:05:54,160 Speaker 3: never enough to justify how much those suckers cost. The 97 00:05:54,160 --> 00:05:57,280 Speaker 3: only person I see regularly feeding money into it is 98 00:05:57,320 --> 00:06:01,719 Speaker 3: an employee, which makes me really wonder if my neighborhood 99 00:06:01,800 --> 00:06:05,240 Speaker 3: sketch station is actually a front for money laundering. 100 00:06:05,720 --> 00:06:08,760 Speaker 4: My money's running to the laundry like there's something smelly 101 00:06:08,800 --> 00:06:10,120 Speaker 4: on Yeah, for sure. 102 00:06:11,120 --> 00:06:14,400 Speaker 3: Anyway, you're more than welcome to use this on the podcast. 103 00:06:14,400 --> 00:06:16,360 Speaker 3: And you can just call me an ominous. That's my 104 00:06:16,480 --> 00:06:19,000 Speaker 3: old AOL username that I thought was so cool and 105 00:06:19,120 --> 00:06:21,360 Speaker 3: edgy when I was fourteen. Well, I think it's still 106 00:06:21,400 --> 00:06:24,799 Speaker 3: cool and edgy today an ominous and I dig the 107 00:06:24,880 --> 00:06:27,800 Speaker 3: reference to aim. It was a golden time for Internet 108 00:06:27,839 --> 00:06:31,960 Speaker 3: communication for us all boy boy, does this ever hit 109 00:06:32,040 --> 00:06:33,800 Speaker 3: home some of the stuff we talked about in that 110 00:06:33,839 --> 00:06:36,560 Speaker 3: episode in terms of I mean you kind of you know, 111 00:06:37,040 --> 00:06:40,640 Speaker 3: ran the gamut here in terms of loose adherence to 112 00:06:40,720 --> 00:06:44,279 Speaker 3: the law where these machines are concerned, the idea that 113 00:06:44,320 --> 00:06:47,760 Speaker 3: it's supposed to only pay with prizes and store credit, 114 00:06:48,279 --> 00:06:52,080 Speaker 3: but that it's more than easy enough to convert those 115 00:06:52,120 --> 00:06:56,080 Speaker 3: winnings to cold hard cash, and the idea of these 116 00:06:56,120 --> 00:07:01,040 Speaker 3: potentially being fronts for other types of illicit activity. Guys, 117 00:07:01,200 --> 00:07:04,760 Speaker 3: is there anything about an Ominous's email that hit home 118 00:07:04,800 --> 00:07:05,039 Speaker 3: for you? 119 00:07:06,360 --> 00:07:10,600 Speaker 4: First off? Misominous? If I may be formal here, thank 120 00:07:10,640 --> 00:07:16,600 Speaker 4: you so much for writing in and verifying something we 121 00:07:16,720 --> 00:07:20,440 Speaker 4: said earlier. One of the signals of a sketchy gas 122 00:07:20,440 --> 00:07:24,680 Speaker 4: station is indeed going to be dust upon some of 123 00:07:24,720 --> 00:07:28,200 Speaker 4: the products. You know, not to sound, not to sound 124 00:07:28,280 --> 00:07:33,280 Speaker 4: like one of those old jerks and basic with a 125 00:07:33,680 --> 00:07:37,680 Speaker 4: putting on the white gloves and walking around and testing dust. 126 00:07:37,720 --> 00:07:38,800 Speaker 4: Do you guys remember that. 127 00:07:38,720 --> 00:07:43,680 Speaker 3: Of course? Yeah, classic trope of the old drill sergeant. 128 00:07:43,920 --> 00:07:44,200 Speaker 5: Yeah. 129 00:07:44,200 --> 00:07:46,560 Speaker 4: But if you see that, right, if you see the 130 00:07:46,680 --> 00:07:51,280 Speaker 4: visible dust, it is a signal that there may be 131 00:07:52,840 --> 00:07:59,320 Speaker 4: something interesting afoot, and we cannot cast dispersion on the 132 00:07:59,440 --> 00:08:03,840 Speaker 4: choices of those owner operators. But mis ominous you have 133 00:08:04,560 --> 00:08:11,960 Speaker 4: you have provided multiple details that seem to indicate this 134 00:08:12,080 --> 00:08:14,920 Speaker 4: is worth looking into. Now, we're not gonna snitch on 135 00:08:14,960 --> 00:08:17,920 Speaker 4: this gas station, are we misominous? Are we norm we. 136 00:08:18,080 --> 00:08:21,160 Speaker 3: Think so, we don't have a snitches no call in 137 00:08:21,200 --> 00:08:23,480 Speaker 3: the gambling you know that way, We did talk about 138 00:08:23,480 --> 00:08:26,960 Speaker 3: there being a direct hotline to the GBI for just 139 00:08:27,040 --> 00:08:31,760 Speaker 3: such snitchery. But yeah, I mean, look, I've certainly it's 140 00:08:31,760 --> 00:08:36,200 Speaker 3: weird how many gas stations there are in certain rural areas, 141 00:08:36,880 --> 00:08:39,280 Speaker 3: in certain maybe like food desert y type areas like 142 00:08:39,320 --> 00:08:42,160 Speaker 3: I mentioned I live in. It just doesn't seem like 143 00:08:42,880 --> 00:08:46,800 Speaker 3: a small stretch like that could sustain that many of 144 00:08:46,840 --> 00:08:50,280 Speaker 3: the same exact business, oftentimes on the same exact side 145 00:08:50,280 --> 00:08:52,880 Speaker 3: of the street, et cetera. And then you do start 146 00:08:52,920 --> 00:08:56,319 Speaker 3: to see in that glut of these types of businesses, 147 00:08:56,800 --> 00:09:00,360 Speaker 3: some of them becoming more and more depleted, and yet 148 00:09:00,440 --> 00:09:02,680 Speaker 3: somehow still remaining. You know, No, I don't know that 149 00:09:02,720 --> 00:09:05,479 Speaker 3: I've ever seen a gas station go out of business. 150 00:09:06,120 --> 00:09:08,000 Speaker 3: It's just I don't know. It's interesting and then a 151 00:09:08,000 --> 00:09:11,480 Speaker 3: little bit odd, and I do tend to lean towards 152 00:09:11,520 --> 00:09:15,400 Speaker 3: nefarious activities from time to time. But this whole you know, 153 00:09:15,679 --> 00:09:19,640 Speaker 3: cash payout thing, it absolutely confirms what we had suspected. 154 00:09:20,559 --> 00:09:22,280 Speaker 2: Can I tell you, guys my favorite thing about and 155 00:09:23,200 --> 00:09:29,959 Speaker 2: ominous message. It's referring to these as ding dings. I 156 00:09:30,000 --> 00:09:32,239 Speaker 2: don't know if you guys have ever seen this glorious 157 00:09:32,280 --> 00:09:35,600 Speaker 2: show that you can find right now. I've seen it 158 00:09:35,600 --> 00:09:39,120 Speaker 2: because I'm father of a young son who loves the 159 00:09:39,160 --> 00:09:42,760 Speaker 2: show Big City Greens. It is a fantastic little animated 160 00:09:42,760 --> 00:09:47,120 Speaker 2: series with one of the main characters being Cricket Green and. 161 00:09:47,000 --> 00:09:49,600 Speaker 4: He does that Big City Greens plural. 162 00:09:49,559 --> 00:09:52,680 Speaker 2: Yes, and he goes around to the Greens as the family. 163 00:09:52,960 --> 00:09:55,600 Speaker 2: He goes around and he calls people ding ding all 164 00:09:55,640 --> 00:10:00,000 Speaker 2: the time, and he's my kids. 165 00:10:00,000 --> 00:10:01,440 Speaker 3: Sometimes I don't like ding ding. 166 00:10:02,160 --> 00:10:03,640 Speaker 4: That's up there with Bozone. 167 00:10:03,920 --> 00:10:06,720 Speaker 2: Yeah, but but it made me think of all these machines. 168 00:10:06,880 --> 00:10:09,480 Speaker 2: And there's even I found an article from what is 169 00:10:09,520 --> 00:10:14,000 Speaker 2: this ninety five point five WSB. We knew WSB the 170 00:10:14,120 --> 00:10:19,400 Speaker 2: radio radio channel, the radio station hereas station exactly, but 171 00:10:19,679 --> 00:10:23,080 Speaker 2: they refer to these as ding ding gambling machines as well, 172 00:10:23,120 --> 00:10:24,200 Speaker 2: which is very funny to me. 173 00:10:24,840 --> 00:10:28,240 Speaker 4: I like the rhyme, and we also want you to 174 00:10:28,320 --> 00:10:29,400 Speaker 4: know mis ominous. 