1 00:00:00,240 --> 00:00:04,680 Speaker 1: From UFOs to psychic powers and government conspiracies. History is 2 00:00:04,800 --> 00:00:09,119 Speaker 1: riddled with unexplained events. You can turn back now or 3 00:00:09,200 --> 00:00:12,079 Speaker 1: learn the stuff they don't want you to know. A 4 00:00:12,240 --> 00:00:25,680 Speaker 1: production of I Heart Radio. Hello, welcome back to the show. 5 00:00:25,800 --> 00:00:28,880 Speaker 1: My name is Matt, my name is Nol. They called 6 00:00:28,880 --> 00:00:31,960 Speaker 1: me Ben. We're joined as always with our super producer Paul, 7 00:00:32,000 --> 00:00:36,040 Speaker 1: Mission controlled dec and most importantly, you are you. You 8 00:00:36,120 --> 00:00:40,240 Speaker 1: are here and that makes this the stuff they don't 9 00:00:40,240 --> 00:00:43,960 Speaker 1: want you to know. Twenty twenty three, a little bit 10 00:00:43,960 --> 00:00:49,360 Speaker 1: of fanfair Paul, if you will perfect, there we go. Uh. 11 00:00:49,520 --> 00:00:52,400 Speaker 1: We we made it. We're coming to you from the 12 00:00:52,479 --> 00:00:56,400 Speaker 1: past year. Uh. Listeners, fellow conspiracy realists, you may have 13 00:00:56,480 --> 00:00:59,280 Speaker 1: noticed that we took some time off, got a little 14 00:00:59,400 --> 00:01:02,240 Speaker 1: R and R. Hopefully by the time you're hearing this, 15 00:01:02,520 --> 00:01:04,600 Speaker 1: and we hope you had a great end of the 16 00:01:04,720 --> 00:01:08,160 Speaker 1: year as well. We figured what better way to kick 17 00:01:08,240 --> 00:01:11,000 Speaker 1: things off by doing one of our favorite segments on 18 00:01:11,040 --> 00:01:14,880 Speaker 1: the show, Strange News. We're going to talk about a 19 00:01:15,959 --> 00:01:20,080 Speaker 1: a fire. We're going to talk about um, a great 20 00:01:20,160 --> 00:01:24,800 Speaker 1: debate regarding the nature of art and ownership. Uh. And 21 00:01:25,160 --> 00:01:28,720 Speaker 1: we're also going to talk about something that I think 22 00:01:28,720 --> 00:01:33,280 Speaker 1: we've always dreamed of nuclear fusion caveat astric astric. Yeah. 23 00:01:33,440 --> 00:01:35,160 Speaker 1: And while like you know, this isn't exactly like a 24 00:01:35,240 --> 00:01:38,600 Speaker 1: year end round up of news, um, several of these 25 00:01:38,600 --> 00:01:42,399 Speaker 1: stories really do kind of encapsulate the zeitgeist of the 26 00:01:42,480 --> 00:01:46,440 Speaker 1: year in some ways. UM. Specifically this fusion thing, which 27 00:01:46,440 --> 00:01:49,520 Speaker 1: has been a long time coming, um for many years. 28 00:01:49,760 --> 00:01:53,960 Speaker 1: And uh, the idea of AI and where it's heading 29 00:01:54,080 --> 00:01:57,760 Speaker 1: and facial recognition uh turning into a bit of a 30 00:01:57,840 --> 00:02:02,080 Speaker 1: novelty item, that is you and people you know fun avatar, 31 00:02:02,240 --> 00:02:05,560 Speaker 1: so their profile without them maybe realizing that they're kind 32 00:02:05,600 --> 00:02:10,160 Speaker 1: of feeding an unseen beast. Yes, and uh, I think 33 00:02:10,280 --> 00:02:14,360 Speaker 1: I think all three of our stories today, uh further 34 00:02:14,520 --> 00:02:18,600 Speaker 1: these larger conversations. So what what better way to kick 35 00:02:18,760 --> 00:02:23,400 Speaker 1: off the new year? I I propose that we um 36 00:02:23,480 --> 00:02:26,880 Speaker 1: I've proposed since we've got two science ones. Uh, we 37 00:02:27,000 --> 00:02:30,200 Speaker 1: start maybe with what you just set up so beautifully. No, 38 00:02:30,440 --> 00:02:34,720 Speaker 1: let's let's talk about LENSA and uh, let's see, now 39 00:02:35,280 --> 00:02:38,240 Speaker 1: everybody's familiar with this. Uh. You if you are on 40 00:02:38,320 --> 00:02:43,520 Speaker 1: social media, you have seen, um some really beautiful profile 41 00:02:43,639 --> 00:02:47,320 Speaker 1: picks in very specific styles that people have used through 42 00:02:47,400 --> 00:02:50,000 Speaker 1: the lens of app. But that that's not the only 43 00:02:50,080 --> 00:02:51,919 Speaker 1: one of its kind out there. But I think that's 44 00:02:51,919 --> 00:02:54,720 Speaker 1: where the debate really took root. As that correct it 45 00:02:54,800 --> 00:02:57,079 Speaker 1: is and it's you. It's the kind of uh viral 46 00:02:57,160 --> 00:03:00,240 Speaker 1: marketing you really can't pay for better. Yeah, let have 47 00:03:00,760 --> 00:03:05,560 Speaker 1: users pay for the privilege of advertising our app. Uh. 48 00:03:05,600 --> 00:03:08,320 Speaker 1: There's no water mark on these images, which I thought 49 00:03:08,320 --> 00:03:11,160 Speaker 1: was really interesting. So it created this conversation where did 50 00:03:11,160 --> 00:03:13,800 Speaker 1: you get that? Where did that come from? Wow, you 51 00:03:13,880 --> 00:03:17,440 Speaker 1: look like an Elvin princess or a superhero or a 52 00:03:17,480 --> 00:03:21,880 Speaker 1: freaking Blade Runner character, you know, all these stylized portraits 53 00:03:22,720 --> 00:03:25,480 Speaker 1: some kind of like, well, I did it because I'm 54 00:03:25,480 --> 00:03:30,560 Speaker 1: a suckle uh and I love a good technology um gimmick, 55 00:03:30,680 --> 00:03:32,440 Speaker 1: you know, a big fan. I don't want to be 56 00:03:32,560 --> 00:03:35,800 Speaker 1: left behind in the conversation, so I uh and the 57 00:03:35,840 --> 00:03:40,560 Speaker 1: first to admit that I unknowingly fed said beast. But again, 58 00:03:40,640 --> 00:03:43,120 Speaker 1: let's get back to kind of the conversation. All of 59 00:03:43,160 --> 00:03:46,040 Speaker 1: a sudden, the Internet was flooded, much like all of 60 00:03:46,040 --> 00:03:51,000 Speaker 1: those um you know kind of AI generated little meme things, 61 00:03:51,080 --> 00:03:52,600 Speaker 1: you know, like, well, what are the you know, you 62 00:03:52,640 --> 00:03:55,000 Speaker 1: feed it some texts or was it not mid journey 63 00:03:55,000 --> 00:03:57,840 Speaker 1: with the original one? Um? Oh, gosh, now I'm forgetting. 64 00:03:57,840 --> 00:04:00,200 Speaker 1: But it was the one that kind of was easy, 65 00:04:00,240 --> 00:04:03,880 Speaker 1: easily accessible without pay internet in some text and you 66 00:04:03,880 --> 00:04:06,600 Speaker 1: could have like Johnny Cash eating corn on the cob 67 00:04:06,800 --> 00:04:08,440 Speaker 1: or whatever it might be. So that was, you know, 68 00:04:08,520 --> 00:04:11,680 Speaker 1: a massive internet phenomenon. This is sort of the next 69 00:04:11,800 --> 00:04:14,720 Speaker 1: version of that. But what these are they're not that 70 00:04:14,920 --> 00:04:20,400 Speaker 1: same kind of weird like a deep dream kind of 71 00:04:20,440 --> 00:04:26,320 Speaker 1: psychedelic mishmash kind of stuff. These are highly, highly stylized 72 00:04:26,480 --> 00:04:30,920 Speaker 1: at times photo realistic portraits of you. Um, and all 73 00:04:30,920 --> 00:04:33,400 Speaker 1: you Gotta do is you know, first asked the question 74 00:04:33,440 --> 00:04:35,960 Speaker 1: like I did. In fact, it was asked of uh 75 00:04:36,080 --> 00:04:41,080 Speaker 1: super producer extraordinaire Alexis code named doc Holiday Jackson. When 76 00:04:41,120 --> 00:04:44,440 Speaker 1: I saw these incredible, you know, beautiful portraits looked like 77 00:04:44,440 --> 00:04:46,560 Speaker 1: a human being had done them, you know, and been 78 00:04:46,600 --> 00:04:50,120 Speaker 1: paid handsomely, you know, to do that, um, to which 79 00:04:50,160 --> 00:04:53,360 Speaker 1: she replied, it's this app called lens Up. Lensa an 80 00:04:53,360 --> 00:04:57,520 Speaker 1: app created by Prisma AI. Um, you feed it a 81 00:04:57,520 --> 00:05:00,480 Speaker 1: handful of selfies. I think it's twenty or something like. 82 00:05:00,560 --> 00:05:01,960 Speaker 1: It says it's either ten or twenty, and I think 83 00:05:02,000 --> 00:05:04,520 Speaker 1: it's I think it's ten. Um, and they have to 84 00:05:04,560 --> 00:05:08,159 Speaker 1: be of a certain you know, uh distance, you know, 85 00:05:08,320 --> 00:05:10,520 Speaker 1: like a certain frame, right, Like you don't want a 86 00:05:10,560 --> 00:05:12,440 Speaker 1: full body thing. I think they'll reject them and they 87 00:05:12,440 --> 00:05:14,279 Speaker 1: won't tell you why, and you just have to find 88 00:05:14,279 --> 00:05:17,200 Speaker 1: one that's more appropriate. And once it does that, depending 89 00:05:17,240 --> 00:05:19,919 Speaker 1: on the load, you know, in terms of the demand, 90 00:05:20,040 --> 00:05:23,719 Speaker 1: it'll take between fifteen twenty. I did it for a 91 00:05:23,720 --> 00:05:26,039 Speaker 1: couple of friends and and a little later, you know, 92 00:05:26,120 --> 00:05:28,440 Speaker 1: after kind of the things started really hitting. It was 93 00:05:28,480 --> 00:05:32,080 Speaker 1: taking a couple of hours to process those selfies. And 94 00:05:32,360 --> 00:05:35,200 Speaker 1: you pay a couple of bucks. Um, I think it's 95 00:05:35,240 --> 00:05:39,040 Speaker 1: like five bucks or something like that for I think fifty, 96 00:05:39,080 --> 00:05:41,440 Speaker 1: and you can pay I think twenty bucks for a hundred, 97 00:05:41,800 --> 00:05:44,000 Speaker 1: and they're done kind of in these buckets, these sort 98 00:05:44,000 --> 00:05:46,839 Speaker 1: of style buckets. Like one of them is like Superhero, 99 00:05:47,320 --> 00:05:50,760 Speaker 1: one of them is like Greek mythology or something like that. 100 00:05:50,839 --> 00:05:53,039 Speaker 1: You know. They had me looking like Odin or you know, 101 00:05:53,120 --> 00:05:56,240 Speaker 1: freaking Thor or whatever, um with the beard and they 102 00:05:56,240 --> 00:05:58,960 Speaker 1: gave me like valkyrie horns and all this stuff and 103 00:05:58,960 --> 00:06:03,080 Speaker 1: then were awesome and they're super cool. That's the thing, y'all. 104 00:06:03,360 --> 00:06:06,600 Speaker 1: This is cool, Okay. I am fascinated by where I 105 00:06:06,800 --> 00:06:09,080 Speaker 1: is going I I did it too, but it didn't 106 00:06:09,240 --> 00:06:11,880 Speaker 1: upload it because I was talking with some of my 107 00:06:11,960 --> 00:06:14,880 Speaker 1: friends in the art community and they were very much 108 00:06:15,480 --> 00:06:17,680 Speaker 1: of the opinion that something was rotten in the state 109 00:06:17,720 --> 00:06:20,400 Speaker 1: of Denmark. You know. That's that's the thing with AI. 110 00:06:20,520 --> 00:06:22,839 Speaker 1: You know, even this like mid Journey stuff. You know, 111 00:06:22,920 --> 00:06:25,719 Speaker 1: our dear friend and illustrator of the stuff they don't 112 00:06:25,720 --> 00:06:28,760 Speaker 1: want you to know book Nick Benson. Um he he 113 00:06:28,800 --> 00:06:32,520 Speaker 1: has a subscription to mid Journey and as simultaneously fascinated 114 00:06:32,560 --> 00:06:37,560 Speaker 1: and terrified by this technology because mid Journey specifically, you've 115 00:06:37,600 --> 00:06:40,719 Speaker 1: got some amazing folks that are using this to kind 116 00:06:40,720 --> 00:06:44,160 Speaker 1: of create images of things that just don't exist. You know, 117 00:06:44,279 --> 00:06:47,080 Speaker 1: if you have the finesse and you can enter the 118 00:06:47,200 --> 00:06:49,599 Speaker 1: right kind of text, which can get really elaborate, like 119 00:06:49,839 --> 00:06:53,760 Speaker 1: you're describing the lighting, you're describing the background, you're describing 120 00:06:53,800 --> 00:06:56,680 Speaker 1: like a style of cinema, you know, like for example, 121 00:06:56,760 --> 00:06:59,000 Speaker 1: or like maybe a director or an artist or whatever. 122 00:06:59,240 --> 00:07:01,680 Speaker 1: And if you do really well, you can create some 123 00:07:01,839 --> 00:07:06,760 Speaker 1: genuinely remarkable things that aren't meant to mimic necessarily what 124 00:07:06,839 --> 00:07:08,719 Speaker 1: a human would do. It's sort of taking it to 125 00:07:08,720 --> 00:07:10,280 Speaker 1: the next level, and you could, let's say you're a 126 00:07:10,320 --> 00:07:13,600 Speaker 1: really interesting artist. You could combine these AI things with 127 00:07:13,680 --> 00:07:15,880 Speaker 1: your own work, or even feed it your own art, 128 00:07:16,160 --> 00:07:19,720 Speaker 1: and it'll like spit out some genuinely fascinating things. Um. 129 00:07:19,920 --> 00:07:22,840 Speaker 1: A buddy of mine, a great artist and musician here 130 00:07:22,840 --> 00:07:25,640 Speaker 1: in landa named Danny Carey Bailey. He if you follow 131 00:07:25,760 --> 00:07:28,560 Speaker 1: him on Instagram, just look for Danny Carey Bailey. Um 132 00:07:28,720 --> 00:07:31,880 Speaker 1: he he like make it. He'll make iterations of these 133 00:07:31,920 --> 00:07:34,640 Speaker 1: things and animate them together to create these kind of 134 00:07:34,720 --> 00:07:39,120 Speaker 1: moving you know, like video loops of this super uncanny 135 00:07:39,200 --> 00:07:43,720 Speaker 1: not uncanny valley, just uncanny, like you know, fantasy landscapes 136 00:07:43,800 --> 00:07:45,760 Speaker 1: and and things that just, like I said, just don't exist. 137 00:07:45,760 --> 00:07:48,520 Speaker 1: These objects that look like something oount of a you know, 138 00:07:48,840 --> 00:07:51,720 Speaker 1: David Cronenberg kind of body horror kind of stuff, like 139 00:07:51,760 --> 00:07:54,040 Speaker 1: really really neat if you kind of know what you're doing. 140 00:07:54,360 --> 00:07:56,640 Speaker 1: But that's not what lenses do. What Lens is doing 141 00:07:56,720 --> 00:08:01,120 Speaker 1: is essentially mimicking these highly stylized portrait that you know, 142 00:08:01,280 --> 00:08:04,840 Speaker 1: folks at say CON's, you know, Comic Con, Dragon Con, whatever, 143 00:08:05,160 --> 00:08:07,240 Speaker 1: they set up their booths and this is the kind 144 00:08:07,280 --> 00:08:09,240 Speaker 1: of stuff they sell that's kind of like D and 145 00:08:09,320 --> 00:08:12,680 Speaker 1: D portraiture, you know, or like like like well, will 146 00:08:12,760 --> 00:08:15,400 Speaker 1: you know fan art, you know, whatever it might be. 147 00:08:15,520 --> 00:08:18,240 Speaker 1: But these are done maybe using some technology like a 148 00:08:18,440 --> 00:08:20,680 Speaker 1: you know, a welcome tablet or whatever. Those than the 149 00:08:20,720 --> 00:08:23,160 Speaker 1: new iterations of that is um. But they're using their 150 00:08:23,440 --> 00:08:26,240 Speaker 1: their their skills as an artist. They're using a stylist 151 00:08:26,280 --> 00:08:28,920 Speaker 1: of some kind, or they're drawing and then scanning them 152 00:08:28,920 --> 00:08:31,200 Speaker 1: into computer and then using that to layer and add 153 00:08:31,200 --> 00:08:34,280 Speaker 1: additional stuff. Or it's entirely analogue and it's you know, 154 00:08:34,440 --> 00:08:37,640 Speaker 1: paint and uh and pen and anchor what have you. Um. 155 00:08:37,679 --> 00:08:40,640 Speaker 1: What this Prisma AI by way of the lens app 156 00:08:41,240 --> 00:08:43,840 Speaker 1: thing is doing is creating what they're referring to as 157 00:08:43,920 --> 00:08:48,800 Speaker 1: magic avatars, which is like biting this whole game, this 158 00:08:48,880 --> 00:08:52,280 Speaker 1: whole style that typically you would have a very skilled 159 00:08:52,360 --> 00:08:54,920 Speaker 1: artist either do a portrait or like let's say a 160 00:08:55,000 --> 00:08:57,920 Speaker 1: character from Game of Thrones or whatever. Um, and you'd 161 00:08:57,920 --> 00:08:59,960 Speaker 1: pay good money for these, or they can sell print 162 00:09:00,160 --> 00:09:02,400 Speaker 1: of them. You know a lot of times original pieces 163 00:09:02,400 --> 00:09:05,320 Speaker 1: are very expensive. There's only one, but if you sell 164 00:09:05,480 --> 00:09:08,760 Speaker 1: really high quality like geekly art prints or whatever, you 165 00:09:08,800 --> 00:09:10,679 Speaker 1: can sell dozens of them and really make a good 166 00:09:10,760 --> 00:09:15,680 Speaker 1: living that way. Um. Again back to Nick, he did 167 00:09:15,720 --> 00:09:18,080 Speaker 1: this as well, and he had friends that did it, 168 00:09:18,320 --> 00:09:22,280 Speaker 1: but it freaks him out while him also completely fascinating him. Um. 169 00:09:22,320 --> 00:09:24,720 Speaker 1: And the reason this is extra sketchy is because it 170 00:09:24,760 --> 00:09:29,640 Speaker 1: could potentially completely remove that kind of business from these 171 00:09:29,679 --> 00:09:34,200 Speaker 1: individuals who rely on this stuff to keep them going. Um. 172 00:09:34,280 --> 00:09:36,920 Speaker 1: Not to mention what this could mean for like say, 173 00:09:37,000 --> 00:09:40,240 Speaker 1: corporate art. You know again, a lot of the individuals 174 00:09:40,640 --> 00:09:43,400 Speaker 1: get these corporate gigs where they're like doing illustrations or 175 00:09:43,440 --> 00:09:46,120 Speaker 1: logos or whatever. And the more this AI stuff progress 176 00:09:46,240 --> 00:09:49,440 Speaker 1: is going to become increasingly distinguishable from quote unquote the 177 00:09:49,480 --> 00:09:53,600 Speaker 1: real thing um as in done by human And we 178 00:09:53,640 --> 00:09:56,800 Speaker 1: know how much corporations love jumping on trends like this 179 00:09:57,040 --> 00:09:59,880 Speaker 1: and love doing I mean, they can to remove the 180 00:10:00,120 --> 00:10:03,040 Speaker 1: human element because it's something they can't control, and this 181 00:10:03,080 --> 00:10:05,200 Speaker 1: will allot on them to keep costs under control. And 182 00:10:05,200 --> 00:10:06,720 Speaker 1: at the end of the day, are they really that 183 00:10:06,840 --> 00:10:11,040 Speaker 1: concerned with how authentic or bespoke because art is as 184 00:10:11,040 --> 00:10:13,760 Speaker 1: long as it kind of gets the job done. Probably not. 185 00:10:14,400 --> 00:10:18,160 Speaker 1: It depends on the corporation, right, if they're architectural firm, 186 00:10:18,280 --> 00:10:21,840 Speaker 1: or if they're a corporation that is involved with um, 187 00:10:21,920 --> 00:10:24,120 Speaker 1: the art world, then they probably do want to have 188 00:10:24,160 --> 00:10:26,520 Speaker 1: some things we spoke, but that's that's to your point. 189 00:10:26,559 --> 00:10:30,040 Speaker 1: It is probably more an exception to rule. You know. Uh, 190 00:10:30,080 --> 00:10:33,160 Speaker 1: this is always a time when people make predictions. And 191 00:10:33,280 --> 00:10:37,000 Speaker 1: one thing that's strange about recording in three through the 192 00:10:37,000 --> 00:10:40,640 Speaker 1: magic podcast editing is we made a prediction on this 193 00:10:40,679 --> 00:10:44,160 Speaker 1: show that is coming to pass. I would say this 194 00:10:44,240 --> 00:10:47,959 Speaker 1: lends a conversation. The reason I think it lends itself 195 00:10:48,000 --> 00:10:51,760 Speaker 1: to a larger conversation. Whatever no pun left behind is 196 00:10:51,800 --> 00:10:56,160 Speaker 1: because um, it's part of this bigger ce change. You 197 00:10:56,200 --> 00:10:59,280 Speaker 1: could go to stuff like sas book dot com right with. 198 00:10:59,320 --> 00:11:02,640 Speaker 1: The prediction we made was that eventually a I will 199 00:11:02,640 --> 00:11:06,640 Speaker 1: have the ability to make bespoke film for you. Put 200 00:11:06,679 --> 00:11:09,360 Speaker 1: in your favorite stars or your name or anyone with 201 00:11:09,480 --> 00:11:12,439 Speaker 1: enough audio footage, visual footage, and boom, it will make 202 00:11:12,440 --> 00:11:14,880 Speaker 1: a movie. I just tried sas book and put in 203 00:11:14,920 --> 00:11:17,000 Speaker 1: stuff they don't want you to know a podcast episode, 204 00:11:17,200 --> 00:11:19,480 Speaker 1: and they gave us the sentence. The first day of 205 00:11:19,520 --> 00:11:22,679 Speaker 1: my trial, the judge, a man named Mr D, asked 206 00:11:22,679 --> 00:11:25,520 Speaker 1: me a series of questions about the events surrounding my birth. 