175 00:10:29,800 --> 00:10:29,920 Speaker 3: Uh. 176 00:10:30,640 --> 00:10:35,200 Speaker 4: We will never call our fellow compatriots ding Ding's, but 177 00:10:35,280 --> 00:10:38,880 Speaker 4: we want you to know that you are not alone 178 00:10:39,440 --> 00:10:43,440 Speaker 4: in a lot of firsthand accounts we have received about 179 00:10:43,559 --> 00:10:48,360 Speaker 4: gas stations. And I got to ask you, guys after 180 00:10:48,440 --> 00:10:51,640 Speaker 4: we recorded the stuff gas stations don't want you to 181 00:10:51,720 --> 00:10:56,320 Speaker 4: know how how were your experiences when you visited a 182 00:10:56,400 --> 00:10:59,600 Speaker 4: gas station next? Did you, guys feel like more tuned 183 00:10:59,760 --> 00:11:05,720 Speaker 4: in to things? Did anybody else purposely visit out of 184 00:11:05,760 --> 00:11:06,600 Speaker 4: the way gas station? 185 00:11:06,800 --> 00:11:08,760 Speaker 3: No, I don't need to because there's a gazillion of 186 00:11:08,800 --> 00:11:11,520 Speaker 3: them in my neck of the woods, and I typically 187 00:11:11,520 --> 00:11:13,800 Speaker 3: go to the same two. Yeah, one of them definitely 188 00:11:13,800 --> 00:11:16,680 Speaker 3: has this big old gambling parlor, and of the two 189 00:11:17,160 --> 00:11:20,520 Speaker 3: is the least legit seeming one. 190 00:11:20,760 --> 00:11:22,440 Speaker 4: So did you ever play? No? 191 00:11:22,600 --> 00:11:24,440 Speaker 3: I never have, but you know what, maybe I will 192 00:11:25,040 --> 00:11:26,800 Speaker 3: and then see how it goes because I am kind 193 00:11:26,800 --> 00:11:28,520 Speaker 3: of a regular they know me there. So I bet 194 00:11:28,559 --> 00:11:30,880 Speaker 3: you if anyone was going to get a kind of special, 195 00:11:31,640 --> 00:11:33,800 Speaker 3: you know, secret treatment, right, it might. 196 00:11:33,679 --> 00:11:34,480 Speaker 4: Be mm hm. 197 00:11:34,760 --> 00:11:37,120 Speaker 3: Well, I'll tell you one thing that this discussion that 198 00:11:37,160 --> 00:11:38,880 Speaker 3: we had did prompt me to do was look a 199 00:11:38,880 --> 00:11:41,480 Speaker 3: little more into just gas station crime rate. Specifically here 200 00:11:41,480 --> 00:11:44,360 Speaker 3: in Atlanta and matt we were talking off here you 201 00:11:44,679 --> 00:11:49,319 Speaker 3: found a story specifically surrounding these gambling machines and specifically 202 00:11:49,559 --> 00:11:53,680 Speaker 3: in Bartow County where Sheriff's office officials are looking for 203 00:11:53,720 --> 00:11:56,840 Speaker 3: three people who were seen stealing from gambling machines. The 204 00:11:56,880 --> 00:11:59,320 Speaker 3: Bartow County Sheriff's Office is asking for the public's help 205 00:11:59,360 --> 00:12:03,679 Speaker 3: and identifying three people connected to stealing money from gambling machines. 206 00:12:03,760 --> 00:12:06,600 Speaker 3: So there's money in the gambling machines, deputy say. The 207 00:12:06,600 --> 00:12:08,880 Speaker 3: theft took place on November twenty that a Texaco gas 208 00:12:08,920 --> 00:12:12,200 Speaker 3: station on Cassville White Road in Cartersville. Two men and 209 00:12:12,240 --> 00:12:15,520 Speaker 3: one woman sat at the Ding Ding gambling machines. This 210 00:12:15,559 --> 00:12:18,360 Speaker 3: is news to me. The press is actually calling it 211 00:12:18,440 --> 00:12:21,319 Speaker 3: that too, And after all three individuals were done playing, 212 00:12:21,320 --> 00:12:23,839 Speaker 3: the cashier provided them with store credit. Upon them bringing 213 00:12:23,880 --> 00:12:27,280 Speaker 3: the credit voucher to redeem, police say. Store camera footage 214 00:12:27,280 --> 00:12:29,760 Speaker 3: showed two of the suspense conserting money into the machine 215 00:12:29,800 --> 00:12:32,240 Speaker 3: and hitting the collect button to get a voucher for 216 00:12:32,280 --> 00:12:36,160 Speaker 3: store credit. They then opened the machine with a duplicate key, 217 00:12:37,120 --> 00:12:40,880 Speaker 3: retracted the cash box, and took all the money and 218 00:12:40,960 --> 00:12:43,960 Speaker 3: of course in my mind immediately asked the question why 219 00:12:44,040 --> 00:12:47,240 Speaker 3: is there money inside these machines, to which I answered, 220 00:12:47,880 --> 00:12:50,320 Speaker 3: because people put the money into the machine to play, 221 00:12:50,520 --> 00:12:52,120 Speaker 3: and the money is stored in there, and that's how 222 00:12:52,160 --> 00:12:55,199 Speaker 3: they take their profit. It's not dispensing money like a 223 00:12:55,240 --> 00:12:59,760 Speaker 3: gambling machine, and Vegas might with actual coins that flood 224 00:12:59,800 --> 00:13:03,439 Speaker 3: out of the old style gambling machines. And employee check 225 00:13:03,480 --> 00:13:06,079 Speaker 3: the machines the next day and discovered approximately two thousand, 226 00:13:06,200 --> 00:13:08,960 Speaker 3: six hundred and sixty four dollars missing between three of 227 00:13:09,000 --> 00:13:12,960 Speaker 3: the machines. That's a decent haul for these machines at 228 00:13:12,960 --> 00:13:15,480 Speaker 3: a rural gas station. So I just think that's another 229 00:13:16,880 --> 00:13:19,920 Speaker 3: point towards the profitability of these things and also the 230 00:13:19,960 --> 00:13:23,520 Speaker 3: potential for crime surrounding them. Oh and really quickly though, 231 00:13:24,000 --> 00:13:27,120 Speaker 3: while we're at it, Ben, you found a voicemail that 232 00:13:27,440 --> 00:13:30,080 Speaker 3: referenced this very thing, and I thought it might be 233 00:13:30,080 --> 00:13:32,120 Speaker 3: a good way to take us out of this segment. 234 00:13:32,800 --> 00:13:37,920 Speaker 4: Yeah, mis ominous and fellow conspiracy realist, we're working live. 235 00:13:38,080 --> 00:13:41,160 Speaker 4: Not all of us have heard this. We got a 236 00:13:41,520 --> 00:13:48,559 Speaker 4: message from a trucker regarding gas stations and reacting specifically 237 00:13:48,800 --> 00:13:52,360 Speaker 4: to the issues of trafficking and we think this is 238 00:13:52,520 --> 00:13:55,560 Speaker 4: very important, so we're just going to play this message. 239 00:13:56,200 --> 00:14:01,520 Speaker 4: Hopefully this will reach people who may need assistance. So 240 00:14:01,720 --> 00:14:03,800 Speaker 4: here we are with Sasquatch. 241 00:14:05,440 --> 00:14:09,880 Speaker 5: Hey, guys, you can call me Sasquatch. Is stunt double 242 00:14:09,960 --> 00:14:13,439 Speaker 5: calling in again. I just listened to your podcast about 243 00:14:14,120 --> 00:14:18,280 Speaker 5: gas stations and truck stops and been a trucker for 244 00:14:19,800 --> 00:14:23,960 Speaker 5: almost two decades now and I have seen some crazy things. 245 00:14:24,000 --> 00:14:25,960 Speaker 5: But one of the things you guys mentioned about was 246 00:14:26,120 --> 00:14:30,480 Speaker 5: the human trafficking at truck stops and gas stations, and 247 00:14:30,560 --> 00:14:33,240 Speaker 5: I have to say that has been greatly reduced. You 248 00:14:33,240 --> 00:14:37,160 Speaker 5: don't see it as often. It's still out there, happens occasionally. 