207 00:11:25,920 --> 00:11:28,040 Speaker 1: He was the first of many I guess who had 208 00:11:28,080 --> 00:11:32,520 Speaker 1: been in the room. Weird but coherent and coherent and 209 00:11:32,640 --> 00:11:35,200 Speaker 1: weirdly on brand in terms of the voice of the 210 00:11:35,240 --> 00:11:37,199 Speaker 1: way we might set up a topic, you know what 211 00:11:37,240 --> 00:11:39,400 Speaker 1: I mean. And we also I think we've we've made 212 00:11:39,480 --> 00:11:41,679 Speaker 1: no secrets about the fact that even our company has 213 00:11:41,720 --> 00:11:45,160 Speaker 1: participated and you know we we we will pilot or 214 00:11:45,200 --> 00:11:49,440 Speaker 1: you know, um invest in kind of technology or technological companies, 215 00:11:49,480 --> 00:11:52,000 Speaker 1: and we've talked about how we participated in a pilot 216 00:11:52,000 --> 00:11:56,160 Speaker 1: program to kind of create um AI versions of our voices. 217 00:11:56,200 --> 00:11:58,199 Speaker 1: And the goal there is to make it where we 218 00:11:58,240 --> 00:12:00,880 Speaker 1: don't have to do a million iteration and ad reads. 219 00:12:01,000 --> 00:12:03,720 Speaker 1: Right this this app or whatever it is, can you know, 220 00:12:03,800 --> 00:12:06,960 Speaker 1: create those for us or GEO target them by feeding 221 00:12:07,000 --> 00:12:08,160 Speaker 1: We had to feed it like we had to do 222 00:12:08,200 --> 00:12:10,319 Speaker 1: a bunch of reads and and feed it this this 223 00:12:10,400 --> 00:12:14,320 Speaker 1: voice data. Um we we can also translate into a 224 00:12:14,320 --> 00:12:17,120 Speaker 1: bunch of languages and make us sound like we speak 225 00:12:17,160 --> 00:12:22,080 Speaker 1: those languages, but imperfectly perfectly. If you know Spanish, the 226 00:12:22,120 --> 00:12:24,560 Speaker 1: idioms are off, well, of course they're gonna be off 227 00:12:24,600 --> 00:12:28,720 Speaker 1: because we're making references and speaking in parlance that is 228 00:12:28,800 --> 00:12:32,160 Speaker 1: that is very specifically American, you know, slang and all 229 00:12:32,200 --> 00:12:35,520 Speaker 1: that stuff. And without a really robust AI they can 230 00:12:35,600 --> 00:12:37,920 Speaker 1: kind of you know, kind of flip those things and 231 00:12:37,920 --> 00:12:42,280 Speaker 1: and uh tetris them into a different format. It's gonna 232 00:12:42,320 --> 00:12:44,440 Speaker 1: be weird. You know. It might get the job done 233 00:12:44,480 --> 00:12:48,160 Speaker 1: and sound to the untrained ear like, okay, that's legit, 234 00:12:48,240 --> 00:12:50,760 Speaker 1: but if you're really a native Spanish speaker, it's gonna 235 00:12:50,800 --> 00:12:54,000 Speaker 1: be super awkward. And uh it required us to kind 236 00:12:54,000 --> 00:12:55,559 Speaker 1: of go back to the drawer. Are you know, bosses 237 00:12:55,559 --> 00:12:57,839 Speaker 1: and whomever is kind of you know, behind the scenes 238 00:12:57,840 --> 00:12:59,480 Speaker 1: of this stuff to go back to the drawing board 239 00:12:59,600 --> 00:13:02,600 Speaker 1: and figure you're out ways to make that stuff more unbelievable. 240 00:13:02,880 --> 00:13:07,120 Speaker 1: Um So, so what exactly is Lensa doing and how 241 00:13:07,120 --> 00:13:09,480 Speaker 1: long has it been around. It's surprisingly it's been around 242 00:13:09,520 --> 00:13:11,839 Speaker 1: since two thousand and eighteen, they say. The company says, 243 00:13:11,880 --> 00:13:15,600 Speaker 1: there's a really good Mashable article by Mera uh nov 244 00:13:15,960 --> 00:13:21,240 Speaker 1: lock Up from earlier this month about this and um 245 00:13:21,400 --> 00:13:23,480 Speaker 1: one thing that you could also do. It's interesting in 246 00:13:23,480 --> 00:13:25,800 Speaker 1: this is you can change your gender. You can you 247 00:13:25,840 --> 00:13:28,160 Speaker 1: can change you can put in you know, female, male 248 00:13:28,400 --> 00:13:30,319 Speaker 1: or other, which I'm not sure kind of what that 249 00:13:30,640 --> 00:13:32,679 Speaker 1: encompasses that I didn't do that, but I have seen 250 00:13:32,800 --> 00:13:35,960 Speaker 1: you know, friends who are in the trans community, you know, 251 00:13:36,120 --> 00:13:38,640 Speaker 1: doing it. For their gender of choice and making these 252 00:13:38,679 --> 00:13:42,160 Speaker 1: like anime elaborate like God, I wish I was that 253 00:13:42,440 --> 00:13:44,520 Speaker 1: I looked like that, you know, And and that's the 254 00:13:44,520 --> 00:13:48,240 Speaker 1: case for you know, any gender. It's all very hyper 255 00:13:49,000 --> 00:13:53,800 Speaker 1: um stylized and hyper kind of like hot, you know. No, 256 00:13:54,120 --> 00:13:58,360 Speaker 1: you said you had to upload like ten or more. Yeah, 257 00:13:58,679 --> 00:14:01,480 Speaker 1: what does the company do with those images and the 258 00:14:01,640 --> 00:14:08,600 Speaker 1: like face data that they create? You have the yeah, yeah, 259 00:14:08,800 --> 00:14:10,920 Speaker 1: And the thing is, though, I mean, you could make 260 00:14:10,960 --> 00:14:13,520 Speaker 1: the argument that it doesn't need you to give it 261 00:14:13,559 --> 00:14:16,920 Speaker 1: to them directly. We know about these scrapers and things, 262 00:14:16,960 --> 00:14:19,280 Speaker 1: you know, how much information we just willingly to shove 263 00:14:19,320 --> 00:14:21,760 Speaker 1: out onto the internet. Um, if you google any of 264 00:14:21,800 --> 00:14:24,760 Speaker 1: our names, you're gonna find probably about ten pictures easily, 265 00:14:24,920 --> 00:14:27,720 Speaker 1: you know that could be used to feed this machine. 266 00:14:28,080 --> 00:14:31,640 Speaker 1: Maybe because we're public, you know whatever, figures for lack 267 00:14:31,680 --> 00:14:34,640 Speaker 1: of a better way of describing it, maybe there's more 268 00:14:34,760 --> 00:14:37,080 Speaker 1: than an average person. But honestly, even an average person, 269 00:14:37,560 --> 00:14:41,200 Speaker 1: Facebook isn't like private exactly unless you go through a 270 00:14:41,200 --> 00:14:43,840 Speaker 1: lot of steps to to completely make it private. And 271 00:14:43,840 --> 00:14:47,440 Speaker 1: even then, I am pretty skeptical as to you know this, 272 00:14:47,640 --> 00:14:50,560 Speaker 1: these things not being available to the right kind of scraper, 273 00:14:50,600 --> 00:14:54,040 Speaker 1: which is just an app that goes and just gathers, gathers, 274 00:14:54,080 --> 00:14:58,760 Speaker 1: gathers all this available data images, um little whatever tidbits 275 00:14:58,760 --> 00:15:01,920 Speaker 1: off the internet. Right Yeah, I'd like to also shout 276 00:15:01,960 --> 00:15:07,680 Speaker 1: out uh the Australian artist Kim Lutwiler. I believe she's 277 00:15:07,680 --> 00:15:11,400 Speaker 1: been making rounds in the Guardian because she had and 278 00:15:11,720 --> 00:15:16,160 Speaker 1: several science outfits. She had seen the styles of artists 279 00:15:16,160 --> 00:15:19,720 Speaker 1: in her community and her own style being used heavily 280 00:15:20,080 --> 00:15:23,160 Speaker 1: and lends a portraits. And the question is are those 281 00:15:23,240 --> 00:15:28,160 Speaker 1: artists being compensated? The answer is is no. And it's 282 00:15:28,200 --> 00:15:30,920 Speaker 1: so insidious, man. It goes back to like my Space 283 00:15:31,000 --> 00:15:38,000 Speaker 1: quizzes and Facebook quizzes, people are obsessively fascinated with themselves, right, 284 00:15:38,120 --> 00:15:41,520 Speaker 1: tell me more about me, show me more about myself. 285 00:15:41,520 --> 00:15:44,680 Speaker 1: There's nothing inherently wrong with that, but it tricks people 286 00:15:44,720 --> 00:15:48,240 Speaker 1: into giving away things that they might not have given 287 00:15:48,240 --> 00:15:51,480 Speaker 1: away if they had, you know, less obtuse terms of 288 00:15:51,520 --> 00:15:56,080 Speaker 1: service or clear explanations. And as you pointed out, we're 289 00:15:56,080 --> 00:16:01,400 Speaker 1: already a bridge too far, we I. It's the equivalent 290 00:16:01,440 --> 00:16:03,560 Speaker 1: of having face tattoos, you know, we have. We have 291 00:16:03,600 --> 00:16:07,560 Speaker 1: irreparably entered the public sphere. For better or worse, you know, 292 00:16:07,680 --> 00:16:11,760 Speaker 1: so learn from learn from us, right, Yeah, And to 293 00:16:12,360 --> 00:16:15,480 Speaker 1: to the previous point about the corporate side of this thing, 294 00:16:15,560 --> 00:16:17,920 Speaker 1: we know AI is being used to generate kind of 295 00:16:17,920 --> 00:16:21,480 Speaker 1: stock images. You know. Um, that's a really great use 296 00:16:21,520 --> 00:16:23,600 Speaker 1: of this. Instead of having to set up a photo shoot, 297 00:16:23,800 --> 00:16:26,160 Speaker 1: you can just you know, use this data that people 298 00:16:26,200 --> 00:16:29,560 Speaker 1: are feeding you to create guy with golf club, you know, 299 00:16:29,680 --> 00:16:32,000 Speaker 1: and cup of coffee or whatever it might be that 300 00:16:32,080 --> 00:16:34,120 Speaker 1: you need. And then it's gonna be a lot cheaper 301 00:16:34,120 --> 00:16:36,480 Speaker 1: than having to license like a Getty image or even 302 00:16:36,560 --> 00:16:39,520 Speaker 1: like what shutter stock or any of these kind of 303 00:16:39,560 --> 00:16:43,040 Speaker 1: like you know, um uh, subscription based services where you 304 00:16:43,040 --> 00:16:45,600 Speaker 1: can use these images, and there are terms of services 305 00:16:45,640 --> 00:16:47,880 Speaker 1: that you you know, have to stick to in terms 306 00:16:47,880 --> 00:16:50,200 Speaker 1: of how you can use it in commercial work or 307 00:16:50,240 --> 00:16:54,520 Speaker 1: what blah blah blah whatever. So lends A claims they 308 00:16:54,520 --> 00:16:59,480 Speaker 1: don't retain this face data. Um, but you know we've 309 00:16:59,480 --> 00:17:03,680 Speaker 1: heard that for And there is an email privacy at 310 00:17:03,800 --> 00:17:08,040 Speaker 1: lensa dash ai dot com where you can request they 311 00:17:08,080 --> 00:17:11,239 Speaker 1: delete all your personal data. But it is kind of 312 00:17:11,240 --> 00:17:17,480 Speaker 1: that like opt out thing again as opposed to giving permission. Um. 313 00:17:17,520 --> 00:17:20,800 Speaker 1: But it's that shiny new object that makes everyone so excited. 314 00:17:20,880 --> 00:17:23,520 Speaker 1: They don't bother reading the terms of use because they 315 00:17:23,560 --> 00:17:26,520 Speaker 1: want their pretty picture, you know, they want their magic 316 00:17:26,600 --> 00:17:30,480 Speaker 1: avatar or whatever. Um and Lessens made no mistake at 317 00:17:30,480 --> 00:17:33,879 Speaker 1: the very least, even if they're not retaining our actual data. 318 00:17:34,359 --> 00:17:39,440 Speaker 1: We are training their AI. We are training this algorithm 319 00:17:39,480 --> 00:17:42,480 Speaker 1: that they have to be the best at this because 320 00:17:42,520 --> 00:17:45,040 Speaker 1: the more data you feed these things, that's how it works. 321 00:17:45,320 --> 00:17:46,720 Speaker 1: That's why it was such a big deal, like in 322 00:17:46,840 --> 00:17:49,440 Speaker 1: one of the Batman movies where they turned every cell 323 00:17:49,480 --> 00:17:51,960 Speaker 1: phone in the world into a microphone or something like that. 324 00:17:52,320 --> 00:17:54,960 Speaker 1: And yeah, and that's what we also here get and 325 00:17:54,960 --> 00:17:58,120 Speaker 1: and worry about with things like alexa um that it's 326 00:17:58,119 --> 00:18:00,520 Speaker 1: when it's listening and what happens to that data, whether 327 00:18:00,560 --> 00:18:03,600 Speaker 1: it retains that are not in some sort of permanent way. 328 00:18:03,640 --> 00:18:06,919 Speaker 1: You are training it to be better to do, to 329 00:18:06,960 --> 00:18:10,359 Speaker 1: be a better AI. UM And back to Nick again. 330 00:18:11,000 --> 00:18:13,040 Speaker 1: Nick does a lot of art for the hip hop 331 00:18:13,080 --> 00:18:15,800 Speaker 1: group Run the Jewels, and when he first got mid Journey, 332 00:18:15,840 --> 00:18:19,760 Speaker 1: he typed in like Killer Mike animated portrait or Killer 333 00:18:19,800 --> 00:18:21,359 Speaker 1: Mike kind of start whatever you I don't remember, I 334 00:18:21,400 --> 00:18:23,800 Speaker 1: don't know the exact text, but when it spit out 335 00:18:24,400 --> 00:18:27,080 Speaker 1: looked a hell of a lot like one of Nick's pieces, 336 00:18:27,600 --> 00:18:31,320 Speaker 1: which exists on the internet, um, you know, in marketing 337 00:18:31,320 --> 00:18:34,399 Speaker 1: materials for Run the Jewels. So it is using the 338 00:18:34,560 --> 00:18:37,600 Speaker 1: work of artists that already is out there to feed 339 00:18:37,680 --> 00:18:42,560 Speaker 1: this algorithm, and it is using our faces, you know, 340 00:18:42,640 --> 00:18:45,280 Speaker 1: to to to create a better algorithm to make kind 341 00:18:45,280 --> 00:18:48,200 Speaker 1: of fake faces. And you said you have to pay 342 00:18:48,240 --> 00:18:50,560 Speaker 1: for this opera. It's free. That's the beauty of it, mean, 343 00:18:50,640 --> 00:18:53,320 Speaker 1: the duty in terms of on their end, yeah, because 344 00:18:53,320 --> 00:18:55,840 Speaker 1: it looks so good, they figured, well, hell we can, 345 00:18:55,920 --> 00:18:57,800 Speaker 1: we can convince people to pay a couple of bucks 346 00:18:57,800 --> 00:18:59,920 Speaker 1: for this. I sure did. I paid for it three time. 347 00:19:00,040 --> 00:19:02,000 Speaker 1: Is one for myself, one for my kid, and one 348 00:19:02,119 --> 00:19:06,760 Speaker 1: from my h my kid's mom. So they are associating 349 00:19:06,880 --> 00:19:10,960 Speaker 1: your face with an account with a credit card, likely 350 00:19:11,119 --> 00:19:14,000 Speaker 1: that you use the thing. Like I said, I'm a big, 351 00:19:14,040 --> 00:19:16,840 Speaker 1: giant sucker. Which is why I think I'm the perfect 352 00:19:16,840 --> 00:19:19,639 Speaker 1: person to bring the story, you know, to you, because 353 00:19:19,680 --> 00:19:21,879 Speaker 1: I was had. And again I've I've mentioned this in 354 00:19:21,880 --> 00:19:26,439 Speaker 1: the past, like do I really care that much? I 355 00:19:26,440 --> 00:19:29,040 Speaker 1: think I'm maybe starting to a little more now that 356 00:19:29,080 --> 00:19:31,560 Speaker 1: I understand kind of more the big picture of this 357 00:19:31,640 --> 00:19:34,560 Speaker 1: and how my my face or my kid's face or 358 00:19:34,640 --> 00:19:36,640 Speaker 1: some fact similar of it could end up in an 359 00:19:36,640 --> 00:19:41,320 Speaker 1: advertisement without my permission or without any um, you know, 360 00:19:41,440 --> 00:19:44,840 Speaker 1: legal recourse. Uh, And that's the future we're heading towards. 361 00:19:44,880 --> 00:19:48,080 Speaker 1: But also, like, just by virtue of being on the Internet, 362 00:19:48,160 --> 00:19:50,600 Speaker 1: I think these algorithms are getting fed whether we you know, 363 00:19:50,720 --> 00:19:53,560 Speaker 1: do it willingly or not. So it's sort of like 364 00:19:53,640 --> 00:19:56,760 Speaker 1: a you know, dann if you do danned if you 365 00:19:56,800 --> 00:19:58,560 Speaker 1: don't kind of situations. So why not just get the 366 00:19:58,560 --> 00:20:01,879 Speaker 1: pretty picture? But may me I'm being naive there, but 367 00:20:02,040 --> 00:20:04,639 Speaker 1: I do, I do understand the future we're heading for. 368 00:20:04,760 --> 00:20:06,600 Speaker 1: I just would like, do I really have a choice? 369 00:20:06,600 --> 00:20:08,520 Speaker 1: So why not just enjoy the ride? I guess. So 370 00:20:08,920 --> 00:20:11,720 Speaker 1: lots more to come with this kind of tech and 371 00:20:11,920 --> 00:20:14,520 Speaker 1: uh the lens app and whatever the next gen version 372 00:20:14,520 --> 00:20:17,040 Speaker 1: of it might be. And UM starting to see the 373 00:20:17,040 --> 00:20:20,680 Speaker 1: way advertising starts to kind of evolve because of these algorithms. 374 00:20:20,960 --> 00:20:22,480 Speaker 1: Because I don't want to freak us out and do 375 00:20:22,520 --> 00:20:25,159 Speaker 1: it too quickly, but it's it's inevitable. So let's take 376 00:20:25,200 --> 00:20:27,880 Speaker 1: a quick break. Here a word from our sponsor, UM, 377 00:20:27,920 --> 00:20:30,240 Speaker 1: possibly with robot voices, because that's definitely a thing that's 378 00:20:30,280 --> 00:20:33,240 Speaker 1: being used in ad reads nowadays too, by the way, Uh, 379 00:20:33,240 --> 00:20:36,200 Speaker 1: and you can usually sort of tell, but it's gonna 380 00:20:36,200 --> 00:20:38,160 Speaker 1: come a point where you can't, and then we'll be back. 381 00:20:44,960 --> 00:20:47,960 Speaker 1: All right, we're back, and we're gonna talk about fire 382 00:20:48,040 --> 00:20:50,840 Speaker 1: really quickly. I'm doing the super fast guys. Uh. Speaking 383 00:20:50,840 --> 00:20:53,359 Speaker 1: of fire, I want to call out my friend Robert 384 00:20:53,400 --> 00:20:59,720 Speaker 1: Jabrie Brown uh slash uh st x pre slash Prefontaine slash. 385 00:21:00,080 --> 00:21:02,480 Speaker 1: There's so many ways you might know him on the 386 00:21:02,480 --> 00:21:05,200 Speaker 1: the old Internet. Just want to shout him out really quickly. 387 00:21:05,359 --> 00:21:07,720 Speaker 1: He had a video come out for a new song 388 00:21:07,840 --> 00:21:10,520 Speaker 1: not long ago. I just want everyone who's out there 389 00:21:10,800 --> 00:21:14,440 Speaker 1: to search YouTube for Robert Jabris r O B E 390 00:21:14,720 --> 00:21:18,520 Speaker 1: R T J A B R E. Search for I'm 391 00:21:18,720 --> 00:21:22,480 Speaker 1: capital I apostrophe M. Check out that video. It's just 392 00:21:22,520 --> 00:21:24,679 Speaker 1: one of the coolest songs I've heard him doing a 393 00:21:24,680 --> 00:21:28,240 Speaker 1: long time. He's gonna He's an incredible artist who creates music. 394 00:21:28,840 --> 00:21:33,640 Speaker 1: Um oh, left hand is good too, that's all. He's 395 00:21:33,680 --> 00:21:37,040 Speaker 1: got a ton of great music out there. Search Robert Jabris. 396 00:21:37,400 --> 00:21:39,120 Speaker 1: He also did a couple of videos that you had 397 00:21:39,160 --> 00:21:41,840 Speaker 1: something to do with Matt. There's one called stuff that 398 00:21:41,960 --> 00:21:44,480 Speaker 1: he did with beats there with participation from one of 399 00:21:44,480 --> 00:21:47,840 Speaker 1: my favorite kind of electronic weird jazzy sample head guys 400 00:21:47,920 --> 00:21:51,000 Speaker 1: named a'man Tobin for Ninja tune. Um. And it's a 401 00:21:51,080 --> 00:21:54,320 Speaker 1: really badass Kung Fu theme video that you and your 402 00:21:54,359 --> 00:21:57,880 Speaker 1: your homies had a big, big hand in. Yes, Chandler Maze, 403 00:21:57,920 --> 00:22:02,680 Speaker 1: Tyler Clang, Casey Pigram and right Elephant. Anyway, just shouting 404 00:22:02,680 --> 00:22:06,640 Speaker 1: out you Robert Debris. Uh, everybody go check him out. Okay, 405 00:22:06,640 --> 00:22:09,640 Speaker 1: here we go now, speaking of other fires, massive fires, 406 00:22:10,000 --> 00:22:14,320 Speaker 1: there was one in the neighborhood of Red Hook in Brooklyn, 407 00:22:14,320 --> 00:22:17,200 Speaker 1: New York. I wasn't really sure where this was, guys, 408 00:22:17,200 --> 00:22:18,960 Speaker 1: so I had to go to Google Maps. I posted 409 00:22:18,960 --> 00:22:21,600 Speaker 1: a link in there if you want to check it out. Um. 410 00:22:21,680 --> 00:22:27,200 Speaker 1: This is a huge, huge warehouse on Columbia Street. And 411 00:22:27,720 --> 00:22:31,720 Speaker 1: one of the things that this warehouse houses, because it's 412 00:22:31,760 --> 00:22:34,080 Speaker 1: not this isn't the only thing in that warehouse, but 413 00:22:34,400 --> 00:22:36,320 Speaker 1: one of the things that it houses is the eerie 414 00:22:36,440 --> 00:22:40,520 Speaker 1: basin auto pound. Guys, when is the last time you 415 00:22:40,600 --> 00:22:43,760 Speaker 1: remember hearing the phrase going too the pound or taking 416 00:22:44,560 --> 00:22:47,000 Speaker 1: You're gonna take a car to the pound, or you 417 00:22:47,000 --> 00:22:50,920 Speaker 1: gotta go to the pound? Right in pounding a car right. 