249 00:14:37,880 --> 00:14:42,760 Speaker 5: But there is a group called Truckers Against Trafficking and 250 00:14:42,800 --> 00:14:46,000 Speaker 5: it was started by a mother and her four daughters 251 00:14:46,040 --> 00:14:49,360 Speaker 5: and one of their friends, and they have done a 252 00:14:49,360 --> 00:14:55,320 Speaker 5: campaign across the US to educate truck drivers, truck stops 253 00:14:55,400 --> 00:15:01,680 Speaker 5: and fuel stops about human trafficking, what to look for, 254 00:15:03,360 --> 00:15:07,120 Speaker 5: the issues that come along with and the damage it 255 00:15:07,200 --> 00:15:13,160 Speaker 5: does it does to people. They are a fantastic organization. 256 00:15:13,320 --> 00:15:17,760 Speaker 5: It's definitely something people should know about. And I really 257 00:15:17,800 --> 00:15:20,680 Speaker 5: believe that the reason why so many truck stops are 258 00:15:20,800 --> 00:15:24,320 Speaker 5: safe havens for people in trafficking situations is because of 259 00:15:24,360 --> 00:15:29,280 Speaker 5: that organization. And the fact that you don't see it 260 00:15:29,320 --> 00:15:33,520 Speaker 5: as much happening in the world is because of that organization. 261 00:15:34,200 --> 00:15:37,760 Speaker 4: And we'll pause it there. We just I think collectively 262 00:15:37,800 --> 00:15:41,840 Speaker 4: agree this is an important message to send out to 263 00:15:41,960 --> 00:15:42,400 Speaker 4: the world. 264 00:15:42,680 --> 00:15:46,880 Speaker 3: Yeah, I mean, truckers are certainly a frontline position in 265 00:15:46,920 --> 00:15:49,480 Speaker 3: this fight, and the fact that they can kind of 266 00:15:49,480 --> 00:15:52,840 Speaker 3: band together to help identify some of these issues is 267 00:15:53,480 --> 00:15:55,040 Speaker 3: a powerful thing, you know. 268 00:15:56,080 --> 00:16:01,120 Speaker 4: Now, No, Sasquatch stunt Double also has an awesome man, Matt. 269 00:16:01,200 --> 00:16:04,440 Speaker 4: You may have spoken with him directly in the past. 270 00:16:05,680 --> 00:16:10,160 Speaker 4: There's another part of this message that we may play 271 00:16:10,160 --> 00:16:14,160 Speaker 4: in the future. Objecting to the term lot lizards, which 272 00:16:14,200 --> 00:16:17,000 Speaker 4: we all I think collectively. 273 00:16:16,840 --> 00:16:19,400 Speaker 3: Absolutely we mentioned that when we brought it up. It 274 00:16:19,480 --> 00:16:22,520 Speaker 3: is just kind of like a parlance of the time. 275 00:16:22,720 --> 00:16:25,800 Speaker 2: I guess let's just say, yeah, we heard from Sasquatch's 276 00:16:25,800 --> 00:16:28,120 Speaker 2: stunt double back when we were talking about stolen meat. 277 00:16:28,280 --> 00:16:31,720 Speaker 3: He had some cool insight about that. Well, with that, 278 00:16:31,800 --> 00:16:34,040 Speaker 3: let's take a quick break here a word from our sponsor, 279 00:16:34,080 --> 00:16:36,080 Speaker 3: and then come back with more messages from you. 280 00:16:42,520 --> 00:16:45,600 Speaker 2: And we've returned, guys, I have a really important update. 281 00:16:45,760 --> 00:16:50,560 Speaker 2: This is Final Fantasy MTG. I'm holding a pack. We're 282 00:16:50,600 --> 00:16:53,440 Speaker 2: not going to open it. We're just gonna state it exists. 283 00:16:53,520 --> 00:16:56,040 Speaker 2: It's real. I have a bunch of packs. Yeah, and 284 00:16:56,200 --> 00:16:59,120 Speaker 2: I got one of these little I can't remember how 285 00:16:59,160 --> 00:16:59,560 Speaker 2: to say this. 286 00:17:00,160 --> 00:17:04,600 Speaker 3: Cactore, cactar, cactus fella doing a little jump. 287 00:17:05,040 --> 00:17:06,520 Speaker 4: Is that a rare pool? No? 288 00:17:06,760 --> 00:17:08,879 Speaker 2: But but no, it's a I think it's a common 289 00:17:09,040 --> 00:17:09,720 Speaker 2: or maybe how. 290 00:17:09,560 --> 00:17:10,560 Speaker 4: Many backs did you get? 291 00:17:10,640 --> 00:17:13,720 Speaker 2: You got all like boosterbacks, right, everyone that was available 292 00:17:13,760 --> 00:17:17,000 Speaker 2: to me in my immediate vicinity. I purchased every single one. 293 00:17:17,200 --> 00:17:19,760 Speaker 2: I'm now in debt. I need your help. I've seen 294 00:17:19,880 --> 00:17:24,040 Speaker 2: the go fund me for Matt's MTG addiction issues. That's 295 00:17:24,080 --> 00:17:26,119 Speaker 2: not the most important thing, guys. The important thing is 296 00:17:26,119 --> 00:17:30,159 Speaker 2: we got a great message from Maximus. Maximus is bringing 297 00:17:30,240 --> 00:17:33,400 Speaker 2: up something that we talked about back in twenty eighteen 298 00:17:33,560 --> 00:17:38,480 Speaker 2: when we made our highly important episode are Frogs Really 299 00:17:38,600 --> 00:17:43,680 Speaker 2: Changing Gender? Also, hearkens back to our August fifteenth, twenty 300 00:17:43,720 --> 00:17:47,640 Speaker 2: twenty three, classic version of that episode. This is you guys, 301 00:17:47,640 --> 00:17:51,320 Speaker 2: remember that whole uh, that whole thing that Alex Jones 302 00:17:51,560 --> 00:17:55,040 Speaker 2: put all of the world through when when he said 303 00:17:55,240 --> 00:17:56,359 Speaker 2: that phrase. 304 00:17:58,160 --> 00:17:58,960 Speaker 3: Frog. 305 00:17:59,520 --> 00:18:03,119 Speaker 2: Yes, there you go. Well, and then you know, we 306 00:18:03,280 --> 00:18:05,480 Speaker 2: on this show looked it up and said, oh crap, 307 00:18:05,760 --> 00:18:08,400 Speaker 2: is there are some really weird things going on actually 308 00:18:08,560 --> 00:18:11,640 Speaker 2: with stuff ending up in the water and having effects 309 00:18:11,640 --> 00:18:16,720 Speaker 2: on amphibian populations. Well, Maximus has called in with a 310 00:18:16,720 --> 00:18:19,920 Speaker 2: whole other group of animals that are being affected by 311 00:18:19,920 --> 00:18:23,280 Speaker 2: the stuff we humans put into ourselves and then pee 312 00:18:23,320 --> 00:18:25,720 Speaker 2: into our toilets. So here we go. 313 00:18:26,359 --> 00:18:32,320 Speaker 6: This is Maximus. Please do an episode exploring the correlation 314 00:18:32,720 --> 00:18:37,159 Speaker 6: between worth control becoming widely available in the United States 315 00:18:37,160 --> 00:18:42,320 Speaker 6: of America and the declining population of fish as water 316 00:18:42,640 --> 00:18:47,320 Speaker 6: is recycled from wastewater systems to drinking water systems and 317 00:18:47,359 --> 00:18:52,080 Speaker 6: then recycled to freshwater systems and is a direct correlation 318 00:18:52,280 --> 00:18:56,440 Speaker 6: and the declining population of freshwater fish and North America 319 00:18:56,560 --> 00:18:58,760 Speaker 6: as always, thank you, keep doing you. 320 00:19:00,000 --> 00:19:03,560 Speaker 2: Oh okay, so that sounds a little weird, right, Like, oh, 321 00:19:03,600 --> 00:19:06,120 Speaker 2: come on now, there can't be a correlation between any 322 00:19:06,160 --> 00:19:08,800 Speaker 2: of that stuff. That doesn't make any sense birth control 323 00:19:08,920 --> 00:19:12,199 Speaker 2: and fish populations. That's human stuff and fish stuff, and 324 00:19:12,280 --> 00:19:16,680 Speaker 2: those two things don't come together at all. Well, you'd 325 00:19:16,680 --> 00:19:20,960 Speaker 2: be wrong, just as I was, just as silence when 326 00:19:21,040 --> 00:19:25,840 Speaker 2: I initially encountered Maximus's message there, because if you do 327 00:19:25,880 --> 00:19:28,840 Speaker 2: a quick little search on the internet machines, you're gonna 328 00:19:28,840 --> 00:19:33,440 Speaker 2: find several articles that are written in the news about 329 00:19:33,440 --> 00:19:38,160 Speaker 2: these things, and several scientific journals that are reporting this 330 00:19:38,440 --> 00:19:41,080 Speaker 2: very thing. First, we'll jump to a two thousand and 331 00:19:41,119 --> 00:19:45,200 Speaker 2: eight article within The Guardian written by James Anderson titled 332 00:19:45,480 --> 00:19:48,960 Speaker 2: birth control for Fish. And in this article you will 333 00:19:49,040 --> 00:19:52,240 Speaker 2: learn about the studies run by doctor Karen Kidd of 334 00:19:52,280 --> 00:19:57,040 Speaker 2: the University of New Brunswick in Canada and some very 335 00:19:57,640 --> 00:20:02,920 Speaker 2: upsetting results, very very setting results. She and her team 336 00:20:03,560 --> 00:20:06,879 Speaker 2: had a really cool idea. There's a group of lakes 337 00:20:07,359 --> 00:20:12,640 Speaker 2: out there in Canada, Ontario that's just north of Minnesota, 338 00:20:13,680 --> 00:20:21,720 Speaker 2: just east of Winnipeg called THEISD Experimental Lakes Area, and IISD, 339 00:20:21,880 --> 00:20:25,639 Speaker 2: by the way, stands for International Institute for Sustainable Development, 340 00:20:26,040 --> 00:20:29,520 Speaker 2: and this lakes area has a whole bunch of freshwater lakes. 341 00:20:29,920 --> 00:20:33,520 Speaker 2: What they did they went to over fifty fifty eight 342 00:20:34,080 --> 00:20:37,480 Speaker 2: research lakes and they checked out all of the populations 343 00:20:37,480 --> 00:20:41,360 Speaker 2: of freshwater fish within those lakes. They gathered as much 344 00:20:41,400 --> 00:20:44,119 Speaker 2: information as they possibly could. Then they went to another 345 00:20:44,200 --> 00:20:47,399 Speaker 2: lake and made sure that lake had an average population 346 00:20:47,440 --> 00:20:48,920 Speaker 2: of all the fish that was found in the other 347 00:20:48,960 --> 00:20:51,840 Speaker 2: fifty eight lakes. They basically made a perfect version of 348 00:20:51,880 --> 00:20:56,240 Speaker 2: an average lake within this area. Right then they started 349 00:20:56,280 --> 00:21:01,800 Speaker 2: adding teeny tiny amounts of a synthetic estrogen that's used 350 00:21:01,880 --> 00:21:05,880 Speaker 2: it's commonly used in birth control pills for humans, and 351 00:21:06,560 --> 00:21:10,879 Speaker 2: they found that populations of specific fish were altered so 352 00:21:11,119 --> 00:21:15,160 Speaker 2: much that the population was almost decimated within the lake, 353 00:21:15,320 --> 00:21:19,080 Speaker 2: almost none, because the males of the of that specific 354 00:21:19,119 --> 00:21:23,360 Speaker 2: fish started to lose their gonads. And they found that 355 00:21:23,480 --> 00:21:27,280 Speaker 2: the which is crazy to think about, and the males 356 00:21:27,320 --> 00:21:31,280 Speaker 2: were also unable to reproduce, Like you can imagine those 357 00:21:31,280 --> 00:21:34,960 Speaker 2: two things being correlated, but it's real stuff. Then she 358 00:21:35,040 --> 00:21:38,600 Speaker 2: went on to author more articles and do more science 359 00:21:38,760 --> 00:21:41,679 Speaker 2: checking out what happens when there's just teeny tiny trace 360 00:21:41,720 --> 00:21:46,840 Speaker 2: amounts of the synthetic estrogen within freshwater lakes and rivers, 361 00:21:47,240 --> 00:21:51,520 Speaker 2: and they found in other species, this tiny amount is 362 00:21:51,560 --> 00:21:54,520 Speaker 2: having a major effect on the ability of these fish 363 00:21:54,560 --> 00:21:58,479 Speaker 2: to breed. And guys, here is the major problem that 364 00:21:58,520 --> 00:21:59,520 Speaker 2: Maximus points out. 365 00:21:59,560 --> 00:21:59,800 Speaker 4: There. 366 00:22:01,119 --> 00:22:03,760 Speaker 2: Teeny tiny trace amounts of this stuff can have an effect. 367 00:22:04,040 --> 00:22:07,000 Speaker 2: And every time humans who are on birth control p 368 00:22:07,760 --> 00:22:11,320 Speaker 2: they release trace amounts of the synthetic estrogen into the 369 00:22:11,359 --> 00:22:15,760 Speaker 2: water systems. The wastewater plants are not able to process 370 00:22:15,760 --> 00:22:18,960 Speaker 2: pharmaceuticals We've talked about that before on this show, which 371 00:22:19,000 --> 00:22:21,719 Speaker 2: then get sent back into the freshwater systems, which then 372 00:22:21,760 --> 00:22:25,240 Speaker 2: have effects on the fish population, which can then have 373 00:22:25,320 --> 00:22:28,080 Speaker 2: an effect on the other species that are within that 374 00:22:28,200 --> 00:22:33,480 Speaker 2: ecosystem that prey upon these smaller fish. I didn't know 375 00:22:33,560 --> 00:22:35,800 Speaker 2: this was real, guys. I didn't think this was real. 376 00:22:35,960 --> 00:22:38,400 Speaker 2: I didn't think there could be this kind of effect, 377 00:22:38,920 --> 00:22:43,400 Speaker 2: especially from the waste that we produce after taking pharmaceuticals. 378 00:22:43,560 --> 00:22:46,199 Speaker 2: In my mind, it was always if pills end up 379 00:22:46,200 --> 00:22:48,240 Speaker 2: in the water system because they go down a drain 380 00:22:48,400 --> 00:22:52,679 Speaker 2: or something. But no, it is processed materials that have 381 00:22:52,800 --> 00:23:00,840 Speaker 2: the effect. Okay, yeah, uh, there's a lot more you 382 00:23:00,880 --> 00:23:03,040 Speaker 2: can go into here. By the way, one of the 383 00:23:03,040 --> 00:23:07,160 Speaker 2: people that co authored one of these studies titled Collapse 384 00:23:07,200 --> 00:23:10,720 Speaker 2: of a Fish population after Exposure to a synthetic estrogen 385 00:23:11,080 --> 00:23:13,440 Speaker 2: that was published in two thousand and seven. One of 386 00:23:13,440 --> 00:23:18,199 Speaker 2: the co authors is Robert Evans. H different, Robert, right, 387 00:23:18,840 --> 00:23:22,080 Speaker 2: I think so, Roberty Evans, I don't know it. I 388 00:23:22,119 --> 00:23:25,400 Speaker 2: don't need You can look up all of this stuff. 389 00:23:25,560 --> 00:23:29,840 Speaker 2: You can search for twenty fourteen article. New study finds 390 00:23:30,000 --> 00:23:34,200 Speaker 2: estrogen has detrimental and surprising effects on freshwater wildlife. That's 391 00:23:34,320 --> 00:23:37,719 Speaker 2: based on a whole other paper that was published titled 392 00:23:37,800 --> 00:23:40,960 Speaker 2: Direct and Indirect Responses of a Freshwater food Web to 393 00:23:41,080 --> 00:23:46,760 Speaker 2: a potent synthetic estrogen. It feels like a major problem 394 00:23:47,320 --> 00:23:51,399 Speaker 2: that we're not thinking about, not talking about, and I 395 00:23:51,400 --> 00:23:54,440 Speaker 2: don't know it just it feels like if that one 396 00:23:55,000 --> 00:23:59,399 Speaker 2: small synthetic thing hormone can have an effect on the 397 00:23:59,440 --> 00:24:03,000 Speaker 2: fish popular as well as we know specific herbicides and 398 00:24:03,040 --> 00:24:07,160 Speaker 2: pesticides can have an effect on amphibian populations. It does 399 00:24:07,240 --> 00:24:09,840 Speaker 2: make me wonder how much of the waste water runoff 400 00:24:09,840 --> 00:24:13,560 Speaker 2: from our treatment plants actually have effects on the wider 401 00:24:13,600 --> 00:24:17,160 Speaker 2: ecosystems that we're just we're kind of forgetting to even 402 00:24:17,160 --> 00:24:19,960 Speaker 2: look at. And that's it, all right, Well, we'll be 403 00:24:20,040 --> 00:24:23,520 Speaker 2: right back with more messages from you, froud. 