418 00:22:51,280 --> 00:22:55,399 Speaker 1: Uh yeah, this is uh just for perspective on the 419 00:22:55,520 --> 00:22:59,720 Speaker 1: road a while back for recorded and on a video 420 00:23:00,000 --> 00:23:03,680 Speaker 1: all with you, Matt, where I said, did you hear 421 00:23:03,720 --> 00:23:07,320 Speaker 1: about the fire? And um, it's it's strange because we 422 00:23:07,359 --> 00:23:12,480 Speaker 1: are constantly in contact about things that go on and 423 00:23:12,680 --> 00:23:16,919 Speaker 1: this sent me down a rabbit hole instantly. Yeah, it was. 424 00:23:17,000 --> 00:23:18,560 Speaker 1: It was a bummer to be on the rest of 425 00:23:18,560 --> 00:23:21,399 Speaker 1: the call. And uh, you know, I'm I'm I'm a 426 00:23:21,600 --> 00:23:25,119 Speaker 1: pretty great listener, but I was uphill for that one. Well, 427 00:23:25,359 --> 00:23:27,520 Speaker 1: nobody on that call, most of whom were in New 428 00:23:27,600 --> 00:23:30,280 Speaker 1: York by the way and in Manhattan, had heard about 429 00:23:30,280 --> 00:23:34,000 Speaker 1: this fire, had seen this fire. Even though the blaze 430 00:23:34,080 --> 00:23:36,960 Speaker 1: was so huge, A lot of New Yorkers who did 431 00:23:37,000 --> 00:23:40,080 Speaker 1: get to see the black smoke arising from Red Hook 432 00:23:40,119 --> 00:23:42,480 Speaker 1: in that area over in Brooklyn, they thought it had 433 00:23:42,520 --> 00:23:45,280 Speaker 1: started on Manhattan because there was so much black smoke 434 00:23:45,680 --> 00:23:49,600 Speaker 1: just pouring over the area. Well, here's why this fire 435 00:23:49,640 --> 00:23:53,240 Speaker 1: is important, why we're talking about it. This facility, this 436 00:23:53,320 --> 00:23:56,919 Speaker 1: pound held a lot of evidence, including cars like you 437 00:23:56,960 --> 00:23:59,960 Speaker 1: would you know, get impounded for that kind of evidence, 438 00:24:00,240 --> 00:24:05,200 Speaker 1: other vehicles. It also held a ton of DNA evidence, 439 00:24:05,680 --> 00:24:13,480 Speaker 1: historical NYPD DNA evidence. Um, oh yeah, decades and decades 440 00:24:13,840 --> 00:24:16,359 Speaker 1: and it was all just in this huge warehouse stored 441 00:24:16,400 --> 00:24:19,680 Speaker 1: away and when this fire occurred. This information is coming 442 00:24:19,760 --> 00:24:25,040 Speaker 1: from December two, by the way, so that's that's when 443 00:24:25,240 --> 00:24:29,520 Speaker 1: the fire occurred. And um that's that's the best information 444 00:24:29,560 --> 00:24:31,040 Speaker 1: we have right now. There haven't been a ton of 445 00:24:31,119 --> 00:24:34,119 Speaker 1: updates about this. All the news was just trying to 446 00:24:34,160 --> 00:24:37,800 Speaker 1: assess how much damage was done to you know, that 447 00:24:37,960 --> 00:24:40,800 Speaker 1: store of DNA and that store of evidence that could 448 00:24:41,359 --> 00:24:45,280 Speaker 1: potentially in some way affect a new case or a 449 00:24:45,320 --> 00:24:48,800 Speaker 1: current case, but mostly it's just affecting older cases, especially 450 00:24:48,840 --> 00:24:52,719 Speaker 1: cold cases, and that doesn't bode well for you know, 451 00:24:53,200 --> 00:24:57,480 Speaker 1: New Yorkers or law enforcement in general. It's terrible too, 452 00:24:57,560 --> 00:25:00,800 Speaker 1: because you know, this is coming on the heels of 453 00:25:01,560 --> 00:25:07,520 Speaker 1: the ongoing COVID pandemic, right or whatever new diseases will 454 00:25:07,560 --> 00:25:12,080 Speaker 1: get published in three So the judicial system already slowed 455 00:25:12,119 --> 00:25:16,240 Speaker 1: to a crawl, right even so, you know, the backlog 456 00:25:16,320 --> 00:25:21,640 Speaker 1: problem has increased by an order of magnitude. But uh, Matt, 457 00:25:21,680 --> 00:25:24,000 Speaker 1: I think I'm speaking for a lot of our fellow 458 00:25:24,040 --> 00:25:29,000 Speaker 1: conspiracy realists here when we say, what's the official explanation 459 00:25:29,160 --> 00:25:33,560 Speaker 1: for the fire, and do you think it is legit? Well, 460 00:25:33,600 --> 00:25:35,720 Speaker 1: you know, I maybe offer right now because I'm speaking 461 00:25:35,760 --> 00:25:40,640 Speaker 1: to you from information from December. At that time, it 462 00:25:40,760 --> 00:25:45,040 Speaker 1: was unknown what sparked the fire. There is one section 463 00:25:45,160 --> 00:25:48,360 Speaker 1: of this huge warehouse that did collapse or did fall 464 00:25:48,520 --> 00:25:51,719 Speaker 1: The top fell in, and underneath that section there were 465 00:25:51,760 --> 00:25:54,240 Speaker 1: a bunch of um if they call him e bikes, 466 00:25:54,720 --> 00:25:57,720 Speaker 1: I'm assuming it's the kind of like bikes you can rent, 467 00:25:57,800 --> 00:26:02,040 Speaker 1: you know, around the city that get recharged and everything. Um, 468 00:26:02,200 --> 00:26:04,040 Speaker 1: they're unsure if that had anything to do with it. 469 00:26:04,560 --> 00:26:09,359 Speaker 1: There's so Marias perhaps Yeah, there's a potential for that, right. Um, 470 00:26:09,400 --> 00:26:13,200 Speaker 1: there was so much combustible material within that large warehouse 471 00:26:13,240 --> 00:26:15,800 Speaker 1: that they were unsure at the time what started it. 472 00:26:16,320 --> 00:26:19,240 Speaker 1: There were six first responders and two civilians that got 473 00:26:19,280 --> 00:26:21,560 Speaker 1: hurt trying to fight this thing and get away from 474 00:26:21,560 --> 00:26:25,560 Speaker 1: this fire. Um. So it was really big and very 475 00:26:25,600 --> 00:26:30,520 Speaker 1: hot obviously. Um, so it's just unknown. Do you have 476 00:26:30,600 --> 00:26:35,920 Speaker 1: a newer information. Uh, we hopefully we will have newer 477 00:26:35,960 --> 00:26:40,439 Speaker 1: information by the time this comes out, but we really 478 00:26:40,440 --> 00:26:42,440 Speaker 1: don't know. One thing that stood out to me, Matt 479 00:26:42,560 --> 00:26:45,600 Speaker 1: after again, I learned this from you. Uh, they learned 480 00:26:45,600 --> 00:26:49,880 Speaker 1: from watching you um, I read in uh, I read 481 00:26:49,920 --> 00:26:54,840 Speaker 1: a statement from the Arson and Explosions squads. Some of 482 00:26:54,840 --> 00:26:58,240 Speaker 1: those first responders you're talking about, uh, and the the 483 00:26:58,320 --> 00:27:03,160 Speaker 1: firefighter chief, a guy named John Hodgens, said the fire 484 00:27:03,240 --> 00:27:06,400 Speaker 1: is likely to burn for a few days. Yeah, when 485 00:27:06,400 --> 00:27:10,000 Speaker 1: it was occurring. Bit of a las fair attitude to 486 00:27:10,080 --> 00:27:14,160 Speaker 1: take towards a structure fire in such a densely populated city. 487 00:27:14,440 --> 00:27:17,080 Speaker 1: Oh yeah, Well, the good I mean, the only good 488 00:27:17,119 --> 00:27:19,840 Speaker 1: thing is that it's on the waterfront. When it comes 489 00:27:19,880 --> 00:27:22,600 Speaker 1: to you know, endangering a lot of other human beings. 490 00:27:22,960 --> 00:27:25,520 Speaker 1: There are a lot of businesses that exist there, like 491 00:27:25,560 --> 00:27:27,480 Speaker 1: on a it almost looks like a pier in a 492 00:27:27,480 --> 00:27:29,600 Speaker 1: couple of areas or just right on you know the 493 00:27:29,600 --> 00:27:33,960 Speaker 1: water there. Um, those were probably in danger. The NYPD 494 00:27:34,080 --> 00:27:37,040 Speaker 1: Chief Joseph Majori said, this is a very serious and 495 00:27:37,119 --> 00:27:40,000 Speaker 1: damaging fire. We don't know the magnitude until we see 496 00:27:40,000 --> 00:27:42,520 Speaker 1: the invoice to see what was in there and see 497 00:27:42,520 --> 00:27:45,760 Speaker 1: what we can salvage. So it's literally like, oh man, 498 00:27:45,840 --> 00:27:47,720 Speaker 1: we because this was all happening in the moment, we 499 00:27:47,800 --> 00:27:50,400 Speaker 1: got to look back see the inventory and then we'll 500 00:27:50,440 --> 00:27:53,199 Speaker 1: figure out how much of it is lost. Because they 501 00:27:53,200 --> 00:27:58,720 Speaker 1: were saying that most of the contents within are probably 502 00:27:58,800 --> 00:28:02,680 Speaker 1: damaged at least damaged, right right, Yeah, and there was 503 00:28:02,720 --> 00:28:07,760 Speaker 1: also this ongoing, uh, concern about people on motorbikes. Right, 504 00:28:07,800 --> 00:28:10,399 Speaker 1: so a lot of a lot of dirt bikes got confiscated. 505 00:28:10,520 --> 00:28:15,159 Speaker 1: A t V s um. Yeah, it's just it instantly sets. 506 00:28:15,240 --> 00:28:21,040 Speaker 1: It could totally be um and innocuous, accidental and tragic fire. 507 00:28:21,440 --> 00:28:26,560 Speaker 1: But also we without alleging conspiracy at this point, we 508 00:28:26,720 --> 00:28:30,280 Speaker 1: have to say it, Uh, there are a couple of 509 00:28:30,320 --> 00:28:32,760 Speaker 1: people who are probably going to get away with some stuff, 510 00:28:32,760 --> 00:28:36,320 Speaker 1: now right, Well, I was gonna ask Matt, I'm picturing, 511 00:28:36,400 --> 00:28:38,840 Speaker 1: you know, and when I'm thinking about these samples being 512 00:28:38,880 --> 00:28:43,560 Speaker 1: stored some sort of cryogenic you know, warehouse of like 513 00:28:43,680 --> 00:28:48,120 Speaker 1: you know, like like dry ice steam kind of share 514 00:28:48,240 --> 00:28:53,360 Speaker 1: lock kind of sitch, I'm assuming that's completely You're you're 515 00:28:53,400 --> 00:28:55,760 Speaker 1: taught each one of not each one of these things. 