404 00:24:30,359 --> 00:24:33,439 Speaker 4: We have returned. We've been going through a bit of 405 00:24:33,480 --> 00:24:39,880 Speaker 4: a pallanteer phase. We received an interesting thought experiment from 406 00:24:40,119 --> 00:24:46,880 Speaker 4: a from a fellow listener going by mister Delay. So 407 00:24:47,080 --> 00:24:52,000 Speaker 4: we're going to hear from mister delay, Lay lay lay delay, 408 00:24:52,080 --> 00:24:54,600 Speaker 4: getting just take it a second to load up. Let's 409 00:24:54,680 --> 00:24:55,200 Speaker 4: keep it in. 410 00:24:56,040 --> 00:24:59,399 Speaker 7: Hey, boys, you can call me mister Delay and feel 411 00:24:59,400 --> 00:25:03,000 Speaker 7: free to my message on the air. I just listened 412 00:25:03,080 --> 00:25:08,520 Speaker 7: to your episodes about train hoppers and your new strange 413 00:25:08,560 --> 00:25:14,800 Speaker 7: news thing about Talenteer and I had a thought. As 414 00:25:15,280 --> 00:25:20,440 Speaker 7: you know, companies like Talent here are increasingly putting Americans, 415 00:25:20,880 --> 00:25:23,800 Speaker 7: certain groups of Americans in their surveillance. And as the 416 00:25:23,840 --> 00:25:27,639 Speaker 7: economy gets mores and homeless movies is on the rise, 417 00:25:29,080 --> 00:25:31,640 Speaker 7: and many of the people that will suffer from both 418 00:25:31,720 --> 00:25:36,320 Speaker 7: things of these things will be younger, more tech stivy generations. 419 00:25:37,080 --> 00:25:42,320 Speaker 7: Might we see a resurgence in train hopping culture in 420 00:25:42,400 --> 00:25:45,439 Speaker 7: the next few years? Just as thought, I want to 421 00:25:45,440 --> 00:25:46,040 Speaker 7: share with y'all. 422 00:25:46,960 --> 00:25:50,879 Speaker 4: So the question then becomes, first off, thank you, mister Delay. 423 00:25:51,560 --> 00:25:57,960 Speaker 4: The question becomes is this a is the pendulum of 424 00:25:58,160 --> 00:26:03,240 Speaker 4: state surveillance going to swing so far that people, especially 425 00:26:03,280 --> 00:26:09,320 Speaker 4: in younger generations, start to unplug or become increasingly analogue. 426 00:26:09,600 --> 00:26:11,560 Speaker 3: I don't know, go off grid. I used to know 427 00:26:11,640 --> 00:26:14,080 Speaker 3: some trained kids back in my own town. They always 428 00:26:14,080 --> 00:26:16,159 Speaker 3: had a dog with a bandana with a name like 429 00:26:16,240 --> 00:26:17,159 Speaker 3: Rusty or something. 430 00:26:17,359 --> 00:26:17,520 Speaker 4: Good. 431 00:26:17,600 --> 00:26:19,879 Speaker 3: Cool folks. They're always in like punk bands, and I 432 00:26:19,920 --> 00:26:23,000 Speaker 3: actually knew a couple of folks who got big time 433 00:26:24,320 --> 00:26:28,680 Speaker 3: arrested like like sting style, like like they were helicopters involved. 434 00:26:28,680 --> 00:26:31,000 Speaker 3: It was a big deal pulling them off the train 435 00:26:31,119 --> 00:26:33,760 Speaker 3: and you know, throwing them in the paddy wagon. It 436 00:26:33,840 --> 00:26:37,560 Speaker 3: is considered, like stowing away is a pretty serious offense, 437 00:26:37,680 --> 00:26:39,280 Speaker 3: and they take it. It took it pretty seriously. But 438 00:26:39,320 --> 00:26:42,840 Speaker 3: I was really taken aback by how aggressive the authorities were. 439 00:26:43,320 --> 00:26:45,080 Speaker 4: Oh yeah, the railroad bulls. 440 00:26:45,280 --> 00:26:47,520 Speaker 3: But danger your question, I mean, I think it's certainly 441 00:26:47,920 --> 00:26:51,719 Speaker 3: that was their goal in those days. Was to be invisible, 442 00:26:51,840 --> 00:26:54,680 Speaker 3: was to be off grid, was to move in silence, 443 00:26:54,840 --> 00:26:57,640 Speaker 3: And it certainly seems like if you don't get caught 444 00:26:57,640 --> 00:26:59,480 Speaker 3: in that fashion, it is a good way of doing it. 445 00:27:00,560 --> 00:27:03,200 Speaker 4: Yeah, So what do you guys, What do you guys 446 00:27:03,240 --> 00:27:08,720 Speaker 4: think about what mister Delay is proposing here. Noel, you've 447 00:27:08,880 --> 00:27:12,320 Speaker 4: noticed that, or you've noted that, there is a real 448 00:27:12,480 --> 00:27:16,800 Speaker 4: contingent of what are sometimes called vagabonds or modern hoboes 449 00:27:17,520 --> 00:27:22,840 Speaker 4: in the United States today. Matt, interested in your experience 450 00:27:22,880 --> 00:27:26,200 Speaker 4: as well. I know that we have all, at various 451 00:27:26,240 --> 00:27:30,359 Speaker 4: times throughout our strange careers, considered going off the grid. 452 00:27:32,359 --> 00:27:36,240 Speaker 4: And Dylan was pointing out before we recorded the idea 453 00:27:36,320 --> 00:27:40,680 Speaker 4: that it is suspicious to not be on social media 454 00:27:40,720 --> 00:27:43,280 Speaker 4: at this point. So so what's your take, man, do 455 00:27:43,320 --> 00:27:46,600 Speaker 4: you do you think, like Noel and I do, that 456 00:27:46,880 --> 00:27:51,080 Speaker 4: more people might be tempted to live in an analog society. 457 00:27:52,520 --> 00:27:55,080 Speaker 2: Yeah, I don't know if I agree that they'll be 458 00:27:55,160 --> 00:27:57,280 Speaker 2: using the trains like that. I think it'll be more 459 00:27:57,320 --> 00:28:01,399 Speaker 2: isolated communities and you know, just house is further away 460 00:28:01,440 --> 00:28:03,280 Speaker 2: from each other. I think we're gonna start doing that. 461 00:28:03,280 --> 00:28:07,240 Speaker 2: That's what humanity seems to be poised to set down 462 00:28:07,280 --> 00:28:07,720 Speaker 2: that path. 463 00:28:08,400 --> 00:28:10,960 Speaker 3: Yeah, it's interesting how like you know, I mean it's 464 00:28:10,960 --> 00:28:15,800 Speaker 3: almost cliche to say, but like with the increasing connectivity 465 00:28:16,000 --> 00:28:18,800 Speaker 3: of the Internet and social media, it almost just you know, 466 00:28:18,920 --> 00:28:24,360 Speaker 3: serves to push people further apart in real life, and 467 00:28:24,560 --> 00:28:29,560 Speaker 3: like anything, you're gonna see a backlash and sort of 468 00:28:29,640 --> 00:28:32,560 Speaker 3: like a let's turn the clock back a little bit. 469 00:28:32,640 --> 00:28:36,040 Speaker 3: Like you know, with streaming services and things like that, 470 00:28:36,080 --> 00:28:39,000 Speaker 3: are like video streaming and also music of course, people 471 00:28:39,040 --> 00:28:42,960 Speaker 3: are now buying more Blu rays, people are buying more 472 00:28:43,440 --> 00:28:45,960 Speaker 3: Vinyl records. It just feels like there's always kind of 473 00:28:45,960 --> 00:28:50,800 Speaker 3: a backlash against the popular movement. People are like wanting 474 00:28:50,840 --> 00:28:53,400 Speaker 3: to read things and holding it in their hands. You know, 475 00:28:53,600 --> 00:28:56,000 Speaker 3: I just think there's this is a very similar impulse. 476 00:28:56,080 --> 00:29:00,600 Speaker 4: Right, Oh yeah, that's a great point. Yeah, because oh also, 477 00:29:00,640 --> 00:29:04,720 Speaker 4: we have to pause just really quickly here to give 478 00:29:04,800 --> 00:29:07,680 Speaker 4: you a stuff that don't want you to know recommendation. 