516 00:28:56,480 --> 00:29:01,280 Speaker 1: The evidence was stored in these big cardboard containers. They 517 00:29:01,320 --> 00:29:04,800 Speaker 1: refer to them as cardboard barrels, which I just don't 518 00:29:04,960 --> 00:29:10,560 Speaker 1: really like that description, but their their car cardboard containers 519 00:29:10,600 --> 00:29:14,880 Speaker 1: of some sort. And when there's fire and you've got cardboard, yeah, 520 00:29:15,960 --> 00:29:20,680 Speaker 1: it becomes fuel and the batteries and uh, any gas 521 00:29:20,680 --> 00:29:23,200 Speaker 1: in the tanks of some of these bikes, which of 522 00:29:23,280 --> 00:29:29,640 Speaker 1: which they're hundreds and hundreds. Also, no sprinklers, is that 523 00:29:29,800 --> 00:29:33,200 Speaker 1: is am I to be told there are no sprinklers here. 524 00:29:33,600 --> 00:29:35,920 Speaker 1: That is a little weird. It's a huge warehouse. You 525 00:29:35,960 --> 00:29:40,160 Speaker 1: think there'll be some kind of fire prevention system, right, 526 00:29:40,280 --> 00:29:43,280 Speaker 1: you do think that's code. Other kinds of evidence in 527 00:29:43,360 --> 00:29:45,400 Speaker 1: here too, though, right, Like this is like essentially like 528 00:29:45,440 --> 00:29:48,800 Speaker 1: a giant you know, evidence storage facility, like the kind 529 00:29:48,800 --> 00:29:51,720 Speaker 1: of breaking bad that they destroyed with magnets, you know 530 00:29:51,760 --> 00:29:53,800 Speaker 1: what I mean. So it would be bagged up guns, 531 00:29:54,320 --> 00:29:57,840 Speaker 1: you know, any other kind of photographic evidence like things 532 00:29:57,880 --> 00:29:59,720 Speaker 1: like that, like all sorts, not just d n A. 533 00:30:00,200 --> 00:30:03,040 Speaker 1: It's like the layer of a dragon that collects evidence 534 00:30:03,080 --> 00:30:07,800 Speaker 1: instead of gold. But but just keep in mind most 535 00:30:07,800 --> 00:30:09,800 Speaker 1: of it, as you thinking about what you said, Ben, 536 00:30:09,840 --> 00:30:11,960 Speaker 1: somebody's gonna get away with it. Most of this stuff 537 00:30:12,040 --> 00:30:15,280 Speaker 1: is from twenty thirty years ago, most of it, right, 538 00:30:15,320 --> 00:30:18,240 Speaker 1: not all right, Um, It's definitely a place where evidence 539 00:30:18,280 --> 00:30:20,760 Speaker 1: goes to just sit and stay. It's not the active 540 00:30:20,800 --> 00:30:24,080 Speaker 1: stuff that would probably be at a prec precinct somewhere. 541 00:30:24,720 --> 00:30:27,760 Speaker 1: Last interruption, I swear, is there no good way to 542 00:30:27,920 --> 00:30:31,160 Speaker 1: quote unquote back up DNA evidence. Do you literally have 543 00:30:31,280 --> 00:30:34,560 Speaker 1: to have the material? You can't like have a record 544 00:30:34,640 --> 00:30:37,160 Speaker 1: that it existed and that be enough. You have to 545 00:30:37,200 --> 00:30:40,680 Speaker 1: have the stuff it could be I guess I I 546 00:30:40,760 --> 00:30:43,440 Speaker 1: don't know how that would work in a trial. Like 547 00:30:43,480 --> 00:30:45,600 Speaker 1: if you just said, I'm just wondering a piece of 548 00:30:45,600 --> 00:30:49,560 Speaker 1: paper that said, here's the d NA, here's a picture 549 00:30:49,760 --> 00:30:52,880 Speaker 1: of what it looks like. Uh, here's a picture of 550 00:30:53,400 --> 00:30:56,640 Speaker 1: years ago, even still be viable to test again, would 551 00:30:56,640 --> 00:30:59,120 Speaker 1: it still have all the juice that you need? It's 552 00:30:59,120 --> 00:31:01,360 Speaker 1: a good question. I mean, we know that there is 553 00:31:01,400 --> 00:31:06,160 Speaker 1: the capacity to store digital uh data wait in d 554 00:31:06,320 --> 00:31:08,920 Speaker 1: n A. That's something a little bit different. But I wonder, 555 00:31:09,280 --> 00:31:12,240 Speaker 1: you know, given the technological lag that a lot of 556 00:31:12,440 --> 00:31:18,280 Speaker 1: authorities face and right the backlogs, the lag they might 557 00:31:18,320 --> 00:31:22,600 Speaker 1: not have, you know, the bleeding edge testing and storage techniques, 558 00:31:23,160 --> 00:31:25,760 Speaker 1: um and which is not a ding on them. You know, 559 00:31:25,840 --> 00:31:30,400 Speaker 1: I'm sure that everybody working in that capacity wants the latest, safest, 560 00:31:30,800 --> 00:31:34,480 Speaker 1: most accurate, reliable stuff, but sometimes the budget is just 561 00:31:34,600 --> 00:31:36,840 Speaker 1: not there, and like maybe the FBI has it, but 562 00:31:36,960 --> 00:31:40,760 Speaker 1: not necessarily the NYPD. Right, Yeah, guys, it just made 563 00:31:40,800 --> 00:31:43,640 Speaker 1: me think I wonder why this doesn't happen more And 564 00:31:43,720 --> 00:31:45,480 Speaker 1: this is a kind of a scary thought to me, 565 00:31:45,760 --> 00:31:50,640 Speaker 1: but why don't evidence storages get attacked more often by 566 00:31:50,680 --> 00:31:54,400 Speaker 1: somebody who's like the associates of someone who's going to 567 00:31:54,520 --> 00:31:57,440 Speaker 1: prison or a part of a big trial. Like I'm 568 00:31:57,440 --> 00:32:00,280 Speaker 1: glad it doesn't have the attacked on Precinct third teen, 569 00:32:00,720 --> 00:32:03,400 Speaker 1: you know, where they've got high level you know mob, 570 00:32:03,560 --> 00:32:07,600 Speaker 1: you know, people in custody and they literally do a siege, 571 00:32:07,640 --> 00:32:09,840 Speaker 1: you know, on this precinct in New York is a 572 00:32:09,880 --> 00:32:13,480 Speaker 1: John Carpenter movie. And again that bit and Breaking Bad 573 00:32:13,720 --> 00:32:16,760 Speaker 1: where there's a laptop they need to erase because it's 574 00:32:16,800 --> 00:32:18,800 Speaker 1: got you know, video on it, and that that was 575 00:32:18,840 --> 00:32:21,440 Speaker 1: honestly the first time I'd ever seen and I was like, yeah, 576 00:32:21,520 --> 00:32:22,720 Speaker 1: I saw the same I saw the same thing. I 577 00:32:22,720 --> 00:32:24,320 Speaker 1: was like, how does this not happen more often? It's 578 00:32:24,360 --> 00:32:28,680 Speaker 1: kind of genius. Well, they also, I mean, you're talking 579 00:32:28,720 --> 00:32:33,560 Speaker 1: about heavy hitters right in that regard, So I imagine 580 00:32:33,720 --> 00:32:37,479 Speaker 1: the evidence is stored accordingly, and let's be honest, sometimes 581 00:32:37,480 --> 00:32:41,680 Speaker 1: stuff disappears. That is also true. Sometimes it's a conspiracy. 582 00:32:42,040 --> 00:32:48,080 Speaker 1: Sometimes it's simple human error, right because incompetence can look 583 00:32:48,120 --> 00:32:51,600 Speaker 1: like malevolence from far enough away. Uh. I just think 584 00:32:51,640 --> 00:32:53,840 Speaker 1: a lot of people who would like evidence to be 585 00:32:53,920 --> 00:32:58,560 Speaker 1: destroyed probably don't have the means to make it so, 586 00:32:58,880 --> 00:33:01,320 Speaker 1: you know. And even if it were inside job, I 587 00:33:01,360 --> 00:33:04,400 Speaker 1: think there are systems in place, you know, that monitor 588 00:33:04,440 --> 00:33:07,320 Speaker 1: the comings and goings and checkings in and out of 589 00:33:07,360 --> 00:33:09,360 Speaker 1: all this kind of stuff that it would be really 590 00:33:09,400 --> 00:33:13,720 Speaker 1: hard to completely eliminate any evidence of the thing being removed, 591 00:33:13,840 --> 00:33:17,760 Speaker 1: short of blowing up the whole facility. Yeah, no, you're right, 592 00:33:18,080 --> 00:33:20,880 Speaker 1: or just setting fire to a bunch of e bikes. Bikes. 593 00:33:22,120 --> 00:33:26,800 Speaker 1: Police police headed historic drug bust. They they found a 594 00:33:26,920 --> 00:33:31,600 Speaker 1: hundred tons of cocaine. Uh, going to trial. Uh, it 595 00:33:31,640 --> 00:33:34,560 Speaker 1: looks like the guys are going up the river for 596 00:33:35,160 --> 00:33:39,920 Speaker 1: possession of eight five tons of cocaine. And you know, 597 00:33:40,040 --> 00:33:42,760 Speaker 1: by the time it gets to the plea bargain, it's 598 00:33:43,000 --> 00:33:51,200 Speaker 1: it's about twenty tons. Still like the Irijuana in India. Obvious, Yeah, 599 00:33:51,240 --> 00:33:54,040 Speaker 1: there is. I'm obviously not a cocaine expert. I'm sure 600 00:33:54,200 --> 00:33:58,080 Speaker 1: anybody more familiar is like tons. Come on, buddy, I'm 601 00:33:58,120 --> 00:34:01,240 Speaker 1: sure it's like less than that right times feels like 602 00:34:01,280 --> 00:34:04,760 Speaker 1: hortel stuff. You think that's too much. The movies, they 603 00:34:04,840 --> 00:34:07,920 Speaker 1: usually measured in kilos. You know, that's sort of the 604 00:34:07,960 --> 00:34:11,280 Speaker 1: base level street amount that it would be a unit 605 00:34:11,400 --> 00:34:13,399 Speaker 1: of you know what I mean. Legal drugs have done 606 00:34:13,520 --> 00:34:17,400 Speaker 1: so much for Americans understanding of the metric system. What 607 00:34:17,440 --> 00:34:20,200 Speaker 1: I mean, I've I've had friends who are drug dealers, 608 00:34:20,200 --> 00:34:22,040 Speaker 1: and I've got to say, I think the statutes past 609 00:34:22,080 --> 00:34:24,000 Speaker 1: thing can say. I've got to say, you know, there 610 00:34:24,000 --> 00:34:26,640 Speaker 1: are a lot of stereotypes. Those guys are great at math, 611 00:34:27,000 --> 00:34:33,080 Speaker 1: you know, for sure, for sure? Uh wow, Hey, well, hey, 612 00:34:33,120 --> 00:34:35,040 Speaker 1: let's do one reminder and let's go to the next segment. 613 00:34:35,440 --> 00:34:38,560 Speaker 1: Whenever you've got video evidence of something, make sure you 614 00:34:38,680 --> 00:34:44,239 Speaker 1: make backups and you disperse them. Cool. All right, let's 615 00:34:44,239 --> 00:34:46,920 Speaker 1: go check. Cool, let's hear a word from our sponsor, 616 00:34:47,000 --> 00:34:56,560 Speaker 1: and we'll be right back. And we've returned. Uh. I'm 617 00:34:56,560 --> 00:34:59,839 Speaker 1: gonna have to keep this one super brief because it's 618 00:35:00,040 --> 00:35:03,399 Speaker 1: news that made the headlines. I think it will be 619 00:35:04,080 --> 00:35:06,319 Speaker 1: a future episode. It opens the door for a lot 620 00:35:06,360 --> 00:35:08,359 Speaker 1: of places. So it's a great way to end our 621 00:35:08,360 --> 00:35:15,160 Speaker 1: first strange news earlier just just quite recently. Uh, the 622 00:35:15,840 --> 00:35:24,120 Speaker 1: Lawrence Livermore National Laboratory or lonell l l l uh right, 623 00:35:24,520 --> 00:35:28,680 Speaker 1: Um just wait, uh, Little has an outfit called the 624 00:35:28,800 --> 00:35:35,279 Speaker 1: National Ignition Facility or NIFF, so little niff uh not 625 00:35:35,400 --> 00:35:38,680 Speaker 1: to be confused. Yeah, it was sound cloud er based camp. 626 00:35:38,760 --> 00:35:42,759 Speaker 1: Little Niff. Uh. Little Niff just announced that they had 627 00:35:42,840 --> 00:35:49,480 Speaker 1: made a huge breakthrough in harnessing controlled nuclear fusion, bringing 628 00:35:49,520 --> 00:35:53,960 Speaker 1: the power of the sun into the hands of humans. 