479 00:29:08,280 --> 00:29:10,680 Speaker 4: If ever, as Nol was saying, you see a blu 480 00:29:10,800 --> 00:29:14,520 Speaker 4: ray or a dusty collection of CDs at the counter 481 00:29:14,600 --> 00:29:18,800 Speaker 4: of your local gas station, buy them, buy the mixtape, 482 00:29:18,880 --> 00:29:21,040 Speaker 4: you know what I mean. You see like the Poughkeepsie 483 00:29:21,080 --> 00:29:26,200 Speaker 4: Posse or something, pick it up as long as it's 484 00:29:26,760 --> 00:29:30,400 Speaker 4: not over thirty dollars. Is that okay? Do you guys 485 00:29:30,400 --> 00:29:34,120 Speaker 4: ever buy this sort of sketchy CS that you see? 486 00:29:34,200 --> 00:29:38,200 Speaker 3: Yeah, especially when I was driving the aforementioned sixteen disc 487 00:29:38,320 --> 00:29:41,080 Speaker 3: changer Beatermobile that I talked about in our previous. 488 00:29:40,800 --> 00:29:44,760 Speaker 4: Episode Legendary, Did you have a name for that vehicle? Now? 489 00:29:44,840 --> 00:29:46,640 Speaker 3: I just made up Beatermobile, and I think I like that. 490 00:29:47,160 --> 00:29:49,840 Speaker 4: I like that too. I like that too. What's your 491 00:29:49,920 --> 00:29:51,200 Speaker 4: social Security number? 492 00:29:51,480 --> 00:29:55,400 Speaker 3: It's a. 493 00:29:56,440 --> 00:29:58,960 Speaker 4: There's one last thing we wanted to share. A lot 494 00:29:59,000 --> 00:30:03,920 Speaker 4: of folks have written to us about the following. We've 495 00:30:03,960 --> 00:30:10,720 Speaker 4: talked at length about large language models. Sometimes called AI problematically, 496 00:30:11,400 --> 00:30:13,760 Speaker 4: and the most famous of those in the West is 497 00:30:13,800 --> 00:30:18,720 Speaker 4: something called chat GPT. Now, it's quite common in education 498 00:30:19,040 --> 00:30:22,600 Speaker 4: in day to day life for people to use chat 499 00:30:22,680 --> 00:30:28,200 Speaker 4: GPT pretty often, and not to sound like old entity 500 00:30:28,440 --> 00:30:32,640 Speaker 4: shouting at the sky, but I think we've all harbored 501 00:30:32,720 --> 00:30:40,920 Speaker 4: concerns that using this stuff may harm cognitive abilities at 502 00:30:40,960 --> 00:30:44,600 Speaker 4: some point and to some degree. There's a new study 503 00:30:44,800 --> 00:30:49,480 Speaker 4: that was recently published from researchers at MIT's Media Lab 504 00:30:50,280 --> 00:30:54,440 Speaker 4: that gives a little bit of quantitative basis to this, 505 00:30:54,960 --> 00:31:00,240 Speaker 4: similar to the Alex Jones frog stuff right, and the 506 00:31:00,320 --> 00:31:08,000 Speaker 4: dangers of synthetic estrogen emission and transmission throughout an unregulated ecosystem. 507 00:31:08,640 --> 00:31:12,600 Speaker 4: This study, guys, have we heard about this? It's kind 508 00:31:12,600 --> 00:31:14,000 Speaker 4: of breaking news. No. 509 00:31:14,000 --> 00:31:15,840 Speaker 3: No, I'm excited to hear about it, though, maybe excited 510 00:31:15,880 --> 00:31:17,680 Speaker 3: to throw and I'm fascinated to hear about it. 511 00:31:19,640 --> 00:31:25,120 Speaker 4: We should ask chat gpt about it. The study divides 512 00:31:25,200 --> 00:31:30,200 Speaker 4: fifty four subjects, all from Boston, all between eighteen to 513 00:31:30,200 --> 00:31:33,560 Speaker 4: thirty nine years old, and it put them in three groups, 514 00:31:34,000 --> 00:31:36,920 Speaker 4: and it asked them to write essays like you would 515 00:31:36,920 --> 00:31:40,560 Speaker 4: write in a college entrance exam, right, or a qualifier 516 00:31:40,600 --> 00:31:45,840 Speaker 4: exam like the SAT and one group uses chat GPT, 517 00:31:46,080 --> 00:31:51,120 Speaker 4: one group uses Google, and the third group is just 518 00:31:51,320 --> 00:31:54,960 Speaker 4: working the way you would in say the nineteen fifties 519 00:31:55,280 --> 00:31:59,040 Speaker 4: or something, right, just the treasures in their own minds. 520 00:31:59,480 --> 00:32:03,320 Speaker 4: And while they were working on these questions, the researchers 521 00:32:03,480 --> 00:32:09,600 Speaker 4: used an EEG to record the brain activity of these 522 00:32:09,680 --> 00:32:13,200 Speaker 4: folks writing these essays, and they recorded it across thirty 523 00:32:13,200 --> 00:32:17,120 Speaker 4: two regions of the brain and they found that provably, 524 00:32:17,720 --> 00:32:22,560 Speaker 4: with an admittedly small sample size, the chat GPT group 525 00:32:22,840 --> 00:32:27,120 Speaker 4: had the lowest brain engagement. And this is a quote 526 00:32:27,160 --> 00:32:33,920 Speaker 4: from the study, consistently underperformed at neural, linguistic and behavioral levels. 527 00:32:34,320 --> 00:32:36,320 Speaker 4: What do we think about that? Does that jibe with 528 00:32:36,440 --> 00:32:39,680 Speaker 4: earlier conversations? Yes, should we be concerned? Yes? 529 00:32:39,760 --> 00:32:42,200 Speaker 3: And yes I think so. I don't mess with them 530 00:32:42,240 --> 00:32:44,680 Speaker 3: at all. And I don't know if maybe it's just 531 00:32:45,320 --> 00:32:47,640 Speaker 3: it's not appealing to me. It's less of like a 532 00:32:47,920 --> 00:32:51,880 Speaker 3: philosophical thing than it just doesn't particularly interest me. And 533 00:32:51,920 --> 00:32:54,200 Speaker 3: maybe that is me getting aged out of a new 534 00:32:54,240 --> 00:32:56,840 Speaker 3: thing to a degree, being old man shouting at cloud. 535 00:32:57,200 --> 00:33:01,000 Speaker 3: But yeah, I can imagine even just the way people 536 00:33:01,040 --> 00:33:04,040 Speaker 3: get obsessed and addicted to the Internet and to social 537 00:33:04,040 --> 00:33:06,080 Speaker 3: media and things. This is just an escalation of that 538 00:33:06,160 --> 00:33:09,760 Speaker 3: because it like talks back and sort of acts as 539 00:33:09,760 --> 00:33:14,160 Speaker 3: a stand for some of that common sense, that kind 540 00:33:14,200 --> 00:33:16,920 Speaker 3: of critical thinking, you know, and those muscles then kind 541 00:33:16,960 --> 00:33:17,480 Speaker 3: of atrophy. 542 00:33:17,840 --> 00:33:23,280 Speaker 2: Well, yeah, it's it's stepped offloading of processing power, right. Yeah, 543 00:33:24,120 --> 00:33:27,840 Speaker 2: So every time you have an AID, Let's say you've 544 00:33:27,840 --> 00:33:31,280 Speaker 2: got books that you're looking at, that's a lot of 545 00:33:31,280 --> 00:33:34,560 Speaker 2: the processing power that you would be using. It's already 546 00:33:34,560 --> 00:33:37,240 Speaker 2: written down somebody else's thoughts, somebody else's words, and now 547 00:33:37,280 --> 00:33:40,200 Speaker 2: you're taking that in and translating that into your thoughts. 548 00:33:40,280 --> 00:33:40,480 Speaker 5: Right. 549 00:33:40,800 --> 00:33:42,640 Speaker 2: Well, then if you've got Google, you're doing kind of 550 00:33:42,680 --> 00:33:44,520 Speaker 2: the same thing, but now you've got access to way 551 00:33:44,560 --> 00:33:46,960 Speaker 2: more thoughts from way more people, and you're processing all 552 00:33:46,960 --> 00:33:49,800 Speaker 2: that stuff. Then, if you're in chat GBT, you really 553 00:33:49,840 --> 00:33:54,800 Speaker 2: are offloading all of the conceptualization, all of the crystallization. 