629 00:35:53,960 --> 00:36:00,400 Speaker 1: How prometheyan right asterix asterick caveat uh so so like 630 00:36:00,520 --> 00:36:03,480 Speaker 1: with any story here, um, I don't know about you, guys. 631 00:36:03,480 --> 00:36:06,120 Speaker 1: A bunch of people were sending this, uh my way, 632 00:36:06,160 --> 00:36:07,560 Speaker 1: you know, what do you make of this? We saw 633 00:36:07,600 --> 00:36:09,360 Speaker 1: a post on Here's where it gets Here's where it 634 00:36:09,400 --> 00:36:12,000 Speaker 1: gets crazy, and a couple of other places. The big 635 00:36:12,120 --> 00:36:17,080 Speaker 1: question is, does this mean that humanity is on the 636 00:36:17,160 --> 00:36:22,439 Speaker 1: cusp of limitless clean power, finally finally getting ourselves off 637 00:36:22,480 --> 00:36:25,920 Speaker 1: the smack that is fossil fuel? Uh and finally, you know, 638 00:36:26,280 --> 00:36:30,160 Speaker 1: um burning fewer things right, which is already kind of 639 00:36:30,239 --> 00:36:34,000 Speaker 1: an archaic way to get energy. It just works. The 640 00:36:34,080 --> 00:36:39,320 Speaker 1: answer is no, not yet, not yet, if the official 641 00:36:39,360 --> 00:36:42,600 Speaker 1: stories are to be believed. In fact, we were talking 642 00:36:42,640 --> 00:36:46,200 Speaker 1: a little bit off air that almost as soon as 643 00:36:46,239 --> 00:36:51,440 Speaker 1: this news came out a bevy of very principled, somewhat 644 00:36:51,480 --> 00:36:56,560 Speaker 1: scandalized experts in nuclear science. We're coming out and saying, 645 00:36:56,640 --> 00:37:00,520 Speaker 1: please please stop it with these crazy headlines. We're not 646 00:37:00,640 --> 00:37:05,120 Speaker 1: the Jetsons, were not Star Trek yet. Uh. I don't know, 647 00:37:05,600 --> 00:37:07,640 Speaker 1: but this is what it made me think of, and 648 00:37:07,640 --> 00:37:09,560 Speaker 1: this is why I wanted to bring it to all 649 00:37:09,600 --> 00:37:13,160 Speaker 1: of us listening along today without getting too much into 650 00:37:13,160 --> 00:37:16,319 Speaker 1: the science, which we absolutely can do in an episode. UM, 651 00:37:16,880 --> 00:37:21,960 Speaker 1: technological suppression is real. A that's a given knowing that 652 00:37:22,280 --> 00:37:29,400 Speaker 1: is it possible that be something like this was successful already? 653 00:37:30,080 --> 00:37:34,920 Speaker 1: Is it possible? Is it plausible? Little Niff? Yeah, So 654 00:37:35,920 --> 00:37:38,080 Speaker 1: it's so funny, man, I have I have, I have 655 00:37:38,160 --> 00:37:40,799 Speaker 1: pitched work up and my tab from previous and there's 656 00:37:40,800 --> 00:37:42,600 Speaker 1: a new record who come out today from Little Simms, 657 00:37:43,080 --> 00:37:45,319 Speaker 1: which seems like a Little Niff and Little Sims could 658 00:37:45,440 --> 00:37:49,800 Speaker 1: guess in each other's records. Just put that out there. A. Yeah, 659 00:37:50,040 --> 00:37:53,200 Speaker 1: but we're talking about the fusion, like, is it possible? Ben? 660 00:37:53,280 --> 00:37:56,880 Speaker 1: I'm so sorry? Okay, Yeah, So here's simply put. The 661 00:37:57,480 --> 00:38:05,040 Speaker 1: big breakthrough is that UH, using a hundred and ninety 662 00:38:05,200 --> 00:38:09,960 Speaker 1: something lasers, they were able to create UH to create 663 00:38:10,000 --> 00:38:13,840 Speaker 1: a situation such that more energy was produced than was 664 00:38:13,920 --> 00:38:18,799 Speaker 1: put in. Oh, which is real sci fi stuff. But 665 00:38:18,880 --> 00:38:23,719 Speaker 1: this doesn't necessarily mean like we've cracked it. Nuclear is 666 00:38:23,760 --> 00:38:27,760 Speaker 1: no longer important. You know, we're where we're off the coal, 667 00:38:28,040 --> 00:38:32,239 Speaker 1: were off the oil starting tomorrow. Yeah, you're correct, that's 668 00:38:32,239 --> 00:38:35,600 Speaker 1: not that's not going to happen. Um the now. This 669 00:38:35,719 --> 00:38:40,359 Speaker 1: is not to diminish the amazing science. Yeah exactly, but 670 00:38:40,360 --> 00:38:43,839 Speaker 1: but it's um, it's it's like, you know, the right 671 00:38:43,920 --> 00:38:47,640 Speaker 1: brothers got got their plane off the ground for a 672 00:38:47,680 --> 00:38:51,040 Speaker 1: few seconds of Kittie Hawk, and everybody's very excited, and 673 00:38:51,080 --> 00:38:55,360 Speaker 1: their question was when can we fly across the world? 674 00:38:56,160 --> 00:38:59,239 Speaker 1: And that took a while. Um, I'm the public to 675 00:38:59,280 --> 00:39:03,480 Speaker 1: put the car before the horse, right right. UM. So 676 00:39:03,560 --> 00:39:08,080 Speaker 1: I'm wondering if it is possible and that this is 677 00:39:08,160 --> 00:39:13,320 Speaker 1: not the first iteration of something like this. But the 678 00:39:13,920 --> 00:39:19,360 Speaker 1: thing that keeps me from going to conspiratorial here is, um, 679 00:39:19,440 --> 00:39:20,719 Speaker 1: if you look at it, if you look at the 680 00:39:20,800 --> 00:39:24,919 Speaker 1: nuts and bolts have been published, it's a lot. It's 681 00:39:24,960 --> 00:39:27,840 Speaker 1: still really expensive to get out to work. This is 682 00:39:27,880 --> 00:39:32,000 Speaker 1: not a light switch. We're not We're just not there yet. Uh. 683 00:39:32,040 --> 00:39:39,720 Speaker 1: And also, can can fusion ever contribute, I mean, fusion 684 00:39:39,760 --> 00:39:43,280 Speaker 1: could contribute to the grid, but could ever really remove 685 00:39:43,440 --> 00:39:47,040 Speaker 1: the path dependence that humans have created. I mean, solar 686 00:39:47,080 --> 00:39:52,520 Speaker 1: technology improves by leaps and bounds, geothermal, wind, hydropower, Uh, 687 00:39:52,640 --> 00:39:55,799 Speaker 1: those are all you know, in many ways they are 688 00:39:56,000 --> 00:40:01,959 Speaker 1: location dependent, but they were did a lot of heads 689 00:40:01,960 --> 00:40:05,120 Speaker 1: start scientifically in terms of the R and D put 690 00:40:05,160 --> 00:40:09,000 Speaker 1: into these right? Yeah, that's a good point, So so 691 00:40:09,239 --> 00:40:14,080 Speaker 1: the other big conspiracy. But first, wait, I didn't get 692 00:40:14,080 --> 00:40:16,759 Speaker 1: a straight with you guys. Is it possible that there 693 00:40:16,800 --> 00:40:22,640 Speaker 1: was technological suppression? No? Man, I don't think before this announced, 694 00:40:23,360 --> 00:40:27,719 Speaker 1: yeah it was it possible. Again, it being such a 695 00:40:27,760 --> 00:40:32,600 Speaker 1: non deal breaker announcement, I think probably not. I think 696 00:40:32,600 --> 00:40:34,720 Speaker 1: they're you know, they're like, hell, yeah, let's let's publish, 697 00:40:34,800 --> 00:40:36,479 Speaker 1: you know, because we did a thing. But it's also 698 00:40:36,560 --> 00:40:40,040 Speaker 1: not like a game changer yet. So if the game 699 00:40:40,120 --> 00:40:43,960 Speaker 1: changer part existed, then sure, But I don't I think 700 00:40:44,000 --> 00:40:46,719 Speaker 1: we'd have some loose lipped scientists that would be you know, 701 00:40:47,160 --> 00:40:49,680 Speaker 1: speaking out or protesting or who knows, I don't know, 702 00:40:49,880 --> 00:40:52,839 Speaker 1: being assassinated. I just I think we gotta I think 703 00:40:52,880 --> 00:40:56,759 Speaker 1: we gotta approach this with super cautious optimism because the 704 00:40:56,760 --> 00:40:59,120 Speaker 1: Guardian pointed out an article they wrote about this that 705 00:40:59,160 --> 00:41:04,759 Speaker 1: you posted. Been about since the nineteen fifties, we've been hearing, oh, 706 00:41:04,920 --> 00:41:08,719 Speaker 1: there's a fusion breakthrough right jam tomorrow, and it just 707 00:41:08,800 --> 00:41:12,240 Speaker 1: kind of yeah, exactly. It reminds me of the prophecies 708 00:41:12,400 --> 00:41:15,279 Speaker 1: thing that colts always have that we talk about, where 709 00:41:16,000 --> 00:41:21,280 Speaker 1: you got to move that goalpost every time, because yeah, 710 00:41:21,360 --> 00:41:23,400 Speaker 1: it's a good point at least, you know, unlike a 711 00:41:23,680 --> 00:41:28,560 Speaker 1: doomsday prophecy um. This is science rights, a real science. 712 00:41:28,800 --> 00:41:31,080 Speaker 1: It makes me think about that company we talked about, 713 00:41:31,160 --> 00:41:33,759 Speaker 1: or we at least briefly mentioned a little while ago, 714 00:41:33,840 --> 00:41:36,000 Speaker 1: the one that's trying to make a fusion piston or 715 00:41:36,040 --> 00:41:39,520 Speaker 1: a gun of some sort that would like reaction on 716 00:41:39,520 --> 00:41:42,520 Speaker 1: one side, use that energy to start the reaction on 717 00:41:42,560 --> 00:41:44,600 Speaker 1: the other side, and then back and forth. But that 718 00:41:44,840 --> 00:41:49,120 Speaker 1: sounds like perpetual motion machine materials. Yeah. I UM. When 719 00:41:49,160 --> 00:41:54,200 Speaker 1: you talked about the millennial prophecies or doomsday uh, predictions 720 00:41:54,360 --> 00:41:57,680 Speaker 1: of cults and religious sex, it made me immediately think, 721 00:41:57,880 --> 00:42:00,959 Speaker 1: are these atomic profits which is a bad name, little 722 00:42:01,000 --> 00:42:07,160 Speaker 1: niff in the atomic profits and it is now we need, 723 00:42:07,960 --> 00:42:12,200 Speaker 1: we need, let's have let's have someone sendative they would 724 00:42:12,200 --> 00:42:14,839 Speaker 1: love to love to hear that project. Um, you guys 725 00:42:14,840 --> 00:42:18,680 Speaker 1: are raising great points. Also, here's one thing that stood out. 726 00:42:20,080 --> 00:42:23,799 Speaker 1: One of the people interviewed or one of the sorry, 727 00:42:23,800 --> 00:42:27,000 Speaker 1: one of the people making announcements regarding this did note 728 00:42:27,040 --> 00:42:30,240 Speaker 1: that NIFF is working with lasers that are quote, nineteen 729 00:42:30,280 --> 00:42:36,400 Speaker 1: eighties technology and acknowledged that the private sector is likely 730 00:42:36,480 --> 00:42:39,839 Speaker 1: ahead of them in some regard. And whenever we think 731 00:42:39,840 --> 00:42:42,040 Speaker 1: of tech suppression, you know, we always think of like 732 00:42:42,800 --> 00:42:46,720 Speaker 1: the men in black, right, the top men of Indiana Jones, 733 00:42:46,800 --> 00:42:49,439 Speaker 1: you know, having cell phones back in the seventies, which 734 00:42:50,120 --> 00:42:53,880 Speaker 1: story for a different day. But um, my last conspiracy. 