554 00:33:55,400 --> 00:33:58,000 Speaker 2: It is now in the hands of something else and 555 00:33:58,040 --> 00:34:02,040 Speaker 2: you're just gonna pair it back. You're just now a 556 00:34:02,120 --> 00:34:06,520 Speaker 2: conduit through which these computers are processing all of the information. 557 00:34:07,120 --> 00:34:09,919 Speaker 2: So I could totally see why it makes the old 558 00:34:10,000 --> 00:34:13,600 Speaker 2: noggin stop working as well as it as it did before. 559 00:34:13,640 --> 00:34:18,000 Speaker 4: At least that's a brilliant observation. It reminds me, well, 560 00:34:18,000 --> 00:34:22,000 Speaker 4: he just said, reminds me of the the old evenings 561 00:34:22,080 --> 00:34:27,600 Speaker 4: when the calculator was proliferating, right, and there was quite 562 00:34:27,640 --> 00:34:32,640 Speaker 4: a bit of social panic and hullabaloo, and people were saying, oh, 563 00:34:32,680 --> 00:34:36,680 Speaker 4: these kids, what's that movie? Stand and Deliver? That were 564 00:34:36,760 --> 00:34:40,279 Speaker 4: James almost he's like these kids. But there was this 565 00:34:40,800 --> 00:34:45,960 Speaker 4: moment wherein the adults of the day were saying, look, 566 00:34:46,440 --> 00:34:52,879 Speaker 4: if every kid learns math via a calculator, then how 567 00:34:52,920 --> 00:34:56,080 Speaker 4: will they do triggonometry in their heads? How will they 568 00:34:56,160 --> 00:35:01,200 Speaker 4: do long division? And turns out that was a good question, 569 00:35:01,400 --> 00:35:03,880 Speaker 4: because we don't know a ton of people in the 570 00:35:03,920 --> 00:35:07,439 Speaker 4: modern day in the West who can do trigonometry or 571 00:35:07,920 --> 00:35:10,560 Speaker 4: long division in their heads unless. 572 00:35:10,280 --> 00:35:12,799 Speaker 3: That's your specialty here, unless you know, you're just one 573 00:35:12,840 --> 00:35:16,319 Speaker 3: of those people that's fascinated with old school math. Because now, 574 00:35:16,360 --> 00:35:19,279 Speaker 3: even like the top dogs like have you know, very 575 00:35:19,360 --> 00:35:22,480 Speaker 3: powerful computers that offload a lot of that a lot 576 00:35:22,480 --> 00:35:25,239 Speaker 3: of those duties too, not to mention the use of 577 00:35:25,280 --> 00:35:28,799 Speaker 3: AI for and quantum computing. We talked about that with 578 00:35:29,400 --> 00:35:32,480 Speaker 3: Jorge Chan on a recent episode of Ridiculous History, that 579 00:35:32,480 --> 00:35:35,120 Speaker 3: they all should check out, very very interesting and kind 580 00:35:35,120 --> 00:35:37,120 Speaker 3: of scary stuff in terms of that offloading. 581 00:35:38,400 --> 00:35:42,160 Speaker 2: Think about it this way, guys, A couple of years 582 00:35:42,200 --> 00:35:45,440 Speaker 2: after we were born, the first state in the United 583 00:35:45,520 --> 00:35:50,239 Speaker 2: States decided that calculators are necessary for their standard exams. 584 00:35:51,400 --> 00:35:54,359 Speaker 2: Before that, it was nineteen seventy five when they when 585 00:35:54,560 --> 00:35:57,680 Speaker 2: the world, when the United States especially said hey, maybe 586 00:35:57,680 --> 00:36:01,240 Speaker 2: calculators would be good for students in a grade and above, 587 00:36:01,680 --> 00:36:05,919 Speaker 2: maybe we should use these calculator things like that. That's 588 00:36:05,960 --> 00:36:09,640 Speaker 2: crazy to think it's been since we've been alive, but still, 589 00:36:10,160 --> 00:36:13,560 Speaker 2: ever since we've been alive, we've had access to calculators, 590 00:36:14,520 --> 00:36:18,400 Speaker 2: and so our brains were never forced to learn the 591 00:36:18,440 --> 00:36:22,160 Speaker 2: things that those before us were forced to do. Right 592 00:36:22,280 --> 00:36:24,480 Speaker 2: that the computing power. 593 00:36:24,400 --> 00:36:27,719 Speaker 3: And we've talked about this often, but one could argue 594 00:36:27,760 --> 00:36:31,280 Speaker 3: that when you free up that stuff, it can adapt 595 00:36:31,400 --> 00:36:35,600 Speaker 3: to do other stuff that is maybe more beneficial. But 596 00:36:36,160 --> 00:36:40,320 Speaker 3: when you start offloading kind of everything and just thought 597 00:36:40,400 --> 00:36:43,319 Speaker 3: and critical thinking in general, that does seem like a 598 00:36:43,400 --> 00:36:45,680 Speaker 3: really dangerous, since slippery slope. 599 00:36:46,239 --> 00:36:48,680 Speaker 4: And that's the point we want to get to exactly 600 00:36:48,880 --> 00:36:52,799 Speaker 4: well put the idea of the brain, the human brain 601 00:36:52,920 --> 00:36:57,880 Speaker 4: as the great repurposer, does have a lot of validity 602 00:36:58,200 --> 00:37:04,000 Speaker 4: to a certain threshold. The name of the study. Shout 603 00:37:04,040 --> 00:37:08,560 Speaker 4: out to you, Dylan for introducing transactive memory. I think 604 00:37:08,600 --> 00:37:11,040 Speaker 4: we read a lot of the same books. The name 605 00:37:11,080 --> 00:37:13,480 Speaker 4: of the study will give us a bit of a 606 00:37:13,560 --> 00:37:17,000 Speaker 4: hint of why this may be different to the earlier 607 00:37:17,040 --> 00:37:22,160 Speaker 4: comparison we introduced about calculators. Here is the title your 608 00:37:22,239 --> 00:37:27,680 Speaker 4: Brain on chat GPT accumulation of here this well cognitive 609 00:37:27,800 --> 00:37:32,600 Speaker 4: debt when using an AI assistant for say, writing task. 610 00:37:33,200 --> 00:37:37,400 Speaker 4: And then we'll triangle the top like an asterisk. Eight authors, 611 00:37:38,120 --> 00:37:45,400 Speaker 4: fantastic work, most from MIT one from Wellesley also in Massachusetts. 612 00:37:45,960 --> 00:37:49,640 Speaker 4: To your point, Noel, it makes us wonder whether there 613 00:37:49,719 --> 00:37:53,879 Speaker 4: are some specific regions of the brain that just have 614 00:37:54,000 --> 00:37:58,759 Speaker 4: to do that one thing right, that one aspect of 615 00:37:59,000 --> 00:38:03,239 Speaker 4: intelligence or processing that may be the muscle matter is 616 00:38:03,280 --> 00:38:06,920 Speaker 4: referring to when we're talking about, you know, uh, atrophy 617 00:38:07,360 --> 00:38:13,279 Speaker 4: of these faculties. Atrophy of these faculties. That sounds like 618 00:38:13,400 --> 00:38:16,160 Speaker 4: a what band would make that. 619 00:38:16,080 --> 00:38:18,160 Speaker 3: Album Corrosion of Conformity? 620 00:38:19,040 --> 00:38:23,120 Speaker 4: True? Is that a real bit is? Are they good? 621 00:38:23,200 --> 00:38:29,480 Speaker 4: I don't know, And we got a hell yeah from 622 00:38:29,640 --> 00:38:34,200 Speaker 4: our Tennessee pal. I feel like it's inevitable. I think 623 00:38:34,239 --> 00:38:38,720 Speaker 4: we all agree that unless we reach an inflection point 624 00:38:38,840 --> 00:38:42,920 Speaker 4: similar to the background of the Doune universe when there 625 00:38:43,000 --> 00:38:47,279 Speaker 4: was a but Lerry and Jahad against thinking machines, I 626 00:38:47,320 --> 00:38:51,360 Speaker 4: believe the future of the human is increasingly cybernetic, and 627 00:38:51,360 --> 00:38:54,000 Speaker 4: I'm interested to hear I think we all are interested 628 00:38:54,040 --> 00:38:57,800 Speaker 4: to hear from you guys about how you see your 629 00:38:57,920 --> 00:39:03,560 Speaker 4: children's education going forward in a world where chat GPT 630 00:39:03,920 --> 00:39:07,319 Speaker 4: kind of becomes like the next iteration of a calculator 631 00:39:07,360 --> 00:39:10,160 Speaker 4: on a test. Yuck. 632 00:39:10,360 --> 00:39:13,080 Speaker 3: Yeah, And that is part of the conversation around it, 633 00:39:13,120 --> 00:39:16,400 Speaker 3: Like in terms of it as a tool, you know, 634 00:39:16,480 --> 00:39:19,560 Speaker 3: and there are some very interesting and useful and relevant 635 00:39:19,600 --> 00:39:22,000 Speaker 3: ways to use it, but unfortunately, it just seems that 636 00:39:22,040 --> 00:39:24,719 Speaker 3: a lot of people are using it in place of, 637 00:39:25,120 --> 00:39:28,319 Speaker 3: you know, things that maybe that shouldn't meant for. 638 00:39:29,040 --> 00:39:31,320 Speaker 2: Well, it's really tough for me, and I think I 639 00:39:31,400 --> 00:39:34,759 Speaker 2: might just be having old man syndrome every time I 640 00:39:34,760 --> 00:39:41,240 Speaker 2: think about this stuff. But the skill of searching for something, 641 00:39:42,440 --> 00:39:46,120 Speaker 2: maybe we don't need that anymore, right necessarily, but the 642 00:39:46,160 --> 00:39:52,560 Speaker 2: skill of sorting through sources, sorting through information, and then 643 00:39:52,760 --> 00:39:55,759 Speaker 2: putting that information together in your head does feel like 644 00:39:55,920 --> 00:39:59,359 Speaker 2: the exact thing like that we talk about on the show. 645 00:39:59,400 --> 00:40:03,160 Speaker 2: That's so important, right, the critical thinking thing, the ability 646 00:40:03,200 --> 00:40:06,680 Speaker 2: to create a third thought out of two different thoughts. 647 00:40:08,440 --> 00:40:10,839 Speaker 2: And if we really do put something in place of 648 00:40:10,840 --> 00:40:14,600 Speaker 2: that overall, for all of society, for just for kids, 649 00:40:14,640 --> 00:40:18,360 Speaker 2: like that's the downfall of humanity. 650 00:40:18,480 --> 00:40:21,040 Speaker 3: Not to mention, if you're just trusting something like that 651 00:40:21,120 --> 00:40:25,160 Speaker 3: so implicitly, and you're offloading your own personal cognitive ability 652 00:40:25,239 --> 00:40:30,040 Speaker 3: to differentiate between fact and fiction and whatever various perspectives. 653 00:40:30,360 --> 00:40:33,240 Speaker 3: Then let's say there were bad actors, or let's say 654 00:40:33,440 --> 00:40:37,120 Speaker 3: that the AI did start to become sentient and wanted 655 00:40:37,160 --> 00:40:39,279 Speaker 3: to use that trust against us. I mean, I don't 656 00:40:39,320 --> 00:40:42,440 Speaker 3: mean to be too alarmist, but if you're completely trusting 657 00:40:42,480 --> 00:40:45,880 Speaker 3: in this, that is a real dangerous situation because then 658 00:40:45,880 --> 00:40:48,479 Speaker 3: it could be people could be manipulated so easily, because 659 00:40:48,520 --> 00:40:51,000 Speaker 3: no one has the ability to make a decision or 660 00:40:51,440 --> 00:40:53,040 Speaker 3: a judgment call for themselves anymore. 661 00:40:53,760 --> 00:40:55,759 Speaker 4: You know what I'm gonna miss you, guys. I'm gonna 662 00:40:55,800 --> 00:40:58,920 Speaker 4: miss m dashes. You know, the long dashes of a 663 00:40:58,960 --> 00:41:02,960 Speaker 4: long dash. Yeah, Now they're for boating. They're seen as 664 00:41:03,000 --> 00:41:07,520 Speaker 4: bad as a trill bey or fedora. Back when the 665 00:41:07,560 --> 00:41:11,000 Speaker 4: men's rights dudes took those over and ruined them for everybody. 666 00:41:11,280 --> 00:41:15,399 Speaker 4: The M dash is now seen as a signal that 667 00:41:15,560 --> 00:41:18,560 Speaker 4: someone has not written their own thing but has instead 668 00:41:18,840 --> 00:41:23,360 Speaker 4: used chat GPT, which is irksome because you guys know me, 669 00:41:23,640 --> 00:41:26,239 Speaker 4: I use M dashes a lot, not as much as 670 00:41:26,239 --> 00:41:30,040 Speaker 4: Emily Dickinson, but I'm always like, and the other thing. 671 00:41:31,200 --> 00:41:34,920 Speaker 2: I just hit dash twice or the minus sign twice 672 00:41:35,120 --> 00:41:35,560 Speaker 2: a lot. 673 00:41:36,080 --> 00:41:38,239 Speaker 4: Yeah, yeah, yeah, yeah, yeah. I mean that's the way 674 00:41:38,360 --> 00:41:41,880 Speaker 4: it moves with uh, it moves with conversation. But I 675 00:41:41,920 --> 00:41:47,160 Speaker 4: think the reason people are maybe anti m dash at 676 00:41:47,160 --> 00:41:52,520 Speaker 4: this point is because to our earlier, earlier conversation, everyone 677 00:41:52,640 --> 00:41:56,520 Speaker 4: is trying to figure out how to differentiate between human 678 00:41:56,560 --> 00:42:03,520 Speaker 4: made thoughts and chat gpt he generated stuff. I wouldn't 679 00:42:03,520 --> 00:42:05,239 Speaker 4: always call it AI slop, but no. 680 00:42:05,800 --> 00:42:09,160 Speaker 3: One thing we talked about with Jorge Ben is this 681 00:42:09,280 --> 00:42:12,040 Speaker 3: idea that you know, when photoshop first came out, and 682 00:42:12,080 --> 00:42:15,000 Speaker 3: how then, you know, as rudimentary as that might have seemed, 683 00:42:15,200 --> 00:42:18,359 Speaker 3: it created a new scenario where people no longer could 684 00:42:18,360 --> 00:42:23,040 Speaker 3: fully trust their eyes. Now, with you know, AI generated 685 00:42:23,120 --> 00:42:27,279 Speaker 3: video looking so convincing, the only real answer there is 686 00:42:27,280 --> 00:42:31,880 Speaker 3: to have like almost mandated watermarks or ways of determining 687 00:42:31,920 --> 00:42:35,160 Speaker 3: whether a piece of content was in fact generated or 688 00:42:35,480 --> 00:42:38,920 Speaker 3: was captured, you know, from the world, because it's going 689 00:42:38,960 --> 00:42:40,160 Speaker 3: to get to a point where we're not gonna be 690 00:42:40,160 --> 00:42:42,719 Speaker 3: able to tell the difference. It's already there in a 691 00:42:42,719 --> 00:42:43,160 Speaker 3: lot of ways. 692 00:42:43,239 --> 00:42:48,000 Speaker 4: Yeah, So, dear large language models, bots and humes alike, 693 00:42:48,920 --> 00:42:52,200 Speaker 4: we we can't wait to hear from you. We're off 694 00:42:52,280 --> 00:42:56,359 Speaker 4: for some adventures. We're going to be returning very soon. 695 00:42:56,480 --> 00:42:59,200 Speaker 4: We hope that you will join us. More importantly, we 696 00:42:59,280 --> 00:43:03,239 Speaker 4: hope that you will tell us your thoughts. We want 697 00:43:03,239 --> 00:43:04,960 Speaker 4: to get in your head. You know what I mean, 698 00:43:05,040 --> 00:43:08,680 Speaker 4: nothing creepy. You can send us an email, call us 699 00:43:08,719 --> 00:43:10,840 Speaker 4: on the phone, or find us on the lines. 700 00:43:11,120 --> 00:43:13,319 Speaker 3: You certainly can't find us all over the lines at 701 00:43:13,320 --> 00:43:15,799 Speaker 3: the handle conspiracy Stuff where we exist on Facebook with 702 00:43:15,840 --> 00:43:19,760 Speaker 3: our Facebook group here's where it gets crazy, on xfka, Twitter, 703 00:43:19,880 --> 00:43:24,000 Speaker 3: and on YouTube video content color for your perusing enjoyment 704 00:43:24,120 --> 00:43:27,320 Speaker 3: on Instagram and TikTok. 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