735 00:42:53,880 --> 00:42:56,279 Speaker 1: I wanted to ask you guys before we before we 736 00:42:56,320 --> 00:43:00,040 Speaker 1: wrap and move on big Oil, you think they do? 737 00:43:00,080 --> 00:43:03,240 Speaker 1: You think they're sweating this at all. They're not stoked. 738 00:43:03,840 --> 00:43:09,920 Speaker 1: They're not stoked like a coal fire there. It is. No, 739 00:43:10,400 --> 00:43:15,319 Speaker 1: It's just I I don't know, because those corporations are 740 00:43:15,440 --> 00:43:19,120 Speaker 1: able to function like state level actors in some regards. 741 00:43:19,200 --> 00:43:24,320 Speaker 1: So I wonder if I'm sure there eyes on this research, 742 00:43:24,360 --> 00:43:28,680 Speaker 1: of course, but I wonder if they're um big enough 743 00:43:28,760 --> 00:43:33,920 Speaker 1: or inclined enough to take ownership of it right like 744 00:43:33,960 --> 00:43:37,319 Speaker 1: sort of how R. J. Reynolds and tobacco companies kind 745 00:43:37,320 --> 00:43:44,160 Speaker 1: of seamlessly shifted into uh smoking cessation tools. They called them, right, 746 00:43:44,200 --> 00:43:48,200 Speaker 1: So is is big oil um going to be able 747 00:43:48,280 --> 00:43:53,359 Speaker 1: to conspire or would they? Would they? Would they even care? 748 00:43:53,520 --> 00:43:55,640 Speaker 1: I mean, if you're very worried about climate change, the 749 00:43:55,680 --> 00:43:58,160 Speaker 1: bad news about this fusion stuff is it's not going 750 00:43:58,200 --> 00:44:02,279 Speaker 1: to get across the finish line in time for all 751 00:44:02,320 --> 00:44:07,800 Speaker 1: those terrible um predictions. What is it in the podcast? 752 00:44:07,840 --> 00:44:09,960 Speaker 1: Should we be an oil company? Let's do a little 753 00:44:10,080 --> 00:44:14,719 Speaker 1: late to the market. That's a point. Yeah, well we'll 754 00:44:14,760 --> 00:44:16,760 Speaker 1: have to stick with a little niff in the topic profit. 755 00:44:18,040 --> 00:44:20,439 Speaker 1: So I don't want to say too much yet because 756 00:44:20,440 --> 00:44:24,160 Speaker 1: I really do feel this would be an excellent future episode. 757 00:44:24,600 --> 00:44:28,480 Speaker 1: And you know what, maya culpa on our end if 758 00:44:28,640 --> 00:44:31,719 Speaker 1: by the time this comes out, diffusion is a thing 759 00:44:31,760 --> 00:44:34,600 Speaker 1: and it's just accelerated very quickly and you're listening to 760 00:44:34,640 --> 00:44:38,799 Speaker 1: this on your fusion powered iPhone in some regard, then 761 00:44:39,120 --> 00:44:40,759 Speaker 1: in that case you were right. But I feel like 762 00:44:40,760 --> 00:44:43,040 Speaker 1: it's a safe bet to say fusion has a ways 763 00:44:43,080 --> 00:44:44,960 Speaker 1: to go. Remember that bit from I think it was 764 00:44:45,080 --> 00:44:47,759 Speaker 1: Back to the Future too, or maybe no, it's the 765 00:44:47,800 --> 00:44:49,719 Speaker 1: end of Back to the Future. One I think. I 766 00:44:49,760 --> 00:44:51,919 Speaker 1: think when it like kind of dovetails into two where 767 00:44:51,920 --> 00:44:54,200 Speaker 1: he comes back from the future, which is for the 768 00:44:54,200 --> 00:44:56,879 Speaker 1: line back to the Future comes from and he's got 769 00:44:56,880 --> 00:45:00,319 Speaker 1: a mr fusion in in the in the DeLorean that 770 00:45:00,360 --> 00:45:03,800 Speaker 1: he's feeding whatever garbage too, and that's you know, the 771 00:45:04,040 --> 00:45:08,520 Speaker 1: next level version of the the flex capacitor, just biomass. 772 00:45:08,560 --> 00:45:11,160 Speaker 1: That also reminds me of years and years ago when uh, 773 00:45:12,000 --> 00:45:15,480 Speaker 1: some research came out from Japan where they had plasma 774 00:45:15,680 --> 00:45:20,439 Speaker 1: uh like this plasma garbage thing basically that you could 775 00:45:20,440 --> 00:45:23,560 Speaker 1: throw anything into it would vaporize it and it would 776 00:45:23,600 --> 00:45:26,360 Speaker 1: create energy, and then we never heard about it again. 777 00:45:26,719 --> 00:45:31,839 Speaker 1: Can we talk about that with Marshall Brain? Yes? We did, yeah, 778 00:45:32,000 --> 00:45:35,279 Speaker 1: in a in a in a recent classic or if 779 00:45:35,280 --> 00:45:37,960 Speaker 1: it's not recent, it's coming very soon. No, Bennet, I 780 00:45:37,960 --> 00:45:44,960 Speaker 1: talked about that with Marshall and yeah, dude, doctor Brain. 781 00:45:45,200 --> 00:45:47,319 Speaker 1: You can't call him doctor because he refuses to get 782 00:45:47,320 --> 00:45:50,520 Speaker 1: a degree. We talked about that, but most if you're listening, 783 00:45:50,960 --> 00:45:55,520 Speaker 1: were being should you should bring Marshall and Chris Cogswell 784 00:45:55,600 --> 00:45:59,960 Speaker 1: back and we should uh talk about nuclear fusion. Yeah, 785 00:46:00,200 --> 00:46:03,600 Speaker 1: we should also do it over pizza or something. I'm 786 00:46:03,600 --> 00:46:07,839 Speaker 1: saying needing today. Uh, folks, we hope this finds you well. 787 00:46:07,880 --> 00:46:12,040 Speaker 1: We can't wait to hear your thoughts. Lends the larger 788 00:46:12,120 --> 00:46:17,400 Speaker 1: move of a I and uh, what's what's happening behind 789 00:46:17,440 --> 00:46:21,919 Speaker 1: these evidence fires? Will there be a real cause determined? Uh? 790 00:46:21,960 --> 00:46:26,759 Speaker 1: And of course nuclear fusion? What do you think how 791 00:46:26,800 --> 00:46:30,239 Speaker 1: long have they known? If you want to be conspiratorial? Uh, well, 792 00:46:30,360 --> 00:46:33,360 Speaker 1: don't keep us waiting to know, reach out, give us 793 00:46:33,360 --> 00:46:35,640 Speaker 1: your thoughts. We can't wait to hear from you. Happy 794 00:46:35,680 --> 00:46:37,960 Speaker 1: New Year. We try to be easy to find online. 795 00:46:38,040 --> 00:46:40,120 Speaker 1: That's right. You can find us on the Internet where 796 00:46:40,120 --> 00:46:45,279 Speaker 1: we are conspiracy stuff on Facebook, Twitter and YouTube, conspiracy 797 00:46:45,280 --> 00:46:48,480 Speaker 1: stuff on Instagram where things are popping off lately. We 798 00:46:48,840 --> 00:46:52,880 Speaker 1: I hope you guys enjoyed our our holiday themed our video. 799 00:46:53,120 --> 00:46:55,960 Speaker 1: Put a lot of hard work into I was personally 800 00:46:56,040 --> 00:46:58,600 Speaker 1: tickled by it. Um thanks to our friends at Station 801 00:46:58,760 --> 00:47:01,280 Speaker 1: sixteen for helping us out with all of these awesome 802 00:47:01,320 --> 00:47:04,920 Speaker 1: new pieces of content that we're putting out content what 803 00:47:05,000 --> 00:47:07,120 Speaker 1: if I become? But seriously that we're really and we 804 00:47:07,200 --> 00:47:08,920 Speaker 1: enjoy doing these. There are a lot of fine Hopefully 805 00:47:08,960 --> 00:47:10,239 Speaker 1: we can keep that going into the new year, and 806 00:47:10,280 --> 00:47:12,080 Speaker 1: then we hope that y'all are also enjoying them as well. 807 00:47:12,600 --> 00:47:15,600 Speaker 1: Oh and don't forget our new TikTok channel. Yeah, that's right. 808 00:47:16,040 --> 00:47:25,040 Speaker 1: We're helping China to help us, help you feed, help us, 809 00:47:25,080 --> 00:47:28,520 Speaker 1: help you help China, help us go viral on TikTok 810 00:47:28,560 --> 00:47:32,560 Speaker 1: because that's what it's all about. And we're we're telling 811 00:47:32,600 --> 00:47:36,359 Speaker 1: your completely true things as well, folks. Um And if 812 00:47:36,400 --> 00:47:39,359 Speaker 1: you do not care to sip the social needs, if 813 00:47:39,360 --> 00:47:43,000 Speaker 1: you're finding yourself having a dry January of one sort 814 00:47:43,160 --> 00:47:46,040 Speaker 1: or another and you prefer, you know, to reach out 815 00:47:46,080 --> 00:47:49,239 Speaker 1: and touch space with your voice on a phone, we 816 00:47:49,320 --> 00:47:51,799 Speaker 1: get you covered there to the number one A three 817 00:47:51,960 --> 00:47:55,640 Speaker 1: three st d w y t K slightly different cadence. 818 00:47:55,680 --> 00:47:58,239 Speaker 1: They're switching things up. You'll hear a voice to hear 819 00:47:58,280 --> 00:48:00,160 Speaker 1: a beep like so beep, you got three minut it's 820 00:48:00,200 --> 00:48:03,880 Speaker 1: those are yours? Go ham go nuts? Uh? And let 821 00:48:03,920 --> 00:48:05,400 Speaker 1: us know if we can use your name and our 822 00:48:05,440 --> 00:48:09,600 Speaker 1: message on air. Most importantly, don't censor yourself. That's not 823 00:48:09,640 --> 00:48:12,520 Speaker 1: what this show is about. We literally just bleep curse 824 00:48:12,560 --> 00:48:15,359 Speaker 1: words because we think it's funnier that way. If you 825 00:48:15,440 --> 00:48:17,520 Speaker 1: have a story you need to tell, You've got some 826 00:48:17,600 --> 00:48:19,960 Speaker 1: links you've got some pictures, take us to the edge 827 00:48:19,960 --> 00:48:22,080 Speaker 1: of the rabbit hole, send us an email. All you 828 00:48:22,120 --> 00:48:23,680 Speaker 1: have to do is drop us a line where we 829 00:48:23,719 --> 00:48:46,160 Speaker 1: are conspiracy at iHeart radio dot com. Stuff they don't 830 00:48:46,160 --> 00:48:48,720 Speaker 1: want you to know is a production of I heart Radio. 831 00:48:49,040 --> 00:48:51,560 Speaker 1: For more podcasts from my heart Radio, visit the iHeart 832 00:48:51,640 --> 00:48:54,400 Speaker 1: Radio app, Apple Podcasts, or wherever you listen to your 833 00:48:54,440 --> 00:48:55,120 Speaker 1: favorite shows.